Area Profile 2014 - Royal Borough of Windsor and Maidenhead

August 2014

Prepared by:

2014 WINDSOR AND MAIDENHEAD COUNCIL

Executive Summary

Whilst performance on reducing injury collisions in the Royal Borough of Windsor and Maidenhead was strong in

2013 (among the lowest ever annual count of reported injury collisions), risk to some vulnerable road user groups

remains a concern and the level of road risk per kilometre in the borough is above the national average; albeit

significantly below more dense urban conurbations such as neighbouring Reading.

This ‘Area Profile’, compiled by Road Safety Analysis, compares road safety performance in the area with that of

neighbouring authorities. Utilising a variety of analytical techniques, casualty and collision trends are scrutinised for

social, economic, demographic and geo-spatial variance that might highlight areas of improvement or indicate the

need for continued investment.

Windsor and Maidenhead’s resident casualty rate is below the national rate and comparable to the rest of Berkshire.

More of the collision involved drivers from the borough actually experience their incident on roads in other areas,

most notably Surrey, Slough, Buckinghamshire and Bracknell. The Mosaic analysis shows that affluence and mobility

are factors attributable to the most overrepresented drivers (based on resident population) who are broadly

classified as busy executives, business leaders and comfortably off suburban families. When further scrutinised, by

average annual mileage, drivers from less affluent communities emerge more strongly.

Pedestrian casualties have risen slightly over a couple of years with the total in 2013 (46) the highest number

recorded since 2009. Nevertheless, the borough’s resident pedestrian casualty rate is 50% lower than the national

average, though in the urban areas of Windsor, Maidenhead and Datchet casualty rates are higher; this rate has

shown very little change in recent years.

Thankfully, 2013 showed a continuation in the trend for zero child fatalities in the borough, although the total

number of children injured has fluctuated somewhat year on year. The resident child casualty continues to

outperform the national benchmark, remaining 37% below the average across the country.

One area where casualty rates are higher than the national average is among resident pedal cyclists, with residents

of Windsor, Eton and Maidenhead being at the highest risk of collision involvement. The total count in 2012 (46) was

lower than the peak in 2011 (51), but the proportion of cycle casualties sustaining serious injuries (28%) was at its

highest level in recent years.

The rate at which resident motorcycle riders are involved in collisions is also higher than the national average, with

riders more likely to come from Ascot, Old Windsor and Wraysbury. The positive news is that the trend is currently

downward.

Windsor and Maidenhead has the highest proportion of drug and alcohol related crashes (7.5%) in the county when

contributory factors are taken into account, markedly above the Berkshire average (6.0%). Although numbers are

low overall, 2013 saw a sharp upturn in distraction related collisions as well.

Finally Windsor and Maidenhead’s young resident driver rate is 25% higher than the national rate and is 22% higher

than the Berkshire average. Higher rates can be seen to the north of Maidenhead; in the Fifield and Holyport area;

and South of Windsor around Old Windsor, Datchet and Wraysbury. Nearly one in three of the casualties arising

from these crashes is a passenger.

Contents

1 INTRODUCTION .............................................................................................................................................. 3

1.1 OVERVIEW ....................................................................................................................................................... 3

1.1.1 Background ........................................................................................................................................... 3

1.1.2 Aims and Objectives .............................................................................................................................. 3

1.1.3 Analytical Techniques ........................................................................................................................... 3

1.2 PROFILE CONFIGURATION .................................................................................................................................... 7

1.2.1 Structure ............................................................................................................................................... 7

1.2.2 Scope ..................................................................................................................................................... 7

2 RESIDENT RISK ................................................................................................................................................ 9

2.1 RESIDENT CASUALTIES ........................................................................................................................................ 9

2.1.1 All Resident Casualties .......................................................................................................................... 9

2.1.2 Resident Pedestrian Casualties ........................................................................................................... 15

2.1.3 Resident Pedal Cyclist Casualties ........................................................................................................ 18

2.1.4 Child Resident Casualties .................................................................................................................... 21

2.2 RESIDENT MOTOR VEHICLE USERS ...................................................................................................................... 24

2.2.1 All Resident Drivers and Riders involved in Collisions ......................................................................... 24

2.2.2 Resident Motorcyclists involved in Collisions ...................................................................................... 29

2.2.3 Young adult resident Drivers involved in Collisions ............................................................................. 32

3 ROAD NETWORK RISK .................................................................................................................................. 37

3.1 COLLISIONS ON ALL ROADS ................................................................................................................................. 37

3.1.1 Rates ................................................................................................................................................... 37

3.1.2 Comparisons ....................................................................................................................................... 37

3.1.3 Trends ................................................................................................................................................. 38

3.1.4 Casualty trends on all roads ................................................................................................................ 41

3.1.5 Contributory Factors ........................................................................................................................... 44

3.2 COLLISIONS ON ROADS BY ENVIRONMENT ............................................................................................................. 50

3.2.1 Urban Roads ....................................................................................................................................... 50

3.2.2 Rural Roads ......................................................................................................................................... 51

4 APPENDICES ................................................................................................................................................. 55

4.1 MOSAIC PUBLIC SECTOR ................................................................................................................................... 55

4.1.1 Complete list of Mosaic Types ............................................................................................................. 55

4.1.2 Profile and distribution for selected Mosaic Types ............................................................................. 57

4.2 DATA TABLES .................................................................................................................................................. 59

4.3 CONTRIBUTORY FACTOR GROUPINGS ................................................................................................................... 64

AREA PROFILE 2014 – ROYAL BOROUGH OF WINDSOR AND MAIDENHEAD

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1 Introduction

1.1 Overview

1.1.1 Background

Area Profiles from Road Safety Analysis (RSA) 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 Windsor and

Maidenhead, as well as casualties and drivers involved in collisions anywhere in Britain who reside in the Windsor

and Maidenhead area.

1.1.2 Aims and Objectives

The aim of this document is to provide a comprehensive profile of road safety issues affecting both Windsor and

Maidenhead’s road network and Windsor and Maidenhead’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.

RSA’s analysis tool MAST Online has also been used to investigate trends for Windsor and Maidenhead’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 Windsor and Maidenhead’s key road safety issues with those of

comparator regions and national figures. The aim is to allow Windsor and Maidenhead to assess its progress

alongside other areas, and work together with neighbours to address common issues.

1.1.3 Analytical Techniques

This section details the analytical techniques employed throughout the Area Profile.

1.1.3.1 Resident road users

Casualty and driver postcodes in STATS 19 make it possible to identify where casualties from Windsor and

Maidenhead reside. Thematic maps are used to illustrate the number of casualties per head of population from each

small area in Windsor and Maidenhead. 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 used are super output areas

as defined by the Office of National Statistics. 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.

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

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MAST Online has been used to determine the casualty figures for Windsor and Maidenhead’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

Windsor and Maidenhead who are involved in collisions, either as casualties or motor vehicle users. Socio-

demographic profiling examines age and gender breakdowns, and for some road user groups includes analysis using

Mosaic Public Sector segmentation, deprivation and/or rurality. More information on Mosaic is provided later in this

section.

Mosaic Public Sector

Insight into the lifestyles of Windsor and Maidenhead resident road casualties and motor vehicle users can be

provided through socio demographic analysis. RSA Mosaic profiling uses Experian’s Mosaic Public Sector cross-

channel classification system2, which is assigned uniquely for each casualty and vehicle user based on individual

postcodes in STATS 19 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 Windsor and Maidenhead 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 69 Types.

Each Group embraces between 3 and 9 Types. A complete list of Mosaic Types is provided in 4.1.1 on page 55 whilst

profiles and distribution for the Mosaic Types identified in this Area Profile as providing insight on Windsor and

Maidenhead’s residents are detailed in 4.1.2 on page 57.

This profile displays Mosaic analysis as Area/Column combination charts, to facilitate quick and easy insight into

residents and relative risk. In these charts, the shaded background area denotes the absolute number of Windsor

and Maidenhead resident casualties or drivers in each Mosaic Type, corresponding to the value axis to the left of

the chart. The columns in the foreground provide an index for each Mosaic Type. These indices are 100 based, where

a value of 100 indicates the number of casualties or drivers shown by the corresponding point in the area is exactly

in proportion to the population of communities in Windsor and Maidenhead where that Type 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.

2 See Appendix B below, or go to http://www.experian.co.uk/marketing-services/products/mosaic-uk.html

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Deprivation

Deprivation levels are examined using UK Index of Multiple Deprivation (IMD) values. IMD is calculated by the Office

of 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 Windsor and

Maidenhead, and can be interpreted in the same way as indices on Mosaic charts as explained in the preceding

section.

Rurality

National rurality classification systems have also been developed to define the rurality of small area geographies.

Each of these small areas was defined as either ‘Urban’ (defined as settlements with over 10,000 residents), ‘Rural’,

or ‘Town’ (a sub-class of ‘Rural’ for settlements under 10,000 residents). STATS19 postcodes for resident road users

from Windsor and Maidenhead have been used to determine the rurality of residents.

1.1.3.2 Collisions

MAST Online has been used to determine annual average road injury collision levels for Windsor and Maidenhead

and relevant comparator areas. Dividing this annual rate by road length in each area generates an annual crash rate

per kilometre of road, which allows direct comparisons to be made between authorities. Road length data have been

taken from central government figures. Charts have been devised which compare local rates with the equivalent

figures for Great Britain. Most similar comparators at district level cannot be included, as road length data is only

available at highway authority level.

Trend analysis examines numbers of collisions on Windsor and Maidenhead’s roads over time and by severity, with

additional trends explored depending on road type. In order to determine the distribution of collisions within

Windsor and Maidenhead, maps show the number of collisions in each small area, divided by the total road length

(in kilometres) within that small area.

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 to 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.

Environment - urban and rural roads

The national urban-rural road classification is only defined in datasets prepared by the Department for Transport,

so it is not possible to define the rurality of individual roads on the basis of collision location data alone. Therefore,

where it is necessary to distinguish between collisions on urban and rural roads, this profile uses data from MAST

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Online. Annual average collisions by rurality and total network urban and rural road lengths have been used to

generate annual collision rates per kilometre of road, which facilitates direct comparison between areas.

1.1.3.3 Comparators

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

This section details the types of comparators used in this Area Profile.

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 Windsor

and Maidenhead’s most similar authorities have been selected using Mosaic classification. Because of the size of

Windsor and Maidenhead only district authorities have been selected for comparison. The chosen five districts are:

Local Authority District

Brentwood Borough

Elmbridge Borough

Guildford Borough

Reigate and Banstead Borough

Waverley Borough

1.1.3.4 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.

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 4.3.


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1.2 Profile Configuration

1.2.1 Structure

The Area Profile has been divided in to separate analysis of key road user groups. The aim is to allow each section to

be used independently if required.

Section 2, starting on page 9, explores Resident Risk. Resident risk analysis includes examining all Windsor and

Maidenhead’s resident casualties and resident motor vehicle users in terms of rates; comparisons with other

relevant 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 Windsor and Maidenhead

are involved in collisions, rather than what happens on local roads.

Section 3, starting on page 37, provides analysis of Road Network Risk. It also examines rates; comparisons; location

by small area; and trends on Windsor and Maidenhead’s roads. Breakdowns by type of road are also included in this

section.

Section 4, starting on page 55, includes Appendices, detailing all of the Mosaic Types and the profile and distribution

of specific Mosaic Types relevant to Windsor and Maidenhead. It also contains data tables of all the analysis referred

to in this Area Profile.

1.2.2 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 Windsor and Maidenhead, regardless of where in

Britain the collision occurred. Resident analysis in this profile is based on the national STATS19 dataset as provided

to RSA by the Department for Transport for publication in MAST Online over the five year period between 2008 and

2012 inclusive. For a more complete explanation, please refer to 1.1.3.1 on methodology for calculating resident

risk.

In contrast, the road network section covers collisions which occurred on Windsor and Maidenhead’s roads,

regardless of where those involved reside. Network analysis is based on local police data supplied to RSA by

authorities in Berkshire over the five year period between 2009 and 2013 inclusive. For a more complete

explanation, please refer to 1.1.3.2 on methodology for calculating network collision risk.



2 Resident Risk

For information about the provenance and scope of data included in this section, please refer to 1.2.2 on page 7. For

an explanation of the methodologies employed throughout this section, please refer to 1.1.3.1 on page 3.

2.1 Resident Casualties

This section refers to casualties who were residents of Windsor and Maidenhead. For information about casualties

on Windsor and Maidenhead’s roads, please refer to 3.1.4.1 on page 41.

2.1.1 All Resident Casualties

2.1.1.1 Rates

Figure 1 shows Windsor and Maidenhead’s resident casualty rate compared to the other Berkshire authorities, most

similar comparator authorities and the national and regional rates.

Figure 1 – Annual average resident casualties (2008-2012) per 10,000 population.

2.1.1.2 Comparisons

Windsor and Maidenhead’s resident casualty rate of 30.0 is below the national rate. It has a lower resident casualty

rate than the South East rate and is the same as the Berkshire rate. Within Berkshire, Windsor and Maidenhead has

the third lowest resident casualty rate behind West Berkshire and Wokingham. Windsor and Maidenhead’s resident

casualty rate is lower than all of its most similar comparator authorities apart from Brentwood.

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Internal

Figure 2 shows Windsor and Maidenhead’s resident casualties’ home location by LSOA. There is no clear pattern to

the distribution with high resident casualty rates scattered across Windsor and Maidenhead. The higher rates can

be found around Horton, Wraysbury and north of Maidenhead.

Figure 2 - Resident casualties home location by LSOA. Casualties per year per 10,000 population (2008-2012).

2.1.1.3 Trends

Figure 3 shows Windsor and Maidenhead resident casualty numbers by severity. This includes Windsor and

Maidenhead residents injured anywhere in the country. Also shown is a 3 year moving average trend line. Resident

casualties increased up to 2006 but have generally reduced since. There were 401 Windsor and Maidenhead

residents injured in collisions in 2012 compared to 457 in 2011. KSI resident casualty numbers have fluctuated but

have remained at a similar level over the past decade. Over the past five years, 11% of Windsor and Maidenhead’s

resident casualties were either killed or seriously injured, compared to 12% nationally.


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Figure 3 - Windsor and Maidenhead resident casualties, by year (2004-2012).

Resident Casualties occurring in other areas

Windsor and Maidenhead residents are mostly involved in collisions on the roads of Windsor and Maidenhead. Fifty-

two percent of Windsor and Maidenhead’s resident casualties between 2008 and 2012 were injured in Windsor and

Maidenhead. This is lower than the national average with 65% of residents involved in collisions in their home

highway authority. Of the remaining 48% of Windsor and Maidenhead resident casualties, the majority are involved

in collisions in nearby highway authorities including Surrey (9%), Slough (9%), Buckinghamshire (7%), Bracknell

Forest (5%) and Wokingham (3%).

2.1.1.4 Socio Demographic Analysis

Age

Figure 4 shows the numbers of resident casualties by age group. The age group with most resident casualties is the

16-24 group. There are less resident casualties aged 65 and over or aged under 16. Figure 5 shows resident casualty

numbers by age group indexed by the population of those age groups in Windsor and Maidenhead. There is also a

national index value for comparison. The chart shows that 16-24 year olds are over-represented as casualties when

indexing based on population. It also shows that Windsor and Maidenhead’s 16-24 year olds are over-represented

compared to 16-24 year olds nationally. Residents in the 25-34 and 35-44 age groups are also over-represented

when taking population in to account but are similarly over-represented compared to the country as a whole.

Residents aged under 16 and aged 55 and over are at a lower risk of being casualties.

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Figure 4 - Windsor and Maidenhead resident casualties by age group (2008-2012).

Figure 5 - Resident casualties by age group, indexed by population (2008-2012).

Segmentation

Analysis of the Mosaic communities in which Windsor and Maidenhead’s resident casualties live provides an insight

into those injured in collisions. For an explanation of methodology and how to understand the following chart, please

refer to 1.1.3.1 on page 3. For more information on Mosaic Public Sector, please refer to 4.1 on page 55.

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Figure 6 - Windsor and Maidenhead resident casualties by Mosaic Type, 2008-2012.

Figure 6 shows Windsor and Maidenhead’s resident casualties by the Mosaic Type of the postcode in which they

live. The red bars show the index value based on the population of those Types living in Windsor and Maidenhead.

The highest numbers of resident casualties come from Busy executives in town houses in dormitory settlements (Type

F22) and Comfortably off suburban families weakly tied to their local community (Type E17). These Types are also

over-represented when taking population in to account.

Successful older business leaders living in sought after suburbs (Type C9) also have high numbers of casualties but

they are under-represented based on the population of these Types living in Windsor and Maidenhead.

Well off commuters living in spacious houses in semi-rural settings (Type D15) and Often indebted families living in

low rise estates (Type K51) contain a large number of resident casualties and these Types are also over-represented

when population is taken in to account. For Type K51 Indexing by annual average mileage produces a higher index

value which suggests that this Type are at a higher risk considering the number of miles they typically drive.

Although overall numbers are lower, Middle aged couples and families in right-to-buy homes (Type K48) are over-

represented as casualties based on their population within Windsor and Maidenhead.

Further information on the characteristics of some of these Mosaic Types and a thematic map showing areas where

these communities live can be found in 4.1.2 on page 57.

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Deprivation

Figure 7 shows resident casualties by the IMD of the LSOA in which they reside. The chart shows that in absolute

terms there are many more casualties from less deprived communities. However, when casualties are indexed by

overall deprivation within Windsor and Maidenhead, as shown by the red index bars, the least deprived

communities are slightly under-represented. Communities which are a little less or a little more deprived than the

national norm are slightly over-represented.

Figure 7 - Resident casualties by Index of Multiple Deprivation (2008-2012).

Rurality

Using the DfT’s rurality classification, 84% of Windsor and Maidenhead’s population live in urban LSOAs. In England

and Wales, 81% of the population live in urban LSOAs so Windsor and Maidenhead has a slightly higher proportion

of its population living in urban areas. Of Windsor and Maidenhead’s resident casualties injured between 2008 and

2012, 80% live in urban LSOAs meaning there is a slight under-representation for urban residents and a slight over-

representation for rural residents, although this doesn’t take in to account the annual distance travelled.

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2.1.2 Resident Pedestrian Casualties

This section refers to pedestrian casualties who are residents of Windsor and Maidenhead. For information about

pedestrian casualties on Windsor and Maidenhead’s roads, please refer to 3.1.4.3 on page 42.

2.1.2.1 Rates

Figure 8 shows Windsor and Maidenhead’s resident pedestrian casualty rate compared to the other Berkshire

authorities, most similar comparator authorities and the national and regional rates.

Figure 8 – Annual average resident pedestrian casualties per 100,000 population (2008-2012).

2.1.2.2 Comparisons

Windsor and Maidenhead’s resident pedestrian casualty rate is 50% lower than the national rate. It is lower than

both the South East rate (31% lower) and the overall Berkshire rate (23% lower). Out of the six Berkshire authorities,

Windsor and Maidenhead has a much lower rate than Slough and Reading. It has a similar rate to Wokingham but is

higher than West Berkshire and Bracknell Forest. Windsor and Maidenhead has a similar rate to Brentwood and has

a lower rate than all the rest of its most similar comparator authorities.

Internal

Figure 9 shows Windsor and Maidenhead’s resident pedestrian casualties by MSOA. There are high pedestrian

casualty rates in the MSOAs in and around the urban areas of Windsor, Maidenhead and Datchet.

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Figure 9 - Windsor and Maidenhead resident pedestrian casualties by MSOA. Casualties per year per 100,000 population.

2.1.2.3 Trends

Resident pedestrian casualties in Windsor and Maidenhead generally haven’t changed much over recent years, as

shown in Figure 10. There were 32 pedestrian casualties from Windsor and Maidenhead in 2012, which is the same

number as there were in 2011. In the past five year period (2008-2012) 23% of resident pedestrian casualties were

either killed or seriously injured, which is the same as the national percentage.


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Figure 10 - Windsor and Maidenhead's resident pedestrian casualties, by year (2004-2012).

Resident Pedestrian Casualties occurring in other areas

Between 2008 and 2012, 72% of Windsor and Maidenhead’s resident pedestrian casualties were involved in

collisions on Windsor and Maidenhead’s roads. Nationally, 82% of a highway authorities residents are involved in

collisions within their home authority.

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2.1.3 Resident Pedal Cyclist Casualties

This section refers to all pedal cyclist casualties who are residents of Windsor and Maidenhead. For information

about all pedal cycle casualties on Windsor and Maidenhead’s roads, please refer to 3.1.4.4 on page 43.

2.1.3.1 Rates

Figure 11 shows resident pedal cycle user casualty rates for Windsor and Maidenhead, Berkshire highway authorities

and Windsor and Maidenhead’s most similar authorities. Also included for comparison are the national rate and the

South East rate.

Figure 11 – Annual average resident pedal cycle user casualties per 100,000 population rate (2008-2012).

2.1.3.2 Comparisons

Windsor and Maidenhead’s resident pedal cycle user casualty rate is higher than the national average. It is also

higher than both the South East rate and the overall Berkshire rate. Within Berkshire, Windsor and Maidenhead has

the third highest rate behind Reading and Slough. Windsor and Maidenhead’s resident pedal cycle user rate is higher

than the comparator authorities of Brentwood and Waverley but is lower than Elmbridge, Guildford and Reigate and

Banstead.

Internal

Figure 12 shows Windsor and Maidenhead’s resident pedal cycle user casualties by home MSOA. Higher rates are

found in MSOAs in Windsor, Eton, and Maidenhead.

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Figure 12 - Resident pedal cycle user casualties by MSOA. Annual average casualties (2008-2012) per 100,000 population.

2.1.3.3 Trends

Figure 13 shows Windsor and Maidenhead’s resident pedal cycle casualty numbers since 2004, by severity. Casualty

numbers have increased over the past decade. There has been a steady increase up to a peak of 61 in 2011. There

was a reduction in 2012 to 46. In the period 2008-2012, 14% of pedal cycle user casualties were either killed or

seriously injured, compared to 16% across Britain as a whole.


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Figure 13 - Resident pedal cycle user casualties, by year (2004-2012).

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2.1.4 Child Resident Casualties

This section refers to all child casualties who are residents of Windsor and Maidenhead. For an explanation of the

methodologies employed throughout this section, please refer to 1.1.3.1 on page 3.

2.1.4.1 Rates

Figure 14 shows child resident casualty rates for Windsor and Maidenhead, other Berkshire authorities and most

similar comparator authorities.

Figure 14 – Annual average child resident casualties (2008-2012) per 10,000 population (of 0-15 year olds).

2.1.4.2 Comparisons

Windsor and Maidenhead’s child resident casualty rate is significantly lower than the national average (37%). It is

21% lower than the South East rate and 6% lower than the overall Berkshire rate. Within Berkshire, Windsor and

Maidenhead has the third highest rate behind Slough and Reading. Windsor and Maidenhead’s child resident

casualty rate is lower than the most similar authorities of Reigate and Banstead and Waverley. It is the same as

Guildford but is higher than Brentwood and Elmbridge.

Internal

Figure 15 shows Windsor and Maidenhead’s child resident casualties by MSOA. There are higher rates in the Fifield

and Holyport area as well as to the north of Maidenhead and to the east of Windsor in the areas around Datchet

and Old Windsor.

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Figure 15 - Child resident casualties by MSOA (2008-2012). Annual average casualties per 10,000 child population.

2.1.4.3 Trends

Figure 16 shows child resident casualties since 2004, by severity. Casualty numbers have fluctuated over recent years

with little overall change. There were 33 child casualties from Windsor and Maidenhead in 2012, the same number

as there were in 2011. In the past five year period (2008-2012) 10% of child casualties were either killed or seriously

injured, compared to 13% across Britain.


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Figure 16 - Child resident casualties, by year (2004-2012).

Child Resident Casualties occurring in other areas

Seventy-four percent of Windsor and Maidenhead’s child resident casualties were injured on Windsor and

Maidenhead’s roads with the rest injured mainly in nearby authorities including Slough (8%) and Surrey (7%).

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2.2 Resident Motor Vehicle Users

2.2.1 All Resident Drivers and Riders involved in Collisions

This section refers to all drivers and riders involved in collisions and who are residents of Windsor and Maidenhead,

regardless of where the collision took place. For an explanation of the methodologies employed throughout this

section, please refer to 1.1.3.1 on page 3. Only adult drivers (aged 16 and over) of motorised vehicles are included

in this section.

2.2.1.1 Rates

Figure 17 shows resident driver rates for Windsor and Maidenhead, most similar authorities and other Berkshire

authorities.

Figure 17 – Annual average resident drivers (2008-2012) per 10,000 adult population.

2.2.1.2 Comparisons

Windsor and Maidenhead’s resident driver rate is 16% lower than the national rate. It is 7% lower than the South

East rate and is similar to the overall Berkshire rate. Windsor and Maidenhead has the third highest resident driver

rate within Berkshire behind Slough and Bracknell Forest. Windsor and Maidenhead has a lower resident driver rate

than all of its most similar comparator authorities apart from Brentwood.

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Internal

Figure 18 shows Windsor and Maidenhead’s resident collision involved drivers’ home location by LSOA. Higher rates

are shown to the east around Horton and Wraysbury; in and around Bray; to the north of Maidenhead; and in the

area around Shurlock Row and Waltham Saint Lawrence.

Figure 18 - Annual average resident drivers (2008-2012) per 10,000 adult population, by LSOA.

2.2.1.3 Trends

Figure 19 shows Windsor and Maidenhead’s annual resident motor vehicle driver numbers by severity. There has

been a general reduction in resident driver numbers over the past decade. In 2012 there was a reduction to 484

from 553 in 2011. In the most recent five year period (2008-2012) 14% of Windsor and Maidenhead’s resident drivers

have been involved in a collision resulting in a killed or seriously injured casualty, compared to the national

percentage of 13.5%.


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Figure 19 - Windsor and Maidenhead's resident drivers, by year (2004-2012).

Resident Driver crash involvement in other areas

Forty-seven percent of Windsor and Maidenhead’s resident drivers are involved in collisions on Windsor and

Maidenhead’s roads. Of the other authorities, 10% of resident drivers are involved in collisions in Surrey; 10% in

Slough; 7% in Buckinghamshire and 5% in Bracknell Forest.


Segmentation

Analysis of the Mosaic communities in which Windsor and Maidenhead’s resident drivers and riders live provides an

insight into those involved in collisions. For an explanation of methodology and how to understand the following

chart, please refer to 1.1.3.1 on page 3. For more information on Mosaic Public Sector, please refer to 4.1 on page

55.

Figure 20 shows resident drivers by Mosaic Type. The red bars show the index value when resident driver numbers

are indexed by the annual average mileage of those Types living in Windsor and Maidenhead.

As with the resident casualty Mosaic analysis, the highest driver numbers come from Busy executives in town houses

in dormitory settlements (Type F22). Although driver numbers are the highest this Type is at the expected collision

involvement level based on annual average mileage typically travelled by this Type.

Successful older business leaders living in sought after suburbs (Type C9) and Comfortably off suburban families

weakly tied to their local community (Type E17) also have high driver numbers. Type C9 is under-represented when

annual mileage is taken in to account, whereas E17 is slightly over-represented.

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Often indebted families living in low rise estates (Type K51) are also involved in a high number of collisions as drivers

and are over-represented based on mileage.

Industrial workers living comfortably in owner occupied semis (Type E18), Middle aged couples and families in right-

to-buy homes (Type K48) and Childless new owner occupiers in cramped new homes (Type H35) all have lower driver

collision involvement numbers but are over-represented when taking mileage in to account.

Figure 20 - Windsor and Maidenhead resident drivers by Mosaic Type.

More information on the characteristics of the communities from some of these Mosaic Types and a thematic map

showing the areas where they live can be found in 4.1.2 on page 57.

Deprivation

Figure 21 shows Windsor and Maidenhead’s resident drivers by IMD. As with resident casualty trends, the chart

shows that in absolute terms there are many more drivers from the least deprived communities. Drivers from these

communities are slightly under-represented when population is taken in to account. Communities which are a little

more deprived than the national norm or a little less deprived than the national norm are slightly over-represented.

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Figure 21 - Resident drivers by IMD (2008-2012).

Rurality

As with resident casualties, resident driver involvement by rurality shows a slight over-representation for resident

drivers from rural LSOAs within Windsor and Maidenhead.

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2.2.2 Resident Motorcyclists involved in Collisions

This section refers to motorcyclists involved in collisions and who are residents of Windsor and Maidenhead. For an

explanation of the methodologies employed throughout this section, please refer to 1.1.3.1 on page 3.

2.2.2.1 Rates

Figure 22 shows the resident motorcycle rider collision involvement rate for Windsor and Maidenhead, Berkshire

authorities and most similar authorities. National and regional rates are also included for comparison.

Figure 22 - Annual average resident motorcycle riders (2008-2012) per 100,000 adult population.

2.2.2.2 Comparisons

Windsor and Maidenhead’s resident motorcycle rider rate is higher than the national rate. It is similar to the South

East rate but is higher than the overall Berkshire rate. Within Berkshire, Windsor and Maidenhead has the second

highest rate just behind Slough. Windsor and Maidenhead has a higher rate than the most similar authorities of

Brentwood, Guildford and Waverley but has a lower rate than Elmbridge and Reigate and Banstead.

Internal

Figure 23 shows Windsor and Maidenhead’s collision involved motorcycle riders by home MSOA. Higher rates can

be found to the south of the borough around Ascot, Old Windsor and Wraysbury. There are also higher rates around

the Dedworth area of Windsor.

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Figure 23 - Annual average resident motorcycle riders per 100,000 adult population, by MSOA (2008-2012).

2.2.2.3 Trends

Shown in Figure 24 is Windsor and Maidenhead’s annual resident motorcycle rider numbers by severity. There has

been very little overall change over the past decade. An increasing trend to 2008 has been following by a general

reduction since. In 2012 there were 44 motorcycle riders from Windsor and Maidenhead involved in injury collisions.

Over the most recent five year period (2008-2012) 29% of Windsor and Maidenhead’s resident motorcycle riders

were involved in injury collisions where one or more of the casualties was killed or seriously injured, compared to

the national percentage of 28%. This represents a high KSI ratio compared to other road user groups.


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Figure 24 - Windsor and Maidenhead resident motorcycle riders, by year (2004-2012).

Resident Motorcyclist crash involvement in other areas

Windsor and Maidenhead’s resident motorcycle riders tend to be involved in collisions on Windsor and

Maidenhead’s roads. Fifty-one percent of residents were involved in collisions on Windsor and Maidenhead’s roads.

Ten percent were involved in collisions in Slough with the rest involved in collisions in neighbouring authorities

including Surrey and Buckinghamshire.

2.2.2.4 Related Casualties

Figure 25 shows the class of casualties in relation to Windsor and Maidenhead’s resident motorcycle riders. This

includes the motorcycle rider themselves, their pillion passenger and any pedestrian involved in a collision with the

motorcycle. The majority (93%) of casualties were the motorcycle rider themselves. This is consistent with the

national percentage.

Figure 25 - Windsor and Maidenhead's resident motorcycle riders - related casualties (2008-2012).

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2.2.3 Young adult resident Drivers involved in Collisions

This section refers to young drivers involved in collisions and who are residents of Windsor and Maidenhead. For an

explanation of the methodologies employed throughout this section, please refer to 1.1.3.1 on page 3. Young drivers

of all motor vehicles except motorcycles are included: motorcycle riders are not included as they are covered in

section 2.2.2.

2.2.3.1 Rates

Figure 26 shows the young resident driver collision involvement rate for Windsor and Maidenhead, Berkshire

authorities and most similar authorities. National and regional rates are also included for comparison.

Figure 26 - Annual average young resident drivers (2008-2012) per 10,000 population (16-24 year olds).

2.2.3.2 Comparisons

Windsor and Maidenhead’s young resident driver rate is 25% higher than the national rate. It is 17% higher than the

South East rate and is 22% higher than the Berkshire rate. Within Berkshire, Windsor and Maidenhead has the

highest young driver collision involvement rate. Windsor and Maidenhead’s rate is higher than the most similar

authorities of Brentwood, Elmbridge and Guildford but is lower than Reigate and Banstead and Waverley.

Internal

Figure 27 shows Windsor and Maidenhead’s young adult resident collision involved drivers by home MSOA. Higher

rates can be seen to the north of Maidenhead; in the Fifield and Holyport area; and South of Windsor around Old

Windsor, Datchet and Wraysbury.

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Figure 27 - Annual average young resident motor vehicle drivers per 10,000 population (of 16-24 year olds), by MSOA (2008-2012).

2.2.3.3 Trends

Figure 28 shows Windsor and Maidenhead’s annual young resident driver numbers, by severity, over the period

2004-2012. There has been a slight overall reduction over the past decade with a 27% reduction from 2004. In 2012

there were 91 young drivers from Windsor and Maidenhead involved in injury collisions.


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Figure 28 - Windsor and Maidenhead young resident driver collision involvement, by year (2004-2012).

Young Resident Driver crash involvement in other areas

Fifty-two percent of Windsor and Maidenhead’s young resident drivers are involved in collisions on Windsor and

Maidenhead’s roads. Other authorities where Windsor and Maidenhead’s young drivers are involved in collisions

include Surrey (12%), Slough (7%), Bracknell Forest (6%) and Buckinghamshire (5%).


Segmentation

Analysis of the Mosaic communities in which Windsor and Maidenhead’s young resident drivers live provides an

insight into those involved in collisions. For an explanation of Mosaic Public Sector and how to understand the

following chart, please refer to 4.1 on page 55 and 1.1.3.1 on page 3 respectively.

Figure 29 shows Windsor and Maidenhead’s young resident drivers by Mosaic Group. Mosaic Group is used instead

of Mosaic Type as numbers are too low to be significant by Type. The highest number of young drivers are from

Wealthy people living in the most sought after neighbourhoods (Group C). This Group’s young drivers are involved

in collisions at the expected level based on typical annual average mileage.

Young drivers from Successful professionals living in suburban or semi-rural homes (Group D), Couples with young

children in comfortable modern housing (Group F) and Middle income families living in moderate suburban semis

(Group E) are also well represented in injury collisions and are over-represented when indexing on annual mileage,

although the mileage figures are for all ages not just 16-24 year olds.

Residents with sufficient incomes in right-to-buy social housing (Group K) are significantly over-represented as young

drivers but driver numbers are low compared to other Groups.

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Figure 29 - Windsor and Maidenhead's young resident drivers by Mosaic Group (2008-2012).

Deprivation

Figure 30 - Windsor and Maidenhead young resident drivers by IMD (2008-2012).

Figure 30 shows young drivers by IMD. The red bars represent the index value showing whether young drivers are

over or under represented based on the population of 16-24 year olds within those communities. Higher young

driver numbers come from the least deprived communities, although numbers are at the expected level based on

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population. Driver numbers are lower in the more deprived communities. The over-representation of some of the

more deprived communities is based on low driver numbers and therefore there is less significance in this.

Rurality

Eighty-five percent of Windsor and Maidenhead’s 16-24 year olds live in urban areas (using the DfT’s rurality

classification). Seventy-nine percent of young drivers involved in injury collisions live in Windsor and Maidenhead’s

urban areas. This means that Windsor and Maidenhead’s urban young drivers are at slightly lower risk of being

involved in an injury collision, if it were true that license holding and annual mileage are evenly distributed amongst

urban and rural young drivers.

2.2.3.5 Related Casualties

Figure 31 shows the class of casualties in relation to Windsor and Maidenhead’s young resident drivers. This includes

the young driver themselves, their passengers and any pedestrian involved in a collision with the young driver. Sixty-

four percent of casualties are the young driver themselves with 30% being passenger casualties and 6% pedestrians.

Figure 31 - Windsor and Maidenhead's young resident drivers - related casualties (2008-2012).

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3 Road Network Risk

3.1 Collisions on all roads

This section refers to all collisions which occurred on Windsor and Maidenhead’s roads. For information on casualties

who live in Windsor and Maidenhead, please refer to 2.1 on page 9 and for analysis involving Windsor and

Maidenhead resident motor vehicle users, please refer to 2.2 on page 24. For an explanation of the methodologies

employed throughout this section, please refer to 1.1.3.2 on page 5.

3.1.1 Rates

3.1.1.1 Collisions per km of road

Figure 32 below shows the rate of annual average collisions between 2008 and 2012 per 10 km of road for Windsor

and Maidenhead and other Berkshire authorities.

Figure 32 – Annual average collisions (2008-2012) per 10km of road.

3.1.2 Comparisons

Windsor and Maidenhead’s collisions per km rate is 39% above the national rate. It is higher than the South East

rate and the overall Berkshire rate. Within Berkshire, Windsor and Maidenhead has the third highest collision rate

behind the more urban areas of Slough and Reading.

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Internal

The map (Figure 33) shows collisions on all roads in Windsor and Maidenhead, by LSOA. Higher collision rates can

be found in the centre of Maidenhead; near to the M4 and A404(M); and near the A308/A332 roundabout in

Windsor.

Figure 33 - Annual average collisions (2009-2013) per 10km of road, by LSOA.

3.1.3 Trends

Figure 34 shows annual collisions on all of Windsor and Maidenhead’s roads, from 2004 to 2013. Collisions on

Windsor and Maidenhead’s roads have reduced by 21% from 2004 and there has been a general downward trend

over the past decade.


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Figure 34 - Windsor and Maidenhead collisions, by year (2004-2013).

Collisions by Hour of the day (Weekdays)

Figure 35 shows collisions on a week day by the hour of the day in which they occurred. There is a peak at 8am

during the morning commute to work and a peak in the afternoon between 4pm and 6pm during the commute

home from work.

Figure 35 - Collisions on Windsor and Maidenhead's roads by Hour of the Day - Weekdays (2009-2013).

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Collisions by Hour of the day (Weekends)

Figure 36 shows collisions on a weekend by the hour of the day in which they occurred. Collisions are more spread

throughout the day than weekdays. Collisions tend to occur between 10am and 6pm.

Figure 36 - Collisions on Windsor and Maidenhead's roads by hour of the day - Weekends (2009-2013).

3.1.3.1 Collisions involving drivers who reside in other areas

Using the driver’s home postcode from STATS19 allows us to analyse where drivers involved in collisions in Windsor

and Maidenhead are from. Forty-four percent of drivers with known postcodes involved in collisions in Windsor and

Maidenhead are from Windsor and Maidenhead. The rest are from nearby authorities including Slough (10%),

Bracknell Forest (7%), Buckinghamshire (7%), Surrey (5%) and Wokingham (4%).

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3.1.4 Casualty trends on all roads

3.1.4.1 All Casualties

Figure 37 shows annual casualty numbers on Windsor and Maidenhead’s roads. Numbers have generally reduced

over recent years. There were 494 casualties on the roads of Windsor and Maidenhead in 2013, down slightly from

515 in 2012.

Figure 37 - Casualties on Windsor and Maidenhead's roads, by year (2004-2013).

3.1.4.2 Child casualties

Figure 38 shows annual child casualty numbers on Windsor and Maidenhead’s roads. Numbers have fluctuated over

recent years. There were 38 child casualties on the roads of Windsor and Maidenhead in 2013. There have been no

child fatalities in any of the past ten years.

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Figure 38 - Child casualties on Windsor and Maidenhead's roads, by year (2004-2013).

3.1.4.3 Pedestrian casualties

Figure 39 shows annual pedestrian casualty numbers on Windsor and Maidenhead’s roads. There has been a general

reduction over recent years. In 2013 there were 46 pedestrian casualties on Windsor and Maidenhead’s roads

compared to 37 in 2012.

Figure 39 - Pedestrian casualties on Windsor and Maidenhead's roads, by year (2004-2013).

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3.1.4.4 Pedal cyclist casualties

Figure 40 shows annual pedal cycle user casualty numbers on Windsor and Maidenhead’s roads. Casualty numbers

have generally increased over the past decade. There was a peak of 68 casualties in 2011. In 2013 there were 54

pedal cycle user casualties.

Figure 40 - Pedal cycle user casualties on Windsor and Maidenhead's roads, by year (2004-2013).

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3.1.5 Contributory Factors

Each section below examines trends in reported collisions 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. The darker shaded trend line shows the three year moving average for collisions involving the CF group

being analysed. The lighter shaded dashed trend line shows a three year average for all collisions where an officer

attended and at least one CF was recorded, for comparison.

For more information about CFs and the techniques used to analyse them see 1.1.3.4 on page 6. For a complete list

of all CFs and CF groupings used by RSA, see 4.3 on page 64.

3.1.5.1 Substance Impairment

This section examines collisions 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.

Trends

Figure 41 shows annual collisions on Windsor and Maidenhead’s roads where at least one of the substance

impairment contributory factors were recorded. The chart shows that substance impairment collision numbers are

low and have fluctuated over the past decade. In the past five year period (2009-2013) 26% of collisions where a

substance impairment CF has been recorded have resulted in a killed or seriously injured casualty. This is compared

to 16% for all officer attended, at least one CF recorded collisions.

Figure 41 - Collisions on Windsor and Maidenhead's roads where CF 501 and/or CF 502 were recorded.

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Comparisons

Figure 42 shows collisions on Windsor and Maidenhead’s roads where at least one of the substance impairment

contributory factors was recorded as a percentage of all officer attended collisions where at least one CF was

recorded. Berkshire and the other Berkshire authorities are also included for comparison.

Figure 42 - Collisions where CF 501 and/or CF 502 were attributed (2009-2013).

Windsor and Maidenhead’s percentage of substance impairment collisions is higher than the overall Berkshire

percentage and is higher than all of the Berkshire authorities.

3.1.5.2 Speed Related

This section examines collisions 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.

Trends

Figure 43 shows annual collisions on Windsor and Maidenhead’s roads where at least one of the speed related

contributory factors were recorded. There has been a general reduction in speed related collisions as there has been

with all CF recorded collisions. In 2013 there were 29 speed related collisions compared to 49 in 2012.

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Figure 43 - Collisions on Windsor and Maidenhead's roads where CF306 and/or CF307 were recorded.

Comparisons

Figure 44 shows collisions on Windsor and Maidenhead’s roads where at least one of the speed related contributory

factors was recorded as a percentage of all officer attended collisions where at least one CF was recorded. Berkshire

and the other Berkshire authorities are also included for comparison.

Figure 44 – Collisions where CF306 and/or CF307 were recorded (2009-2013).

Windsor and Maidenhead has a higher percentage of speed related collisions than the overall Berkshire percentage.

It has the highest percentage of all the Berkshire authorities.

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3.1.5.3 Distraction

This section examines collisions where at least one of the contributory factors 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.

Trends

Figure 45 shows annual collisions on Windsor and Maidenhead’s roads where at least one of the distraction

contributory factors were recorded. Although numbers are fairly low there have been increases in recent years. In

2013 there were 38 distraction related collisions compared to 23 in 2012.

Figure 45 - Annual collisions in Windsor and Maidenhead where CF101, CF102 and/or CF103 were recorded.

Comparisons

Figure 46 shows collisions on Windsor and Maidenhead’s roads where at least one of the distraction contributory

factors were recorded as a percentage of all officer attended collisions where at least one CF was recorded. Berkshire

and the other Berkshire authorities are also included for comparison.

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Figure 46 - Collisions where CF508, CF509 and/or CF510 were recorded (2009-2013).

Windsor and Maidenhead has the highest percentage of distraction related collisions in Berkshire and is quite a bit

higher than the overall Berkshire percentage.

3.1.5.4 Unsafe Behaviour

This section examines collisions where at least one of the contributory factors 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.

Trends

Figure 47 shows annual collisions on Windsor and Maidenhead’s roads where at least one of the unsafe behaviour

contributory factors were recorded. Collisions have fluctuated with very little overall change. In 2013 there were 47

collisions where an unsafe behaviour CF was recorded compared to 72 in 2012.

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Figure 47 - Collisions on Windsor and Maidenhead's roads where CF601 and/or CF602 were recorded.

Comparisons

Figure 48 shows collisions on Windsor and Maidenhead’s roads where at least one of the unsafe behaviour

contributory factors were recorded as a percentage of all officer attended collisions where at least one CF was

recorded. Berkshire and the other Berkshire authorities are also included for comparison.

Figure 48 - Percentage of collisions where CF601 and/or CF602 were recorded (2009-2013).

Windsor and Maidenhead’s percentage of unsafe behaviour related collisions is higher than the Berkshire

percentage and is higher than all of the other Berkshire authorities.

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3.2 Collisions on roads by environment

For more information on the methodology used to analyse networks by road environment, see 1.1.3.2 on page 5.

3.2.1 Urban Roads

This section includes all roads in urban areas of Windsor and Maidenhead, including strategic roads.

3.2.1.1 Rates

Collisions per km of road

Figure 49 below shows the rate of annual average collisions per 10 km of urban road. Berkshire and the other

Berkshire authorities are included for comparison.

Figure 49 - Annual average collisions on urban roads (2008-2012) per 10km of urban road.

3.2.1.2 Comparisons

Windsor and Maidenhead’s urban road collision rate is 41% lower than the national rate. It is 34% lower than the

South East rate and 21% lower than the Berkshire rate. Within Berkshire, Windsor and Maidenhead has the third

highest rate behind the more densely populated boroughs of Slough and Reading although it is not much higher than

the other authorities.

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3.2.1.3 Trends

Figure 50 shows the annual numbers of collisions on Windsor and Maidenhead’s urban roads between 2004 and

2012. Windsor and Maidenhead’s urban road collisions have generally reduced. In 2012 there were 162 collisions

on Windsor and Maidenhead’s urban roads, down 22% from 2004.

Figure 50 - Windsor and Maidenhead's collisions on urban roads, by year (2004-2012).

3.2.2 Rural Roads

This section includes all roads in rural areas of Windsor and Maidenhead, including strategic roads.

3.2.2.1 Rates

Collisions per km of road

Figure 51 shows the rate of annual average collisions per 10 km of rural road. Berkshire and the other Berkshire

authorities are included for comparison.

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Figure 51 - Annual average collisions on rural roads (2008-2012) per 10km of rural road.

3.2.2.2 Comparisons

Windsor and Maidenhead has a higher rural road collision rate than the national rate and is also higher than the

South East and Berkshire rates. Of the six Berkshire authorities Slough has the highest rural collision rate although

this is skewed by the rarity of rural roads in the area and this is reflected in the chart. Windsor and Maidenhead has

the third highest rate of all the Berkshire authorities behind Slough and Reading.

3.2.2.3 Trends

Figure 52 shows the annual numbers of collisions on Windsor and Maidenhead’s rural roads between 2004 and

2012. There has been a downward trend over recent years. In 2012 there were 223 collisions on Windsor and

Maidenhead’s rural roads compared to 192 in 2011.

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Figure 52 - Windsor and Maidenhead's rural roads collisions, by year (2004-2012).

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4 Appendices

4.1 Mosaic Public Sector

This section provides information on all of the Mosaic Types and more detailed analysis of the specific Types

identified as being of interest to Windsor and Maidenhead. More information on what Mosaic is can be found in

1.1.3.1 on page 3.

4.1.1 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.

Group Description Type Description

A Residents of isolated rural communities

A01 Rural families with high incomes, often from city jobs

A02 Retirees electing to settle in environmentally attractive localities

A03 Remote communities with poor access to public and commercial services

A04 Villages with few well paid alternatives to agricultural employment

B Residents of small and mid-sized towns with strong local roots

B05 Better off empty nesters in low density estates on town fringes

B06 Self employed trades people living in smaller communities

B07 Empty nester owner occupiers making little use of public services

B08 Mixed communities with many single people in the centres of small towns

C Wealthy people living in the most sought after neighbourhoods

C09 Successful older business leaders living in sought-after suburbs

C10 Wealthy families in substantial houses with little community involvement

C11 Creative professionals seeking involvement in local communities

C12 Residents in smart city centre flats who make little use of public services

D Successful professionals living in suburban or semi-rural homes

D13 Higher incomes older champions of village communities

D14 Older people living in large houses in mature suburbs

D15 Well off commuters living in spacious houses in semi rural settings

D16 Higher incomes families concerned with education and careers

E Middle income families living in moderate suburban semis

E17 Comfortably off suburban families weakly tied to their local community

E18 Industrial workers living comfortably in owner occupied semis

E19 Self reliant older families in suburban semis in industrial towns

E20 Upwardly mobile South Asian families living in inter war suburbs

E21 Middle aged families living in less fashionable inter war suburban semis

F Couples with young children in comfortable modern housing

F22 Busy executives in town houses in dormitory settlements

F23 Early middle aged parents likely to be involved in their children’s education

F24 Young parents new to their neighbourhood, keen to put down roots

F25 Personnel reliant on the Ministry of Defence for public services

G Young, well-educated city dwellers

G26 Well educated singles living in purpose built flats

G27 City dwellers owning houses in older neighbourhoods

G28 Singles and sharers occupying converted Victorian houses

G29 Young professional families settling in better quality older terraces

G30 Diverse communities of well educated singles living in smart, small flats

G31 Owners in smart purpose built flats in prestige locations, many newly built

G32 Students and other transient singles in multi-let houses

G33 Transient singles, poorly supported by family and neighbours

G34 Students involved in college and university communities

H Couples and young singles in small modern starter homes

H35 Childless new owner occupiers in cramped new homes

H36 Young singles and sharers renting small purpose built flats

H37 Young owners and rented developments of mixed tenure

H38 People living in brand new residential developments

I Lower income workers in urban terraces in often diverse areas

I39 Young owners and private renters in innef city terraces

I40 Multi-ethnic communities in newer suburbs away from the inner city


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I41 Renters of older terraces in ethnically diverse communities

I42 South Asian communities experiencing social deprivation

I43 Older town centre terraces with transient, single populations

I44 Low income families occupying poor quality older terraces

J Owner occupiers in older-style housing in ex-industrial areas

J45 Low income communities reliant on low skill industrial jobs

J46 Residents in blue collar communities revitalised by commuters

J47 Comfortably off industrial workers owning their own homes

K Residents with sufficient incomes in right-to-buy council houses

K48 Middle aged couples and families in right-to-buy homes

K49 Low income older couples long established in former council estates

K50 Older families in low value housing in traditional industrial areas

K51 Often indebted families living in low rise estates

L Active elderly people living in pleasant retirement locations

L52 Communities of wealthy older people living in large seaside houses

L53 Residents in retirement, second home and tourist communities

L54 Retired people of modest means commonly living in seaside bungalows

L55 Capable older people leasing/owning flats in purpose built blocks

M Elderly people reliant on state support

M56 Older people living on council estates with limited budgets

M57 Old people in flats subsisting on welfare payments

M58 Less mobile older people requiring a degree of care

M59 People living in social accommodation designed for older people

N Young people renting flats in high density social housing

N60 Tenants in council flats on estates at risk of serious social problems

N61 Childless tenants in council flats with modest social needs

N62 Young renters in flats with a cosmopolitan mix

N63 Multiculrural tenants renting flats in areas of social housing

N64 Diverse homesharers renting small flats in densely populated areas

N65 Young singles in multi-ethnic communities, many in high rise flats

N66 Childless, low income tenants in high rise flats

O Families in low-rise council housing with high levels of benefit need

O67 Older tenants in low rise council estates where jobs are scarce

O68 Families with varied structures living in low rise council estates

069 Vulnerable young parents needing substantial state support


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4.1.2 Profile and distribution for selected Mosaic Types

The table below shows the Mosaic Types identified in the Mosaic analysis section 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 53 shows Windsor and Maidenhead’s LSOAs colour coded by dominant Mosaic Type. The four Types from the

above table are shown in the map.

Busy executives in town houses in dormitory settlements (Type F22) dominate in several areas across the borough

including the outskirts of Maidenhead, Wraysbury, The Village and Ascot. Comfortably off suburban families weakly

tied to their local community (Type E17) are dominant in Eton Wick, in the Dedworth area of Windsor, and in and

around Cookham. Well off commuters living in spacious houses in semi rural settings (Type D15) dominate the area

in and around Horton, south of Holyport and in the area around Hurley. Often indebted families living in low rise

estates (Type K51) dominate in parts of Maidenhead and Windsor.

F22 Busy executives in town houses in dormitory settlements

E17 Comfortably off suburban families weakly tied to their local community

D15 Well off commuters living in spacious houses in semi rural settings

K51 Often indebted families living in low rise estates

These work oriented, well paid executives work long hours. They live in small but expensive housing in owner-occupied estates in post-war dormitory towns. They are mostly middle aged, tend to buy more upmarket mainstream brands and are regular users of the internet.

Families headed by junior white collar or semi-skilled manual workers with comfortable living standards. They generally have limited education but there is low unemployment amongst these communities. They are price sensitive, have children living at home and drive a high number of miles.

Households of empty nesters who have enjoyed fruitful careers and positions in senior management. There is a good sense of local community with traditional values and strong friendship networks. Car ownership is high and the village has been a base from which to commute.

Large families on council estates experiencing some problems with debt. These families shop for convenience and have some benefit dependency. They are influenced by the prevalence of children in the home and advertising, but express relatively low environmental concern.


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Figure 53 - Windsor and Maidenhead's dominant Mosaic Types by LSOA.


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4.2 Data Tables

All Casualties – Windsor and Maidenhead Roads (3.1.4.1)

KSI KSI Total Overall Total

Year Fatal Serious Slight

2009 6 62 68 458 526

2010 2 45 47 414 461

2011 4 56 60 432 492

2012 2 58 60 455 515

2013 2 52 54 440 494

Overall Total 16 273 289 2199 2488

Child Casualties – Windsor and Maidenhead Roads (3.1.4.2)



2009 0 4 4 27 31

2010 0 2 2 24 26

2011 0 2 2 33 35

2012 0 3 3 39 42

2013 0 3 3 35 38

Overall Total 0 14 14 158 172

Pedestrian Casualties – Windsor and Maidenhead Roads (3.1.4.3)



2009 0 10 10 40 50

2010 1 9 10 32 42

2011 2 6 8 26 34

2012 1 8 9 28 37

2013 0 8 8 38 46


Pedal Cycle User Casualties – Windsor and Maidenhead Roads (3.1.4.4)



2009 2 6 8 40 48

2010 0 4 4 39 43

2011 0 6 6 62 68

2012 0 13 13 40 53

2013 0 9 9 45 54



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All Collisions – Windsor and Maidenhead Roads (3.1.3)



2009 6 49 55 318 373

2010 2 44 46 301 347

2011 4 52 56 319 375

2012 2 56 58 327 385

2013 2 46 48 316 364

Overall Total 16 247 263 1581 1844

Collisions by hour of the day (Weekdays) 2009 -2013 – Windsor and Maidenhead roads (3.1.3)


Hour Fatal Serious Slight

Midnight 0 2 2 10 12

1AM 0 3 3 9 12

2AM 1 2 3 7 10

3AM 0 2 2 9 11

4AM 0 1 1 4 5

5AM 0 0 0 11 11

6AM 2 7 9 25 34

7AM 0 10 10 83 93

8AM 0 10 10 141 151

9AM 0 14 14 79 93

10AM 0 9 9 53 62

11AM 2 8 10 54 64

Noon 0 6 6 50 56

1PM 0 9 9 44 53

2PM 3 8 11 51 62

3PM 0 11 11 78 89

4PM 1 10 11 98 109

5PM 1 15 16 117 133

6PM 1 11 12 110 122

7PM 0 13 13 72 85

8PM 1 6 7 45 52

9PM 0 4 4 24 28

10PM 0 2 2 27 29

11PM 1 6 7 23 30

Overall Total 13 169 182 1224 1406


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Collisions by hour of the day (Weekends) 2009-2013 – Windsor and Maidenhead roads (3.1.3)


Hour Fatal Serious Slight

Midnight 0 4 4 11 15

1AM 0 4 4 9 13

2AM 1 4 5 12 17

3AM 0 4 4 7 11

4AM 0 2 2 3 5

5AM 0 1 1 2 3

6AM 0 1 1 5 6

7AM 0 1 1 7 8

8AM 0 0 0 22 22

9AM 0 6 6 18 24

10AM 0 9 9 20 29

11AM 0 2 2 21 23

Noon 0 2 2 25 27

1PM 0 5 5 16 21

2PM 0 2 2 29 31

3PM 1 1 2 25 27

4PM 0 7 7 20 27

5PM 0 6 6 16 22

6PM 0 5 5 25 30

7PM 0 0 0 17 17

8PM 1 2 3 8 11

9PM 0 6 6 16 22

10PM 0 1 1 6 7

11PM 0 3 3 17 20


Collisions on urban roads in Windsor and Maidenhead (3.2.1.3)



2008 2 22 24 171 195

2009 2 15 17 172 189

2010 0 14 14 145 159

2011 1 23 24 159 183

2012 2 25 27 135 162



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Collisions on rural roads in Windsor and Maidenhead (3.2.2.3)



2008 3 33 36 207 243

2009 4 34 38 146 184

2010 2 30 32 154 186

2011 3 29 32 160 192

2012 0 31 31 192 223

Overall Total 12 157 169 859 1028

Collisions involving factors 501 and/or 502 (substance impairment) - Windsor and Maidenhead roads

(3.1.5.1)

Collisions involving factors 306 and/or 307 (speed related) - Windsor and Maidenhead roads (3.1.5.2)



2009 2 9 11 31 42

2010 0 8 8 39 47

2011 1 8 9 29 38

2012 0 9 9 40 49

2013 0 2 2 27 29


Collisions involving factors 508, 509 and/or 510 (distraction related) - Windsor and Maidenhead roads

(3.1.5.3)



2009 1 2 3 18 21

2010 0 1 1 25 26

2011 0 3 3 19 22

2012 0 2 2 21 23

2013 0 6 6 32 38




2009 1 3 4 14 18

2010 0 3 3 14 17

2011 1 9 10 16 26

2012 0 4 4 19 23

2013 0 8 8 18 26



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Collisions involving factors 601 and/or 602 (unsafe behaviour) - Windsor and Maidenhead roads

(3.1.5.4)



2009 2 8 10 57 67

2010 0 8 8 46 54

2011 0 13 13 61 74

2012 0 12 12 60 72

2013 1 12 13 34 47



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4.3 Contributory Factor Groupings

Injudicious Action Driver Errors or

Reactions Driver Impairment or

Distraction Behaviour or Inexperience

Other

Traffic Contraventions Manoeuvre Errors Substance Impairments Nervous Behaviour Vehicle Defects

Disobeyed automatic traffic signal

Poor turn or manoeuvre Impaired by alcohol Nervous, uncertain or panic

Tyres illegal, defective or under-inflated

Disobeyed double white lines

Failed to signal or misleading signal

Impaired by drugs (illicit or medicinal)

Learner or inexperienced driver/rider

Defective lights or indicators

Disobeyed ‘Give way’ or ‘Stop’ signs or markings

Passing too close to cyclist, horse rider or pedestrian

Inexperience of driving on the left

Defective brakes

Disobeyed pedestrian crossing facility

Unfamiliar with model of vehicle

Defective steering or suspension

Illegal turn or direction of travel

Defective or missing mirrors Overloaded or poorly loaded vehicle or trailer

Speed Choices Control Errors Distraction Unsafe Behaviour Road Surface

Exceeding speed limit Sudden braking Driver using mobile phone

Aggressive driving Poor or defective road surface

Travelling too fast for conditions

Swerved Distraction in vehicle Careless, reckless or in a hurry

Deposit on road (e.g. oil, mud, chippings)

Loss of control Distraction outside vehicle

Slippery road (due to weather)

Close Following Observation Error Health Impairments Pedal Cycle Behaviour Affected Vision

Following too close Failed to look properly Uncorrected, defective eyesight

Vehicle travelling along pavement

Stationary or parked vehicle(s)

Failed to judge other person’s path or speed

Illness or disability, mental or physical

Cyclist entering road from pavement Not displaying lights at night or in poor visibility Cyclist wearing dark clothing at night

Vegetation Road layout (e.g. bend, winding road, hill crest) Buildings, road signs, street furniture

Junction Errors Fatigue Impairment Pedestrian Behaviour Dazzling headlights

Junction overshoot Fatigue Crossing road masked by stationary or parked vehicle

Dazzling sun

Junction restart (moving off at junction)

Failed to look properly Failed to judge vehicle’s path or speed Wrong use of pedestrian crossing facility Dangerous action in carriageway (e.g. playing) Careless, reckless or in a hurry Impaired by alcohol Impaired by drugs (illicit or medicinal) Pedestrian wearing dark clothing at night Disability or illness, mental or physical

Rain, sleet, snow or fog Spray from other vehicles Visor or windscreen dirty or scratched Vehicle blind spot

Documents

Area Profile 2014 - Royal Borough of Windsor and Maidenhead