1 Executive Summary

This Area Profile presents a systematic overview of resident and road risk in Wokingham. The insight derived from this report can inform the design and development of road safety interventions, underpin local road safety strategies and support local authorities and their stakeholders to secure safer roads and healthier communities across the area. Area Profiles are compiled using analytical techniques which, not only compare long term trends but also use rate-based measures derived from a range of datasets.

Wokingham’s overall resident casualty figure has decreased gradually over the last ten years, particularly since 2015. Wokingham’s resident casualty rate was 38% lower than the national rate and 40% lower than the South- East regional rate. Resident casualty numbers have seen a steady downward trend since 2014. Half of Wokingham’s resident casualties are injured outside of the borough. Both the highest and over-represented number of Wokingham’s casualties are from mosaic type I36; stable families with children, renting higher value homes from social landlords. Wokingham’s resident casualties are most likely to come from the least deprived 10% of the population, however communities in the more deprived 40% and the less deprived 40% are over-represented as resident casualties, despite having lower numbers of resident casualties. Resident casualties have been broken down into the following cohorts:

  1. Resident child casualty numbers from Wokingham have seen a fluctuating but downward trend overall over the past decade, and despite the pandemic, numbers were virtually the same in 2020 and 2021. There has been one resident child fatality in the last decade, in 2020. Just over three-quarters of Wokingham’s resident child casualties were injured in Wokingham.
  2. Resident pedestrian casualty numbers rose steadily at the start of the decade, to a peak in 2014, and since then there has been a steady downward trend. However after a dramatic decrease in numbers in 2017, resident pedestrian casualty numbers have since plateaued at this level with minor fluctuation. Sixty-nine percent of Wokingham’s resident pedestrian casualties were injured in Wokingham.
  3. Resident pedal cyclist casualty numbers have decreased consistently over the last decade from their peak in 2012, with the only notable rise in numbers occurring in 2016. Resident pedal cyclist casualties did not decrease in the pandemic year of 2020 from previous years, as was the case with resident casualties overall. Sixty-four percent of Wokingham’s resident pedal cyclist casualties were injured in Wokingham.

The number of collision-involved resident drivers from Wokingham has decreased over the last ten years, but more so since 2015. The rate per 100,000 population was 45% below the national rate and 40% below the South-East regional rate. The rate for Wokingham was lower than that of Windsor and Maidenhead, Reading, Bracknell Forest and West Berkshire. It was significantly lower than that of Slough. Most of the collision involved drivers are of working age (17-65) and are more likely to come from communities of mosaic type B07, high achieving families living fast track lives, advancing careers, finances and their school-aged kid’s development. Collision-involved drivers of this mosaic type are under-represented relative to their population in Wokingham however, whereas Type G26, affluent families with growing children living in upmarket housing in city environs; Type G27, well-qualified older singles with incomes from successful professional careers in good quality housing; and Type H33, young families and singles setting up home in modern developments that are popular with their peers, are all over-represented relative to their populations in addition to featuring frequently as collision-involved resident drivers. Although they represent lower numbers of collision-involved resident drivers in Wokingham, drivers from communities of stable families with children, renting higher value homes from social landlords (Type I36) are significantly over-represented in collision involvement relative to their population.

An extra section has been added to this Area Profile to specifically look at young drivers (aged 17 to 24). There has been a steady downward trend in resident collision-involved younger drivers over the last decade, particularly from 2016 onwards. The rate per 100,000 population was 18% below the national rate and 27% below the South-East regional rate. Forty-four percent of Wokingham’s resident young drivers were involved in collisions in Wokingham.

The number of resident motorcycle riders involved in collisions has fluctuated notably over the last decade, with a peak in 2016. Half of these resident collision-involved motorcycle riders were involved in collisions on Wokingham’s roads. Wokingham’s resident motorcycle collision involvement rate was 43% below the national rate and 46% below the South-East regional rate.

As well as reviewing the risk to residents, this Area Profile has considered collision rates on the local road network. The number of collisions on Wokingham’s road network has decreased steadily over the last decade. However in 2021, numbers rose again slightly following the reduction in 2020 that coincided with pandemic-related travel. The collision rate per 100km of road on Wokingham’s road network was 16% below the national rate and 35% below the South-East regional rate. Wokingham’s collision rate was below the rate for Berkshire as a whole and was lower than all comparator authorities in Berkshire except West Berkshire.

Collision numbers on urban roads in Wokingham saw a downward trend over the last decade from 2015 onwards. However as with all roads, numbers rose again in 2021 following the reduction in 2020 that coincided with pandemic-related travel restrictions. This rise in 2021 brought collisions numbers back in line with pre-pandemic levels. The collision rate between 2017 and 2021 was less than half of both the national and South-East regional urban collision rates. Wokingham’s urban collision rate was 39% lower than the overall rate for Berkshire on urban roads. Analysis of the collision dynamics at the time of the collision show that 28% of collisions on urban roads involved no vehicle-to-vehicle impact. Where multiple vehicles were involved, 18% involved rear vehicle impacts; 9% involved side impacts; and 12% involved head-on impacts. The driver actions at the time of the collision show that the highest percentage of collisions on urban roads were when making a right turn, followed by a slow manoeuvre such as stopping.

Collision numbers on rural roads in Wokingham have been steadily falling over the last decade since 2014, Despite pandemic-related measures, the number of collisions has started to increase marginally year-on-year since 2019. The collision rate between 2017 and 2021 was 65% higher than the national rate, but 13% lower the South-East regional rate. Wokingham’s collision rate on rural roads was 12% higher than the overall rate for Berkshire. As with the rate for collisions on all roads, Wokingham’s collision rate on rural roads was the second lowest in Berkshire amongst comparator authorities, after West Berkshire. Analysis of the collision dynamics at the time of the collision show that almost a third of collisions on rural roads involved no vehicle-to-vehicle impact. Where multiple vehicles were involved, 21% involved rear vehicle impacts; 7% involved side impacts; and 9% involved head-on impacts. The driver actions at the time of the collision show that the highest percentage of collisions on urban roads involved run-off incidents, particularly run-offs to the nearside of the carriageway.

The factors that contribute towards collisions on Wokingham’s road network (CFs) are also measured. It is entirely possible that combination of factors led to a collision taking place, and the results do not produce figures that represent the number of incidents ‘caused’ by a single factor. Speeding, as measured by the factors ‘exceeding the speed limit’ or ‘travelling too fast for conditions’, has decreased gradually on Wokingham’s roads (with 2015 and 2020 as exceptions to the overall trend). Together, these factors still play a role in just under 9% of officer attended collisions in Wokingham, a percentage that is below the national and South-East percentages for speeding contributory factors.

The number of impairment CFs attributed, ‘impaired by alcohol’ or ‘impaired by drugs (illicit or medicinal)’, has fluctuated significantly over the last decade, appearing to show a downward trend up until 2016, after which point numbers have increased to levels seen at the start of the decade. Impairment CFs were attributed in 8.6% of officer attended collisions on Wokingham’s roads, a percentage that is notably higher than the national and South-East Regional percentages. Road surface contributory factors show a consistently declining trend in Wokingham, with at least one of these factor only attributed in 5.9% of Wokingham’s officer attended collisions. This is below the national and South-East regional percentages. Control error contributory factors also show a declining trend across the decade, however these CFs attributed in 16.4% of officer attended collisions, broadly in line with the national and South-East percentages. Whilst the number of unsafe behaviour contributory factors attributed, ‘aggressive driving’ or ‘careless, reckless or in a hurry’, has decreased moderately since the start of decade; 18.6% of officer-attended collisions were attributed an unsafe behaviour CF. This is higher than the national percentage but in line with the South-East regional percentage. Close following contributory factors have decreased dramatically, in particular after 2015, and were only allocated in 3.9% of officer attended collisions, a slightly lower proportion than those seen at the national and South-East regional levels. Medically unfit contributory factor numbers have fluctuated overall over the last decade, despite being only marginally higher in 2021 than they were in 2012. 4.2% of officer-attended collisions received a medically unfit CF, higher than both the national and South-East regional percentages. Distraction contributory factor numbers have also fluctuated over the past decade, but to a lesser extent, and were attributed to 6.5% of collisions attended by an officer, a markedly higher proportion than those seen nationally and in the South East Region.

In summary the road safety risk rates for Wokingham residents are, for the most part, lower than the national and regional norms and have decreased over the last ten years. Resident drivers have a lower risk rate than most of the comparator authorities.

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 Mosaic 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 Road Safety Analysis (RSA) 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 the Analytical Techniques section on page 5.1. 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, constabularies 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 Mosaic Types and the profile and distribution of specific Mosaic 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 STATS 19 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 Road Safety Analysis by the Department for Transport for publication in MAST Online over the five-year period between 2017 and 2021 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 2017 and 2021 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.

Between 2017 and 2021 Wokingham had a resident casualty rate of 138 casualties per year per 100,000 population.

Figure 3.1: Annual average Wokingham resident casualties per 100,000 population (2017 - 2021)

Annual average Wokingham resident casualties per 100,000 population (2017 - 2021)

3.1.1.2 Comparisons

Wokingham’s resident casualty rate was 38% lower than the national rate, 40% lower than the regional rate, and 20% below the rate for Berkshire as a whole. Within Berkshire, Wokingham ’s resident casualty rate was in line with that of West Berkshire and lower than the rates of Bracknell Forest, Reading, Slough and Windsor & Maidenhead. Wokingham’s resident casualty rate is lower than that of most similar comparator authorities but broadly similar to South Oxfordshire.

3.1.1.2.1 Residency by Small Area

Figure 3.2 shows the home location of the 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 can be found around Wokingham town, Aborfield Green and around Suttons Business Park. There are also high resident casualty rates around Finchhampstead, Shinfield and Woodley.

Figure 3.2: Wokingham resident casualties home location by LSOA, casualties per year per 100,000 population (2017-2021)

Wokingham resident casualties home location by LSOA, casualties per year per 100,000 population (2017-2021)

3.1.1.4 Socio Demographic Analysis

3.1.1.4.1 Age

Figure 3.4 shows the numbers of resident casualties b age groups.

The largest number of resident casualties are in the 25-34 age group. These are followed by the 17-24 age group. and the 35-44 age group. There are fewer casualties aged under 17 and over 65.

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.

When taking the relative population of each age group into account, the 17-24 age group is over-represented in casualty numbers, and to a greater extent than the over-representation seen nationally. This is also true, although to a lesser extent, of the 25-34 age group. Residents in the 35-44 and 45-54 age groups are only slightly over-represented in casualty numbers, and this is less than the nationally observed over-representation. Residents in the age groups under 17 and over 54 years of age are underrepresented in casualty numbers based on their share of the population.

Figure 3.4: Wokingham resident casualties, by age group (2017-2021)

Wokingham resident casualties, by age group (2017-2021)

Figure 3.5: Wokingham resident casualties, by age group and indexed by population (2017-2021)

Wokingham resident casualties, by age group and indexed by population (2017-2021)

Figure 3.6 illustrates the overall trend for the four age groups over the last ten years.

Casualty trends for most Wokingham resident age groups are decreasing with the exception of the under 17 age group which remains the same.

Figure 3.6: Wokingham resident casualty trend by age group (2012-2021)

Wokingham resident casualty trend by age group (2012-2021)
3.1.1.4.2 Segmentation

Analysis of the Mosaic communities in which Wokingham’s resident casualties live provides an insight into those injured in collisions. For an explanation of Mosaic 7 and how to understand the following chart, please refer to section 5.1.1.1.

The most significantly over-represented resident casualties from Wokingham are from communities of Stable families with children, renting higher value homes from social landlords (Type I36). They do not have the highest number of casualties but significant over representation when accounting for the population share.

The largest number of resident casualties belong to the group of High achieving families living fast-track lives, advancing careers, finances and their school-age kids’ development (Type B07), however these communities are under-represented considering the relative population.

Communities of Affluent families with growing children living in upmarket housing in city environs (Type G26) also have high casualty numbers and are slightly over-represented.

Figure 3.7: Wokingham resident casualties, by Mosaic Type (2017-2021)

Wokingham resident casualties, by Mosaic Type (2017-2021)
3.1.1.4.3 Deprivation

Figure 3.8 shows resident casualties by the IMD of the LSOA (Lower Super Output Area) in which they reside.

The highest number of resident casualties come from communities in the least deprived 10% decile. Despite this, these communities are slightly under-represented in casualty numbers when accounting for relative population. There are much lower numbers of casualties from the less deprived and more deprived 40% deciles, but these communities are noticeably over-represented in casualty numbers.

Figure 3.8: Wokingham resident casualties, by Index of Multiple Deprivation (2017-2021)

Wokingham resident casualties, by Index of Multiple Deprivation (2017-2021)

3.1.2 Resident Child Casualties

This section examines child 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 3.9 shows the Wokingham resident child casualty rate compared to the national and regional rates, and to the most similar comparators.

Wokingham had a resident child casualty rate between 2017 and 2021 of 66 casulties per year, per 100,000 child population.

Figure 3.9: Annual average Wokingham resident child casualties per 100,000 population (2017-2021)

Annual average Wokingham resident child casualties per 100,000 population (2017-2021)

3.1.2.2 Comparisons

Wokingham’s resident child casualty rate was 41% below the national rate, 38% below the South East regional rate, and 10% below the overall Berkshire rate. Within Berkshire, Bracknell Forest, Windsor & Maidenhead and West Berkshire all had a lower resident child casualty rate than Wokingham. Of the most similar comparators, Wokingham’s resident child casualty rate is in line with that of South Cambridgeshire, lower than the rates of Hart, Surrey Heath and Wycombe, but higher than the rate for South Oxfordshire.

3.1.2.2.1 Residency by Small Area

Figure 3.10 shows the home location of Wokingham’s resident child casualties by lower layer super output area (LSOA). The thematic map is coloured by resident casualties per year per population of LSOA.

The highest child casualty rates can be found amongst residents of South Lake and just south of Charvil. There are also high resident child casualty rates to the north of Wokingham, in parts of Early, and around Winnersh.

Figure 3.10: Wokingham resident child casualties home location by LSOA, casualties per year per 100,000 population (2017-2021)

Wokingham resident child casualties home location by LSOA, casualties per year per 100,000 population (2017-2021)

3.1.3 All Wokingham Resident Pedestrian Casualties

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

3.1.3.1 Rates

Figure 3.12 shows the resident pedestrian casualty rates for Wokingham compared to the national and regional rates, as well as the most similar comparators.

Between 2017 and 2021, Wokingham had a resident pedestrian casualty rate of 15 casualties per year, per 100,000 population.

Figure 3.12: Annual average Wokingham resident pedestrian casualties per 100,000 population (2017-2021)

Annual average Wokingham resident pedestrian casualties per 100,000 population (2017-2021)

3.1.3.2 Comparisons

The resident pedestrian casualty rate for Wokingham is half the national rate, 38% below the regional rate, and 25% below the overall Berkshire rate. Within Berkshire, Wokingham’s pedestrian casualty rate is higher than those of Bracknell Forest, but lower than that of Reading, Slough and Windsor & Maidenhead. Of the most similar comparator authorities, Wokingham’s pedestrian casualty rate is higher than that of South Cambridgeshire and South Oxfordshire, but lower than that of Hart, Surrey Heath and Wycombe.

3.1.3.2.1 Residency by Small Area

Figure 3.13 shows the home location of Wokingham’s resident pedestrian casualties by lower layer super output area (LSOA). The thematic map is coloured by resident casualties per year per population of LSOA.

Resident pedestrian casualty rates are highest around Sindlesham, Lower Early, and Wokingham Town. There are also high rates in parts of Winnersh, Emmbrook and Woodley.

Figure 3.13: Wokingham resident pedestrian casualties home location by LSOA, casualties per year per 100,000 population (2017-2021)

Wokingham resident pedestrian casualties home location by LSOA, casualties per year per 100,000 population (2017-2021)

3.1.4 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.

3.1.4.1 Rates

Figure 3.15 shows the resident pedal cyclist casualty rates for Wokingham compared to the national and regional rates, as well as the most similar comparators.

Wokingham had a resident pedal cyclist casualty rate of 22 casualties per year, per 100,000 population.

Figure 3.15: Annual average Wokingham resident pedal cyclist casualties per 100,000 population (2017-2021)

Annual average Wokingham resident pedal cyclist casualties per 100,000 population (2017-2021)

3.1.4.2 Comparisons

Wokingham’s resident pedal cyclist casualty rate is 18% below the national rate, 20% below the regional rate for the South East, and 10% below the overall rate for Berkshire. Within Berkshire, Wokingham’s rate is above the rates of Bracknell Forest and West Berkshire, but below the rates of Reading, Slough, and Windsor & Maidenhead. Of the most similar comparator authorities, Wokingham’s rate is below that of South Cambridge, but above those of Hart and Wycombe.

3.1.4.2.1 Residency by Small Area

Figure 3.16 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 can be found around Lower Earley and Emmbrook. There are also high rates around parts of Woodley and Finchampstead.

Figure 3.16: Wokingham resident pedal cyclist casualties home location by LSOA, casualties per year per 100,000 population (2017-2021)

Wokingham resident pedal cyclist casualties home location by LSOA, casualties per year per 100,000 population (2017-2021)

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

Wokingham had a resident driver involvement rate of 146 drivers per year, per 100,000 population.

Figure 3.18: Annual average Wokingham resident involved drivers per 100,000 population (2017-2021)

Annual average Wokingham resident involved drivers per 100,000 population (2017-2021)

3.2.1.2 Comparisons

The resident driver collision involvement rate for Wokingham was 45% below the national rate, 40% below the regional rate, and 19% below the rate for Berkshire as a whole. Within Berkshire, Wokingham’s rate is slightly lower than that of West Berkshire, Windsor & Maidenhead, Reading and Bracknell Forest, and significantly below that of Slough. Wokingham’s rate was below that of all the most similar comparator authorities apart from South Oxfordshire.

3.2.1.2.1 Residency by Small Area

Figure 3.19 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 can be found towards the south of Woodley, the North of Shinfield, and the North of Crowthorne. There are also high involved drivers rates around Hurst, Spencers Wood, Three Mile Cross and Finchampstead.

Figure 3.19: Wokingham resident involved drivers home location by LSOA, involved drivers per year per 100,000 population (2017-2021)

Wokingham resident involved drivers home location by LSOA, involved drivers per year per 100,000 population (2017-2021)

3.2.1.4 Socio Demographic Analysis

3.2.1.4.1 Age

Figure 3.21 shows the numbers of resident involved drivers by specified age groups.

The largest number of resident involved drivers are in the 25-34 and 35-44 age group. These are followed by the 45-54 and 17-24 age groups.

It is more informative to consider Figure 3.22 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.

When taking into account the relative population of each age group, the 17-24 age group is over-represented in driver numbers and to a greater extent than the over-representation seen nationally. This is also true, although to a lesser extent of the 25-34 age group. Resident involved drivers in the 35-44 and 45-54 age groups are only slightly over-represented in driver numbers, and this is less than the nationally observed over-representation. Resident drivers in the age bands 55 and over are under-represented in driver numbers based on their share of the population.

Figure 3.21: Wokingham resident involved drivers, by age group (2017-2021)

Wokingham resident involved drivers, by age group (2017-2021)

Figure 3.22: Wokingham resident involved drivers, by age group and indexed by population (2017-2021)

Wokingham resident involved drivers, by age group and indexed by population (2017-2021)

Figure 3.23 illustrates the overall trend for the four age groups over the last ten years.

Involved trends by all Wokingham resident driver age groups have decreased over the last ten years. With the exception of the under 17 age group, numbers increased to pre-pandemic levels in 2021.

Figure 3.23: Wokingham resident involved drivers trend by age group (2012-2021)

Wokingham resident involved drivers trend by age group (2012-2021)
3.2.1.4.2 Segmentation

Analysis of the Mosaic communities in which Wokingham’s resident drivers live provides an insight into those injured in collisions. For an explanation of Mosaic 7 and how to understand the following chart, please refer to section 5.1.1.1.

The largest number of resident involved drivers come from communities of High-achieving families living fast-track lives, advancing careers, finances and their school-aged kids’ development (Type B07). When taking into account the relative population of this type, these communities are under-represented in collision involvement. The next largest numbers of involved drivers are Affluent families with growing children living in upmarket housing in city environs (Type G26), Well-qualified older singles with incomes from successful professional careers in good quality housing (Type G27) and Young families and singles setting up home in modern developments that are popular with their peers (Type H33). Drivers from all three communities are a little over-represented in collision involvement given their share of the population of Wokingham.

Communities of Stable families with children, renting higher value homes from social landlords (Type I36) respresent lower levels of collision involved drivers, but are significantly over-represented in collisions given their share of the population.

Figure 3.24: Wokingham resident involved drivers, by Mosaic Type (2017-2021)

Wokingham resident involved drivers, by Mosaic Type (2017-2021)
3.2.1.4.3 Deprivation

Figure 3.25 shows resident involved drivers by the IMD of the LSOA (Lower Super Output Area) in which they reside.

The highest numbers of resident involved drivers come from communities in the least deprived 10% decile. However, when considering their share of the population, they are slightly under-represented in collision involvement. The next largest number of resident involved drivers come from communities in the less deprived 20% decile, and these communities are slightly overrepresented in collisions. Communities in the less deprived and more deprived 40% deciles and the less deprived 30% deciles represent a much lower number of involved drivers but are over-represented when accounting for their relative population.

Figure 3.25: Wokingham resident involved drivers, by Index of Multiple Deprivation (2017-2021)

Wokingham resident involved drivers, by Index of Multiple Deprivation (2017-2021)

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

Wokingham had a resident collision involvement rate for young drivers of 290 drivers per year per 100,000 population.

Figure 3.27: Annual average Wokingham resident young involved drivers per 100,000 population (2017-2021)

Annual average Wokingham resident young involved drivers per 100,000 population (2017-2021)

3.2.3.2 Comparisons

Wokingham’s young driver collision involvement rate between 2017 and 2021 was 18% less the national rate. This is 27% below the regional rate for the South East and 1% below the overall Berkshire rate. Within Berkshire, Reading has the lowest young driver collision involvement rate, followed by Bracknell Forest. Wokingham’s young driver involvement rate is below that of all the most similar comparator authorities.

3.2.3.2.1 Residency by Small Area

Figure 3.28 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.

Some of the highest rates of young driver collision involvement can be found among residents living North of Crowthorne, around Gardeners Green, Emmbrook and in parts of Lower Earley. There are also high collision involvement rates amongst young drivers from Woodley area, Spencers Wood and Shinfield.

Figure 3.28: Wokingham resident young involved drivers home location by LSOA, young involved drivers per year per 100,000 population (2017-2021)

Wokingham resident young involved drivers home location by LSOA, young involved drivers per year per 100,000 population (2017-2021)

3.2.3.4 Socio Demographic Analysis

3.2.3.4.1 Segmentation

Analysis of the Mosaic communities in which Wokingham’s resident young drivers live provides an insight into those injured in collisions. For an explanation of Mosaic 7 and how to understand the following chart, please refer to section 5.1.1.1.

Figure 3.30 shows resident collision-involved young drivers by the Mosaic Group of the community in which they reside. The majority of collision involved young drivers are from communities of High-achieving families living fast-track lives, advancing careers, finances and their school-age kids’ development (Type B07) or of Affluent families with growing children living in upmarket housing in city environs (Type G26). Young drivers from Mosaic type B07 are more over-represented in collision involvement than expected given their share of the population of Wokingham as indicated by an index of 110 (shown in red).

Figure 3.30: Wokingham resident young involved drivers, by Mosaic Type (2017-2021)

Wokingham resident young involved drivers, by Mosaic Type (2017-2021)
3.2.3.4.2 Deprivation

Figure 3.31 shows resident involved young drivers by the IMD of the LSOA (Lower Super Output Area) in which they reside.

The largest number of resident involved young drivers come from communities in the least deprived 10% decile. Despite this, when taking into account the relative population of these communities within Wokingham, they are slightly underrepresented in collision involvement. There is also a large number of involved young drivers from communities in the less deprived 20% decile, and these communities are considerably over-represented relative to their population share.

Figure 3.31: Wokingham resident young involved drivers, by Index of Multiple Deprivation (2017-2021)

Wokingham resident young involved drivers, by Index of Multiple Deprivation (2017-2021)

3.3 Wokingham resident motorcycle riders involved in collisions

3.3.1 Resident Motorcyclist Involvement

This section refers to motorcyclists involved in collisions and who are residents of Wokingham.

3.3.1.1 Rates

Figure 3.33 shows the resident motorcyclist involvement rates for Wokingham compared to the national and regional rates, as well as the most similar comparators.

Wokingham had a resident motorcyclist collision involvement rate of 15.2 motorcyclists per year, per 100,000 population between 2017 and 2021.

Figure 3.33: Annual average Wokingham resident involved motorcyclist per 100,000 population (2017-2021)

Annual average Wokingham resident involved motorcyclist per 100,000 population (2017-2021)

3.3.1.2 Comparisons

Wokingham’s resident motorcyclist collision involvement rate was 43% lower than the national rate. This is 46% below the regional rate for the South East, and 28% below the overall Berkshire rate. Within Berkshire, Wokingham had the lowest resident motorcyclist involvement rate. Wokingham’s resident motorcyclist involvement rate was in line with that of South Oxfordshire, and lower than all the other most similar comparator authorities.

3.3.1.2.1 Residency by Small Area

Figure 3.34 shows the home location of Wokingham’s collision involved resident motorcyclists by lower layer super output area (LSOA). The thematic map is coloured by resident involved motorcyclists per year per population of LSOA.

The highest motorcyclist involvement rates are amongst residents of Wokingham town. There are also high resident motorcyclist involvement rates amongst residents living in the residential areas around Molly Millars Lane industrial estate outside Wokingham town centre and Woodley.

Figure 3.34: Wokingham resident involved motorcyclist home location by LSOA, involved motorcyclist per year per 100,000 population (2017-2021)

Wokingham resident involved motorcyclist home location by LSOA, involved motorcyclist per year per 100,000 population (2017-2021)

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 2017 and 2021 per 100km of road in Wokingham compared to the national and regional rates, and those of the most similar comparators.

Between 2017 and 2021, Wokingham had a collision rate of 23.5 collisions per year, per 100km road on its road network.

Figure 4.1: Annual average collisions per 100km of road (2017-2021)

Annual average collisions per 100km of road (2017-2021)

4.1.1.2 Comparisons

The collision rate in Wokingham was 16% below the national collision rate. This is 35% below the regional rate for the South East, and 22% below the overall Berkshire collision rate. Within Berkshire, West Berkshire had the lowest collision rate followed by Wokingham.

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.

The highest collision rates in Wokingham can be found in Wokingham town centre, Early and Winnersh.

Figure 4.2: Annual average collisions per 100km of road (2017-2021)

Annual average collisions per 100km of road (2017-2021)

4.1.1.4 Collisions by day of the week

Figure 4.4 shows collisions in Wokingham by day of the week and severity. More collisions occur on weekdays in Wokingham than at weekends.

Figure 4.4: Wokingham collisions, by day of the week and severity (2017-2021)

Wokingham collisions, by day of the week and severity (2017-2021)

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. There are clear peaks around both the morning commute (7am to 9am) and the evening commute (3pm to 7pm), with very few collisions before 7am or after 9am.

Figure 4.5: Wokingham collisions, by hour of the day during weekdays (2017-2021)

Wokingham collisions, by hour of the day during weekdays (2017-2021)
4.1.1.5.2 Collisions by hour of the day on weekends

Figure 4.6 shows collisions on weekends by the hour of the day in which they occurred. Compared to weekdays, collision numbers are more evenly spread throughout the day, with the majority occurring after 10am and before 10pm.

Figure 4.6: Wokingham collisions, by hour of the day during weekends (2017-2021)

Wokingham collisions, by hour of the day during weekends (2017-2021)

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. Three quarters (76%) of Wokingham’s collisions occurred during daylight. Of the remaining 24%, the majority took place in the presence of lit street lighting (16%).

Figure 4.7: Wokingham collisions by light conditions (2017-2021)

Wokingham collisions by light conditions (2017-2021)

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. Over four in five collisions (87%) in Wokingham took place during fine weather, without high winds. Of the remaining 13% that took place during adverse weather conditions, most were during rain or snow, without high winds (10%).

Figure 4.8: Wokingham collisions by weather conditions (2017-2021)

Wokingham collisions by weather conditions (2017-2021)
4.1.1.7.1 Collision involved drivers who reside in other areas

Of the drivers involved in collisions in Wokingham for whom home location was recorded, 51% were Wokingham residents. Of the remaining 49%, the majority were residents of Reading (14%), Bracknell Forest (8%), Hampshire (5%), West Berkshire (3%), Windsor and Maidenhead (3%) and Oxfordshire (2%).

4.1.1.8 Collision dynamics and driver action

4.1.1.8.1 Collision dynamics

Figure 4.9 shows collisions in Wokingham by the dynamics resulting in the collision. For more information about how collision dynamics are derived, please refer to 5.1.4. Almost a third (29%) of collisions in Wokingham resulted in no impact between vehicles. Of the remaining 71% of collisions, 11% involved a head on impact, 19% involved a rear impact and 8% involved a side impact. The rest either involved another type of conflict (10%) or had insufficient data to determine the type of impact.

Figure 4.9: Wokingham collisions by collision dynamics (2017-2021)

Wokingham collisions by collision dynamics (2017-2021)
4.1.1.8.2 Driver actions

Figure 4.10 shows collisions in Wokingham by the presence of different driver actions. For more information about how drivers actions are derived, please refer to 5.1.5. It should be noted that multiple driver behaviours may be present within the same collision. Right turns were the most prevalent driver action in collisions in Wokingham , followed by runoffs. Most of these were nearside runoffs. Slow vehicle manouevres, such as being parked, waiting to proceed, slowing down, or stopping, were also present in a high number of collisions.

Figure 4.10: Wokingham collisions by driver actions (2017-2021)

Wokingham collisions by driver actions (2017-2021)

4.1.1.9 Road environment

4.1.1.9.1 Road class

Figure 4.11 shows collisions in Wokingham by class of road. Forty-four percent of collisions in Wokingham were on A roads. Unclassified roads featured over a third (34%) of collisions, whilst 15% of collisions took place on B roads and 8% took place on motorways.

Figure 4.11: Wokingham collisions by road class (2017-2021)

Wokingham collisions by road class (2017-2021)
4.1.1.9.2 Carriageway type

Figure 4.12 shows collisions in Wokingham by carriageway type of road. Nearly three quarters (74%) of collisions were on single carriageway roads, whilst 13% were on dual carriageways. Around 10% of collisions were on roundabouts, 2% were on one-way streets, and 1% were on slip roads.

Figure 4.12: Wokingham collisions by road carriageway type (2017-2021)

Wokingham collisions by road carriageway type (2017-2021)
4.1.1.9.3 Junction type

Figure 4.13 shows collisions in Wokingham by the presence and type of junction. Over half (55%) of collisions in Wokingham took place at a junction. Of these, most were at a normal junction (34%), whilst 19% were at a roundabout. Seven percent were at a private driveway.

Figure 4.13: Wokingham collisions by junction type (2017-2021)

Wokingham collisions by junction type (2017-2021)
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). Of those collisions that did take place at a junction, the vast majority were at a give way or uncontrolled junction. Around 14% were at junctions with automatic traffic signals. Very few collisions were at junctions with stop signs (0.8%) or at junctions controlled by an authorised person (0.2%).

Figure 4.14: Wokingham collisions by junction control (2017-2021)

Wokingham collisions by junction control (2017-2021)

4.2 Collisions on Urban Roads in Wokingham

The following section investigates collisions in Wokingham which occurred on urban roads.

4.2.1 Rates

4.2.1.1 Collisions on urban road per 100km of urban road

Figure 4.20 below shows the rate of average annual collisions on urban roads between 2017 and 2021 per 100km of urban road in Wokingham compared to the national and regional rates, and those of the most similar comparators.

On Wokingham’s urban roads between 2017 and 2021, there was a collision rate of 23 collisions per year, per 100km of urban road.

Figure 4.20: Annual average collisions on urban roads per 100km of urban road (2017-2021)

Annual average collisions on urban roads per 100km of urban road (2017-2021)

4.2.1.2 Comparisons

Wokingham’s urban road collision rate was less than half the national urban road collision rate and the regional rate. This is 39% below the overall Berkshire rate. Within Berkshire, West Berkshire has the lowest urban roads collision rate, followed by Bracknell Forest which is in line with Wokingham. The highest urban roads collision rates are in Slough (78) and Reading (64).

4.2.1.4 Collision dynamics and driver actions on urban roads

4.2.1.4.1 Collision dynamics

Figure 4.22 shows collisions on urban roads in Wokingham by the dynamics resulting in the collision. For more information about how collision dynamics are derived, please refer to 5.1.4. The breakdown of collisions by the dynamics of the collision is similar on urban roads to all roads. Over a quarter of collisions (28%) had no impact between vehicles. Around 12% were head-on collisions, 18% were rear impacts, and 9% were side impacts.

Figure 4.22: Wokingham collisions on urban roads by collision dynamics (2017-2021)

Wokingham collisions on urban roads by collision dynamics (2017-2021)
4.2.1.4.2 Driver actions

Figure 4.23 shows collisions on urban roads in Wokingham by the presence of different driver actions. For more information about how drivers actions are derived, please refer to 5.1.5. It should be noted that multiple driver behaviours may be present within the same collision. Right turns were the most prevalent driver action in collisions in Wokingham , followed by slow maneouvres such as being parked, waiting to proceed, slowing down or stopping. Runoffs and in particular nearside run offs were also present in a high number of collisions.

Figure 4.23: Wokingham collisions on urban roads by driver actions (2017-2021)

Wokingham collisions on urban roads by driver actions (2017-2021)

4.2.1.5 Urban road environment

4.2.1.5.1 Road class

Figure 4.24 shows collisions on urban roads in Wokingham by class of road. Compared to all roads, more urban road collisions take place on unclassified roads (41%, compared to 34%), and fewer take place on motorways (3%).

Figure 4.24: Wokingham collisions on urban roads by road class (2017-2021)

Wokingham collisions on urban roads by road class (2017-2021)
4.2.1.5.2 Carriageway type

Figure 4.25 shows collisions on urban roads in Wokingham by carriageway type of road. When compared to all roads, a lower proportions of urban collisions take place on dual carriageways (7%, compared to 13%) whilst a higher proportion take place on single carriageways (80%, compared to 74%).

Figure 4.25: Wokingham collisions on urban roads by road carriageway type (2017-2021)

Wokingham collisions on urban roads by road carriageway type (2017-2021)
4.2.1.5.3 Junction type

Figure 4.26 shows collisions on urban roads in Wokingham by the presence and type of junction. Just under a third (30%) of urban collisions took place away from a junction. This is lower than the proportion for all roads (39%). Of the 61% of urban collisions that did take place at a junction, most were at a normal junction (40%). Around 20% took place at roundabouts, and 8% were at private drives.

Figure 4.26: Wokingham collisions on urban roads by junction type (2017-2021)

Wokingham collisions on urban roads by junction type (2017-2021)
4.2.1.5.4 Junction control

Figure 4.27 shows collisions on urban roads in Wokingham by the type of junction control (if the collision took place at a junction). Of those collisions that did take place at a junction, the vast majority were at a give way or uncontrolled junction. Around 13% were at junctions with automatic traffic signals. Very few collisions were at junctions with stop signs (0.2%) or at junctions controlled by an authorised person (0.2%).

Figure 4.27: Wokingham collisions on urban roads by junction control (2017-2021)

Wokingham collisions on urban roads by junction control (2017-2021)

4.3 Collisions on Rural Roads in Wokingham

The following section investigates collisions in Wokingham which occurred on rural roads.

4.3.1 Rates

4.3.1.1 Collisions on rural road per 100km of rural road

Figure 4.33 shows the rate of average annual collisions on rural roads between 2017 and 2021 per 100km of rural road in Wokingham compared to the national and regional rates, and those of the most similar comparators.

Wokingham’s rural road collision rate between 2017 and 2021 was 24 collisions per year, per 100km of rural road.

Figure 4.33: Annual average collisions on rural roads per 100km of rural road (2017-2021)

Annual average collisions on rural roads per 100km of rural road (2017-2021)

4.3.1.2 Comparisons

Wokingham’s rural road collision rate is 65% higher than the national rate, and 12% higher than the overall rate for Berkshire. This is 13% lower than the South East’s regional rate. Wokingham’s rate is the second lowest within Berkshire, above West Berkshire.

4.3.1.4 Collision dynamics and driver actions on rural roads

4.3.1.4.1 Collision dynamics

Figure 4.35 shows collisions on rural roads in Wokingham by the dynamics resulting in the collision. For more information about how collision dynamics are derived, please refer to 5.1.4. The breakdown of collisions by the dynamics of the collision is similar on rural roads to all roads. Almost a third of collisions (31%) had no impact between vehicles. Around 9% were head-on collisions, 21% were rear impacts, and 7% were side impacts.

Figure 4.35: Wokingham collisions on rural roads by collision dynamics (2017-2021)

Wokingham collisions on rural roads by collision dynamics (2017-2021)
4.3.1.4.2 Driver actions

Figure 4.36 shows collisions on rural roads in Wokingham by the presence of different driver actions. For more information about how drivers actions are derived, please refer to 5.1.5. It should be noted that multiple driver behaviours may be present within the same collision. Right turns were the most prevalent driver action in collisions on rural roads in Wokingham , followed by Runoffs. Slow maneouvres such as being parked, waiting to proceed, slowing down or stopping were also present in a high number of collisions.

Figure 4.36: Wokingham collisions on rural roads by driver actions (2017-2021)

Wokingham collisions on rural roads by driver actions (2017-2021)

4.3.1.5 Rural road environment

4.3.1.5.1 Road class

Figure 4.37 shows collisions on rural roads in Wokingham by class of road. Compared to all roads, more rural road collisions take place on motorways or A(M) roads (17%, compared to 9%), and fewer take place on unclassified roads (25% compared to 34%).

Figure 4.37: Wokingham collisions on rural roads by road class (2017-2021)

Wokingham collisions on rural roads by road class (2017-2021)
4.3.1.5.2 Carriageway type

Figure 4.38 shows collisions on rural roads in Wokingham by carriageway type of road. When compared to all roads, a higher proportion of rural collisions take place on dual carriageways (21%, compared to 13%) whilst a lower proportion take place on single carriageways (67%, compared to 74%).

Figure 4.38: Wokingham collisions on rural roads by road carriageway type (2017-2021)

Wokingham collisions on rural roads by road carriageway type (2017-2021)
4.3.1.5.3 Junction type

Figure 4.39 shows collisions on rural roads in Wokingham by the presence and type of junction. Almost half (49%) of rural collisions took place away from a junction. This is higher than the proportion for all roads (39%). Of the 51% collisions that did take place at a junction, most were at a normal junction (26%). Around 17% took place at roundabouts, and 5% were at private drives.

Figure 4.39: Wokingham collisions on rural roads by junction type (2017-2021)

Wokingham collisions on rural roads by junction type (2017-2021)
4.3.1.5.4 Junction control

Figure 4.40 shows collisions on rural roads in Wokingham by the type of junction control (if the collision took place at a junction). Of those collisions that did take place at a junction, the vast majority were at a give way or uncontrolled junction. Around 16% were at junctions with automatic traffic signals. Very few collisions were at junctions with stop signs (3%).

Figure 4.40: Wokingham collisions on rural roads by junction control (2017-2021)

Wokingham collisions on rural roads by junction control (2017-2021)

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.

4.4.1.2 Comparisons

Figure 4.49 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.

Just under 9% of officer attended collisions in Wokingham were attributed a speed choice CF. This is lower than the proportions seen nationally, regionally, and across Berkshire as a whole. Within Berkshire, Reading has the lowest proportion of speed related collisions (7.1%), followed by Wokingham. Of the most similar comparator authorities, Wokingham’s percentage of speed related collisions is higher than that of Surrey Heath (6.3%), but lower than those of Hart, South Cambridgeshire, South Oxfordshire, and Wycombe.

Figure 4.49: Percentage of collisions in Wokingham and comparators where CF306 and/or CF307 were recorded (2017-2021)

Percentage of collisions in Wokingham and comparators where CF306 and/or CF307 were recorded (2017-2021)

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.

4.4.2.2 Comparisons

Figure 4.52 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.

Of Wokingham’s officer attended collisions, 8.6% were attributed an impairment CF. This is higher than the national and South East regional proportions. Within Berkshire, Slough has the lowest percentage of impairment related collisions. Wokingham’s percentage was in line with that of Reading, and Windsor & Maidenhead and higher than that of West Berkshire, Bracknell Forest and Slough. Wokingham also has a higher proportion of collisions attributed an impairment CF than all the most similar comparator authorities apart from Wycombe.

Figure 4.52: Percentage of collisions in Wokingham and comparators where CF501 and/or CF502 were recorded (2017-2021)

Percentage of collisions in Wokingham and comparators where CF501 and/or CF502 were recorded (2017-2021)

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.

4.4.3.2 Comparisons

Figure 4.55 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.

Between 2017 and 2021, 5.9% of Wokingham’s officer attended collisions were attributed a road surface CF. This is below the national and the South East regional rate. Within Berkshire, Slough and Reading have the lowest percentages of collisions attributed a road surface CF, followed by Wokingham. Surrey Heath has the lowest proportion of road surface related collisions (6.8%) of all the most similar comparator authorities, still higher than the percentage for Wokingham.

Figure 4.55: Percentage of collisions in Wokingham and comparators where CF101 and/or CF102 and/or CF103 were recorded (2017-2021)

Percentage of collisions in Wokingham and comparators where CF101 and/or CF102 and/or CF103 were recorded (2017-2021)

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.

4.4.4.2 Comparisons

Figure 4.58 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.

In Wokingham, 16.4% of collisions attended by a police officer were attributed a control error CF. This is in line with both the GB and South East percentage. Of all comparators, Wokingham’s percentage is in line with Windsor & Maidenhead. These are higher than the other Berkshire authorities of Slough and Reading and the external comparators of Wycombe and Surrey Heath.

Figure 4.58: Percentage of collisions in Wokingham and comparators where CF408 and/or CF409 and/or CF410 were recorded (2017-2021)

Percentage of collisions in Wokingham and comparators where CF408 and/or CF409 and/or CF410 were recorded (2017-2021)

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.

4.4.5.2 Comparisons

Figure 4.61 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, 18.6% of collisions attended by a police officer were attributed an unsafe behaviour CF. This is higher than the GB percentage but in line with the percentage for the South-East. Wokingham’s percentage is similar to West Berkshire and higher than Reading and Windsor & Maidenhead.

Figure 4.61: Percentage of collisions in Wokingham and comparators where CF601 and/or CF602 were recorded (2017-2021)

Percentage of collisions in Wokingham and comparators where CF601 and/or CF602 were recorded (2017-2021)

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.

4.4.6.2 Comparisons

Figure 4.64 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.

In Wokingham, 6.5% of collisions attended by a police officer were attributed a distraction CF. This is higher than both the GB and the South East percentage. Wokingham’s percentage is higher than all other Berkshire authorities but is lower than most external comparators.

Figure 4.64: Percentage of collisions in Wokingham and comparators where CF508 and/or CF509 and/or CF510 were recorded (2017-2021)

Percentage of collisions in Wokingham and comparators where CF508 and/or CF509 and/or CF510 were recorded (2017-2021)

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.

4.4.7.2 Comparisons

Figure 4.67 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.

In Wokingham, 4.2% of collisions attended by a police officer were attributed a medically unfit CF. This is higher than both the percentage for GB and the South East region. Wokingham’s percentage is higher than all other Berkshire authorities apart from West Berkshire, Bracknell Forest and most external comparators.

Figure 4.67: Percentage of collisions in Wokingham and comparators where CF504 and/or CF505 were recorded (2017-2021)

Percentage of collisions in Wokingham and comparators where CF504 and/or CF505 were recorded (2017-2021)

4.4.8 Close Following

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

4.4.8.2 Comparisons

Figure 4.70 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.

In Wokingham, 3.9% of collisions attended by a police officer were attributed the close following CF. This is lower than both the GB and the South East percentage. Wokingham’s percentage is lower than all other Berkshire authorities apart from Reading and all external comparators apart from Surrey Heath.

Figure 4.70: Percentage of collisions in Wokingham and comparators where CF308 was recorded (2017-2021)

Percentage of collisions in Wokingham and comparators where CF308 was recorded (2017-2021)

5 Appendices

5.1 Analytical Techniques

5.1.1 Resident road users

Casualty and driver postcodes in STATS 19 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 Mosaic 7 segmentation, deprivation and/or rurality. More information on Mosaic is provided later in this section.

5.1.1.1 Mosaic 7

Insight into the lifestyles of Wokingham resident road casualties and motor vehicle users can be provided through socio demographic analysis. RSA Mosaic profiling uses Experian’s Mosaic 7 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 Mosaic Types, so residency analysis is based on about five out of six Wokingham residents involved in reported injury collisions.

Mosaic 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. The system was devised under the direction of Professor Richard Webber, a leading authority on consumer segmentation, using data from a wide range of public and private sources. It is used to inform policy decisions, communications activity and resource strategies across the public sector.

Mosaic presently classifies the community represented by each UK postcode into one of 15 Groups and 66 Types. Each Group embraces between 3 and 6 Types. A complete list of Mosaic Types is provided in 5.2.1 whilst profiles and distribution for the Mosaic Types identified in this Area Profile as providing insight on Wokingham’s residents are detailed in 5.2.2.

This profile displays Mosaic 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 Mosaic Type or Group, corresponding to the value axis to the left of the chart. The columns in the foreground provide an index for each Mosaic 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 Mosaic profiles for drivers may be provided with indices based on Experian’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 Mosaic 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.

5.1.3 Comparators

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

On a regional level, all of the other Berkshire authorities have been analysed to show how resident road user and collision rates differ between authority areas within the county.

It is not always appropriate to compare an authority solely against it’s neighbours , especially when the authority has unique characteristics in terms of socio-demographic composition and/or road network. In this Area Profile, Wokingham’s most similar authorities have been selected using Mosaic classification. Because of the size of Wokingham , only district authorities have been selected for comparison. The chosen five districts are:

Local Authority District
Hart District
South Cambridgeshire District
South Oxfordshire District
Surrey Heath Borough
Wycombe District

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

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.

o 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.

o 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

5.1.5 Driver Actions

The derivation of ‘Driver Action’ from STATS 19 data is carried out using a combination of two data collection fields, ‘Vehicle Manoeuvres’ and ‘Vehicle leaving carriageway’. The definitions of driver actions 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 RSA often organises CFs into groupings. A complete list of all CFs and their groupings may be found in section 5.4.

5.2 Mosaic 7

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

5.2.1 Complete list of Mosaic Types

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

5.2.2 Profile and distribution for selected Mosaic Types

The table below shows Mosaic 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.

Figure 5.1 shows Wokingham’s LSOAs colour coded by dominant Mosaic Type.

Figure 5.1: Dominant Mosaic Types in Wokingham

Dominant Mosaic Types in Wokingham

5.3 Data Tables

All Casualties - Wokingham Residents (3.1.1)
Year Fatal Serious Slight Total
2012 4 40 351 395
2013 1 51 302 354
2014 4 41 318 363
2015 2 42 319 363
2016 3 51 275 329
2017 5 37 215 257
2018 5 31 226 262
2019 1 30 204 235
2020 2 25 167 194
2021 4 39 192 235
Total 31 387 2569 2987
Child Casualties - Wokingham Residents (3.1.2)
Year Fatal Serious Slight Total
2012 0 5 37 42
2013 0 5 26 31
2014 0 5 17 22
2015 0 5 30 35
2016 0 4 26 30
2017 0 5 17 22
2018 0 3 25 28
2019 0 1 24 25
2020 1 2 22 25
2021 0 4 22 26
Total 1 39 246 286
Pedestrian Casualties - Wokingham Residents (3.1.3)
Year Fatal Serious Slight Total
2012 0 6 27 33
2013 0 7 26 33
2014 2 10 24 36
2015 1 7 27 35
2016 0 4 31 35
2017 1 9 18 28
2018 3 4 17 24
2019 0 7 20 27
2020 0 6 16 22
2021 1 7 20 28
Total 8 67 226 301
Pedal Cycle User Casualties - Wokingham Residents (3.1.4)
Year Fatal Serious Slight Total
2012 1 8 48 57
2013 0 11 41 52
2014 0 8 38 46
2015 0 6 35 41
2016 0 13 39 52
2017 1 5 31 37
2018 0 7 32 39
2019 0 5 33 38
2020 2 5 32 39
2021 0 4 27 31
Total 4 72 356 432
Motor Vehicle Drivers Involved in Injury Collisions - Wokingham Residents (3.2.1)
Year Fatal Serious Slight Total
2012 4 44 383 431
2013 4 55 322 381
2014 4 49 345 398
2015 5 41 359 405
2016 5 49 297 351
2017 1 35 250 286
2018 8 37 232 277
2019 2 31 212 245
2020 5 24 176 205
2021 5 37 196 238
Total 43 402 2772 3217
Motorcyclists Involved in Injury Collisions - Wokingham Residents (3.3.1)
Year Fatal Serious Slight Total
2012 1 4 32 37
2013 0 17 25 42
2014 1 9 28 38
2015 0 17 21 38
2016 2 17 27 46
2017 0 9 17 26
2018 2 7 21 30
2019 1 6 21 28
2020 0 3 13 16
2021 1 12 17 30
Total 8 101 222 331
Young Adult Drivers Involved in Injury Collisions - Wokingham Residents (3.2.3)
Year Fatal Serious Slight Total
2012 2 10 75 87
2013 1 7 49 57
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 25 32
Total 5 66 457 528
All Collisions - Wokingham Roads (4.1)
Year Fatal Serious Slight Total
2012 2 31 237 270
2013 1 49 200 250
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
Total 23 351 1843 2217
Urban Collisions - Wokingham Roads (4.2)
Year Fatal Serious Slight Total
2012 1 12 134 147
2013 0 20 97 117
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
Total 11 164 983 1158
Rural Collisions - Wokingham Roads (4.3)
Year Fatal Serious Slight Total
2012 1 19 103 123
2013 1 29 103 133
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
Total 12 187 860 1059
Collisions by Hour of the Day (Weekdays) - Wokingham Roads (4.1.1.5)
Time of Day Fatal Serious Slight Total
Midnight 1 3 4 8
1am 0 2 2 4
2am 0 0 2 2
3am 0 0 3 3
4am 0 0 1 1
5am 0 1 0 1
6am 1 3 16 20
7am 1 10 36 47
8am 0 14 62 76
9am 0 4 32 36
10am 0 6 28 34
11am 0 2 19 21
Noon 0 2 25 27
1pm 1 6 33 40
2pm 1 8 30 39
3pm 0 8 62 70
4pm 0 6 48 54
5pm 0 9 70 79
6pm 2 8 57 67
7pm 1 8 25 34
8pm 0 2 18 20
9pm 0 5 11 16
10pm 1 3 16 20
11pm 0 3 3 6
Total 9 113 603 725
Collisions by Hour of the Day (Weekends) - Wokingham Roads (4.1.1.5)
Time of Day Fatal Serious Slight Total
Midnight 0 1 7 8
3am 0 1 2 3
4am 0 2 0 2
6am 0 0 2 2
7am 0 1 6 7
8am 0 0 4 4
9am 0 1 8 9
10am 0 2 10 12
11am 0 1 12 13
Noon 0 3 12 15
1pm 1 4 10 15
2pm 0 3 11 14
3pm 1 3 6 10
4pm 0 2 8 10
5pm 1 4 15 20
6pm 1 1 13 15
7pm 0 2 7 9
8pm 0 1 4 5
9pm 0 2 12 14
10pm 0 2 5 7
11pm 0 2 1 3
Total 4 38 155 197
Collisions Involving Factors 306 and/or 307 (Speed Related) - Wokingham Roads (4.4.1)
Year Fatal Serious Slight Total
2012 0 3 18 21
2013 0 4 16 20
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
Total 3 23 136 162
Collisions Involving Factors 501 and/or 502 (Impairment Related) - Wokingham Roads (4.4.2)
Year Fatal Serious Slight Total
2012 0 4 10 14
2013 0 3 5 8
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
Total 3 30 73 106
Collisions Involving Factors 101 and/or 102 and/or 103 (Road Surface Related) - Wokingham Roads (4.4.3)
Year Serious Slight Total
2012 2 22 24
2013 5 21 26
2014 2 19 21
2015 5 18 23
2016 2 15 17
2017 0 11 11
2018 0 9 9
2019 1 7 8
2020 1 5 6
2021 0 7 7
Total 18 134 152
Collisions Involving Factors 408 and/or 409 and/or 410 (Control Error Related) - Wokingham Roads (4.4.4)
Year Fatal Serious Slight Total
2012 0 6 53 59
2013 0 13 46 59
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
Total 6 61 294 361
Collisions Involving Factors 601 and/or 602 (Unsafe Behaviour Related) - Wokingham Roads (4.4.5)
Year Fatal Serious Slight Total
2012 1 8 34 43
2013 0 5 23 28
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
Total 4 63 244 311
Collisions Involving Factors 508 and/or 509 and/or 510 (Distraction Related) - Wokingham Roads (4.4.6)
Year Fatal Serious Slight Total
2012 1 2 9 12
2013 0 0 11 11
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
Total 2 16 95 113
Collisions Involving Factors 504 and/or 505 (Medically Unfit) - Wokingham Roads (4.4.7)
Year Fatal Serious Slight Total
2012 0 1 5 6
2013 0 1 10 11
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
Total 2 14 53 69
Collisions Involving Factors 308 (Close Following Related) - Wokingham Roads (4.4.8)
Year Serious Slight Total
2012 0 11 11
2013 0 16 16
2014 1 17 18
2015 0 17 17
2016 1 11 12
2017 1 6 7
2018 1 6 7
2019 2 4 6
2020 1 3 4
2021 1 2 3
Total 8 93 101

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 RSA has used in the past for this purpose. Clients may wish to devise alternative approaches.

5.5 List of Figures

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

  2. http://www.experian.co.uk/marketing-services/products/mosaic-uk.html↩︎