Wokingham Area Profile 2019 to 2023

1 Executive Summary

This Area Profile provides a comprehensive analysis and systematic review of road safety outcomes for Wokingham residents and the wider road network, using STATS19 data and Acorn data for classifying groups based on socio - demographic information. These findings can enable the authority to understand local risk patterns and identify priority groups for intervention.

Wokingham’s resident casualty rate is 131 casualties per year per 100,000 for the reporting period 2019 – 2023. This is 36% below the national rate and 39% below the South East rate. Among similar comparator authorities, Wokingham ranks third lowest, behind South Oxfordshire and West Berkshire. Between 2019 and 2023, 48% of all resident casualties, including Wokingham residents, occurred within Wokingham. Of the remaining 52%, the majority of Wokingham’s resident casualties were injured in Reading (11%).

The most represented Acorn category across a variety of socio - demographic groups is ‘Affluent, older homeowners’ (D8). In addition, most Wokingham residents belong to the less deprived deciles.

Wokingham’s resident driver involvement rate is 134 drivers per year per 100,000 population. Between 2019 and 2023, Wokingham’s resident driver collision involvement rate was 44% below the national involvement rate and 41% below the South East regional resident driver involvement rate. Moreover, among similar comparator authorities, Wokingham has the second lowest resident driver involvement rate, behind South Oxfordshire, and the lowest among all other Berkshire authorities.

In 2023, there were 235 resident driver involved collisions in Wokingham, continuing the overall downward trend from 398 collisions in 2014. Although there was an increase from a low recorded in 2020 (205) that can be attributed to the Covid - 19 pandemic, the long - term trend since 2014 has seen a decline. Fatal collisions involving resident drivers have dropped sharply from 8 in 2022 to 1 in 2023. Of the 1,058 collisions involving Wokingham’s resident drivers, 47% occurred within the authority itself, a notable increase from 42% in the previous reporting period (2018 – 2022). The most common crash location for resident drivers outside the authority was Reading, accounting for 11% of collisions.

Wokingham’s collision rate is 18% lower than the national rate, 37% below the South East regional collision rate, and 25% below the overall Berkshire county rate. Serious injury collisions have shown a slight upward trend in recent years, increasing from 22 in 2019 to 33 in 2023. In contrast, slight injury collisions have decreased gradually over the decade by 38%. When looking at road types, most collisions on the network occur on A roads (39%), closely followed by unclassified roads (35%).

Furthermore, about three – quarters (76%) of collisions occur on single carriageways, followed by dual carriageways (12%) and roundabouts (9%). Cars are involved in the majority of collisions in Wokingham (68%) followed by cycles (12%), goods vehicles (10%), and motorbikes (9%). It is noteworthy, that motorcycle user casualties have remained steady at 33 and have not shown a decreasing trend since 2021, unlike other demographic groups.

When examining contributory factors, collisions attributed to impairment - related factors in Wokingham have halved compared to the 14 recorded in 2022. It is important to note that multiple contributory factors can be attributed to a single collision thus, findings should be interpreted with caution. While collisions attributed to speed choice contributory factors have not seen as dramatic a reduction, the number has decreased from 14 in 2022 to 11 in 2023. Additionally, collisions attributed to control errors have seen a steady decline from 48 recorded in 2014 to 13 in 2023, representing a 78% reduction over the decade.

Thus, for the most part, Wokingham fares well in terms of safety when compared to national rates and its regional counterparts.

2 Introduction

2.1 Overview

2.1.1 Background

Area Profiles from Agilysis provide overviews of road safety performance within specific local areas. This profile delivers detailed analysis and insight on all injury collisions reported to the police in Wokingham, as well as casualties and drivers involved in collisions anywhere in Britain who reside in Wokingham.

Area Profile formats are modular, which affords the flexibility to select topics for inclusion to reflect local needs and allows each section of the report to be used independently if required. Profile design allows authorities to understand general casualty and collision trends affecting their residents and roads, as well as selecting particular topics based on local issues. Experts from Agilysis work with commissioning authorities to ensure that selected topics provide an accurate and relevant assessment. After production of a first Area Profile, updates can be produced in future years covering the entire document or selected existing sections, whilst new topics can also be introduced in response to latest trends and concerns.

2.1.2 Aims and Objectives

The aim of this document is to provide a comprehensive profile of road safety issues affecting Wokingham’s road network and Wokingham’s residents, primarily using STATS19 collision data¹ and Acorn socio-demographic classification. Annual trends are presented and analysed for key road user groups, predominantly based on data from the last five full years of available statistics but referring to older figures where appropriate.

The Agilysis analysis tool MAST Online has also been used to investigate trends for Wokingham’s residents involved in road collisions anywhere in the country, including socio - demographic profiling of casualties and drivers. MAST has been used to allow comparison of Wokingham’s key road safety issues with those of comparator regions and national figures. The aim is to allow Wokingham to assess its progress alongside other areas, and work together with neighbours to address common issues.

2.1.3 Analytical Techniques

The analytical techniques employed throughout this Area Profile are detailed in Section 5.1 on Analytical Techniques. Please refer to this section for information on the terminology and data sources used as well to understand methodologies utilised and the structure and scope of the report.

2.2 Profile Configuration

2.2.1 Structure

The Area Profile has been divided into separate analysis of key road user groups. The aim is to allow each section to be used independently if required. This will also allow Wokingham to update selected sections when appropriate, without a requirement to update the entire document.

Section 3 explores Resident Risk. Resident risk analysis includes examining all of Wokingham’s resident casualties and resident motor vehicle users in terms of rates, comparisons with other relevant police forces and authorities; residency by small area; trends and socio-demographic analysis. Specific road user groups will also be analysed against these measures. The focus of this section is on how the people of Wokingham are involved in collisions, rather than what happens on local roads.

Section 4 provides analysis of Road Network Risk. It also examines rates; comparisons; location by small area; and trends on Wokingham’s roads. Breakdowns by rurality classification of road are also included in this section.

Section 5 includes Appendices detailing all Acorn Types and the profile and distribution of specific Acorn Types relevant to Wokingham. It also contains data tables for all analysis referred to in this Area Profile.

2.2.2 Scope

All figures included in this report are based on STATS19 collision data. The residents section covers casualties and motor vehicle users involved in collisions who are residents of Wokingham, regardless of where in Britain the collision occurred. Resident analysis in this profile is based on the national STATS19 dataset as provided to Agilysis by the Department for Transport for publication in MAST Online over the five - year period between 2019 and 2023 inclusive. For a more complete explanation, please refer to 5.1.1 on methodology for calculating resident risk.

In contrast, the road network section covers collisions which occurred on Wokingham’s roads, regardless of where those involved reside. Network analysis is also based on the national STATS19 dataset over the five-year period between 2019 and 2023 inclusive. For a more complete explanation, please refer to 5.1.1 on methodology for calculating network collision risk.

3 Wokingham Resident Risk

For information about the provenance and scope of data included in this section, please refer to section 2.2.2. For an explanation of the methodologies employed throughout this section, please refer to 5.1.1.

3.1 Wokingham Resident Casualties

This section examines all casualties who were residents of Wokingham at the time of injury. For information about Wokingham’s resident motor vehicle users involved in collisions on all roads, please refer to section 3.2.

3.1.1 All Resident Casualties

3.1.1.1 Rates

Figure 3.1 shows the resident casualty rates for Wokingham compared to the national and regional rates, as well as the most similar comparators.

Wokingham’s resident casualty rate is 131 casualties per year, per 100,000 population.

Figure 3.1: Annual average Wokingham resident casualties per 100,000 population (2019 - 2023)

3.1.1.2 Comparisons

Wokingham’s 2019 to 2023 resident casualty rate is 36% below the national resident casualty rate and 39% below the South East regional resident casualty rate. Against other similar comparator authorities, Wokingham has the third lowest resident casualty rate, behind South Oxfordshire (115 per 100,000 population) and West Berkshire (129 per 100,000 population).

3.1.1.2.1 Residency by Small Area

Figure 3.2 shows the home location of Wokingham’s resident casualties by lower layer super output area (LSOA). The thematic map is coloured by resident casualties per year per population of LSOA.

The highest resident casualty rates are in Earley, the northwest of Shinfield, central areas of Finchampstead, and the east of Wokingham Town. High resident casualty rates are also found in the northwest of Winnersh, most of Shinfield, the south of Arborfield & Garrison, the whole of Crowthorne North (except for the southeast of this area), the northeast of Wokingham Town, and the east of Wokingham East.

Figure 3.2: Wokingham resident casualties home location by LSOA, casualties per year per 100,000 population (2019-2023)

3.1.1.3 Trends

Figure 3.3 shows Wokingham’s annual resident casualty numbers since 2014, by severity. This includes residents injured anywhere in the country. Also shown is a 3-year moving average trend line.

In Wokingham, there were 241 total resident casualties in 2023. Following a clear downward trend in resident casualty numbers since 2014 to 2020, the number of Wokingham residents injured in collisions increased in 2021 and has remained at a similar level since. Serious resident injuries specifically followed this same pattern, except for 2016 that saw an increase compared to the previous year. Similarly, slight resident injuries also followed this general pattern. In contrast, there was no consistent pattern in reductions of fatalities, although caution should be applied when interpreting the fatality figure as there were fewer of those in the period of 2014 to 2023 (ranging from 1 in 2019 to 5 in 2017 and 2018), compared to serious resident casualties (25 in 2020, to 51 in 2015) and slight resident casualties (167 in 2020, to 319 in 2015).

Figure 3.3: Wokingham resident casualties, by year and severity (2014-2023)

3.1.1.3.1 Resident Casualties occurring in other areas

Between 2019 and 2023, there were 1,161 Wokingham resident casualties that occurred across 60 areas. There were 562 resident casualties that occurred within Wokingham (48% of all resident casualties). Of the remaining 52%, the majority were injured in Reading (131 casualties; 11%).

3.1.1.4 Socio Demographic Analysis

3.1.1.4.1 Age

Figure 3.4 shows the numbers of resident casualties by ten specified age groups.

Out of a total of 1,152 resident casualties, the 25 - 34 age group recorded the highest number of casualties with 222 casualties (19%), followed by the 35 - 44 category with 197 casualties (17%). The 17 - 24 age group was involved in 187 casualties (16%). Combined, these 3 groups account for 606 casualties (53%), highlighting a significant concentration of casualties among these age groups.

The highest number of serious injuries occured in the 17 - 24 and 25 - 34 age groups, each with 29 serious injuries (26%). The 45 - 54 group follows closely with 28 serious injuries. Fatalities are recorded in single digits with the highest among the 35 - 44 age group with 4 fatalities (25%), followed by the 45 - 54, 55 - 64 and 75 - 84 groups each with 2 fatalities. Slight injuries form the bulk of road casualties in Wokingham, with 971 casualties (84% of total casualties). The 25 - 34 age group recorded the highest number of slight injuries at 193 (19%), followed by 35 - 44 with 172 (18%) and 17 - 24 with 156 casualties (16%).

It is more informative to consider Figure 3.5 which shows resident casualty numbers by age group indexed by the population of those age groups in Wokingham. There is also a national index value for comparison.

Wokingham’s resident casualties closely mirror national trends with some pronounced extremes. Young adults aged 17 - 24 are the most overrepresented compared to the national index followed by the 25 - 34 age group. On the other hand, most older age groups (55+) are underrepresented nationally and in Wokingham with the proportion of the 85+ age group more underrepresented in Wokingham compared to the national index. This same trend is also reflected for the younger segments of the population (under 5 to 16) with these being more underrepresented in Wokingham compared to national figures.

Figure 3.4: Wokingham resident casualties, by age group (2019-2023)

Figure 3.5: Wokingham resident casualties, by age group and indexed by population (2019-2023)

3.1.1.4.2 Segmentation

Analysis of the Acorn communities in which Wokingham’s resident casualties live provides an insight into those injured in collisions. For an explanation of Acorn and how to understand the following chart, please refer to section 5.1.1.1.

When considering the 10 Acorn groups with the highest resident casualty numbers from 2019 to 2023 in Wokingham, there are 4 groups that are overrepresented and the remaining 6 groups are underrepresented, compared to the relative population within each Acorn group. Whilst those that are ‘affluent, older homeowners’ (D8; 27% of the population) are associated with the highest number of resident casualties in Wokingham, they are underrepresented compared to the relative population with an index value of 86. The same under - representation trend is seen in the ‘mixed life stages in semi - detached homes’ category (G20; 12% of the population), with an associated index value of 88. Similarly, ‘families in leafy surburbs’ (E13; 11% of the population) is underrepresented with an index value of 68.

In contrast, ‘restricted residents that are socially renting’ (M37; 3% of the population) constitute the most overrepresented category with an associated index value of 193, followed by the ‘professional families and couples in suburban, owner - occupied areas’ (J27; 3% of the population) with an index value of 141. The next most overrepresented Acorn group is the ‘families and couples in terraces’ category (J28; 5% of the population) with an index value of 122, which is closely followed by those that are ‘privately renting squeezed professionals in flats’ (P45; 4% of the population) with an index value of 118.

Figure 3.6: Wokingham resident casualties, by Acorn Type (2019-2023)

3.1.1.4.3 Deprivation

Figure 3.7 shows resident casualties by the IMD of the LSOA (Lower Super Output Area) in which they reside.

The largest number of resident casualties were from communities in the less deprived IMD deciles. This is particularly true of the least deprived 10% decile. This is followed by the less deprived 20% decile that accounts for fewer resident casualties compared to the least deprived 10% decile, but is overrepresented compared to the relative population with an index value of 126.

While the less deprived 30%, less deprived 40% and more deprived 40% deciles are not represented in a large number of resident casualties in Wokingham, they are overrepresented compared to the relative population with index values of 141, 273 and 223. The less deprived 40% decile is the most overrepresented when compared to national figures.

Figure 3.7: Wokingham resident casualties, by Index of Multiple Deprivation (2019-2023)

3.1.2 Resident Young Adult Casualties

This section examines young adult casualties who are residents of Wokingham. For an explanation of the methodologies employed throughout this section, please refer to 5.1.1.

3.1.2.1 Rates

Figure 3.8 shows the resident young adult casualty rates for Wokingham compared to the national and regional rates, as well as the most similar comparators.

Wokingham’s resident young adult casualty rate is 270 casualties per year, per 100,000 population.

Figure 3.8: Annual average Wokingham resident young adult casualties per 100,000 population (2019-2023)

3.1.2.2 Comparisons

Wokingham’s 2019 to 2023 resident young adult casualty rate is 31% below the national resident young adult casualty rate and 40% below the South East regional resident young adult casualty rate. Against other similar comparator authorities, Wokingham has the second lowest resident young adult casualty rate, behind Reading (249 per 100,000 population).

3.1.2.2.1 Residency by Small Area

Figure 3.9 shows the home location of Wokingham’s resident young adult casualties by lower layer super output area (LSOA). The thematic map is coloured by resident young adult casualties per year per young adult population of LSOA.

The highest resident young adult casualty rates are in the south of Arborfield & Garrison. High resident young adult casualty rates are also found in the west of Spencers Wood & Swallowfield and centre of Woodley South.

Figure 3.9: Wokingham resident young adult casualties home location by LSOA, casualties per year per 100,000 population (2019-2023)

3.1.2.3 Trends

Figure 3.10 shows Wokingham’s annual resident young adult casualty numbers since 2014, by severity. This includes residents injured anywhere in the country. Also shown is a 3-year moving average trend line.

In Wokingham, there were 33 total resident young adult casualties in 2023. Whilst there has been no consistent trend of increase or decrease in total resident young adult casualties between 2014 and 2023, there is a general decrease from a peak of 87 total casualties in 2014 to 33 total casualties in 2023. Fatalities (1) and serious injuries (5) among resident young adults were recorded in single digits whereas there were 27 slight resident young adult casualties in this group in 2023. Slight injuries have not had a consistent trend of an increase or decrease, although they have generally decreased from a peak of 77 in 2014 to 27 in 2023.

Figure 3.10: Wokingham resident young adult casualties, by year and severity (2014-2023)

3.1.2.3.1 Resident Young Adult Casualties occurring in other areas

Between 2019 and 2023, there were 187 Wokingham resident young adult casualties that occurred across 27 areas. There were 86 resident young adult casualties that occurred within Wokingham (46% of all resident young adult casualties). Of the remaining 54%, the majority were injured in Reading (25 casualties; 13%), closely followed by Bracknell Forest (18 casualties; 10%).

3.1.2.4 Socio Demographic Analysis

3.1.2.4.1 Segmentation

Analysis of the Acorn communities in which Wokingham’s resident young adult casualties live provides an insight into those injured in collisions. For an explanation of Acorn and how to understand the following chart, please refer to section 5.1.1.1.

Whilst those that are affluent, older homeowners (D8; 27% of the population) are associated with the most number of resident young adult casualties across all Acorn groups in Wokingham, they are underrepresented compared with the relative population with an index value of 81. The mixed life stages in semi - detached homes (G20;12% of the population) is associated with the second highest number of resident young adult casualties.

Figure 3.11: Wokingham resident young adult casualties, by Acorn Type (2019-2023)

3.1.2.4.2 Deprivation

Figure 3.12 shows resident young adult casualties by the IMD of the LSOA (Lower Super Output Area) in which they reside.

The largest number of resident young adult casualties were from communities in the less deprived IMD deciles. This is particularly true of the less deprived 20% and least deprived 10%, with respective index values of 172 and 109.

Figure 3.12: Wokingham resident young adult casualties, by Index of Multiple Deprivation (2019-2023)

3.1.3 Resident Adult Casualties

This section examines adult casualties who are residents of Wokingham. For an explanation of the methodologies employed throughout this section, please refer to 5.1.1.

3.1.3.1 Rates

Figure 3.13 shows the resident adult casualty rates for Wokingham compared to the national and regional rates, as well as the most similar comparators.

Wokingham’s resident adult casualty rate is 161 casualties per year, per 100,000 population.

Figure 3.13: Annual average Wokingham resident adult casualties per 100,000 population (2019-2023)

3.1.3.2 Comparisons

Wokingham’s 2019 to 2023 resident adult casualty rate is 35% below the national resident adult casualty rate and 38% below the South East regional resident adult casualty rate. Against other similar comparator authorities, Wokingham has the third lowest resident adult casualty rate, behind South Oxfordshire (143 per 100,000 population) and West Berkshire (154 per 100,000 population).

3.1.3.2.1 Residency by Small Area

Figure 3.14 shows the home location of Wokingham’s resident adult casualties by lower layer super output area (LSOA). The thematic map is coloured by resident adult casualties per year per adult population of LSOA.

The highest resident adult casualty rates are in the northwest of Earley, the northwest of Shinfield, the centre of Arborfield & Garrison, the whole of Crowthorne North (except for the southeast of this area), the west of Wokingham Town, the north of Arborfield & Garrison, the northeast of Wokingham Town, and the south of Twyford East & Wargrave.

Figure 3.14: Wokingham resident adult casualties home location by LSOA, casualties per year per 100,000 population (2019-2023)

3.1.3.3 Trends

Figure 3.15 shows Wokingham’s annual resident adult casualty numbers since 2014, by severity. This includes residents injured anywhere in the country. Also shown is a 3-year moving average trend line.

In Wokingham, there were 147 total resident adult casualties in 2023. Whilst there has been no consistent trend of increase or decrease in total resident adult casualties between 2014 and 2023, there is a general decrease from a peak of 204 total casualties in 2014 to 147 total casualties in 2023. Resident adult serious casualties in Wokingham have slightly increased to 22 compared with 16 recorded in 2022. On the other hand, slight injury casualties have also not had a consistent trend of increase or decrease during this period, although they have generally decreased from a peak of 185 in 2014 to 124 in 2023. There were under 100 slight resident adult casualties in 2019 and 2020, but all other years in the period 2014 to 2023 saw above 100 slight casualties.

Figure 3.15: Wokingham resident adult casualties, by year and severity (2014-2023)

3.1.3.3.1 Resident Adult Casualties occurring in other areas

Between 2019 and 2023, there were 679 Wokingham resident adult casualties that occurred across 52 areas. There were 307 resident adult casualties that occurred within Wokingham (45% of all resident adult casualties). Of the remaining 55%, the majority were injured in Reading (76 casualties; 11%), closely followed by Hampshire (53 casualties; 8%) and Surrey (43 casualties; 6%).

3.1.3.4 Socio Demographic Analysis

3.1.3.4.1 Segmentation

Analysis of the Acorn communities in which Wokingham’s resident adult casualties live provides an insight into those injured in collisions. For an explanation of Acorn and how to understand the following chart, please refer to section 5.1.1.1.

Whilst those that are affluent, older homeowners (D8; 27% of the population) are associated with the most number of resident adult casualties across all Acorn groups in Wokingham, they are underrepresented compared with the relative population with an index value of 78. The mixed life stages in semi - detached homes (G20; 12% of the population) were associated with the second highest resident adult casualties in Wokingham with these casualty numbers being in line with the national trend. In contrast, the families in leafy suburbs (E13; 11% of the population) while being associated with fewer resident adult casualties in Wokingham, is underrepresented compared to the relative population with an index value of 64.

Barring these acorn groups, most other Acorn groups saw a trend of over - representation. The three most overrepresented Acorn groups in this segment include restricted residents, socially renting (M37; 3% of the population), professional families and couples in suburban, owner - occupied areas (J27; 3% of the population) and families and couples in terraces (J28; 5% of the population). While the M37 group was overrepresented compared to the relative population with an index value of 182, J27 had an index value of 164, followed by 146 for the J28 category.

Figure 3.16: Wokingham resident adult casualties, by Acorn Type (2019-2023)

3.1.3.4.2 Deprivation

Figure 3.17 shows resident adult casualties by the IMD of the LSOA (Lower Super Output Area) in which they reside.

The largest number of resident adult casualties were from communities in the less deprived IMD deciles. This is particularly true of the less deprived 30%, followed by the less deprived 20%, and then the least deprived 10%. Whilst these respective IMD deciles were associated with successively more casualties, they had respective index values that reduced from 143 to 122 and 103.

Figure 3.17: Wokingham resident adult casualties, by Index of Multiple Deprivation (2019-2023)

3.1.4 Resident Older Casualties

This section examines older casualties who are residents of Wokingham. For an explanation of the methodologies employed throughout this section, please refer to section 5.1.1.

3.1.4.1 Rates

Figure 3.18 shows the resident older casualty rates for Wokingham compared to the national and regional rates, as well as the most similar comparators.

Wokingham’s resident older casualty rate is 84 casualties per year, per 100,000 population.

Figure 3.18: Annual average Wokingham resident older casualties per 100,000 population (2019-2023)

3.1.4.2 Comparisons

Wokingham’s 2019 to 2023 resident older casualty rate is 27% below the national resident casualty rate and 36% below the South East regional resident older casualty rate. Against other similar comparator authorities, Wokingham has the third lowest resident older casualty rate, behind South Oxfordshire (75 per 100,000 population) and Reading (77 per 100,000 population).

3.1.4.2.1 Residency by Small Area

Figure 3.19 shows the home location of Wokingham’s resident older casualties by lower layer super output area (LSOA). The thematic map is coloured by resident older casualties per year per older population of LSOA.

The highest resident older casualty rates are in the east of Finchampstead. High resident older casualty rates are also found in the east of Wokingham Town.

Figure 3.19: Wokingham resident older casualties home location by LSOA, casualties per year per 100,000 population (2019-2023)

3.1.4.3 Trends

Figure 3.20 shows Wokingham’s annual resident older casualty numbers since 2014, by severity. This includes residents injured anywhere in the country. Also shown is a 3-year moving average trend line.

In Wokingham, there were 37 total resident older casualties in 2023. There was a general decrease in total casualties between 2014 (49 casualties) to 2020 (24 casualties), but there have been successive increases in total resident older casualties since 2020. KSI casualties are largely in line with the previous year. For slight resident older casualties, except for 2016 when the figure increased from the previous year, there was a general decrease between 2014 and 2021. However, slight injury casualties have marginally increased from 25 in 2022 to 29 in 2023. Overall, 2023 sees a similar trend as 2022 with no major fluctuations.

Figure 3.20: Wokingham resident older casualties, by year and severity (2014-2023)

3.1.4.3.1 Resident Older Casualties occurring in other areas

Between 2019 and 2023, there were 170 Wokingham resident older casualties that occurred across 23 areas. There were 80 resident older casualties that occurred within Wokingham (47% of all resident older casualties). Of the remaining 53%, the majority were injured in Reading (17 casualties; 10%), closely followed by Surrey (16 casualties; 9%), Hampshire (14 casualties; 8%), and Bracknell Forest (12 casualties; 7%).

3.1.4.4 Socio Demographic Analysis

3.1.4.4.1 Segmentation

Analysis of the Acorn communities in which Wokingham’s resident older casualties live provides an insight into those injured in collisions. For an explanation of Acorn and how to understand the following chart, please refer to section 5.1.1.1.

Those that are affluent, older homeowners (D8; 27% of the population) are associated with the greatest number of resident older casualties across all Acorn groups, which follows the trend when considering all other earlier demographic breakdowns. Additionally, they are overrepresented compared with the relative population with an associated index value of 132.

Figure 3.21: Wokingham resident older casualties, by Acorn Type (2019-2023)

3.1.4.4.2 Deprivation

Figure 3.22 shows resident older casualties by the IMD of the LSOA (Lower Super Output Area) in which they reside.

The largest number of resident older casualties were from communities in the less deprived IMD deciles. This is particularly true of the least deprived 10%, which is associated with a notably higher number of casualties in Wokingham than any other IMD decile. It is also overrepresented compared with the relative population with an associated index value of 115.

Figure 3.22: Wokingham resident older casualties, by Index of Multiple Deprivation (2019-2023)

3.1.5 All Wokingham Resident Pedal Cyclist Casualties

This section examines pedal cyclist casualties who are residents of Wokingham. For an explanation of the methodologies employed throughout this section, please refer to 5.1.1.

3.1.5.1 Rates

Figure 3.23 shows the resident pedal cyclist casualty rates for Wokingham compared to the national and regional rates, as well as the most similar comparators.

Wokingham’s resident pedal cyclist casualty rate is 20 casualties per year, per 100,000 population.

Figure 3.23: Annual average Wokingham resident pedal cyclist casualties per 100,000 population (2019-2023)

3.1.5.2 Comparisons

Wokingham’s 2019 to 2023 resident pedal cyclist casualty rate is 21% below the national resident pedal cyclist casualty rate and 20% below the South East regional resident pedal cyclist casualty rate. Against other similar comparator authorities, Wokingham has the fourth lowest resident pedal cyclist casualty rate, behind Bracknell Forest (13 per 100,000 population), West Berkshire (17 per 100,000 population), and South Oxfordshire (19 per 100,000 population).

3.1.5.2.1 Residency by Small Area

Figure 3.24 shows the home location of Wokingham’s resident pedal cyclist casualties by lower layer super output area (LSOA). The thematic map is coloured by resident pedal cyclist casualties per year per population of LSOA.

The highest resident pedal cyclist casualty rates are in the northwest of Shinfield, the south of Southlake, the north of Wokingham West & South, and the west of Twyford West & Charvil.

Figure 3.24: Wokingham resident pedal cyclist casualties home location by LSOA, casualties per year per 100,000 population (2019-2023)

3.1.5.3 Trends

Figure 3.25 shows Wokingham’s annual resident pedal cyclist casualty numbers since 2014, by severity. This includes residents injured anywhere in the country. Also shown is a 3-year moving average trend line.

In Wokingham, there were 39 total resident pedal cyclist casualties in 2023. There has been variation between 2014 and 2023 in the total resident pedal cyclist casualties, with the figure of 39 in 2023 being slightly lower than the figure of 46 in 2014, although the 2023 figure is notably higher than the figure of 26 in 2022. These increases between 2022 and 2023 can be associated with double the serious injuries and 9 more slight injuries in resident pedal cyclists.

Figure 3.25: Wokingham resident pedal cyclist casualties, by year and severity (2014-2023)

3.1.5.3.1 Resident Pedal Cyclist Casualties occurring in other areas

Between 2019 and 2023, there were 173 Wokingham resident pedal cyclist casualties that occurred across 12 areas. There were 114 resident pedal cyclist casualties that occurred within Wokingham (66% of all resident pedal cyclist casualties). Of the remaining 34%, the majority were injured in Reading (29 casualties; 17%).

3.1.5.4 Socio Demographic Analysis

3.1.5.4.1 Age

Figure 3.26 shows the numbers of resident pedal cyclist casualties by ten specified age groups.

The 45 - 54 age group accounts for the highest number of total resident pedal cyclist casualties (28% of total casualties) followed by the 35 - 44 age group with 25 casualties (15%) and the 25 - 34 group with 23 casualties (14%). In contrast, the 65 - 74 age group has the lowest number of casualties (3 casualties;2%). The 85+ age group recorded no casualties.

There are only 2 fatalities across all age groups - one each in the 5 - 16 and 35 - 44 age categories. Serious resident pedal cyclist injuries were highest among the 45 - 54 age group (12;46% of all serious injuries), followed by the 35 - 44 and 55 - 64 groups, each contributing 3 and 4 serious injuries respectively. Notably, the 65 - 74 category reported no serious injuries. In terms of slight injuries, the 45 - 54 age group again leads with slight injuries (35;29%), followed by the 25 - 34 and 35 - 44 age groups each reporting 21 slight injuries (18%). The 65 - 74 and 75 - 84 groups combined accounted for 7 slight injuries (6%).

It is more informative to consider Figure 3.27 which shows resident pedal cyclist casualty numbers by age group indexed by the population of those age groups in Wokingham. There is also a national index value for comparison.

The 45 - 54 age group in Wokingham shows the most dramatic deviation from the national trend with Wokingham casualty numbers being nearly 60% higher than the national index. The age groups of 25 - 34 and 35 - 44 show a notable reversal from the national trend with being overrepresented nationally but Wokingham casualty numbers show a relatively lower representation in the 25 - 34 group whereas there is negligible representation in the 35 - 44 age group. The 55 - 64 age group shows a contrasting pattern with being overrepresented in Wokingham and underrepresented nationally. The older age groups of (65 - 74 and 75 - 84) follow the same direction of the national index however, the 65 - 74 age group is more underrepresented in Wokingham and the 75 - 84 group is relatively less underrepresented compared to the national index.

Figure 3.26: Wokingham resident pedal cyclist casualties, by age group (2019-2023)

Figure 3.27: Wokingham resident pedal cyclist casualties, by age group and indexed by population (2019-2023)

3.1.5.4.2 Segmentation

Analysis of the Acorn communities in which Wokingham’s resident pedal cyclist casualties live provides an insight into those injured in collisions. For an explanation of Acorn and how to understand the following chart, please refer to section 5.1.1.1.

Similar to older drivers, those that are affluent, older homeowners (D8; 27% of the population) are associated with the greatest number of resident pedal cyclist casualties across all Acorn groups. They are overrepresented compared to the relative population with an index value of 119.

Figure 3.28: Wokingham resident pedal cyclist casualties, by Acorn Type (2019-2023)

3.1.5.4.3 Deprivation

Figure 3.29 shows resident pedal cyclist casualties by the IMD of the LSOA (Lower Super Output Area) in which they reside.

The largest number of resident pedal cyclist casualties were from communities in the less deprived IMD deciles. This is particularly true of the least deprived 10%, which is associated with a notably higher number of casualties than any other IMD decile. It has an associated index value of 118.

Figure 3.29: Wokingham resident pedal cyclist casualties, by Index of Multiple Deprivation (2019-2023)

3.2 Wokingham Resident Drivers involved in Collisions

This section refers to all drivers of motor vehicles and motorcycles involved in collisions and who are residents of Wokingham.

3.2.1 All Resident Motor Vehicle Driver Involvement (excluding motorcycle riders)

This section analyses all persons recorded as being [a] Wokingham resident in charge of a motor vehicle (other than a motorcycle or moped) involved in a collision, regardless of age. Therefore, it includes a small number of drivers recorded as being under the age of seventeen.

3.2.1.1 Rates

Figure 3.30 shows the resident driver involvement rates for Wokingham compared to the national and regional rates, as well as the most similar comparators.

Wokingham’s resident driver involvement rate is 134 resident drivers per year, per 100,000 population.

Figure 3.30: Annual average Wokingham resident involved drivers per 100,000 population (2019-2023)

3.2.1.2 Comparisons

Wokingham’s 2019 to 2023 resident driver collision involvement rate is 44% below the national involvement rate and 41% below the South East regional resident driver involvement rate. Against other similar comparator authorities, Wokingham has the second lowest resident driver involvement rate among comparator authorities, behind South Oxfordshire (117 drivers per 100,000 population). Wokingham’s rate is the lowest among all other Berkshire authorities.

3.2.1.2.1 Residency by Small Area

Figure 3.31 shows the home location of Wokingham’s collision-involved resident drivers by lower layer super output area (LSOA). The thematic map is coloured by resident involved drivers per year per population of LSOA.

The highest resident driver involvement rates are in the west of Earley, the north of Arborfield & Garrison, and the southwest of Spencers Wood & Swallowfield.

Figure 3.31: Wokingham resident involved drivers home location by LSOA, drivers per year per 100,000 population (2019-2023)

3.2.1.3 Trends

Figure 3.32 shows Wokingham’s annual collision-involved resident driver numbers since 2014, by severity. This includes resident drivers involved in collisions anywhere in the country. Also shown is a 3-year moving average trend line.

In Wokingham, there were 235 resident driver involved collisions in 2023, marking a continued decline from 398 in 2014, a reduction of over 41% over the decade with the exception of an increase following the Covid - 19 pandemic in 2020. It is noteworthy that fatal collisions involving resident drivers have dropped sharply from 8 in 2022 to 1 in 2023, a 88% decline. This figure also ties with 2017 as the lowest number of fatal collisions recorded across the ten - year span. On the other hand, serious injuries arising from these collisions have seen a rising trend since 2020. After the Covid - 19 pandemic related low of 24, this figure has increased to 45 in 2023, the highest since 2017. Slight injury collisions have fallen to 189 in 2023 compared with 2022’s 221 statistic.

Figure 3.32: Wokingham resident involved drivers, by year and severity (2014-2023)

3.2.1.3.1 Resident driver collision involvement in other areas

Of the 1058 collisions involving Wokingham’s resident drivers, 47% occurred within the authority itself, a notable increase from 42% in the previous reporting period (2018 - 2022). The remaining 53% of collisions occurred outside Wokingham, predominantly in neighbouring authorities. The most common external crash location was Reading, accounting for 131 collisions (11%). This was followed by Hampshire (7%), Surrey (6%), and Bracknell Forest (6%). Together these six areas comprise of over 85% of all external collisions involving Wokingham’s resident drivers.

3.2.1.4 Socio Demographic Analysis

3.2.1.4.1 Age

Figure 3.33 shows the numbers of resident involved drivers by ten specified age groups.

From a total of 684 resident driver involved collisions in Wokingham, the 25 - 34 age group reported the highest number of collisions (159), followed closely by the 35 - 44 group with 149 collisions. Together, these two groups account for 45% of resident driver - involved collisions. These two groups also dominate across serious and slight injuries resulting from these collisions with the 25 - 34 group accounting for 23 serious injuries (24%) and 135 slight injuries (24%). The 35 - 44 group accounts for 20% of serious injuries and 22% of slight injuries resulting from resident driver - involved collisions. The 17 - 24 age group is also involved in 16 serious injuries (17%) and 76 slight injuries (13%) from these collisions.

On the other hand, the 55 - 65 age group is notably overrepresented in fatal collisions, involved in 5 out of 14 total fatal collisions (36%) while comprising of 11% of total collisions. This group also presents 14% of collisions resulting in serious injuries. Meanwhile, slight injuries are largely concentrated among drivers aged 25 - 54, that collectively account for nearly 64% of all collisions in this category (366 collisions).

It is more informative to consider Figure 3.34 which shows resident involved driver numbers by age group indexed by the population of those age groups in Wokingham. There is also a national index value for comparison.

Wokingham’s resident driver involved collision patterns generally align with national trends, with a few notable deviations. The most significant is seen in the 25–34 age group, where Wokingham shows a marked over-representation in resident driver involved collisions compared to the national index. Similar over - representation is seen in the 17 – 24 and 35 – 44 age groups, suggesting that younger and early middle - aged resident drivers in Wokingham are more frequently involved in collisions than their national counterparts.

In contrast, the 45 – 54 age group is underrepresented in Wokingham when compared with the national index. Among older drivers (aged 55+), all age groups are underrepresented nationally and in Wokingham. However, Wokingham’s resident driver involved collisions in the 55 – 64 group show a greater level of under - representation than the national figure, while the 65 – 74, 75 – 84, and 85+ groups although underrepresented but not as significantly as the national index. Children and the younger population aged under 16 are consistently underrepresented across both Wokingham and national figures.

Figure 3.33: Wokingham resident involved drivers, by age group (2019-2023)

Figure 3.34: Wokingham resident involved drivers, by age group and indexed by population (2019-2023)

3.2.1.4.2 Segmentation

Analysis of the Acorn communities in which Wokingham’s resident drivers live provides an insight into those injured in collisions. For an explanation of Acorn and how to understand the following chart, please refer to section 5.1.1.1.

Affluent older homeowners (D8) make up 27% of the population and have the highest total number of resident driver collisions in Wokingham but are actually underrepresented with an index value of 84. The mixed life stage residents in semi - detached homes (G20) are involved in a relatively lower number of resident driver collisions in Wokingham and are also underrepresented compared to the national index. Some other underrepresented groups include families in leafy suburbs (E13;11% of population) and executives in expensive suburban houses (C6;6% of population).

On the other hand, the restricted residents category (M37) although involved in a lower number of resident driver collisions, is the most overrepresented category compared to the national index with an index value of 171.

Figure 3.35: Wokingham resident involved drivers, by Acorn Type (2019-2023)

3.2.1.4.3 Deprivation

Figure 3.36 shows resident involved drivers by the IMD of the LSOA (Lower Super Output Area) in which they reside.

The least deprived areas, particularly the least deprived 10% decile are involved in the most resident involved driver collisions in Wokingham and this is slightly overrepresented compared to the national index with an index value of 107. Despite lower absolute numbers in the less deprived 40% decile, it is dramatically overrepresented compared to the national index with an index value of 221. This trend of overrepresentation is also reflected in other less deprived deciles of 20% and 30% and the more deprived 40% decile with an index value of 169.

Figure 3.36: Wokingham resident involved drivers, by Index of Multiple Deprivation (2019-2023)

3.2.2 Related Casualties

3.2.2.1 Passenger and pedestrian casualties

The related casualties of Wokingham’s resident drivers have been analysed. Related casualties can be the driver themselves; an injured passenger; or a pedestrian struck by the driver’s vehicle. Consequently, injured drivers and passengers of other vehicles are not included in the analysis.

Between 2019 and 2023, among Wokingham’s resident drivers, 65% were resident driver or riders, 24% were vehicle or pillion passengers, and 11% were pedestrian who were injured as a result of a driver’s vehicle colliding with them. It should be noted that the related casualties of Wokingham’s resident drivers could live anywhere in the country and could be injured anywhere. These trends are in line with the previous year.

Figure 3.37: Injured passengers in Wokingham’s resident involved drivers’ vehicles, compared to all drivers (2019-2023)

Most drivers involved collisions where no passengers were injured (87%), which is proportional to the population with an index value of 100. Additionally, there were 10% of road traffic collisions involving 1 injured passenger, which is an under - representation compared to the national proportion, with an index value of 94. In contrast, road traffic collisions involving injuries to 2 to 4 passengers constituted 3% of the overall total but were overrepresented with an index value of 132.

3.2.3 Resident Young Driver Involvement (aged 17 to 24)

This section analyses all young Wokingham resident drivers involved in a collision.

3.2.3.1 Rates

Figure 3.38 shows the resident young driver involvement rates for Wokingham compared to the national and regional rates, as well as the most similar comparators.

Wokingham’s resident young driver collision involvement rate is 227 drivers per year, per 100,000 population. This is lower than the previous reporting period’s (2018 - 2022) rate of 244 drivers per year, per 100,000 population.

Figure 3.38: Annual average Wokingham resident young involved drivers per 100,000 population (2019-2023)

3.2.3.2 Comparisons

Between 2019 to 2023, Wokingham’s resident young driver collision involvement rate is 28% below the national resident young driver collision involvement rate and 39% below the South East’s regional rate. Against other similar comparator authorities, Wokingham has the second lowest resident young driver collision involvement rate, behind Reading (166 per 100,000 population).

3.2.3.2.1 Residency by Small Area

Figure 3.39 shows the home location of Wokingham’s collision-involved resident young drivers by lower layer super output area (LSOA). The thematic map is coloured by resident involved young drivers per year per young adult population of LSOA.

The highest resident young driver collision involvement rates are in the southeast of Twyford West & Charvil and north of Woodley East.

Figure 3.39: Wokingham resident young involved drivers home location by LSOA, young drivers per year per 100,000 population (2019-2023)

3.2.3.3 Trends

Figure 3.40 shows Wokingham’s annual collision-involved resident young driver numbers since 2014, by severity. This includes resident drivers involved in collisions anywhere in the country. Also shown is a 3-year moving average trend line.

Resident young driver involved collisions in Wokingham have halved over the past decade, decreasing by 50% from 60 collisions in 2014 to 30 collisions in 2023. The total number of collisions involving resident young drivers in Wokingham remain unchanged between 2022 and 2023.

Figure 3.40: Wokingham resident young involved drivers, by year and severity (2014-2023)

3.2.3.3.1 Resident young driver collision involvement in other areas

Amongst Wokingham’s resident young driver collisions in 2023, 40% were involved in collisions within Wokingham, a slight decrease compared to 43% reported across 2018 - 2022. The remaining 60% were involved in collisions outside the authority predominantly in Surrey (18%), Reading and Bracknell Forest (14% each), Hampshire (9%), Windsor & Maidenhead and West Berkshire (5% each). These six authorities accounted for over two - thirds of all collisions outside Wokingham involving resident young drivers.

3.2.3.4 Socio Demographic Analysis

3.2.3.4.1 Segmentation

Analysis of the Acorn communities in which Wokingham’s resident young drivers live provides an insight into those injured in collisions. For an explanation of Acorn and how to understand the following chart, please refer to section 5.1.1.1.

Collision involved young drivers in Wokingham largely fall under the affluent, older homeowners category (D8), similar to other demographic profiles. This is slightly underrepresented in proportion to the general population with an index value of 91 (shown in red). As these are younger drivers, the socio - demographic profile is likely to represent their parents profile.

Figure 3.41: Wokingham resident young involved drivers, by Acorn Type (2019-2023)

3.2.3.4.2 Deprivation

Figure 3.42 shows resident involved young drivers by the IMD of the LSOA (Lower Super Output Area) in which they reside.

Collision involved resident young drivers in Wokingham largely belong to least deprived communities, specifically the least deprived 10% decile. This is slightly overrepresented when compared to the relative population with an index value of 118. The less deprived 20% decile is the second - most represented decile among resident young drivers further reflecting the skew towards less deprived communities.

Figure 3.42: Wokingham resident young involved drivers, by Index of Multiple Deprivation (2019-2023)

3.2.4 Related Casualties

3.2.4.1 Passenger and pedestrian casualties

The related casualties of Wokingham’s resident young drivers have been analysed. Related casualties can be the driver themselves; an injured passenger; or a pedestrian struck by the driver’s vehicle. Consequently, injured drivers and passengers of other vehicles are not included in the analysis.

Among Wokingham’s resident young drivers, 60% of the casualties were either drivers or riders. Vehicle or pillion passengers were involved in 31% of casualties whereas pedestrians were involved in 9% of casualties as a result of a collision with a young driver’s vehicle. It must be noted that the related casualties of resident young drivers across Wokingham could live anywhere in the country and have been injured anywhere.

Figure 3.43: Injured passengers in Wokingham’s resident involved young drivers’ vehicles, compared to all young drivers (2019-2023)

Most resident young drivers in Wokingham do not have injured passengers in their vehicle. Less than 30 resident young drivers involve 1 passenger casualty.

3.2.5 Resident Adult Driver Involvement

This section analyses all adult Wokingham resident drivers involved in a collision.

3.2.5.1 Rates

Figure 3.44 shows the resident adult driver involvement rates for Wokingham compared to the national and regional rates, as well as the most similar comparators.

Wokingham’s resident adult driver involvement rate is 194 casualties per year, per 100,000 population.

Figure 3.44: Annual average Wokingham resident adult involved drivers per 100,000 population (2019-2023)

3.2.5.2 Comparisons

Wokingham’s 2019 to 2023 resident adult driver involvement rate is 35% below the national resident adult driver involvement rate and 39% below the South East regional resident adult driver involvement rate. Among comparator authorities, Wokingham has the fourth lowest resident adult driver involvement rate, behind South Oxfordshire (161 per 100,000 population), West Berkshire (179 per 100,000 population), and Windsor & Maidenhead (193 per 100,000 population).

3.2.5.2.1 Residency by Small Area

Figure 3.45 shows the home location of Wokingham’s collision-involved resident adult drivers by lower layer super output area (LSOA). The thematic map is coloured by resident involved adult drivers per year per adult population of LSOA.

The highest resident adult driver involvement rates are in the north of Arborfield & Garrison. High resident adult driver involvement rates are also found in Earley and the southwest of Spencers Wood & Swallowfield.

Figure 3.45: Wokingham resident adult involved drivers home location by LSOA, adult drivers per year per 100,000 population (2019-2023)

3.2.5.3 Trends

Figure 3.46 shows Wokingham’s annual collision-involved resident adult driver numbers since 2014, by severity. This includes resident drivers involved in collisions anywhere in the country. Also shown is a 3-year moving average trend line.

Wokingham recorded 156 total resident adult driver collisions in 2023. Between 2014 and 2023, the number of resident adult driver involved collisions declined by 37% to 156 in 2023. This reduction has largely been driven by a sustained decline in slight injuries resulting from these collisions which have reduced by 41% over the period. Fatal collisions have fluctuated over the decade however, 2023 marked the first year with no fatal collisions since 2014. On the other hand, serious injuries resulting from these collisions remain elevated in recent years, with 27 recorded in 2023 closely aligning with 29 serious injuries from resident adult driver involved collisions reported in 2014.

Figure 3.46: Wokingham resident adult involved drivers, by year and severity (2014-2023)

3.2.5.3.1 Resident adult driver collision involvement in other areas

Between 2019 and 2023, 39% of Wokingham’s resident adult driver involved collisions occurred within the authority while the majority (61%;505 collisions) occurred in other areas. The most common external crash locations include Reading (13%;105 collisions), Surrey (9%;73 collisions), Hampshire (8%,62 collisions), Bracknell Forest (4%;36 collisions) and West Berkshire (4%;30 collisions).

3.2.5.4 Socio Demographic Analysis

3.2.5.4.1 Segmentation

Analysis of the Acorn communities in which Wokingham’s resident adult drivers live provides an insight into those injured in collisions. For an explanation of Acorn and how to understand the following chart, please refer to section 5.1.1.1.

Whilst those that are affluent, older homeowners (D8;27% of the population) are associated with the highest number of resident adult driver involved collisions, they are underrepresented compared to the relative population with an index value of 74. The mixed life stages in semi - detached homes(G20;12% of the population) involves the second highest represented category in collision involved resident adult drivers. However, G20 is underrepresented with an index value of 88.

There are several other Acorn categories that are involved in fewer collisions in Wokingham but are overrepresented when compared to the relative population. The restricted residents that are socially renting (M37;3% of the population) is the most overrepresented with an index value of 188.

Figure 3.47: Wokingham resident adult involved drivers, by Acorn Type (2019-2023)

3.2.5.4.2 Deprivation

Figure 3.48 shows resident involved adult drivers by the IMD of the LSOA (Lower Super Output Area) in which they reside.

The largest number of resident adult driver involved collisions were from communities in the less deprived IMD deciles. This is particularly true of the least deprived 10%, which is associated with the highest number of collisions than any other IMD decile. However, it has an associated index value of 106 indicating a marginal overrepresentation.

Similarly, the less deprived deciles of 20% and 30% are overrepresented with an index value of 125 and 172 respectively. However, resident adult drivers from these deciles are involved in a significantly lower number of collisions that the least deprived 10% decile.

Figure 3.48: Wokingham resident adult involved drivers, by Index of Multiple Deprivation (2019-2023)

3.2.6 Related Casualties

3.2.6.1 Passenger and pedestrian casualties

The related casualties of Wokingham’s resident adult drivers have been analysed. Related casualties can be the driver themselves; an injured passenger; or a pedestrian struck by the driver’s vehicle. Consequently, injured drivers and passengers of other vehicles are not included in the analysis.

Between 2019 and 2023, 67% of casualties were driver or riders, 23% were vehicle or pillion passengers, and 10% were pedestrians as a result of resident adult driver involved collisions.

Figure 3.49: Injured passengers in Wokingham’s resident involved adult drivers’ vehicles, compared to all adult drivers (2019-2023)

Most resident adult driver involved collisions resulted in no passengers being injured. While collisions resulting in one passenger involved are relatively few, this figure is underrepresented compared to the relative population with an index value of 77.

3.2.7 Resident Older Driver Involvement

This section analyses all older Wokingham resident drivers involved in a collision.

3.2.7.1 Rates

Figure 3.50 shows the resident older driver involvement rates for Wokingham compared to the national and regional rates, as well as the most similar comparators.

Wokingham’s resident older driver involvement rate is 91 older drivers per year, per 100,000 population.

Figure 3.50: Annual average Wokingham resident involved older drivers per 100,000 population (2019-2023)

3.2.7.2 Comparisons

Wokingham’s 2019 to 2023 resident older driver involvement rate is 31% below the national rate and 41% below the South East regional rate. Against other similar comparator authorities, Wokingham has the third lowest resident older driver involvement rate, behind South Oxfordshire (82 per 100,000 population) and Reading (84 per 100,000 population).

3.2.7.2.1 Residency by Small Area

Figure 3.51 shows the home location of Wokingham’s collision-involved resident older drivers by lower layer super output area (LSOA). The thematic map is coloured by resident involved older drivers per year per older population of LSOA.

The highest resident older driver involvement rates are in the east of Wokingham Town and west of Shinfield.

Figure 3.51: Wokingham resident involved older drivers home location by LSOA, older drivers per year per 100,000 population (2019-2023)

3.2.7.3 Trends

Figure 3.52 shows Wokingham’s annual collision-involved resident older driver numbers since 2014, by severity. This includes resident drivers involved in collisions anywhere in the country. Also shown is a 3-year moving average trend line.

Between 2014 and 2023, resident older driver involved collisions in Wokingham decreased by 45%, falling from 78 to 43 collisions. This long - term decline has been driven primarily by a 52% reduction in slight injuries resulting from these collisions. Fatal collisions have remained relatively low, though they peaked in 2022 with 4 fatal collisions, before falling to 1 in 2023.

In contrast, serious injuries have risen notably in recent years. In 2023, 12 serious injuries were recorded, the highest figure in the ten - year period, continuing the sharp increase first observed in 2022 (9 serious injuries) following from 2 recorded serious injuries in 2021. This suggests a shift in injury severity, despite overall reduction in collision numbers.

Figure 3.52: Wokingham resident involved older drivers, by year and severity (2014-2023)

3.2.7.3.1 Resident older driver collision involvement in other areas

Between 2019 and 2023, 39% of collisions involving resident older drivers took place within Wokingham whereas the majority of collisions (61%) took place outside the authority. The most common external collision locations include Surrey (11%), Reading and Bracknell Forest (8% each), and Hampshire (5%). These four areas accounted for nearly one - third of all collisions involving Wokingham’s older drivers.

3.2.8 Related Casualties

3.2.8.1 Passenger and pedestrian casualties

The related casualties of Wokingham’s resident older drivers have been analysed. Related casualties can be the driver themselves; an injured passenger; or a pedestrian struck by the driver’s vehicle. Consequently, injured drivers and passengers of other vehicles are not included in the analysis.

Between 2019 and 2023, 66% of casualties were driver or riders, 23% were vehicle or pillion passengers, and 11% were pedestrians as a result of collisions with older drivers. These findings are in line with the previous reporting period.

Figure 3.53: Injured passengers in Wokingham’s resident involved older drivers’ vehicles, compared to all older drivers (2019-2023)

As seen above, the majority of casualties from collisions with older drivers involve drivers or riders. Hence, it is expected that drivers are the most injured category which is also representative of the general population.

4 Wokingham Road Network Risk

For information about the provenance and scope of data included in this section, please refer to section 2.2.2. For an explanation of the methodologies employed throughout this section, please refer to section 5.1.2.

4.1 Collisions in Wokingham

This section refers to all collisions which occurred on Wokingham’s roads. For an explanation of the methodologies employed throughout this section, please refer to section 5.1.2.

4.1.1 Rates

4.1.1.1 Collisions per 100km of road

Figure 4.1 below shows the rate of average annual collisions between 2019 and 2023 per 100km of road in Wokingham compared to the national and regional rates, and those of the most similar comparators.

Between 2019 - 2023, Wokingham had a collision rate of 21.4 collisions per year, per 100 km of the road network. This is slightly lower than the previous reporting period’s collision rate of (22.4).

Figure 4.1: Annual average collisions per 100km of road (2019-2023)

4.1.1.2 Comparisons

Wokingham’s collision rate was 18% lower than the national rate, 37% below the South East regional collision rate and 24% below the overall Berkshire County rate. Within Berkshire, West Berkshire recorded the lowest collision rate at 13.7 collisions per 100 km, followed by Wokingham. In contrast, Reading and Slough had significantly higher collision rates, at 62.6 and 72.2 collisions per 100 km, approximately three times higher than Wokingham’s rate.

4.1.1.2.1 Collisions by Small Area

Figure 4.2 shows collisions on all roads in Wokingham by LSOA. The thematic map is colour coded by the rate of annual average collisions per 100km of road.

Similar to the previous year’s trend, the highest collision rates were found in the southeastern part of Wokingham town centre.

Figure 4.2: Annual average collisions per 100km of road (2019-2023)

4.1.1.3 Trends

Figure 4.3 shows annual collisions on Wokingham’s roads, since 2014 by severity.

Collisions on Wokingham’s road network have declined by 36% from 265 in 2014 to 170 in 2023. While fatal collisions have remained low and variable, with 2 recorded in 2023, serious injuries from collisions have shown a slight upward trend in recent years, increasing from 22 in 2019 to 33 in 2023. On the other hand, slight injuries from collisions have seen a gradual decrease over the decade by 38%.

Figure 4.3: Wokingham collisions, by year and severity (2014-2023)

4.1.1.4 Collisions by day of the week

Figure 4.4 shows collision in Wokingham by day of the week and severity. Tuesday, Wednesday, and Friday each recorded a high number of collisions, with Wednesday reporting the highest at 146, and both Tuesday and Friday close behind at 145. In contrast, Sunday had the lowest number of collisions (64), less than half the midweek totals.

Figure 4.4: Wokingham collisions, by day of the week and severity (2019-2023)

4.1.1.5 Collisions by hour of the day

4.1.1.5.1 Collisions by hour of the day on weekdays

Figure 4.5 shows collisions on weekdays by the hour of the day in which they occurred.

Collision trends on Wokingham’s road network follow a clear bimodal pattern, peaking during the morning (7am - 9 am) and evening (3 pm - 6 pm) commuting hours. The highest number of collisions were reported at 8 am (76 collisions). The evening period (4 pm - 6 pm) accounted for 189 collisions (21%). These trends are likely to be proportional to the traffic flow on the network.

Figure 4.5: Wokingham collisions, by hour of the day during weekdays (2019-2023)

4.1.1.5.2 Collisions by hour of the day on weekends

Figure 4.6 shows collisions on a weekend by the hour of the day in which they occurred. As expected, collisions occurring over the weekend on Wokingham’s road network are more concentrated in the late morning and early evening hours with the highest number of collisions observed at 11 am and 5 pm (18 collisions each). The time - period of 10 am to 5 pm accounts for most collisions occurring over the weekend.

Figure 4.6: Wokingham collisions, by hour of the day during weekends (2019-2023)

4.1.1.6 Collisions by light conditions

Figure 4.7 shows collisions in Wokingham by the light conditions at the time of the collision. The majority of collisions on Wokingham’s road network occur in daylight (77%), followed by the dark with streetlights lit category accounting for 16% of collisions. The darkness streetlights unlit category represents 7% of collisions on the network.

Figure 4.7: Wokingham collisions by light conditions (2019-2023)

4.1.1.7 Collisions by weather conditions

Figure 4.8 shows collisions in Wokingham by the weather conditions present at the time of the collision. Most collisions on Wokingham’s network took place in fine weather without any high winds (88%) followed by 11% collisions in bad weather when it was either raining or snowing without high winds. The fine with high winds and raining or snowing with high winds together accounted for 1% of collisions.

Figure 4.8: Wokingham collisions by weather conditions (2019-2023)

4.1.1.7.1 Collision-involved drivers who reside in other areas

Of the drivers involved in collisions in Wokingham with a known home location, 53% were Wokingham residents. The majority of non - resident drivers with a known home location from a total of 586 non - resident drivers came from Reading (30%), Bracknell Forest (17%), Hampshire (11%) and Windsor & Maidenhead (7%). Thus, over half of the drivers crashing in Wokingham involve Wokingham residents.

4.1.1.8 Collision dynamics and driver actions

4.1.1.8.1 Collision dynamics

Figure 4.9 shows collisions in Wokingham by the dynamics resulting in the collision. A description of collision dynamics and the derivation using STATS19 data is outlined in section 5.1.4 of this report.

The majority of drivers involved in collisions in Wokingham were recorded as single - vehicle collisions (30%), suggesting that drivers may have lost control or struck roadside objects such as trees or barriers. Side - impact collisions and the other impact category, represented 19% and 20% of collisions respectively. Head - on and rear - end collisions occurred at nearly equal rates, each accounting for 16% of all collisions.

Figure 4.9: Wokingham collisions by collision dynamics (2019-2023)

4.1.1.8.2 Driver actions

Figure 4.10 shows collisions in Wokingham by the presence of different driver actions. An explanation of the derivation of driver actions and the definitions are included in section 5.1.5 of this report. Note that collisions can have multiple driver behaviours present, so there may be some overlap in numbers.

The most frequently recorded driver action in collisions on Wokingham’s road network was a right - turn manoeuvre, accounting for 25% of all crashes. This was followed by vehicle run - off incidents, which made up 21%, with 13% involving a nearside run - off. Slow speed manoeuvres such as crashes with parked vehicles or vehicles waiting to proceed accounted for 13% of collisions. Left - turn manoeuvres were less common, contributing to 7% of all collisions.

Figure 4.10: Wokingham collisions by driver actions (2019-2023)

4.1.1.9 Road environment

4.1.1.9.1 Road class

Figure 4.11 shows collisions in Wokingham by class of road. The majority of collisions on the network occur on A roads (39%) closely followed by unclassified roads accounting for 35% of collisions. On the other hand, motorways account for 9% of collisions whereas 17% of collisions take place on B roads. Thus, most crashes on Wokingham’s network take place on A roads and unclassified roads.

Figure 4.11: Wokingham collisions by road class (2019-2023)

4.1.1.9.2 Carriageway type

Figure 4.12 shows collisions in Wokingham by carriageway type of road. About three - quarters (76%) of collisions occur on single carriageways followed by dual carriageways (12%) and roundabouts (9%). One - way streets and slip roads collectively account for 4% of collisions on the network.

Figure 4.12: Wokingham collisions by road carriageway type (2019-2023)

4.1.1.9.3 Junction type

Figure 4.13 shows collisions in Wokingham by the presence and type of junction. Most collisions on the network took place away from a junction (38%). This is followed closely by a normal junction (crossroads or T junctions) accounting for 35% of collisions on the network. Crashes occurring at roundabouts and private drives led to 20% and 5% of crashes respectively.

Figure 4.13: Wokingham collisions by junction type (2019-2023)

4.1.1.9.4 Junction control

Figure 4.14 shows collisions in Wokingham by the type of junction control (if the collision took place at a junction). Over three quarters of the crashes on the Wokingham network took place at a give way or uncontrolled junction (84%). Additionally, 15% of collisions took place where an auto traffic signal was present whereas stop signs accounted for only 1% of collisions. These figures are in line with the previous reporting period’s findings.

Figure 4.14: Wokingham collisions by junction control (2019-2023)

4.1.2 Casualty trends on all roads

4.1.2.1 All casualties

Figure 4.15 shows annual casualty numbers for collisions on Wokingham’s roads. While overall casualties in Wokingham have declined by 40% over the decade, a rising trend has emerged since 2021 with casualties increasing by 26% in 2021. However, there was a 10% decrease in 2023 compared to 2022, largely driven by a reduction in slight injuries. Notably, serious injuries have seen an increase by 50% between 2022 and 2023. On the other hand, fatalities have remained relatively stable throughout the ten - year period.

Figure 4.15: Casualties on Wokingham’s roads by year (2014-2023)

4.1.2.1.1 Casualty class

Figure 4.16 shows the classes of casualties injured in Wokingham. Unsurprisingly, about three - quarters of the casualties on the network were drivers or riders (72%). Other road user casualties include vehicle or pillion passengers (18%) and pedestrians (11%).

Figure 4.16: Wokingham casualties by casualty class (2019-2023)

4.1.2.1.2 Casualty age

Figure 4.17 shows the age groups of casualties injured in Wokingham. The 25 - 34 age group accounts for the highest number of casualties (216 casualties;20%) followed by an almost equal split of casualties between the 17 - 24 and 35 - 44 age group (17% each). As expected, casualties decline as age increases which could possibly be attributed to lower exposure on the network. The 45 - 54 age group accounts for 15% of casualties whereas the 55 - 64 group is represented in 11% of all casualties.

Figure 4.17: Wokingham casualties by age group (2019-2023)

4.1.2.1.3 Casualty gender

Figure 4.18 shows the breakdown of casualties injured in Wokingham by gender. More than half of the casualties across Wokingham are males (63%) compared with 37% of female casualties.

Figure 4.18: Wokingham casualties by gender (2019-2023)

4.1.2.2 Pedal cyclist casualties

Figure 4.19 shows annual pedal cyclist casualty numbers on Wokingham’s roads. Pedal cyclists represent a smaller share of casualties on Wokingham’s road network and have experienced a general decline in casualty figures since the Covid - 19 pandemic. The previous year, 2022 recorded the lowest number of pedal cycle casualties over the past decade (27). Between 2022 and 2023, total pedal cycle casualties have increased by 30%, rising from 27 to 35. A modest increase in serious injuries was noted (6 serious injuries), double the figure recorded in 2022.

Figure 4.19: Pedal cyclist casualties on Wokingham’s roads by year (2014-2023)

4.1.2.3 Motorcycle user casualties

Figure 4.20 shows annual motorcycle user casualty numbers on Wokingham’s roads. Motorcycle user casualties have seen an increasing trend since 2020. While the total number of motorcycle casualties have remained the same since 2021 (33) there were some marginal fluctuations in the severity profile of the casualties. Serious injuries rose from 5 in 2022 to 8 in 2023 whereas slight injuries have decreased marginally from 28 to 25. On the other hand, 2021 saw double the serious injuries recorded in 2022 (10) and 23 slight injuries.

Figure 4.20: Motorcycle user casualties on Wokingham’s roads by year (2014-2023)

4.1.3 Driver trends on all roads

4.1.3.1 Vehicle type

Figure 4.21 shows the types of vehicles involved in collisions in Wokingham. Cars are involved in the majority of collisions in Wokingham (68%). Other most common types of vehicles involved in collisions include cycles (12%), goods vehicles (10%), and motorbikes (9%).

Figure 4.21: Wokingham collision-involved drivers by vehicle type (2019-2023)

4.1.3.2 All drivers

This section covers drivers of motor vehicles involved in collisions. This excludes both motorcycle riders and pedal cyclists, who are covered in subsequent sections.

Figure 4.22 shows annual driver collision involvement on Wokingham’s roads. Driver involved collisions have declined over the decade, dropping from 409 in 2014 to 254 collisions in 2023. Collision figures have gradually increased since 2020 with the 2023 reported figures (254 collisions) slightly exceeding the pre - pandemic level in 2019 (244). From 2022 to 2023, there was a 10% decrease in driver - involved collisions (from 283 to 254) driven by a reduction in slight injuries from collisions.

While the overall collision figures have shown a decline, serious injuries from collisions have increased by 55% compared to the previous year, the highest recorded since 2017. Fatal collisions have remained relatively stable, typically between 0 - 5 recorded per year over the decade.

Figure 4.22: Drivers involved in collisions on Wokingham’s roads by year (2014-2023)

4.1.3.2.1 Young drivers

Figure 4.23 shows annual numbers of young drivers involved in collisions on Wokingham’s roads. In this analysis, young drivers are those aged 17 to 24. Young driver collisions have decreased by 37% over the decade, from 49 in 2014 to 31 in 2023. Collisions saw a sharp drop in 2020 likely influenced by the Covid - 19 pandemic. Collisions have seen an increase after 2020, peaking at 44 in 2022, before falling to 31 in 2023 (30% decrease). While an overall decline was recorded, 2023 saw the highest number of serious injury collisions recorded (10) in this decade.

Figure 4.23: Collision-involved young drivers on Wokingham’s roads by year (2014-2023)

4.1.3.2.2 Older drivers

Figure 4.24 shows annual numbers of older drivers involved in collisions on Wokingham’s roads. In this analysis, older drivers are those aged 60 and over. In 2022, collisions involving older drivers spiked to 40, marking one of the highest recorded collision figures in the recent years. However, 2023 saw a decline in collision figures by 15% (34 collisions). This drop has largely been driven by a decline in slight injuries from collisions (27%;24 slight injuries).

Figure 4.24: Collision-involved older drivers on Wokingham’s roads by year (2014-2023)

4.1.3.3 Motorcycle riders

Figure 4.25 shows annual numbers of motorcycle riders involved in collisions on Wokingham’s roads. As with most road user groups, motorcycle rider involved collisions have increased after 2020. Since 2021, the total number of collisions involving this road user group have remained stable ranging from 32 to 34 collisions. Serious injuries from collisions have increased slightly from 6 to 8 serious injuries whereas the slight injury collisions have dropped marginally from 27 to 26. The trend of no fatal collisions involving motorcycle riders has continued since 2019.

Figure 4.25: Collision-involved motorcycle riders on Wokingham’s roads by year (2014-2023)

4.1.3.4 Pedal cyclists

Figure 4.26 shows annual numbers of pedal cyclists involved in collisions on Wokingham’s roads. Figures pertaining to pedal cyclists involved in collisions have slightly increased from 28 collisions in 2022 to 36 collisions in 2023 (29% increase). This rise can be largely attributed to an increase in serious injuries from collisions which have nearly tripled compared to the previous year (from 3 to 8). Slight injury collisions have also seen an increase from 25 recorded slight injuries to 28 in 2023.

Figure 4.26: Collision-involved pedal cyclists on Wokingham’s roads by year (2014-2023)

4.2 Collisions on Urban Roads in Wokingham

The following section investigates collisions in Wokingham which occurred on urban roads. For an explanation of how urban roads have been identified in Wokingham, please refer to Section 5.1.2.1.1.

4.2.1 Rates

4.2.1.1 Collisions on urban roads per 100km of urban road

Figure 4.27 below shows the rate of average annual collisions on urban roads between 2019 and 2023 per 100km of urban road in Wokingham compared to the national and regional rates, and those of the most similar comparators.

Between 2019 and 2023, Wokingham’s urban roads recorded a collision rate of 21 collisions per year, per 100 km of urban road length. This is similar to the previous reporting period’s (2018 - 2022) collision rate of 22 collisions.

Figure 4.27: Annual average collisions on urban roads per 100km of urban road (2019-2023)

4.2.1.2 Comparisons

Wokingham’s urban road collision rate is less than half of the national collision rate (46) and the South East’s regional collision rate (45). It is also 38% lower than the overall Berkshire average of 35 collisions on urban roads per 100 km.

Within Berkshire, West Berkshire has the lowest urban road collision rate at 18 collisions per 100 km, followed closely by Wokingham. Windsor & Maidenhead record a slightly higher collision rate at 25 collisions per 100 km whereas Reading and Slough recorded significantly higher urban road collision rates at 62 and 68 collisions per 100 km respectively, over three times higher than Wokingham’s rate.

4.2.1.2.1 Collisions on Urban Roads by Small Area

Figure 4.28 shows collisions on urban roads in Wokingham by LSOA. The thematic map is colour coded by the rate of annual average collisions on urban roads per 100km of urban road. The highest number of collisions on urban roads in Wokingham are found in the southwestern part of Wokingham’s town centre.

Figure 4.28: Annual average collisions on urban roads per 100km of urban road (2019-2023)

4.2.1.3 Trends

Figure 4.29 shows annual collisions on Wokingham’s urban roads, since 2014 by severity. Collisions on urban roads have reduced by 31% over the past decade, falling from 131 in 2014 to 90 in 2023. Compared to the previous year, 2023 recorded a 14% decrease in urban road collisions (down from 104 in 2022). Slight injury collisions have seen a decline from 91 in 2022 to 72 in 2023.

Figure 4.29: Wokingham collisions on urban roads, by year and severity (2014-2023)

4.2.1.4 Collisions by day of the week

Figure 4.30 shows collisions on urban roads in Wokingham by day of the week and severity.

Most collisions on Wokingham’s urban roads occur on Tuesday, Wednesday, and Friday.

Figure 4.30: Wokingham collisions on urban roads, by day of the week and severity (2019-2023)

4.2.1.5 Collisions on urban roads by hour of the day

4.2.1.5.1 Collisions on urban roads by hour of the day on weekdays

Figure 4.31 shows collisions on urban roads on weekdays by the hour of the day in which they occurred.

Collisions on urban roads in Wokingham are heavily concentrated during commuting hours, with clear peaks in the afternoon (3 - 6 pm) and the morning (7 - 9 am). This is likely to be influenced by the traffic flow during commuting hours.

Figure 4.31: Wokingham collisions on urban roads, by hour of the day during weekdays (2019-2023)

4.2.1.5.2 Collisions on urban roads by hour of the day on weekends

Figure 4.32 shows collisions on urban roads on a weekend by the hour of the day in which they occurred.

Wokingham’s urban road network recorded no fatal collisions over the weekend. Both serious and slight injuries from collisions occurred sporadically across the day, without a single dominant pattern. However, the late morning period between 10 am and noon recorded the highest concentration of collisions, accounting for over one - third of the weekend’s total crashes.

Figure 4.32: Wokingham collisions on urban roads, by hour of the day during weekends (2019-2023)

4.2.1.6 Collisions on urban roads by light conditions

Figure 4.33 shows collisions on urban roads in Wokingham by the light conditions at the time of the collision.

Over three - quarters of collisions occur in daylight across Wokingham’s urban roads with the darkness and streetlights lit category accounting for 19% of collisions. The darkness and streetlights unlit category represents a marginal percentage of crashes on the network (2%).

Figure 4.33: Wokingham collisions on urban roads by light conditions (2019-2023)

4.2.1.7 Collisions on urban roads by weather conditions

Figure 4.34 shows collisions on urban roads in Wokingham by the weather conditions present at the time of the collision.

The majority of crashes on the urban road network occur in good weather conditions without high winds (89%). High winds was not recorded as a key contributor for crashes whereas the ‘raining or snowing without high winds’ category represents 10% of crashes.

Figure 4.34: Wokingham collisions on urban roads by weather conditions (2019-2023)

4.2.1.7.1 Collisions on urban roads by driver residency

Of the collisions on urban roads in Wokingham where the home location was recorded, Wokingham resident drivers accounted for just under half of recorded collisions (49%). Non - resident drivers made up 51% of crashes with the largest share from Reading (23%). Surrey and Bracknell Forest each accounted for 6% of collisions followed by Hampshire drivers representing 3% of crashes.

4.2.1.8 Collision dynamics and driver actions on urban roads

4.2.1.8.1 Collision dynamics

Figure 4.35 shows collisions on urban roads in Wokingham by the dynamics resulting in the collision. A description of collision dynamics and the derivation using STATS19 data is outlined in section 5.1.4 of this report.

Most collisions on urban roads in Wokingham are single vehicle collisions (28%) mirroring the trend observed on all roads in the authority. Side impact and other impact collisions were the next most represented dynamic accounting for 21% and 22% of urban road collisions respectively. Head - on impacts comprised of 16% of collisions marking a slight increase from the previous reporting period (12%) while rear impact collisions made up 13% of the total collisions.

Figure 4.35: Wokingham collisions on urban roads by collision dynamics (2019-2023)

4.2.1.8.2 Driver actions

Figure 4.36 shows collisions on urban roads in Wokingham by the presence of different driver actions. An explanation of the derivation of driver actions and the definitions are included in section 5.1.5 of this report. Note that collisions can have multiple driver behaviours present, so there may be some overlap in numbers.

Similar to the previous reporting period, drivers making a right turn were involved in the highest number of collisions (31%) followed by a slow manoeuvre (14%). Slow manoeuvres can include driver actions such as slowing down, waiting to proceed, among others. Run - off collisions on urban roads represented 12% of total collisions compared with previous year’s 10% figure.

Figure 4.36: Wokingham collisions on urban roads by driver actions (2019-2023)

4.2.1.9 Urban road environment

4.2.1.9.1 Road class

Figure 4.37 shows collisions on urban roads in Wokingham by class of road. The majority of collisions on urban roads in Wokingham take place on unclassified roads (44%) compared with 37% on A roads and 16% on B roads. Motorways represent a small number of collisions on urban roads in Wokingham (3%).

Figure 4.37: Wokingham collisions on urban roads by road class (2019-2023)

4.2.1.9.2 Carriageway type

Figure 4.38 shows collisions on urban roads in Wokingham by carriageway type of road. Single carriageways are the most common road type for urban collisions in Wokingham, accounting for 81% of incidents, slightly higher than the 76% observed across all road types. In contrast, dual carriageways represent a smaller share of urban road collisions (5%), compared to 12% across all roads. Roundabouts account for 10% of urban collisions, while one - way streets account for 3% of crashes.

Figure 4.38: Wokingham collisions on urban roads by road carriageway type (2019-2023)

4.2.1.9.3 Junction type

Figure 4.39 shows collisions on urban roads in Wokingham by the presence and type of junction. Most collisions on urban roads took place at a normal junction (crossroads or T junctions; 41%). A considerable number of collisions took place where there was no junction (28%) and roundabouts account for 22% of crashes on the urban road network.

Figure 4.39: Wokingham collisions on urban roads by junction type (2019-2023)

4.2.1.9.4 Junction control

Figure 4.40 shows collisions on urban roads in Wokingham by the type of junction control (if the collision took place at a junction). In line with the trend observed on all roads, give way or controlled junctions account for the majority of collisions on urban roads (85%). This is followed by 14% of collisions taking place where an auto traffic signal is present whereas the authorised person and stop sign categories combined account for 1% of crashes on urban roads in Wokingham.

Figure 4.40: Wokingham collisions on urban roads by junction control (2019-2023)

4.2.2 Casualty trends on urban roads

4.2.2.1 All casualties

Figure 4.41 shows annual casualty numbers for collisions on Wokingham’s urban roads.

Casualties on urban roads have seen an increasing trend after the pandemic low in 2020 (93), peaking again at 135 in 2022, before dropping to 97 in 2023, a 28% decrease. This sharp reduction in 2023 is largely driven by a 36% fall in slight injuries (from 121 in 2022 to 78 in 2023). This trend was also observed in casualties taking place on all roads.

Figure 4.41: Casualties on Wokingham’s urban roads by year (2014-2023)

4.2.3 Driver trends on urban roads

4.2.3.1 Vehicle type

Figure 4.42 shows the types of vehicles involved in collisions on urban roads in Wokingham. Over half of the collisions on the urban road network involve cars in Wokingham (68%). Other frequent vehicle types involved in crashes include cycles (13%), motorbikes (10%) and good vehicles (8%).

Figure 4.42: Wokingham collision-involved drivers on urban roads by vehicle type (2019-2023)

4.2.3.2 All drivers

This section covers drivers of motor vehicles involved in collisions on urban roads. This excludes both motorcycle riders and pedal cyclists, who are covered in subsequent sections.

Figure 4.43 shows annual driver collision involvement on Wokingham’s urban roads. Driver involvement in urban road collisions has declined by 36% over the decade, from 185 in 2014 to 119 in 2023. The total number of urban drivers involved in collisions has dropped by 24% in 2023 compared to 2022 (from 156 to 119). This sharp decline was driven by a 28% reduction in slight injury collisions, which have reduced from 138 in 2022 to 100 in 2023.

Figure 4.43: Drivers involved in collisions on Wokingham’s urban roads by year (2014-2023)

4.3 Collisions on Rural Roads in Wokingham

The following section investigates collisions in Wokingham which occurred on rural roads. For an explanation of how rural roads have been identified in Wokingham, please refer to Section 5.1.2.1.1.

4.3.1 Rates

4.3.1.1 Collisions on rural roads per 100km of rural road

Figure 4.44 below shows the rate of average annual collisions on rural roads between 2019 and 2023 per 100km of rural road in Wokingham compared to the national and regional rates, and those of the most similar comparators.

Wokingham’s collision rate was 22 collisions per year, per 100 km of rural roads. This is similar to the previous reporting period’s collision rate of 23 collisions per year, per 100 km.

Figure 4.44: Annual average collisions on rural roads per 100km of rural road (2019-2023)

4.3.1.2 Comparisons

Wokingham’s rural road collision rate is 59% higher than the national statistic and 10% above the overall Berkshire county figure. In Berkshire, West Berkshire has the lowest rural road collision rate at 12 collisions per year, per 100 km of rural roads. However, Wokingham’s rate is 15% below the overall South East region, 28% lower than Windsor & Maidenhead and 30% below Bracknell Forest’s collision rate. Reading and Slough have the highest rural road collision rates among the comparators that are 3 times - 5 times higher than Wokingham’s rate.

4.3.1.2.1 Collisions on Rural Roads by Small Area

Figure 4.45 shows collisions on rural roads in Wokingham by LSOA. The thematic map is colour coded by the rate of annual average collisions on rural roads per 100km of rural road.

The highest rural collision rates were seen across the southern part of Twyford West & Charvil, northeastern part of Sonning and Woodley North and the northwestern region of Woodley East.

Figure 4.45: Annual average collisions on rural roads per 100km of rural road (2019-2023)

4.3.1.3 Trends

Figure 4.46 shows annual collisions on Wokingham’s rural roads, since 2014 by severity.

A flattening trend was observed for rural road collisions in Wokingham in recent years, with total collisions ranging between 79 and 88 collisions. While there was a 10% decrease in total rural collisions from 2021 (88) to 2022 (79), 2023 figures remain largely unchanged, recording 80 collisions.

There were no fatal collisions for the second consecutive year, continuing a positive trend. However, serious injury collisions rose, increasing by 55% from 11 in 2022 to 17 in 2023. In contrast, slight injury collisions showed minor fluctuation, with 63 recorded in 2023, down from 68 in the previous year.

Figure 4.46: Wokingham collisions on rural roads, by year and severity (2014-2023)

4.3.1.4 Collisions by day of the week

Figure 4.47 shows collisions on rural roads in Wokingham by day of the week and severity.

Friday recorded the highest number of rural road collisions with 69 collisions, followed closely by Wednesday (67) and Tuesday (64). Sunday saw the lowest number of collisions with 32 collisions.

Figure 4.47: Wokingham collisions on rural roads, by day of the week and severity (2019-2023)

4.3.1.5 Collisions on rural roads by hour of the day

4.3.1.5.1 Collisions on rural roads by hour of the day on weekdays

Figure 4.48 shows collisions on rural roads on weekdays by the hour of the day in which they occurred. The highest number of collisions were recorded at 8 am (34) which is likely to be associated with an increase in commuting traffic at this hour. The evening hours of 4 pm and 6 pm each recorded 28 collisions. Daytime hours between 6 am and 6 pm account for 83% of all weekday rural road collisions whereas the hours between midnight - 5 am account for just 4% (12 collisions) of the total collisions. Although the number of rural collisions decrease after 8 pm, fatal collisions were recorded in off - peak hours with one each at midnight, 10 pm and 6 am respectively.

Figure 4.48: Wokingham collisions on rural roads, by hour of the day during weekdays (2019-2023)

4.3.1.5.2 Collisions on rural roads by hour of the day on weekends

Figure 4.49 shows collisions on rural roads on a weekend by the hour of the day in which they occurred. The evening hour 5 pm recorded the highest number of collisions (12) on rural roads in Wokingham over the weekend. In contrast, weekday peak hours reached 28 - 34 collisions. Another subsequent peak in collisions is seen at 1 pm with 9 collisions. Overall, as expected weekdays record a higher number of collisions and are concentrated during commuting hours whereas weekend collisions are fewer and more evenly spread out with peaks seen in the afternoon and early evening hours.

Figure 4.49: Wokingham collisions on rural roads, by hour of the day during weekends (2019-2023)

4.3.1.6 Collisions on rural roads by light conditions

Figure 4.50 shows collisions on rural roads in Wokingham by the light conditions at the time of the collision. The majority of collisions on rural roads in Wokingham take place in daylight (74%). This is followed by an almost even split between collisions occurring in the dark with streetlights lit category (13%) and dark with streetlights unlit category (12%).

Figure 4.50: Wokingham collisions on rural roads by light conditions (2019-2023)

4.3.1.7 Collisions on rural roads by weather conditions

Figure 4.51 shows collisions on rural roads in Wokingham by the weather conditions present at the time of the collision. The majority of the collisions on Wokingham’s rural roads occur in good weather, ‘fine without high winds’ (86%). A considerable number of collisions take place when it is either raining or snowing without high winds (12%). Overall, as seen with urban roads, high winds were not attributed to a large number of collisions in Wokingham.

Figure 4.51: Wokingham collisions on rural roads by weather conditions (2019-2023)

4.3.1.7.1 Collisions on rural roads by driver residency

Around two - thirds of drivers involved in collisions on Wokingham’s rural roads, where home location was recorded, were non - residents. In contrast, 34% of collisions involved Wokingham residents. Among non - resident drivers, the majority came from Reading (15%), followed by Bracknell Forest (9%), Hampshire (7%), Windsor & Maidenhead (5%), and West Berkshire (3%).

4.3.1.8 Collision dynamics and driver actions on rural roads

4.3.1.8.1 Collision dynamics

Figure 4.52 shows collisions on rural roads in Wokingham by the dynamics resulting in the collision. A description of collision dynamics and the derivation using STATS19 data is outlined in section 5.1.4 of this report.

On Wokingham’s rural road network, single vehicle collisions represent the most common collision dynamic accounting for 32% of all collisions. This is slightly higher than 28% of single vehicle collisions on urban roads. Rear impact collisions are the second most prevalent (18%), followed closely by the head - on and side impact collision dynamics that are evenly split at 16%. Conversely, side impact collisions are more prevalent on urban roads (21%).

Figure 4.52: Wokingham collisions on rural roads by collision dynamics (2019-2023)

4.3.1.8.2 Driver actions

Figure 4.53 shows collisions on rural roads in Wokingham by the presence of different driver actions. An explanation of the derivation of driver actions and the definitions are included in section 5.1.5 of this report. Note that collisions can have multiple driver behaviours present, so there may be some overlap in numbers.

The driver actions of a vehicle runoff (32%) and runoff nearside (19%) accounted for the highest number of crashes on Wokingham’s rural roads. This is consistent with the high number of single vehicle collisions inferred earlier. In contrast, runoff collisions on urban roads represented 12% of crashes. The vehicle manoeuvre involving a right turn accounted for 18% of crashes on the rural network compared with 31% of crashes on the urban network.

Figure 4.53: Wokingham collisions on rural roads by driver actions (2019-2023)

4.3.1.9 Rural road environment

4.3.1.9.1 Road class

Figure 4.54 shows collisions on rural roads in Wokingham by class of road. Motorways account for 16% of crashes compared with 41% and 18% of crashes on A and B roads respectively. Unclassified roads on the rural network also represent a large number of crashes (25%). On the other hand, the majority of crashes on urban roads take place on unclassified roads (44%) whereas motorways on urban roads account for only 3% of crashes.

Figure 4.54: Wokingham collisions on rural roads by road class (2019-2023)

4.3.1.9.2 Carriageway type

Figure 4.55 shows collisions on rural roads in Wokingham by carriageway type of road. Single carriageways represent just under three - quarters of collisions on the rural network (70%) compared with dual carriageways accounting for 20% of collisions. When compared to all roads, rural roads see a higher number of crashes on dual carriageways than all roads (12%). Roundabouts represent 9% of crashes on the rural network.

Figure 4.55: Wokingham collisions on rural roads by road carriageway type (2019-2023)

4.3.1.9.3 Junction type

Figure 4.56 shows collisions on rural roads in Wokingham by the presence and type of junction. Just under half of the crashes on Wokingham’s rural road network took place where no junction was present (49%) compared with 28% taking place at a normal junction (Crossroads or T junction). Roundabouts account for 17% of crashes followed by 4% of crashes at private drives. This is consistent with the higher number of single vehicle collisions and vehicle runoffs inferred above.

Figure 4.56: Wokingham collisions on rural roads by junction type (2019-2023)

4.3.1.9.4 Junction control

Figure 4.57 shows collisions on rural roads in Wokingham by the type of junction control (if the collision took place at a junction). The majority of crashes took place at a give way or uncontrolled junction (82%) which is slightly lower than the urban roads and all roads figures of 85% and 84% respectively. While auto traffic signals represented 16% of collisions on the rural network, stop signs accounted for 2%.

Figure 4.57: Wokingham collisions on rural roads by junction control (2019-2023)

4.3.2 Casualty trends on rural roads

4.3.2.1 All casualties

Figure 4.58 shows annual casualty numbers for collisions on Wokingham’s rural roads. Casualties on rural roads in Wokingham have declined by 40% over the past decade, from 198 in 2014 to 119 in 2023. The total number of casualties have increased by 12% between 2022 (106 casualties) and 2023 (119 casualties). This increase has largely been driven by a rise in serious injuries which rose from 11 in 2022 to 19 in 2023. Slight injuries have increased modestly compared to the previous year from 95 to 100 (5% increase). No fatalities were recorded on the rural road network in line with the previous year’s findings.

Figure 4.58: Casualties on Wokingham’s rural roads by year (2014-2023)

4.3.3 Driver trends on rural roads

4.3.3.1 Vehicle type

Figure 4.59 shows the types of vehicles involved in collisions on rural roads in Wokingham. Unsurprisingly, cars are involved in the majority of collisions on rural roads (69%) followed by goods vehicles (12%) and cycles (10%). Motorbikes represent 8% of crashes on Wokingham’s rural roads whereas buses account for 0.4% of crashes. Rural roads in Wokingham account for a higher number of goods vehicle collisions compared with urban roads (8%) and all roads (10%).

Figure 4.59: Wokingham collision-involved drivers on rural roads by vehicle type (2019-2023)

4.3.3.2 All drivers

This section covers drivers of motor vehicles involved in collisions on rural roads. This excludes both motorcycle riders and pedal cyclists, who are covered in subsequent sections.

Figure 4.60 shows annual driver collision involvement on Wokingham’s rural roads. Drivers involved in collisions on rural roads declined by 40% over the decade from 224 in 2014 to 135 in 2023. While rural drivers involved in collisions increased by 6% from 127 in 2022 to 135 in 2023, the urban road network saw a 24% drop in collisions. The rise in these collisions can be attributed to a doubling of serious injuries, rising from 15 to 31. Slight injuries from collisions fell modestly on rural roads (from 112 to 104). No fatal collisions involving rural drivers were recorded on the rural road network between 2022 and 2023, a major improvement from 2021’s 4 recorded fatal collisions.

Figure 4.60: Drivers involved in collisions on Wokingham’s rural roads by year (2014-2023)

4.4 Contributory Factors

Each section below examines trends in reported collisions on Wokingham’s roads involving groups of related contributory factors (CFs). For each group, the total number of collisions in which any CF in the group was recorded has been determined. To provide comparative context, each chart also shows the three-year average of all police attended collisions with recorded CFs.
For more information about CFs and the techniques used to analyse them see section 5.1.6. For a complete list of all CFs and CF groupings used by Agilysis, see section 5.4.

4.4.1 Speed Related

This section examines collisions, by severity, where at least one of the contributory factors 306 Exceeding speed limit and/or 307 Travelling too fast for conditions was attributed to one or more vehicles. This may include some instances where these factors were applied more than once in the same collision.

4.4.1.1 Trends

Figure 4.61: Collisions in Wokingham where CF306 and/or CF307 were recorded (2014-2023)

Figure 4.61 shows annual collisions on Wokingham’s roads where at least one of the speed choice CFs were recorded, with a three-year moving average trend line for speed choice collisions. Figure 4.62 shows the trends for collisions where speed choice CFs were recorded and for collisions where a police officer attended, indexed over a 2014 baseline for comparison.

The number of collisions attributed to contributory factors 306/ 307 have reduced from 14 in 2022 to 11 in 2023. Serious injury collisions involving these contributory factors doubled in 2023 (4) compared to 2022 (2), matching the peak levels seen in 2015 and 2017. Conversely, slight injury collisions involving CFs 306/307 have reduced by 42% from 12 in 2022 to 7 in 2023, the lowest since 2014.

The relationship between collisions attributed to CF306 or CF307 and the number of police attended collisions have seen a fluctuating trend. With 2014 as a baseline, the number of collisions attributed to these CFs is slightly higher than the police attended collisions.

Figure 4.62: Collision trends in Wokingham where CF306 and/or CF307 were recorded compared to officer attended collision trends (2014-2023)

4.4.1.2 Comparisons

Figure 4.63 shows collisions on Wokingham’s roads where at least one of the speed choice CFs was recorded, as a percentage of all officer attended collisions where any CF was recorded. Also shown are the national, regional and comparator authorities’ percentages.

In Wokingham, 9.7% of all recorded collisions were attributed to speed choice contributory factors. This is lower than the national statistic (11.3%), the broader South East region (12%) and slightly below the overall Berkshire county average (10%). Wokingham’s rate is also slightly lower than Bracknell Forest (10%), West Berkshire (10.5%), and Windsor & Maidenhead (10.2%) but higher than Reading (8.8%) and Surrey Heath (8.6%). Slough recorded the highest number of collisions attributed to CF306 and CF307 in the Berkshire county at 11.4%.

Figure 4.63: Percentage of collisions in Wokingham and comparators where CF306 and/or CF307 were recorded (2019-2023)

4.4.2 Impairment

This section examines collisions, by severity, where at least one of the contributory factors 501 Impaired by alcohol and/or 502 Impaired by drugs (illicit or medicinal) was attributed to one or more drivers. This may include some instances where these factors were applied more than once in the same collision.

4.4.2.1 Trends

Figure 4.64: Collisions in Wokingham where CF501 and/or CF502 were recorded (2014-2023)

Figure 4.64 shows annual collisions on Wokingham’s roads where at least one of the impairment CFs were recorded, with a three-year moving average trend line for impairment collisions. Figure 4.65 shows the trends for collisions where impairment CFs were recorded and for collisions where a police officer attended, indexed over a 2014 baseline for comparison.

Collisions attributed to impairment related contributory factors in Wokingham have followed a fluctuating trend over the past decade, with certain years recording notably higher figures and others considerably lower. The lowest number of impairment - related collisions was recorded in 2016 (5), while 2023 reported the second lowest figure (7). This marks a significant reduction compared to 2022, which recorded 14 such collisions, indicating that the number of collisions linked to CF501 or CF502 have halved.

In line with 2022, no fatal collisions were attributed to impairment in 2023. Notably, slight injury collisions also fell sharply, dropping from 12 in 2022 to just 4 in 2023. Using 2014 as a baseline, the proportion of impairment related collisions are marginally higher than the number of police attended collisions. However, the gap between collisions attributed to impairment and those attended by officers has narrowed, particularly since 2022.

Figure 4.65: Collision trends in Wokingham where CF501 and/or CF502 were recorded compared to officer attended collision trends (2014-2023)

4.4.2.2 Comparisons

Figure 4.66 shows collisions on Wokingham’s roads where at least one of the impairment CFs was recorded, as a percentage of all officer attended collisions where any CF was recorded. Also shown are the national, regional and comparator authorities’ percentages.

In Wokingham, 9.6% of all officer recorded collisions were attributed to impairment related contributory factors. This is higher than the GB statistic (7.4%) and the overall Berkshire county figure (7.9%). Wokingham surpasses many other comparator authorities including Reading (7.2%), Slough (5.1%) and Windsor & Maidenhead (7.7%). In contrast, authorities with higher rates than Wokingham include South Cambridgeshire and South Oxfordshire at 10%.

Figure 4.66: Percentage of collisions in Wokingham and comparators where CF501 and/or CF502 were recorded (2019-2023)

4.4.3 Road Surface Conditions

This section examines collisions, by severity, where at least one of the CFs 101 Poor or defective road surface, 102 Deposit on road (e.g. oil, mud, chippings) and/or 103 Slippery road (due to weather) was attributed. This may include some instances where more than one of these factors were applied in the same collision.

4.4.3.1 Trends

Figure 4.67: Collisions in Wokingham where CF101 and/or CF102 and/or CF103 were recorded (2014-2023)

Figure 4.67 shows annual collisions on Wokingham’s roads where at least one of the road surface CFs were recorded, with a three-year moving average trend line for road surface collisions. Figure 4.68 shows the trends for collisions where road surface CFs were recorded and for collisions where a police officer attended, indexed over a 2014 baseline for comparison.

Officer recorded collisions related to road surface conditions related contributory factors have remained in single digits with 5 recorded in 2023 compared with 13 in 2022. No fatal collisions were attributed to these contributory factors in this reporting period, since 2014. Moreover, 2023 also saw no serious injury collisions compared with 2 recorded in 2022. Thus, the 5 recorded collisions pertain to slight injury collisions, this marks a clear decline from the peak seen in 2022.

Considering 2014 as a baseline, the proportion of police attended collisions related to road surface conditions are higher than the number of recorded collisions attributed to these contributory factors.

Figure 4.68: Collision trends in Wokingham where CF101 and/or CF102 and/or CF103 were recorded compared to officer attended collision trends (2014-2023)

4.4.3.2 Comparisons

Figure 4.69 shows collisions on Wokingham’s roads where at least one of the road surface CFs was recorded, as a percentage of all officer attended collisions where any CF was recorded. Also shown are the national, regional and comparator authorities’ percentages.

The percentage of officer attended collisions in Wokingham related to road surface conditions is 6.3%. Wokingham’s rate is lower than the national rate (7.8%), the South East (8%), Bracknell Forest (8.2%), West Berkshire (9.1%), South Oxfordshire (11.7%) and many other comparator authorities. However, Wokingham has a higher rate compared to Reading and Slough (4.6% each), Windsor & Maidenhead (5.9%) and Surrey Heath (5.9%).

Figure 4.69: Percentage of collisions in Wokingham and comparators where CF101 and/or CF102 and/or CF103 were recorded (2019-2023)

4.4.4 Control Errors

This section examines collisions, by severity, where at least one of the CFs 408 Sudden braking, 409 Swerved and/or 410 Loss of Control was attributed. This may include some instances where more than one of these factors were applied in the same collision.

4.4.4.1 Trends

Figure 4.70: Collisions in Wokingham where CF408 and/or CF409 and/or CF410 were recorded (2014-2023)

Figure 4.70 shows annual collisions on Wokingham’s roads where at least one of the control error CFs were recorded, with a three-year moving average trend line for control error collisions. Figure 4.71 shows the trends for collisions where control error CFs were recorded and for collisions where a police officer attended, indexed over a 2014 baseline for comparison.

The total number of collisions attributed to control errors in Wokingham has steadily declined, from 48 in 2014 to 13 in 2023, a 73% reduction over the decade. Consistent with the previous year, no fatal collisions were attributed to these contributory factors. Both serious and slight injury collisions have reduced from 6 and 20 in 2022 to 2 and 11 in 2023 respectively. Overall, 2023 saw a 50% drop in collisions attributed to these contributory factors compared with 2022.

With 2014 as a baseline, the proportion of officer attended collisions pertaining to control errors in Wokingham is marginally higher than the number of collisions attributed to these contributory factors.

Figure 4.71: Collision trends in Wokingham where CF408 and/or CF409 and/or CF410 were recorded compared to officer attended collision trends (2014-2023)

4.4.4.2 Comparisons

Figure 4.72 shows collisions on Wokingham’s roads where at least one of the control error CFs was recorded, as a percentage of all officer attended collisions where any CF was recorded. Also shown are the national, regional and comparator authorities’ percentages.

Wokingham’s collisions attributed to CF408/CF409/CF410 represent a 16.5% rate. This is almost at par with the national, South East and Berkshire county rate. Wokingham recorded a lower rate than Bracknell Forest (19.2%), Windsor & Maidenhead (17.6%), West Berkshire (21.3%) and many other comparator authorities. On the other hand, Wokingham’s rate was higher than Reading (10%), Slough (11.5%) and Surrey Heath (11.4%).

Figure 4.72: Percentage of collisions in Wokingham and comparators where CF408 and/or CF409 and/or CF410 were recorded (2019-2023)

4.4.5 Unsafe Behaviour

This section examines collisions, by severity, where at least one of the CFs 601 Aggressive driving, and/or 602 Careless, reckless or in a hurry was attributed. This may include some instances where more than one of these factors were applied in the same collision.

4.4.5.1 Trends

Figure 4.73: Collisions in Wokingham where CF601 and/or CF602 were recorded (2014-2023)

Figure 4.73 shows annual collisions on Wokingham’s roads where at least one of the unsafe behaviour CFs were recorded, with a three-year moving average trend line for unsafe behaviour collisions. Figure 4.74 shows the trends for collisions where unsafe behaviour CFs were recorded and for collisions where a police officer attended, indexed over a 2014 baseline for comparison.

The total number of collisions attributed to unsafe behaviour in Wokingham have declined from 39 in 2014 to 24 in 2023, a 38% reduction over the decade. Despite the overall downward trend, the number of serious injury collisions attributed to these contributory factors have increased to 8 from 2 in 2022, the highest since 2014. On the other hand, slight injury collisions have reduced from 28 in 2022 to 16 in 2023. With 2014 as a baseline, the proportion of collisions attributed to CF601/CF602 are marginally higher than the officer attended collisions.

Figure 4.74: Collision trends in Wokingham where CF601 and/or CF602 were recorded compared to officer attended collision trends (2014-2023)

4.4.5.2 Comparisons

Figure 4.75 shows collisions on Wokingham’s roads where at least one of the unsafe behaviour CFs was recorded, as a percentage of all officer attended collisions where any CF was recorded. Also shown are the national, regional and comparator authorities’ percentages.

In Wokingham 20.6% of collisions were attributed to unsafe behaviour. This is slightly above the national statistic of 19.3% and almost identical to the South East (20.9%) and overall Berkshire county (21.6%) figures. Slough, South Oxfordshire, and Surrey Heath show significantly higher rates than Wokingham, over 5% higher. In contrast, Hart reported the lowest rate (9.5%) among comparator authorities.

Figure 4.75: Percentage of collisions in Wokingham and comparators where CF601 and/or CF602 were recorded (2019-2023)

4.4.6 Distraction

This section examines collisions, by severity, where at least one of the CFs 508 Driver using mobile phone, 509 Distraction in vehicle and/or 510 Distraction outside vehicle was attributed. This may include some instances where more than one of these factors were applied in the same collision.

4.4.6.1 Trends

Figure 4.76: Collisions in Wokingham where CF508 and/or CF509 and/or CF510 were recorded (2014-2023)

Figure 4.76 shows annual collisions on Wokingham’s roads where at least one of the distraction CFs were recorded, with a three-year moving average trend line for distraction collisions. Figure 4.77 shows the trends for collisions where distraction CFs were recorded and for collisions where a police officer attended, indexed over a 2014 baseline for comparison.

Collisions attributed to distraction have reduced from 16 in 2014 to 11 in 2023 in Wokingham. In line with the previous year, there were no fatal collisions related to distraction with only 2014 recording 1 fatal collision. Serious injury collisions have largely remained the same since 2020 with 4 recorded in 2023. Slight injury collisions have remained consistent with the previous year (7). Overall, the number of collisions related to distraction in Wokingham have remained below 15 since 2015.

Considering 2014 as a baseline, the proportion of collisions attributed to contributory factors pertaining to distraction (CF508/CF509) are slightly higher than officer attended collisions.

Figure 4.77: Collision trends in Wokingham where CF508 and/or CF509 and/or CF510 were recorded compared to officer attended collision trends (2014-2023)

4.4.6.2 Comparisons

Figure 4.78 shows collisions on Wokingham’s roads where at least one of the distraction CFs was recorded, as a percentage of all officer attended collisions where any CF was recorded. Also shown are the national, regional and comparator authorities’ percentages.

Although the overall recorded collisions related to distraction remain under 15 in Wokingham, it sees one of the highest rates (7.5%). Wokingham recorded a significantly higher rate than most authorities including the national statistic (4.9%), South East (5.8%) and the overall Berkshire county (5.1%). However, Wokingham recorded similar rates as Hart (7.4%) and Surrey Heath (7.3%).

Figure 4.78: Percentage of collisions in Wokingham and comparators where CF508 and/or CF509 and/or CF510 were recorded (2019-2023)

4.4.7 Medically Unfit

This section examines collisions, by severity, where at least one of the CFs 504 Uncorrected, defective eyesight and/or 505 Illness or disability, mental or physical was attributed. This may include some instances where more than one of these factors were applied in the same collision.

4.4.7.1 Trends

Figure 4.79: Collisions in Wokingham where CF504 and/or CF505 were recorded (2014-2023)

Figure 4.79 shows annual collisions on Wokingham’s roads where at least one of the medically unfit CFs were recorded, with a three-year moving average trend line for medically unfit collisions. Figure 4.80 shows the trends for collisions where medically unfit CFs were recorded and for collisions where a police officer attended, indexed over a 2014 baseline for comparison.

Collisions attributed to medically unfit drivers in 2023 were recorded as one of the highest since 2014 at 10 recorded collisions. This is significantly higher than the 4 collisions recorded in 2022. Only two fatal collisions related to these contributory factors were recorded since 2014 with 2023 seeing none. Moreover, slight injury collisions have doubled in 2023 (8) compared with 2022 (4). Overall, collisions attributed to the medically unfit category have seen a fluctuating trend in Wokingham. With 2014 as a baseline, the proportion of collisions attributed to being medically unfit is significantly higher than the police attended collisions. This is in line with the spike in collisions recorded in 2023.

Figure 4.80: Collision trends in Wokingham where CF504 and/or CF505 were recorded compared to officer attended collision trends (2014-2023)

4.4.7.2 Comparisons

Figure 4.81 shows collisions on Wokingham’s roads where at least one of the medically unfit CFs was recorded, as a percentage of all officer attended collisions where any CF was recorded. Also shown are the national, regional and comparator authorities’ percentages.

Wokingham recorded 4.9% of collisions attributed to medically unfit contributory factors. This rate is significantly higher than the national (2.6%), South East (3.2%) and overall Berkshire county (3.9%) rates. Wokingham recorded a higher rate than many other comparator authorities with only West Berkshire recording a higher rate at 5.9%.

Figure 4.81: Percentage of collisions in Wokingham and comparators where CF504 and/or CF505 were recorded (2019-2023)

4.4.8 Close Following

This section examines collisions, by severity, where the CF 308 Following too close was attributed.

4.4.8.1 Trends

Figure 4.82: Collisions in Wokingham where CF308 was recorded (2014-2023)

Figure 4.82 shows annual collisions on Wokingham’s roads where CF 308 was recorded, with a three-year moving average trend line for close following collisions. Figure 4.83 shows the trends for collisions where CF 308 was recorded and for collisions where a police officer attended, indexed over a 2014 baseline for comparison.

Officer recorded collisions related to close following in Wokingham saw no fatal collisions in this reporting period. In line with the previous year, there were no serious injury collisions while 4 slight injury collisions were recorded. Thus, the total number of collisions related to close following (4) solely pertain to slight injury collisions. Overall, Wokingham has seen a declining trend in these collisions with 2014 recording 18 collisions compared with 4 in 2023.

With 2014 as a baseline, the proportion of police attended collisions is higher than the recorded collisions pertaining to close following in Wokingham.

Figure 4.83: Collision trends in Wokingham where CF308 was recorded compared to officer attended collision trends (2014-2023)

4.4.8.2 Comparisons

Figure 4.84 shows collisions on Wokingham’s roads where the close following CF was recorded, as a percentage of all officer attended collisions where any CF was recorded. Also shown are the national, regional and comparator authorities’ percentages.

Wokingham recorded 3.2% of collisions attributed to close following, the second lowest rate among the comparator authorities with Reading recording the lowest (3%). Wokingham recorded a lower rate than the national (4.1%), South East (4.6%) and Berkshire county (4.2%) figures. The authority also recorded a lower rate than many other authorities including Bracknell Forest (4.1%), Windsor & Maidenhead (4.4%), West Berkshire (4.6%), Hart (4.3%), among others. Overall, Slough and South Cambridgeshire recorded the highest rates in this category with 5.5% and 7% respectively.

Figure 4.84: Percentage of collisions in Wokingham and comparators where CF308 was recorded (2019-2023)

5 Appendices

5.1 Analytical Techniques

5.1.1 Resident road users

Casualty and driver postcodes in STATS19 make it possible to identify where casualties from Wokingham reside. Thematic maps are used to illustrate the number of casualties per head of population from each small area in Wokingham. Areas on maps are progressively coloured, indicating annual average rates relative to the population of that area.

The geographical units used for this analysis are based on similar populations, which enables meaningful comparative analysis within and between authorities. In England and Wales the areas typically used are super output areas as defined by the Office for National Statistics (ONS). Where appropriate, lower level small areas are employed: for England and Wales these are lower layer super output areas (LSOAs) of around 1,600 residents on average. In some cases, larger groupings are used, as is the case in MAST Online: for England and Wales these are middle layer super output areas (MSOAs) with an average of nearly 8,000 residents each.

MAST Online has been used to determine the casualty figures for Wokingham’s residents injured in road collisions anywhere in Britain. Using national population figures (by age where appropriate), casualty and driver/rider involvement rates per head of population have been calculated. Charts have been devised which compare the local rates with the equivalent figures for Great Britain and for selected comparators. Trend analysis examines resident road user collision involvement over time and by severity, and additional trends are explored depending on road user type.

Where appropriate, socio - demographic analysis is conducted to provide insight into the backgrounds of people from Wokingham who are involved in collisions, either as casualties or motor vehicle users. Socio - demographic profiling examines age breakdowns, and for some road user groups includes analysis using Acorn segmentation, deprivation and/or rurality. More information on Acorn is provided later in this section.

5.1.1.1 Acorn

Insight into the lifestyles of Wokingham resident road casualties and motor vehicle users can be provided through socio demographic analysis. Agilysis Acorn profiling uses CACI’s Acorn cross - channel classification system², which is assigned uniquely for each casualty and vehicle user based on individual postcodes in STATS19 records. Typically, nearly 85% of casualty and driver STATS19 records can be matched to Acorn Types, so residency analysis is based on about five out of six Wokingham residents involved in reported injury collisions.

Acorn is intended to provide an accurate and comprehensive view of citizens and their needs by describing them in terms of demographics, lifestyle, culture and behaviour. By analysing data from hundreds of different sources, and segmenting UK postcodes by common characteristics, Acorn provides a detailed understanding of the various types of people who make up customer bases and catchment areas.

Acorn presently classifies the community represented by each UK postcode into one of 7 categories, 22 Groups and 65 Types. Each Group embraces between 3 and 6 Types. A complete list of Acorn Types is provided in 5.2.1 whilst profiles and distribution for the Acorn Types identified in this Area Profile as providing insight on Wokingham’s residents are detailed in 5.2.2.

This profile displays Acorn analysis as dual series column charts, to facilitate quick and easy insight into residents and relative risk. In these charts, the wider background columns denote the absolute number of Wokingham resident casualties or drivers in each Acorn Type or Group, corresponding to the value axis to the left of the chart. The columns in the foreground provide an index for each Acorn Type or Group. These indices are 100 based, where a value of 100 indicates the number of casualties or drivers shown by the corresponding background column is exactly in proportion to the population of communities in Wokingham where that Type or Group predominates. Indices over 100 indicate over representation of that Type among casualties or motor vehicle users relative to the population: for example, a value of 200 would signify that people resident in communities of that Type were involved in collisions at twice the expected rate. Conversely, indices below 100 suggest under representation, so an index of 50 would imply half the expected rate. Inevitably, index values become less significant as numbers of involved residents decrease, because increased random fluctuations tend to decrease levels of confidence.

Where appropriate, additional Acorn profiles for drivers may be provided with indices based on CACI’s estimate of the average annual mileage typically driven by each Group or Type. These profiles help to identify situations where exposure to road risk for some communities is out of proportion to their population due to unusually high or low levels of vehicle use.

5.1.1.2 Deprivation

Deprivation levels are examined using UK Index of Multiple Deprivation (IMD) values. IMD is calculated by the Office for National Statistics (ONS), the Scottish Government and the Welsh Government, and uses a range of economic, social and housing data to generate a single deprivation score for each small area in the country. This profile uses deciles, which are ten groups of equal frequency ranging from the 10% most deprived areas to the 10% least deprived. It should be remembered that indices of multiple deprivation include income, employment, health, education, access to services and living environment and are not merely about relative wealth.

In order to interpret deprivation more accurately at local level, this profile includes indexed IMD charts. Indices in these charts show risk relative to the predominance of each IMD decile in the population of Wokingham and can be interpreted in the same way as indices on Acorn charts as explained in the preceding section.

5.1.2 Collisions

MAST Online has been used to determine average annual road injury collision levels for Wokingham and relevant comparator areas. Dividing this annual rate by road length in each area generates an annual collision rate per kilometre of road, which allows direct comparisons to be made between authorities. Road length data have been taken from central government figures, and where required have been calculated separately for different road classes and environments. Charts have been devised which compare local rates with the equivalent figures for Great Britain and comparator highway authorities. District authorities cannot be included, as road length data is only available at highway authority level.

Trend analysis examines numbers of collisions on Wokingham’s roads over time and by severity, with additional trends explored, sometimes classified by kinds of road network. In order to determine the distribution of collisions within Wokingham, maps show the number of collisions in each small area, divided by the total road length (in kilometres) within that small area

5.1.2.1 Contrasting kinds of road network

Road networks vary considerably across the country. It is often useful to analyse and compare collision rates between authorities on certain kinds of road. Ideally such comparisons would take traffic flow into account, so collision rates per vehicle distance travelled could be calculated. However, traffic flow data for different kinds of road network is not available, so this profile can only calculate collision rates using road length. Road length data by kind of road network has been taken from DfT figures where possible. As with all collisions, trend charts are provided in addition to rate comparison charts.

5.1.2.1.1 Rurality

Within Wokingham, the road network has been split into either Urban and Rural or SRN and local roads. These types have been analysed separately under Sections 4.2 and 4.3 in the Area Profile. Routes were split into urban and rural in accordance with the ONS rural/urban classifications by LSOA (Lower Layer Super Output Area). Note that the term ‘urban’ both in the ONS classification and in this report denotes an area which forms part of a contiguous conurbation with a total population of more than 10,000.

5.1.3 Comparators

In order to put the figures for Wokingham into context, comparisons with other areas have been made.

• Great Britain
• South East
• Berkshire
• Bracknell Forest
• Reading
• Slough
• Windsor & Maidenhead
• West Berkshire
• Hart
• South Cambridgeshire
• South Oxfordshire
• Surrey Heath

5.1.4 Collision Dynamics

Many collisions entail some (or all) of the vehicles involved coming into direct conflict with each other. To maximise insight into such incidents, Agilysis categorises all collisions by their Collision Dynamic, based on the nature of inter-vehicle conflicts they comprised. This assessment is based on the directions in which vehicles were travelling, and the points of impact at which they first made contact.

The Collision Dynamic categories (arranged in the hierarchical order in which they are applied) are as follows:

• No Conflict
• Head On
• Shunt
• Side Impact
• Other Conflict
• Conflict Unknown

A collision is defined as No Conflict if: it only involved one non-parked vehicle OR all involved non-parked vehicles had no impact OR all bar one of the involved non-parked vehicles had no impact.

A collision is defined as Head On if: any involved non-parked vehicle which had a front impact was travelling in a direction which differed by between 135⁰ and 225⁰ from the path of another involved non-parked vehicle which had a non-rear impact.

A collision is defined as a Shunt if: the collision was not a Head On AND; any involved non-parked vehicle which had a rear impact was travelling in a direction which only differed by up to 45⁰ either way from the path of another involved non-parked vehicle which had a non-rear impact.

A collision is defined as a Side Impact if: the collision was not a Head On or Shunt AND; any involved non-parked vehicle which had a side impact was travelling in a direction which differed by 45⁰ to 135⁰ either way from the path of another involved non-parked vehicle which had a non-rear impact.

A collision is defined as Other Conflict if: the collision was not a Head On, Shunt or Side Impact AND; at least two involved non-parked vehicles with known directions of travel had any impact.

A collision is defined as Conflict Unknown if: the collision was not a No Impact, Head On, Shunt, Side Impact or Other Impact (NOTE: this includes cases where data for first point of impact and/or direction of travel was missing or unknown, in a manner which precluded the application of any other definition).

5.1.4.1 Limitations

Certain vagaries inherent in STATS19 recording may confound this categorisation in some circumstances. These, along with the available mitigations, are listed below.

1. Collisions involving more than two vehicles may comprise multiple types of conflict within the same incident, which STATS19 data by its nature cannot always distinguish with certainty. Collision Dynamics defines the primary dynamic of such collisions by using a ‘hierarchy’ of conflicts which gives certain types of conflict precedence over others.
   • In some circumstances it may be preferable to mitigate this uncertainty by analysing two vehicle collisions only.
2. Recorded first points of impact may refer to contact with pedestrians or other objects, rather than with other vehicles. From STATS19 data, it is not always possible to ascertain with certainty to what counterpart any given impact refers.
   • For this reason, in some circumstances it may be preferable to mitigate this uncertainty by analysing collisions separately where injured pedestrians and/or impact with other objects were recorded.

5.1.5 Driver Actions

The derivation of ‘Driver Action’ from STATS19 data is carried out using a combination of two data collection fields, ‘Vehicle Manoeuvres’ and ‘Vehicle leaving carriageway’. The definitions of driver action used in this report are as follows:

Driver Action	Definition
Involved Slow Manoeuvre	Vehicle was stopping, stationary or moving off
Involved Right Turn	Vehicle was turning right, or waiting to do so
Involved Left Turn	Vehicle was turning left, or waiting to do so
Involved Runoff	Combination of ‘Involved Runoff Other’ and ‘Involved Runoff Nearside’
Involved Runoff Other	Vehicle left carriageway in any other fashion
Involved Runoff Nearside	Vehicle left carriageway to the nearside (whether rebounded or not)

5.1.6 Contributory factors

Police officers who attended the scene of an injury collision may choose to record certain contributory factors (CFs) which in the officer’s view were likely to be related to the incident. Up to six CFs can be recorded for each collision. CFs reflect the officer’s opinion at the time of reporting, but may not be the result of extensive investigation. Consequently, CFs should be regarded only as a general guide for identifying factors as possible concerns.

In all CF analysis, only collisions which were both attended by a police officer and for which at least one factor was recorded are included. Since multiple CFs can be recorded for a single collision, the same incidents may be included in analysis of more than one CF.

In CF analysis specifically related to pedestrians, only CFs directly assigned either to pedestrian casualties or to drivers and riders who first hit a pedestrian casualty are analysed. For ease of analysis and interpretation Agilysis often organises CFs into groupings. A complete list of all CFs and their groupings may be found in section 5.4.

5.2 Acorn

This section provides information on all of the Acorn Types and more detailed analysis of the specific Types identified as being of interest to Wokingham. More information on what Acorn is can be found in section 5.1.1.1.

5.2.1 Complete list of Acorn Types

Below is a complete list of all the Acorn Types, with descriptions, shown in the Acorn Group to which they belong.

A - Exclusive Addresses
A1	High-flyers in luxury apartments and townhouses ###################
A2	Wealthy, gentrified areas #########################################
A3	Asset-rich, out-of-town older families ############################

B - Flourishing Capital
B4	High-end professionals in city flats ##############################
B5	Successful young families in smart urban areas ####################

C - Upmarket Families
C6	Executives in expensive suburban houses ###########################
C7	Prosperous families in green-belt areas with substantial homes ####

D - Commuter-Belt Wealth
D8	Affluent, older homeowners ########################################
D9	Families and couples in comfortable homes #########################
D10	Well-off families in larger semis #################################
D11	Mature and moneyed out-of-towners #################################
D12	Well-to-do empty nesters in detached houses #######################

E - Prosperous Professionals
E13	Families in leafy suburbs #########################################
E14	Upmarket young families in terraces ###############################
E15	Educated professionals renting flats ##############################

F - Mature Success
F16	Families and couples in detached houses ###########################
F17	Older, rural empty nesters and couples ############################
F18	Countryside retirees in spacious houses ###########################
F19	Sophisticated couples living comfortably in detached homes ########

G - Settled Suburbia
G20	Mixed lifestages in semi-detached homes ###########################
G21	Mid-life suburban living ##########################################

H - Metropolitan Surroundings
H22	Younger families and sharers in city terraces #####################
H23	Culturally diverse suburban families ##############################

I - Up-and-Coming Urbanites
I24	Young professionals renting city flats ############################
I25	Privately renting students and house sharers ######################
I26	Younger couples and singles in flats ##############################

J - Aspiring Communities
J27	Professional families and couples in suburban, owner-occupied areas
J28	Families and couples in terraces ##################################

K - Semi-Rural Maturity
K29	Senior home-owning couples ########################################
K30	Empty nesters in owner-occupied detached homes ####################
K31	Comfortable, home-owning families and empty nesters ###############
K32	Older comfortable families and couples in detached, rural properties
K33	Retirees in semi-detached and detached properties #################

L - Traditional Homeowners
L34	Older owner-occupier households in semis ##########################
L35	Settled communities, semi-detached properties #####################

M - Family Renters
M36	Cost-conscious families in terraces ###############################
M37	Restricted residents, socially renting ############################

N - Urban Diversity
N38	Younger families, multi-occupancy and rented households ###########
N39	Diverse communities in smaller semis and terraces #################
N40	Young families, limited means in terraced metropolitan areas ######

O - Stable Seniors
O41	Living on modest means in terraces ################################
O42	Retired homeowners in semi-detached and detached houses ###########
O43	Older couples living in detached houses, rural communities ########

P - Tenant Living
P44	Urban, aspiring flat dwellers #####################################
P45	Privately renting squeezed professionals in flats #################
P46	Sharers and students in private rentals ###########################
P47	Singles and couples in rented flats ###############################

Q - Limited Budgets
Q48	Routine occupations, socially renting families in semis ###########
Q49	Socially renting single adult households ##########################

R - Hard-Up Households
R50	Single-parent families in terraced housing ########################
R51	Older, single-person households on the outskirts of town ##########
R52	Socially renting families in terraces #############################

S - Cash-Strapped Families
S53	Diverse families and sharers in flats #############################
S54	Young families in socially rented semis ###########################
S55	Families in low-value terraced housing ############################
S56	Diverse young families in rented terraces and flats ###############

T - Constrained Pensioners
T57	Older renters in flats and tenements ##############################
T58	Poorer pensioners in semis ########################################

U - Challenging Circumstances
U59	Students and sharers in multi-occupancy flats #####################
U60	Socially renting single adult households in flats #################
U61	Socially rented flats, singles and pensioners #####################

V - Not Private Households
V62	Students in halls of residence ####################################
V63	Active communal populations #######################################
V64	Inactive communal populations #####################################
V65	Non residential postcodes #########################################

5.2.2 Profile and distribution for selected Acorn Types

The table below shows Acorn Types identified by socio - demographic profiling of the resident casualties and resident drivers sections of the report, with some of the main characteristics of these Types. These can be used to create a picture of the target audience in terms of economic and educational position; family life; and transport preferences including mileage and car ownership. This information is invaluable for understanding target audiences and knowing how to communicate with them.

C6	D11	D8	E13	E14
Executives in expensive suburban houses	Mature and moneyed out-of-towners	Affluent, older homeowners	Families in leafy suburbs	Upmarket young families in terraces
Executives in expensive suburban houses	Mature and moneyed out-of-towners	Affluent, older homeowners	Families in leafy suburbs	Upmarket young families in terraces

G20	I26	J27	J28	K29
Mixed lifestages in semi-detached homes	Younger couples and singles in flats	Professional families and couples in suburban, owner-occupied areas	Families and couples in terraces	Senior home-owning couples
Mixed lifestages in semi-detached homes	Younger couples and singles in flats	Professional families and couples in suburban, owner-occupied areas	Families and couples in terraces	Senior-home owning couples

M37	P45	Q49
Restricted residents, socially renting	Privately renting squeezed professionals in flats	Socially renting single adult households
Restricted residents, socially renting	Privately renting squeezed professionals in flats	Socially renting single adults households

5.3 Data Tables

All Casualties - Wokingham Residents (3.1.1)

Year	Fatal	Serious	Slight	Total
2014	4	41	318	363
2015	2	42	319	363
2016	3	51	275	329
2017	5	37	216	258
2018	5	31	226	262
2019	1	30	204	235
2020	2	25	167	194
2021	4	39	191	234
2022	4	36	217	257
2023	3	37	201	241
Total	33	369	2334	2736

Motor Vehicle Drivers Involved in Injury Collisions - Wokingham Residents (3.2.1)

Year	Fatal	Serious	Slight	Total
2014	4	49	345	398
2015	5	41	359	405
2016	5	49	297	351
2017	1	35	251	287
2018	8	37	232	277
2019	2	31	212	245
2020	5	24	176	205
2021	5	37	195	237
2022	8	39	221	268
2023	1	45	189	235
Total	44	387	2477	2908

Young Adult Drivers Involved in Injury Collisions - Wokingham Residents (3.2.3)

Year	Fatal	Serious	Slight	Total
2014	0	7	53	60
2015	0	3	55	58
2016	0	12	60	72
2017	0	7	48	55
2018	0	6	35	41
2019	0	6	34	40
2020	1	2	23	26
2021	1	6	24	31
2022	0	4	26	30
2023	0	6	24	30
Total	2	59	382	443

All Collisions - Wokingham Roads (4.1)

Year	Fatal	Serious	Slight	Total
2014	3	44	218	265
2015	1	37	226	264
2016	3	39	204	246
2017	4	39	168	211
2018	3	35	164	202
2019	0	22	146	168
2020	3	28	124	155
2021	3	27	156	186
2022	1	23	159	183
2023	2	33	135	170
Total	23	327	1700	2050

Urban Collisions - Wokingham Roads (4.2)

Year	Fatal	Serious	Slight	Total
2014	1	24	106	131
2015	1	20	127	148
2016	2	17	101	120
2017	2	20	99	121
2018	2	17	89	108
2019	0	6	87	93
2020	1	10	64	75
2021	1	18	79	98
2022	1	12	91	104
2023	2	16	72	90
Total	13	160	915	1088

Rural Collisions - Wokingham Roads (4.3)

Year	Fatal	Serious	Slight	Total
2014	2	20	112	134
2015	0	17	99	116
2016	1	22	103	126
2017	2	19	69	90
2018	1	18	75	94
2019	0	16	59	75
2020	2	18	60	80
2021	2	9	77	88
2022	0	11	68	79
2023	0	17	63	80
Total	10	167	785	962

Collisions by Hour of the Day (Weekdays) - Wokingham Roads (4.1.1.5)

Time of Day	Fatal	Serious	Slight	Total
Midnight	1	2	3	6
1am	0	0	2	2
2am	0	0	3	3
3am	0	1	2	3
4am	0	0	3	3
5am	0	0	2	2
6am	1	1	15	17
7am	1	6	37	44
8am	0	11	65	76
9am	0	4	27	31
10am	0	3	27	30
11am	1	3	13	17
Noon	1	6	23	30
1pm	0	7	36	43
2pm	1	7	27	35
3pm	0	4	53	57
4pm	0	9	52	61
5pm	0	5	62	67
6pm	0	9	52	61
7pm	0	8	24	32
8pm	1	3	16	20
9pm	0	2	14	16
10pm	1	3	10	14
11pm	0	2	0	2
Total	8	96	568	672

Collisions by Hour of the Day (Weekends) - Wokingham Roads (4.1.1.5)

Time of Day	Fatal	Serious	Slight	Total
Midnight	0	1	3	4
1am	0	0	1	1
2am	0	0	0	0
3am	0	1	0	1
4am	0	1	2	3
5am	0	0	0	0
6am	0	0	1	1
7am	0	1	6	7
8am	0	1	3	4
9am	0	1	8	9
10am	0	3	11	14
11am	0	4	14	18
Noon	0	2	13	15
1pm	0	2	12	14
2pm	0	5	7	12
3pm	0	3	9	12
4pm	0	1	9	10
5pm	1	2	15	18
6pm	0	2	6	8
7pm	0	1	8	9
8pm	0	1	7	8
9pm	0	1	8	9
10pm	0	1	5	6
11pm	0	3	4	7
Total	1	37	152	190

Collisions Involving Factors 306 and/or 307 (Speed Related) - Wokingham Roads (4.4.1)

Year	Fatal	Serious	Slight	Total
2014	0	1	18	19
2015	0	5	19	24
2016	0	1	16	17
2017	2	4	10	16
2018	0	1	9	10
2019	0	1	8	9
2020	1	0	14	15
2021	0	3	8	11
2022	0	2	12	14
2023	0	4	7	11
Total	3	22	121	146

Collisions Involving Factors 501 and/or 502 (Impairment Related) - Wokingham Roads (4.4.2)

Year	Fatal	Serious	Slight	Total
2014	0	3	9	12
2015	0	1	6	7
2016	0	0	5	5
2017	1	2	7	10
2018	0	3	9	12
2019	0	4	5	9
2020	1	5	8	14
2021	1	5	9	15
2022	0	2	12	14
2023	0	3	4	7
Total	3	28	74	105

Collisions Involving Factors 101 and/or 102 and/or 103 (Road Surface Related) - Wokingham Roads (4.4.3)

Year	Fatal	Serious	Slight	Total
2014	0	2	19	21
2015	0	5	18	23
2016	0	2	15	17
2017	0	0	11	11
2018	0	0	9	9
2019	0	1	7	8
2020	0	1	5	6
2021	0	0	7	7
2022	0	2	11	13
2023	0	0	5	5
Total	0	13	107	120

Collisions Involving Factors 408 and/or 409 and/or 410 (Control Error Related) - Wokingham Roads (4.4.4)

Year	Fatal	Serious	Slight	Total
2014	1	7	40	48
2015	0	7	33	40
2016	1	6	34	41
2017	2	2	22	26
2018	0	5	20	25
2019	0	5	14	19
2020	1	8	11	20
2021	1	2	21	24
2022	0	6	20	26
2023	0	2	11	13
Total	6	50	226	282

Collisions Involving Factors 601 and/or 602 (Unsafe Behaviour Related) - Wokingham Roads (4.4.5)

Year	Fatal	Serious	Slight	Total
2014	0	6	33	39
2015	0	7	29	36
2016	0	8	28	36
2017	1	6	22	29
2018	0	7	20	27
2019	0	5	17	22
2020	1	5	15	21
2021	1	6	23	30
2022	0	2	28	30
2023	0	8	16	24
Total	3	60	231	294

Collisions Involving Factors 508 and/or 509 and/or 510 (Distraction Related) - Wokingham Roads (4.4.6)

Year	Fatal	Serious	Slight	Total
2014	1	3	12	16
2015	0	3	12	15
2016	0	1	13	14
2017	0	1	8	9
2018	0	1	10	11
2019	0	1	6	7
2020	0	2	5	7
2021	0	2	9	11
2022	0	3	7	10
2023	0	4	7	11
Total	1	21	89	111

Collisions Involving Factors 504 and/or 505 (Medically Unfit) - Wokingham Roads (4.4.7)

Year	Fatal	Serious	Slight	Total
2014	1	1	5	7
2015	0	1	4	5
2016	1	3	7	11
2017	0	2	5	7
2018	0	1	5	6
2019	0	3	3	6
2020	0	0	3	3
2021	0	1	6	7
2022	0	0	4	4
2023	0	2	8	10
Total	2	14	50	66

Collisions Involving Factors 308 (Close Following Related) - Wokingham Roads (4.4.8)

Year	Fatal	Serious	Slight	Total
2014	0	1	17	18
2015	0	0	17	17
2016	0	1	11	12
2017	0	1	6	7
2018	0	1	6	7
2019	0	2	4	6
2020	0	1	3	4
2021	0	1	2	3
2022	0	0	3	3
2023	0	0	4	4
Total	0	8	73	81

5.4 Contributory Factor Groupings

In order to facilitate insight into specific road safety issues, Area Profile documents can include sections which analyse collisions on a network and/or resident casualties/drivers on the basis of contributory factors assigned by attending police officers. While conducting this analysis, it has often been found useful to group together certain factors which reflect broadly similar aspects of road risk. This table identifies various groups of factors which Agilysis has used in the past for this purpose. Clients may wish to devise alternative approaches.

Injudicious Action
Traffic Contraventions	Disobeyed automatic traffic signal	Disobeyed double white lines	Disobeyed 'Give way' or 'Stop' signs or markings	Disobeyed pedestrian crossing facility	Illegal turn or direction of travel
Driver Errors or Reactions
Manoeuvre Errors	Poor turn or manoeuvre	Failed to signal or misleading signal	Passing too close to cyclist, horse rider or pedestrian
Driver Impairment or Distraction
Substance Impairments	Impaired by alcohol	Impaired by drugs (illicit or medicinal)
Behaviour or Inexperience
Nervous Behaviour	Nervous, uncertain or panic	Learner or inexperienced driver/rider	Inexperience of driving on the left	Unfamiliar with model of vehicle
Speed Choices
Exceeding speed limit	Travelling too fast for conditions
Control Errors
Sudden braking	Swerved	Loss of control	Observation Error	Failed to look properly	Failed to judge other person's path or speed
Distraction
Driver using mobile phone	Distraction in vehicle	Distraction outside vehicle	Health Impairments	Uncorrected, defective eyesight	Illness or disability, mental or physical
Unsafe Behaviour
Aggressive driving	Careless, reckless or in a hurry
Defective steering or suspension
Defective or missing mirrors	Overloaded or poorly loaded vehicle or trailer	Road Surface	Poor or defective road surface	Deposit on road (e.g. oil, mud, chippings)	Slippery road (due to weather)
Affected Vision	Stationary or parked vehicle(s)	Vegetation	Road layout (e.g. bend, winding road, hill crest)	Buildings, road signs, street furniture	Dazzling headlights
Dazzling sun	Rain, sleet, snow or fog	Spray from other vehicles	Visor or windscreen dirty or scratched	Vehicle blind spot
Close Following
Following too close
Junction Errors
Junction overshoot	Junction restart (moving off at junction)
Fatigue Impairment
Fatigue
Pedal Cycle Behaviour
Vehicle travelling along pavement	Cyclist entering road from pavement	Not displaying lights at night or in poor visibility	Cyclist wearing dark clothing at night	Pedestrian Behaviour	Crossing road masked by stationary or parked vehicle
Failed to look properly	Failed to judge vehicle's path or speed	Wrong use of pedestrian crossing facility	Dangerous action in carriageway (e.g. playing)	Careless, reckless or in a hurry	Impaired by alcohol
Impaired by drugs (illicit or medicinal)	Pedestrian wearing dark clothing at night	Disability or illness, mental or physical
Other
Vehicle Defects	Tyres illegal, defective or under-inflated	Defective lights or indicators	Defective brakes

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1. For further information, go to https://www.gov.uk/government/publications/road-accidents-and-safety-statistics-guidance↩︎

2. https://acorn.caci.co.uk/how-acorn-works/.html↩︎