1 Executive Summary

This Area Profile presents a systematic overview of resident and road risk in West Berkshire. 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.

West Berkshire’s overall resident casualty rate is 37% lower than the national rate and 38% lower than the rate for the South East region. Resident casualty numbers have seen a steady downward trend over the last decade. Forty two percent of West Berkshire’s resident casualties are injured outside of the county. The greatest and over-represented number of West Berkshire’s resident casualties are from mosaic type I36; stable families with children, renting higher value homes from social landlords. West Berkshire’s resident casualties are most likely to come from the least deprived 10% of the population. Resident casualties have been broken down into the following cohorts:

  1. Resident child casualty numbers from West Berkshire have seen a downward trend since 2016 and despite the pandemic, numbers were lower in 2021 than 2020. No resident children were killed in the last 7 years. Three quarters of West Berkshire’s child casualties were injured in West Berkshire.
  2. Resident pedal cyclist casualty numbers have decreased since 2015 (with the exception of 2020). Almost three quarters of West Berkshire’s pedal cyclist casualties were injured on West Berkshire’s roads. The number of seriously injured West Berkshire resident casualties has also fallen with just 1 recorded serious casualty in 2021.

Collision involved resident drivers from West Berkshire have decreased over the last ten years. The rate per 100,000 population is 43% lower than the national rate and 38% lower than the rate for the South East region. The rate for West Berkshire is lower than all other Berkshire authorities apart from Wokingham. Most of the collision involved drivers are of working age (17-65) and are more likely to come from communities of mosaic type C10, prosperous owners of country houses including affluent families, successful farmers and second-home owners or type B07, high achieving families living fast-track lives, advancing careers, finances and their school-age kids’ development.

An extra section has been added to this study to specifically look at young drivers (aged 17 to 24). Collision involved resident young drivers have decreased between 2012 and 2019 and then rose again slightly in 2020 and 2021. The rate per 100,000 population is 8% lower than the national rate and 18% lower than the regional rate. Forty-six percent of West Berkshire’s resident young drivers were involved in collisions in Berkshire.

The number of West Berkshire’s resident motorcycle riders involved in collisions has fluctuated over the last decade, with an overall downward trend, and the largest number of riders can be found in the 17 to 24 age group. Fifty-four percent of them were involved in collisions on West Berkshire’s roads. West Berkshire’s motorcyclist collision involvement rate was 45% below the national rate and 45% below the rate for the South East region. Of the Berkshire authorities, West Berkshire’s motorcyclist involvement rate is lower than all apart from Wokingham.

As well as reviewing the risk to residents, this Area Profile has considered collision rates on the local road network. Collisions on West Berkshire’s road network have decreased steadily over the last decade. The collision rate per 100km road on West Berkshire’s road network was half that the national rate and 61% lower than the rate for the South East region. West Berkshire’s collision rate is lower than that of all the other Berkshire authorities.

Collision numbers on urban roads in West Berkshire saw a sharp reduction in 2016, followed by another in 2020. However, 2021 has seen a rise in collision numbers consistent with pre-pandemic levels and the number of serious injury collisions on urban roads has hit its lowest level in the last ten years. The collision rate between 2017 and 2021 was lower than all other Berkshire authorities. Analysis of the collision dynamics at the time of the collision show that just over a third of collisions on urban roads resulted in no vehicle-to-vehicle impact. Where multiple vehicles were involved, 16% involved rear vehicle impact, 10% side impact and 9% head on or another point of the vehicle. 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. Fifty-seven percent of collisions on West Berkshire’s urban roads took place on unclassified roads. Higher urban collision rates are found in north-west Newbury Central & Greenham and Calcot North & Little Heath.

Collision numbers on rural roads in West Berkshire have been steadily falling since 2012, despite a small increase in 2016. There was no change between 2020 and 2021. The collision rate between 2017 and 2021 was 12% below the national average and 54% below the rate for the South East. Within Berkshire, West Berkshire has the lowest rural road collision rate. Analysis of the collision dynamics at the time of the collision show that just over a third of collisions on rural roads resulted in no vehicle-to-vehicle impact. Where multiple vehicles were involved, 24% and 7% head on impact or another point of the vehicle. The driver actions at the time of the collision show that the highest percentage of collisions on rural roads involved runoff and runoff to the nearside of the carriageway. Thirty-eight percent of collisions on West Berkshire’s urban roads took place on unclassified roads. Higher rural collision rates are found in Hungerford, east Theale & Beenham, south-east Streatley & Pangbourne and south-west Burghfield Common.

The factors that contribute towards crashes are also measured. It is entirely possible that a 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 factor ‘exceeding speed limit’ or ‘traveling too fast for conditions’ has dropped significantly on West Berkshire’s roads. Together these factors still play a part in 11% of all collisions, a percentage that is only slightly higher than the national percentage and the South East region.

Factors that relate to the road environment have also been measured. Road surface factors including slippery, icy and defective roads are summarised and show a declining trend. Despite this, the last three years have reported the highest ratios of severe consequences with a quarter or more collisions attributed a road surface condition CF resulting in fatal or serious injury. These factors play a part in almost 12% of all collisions which is higher than the national percentage and the South East region. The recording of ‘loss of control’, ‘close following’ and ‘distraction’ factors in West Berkshire all follow a declining trend. ‘Unsafe behaviour’, ‘impairment’ and ‘medically unfit’ factors have been variable over the last ten years and annual fluctuations are most likely due to the small number of collisions in question.

In summary the road safety risk rates for West Berkshire’s residents are, for the most part, lower than the national and regional norm and have decreased over the last ten years. Resident drivers have a lower risk rate than many 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 West Berkshire, as well as casualties and drivers involved in collisions anywhere in Britain who reside in West Berkshire.

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 West Berkshire’s road network and West Berkshire’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 West Berkshire’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 West Berkshire’s key road safety issues with those of comparator regions and national figures. The aim is to allow West Berkshire 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 the West Berkshire 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 West Berkshire’s resident casualties and resident motor vehicle users in terms of rates, comparisons with other relevant police force 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 West Berkshire 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 West Berkshire’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 West Berkshire. 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 West Berkshire, 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 West Berkshire’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 West Berkshire 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 West Berkshire Resident Casualties

This section examines all casualties who were residents of West Berkshire at the time of injury. For information about West Berkshire’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 West Berkshire compared to the national and regional rates, as well as the most similar comparators.

West Berkshire’s resident casualty rate for 2021 is 142.5 casualties per year, per 100,000 population.

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

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

3.1.1.2 Comparisons

West Berkshire’s casualty rate is 37% below the national casualty rate and 38% below the South East regional rate. It is 18% lower than the overall rate for Berkshire with only one of its neighbouring authorities - Wokingham - having a casualty rate lower than West Berkshire. Likewise against other similar comparator authorities just South Oxfordshire has a lower casualty rate than West Berkshire.

3.1.1.2.1 Residency by Small Area

Figure 3.2 shows the home location of West Berkshire’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 casualty rate is in Upper Lambourn with high rates also found in Hungerford, Hermitage and Cold Ash (north of the M4), Mortimer, around Theale and parts of Thatcham.

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

West Berkshire 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 by ten specified age groups.

The highest number of resident casualties come from the 17-24 years, 25-34 years and 35-44 years age groups. There are few resident casualties aged under 17 years or over 65 years. Residents aged 17-24 and 45-54 years account for the most killed and seriously injured casualties.

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 West Berkshire. There is also a national index value for comparison.

This shows that residents aged 17 to 44 are over-represented when population is taken into account and resident casualties aged 17-24 years are over represented in West Berkshire by almost 30% higher than the national index. Casualties in the 25-34, and 35-44 year age groups are over represented to a lesser amount but still exceed the national index. Resident casualties in the age group 45-54 years are slightly over represented although their numbers are very similar to what we would expect to see given the relative population. Casualties aged 5-16 years and 85+ years are under represented in collisions in West Berkshire and more so than the under representation seen nationally.

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

West Berkshire resident casualties, by age group (2017-2021)

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

West Berkshire 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.

The casualty involvement of all age groups has steadily decreased over the decade, although the percentage reduction has reduced to 45% (from 54% in 2020) as a result of the increase in casualty numbers in 2021. The under 17 years and 17-24 year age groups continue to experience the most significant decreases with 58% and 52% reductions respectively. The number of resident casualties aged 25-59 years and aged 60 years also continue to see a moderate reduction over the same period with reductions of 42% and 34% each. Under 17 year resident casualties was the only age group not to see an increase in casualty numbers in 2021, maintaining a downward trend.

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

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

Analysis of the Mosaic communities in which West Berkshire’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.

Figure 3.7 shows the Mosaic Groups of West Berkshire’s resident casualties based on the postcode in which they live. Unsurprisingly there is little change in the socio-demographics of the authority’s casualties from previous years with Mosaic Groups C10 - Wealthy Landowners and I36 - Solid Economy accounting for the most casualties and the latter over-represented in terms of the relative population (index value of 180).

Those from communities of rural families living in affordable village homes who are reliant on the local economy for jobs (Type D15) account for the smallest number of resident casualties however the 46 casualties from this Mosaic Group are over-representative of the local population, shown by an index value of 168.

As has been evident in previous years’ collision and casualty statistics, West Berkshire residents from 3 Mosaic groups remain under-represented as casualties injured in road traffic collisions - Type C10: Wealthy Landowners, F23 - Family Ties & B07 - Alpha Families. However 2021 data shows that residents of Type G29, communities of professional families with children in traditional mid-range suburbs where neighbours are often older are now under-represented which might suggest that the relative population numbers have increased in the area as well as the number of casualties reducing.

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

West Berkshire 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 majority of resident casualties come from communities in the less deprived IMD deciles and whilst residents from the least deprived 10% - 30% deciles account for some of the highest numbers of casualties they are under-represented in terms of the relative population. By comparison residents of the least deprived 40% decile also account for some of the highest number of resident casualties but are over-represented relative to the local population.

The number of resident casualties who are in the more deprived 50% decile has fallen significantly from 2020 to 2021 but these 40 casualties are now over-representative of the local population suggesting the population levels in this decile have increased over the same time period.

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

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

3.1.2 Resident Child Casualties

This section examines child casualties who are residents of West Berkshire. 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 West Berkshire resident child casualty rate compared to the national and regional rates, and to the most similar comparators.

West Berkshire’s child casualty rate has fallen since 2020 to 62 child casualties per year, per 100,000 child population.

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

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

3.1.2.2 Comparisons

The resident child casualty rate for West Berkshire was 43% below the national rate and 41% below the South East regional rate. It is has also fallen against the overall Berkshire rate dropping to 15% lower, although Bracknell Forest and Windsor & Maidenhead still have lower child casualty rates within the county. When considered against similar comparator authorities West Berkshire’s rate was lower than Aylesbury Vale and East Hampshire but higher than South Oxfordshire and Vale of White Horse.

3.1.2.2.1 Residency by Small Area

Figure 3.10 shows the home location of West Berkshire’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 resident child casualty rate can be found in north-west Thatcham with high child casualty rates also found in Upper Lambourn, parts of Theale and Upper Basildon.

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

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

3.1.3 All West Berkshire Resident Pedal Cyclist Casualties

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

3.1.3.1 Rates

Figure 3.12 shows the resident pedal cyclist casualty rates for West Berkshire compared to the national and regional rates, as well as the most similar comparators.

The pedal cyclist casualty rate for West Berkshire is 17.8 casualties per year, per 100,000 population.

Figure 3.12: Annual average West Berkshire resident pedal cyclist casualties per 100,000 population (2017-2021)

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

3.1.3.2 Comparisons

The resident pedal cyclist casualty rate for West Berkshire was 32% below the rate for Great Britain and 34% below the South East regional rate. West Berkshire’s rate is virtually the same as Bracknell Forest and together they have the lowest rates in the county at 26% below the overall rate for Berkshire. Compared to other similar authorities West Berkshire’s pedal cyclist casualty rate is higher than Aylesbury Vale and East Hampshire but lower than South Oxfordshire, Vale of White Horse and Horsham.

3.1.3.2.1 Residency by Small Area

Figure 3.13 shows the home location of West Berkshire’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 pedal cyclist casualty rate is found in the north east of Newbury Wash Common with high rates also found in parts of Thatcham Town, Hermitage & Cold Ash, Newbury North West, Burghfield Common, Calcot South and Calcot North & Little Heath.

Figure 3.13: West Berkshire resident pedal cyclist casualties home location by LSOA, casualties per year per 100,000 population (2017-2021)

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

3.2 West Berkshire Resident Drivers involved in Collisions

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

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

This section analyses all persons recorded as being [a] West Berkshire 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 3.15 shows the resident driver involvement rates for West Berkshire compared to the national and regional rates, as well as the most similar comparators.

West Berkshire has a resident driver involvement casualty rate of 152 drivers per year, per 100,000 population.

Figure 3.15: Annual average West Berkshire resident involved drivers per 100,000 population (2017-2021)

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

3.2.1.2 Comparisons

West Berkshire’s resident driver collision-involvement rate remains at a similar level as in 2020 relative to the national and regional rates being 43% and 38% below each respectively. Within Berkshire, its rate is broadly equivalent to Windsor and Maidenhead with just Wokingham reporting a lower resident driver rate. Across a wider area and against similar comparator authorities, West Berkshire is higher than South Oxfordshire but lower than Horsham, East Hampshire and Aylesbury Vale.

3.2.1.2.1 Residency by Small Area

Figure 3.16 shows the home location of West Berkshire’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 found in east Lambourn & Great Shefford, east Kintbury & Boxford, north-east and east Theale and Beenham and west Burghfield Common.

Figure 3.16: West Berkshire resident involved drivers home location by LSOA, involved drivers per year per 100,000 population (2017-2021)

West Berkshire 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 3.4 shows the numbers of resident involved drivers by ten specified age groups.

Drivers aged 25-34 years account for the highest number of West Berkshire resident drivers, followed closely by 17-24 year olds, drivers aged 45-54 years and then 35-44 year old drivers. Resident drivers aged 65+ years account for just 13% of the total number of drivers involved in collisions from West Berkshire.

It is more informative to consider Figure 3.19 which shows resident involved driver numbers by age group indexed by the population of those age groups in West Berkshire. There is also a national index value for comparison.

Figure 3.19 shows that the number of collision-involved 17-24 and 25-34 year old resident drivers are over-representative of each of the relative populations with 17-24 year olds also 54% higher than the national index. All other drivers are under the national index and the number of under 17 year old drivers and drivers aged 65 and over under-represented against the local population.

Figure 3.18: West Berkshire resident involved drivers, by age group (2017-2021)

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

Figure 3.19: West Berkshire resident involved drivers, by age group and indexed by population (2017-2021)

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

Figure 3.20 illustrates the overall trend for the four age groups over the last ten years.

There has been a steady decline in resident involved driver collisions over the last ten years with numbers falling by 48% overall. Resident drivers aged 17-24 years have seen the greatest reduction of 63%. Between 2016 to 2017 saw the greatest reduction in 25-59 year old resident driver involvement, a trend that continued into 2020. However collision figures for 2021 show an increase in the number of resident drivers across all four age categories by between 5% and 34%.

Figure 3.20: West Berkshire resident involved drivers trend by age group (2012-2021)

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

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

Figure 3.21 shows West Berkshire’s resident collision-involved drivers by the Mosaic Type of the postcode where they live. The red bars show the index value based on the population of those Types living in West Berkshire. A greater proportion of resident drivers, in 2021 compared to previous years, come from communities of prosperous owners of country houses including affluent families, successful farmers and second-home owners (Type C10). The remainder of the resident drivers are spread fairly evenly between nine different Mosaic types.

In a further change from last year’s data, the number of resident drivers from Type C10 are now slightly over-represented in collisions relative to the local population with an index value of 115, which is the same for drivers from Type H30 - Primary Ambitions, Type I36 - Solid Economy and Type D14 - Satellite Settlers. The number of drivers from Mosaic group C11, communities of country-loving families pursuing a rural idyll in comfortable village homes, many commuting some distance to work are considerably over-represented when relative population is considered, with an index value of 170.

By comparison, residents of active families with adult children and some teens, giving prolonged support to the next generation (Type F23) are those most under-represented in collisions, alongside professional families with children in traditional mid-range suburbs where neighbours are often older (Type G29).

The number of drivers from communities of high achieving families living fast-track lives, advancing careers, finances and their school-age kids’ development (Type B07) and Type H33 - young families and singles setting up home in modern developments that are popular with their peers are consistent with the respective local populations.

Figure 3.21: West Berkshire resident involved drivers, by Mosaic Type (2017-2021)

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

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

The largest number of resident involved drivers come from communities in the less deprived IMD deciles. This is particularly true of the less deprived 20%, and to a lesser extent the less deprived 40%. The least deprived 10% is notably under-represented however with an index value of 81, whilst the less deprived 50% and 40% deciles are over-represented with index values of 114 and 119 respectively. The number of resident drivers involved in collisions from the more deprived 40% decile is under-represented against the relative population with an index value of 79.

Figure 3.22: West Berkshire resident involved drivers, by Index of Multiple Deprivation (2017-2021)

West Berkshire 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 West Berkshire resident drivers involved in a collision.

3.2.3.1 Rates

Figure 3.24 shows the resident young driver involvement rates for West Berkshire compared to the national and regional rates, as well as the most similar comparators.

West Berkshire’s resident young driver involvement rate is 324 drivers per year, per 100,000 population.

Figure 3.24: Annual average West Berkshire resident young involved drivers per 100,000 population (2017-2021)

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

3.2.3.2 Comparisons

West Berkshire’s resident young driver involvement rate remains consistent in 2021 to its position against the national and regional rates in 2020, at 8% and 18% below each respectively. Its rate is slightly higher than previously against the wider Berkshire rate at 11% above; only Slough reports a higher resident young driver involvement rate of all neighbouring authorities. Against similar comparator authorities, West Berkshire continues to be lower than East Hampshire and Horsham, but higher than South Oxfordshire, Aylesbury Vale and Vale of White Horse.

3.2.3.2.1 Residency by Small Area

Figure 3.25 shows the home location of the West Berkshire’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 involvement rates are found in east Lambourn & Great Shefford, east Kintbury & Boxford, north-east and south-east Theale & Beenham and south-west Burghfield Common.

Figure 3.25: West Berkshire resident young involved drivers home location by LSOA, young involved drivers per year per 100,000 population (2017-2021)

West Berkshire 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 West Berkshire’s resident young drivers live provides an insight into those involved in collisions. For an explanation of Mosaic 7 and how to understand the following chart, please refer to section 5.1.1.1.

Figure 3.27 shows West Berkshire’s resident young drivers by the Mosaic type they live in based on their home postcode.

The socio-demographic distribution of young adult drivers involved in collisions remains largely unchanged from 2020 with young drivers from communities of prosperous owners of country houses including affluent families, successful farmers and second-home owners (Type C10) and high achieving families living fast-track lives, advancing careers, finances and their school-age kids’ development (Type B07) most prevalent. In a change from previous years Mosaic Type G29 - professional families with children in traditional mid-range suburbs where neighbours are often older has been replaced by Type G28 - Modern Parents; busy couples in modern detached homes juggling the demands of school-age children and careers.

Figure 3.27: West Berkshire resident young involved drivers, by Mosaic Type (2017-2021)

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

Figure 3.28 shows resident involved young drivers by the IMD of the LSOA (Lower Super Output Area) in which they reside.

The largest number of resident young drivers come from communities in the less deprived IMD deciles. This is particularly true of the less deprived 20% and to a slightly lesser extent the least deprived 40% and least deprived 10% deciles. The less deprived 30% continues to be represented at broadly the level that would be expected based upon population, whilst the least deprived 50% and 40% deciles are over-represented with index values of 119 and 127 respectively.

Figure 3.28: West Berkshire resident young involved drivers, by Index of Multiple Deprivation (2017-2021)

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

3.3 West Berkshire 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 West Berkshire.

3.3.1.1 Rates

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

The resident motorcyclist involvement rate for West Berkshire is 18 riders per year, per 100,000 population.

Figure 3.30: Annual average West Berkshire resident involved motorcyclist per 100,000 population (2017-2021)

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

3.3.1.2 Comparisons

West Berkshire’s motorcyclist involvement rate continues to be approximately one third lower than the national and regional rate and 14% below the rate for Berkshire overall. Of the neighbouring authorities, just Wokingham have a lower rate, whilst the motorcyclist involvement rate for Reading and Slough is around 30% higher. Comparing West Berkshire to other similar comparator authorities, just South Oxfordshire and Aylesbury have lower motorcyclist involvement rates. Vale of White Horse and East Hampshire are very similar while Horsham’s is much higher and similar to Reading.

3.3.1.2.1 Residency by Small Area

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

The highest motorcyclist involvement rates are found in Burghfield Common and Newbury Clay Hill with high rates also in Mortimer & Aldermarston North, Westwood and Hungerford.

Figure 3.31: West Berkshire resident involved motorcyclist home location by LSOA, involved motorcyclist per year per 100,000 population (2017-2021)

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

3.3.1.4 Socio Demographic Analysis

3.3.1.4.1 Age

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

The highest number of resident motorcyclist involved in collisions are aged 17-24 years at nearly twice the number of resident motorcyclist collision-involved riders aged 25-34 or 35-44 years. The age group 17-24 year olds also represent the highest number of resident motorcyclists involved in fatal or serious collisions, followed by those aged 45-54 years.

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

The high number of resident collision-involved motorcyclist riders aged 17-24 years is over-representative of the relative population at 46% above the national index for this age group. Resident motorcyclists aged 25-44 years are also over-represented against their respective local populations with riders aged 35-44 years also above the national index. Resident motorcyclists involved in collisions of all other ages are under-represented relative to the local population.

Figure 3.33: West Berkshire resident involved motorcyclists, by age group (2017-2021)

West Berkshire resident involved motorcyclists, by age group (2017-2021)

Figure 3.34: West Berkshire resident involved motorcyclists, by age group and indexed by population (2017-2021)

West Berkshire resident involved motorcyclists, by age group and indexed by population (2017-2021)

4 West Berkshire 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 West Berkshire

This section refers to all collisions which occurred on West Berkshire’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 West Berkshire compared to the national and regional rates, and those of the most similar comparators.

Between 2017 and 2021, West Berkshire had a collision rate of 14.3 collisions per year, per 100km of road.

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 is half that of the national rate and 61% lower than the collision rate for the South East. As the authority with the lowest collision rate in Berkshire it is also 53% below the overall county rate.

4.1.1.2.1 Collisions by Small Area

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

The highest collision rates can be found in Newbury Central & Greenham and Calcot North & Little Heath.

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 collision in West Berkshire by day of the week and severity. The most collisions occur on Thursdays and Tuesdays with the least collisions on Sundays and Wednesdays.

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

West Berkshire 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. As might be expected there are distinct peaks in the number of collisions occurring during the morning and evening peak periods of 7am- 9am and 4pm - 7pm.

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

West Berkshire 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 a weekend by the hour of the day in which they occurred. Collision numbers are more evenly distributed through the day during the weekend, although there are peaks between 11am-12Noon, 1-2pm and 3-4pm.

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

West Berkshire collisions, by hour of the day during weekends (2017-2021)
4.1.1.5.3 Collision involved drivers who reside in other areas

Just over half of all drivers involved in collisions on West Berkshire’s roads are residents of West Berkshire. Whilst the rest are spread across 78 different authorities in Great Britain, 11% occur in Hampshire, 11% in Reading, 5% in Oxfordshire, 3% in each of Surrey, Wokingham and Wiltshire and 2% in Swindon.

4.1.1.6 Collision dynamics and driver actions

4.1.1.6.1 Collision dynamics

Figure 4.7 shows collisions in West Berkshire by the dynamics resulting in the collision. Multiple vehicle collisions regardless of the point of impact are collectively the most prevalent type of collision occurring. For those vehicles colliding with another, rear impact, no head on is the most common single collision dynamic accounting for 21% of collisions although it is less than those collisions involving no impact between vehicles (35%). Less than 10% of collisions involve head-on or side impact respectively.

Figure 4.7: West Berkshire collisions by collision dynamics (2017-2021)

West Berkshire collisions by collision dynamics (2017-2021)
4.1.1.6.2 Driver actions

Figure 4.8 shows collisions in West Berkshire by the presence of different driver actions. As can be seen in the graph, collisions involving run-off account for the highest percentage of collisions with drivers making a right turn reporting the second highest percentage of collisions. Drivers making a left turn are involved in the fewest percentage of collisions.

Figure 4.8: West Berkshire collisions by driver actions (2017-2021)

West Berkshire collisions by driver actions (2017-2021)

4.1.1.7 Road environment

4.1.1.7.1 Road class

Figure 4.9 shows collisions in West Berkshire by class of road. The largest percentage of collisions occur on unclassified roads, followed by A class roads and the Motorway (M4). This is likely to be proportional to the length of unclassified roads in West Berkshire and the volume of traffic using the motorway.

Figure 4.9: West Berkshire collisions by road class (2017-2021)

West Berkshire collisions by road class (2017-2021)
4.1.1.7.2 Carriageway type

Figure 4.10 shows collisions in West Berkshire by the carriageway type of the road. Following the pattern of collisions on road class, it is no surprise that the largest percentage of collisions occur on single carriageway roads, then dual carriageways.

Figure 4.10: West Berkshire collisions by road carriageway type (2017-2021)

West Berkshire collisions by road carriageway type (2017-2021)
4.1.1.7.3 Junction type

Figure 4.11 shows collisions in West Berkshire by the presence and type of junction. Just over half of collisions are reported to have occurred away from a junction. Of those collisions occurring at junctions, 28% are reported at normal junctions - crossroads or T-junction, 13% at roundabouts and 5% at private drives.

Figure 4.11: West Berkshire collisions by junction type (2017-2021)

West Berkshire collisions by junction type (2017-2021)
4.1.1.7.4 Junction control

Figure 4.12 shows collisions in West Berkshire by the type of junction control (if the collision took place at a junction). Just 11% of the junctions at which collisions are reported to have occurred have been subject to traffic signal control, with the vast majority, 88%, being uncontrolled or Give Way junctions.

Figure 4.12: West Berkshire collisions by junction control (2017-2021)

West Berkshire collisions by junction control (2017-2021)

4.2 Collisions on Urban Roads in West Berkshire

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

4.2.1 Rates

4.2.1.1 Collisions on urban road per 100km of urban road

Figure 4.30 below shows the rate of average annual collisions on urban roads between 2017 and 2021 per 100km of urban road in West Berkshire compared to the national and regional rates, and those of the most similar comparators.

West Berkshire’s urban roads had a collision rate of 19.3 collisions per year, per 100km of urban road length.

Figure 4.30: 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

West Berkshire’s urban roads collision rate is 62% lower than the national rate, 60% lower than the regional rate and 48% lower than the county rate for Berkshire. West Berkshire had the lowest urban roads collision rate in Berkshire and against individual neighbouring authorities.

Collisions on Urban Roads by Small Area

Figure 4.31 shows collisions on urban roads in West Berkshire 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 collision rate on West Berkshire’s urban roads is in north-west Newbury Central & Greenham and Calcot North & Little Heath.

Figure 4.31: 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)

4.2.1.4 Collisions by day of the week

Figure 4.33 shows collisions on urban roads in West Berkshire by day of the week and severity.

The fewest collisions occur on West Berkshire’s urban roads on Sundays and Wednesdays with the highest number occurring on Tuesdays and Thursdays.

Figure 4.33: West Berkshire collisions on urban roads, by day of the week and severity (2017-2021)

West Berkshire collisions on urban roads, by day of the week and severity (2017-2021)

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 4.34 shows collisions on urban roads on weekdays by the hour of the day in which they occurred. The morning peak period, and specifically between 8am and 9am, is when the highest number of collisions occur on West Berkshire’s urban roads, over 200% higher than the 24hour hourly average. The evening peak, between 5-6pm is when the second highest number of collisions occur on the authorities urban roads.

Figure 4.34: West Berkshire collisions on urban roads, by hour of the day during weekdays (2017-2021)

West Berkshire collisions on urban roads, by hour of the day during weekdays (2017-2021)
4.2.1.5.2 Collisions on urban roads by hour of the day on weekends

Figure 4.35 shows collisions on urban roads on a weekend by the hour of the day in which they occurred. The distribution of speeds by hour across the weekend is much more spread out with peaks at 10am, between 1-3pm and 6-8pm. Collisions resulting in serious injury are more prevalent between 2-3pm and 7-8pm.

Figure 4.35: West Berkshire collisions on urban roads, by hour of the day during weekends (2017-2021)

West Berkshire collisions on urban roads, by hour of the day during weekends (2017-2021)

4.2.1.6 Collisions on urban roads by light conditions

Figure 4.36 shows collisions on urban roads in West Berkshire by the light conditions at the time of the collision. Three quarters of all collisions on West Berkshire’s urban roads occur during daylight. Of those collisions occurring during hours of darkness, the majority are under street-lit conditions (22%).

Figure 4.36: West Berkshire collisions on urban roads by light conditions (2017-2021)

West Berkshire collisions on urban roads by light conditions (2017-2021)

4.2.1.7 Collisions on urban roads by weather conditions

Figure 4.37 shows collisions on urban roads in West Berkshire by the weather conditions present at the time of the collision. Whilst the majority of collisions on West Berkshire’s urban roads are during fine and dry weather conditions, of the remainder, the majority (10%) occurred when the weather was wet, without high winds.

Figure 4.37: West Berkshire collisions on urban roads by weather conditions (2017-2021)

West Berkshire collisions on urban roads by weather conditions (2017-2021)
4.2.1.7.1 Collisions on urban roads by driver residency

At a national scale, 50% of collisions on urban roads occur on the driver’s home authority roads. In West Berkshire 61% of the collisions on the urban roads involve drivers who are from West Berkshire. Of the remainder, for a large proportion (22%) the driver residency is unknown but 6% come from Reading, 4% from Hampshire and the rest from other neighbouring authorities.

4.2.1.8 Collision dynamics and driver actions on urban roads

4.2.1.8.1 Collision dynamics

Figure 4.38 shows collisions on urban roads in West Berkshire by the dynamics resulting in the collision. For more information on how collision dynamics are derived, please refer to 5.1.4

Just over a third of collisions on urban roads resulted in no vehicle to vehicle impact. Where multiple vehicles were involved in the collision 16% involved rear vehicle impact, 10% side impact and 9% in head-on, or impact at another point on the vehicle respectively.

Figure 4.38: West Berkshire collisions on urban roads by collision dynamics (2017-2021)

West Berkshire collisions on urban roads by collision dynamics (2017-2021)
4.2.1.8.2 Driver actions

Figure 4.39 shows collisions on urban roads in West Berkshire by the presence of different driver actions. Consistent with the high percentage of multi-vehicle collisions on urban roads resulting in rear or side impact, the driver behaviour with highest percentage of collisions on urban roads is making a right-turn followed by a slow manoeuvre such as stopping.

Figure 4.39: West Berkshire collisions on urban roads by driver actions (2017-2021)

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

4.2.1.9 Urban road environment

4.2.1.9.1 Road class

Figure 4.40 shows collisions on urban roads in West Berkshire by class of road. Typical of urban environments where the majority of roads are unclassified, 57% of collisions on West Berkshire’s urban roads are on those roads of the lowest hierarchy in the road classification system.

Figure 4.40: West Berkshire collisions on urban roads by road class (2017-2021)

West Berkshire collisions on urban roads by road class (2017-2021)
4.2.1.9.2 Carriageway type

Figure 4.41 shows collisions on urban roads in West Berkshire by carriageway type of road. Consistent with the above, 75% of collisions occur on single carriageways.

Figure 4.41: West Berkshire collisions on urban roads by road carriageway type (2017-2021)

West Berkshire collisions on urban roads by road carriageway type (2017-2021)
4.2.1.9.3 Junction type

Figure 4.42 shows collisions on urban roads in West Berkshire by the presence and type of junction. Two thirds of collisions on West Berkshire’s urban roads are split evenly between those that don’t occur at a junction and those occurring at normal junctions such as crossroads or T-junctions. Just a quarter of collisions occur at roundabouts and 7% at private driveways.

Figure 4.42: West Berkshire collisions on urban roads by junction type (2017-2021)

West Berkshire collisions on urban roads by junction type (2017-2021)
4.2.1.9.4 Junction control

Figure 4.43 shows collisions on urban roads in West Berkshire by the type of junction control (if the collision took place at a junction). Only 16% of the collisions occurring at junctions on West Berkshire’s urban roads are subject to traffic signal control with give way or uncontrolled junctions accounting for 83% of collisions at junctions.

Figure 4.43: West Berkshire collisions on urban roads by junction control (2017-2021)

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

4.3 Collisions on Rural Roads in West Berkshire

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

4.3.1 Rates

4.3.1.1 Collisions on rural road per 100km of rural road

Figure 4.66 below shows the rate of average annual collisions on rural roads between 2017 and 2021 per 100km of rural road in West Berkshire compared to the national and regional rates, and those of the most similar comparators.

West Berkshire’s rural roads had a collision rate of 12.9 collisions per year, per 100km of rural road length.

Figure 4.66: 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

West Berkshire’s rural roads collision rate has fallen further (compared to 2020) against the rate for Great Britain and regionally to 12% below the national average and 54% below the rate for the South East. Within Berkshire, West Berkshire has the lowest rural roads collision rate at 41% below the county rate and below neighbouring authorities such as Wokingham (24.2), Slough (128.9) and Windsor & Maidenhead (34).

4.3.1.2.1 Collisions on Rural Roads by Small Area

Figure 4.67 shows collisions on rural roads in West Berkshire 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 roads collision rates are found in Hungerford, east Theale & Beenham, south-east Streatley & Pangbourne and south-west Burghfield Common.

Figure 4.67: 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)

4.3.1.4 Collisions by day of the week

Figure 4.69 shows collisions on rural roads in West Berkshire by day of the week and severity. The total number of collisions on rural roads is fairly consistent across the week. With a weekly average of 101 collisions per day, Sunday has the fewest with 91 collisions and Thursday and Friday the highest with 110 respectively. The most severe collisions (killed and seriously injured) occur on West Berkshire’s rural roads on Tuesdays, followed by Sundays.

Figure 4.69: West Berkshire collisions on rural roads, by day of the week and severity (2017-2021)

West Berkshire collisions on rural roads, by day of the week and severity (2017-2021)

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 4.70 shows collisions on rural roads on weekdays by the hour of the day in which they occurred. The distribution of collisions on rural roads throughout weekdays reveals two distinct peaks between 7-10am and 4-7pm. The severity of collisions throughout the weekday on rural roads is substantially higher between 4-5pm with 15 killed or seriously injured collisions, a minimum of 60% higher than any other hour of the weekday.

Figure 4.70: West Berkshire collisions on rural roads, by hour of the day during weekdays (2017-2021)

West Berkshire collisions on rural roads, by hour of the day during weekdays (2017-2021)
4.3.1.5.2 Collisions on rural roads by hour of the day on weekends

Figure 4.71 shows collisions on rural roads on a weekend by the hour of the day in which they occurred. Unsurprisingly, at weekends there is not the same distribution of collisions corresponding with the AM and PM peak periods. The highest number of collisions on rural roads at weekends occur between 1-2pm and second highest between 11am - 12Noon.

Figure 4.71: West Berkshire collisions on rural roads, by hour of the day during weekends (2017-2021)

West Berkshire collisions on rural roads, by hour of the day during weekends (2017-2021)

4.3.1.6 Collisions on rural roads by light conditions

Figure 4.72 shows collisions on rural roads in West Berkshire by the light conditions at the time of the collision. Similar to collisions on the urban road network of West Berkshire, three quarters of collisions on the authority’s rural roads occur during daylight with just 16% of collisions occurring during darkness, at locations where there is no street-lighting.

Figure 4.72: West Berkshire collisions on rural roads by light conditions (2017-2021)

West Berkshire collisions on rural roads by light conditions (2017-2021)

4.3.1.7 Collisions on rural roads by weather conditions

Figure 4.73 shows collisions on rural roads in West Berkshire by the weather conditions present at the time of the collision. The pattern of collisions by weather conditions on rural roads shows little variation from the percentage of all collisions or those on urban roads by weather condition. Eight-five per cent of collisions on rural roads occur when the weather is fine and dry; the number of collisions on rural roads, compared to all roads or urban roads, when the weather is fog or mist is fractionally higher.

Figure 4.73: West Berkshire collisions on rural roads by weather conditions (2017-2021)

West Berkshire collisions on rural roads by weather conditions (2017-2021)
4.3.1.7.1 Collisions on rural roads by driver residency

Of West Berkshire’s rural roads collisions, 33% of the the drivers involved reside in West Berkshire. This is below the national average percentage of resident involved collisions on rural roads of 50%. The bulk of the remainder of drivers involved in collisions on West Berkshire’s rural roads are from Hampshire (9%), Reading (6%), Oxfordshire (6%) and Swindon (3%).

4.3.1.8 Collision dynamics and driver actions on rural roads

4.3.1.8.1 Collision dynamics

Figure 4.74 shows collisions on rural roads in West Berkshire by the dynamics resulting in the collision. For more information on how collision dynamics are derived, please refer to 4.1.1.6.1.

Single vehicle collisions account for the largest percentage of collisions on rural roads with 35% of the share. Where multiple vehicles are involved, 24% of collisions on rural roads result in rear impact and just 7% head-on impact.

Figure 4.74: West Berkshire collisions on rural roads by collision dynamics (2017-2021)

West Berkshire collisions on rural roads by collision dynamics (2017-2021)
4.3.1.8.2 Driver actions

Figure 4.75 shows collisions on rural roads in West Berkshire by the presence of different driver actions. Consistent with the higher percentage of single vehicle collisions on West Berkshire’s rural roads, the largest percentage of driver behaviour category is vehicles involved in runoff and runoff to the nearside of the carriageway. The smallest percentage of collisions on rural roads involve vehicles making a left turn.

Figure 4.75: West Berkshire collisions on rural roads by driver actions (2017-2021)

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

4.3.1.9 Rural road environment

4.3.1.9.1 Road class

Figure 4.76 shows collisions on rural roads in West Berkshire by class of road. Over two thirds of collisions on roads identified as rural are either classified A roads (36%) or un-classified (38%).

Figure 4.76: West Berkshire collisions on rural roads by road class (2017-2021)

West Berkshire collisions on rural roads by road class (2017-2021)
4.3.1.9.2 Carriageway type

Figure 4.77 shows collisions on rural roads in West Berkshire by carriageway type of road. Consistent with the class of rural road on which collisions tend to occur, 68% of collisions are on single carriageways and 26% on dual carriageways.

Figure 4.77: West Berkshire collisions on rural roads by road carriageway type (2017-2021)

West Berkshire collisions on rural roads by road carriageway type (2017-2021)
4.3.1.9.3 Junction type

Figure 4.78 shows collisions on rural roads in West Berkshire by the presence and type of junction. Having seen earlier that the predominant driver behaviour in collisions on rural roads is vehicle runoff, this is reinforced by the distribution of collisions by junction type where 59% of collisions on rural roads are reported to have occurred away from a junction. Of those collisions that do occur at a junction, 25% are normal junctions such as T-junctions or crossroads.

Figure 4.78: West Berkshire collisions on rural roads by junction type (2017-2021)

West Berkshire collisions on rural roads by junction type (2017-2021)
4.3.1.9.4 Junction control

Figure 4.79 shows collisions on rural roads in West Berkshire by the type of junction control (if the collision took place at a junction). Unsurprisingly when considering rural roads, 91% of collisions occurred at junctions with no formal control - stop sign, traffic signals or authorised person.

Figure 4.79: West Berkshire collisions on rural roads by junction control (2017-2021)

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

4.4 Contributory Factors

Each section below examines trends in reported collisions on West Berkshire’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 4.104 shows collisions on West Berkshire’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.

Of all collisions in West Berkshire between 2017 and 2021 with police officer attendance, 11.1% of collisions were attributed a speed choice CF. This is higher than the percentages seen nationally and regionally in the South East. West Berkshire had the highest percentage of speed choice attributed collisions of all the authorities in Berkshire. This percentage was also higher than all but two of the similar external comparator authorities, with the exceptions being South Oxfordshire and East Hampshire.

Figure 4.104: Percentage of collisions in West Berkshire and comparators where CF306 and/or CF307 were recorded (2017-2021)

Percentage of collisions in West Berkshire 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 4.107 shows collisions on West Berkshire’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.

The percentage of collisions with officer attendance and attributed impairment CFs between 2017 and 2021 remains virtually the same as previous years at a rate of 7.7%. This continues to be higher than the national average, fractionally higher than the percentage seen across Berkshire as a whole and very similar to the percentage for the South East region. Within Berkshire, just Bracknell Forest and Slough have lower rates together with the external comparator authorities of Aylesbury Vale, East Hampshire and Vale of White Horse.

Figure 4.107: Percentage of collisions in West Berkshire and comparators where CF501 and/or CF502 were recorded (2017-2021)

Percentage of collisions in West Berkshire 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 4.110 shows collisions on West Berkshire’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.

Despite the low number of collisions attributed road surface condition CFs in West Berkshire the percentage to total collisions is higher than the national and regional rates, and all other authorities within Berkshire. Only South Oxfordshire reports a higher percentage of collisions attributed with road surface condition CFs of the wider comparative authorities.

Figure 4.110: Percentage of collisions in West Berkshire and comparators where CF101 and/or CF102 and/or CF103 were recorded (2017-2021)

Percentage of collisions in West Berkshire 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 4.113 shows collisions on West Berkshire’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.

Similar to road surface condition related CFs, South Oxfordshire are the only authority to have a higher rate than West Berkshire, although the rate in Vale of White Horse and East Hampshire are very similar. Reading and Slough report the lowest rate of control error related collisions which is likely related to the more built-up, slower speed characteristics of these urban road networks.

Figure 4.113: Percentage of collisions in West Berkshire and comparators where CF408 and/or CF409 and/or CF410 were recorded (2017-2021)

Percentage of collisions in West Berkshire 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 4.116 shows collisions on West Berkshire’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.

West Berkshire’s percentage of collisions attributed unsafe behaviour CFs is very similar to that for Great Britain as a whole, the South East region and the neighbouring authorities of Reading, Windsor & Maidenhead and Wokingham. Bracknell Forest and Slough have higher rates alongside Aylesbury Vale, Horsham, South Oxfordshire and Vale of White Horse.

Figure 4.116: Percentage of collisions in West Berkshire and comparators where CF601 and/or CF602 were recorded (2017-2021)

Percentage of collisions in West Berkshire 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 4.119 shows collisions on West Berkshire’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.

The rate of distraction CF attributed collisions in West Berkshire is the third lowest in Berkshire, above just Bracknell Forest and Reading. It is lower than the national and regional average and lower than all other external comparator authorities, with the exception of East Hampshire.

Figure 4.119: Percentage of collisions in West Berkshire and comparators where CF508 and/or CF509 and/or CF510 were recorded (2017-2021)

Percentage of collisions in West Berkshire 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 4.122 shows collisions on West Berkshire’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.

The national rate for medically unfit related collisions is 2.5%, however West Berkshire’s rate is 5.1%, higher also than the overall county rate of 3.4% and rates for Reading and Slough which are lower than the national rate. East Hampshire and South Oxfordshire have the closest rates to that of West Berkshire at 4.8% and 4.7% respectively.

Figure 4.122: Percentage of collisions in West Berkshire and comparators where CF504 and/or CF505 were recorded (2017-2021)

Percentage of collisions in West Berkshire 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 4.125 shows collisions on West Berkshire’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.

The rate of collisions attributed to CF308 ‘following too close’ across Berkshire and external comparator authorities shows more variation than other contributory factors. West Berkshire has a rate of 5% which is slightly higher than the GB rate, South East regional rate and rates of neighbouring authorities Bracknell Forest, Reading and Wokingham. West Berkshire’s rate is also higher than Aylesbury Vale, Horsham and South Oxfordshire. This leaves Slough, Windsor & Maidenhead, East Hampshire and Vale of White Horse with rates higher than West Berkshire.

Figure 4.125: Percentage of collisions in West Berkshire and comparators where CF308 was recorded (2017-2021)

Percentage of collisions in West Berkshire 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 West Berkshire reside. Thematic maps are used to illustrate the number of casualties per head of population from each small area in West Berkshire. 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 West Berkshire’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 West Berkshire 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 West Berkshire 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 West Berkshire 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 West Berkshire’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 West Berkshire 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 West Berkshire 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 West Berkshire 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 West Berkshire 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 West Berkshire’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 West Berkshire, 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 West Berkshire into context, comparisons with other areas have been made.

Regional

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.

Socio Demographic

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

Table 1 - Comparator Authorities for West Berkshire

Local Authority District
Aylesbury Vale
East Hampshire
Horsham
South Oxfordshire
Vale of White Horse

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 STATS 19 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 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 West Berkshire. 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 West Berkshire’s LSOAs colour coded by dominant Mosaic Type.

Figure 5.1: Dominant Mosaic Types in West Berkshire

Dominant Mosaic Types in West Berkshire

5.3 Data Tables

All Casualties - West Berkshire Residents (3.1.1)
Year Fatal Serious Slight Total
2012 6 54 325 385
2013 2 41 324 367
2014 4 44 289 337
2015 2 53 278 333
2016 3 37 282 322
2017 3 36 235 274
2018 6 39 201 246
2019 4 21 186 211
2020 1 30 153 184
2021 0 27 187 214
Total 31 382 2460 2873
Child Casualties - West Berkshire Residents (3.1.2)
Year Fatal Serious Slight Total
2012 0 6 25 31
2013 0 4 26 30
2014 1 5 33 39
2015 0 4 24 28
2016 0 2 37 39
2017 0 2 26 28
2018 0 1 23 24
2019 0 5 19 24
2020 0 3 13 16
2021 0 2 11 13
Total 1 34 237 272
Pedestrian Casualties - West Berkshire Residents (??)
Year Fatal Serious Slight Total
2012 2 5 20 27
2013 0 6 18 24
2014 1 8 22 31
2015 0 3 18 21
2016 1 2 27 30
2017 0 7 24 31
2018 2 4 22 28
2019 2 4 19 25
2020 0 3 16 19
2021 0 3 11 14
Total 8 45 197 250
Pedal Cycle User Casualties - West Berkshire Residents (3.1.3)
Year Fatal Serious Slight Total
2012 1 9 26 36
2013 0 5 41 46
2014 1 4 32 37
2015 0 12 23 35
2016 0 10 22 32
2017 0 4 25 29
2018 0 7 21 28
2019 0 5 23 28
2020 0 11 23 34
2021 0 1 21 22
Total 2 68 257 327
Motor Vehicle Drivers Involved in Injury Collisions - West Berkshire Residents (3.2.1)
Year Fatal Serious Slight Total
2012 6 67 357 430
2013 6 49 346 401
2014 7 51 336 394
2015 3 47 306 356
2016 5 57 268 330
2017 1 39 243 283
2018 3 44 244 291
2019 4 29 189 222
2020 1 30 151 182
2021 2 36 189 227
Total 38 449 2629 3116
Motorcyclists Involved in Injury Collisions - West Berkshire Residents (3.3.1)
Year Fatal Serious Slight Total
2012 2 12 35 49
2013 0 12 24 36
2014 0 9 24 33
2015 1 10 24 35
2016 0 9 27 36
2017 2 12 18 32
2018 1 16 25 42
2019 1 6 16 23
2020 1 3 16 20
2021 0 8 17 25
Total 8 97 226 331
Young Adult Drivers Involved in Injury Collisions - West Berkshire Residents (3.2.3)
Year Fatal Serious Slight Total
2012 2 17 76 95
2013 0 11 67 78
2014 1 8 55 64
2015 1 10 56 67
2016 1 6 52 59
2017 0 4 47 51
2018 0 9 36 45
2019 1 5 26 32
2020 0 7 26 33
2021 0 7 30 37
Total 6 84 471 561
All Collisions - West Berkshire Roads (4.1)
Year Fatal Serious Slight Total
2012 8 62 277 347
2013 3 45 278 326
2014 6 53 266 325
2015 3 49 242 294
2016 8 53 237 298
2017 1 43 193 237
2018 5 41 161 207
2019 9 32 169 210
2020 3 35 132 170
2021 4 31 158 193
Total 50 444 2113 2607
Urban Collisions - West Berkshire Roads (4.2)
Year Fatal Serious Slight Total
2012 2 14 83 99
2013 0 12 84 96
2014 2 14 81 97
2015 0 17 86 103
2016 2 8 55 65
2017 0 14 57 71
2018 1 14 47 62
2019 2 8 62 72
2020 0 8 30 38
2021 0 5 56 61
Total 9 114 641 764
Rural Collisions - West Berkshire Roads (4.3)
Year Fatal Serious Slight Total
2012 6 48 194 248
2013 3 33 194 230
2014 4 39 185 228
2015 3 32 156 191
2016 6 45 182 233
2017 1 29 136 166
2018 4 27 114 145
2019 7 24 107 138
2020 3 27 102 132
2021 4 26 102 132
Total 41 330 1472 1843
Collisions by Hour of the Day (Weekdays) - West Berkshire Roads (4.1.1.5)
Time of Day Fatal Serious Slight Total
Midnight 0 1 2 3
1am 0 2 1 3
2am 0 0 4 4
3am 0 1 4 5
4am 1 1 3 5
5am 0 2 6 8
6am 0 2 15 17
7am 3 6 37 46
8am 0 13 67 80
9am 2 4 38 44
10am 2 4 27 33
11am 1 6 26 33
Noon 1 7 30 38
1pm 1 6 34 41
2pm 0 7 40 47
3pm 2 8 41 51
4pm 1 18 51 70
5pm 1 9 57 67
6pm 1 8 44 53
7pm 0 9 30 39
8pm 0 5 23 28
9pm 2 6 13 21
10pm 0 1 17 18
11pm 1 4 8 13
Total 19 130 618 767
Collisions by Hour of the Day (Weekends) - West Berkshire Roads (4.1.1.5)
Time of Day Fatal Serious Slight Total
Midnight 0 0 1 1
1am 0 0 3 3
2am 0 2 1 3
3am 0 2 1 3
4am 0 0 1 1
6am 0 3 2 5
7am 0 0 4 4
8am 0 0 10 10
9am 0 1 8 9
10am 0 5 10 15
11am 1 6 16 23
Noon 0 1 15 16
1pm 0 3 24 27
2pm 1 4 14 19
3pm 0 6 16 22
4pm 0 1 15 16
5pm 0 3 13 16
6pm 1 2 12 15
7pm 0 3 9 12
8pm 0 3 6 9
9pm 0 2 3 5
10pm 0 3 5 8
11pm 0 2 6 8
Total 3 52 195 250
Collisions Involving Factors 306 and/or 307 (Speed Related) - West Berkshire Roads (4.4.1)
Year Fatal Serious Slight Total
2012 2 3 33 38
2013 1 7 34 42
2014 1 7 23 31
2015 0 6 24 30
2016 3 11 28 42
2017 0 6 21 27
2018 0 6 13 19
2019 0 3 11 14
2020 1 2 13 16
2021 1 2 10 13
Total 9 53 210 272
Collisions Involving Factors 501 and/or 502 (Impairment Related) - West Berkshire Roads (4.4.2)
Year Fatal Serious Slight Total
2012 0 4 16 20
2013 0 4 11 15
2014 2 3 8 13
2015 0 3 9 12
2016 3 10 8 21
2017 0 0 5 5
2018 0 8 7 15
2019 0 3 14 17
2020 0 7 3 10
2021 0 4 11 15
Total 5 46 92 143
Collisions Involving Factors 101 and/or 102 and/or 103 (Road Surface Related) - West Berkshire Roads (4.4.3)
Year Fatal Serious Slight Total
2012 0 6 37 43
2013 0 5 38 43
2014 3 6 28 37
2015 0 4 18 22
2016 0 8 33 41
2017 0 3 25 28
2018 1 3 17 21
2019 0 4 9 13
2020 0 4 12 16
2021 1 3 10 14
Total 5 46 227 278
Collisions Involving Factors 408 and/or 409 and/or 410 (Control Error Related) - West Berkshire Roads (4.4.4)
Year Fatal Serious Slight Total
2012 3 13 75 91
2013 2 13 64 79
2014 4 14 65 83
2015 0 12 43 55
2016 3 10 44 57
2017 0 10 37 47
2018 1 10 29 40
2019 2 8 27 37
2020 2 7 21 30
2021 0 6 20 26
Total 17 103 425 545
Collisions Involving Factors 601 and/or 602 (Unsafe Behaviour Related) - West Berkshire Roads (4.4.5)
Year Fatal Serious Slight Total
2012 0 9 39 48
2013 0 10 26 36
2014 1 10 39 50
2015 0 4 31 35
2016 3 18 25 46
2017 0 8 27 35
2018 0 4 24 28
2019 2 5 23 30
2020 1 8 16 25
2021 0 10 20 30
Total 7 86 270 363
Collisions Involving Factors 508 and/or 509 and/or 510 (Distraction Related) - West Berkshire Roads (4.4.6)
Year Fatal Serious Slight Total
2012 0 1 17 18
2013 0 1 16 17
2014 0 4 15 19
2015 0 2 12 14
2016 2 5 11 18
2017 0 1 7 8
2018 0 1 7 8
2019 0 1 5 6
2020 0 0 7 7
2021 0 1 5 6
Total 2 17 102 121
Collisions Involving Factors 504 and/or 505 (Medically Unfit) - West Berkshire Roads (4.4.7)
Year Fatal Serious Slight Total
2012 1 0 5 6
2013 0 3 12 15
2014 1 3 12 16
2015 0 2 3 5
2016 0 4 1 5
2017 0 2 5 7
2018 0 1 5 6
2019 1 2 6 9
2020 0 2 3 5
2021 1 4 9 14
Total 4 23 61 88
Collisions Involving Factors 308 (Close Following Related) - West Berkshire Roads (4.4.8)
Year Fatal Serious Slight Total
2012 0 2 22 24
2013 0 2 17 19
2014 0 1 13 14
2015 0 1 16 17
2016 0 3 11 14
2017 0 0 13 13
2018 0 0 4 4
2019 1 0 7 8
2020 0 0 6 6
2021 0 1 8 9
Total 1 10 117 128

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.

  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↩︎