August 2014
Prepared by:
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.
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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
1 1.1
Introduction 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-statisticsguidance
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INTRODUCTION 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. Sociodemographic 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 crosschannel 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
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See Appendix B below, or go to http://www.experian.co.uk/marketing-services/products/mosaic-uk.html
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INTRODUCTION
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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INTRODUCTION 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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INTRODUCTION
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.
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AREA PROFILE 2014 – ROYAL BOROUGH OF WINDSOR AND MAIDENHEAD
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. 45.0
Resident Casualty Rate
40.0 35.0 30.0 25.0 20.0 15.0 10.0 5.0 0.0
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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RESIDENT RISK
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).
600
Resident Casualties
500
400
300
200
100
0 2004
2005
2006
2007
Fatal
Serious
2008
2009 Slight
2010
2011
2012
Trend
Resident Casualties occurring in other areas Windsor and Maidenhead residents are mostly involved in collisions on the roads of Windsor and Maidenhead. Fiftytwo 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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RESIDENT RISK Figure 4 - Windsor and Maidenhead resident casualties by age group (2008-2012).
700 Slight
Serious
Fatal
75-84
85+
Resident Casualties
600 500 400 300 200 100 0 <5
5-15
16-24
25-34
35-44 45-54 Age Group
55-64
65-74
Figure 5 - Resident casualties by age group, indexed by population (2008-2012).
350
250
Index
RBWM
291
300
GB
215
200 149 147
150
109
119
100 97 94 50 0
36
67 66
51
<16
16-24
25-34
35-44
45-54
55-64
47 49 65+
Age Group
Segmentation Analysis of the Mosaic communities in which Windsor and Maidenheadâ&#x20AC;&#x2122;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.
300
Resident Casualties
250
140
134 200
119
116
110
102
124
121
E18
H35
150
99 85
81
100
96
94 79
78
50
0 F22
E17
C9
D15
K51
G26
D13
D16
C11
D14
C10
K48
G29
Mosaic Type
Figure 6 shows Windsor and Maidenheadâ&#x20AC;&#x2122;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 overrepresented 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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RESIDENT RISK
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).
800 700
Resident Casualties
600
131
125 117
116
116 105
500 94
400
87
300 200 100 0 Most More More More More Less Less Less Less Least Deprived Deprived Deprived Deprived Deprived Deprived Deprived Deprived Deprived Deprived 10% 20% 30% 40% 50% 50% 40% 30% 20% 10% IMD Decile
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 overrepresentation 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). 50.0
Pedestrian Casualty Rate
45.0 40.0 35.0 30.0 25.0 20.0 15.0 10.0 5.0 0.0
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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RESIDENT RISK
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 havenâ&#x20AC;&#x2122;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).
45
Resident Pedestrian Casualties
40 35 30 25 20 15 10 5 0 2004
2005
2006 Fatal
2007
2008
Serious
2009 Slight
2010
2011
2012
Trend
Resident Pedestrian Casualties occurring in other areas Between 2008 and 2012, 72% of Windsor and Maidenheadâ&#x20AC;&#x2122;s resident pedestrian casualties were involved in collisions on Windsor and Maidenheadâ&#x20AC;&#x2122;s roads. Nationally, 82% of a highway authorities residents are involved in collisions within their home authority.
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RESIDENT RISK
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).
Resident Pedal Cycle User Casualty Rate
60.0 50.0 40.0 30.0 20.0 10.0 0.0
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 Maidenheadâ&#x20AC;&#x2122;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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RESIDENT RISK
Figure 13 - Resident pedal cycle user casualties, by year (2004-2012).
Resident Pedal Cycle User Casualties
70 60 50 40 30 20 10 0 2004
2005
2006 Fatal
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2007 Serious
2008
2009 Slight
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2010 Trend
2011
2012
RESIDENT RISK
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). 20.0
Child resident Casualty Rate
18.0 16.0 14.0 12.0 10.0 8.0 6.0 4.0 2.0 0.0
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).
40
Child resident Casualties
35 30 25 20 15 10 5 0 2004
2005
2006 Fatal
2007 Serious
2008
2009 Slight
2010
2011
2012
Trend
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 â&#x20AC;&#x201C; Annual average resident drivers (2008-2012) per 10,000 adult population. 70.0
Resident Drivers Rate
60.0 50.0 40.0 30.0 20.0 10.0 0.0
2.2.1.2 Comparisons Windsor and Maidenheadâ&#x20AC;&#x2122;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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RESIDENT RISK
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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RESIDENT RISK
Figure 19 - Windsor and Maidenhead's resident drivers, by year (2004-2012).
700 600
Resident Drivers
500 400 300 200 100 0 2004
2005
2006
2007
Fatal
Serious
2008
2009 Slight
2010
2011
2012
Trend
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.
2.2.1.4 Socio Demographic Analysis 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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RESIDENT RISK
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 rightto-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.
350 300
Resident Drivers
250
135
200
107 150
101
100
109
99 100
137
130
126
106 90
92
D16
C11
77
86
95
50 0 F22
C9
E17
D15
K51
G26
D13
C10
D14
E18
G29
K48
H35
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 Maidenheadâ&#x20AC;&#x2122;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).
1000 900
Resident Drivers
700
124
123
800
115
110
102
106
600 92
500
90
400 300 200 100 0 Most More More More More Less Less Less Less Least Deprived Deprived Deprived Deprived Deprived Deprived Deprived Deprived Deprived Deprived 10% 20% 30% 40% 50% 50% 40% 30% 20% 10% IMD Decile
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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RESIDENT RISK
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.
Resident Motorcycle Riders Rate
60.0 50.0 40.0 30.0 20.0 10.0 0.0
2.2.2.2 Comparisons Windsor and Maidenheadâ&#x20AC;&#x2122;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 Maidenheadâ&#x20AC;&#x2122;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).
70
Motorcycle Riders
60 50 40 30 20 10 0 2004
2005
2006
2007
Fatal
2008
Serious
2009 Slight
2010
2011
2012
Trend
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).
12 7 Rider Passenger Pedestrian
250
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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). 100.0
Young Resident Drivers Rate
90.0 80.0 70.0 60.0 50.0 40.0 30.0 20.0 10.0 0.0
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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RESIDENT RISK
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 Maidenheadâ&#x20AC;&#x2122;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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RESIDENT RISK
Figure 28 - Windsor and Maidenhead young resident driver collision involvement, by year (2004-2012).
140
Young Resident Drivers
120 100 80 60 40 20 0 2004
2005
2006
2007
Fatal
2008
Serious
2009 Slight
2010
2011
2012
Trend
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%).
2.2.3.4 Socio Demographic Analysis 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).
120
Young Resident Drivers
100
161
80
60
40
109
114
116
D
F
E
95
20
0 C
K
Mosaic Group
Deprivation Figure 30 - Windsor and Maidenhead young resident drivers by IMD (2008-2012).
200 180
Young Resident Drivers
Index
146
Young Resident Drivers
160 140
118
110
100
120 100 80
93
92
95
79
60 40 20 0 Most More More More More Less Less Less Less Least Deprived Deprived Deprived Deprived Deprived Deprived Deprived Deprived Deprived Deprived 10% 20% 30% 40% 50% 50% 40% 30% 20% 10% IMD Decile
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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RESIDENT RISK
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. Sixtyfour 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).
28 Driver
146
Passenger
309
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Pedestrian
AREA PROFILE 2014 – ROYAL BOROUGH OF WINDSOR AND MAIDENHEAD
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. 16.0
Collisions per 10km Rate
14.0 12.0 10.0 8.0 6.0 4.0 2.0 0.0
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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ROAD NETWORK RISK
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).
500 450 400
All Collisions
350 300 250 200 150 100 50 0 2004
2005
2006
2007
Fatal
2008 Serious
2009 Slight
2010
2011
2012
2013
Trend
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).
160 140 120
Collisions
100 80 60 40 20 0
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ROAD NETWORK RISK
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).
35 30
Collisions
25 20 15 10 5 0
3.1.3.1 Collisions involving drivers who reside in other areas Using the driverâ&#x20AC;&#x2122;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 Maidenheadâ&#x20AC;&#x2122;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).
700 600
Casualties
500 400 300 200 100 0 2004
2005
2006 Fatal
2007
2008 Serious
2009 Slight
2010
2011
2012
2013
Trend
3.1.4.2 Child casualties Figure 38 shows annual child casualty numbers on Windsor and Maidenheadâ&#x20AC;&#x2122;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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ROAD NETWORK RISK
Figure 38 - Child casualties on Windsor and Maidenhead's roads, by year (2004-2013).
50 45 40
Child Casualties
35 30 25 20 15 10 5 0 2004
2005
2006
2007
Fatal
2008 Serious
2009
2010
Slight
2011
2012
2013
Trend
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).
70
Pedestrian Casualties
60 50 40 30 20 10 0 2004
2005
2006 Fatal
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2007
2008 Serious
2009 Slight
© ROAD SAFETY ANALYSIS
2010 Trend
2011
2012
2013
Figure 40 shows annual pedal cycle user casualty numbers on Windsor and Maidenheadâ&#x20AC;&#x2122;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.
ROAD NETWORK RISK
3.1.4.4 Pedal cyclist casualties
Figure 40 - Pedal cycle user casualties on Windsor and Maidenhead's roads, by year (2004-2013).
80
Pedal Cycle User Casualties
70 60 50 40 30 20 10 0 2004
2005
2006 Fatal
2014
2007
2008 Serious
2009 Slight
2010
2011
2012
2013
Trend
ROYAL BOROUGH OF WINDSOR AND MAIDENHEAD
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ROAD NETWORK RISK
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 Maidenheadâ&#x20AC;&#x2122;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.
Substance Impairment Collisions
35 30 25 20 15 10 5 0 2005
2006
2007 Collisions
PAGE | 44
2008
2009
2010
3 Year Trend
Š ROAD SAFETY ANALYSIS
2011 All 3 year trend
2012
2013
ROAD NETWORK RISK
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). 8% 7%
Substance Impairment
6% 5% 4% 3% 2% 1% 0% BERKSHIRE
Bracknell Forest
Reading
Slough Borough West Berkshire
Windsor and Maidenhead Royal Borough
Wokingham Borough
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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ROAD NETWORK RISK
Figure 43 - Collisions on Windsor and Maidenhead's roads where CF306 and/or CF307 were recorded.
60
Speed Related Collisions
50
40
30
20
10
0 2005
2006
2007
2008
Collisions
2009
2010
3 Year Trend
2011
2012
2013
All 3 year trend
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). 16% 14%
Speed Related
12% 10% 8% 6% 4% 2% 0% BERKSHIRE
Bracknell Forest
Reading
Slough Borough West Berkshire
Windsor and Maidenhead Royal Borough
Wokingham Borough
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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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.
ROAD NETWORK RISK
3.1.5.3
Trends Figure 45 shows annual collisions on Windsor and Maidenheadâ&#x20AC;&#x2122;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.
40
Distraction Related Collisions
35 30 25 20 15 10 5 0 2005
2006
2007 Collisions
2008
2009 3 Year Trend
2010
2011
2012
2013
All 3 year trend
Comparisons Figure 46 shows collisions on Windsor and Maidenheadâ&#x20AC;&#x2122;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). 10% 9% 8%
Distraction
7% 6% 5% 4% 3% 2% 1% 0% BERKSHIRE
Bracknell Forest
Reading
Slough Borough West Berkshire
Windsor and Maidenhead Royal Borough
Wokingham Borough
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 Maidenheadâ&#x20AC;&#x2122;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.
80 70
Unsafe Behaviour
60 50 40 30 20 10 0 2005
2006
2007
2008
Collisions
2009
2010
3 Year Trend
2011
2012
2013
All 3 year trend
Comparisons Figure 48 shows collisions on Windsor and Maidenheadâ&#x20AC;&#x2122;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). 25%
Unsafe Behaviour
20%
15%
10%
5%
0% BERKSHIRE
Bracknell Forest
Reading
Slough Borough West Berkshire
Windsor and Maidenhead Royal Borough
Wokingham Borough
Windsor and Maidenheadâ&#x20AC;&#x2122;s percentage of unsafe behaviour related collisions is higher than the Berkshire percentage and is higher than all of the other Berkshire authorities.
2014
ROYAL BOROUGH OF WINDSOR AND MAIDENHEAD
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ROAD NETWORK RISK
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.
Collisions on Urban Roads Rate
14.0 12.0 10.0 8.0 6.0 4.0 2.0 0.0 GREAT BRITAIN
SOUTH EAST BERKSHIRE
Bracknell Forest
Reading
Slough Borough
West Windsor and Wokingham Berkshire Maidenhead Borough Royal Borough
3.2.1.2 Comparisons Windsor and Maidenheadâ&#x20AC;&#x2122;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.
PAGE | 50
Š ROAD SAFETY ANALYSIS
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.
ROAD NETWORK RISK
3.2.1.3 Trends
Figure 50 - Windsor and Maidenhead's collisions on urban roads, by year (2004-2012).
250
Collisions on Urban Roads
200
150
100
50
0 2004
2005
2006
2007 Collisions
3.2.2
2008
2009
2010
2011
2012
Trend
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.
2014
ROYAL BOROUGH OF WINDSOR AND MAIDENHEAD
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ROAD NETWORK RISK
Figure 51 - Annual average collisions on rural roads (2008-2012) per 10km of rural road. 18.0
Collisions on Rural Roads Rate
16.0 14.0 12.0 10.0 8.0 6.0 4.0 2.0 0.0 GREAT BRITAIN
SOUTH EAST BERKSHIRE
Bracknell Forest
Reading
Slough Borough
West Windsor and Wokingham Berkshire Maidenhead Borough Royal Borough
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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© ROAD SAFETY ANALYSIS
ROAD NETWORK RISK
Figure 52 - Windsor and Maidenhead's rural roads collisions, by year (2004-2012).
300
Collisions on Rural Roads
250
200
150
100
50
0 2004
2005
2006
2007 Collisions
2014
2008
2009
2010
2011
2012
Trend
ROYAL BOROUGH OF WINDSOR AND MAIDENHEAD
PAGE | 53
AREA PROFILE 2014 â&#x20AC;&#x201C; ROYAL BOROUGH OF WINDSOR AND MAIDENHEAD
4
4.1
Appendices
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 A
Description Residents of isolated rural communities
B
Residents of small and midsized towns with strong local roots
C
Wealthy people living in the most sought after neighbourhoods
D
Successful professionals living in suburban or semi-rural homes
E
Middle income families living in moderate suburban semis
F
Couples with young children in comfortable modern housing
G
Young, well-educated dwellers
H
Couples and young singles in small modern starter homes
I
Lower income workers in urban terraces in often diverse areas
2014
city
Type A01 A02 A03 A04 B05 B06 B07 B08 C09 C10 C11 C12 D13 D14 D15 D16 E17 E18 E19 E20 E21 F22 F23 F24 F25 G26 G27 G28 G29 G30 G31 G32 G33 G34 H35 H36 H37 H38 I39 I40
Description Rural families with high incomes, often from city jobs Retirees electing to settle in environmentally attractive localities Remote communities with poor access to public and commercial services Villages with few well paid alternatives to agricultural employment Better off empty nesters in low density estates on town fringes Self employed trades people living in smaller communities Empty nester owner occupiers making little use of public services Mixed communities with many single people in the centres of small towns Successful older business leaders living in sought-after suburbs Wealthy families in substantial houses with little community involvement Creative professionals seeking involvement in local communities Residents in smart city centre flats who make little use of public services Higher incomes older champions of village communities Older people living in large houses in mature suburbs Well off commuters living in spacious houses in semi rural settings Higher incomes families concerned with education and careers Comfortably off suburban families weakly tied to their local community Industrial workers living comfortably in owner occupied semis Self reliant older families in suburban semis in industrial towns Upwardly mobile South Asian families living in inter war suburbs Middle aged families living in less fashionable inter war suburban semis Busy executives in town houses in dormitory settlements Early middle aged parents likely to be involved in their childrenâ&#x20AC;&#x2122;s education Young parents new to their neighbourhood, keen to put down roots Personnel reliant on the Ministry of Defence for public services Well educated singles living in purpose built flats City dwellers owning houses in older neighbourhoods Singles and sharers occupying converted Victorian houses Young professional families settling in better quality older terraces Diverse communities of well educated singles living in smart, small flats Owners in smart purpose built flats in prestige locations, many newly built Students and other transient singles in multi-let houses Transient singles, poorly supported by family and neighbours Students involved in college and university communities Childless new owner occupiers in cramped new homes Young singles and sharers renting small purpose built flats Young owners and rented developments of mixed tenure People living in brand new residential developments Young owners and private renters in innef city terraces Multi-ethnic communities in newer suburbs away from the inner city
ROYAL BOROUGH OF WINDSOR AND MAIDENHEAD
PAGE | 55
APPENDICES PAGE | 56
J
Owner occupiers in older-style housing in ex-industrial areas
K
Residents with sufficient incomes in right-to-buy council houses
L
Active elderly people living in pleasant retirement locations
M
Elderly people reliant on state support
N
Young people renting flats in high density social housing
O
Families in low-rise council housing with high levels of benefit need
I41 I42 I43 I44 J45 J46 J47 K48 K49 K50 K51 L52 L53 L54 L55 M56 M57 M58 M59 N60 N61 N62 N63 N64 N65 N66 O67 O68 069
Renters of older terraces in ethnically diverse communities South Asian communities experiencing social deprivation Older town centre terraces with transient, single populations Low income families occupying poor quality older terraces Low income communities reliant on low skill industrial jobs Residents in blue collar communities revitalised by commuters Comfortably off industrial workers owning their own homes Middle aged couples and families in right-to-buy homes Low income older couples long established in former council estates Older families in low value housing in traditional industrial areas Often indebted families living in low rise estates Communities of wealthy older people living in large seaside houses Residents in retirement, second home and tourist communities Retired people of modest means commonly living in seaside bungalows Capable older people leasing/owning flats in purpose built blocks Older people living on council estates with limited budgets Old people in flats subsisting on welfare payments Less mobile older people requiring a degree of care People living in social accommodation designed for older people Tenants in council flats on estates at risk of serious social problems Childless tenants in council flats with modest social needs Young renters in flats with a cosmopolitan mix Multiculrural tenants renting flats in areas of social housing Diverse homesharers renting small flats in densely populated areas Young singles in multi-ethnic communities, many in high rise flats Childless, low income tenants in high rise flats Older tenants in low rise council estates where jobs are scarce Families with varied structures living in low rise council estates Vulnerable young parents needing substantial state support
Š ROAD SAFETY ANALYSIS
APPENDICES
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.
F22
E17
D15
K51
Busy executives in town houses in dormitory settlements
Comfortably off suburban families weakly tied to their local community
Well off commuters living in spacious houses in semi rural settings
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 semiskilled 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.
Figure 53 shows Windsor and Maidenheadâ&#x20AC;&#x2122;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.
2014
ROYAL BOROUGH OF WINDSOR AND MAIDENHEAD
PAGE | 57
APPENDICES Figure 53 - Windsor and Maidenhead's dominant Mosaic Types by LSOA.
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© ROAD SAFETY ANALYSIS
APPENDICES
4.2
Data Tables
All Casualties – Windsor and Maidenhead Roads (3.1.4.1) KSI Year 2009 2010 2011 2012 2013 Overall Total
Fatal 6 2 4 2 2 16
KSI Total Serious 62 45 56 58 52 273
68 47 60 60 54 289
Overall Total Slight 458 414 432 455 440 2199
526 461 492 515 494 2488
Child Casualties – Windsor and Maidenhead Roads (3.1.4.2) KSI Year 2009 2010 2011 2012 2013 Overall Total
Fatal 0 0 0 0 0 0
KSI Total Serious 4 2 2 3 3 14
4 2 2 3 3 14
Overall Total Slight 27 24 33 39 35 158
31 26 35 42 38 172
Pedestrian Casualties – Windsor and Maidenhead Roads (3.1.4.3) KSI Year 2009 2010 2011 2012 2013 Overall Total
Fatal 0 1 2 1 0 4
KSI Total Serious 10 9 6 8 8 41
10 10 8 9 8 45
Overall Total Slight 40 32 26 28 38 164
50 42 34 37 46 209
Pedal Cycle User Casualties – Windsor and Maidenhead Roads (3.1.4.4) KSI Year 2009 2010 2011 2012 2013 Overall Total
2014
Fatal 2 0 0 0 0 2
KSI Total Serious 6 4 6 13 9 38
8 4 6 13 9 40
ROYAL BOROUGH OF WINDSOR AND MAIDENHEAD
Overall Total Slight 40 39 62 40 45 226
48 43 68 53 54 266
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APPENDICES
All Collisions – Windsor and Maidenhead Roads (3.1.3)
KSI Year 2009 2010 2011 2012 2013 Overall Total
Fatal 6 2 4 2 2 16
KSI Total Serious 49 44 52 56 46 247
55 46 56 58 48 263
Overall Total Slight 318 301 319 327 316 1581
373 347 375 385 364 1844
Collisions by hour of the day (Weekdays) 2009 -2013 – Windsor and Maidenhead roads (3.1.3) KSI Hour Midnight 1AM 2AM 3AM 4AM 5AM 6AM 7AM 8AM 9AM 10AM 11AM Noon 1PM 2PM 3PM 4PM 5PM 6PM 7PM 8PM 9PM 10PM 11PM Overall Total
PAGE | 60
Fatal 0 0 1 0 0 0 2 0 0 0 0 2 0 0 3 0 1 1 1 0 1 0 0 1 13
KSI Total Serious 2 3 2 2 1 0 7 10 10 14 9 8 6 9 8 11 10 15 11 13 6 4 2 6 169
2 3 3 2 1 0 9 10 10 14 9 10 6 9 11 11 11 16 12 13 7 4 2 7 182
© ROAD SAFETY ANALYSIS
Overall Total Slight 10 9 7 9 4 11 25 83 141 79 53 54 50 44 51 78 98 117 110 72 45 24 27 23 1224
12 12 10 11 5 11 34 93 151 93 62 64 56 53 62 89 109 133 122 85 52 28 29 30 1406
KSI Hour Midnight 1AM 2AM 3AM 4AM 5AM 6AM 7AM 8AM 9AM 10AM 11AM Noon 1PM 2PM 3PM 4PM 5PM 6PM 7PM 8PM 9PM 10PM 11PM Overall Total
Fatal 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 3
KSI Total Serious 4 4 4 4 2 1 1 1 0 6 9 2 2 5 2 1 7 6 5 0 2 6 1 3 78
4 4 5 4 2 1 1 1 0 6 9 2 2 5 2 2 7 6 5 0 3 6 1 3 81
APPENDICES
Collisions by hour of the day (Weekends) 2009 -2013 â&#x20AC;&#x201C; Windsor and Maidenhead roads (3.1.3)
Overall Total Slight 11 9 12 7 3 2 5 7 22 18 20 21 25 16 29 25 20 16 25 17 8 16 6 17 357
15 13 17 11 5 3 6 8 22 24 29 23 27 21 31 27 27 22 30 17 11 22 7 20 438
Collisions on urban roads in Windsor and Maidenhead (3.2.1.3) KSI Year 2008 2009 2010 2011 2012 Overall Total
2014
Fatal 2 2 0 1 2 7
KSI Total Serious 22 15 14 23 25 99
24 17 14 24 27 106
ROYAL BOROUGH OF WINDSOR AND MAIDENHEAD
Overall Total Slight 171 172 145 159 135 782
195 189 159 183 162 888
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APPENDICES
Collisions on rural roads in Windsor and Maidenhead (3.2.2.3)
KSI Year 2008 2009 2010 2011 2012 Overall Total
Fatal 3 4 2 3 0 12
KSI Total Serious 33 34 30 29 31 157
36 38 32 32 31 169
Overall Total Slight 207 146 154 160 192 859
243 184 186 192 223 1028
Collisions involving factors 501 and/or 502 (substance impairment) - Windsor and Maidenhead roads (3.1.5.1) KSI Year 2009 2010 2011 2012 2013 Overall Total
Fatal 1 0 1 0 0 2
KSI Total Serious 3 3 9 4 8 27
4 3 10 4 8 29
Overall Total Slight 14 14 16 19 18 81
18 17 26 23 26 110
Collisions involving factors 306 and/or 307 (speed related) - Windsor and Maidenhead roads (3.1.5.2) KSI Year 2009 2010 2011 2012 2013 Overall Total
Fatal 2 0 1 0 0 3
KSI Total Serious 9 8 8 9 2 36
11 8 9 9 2 39
Overall Total Slight 31 39 29 40 27 166
42 47 38 49 29 205
Collisions involving factors 508, 509 and/or 510 (distraction related) - Windsor and Maidenhead roads (3.1.5.3) KSI Year 2009 2010 2011 2012 2013 Overall Total
PAGE | 62
Fatal 1 0 0 0 0 1
KSI Total Serious 2 1 3 2 6 14
3 1 3 2 6 15
Š ROAD SAFETY ANALYSIS
Overall Total Slight 18 25 19 21 32 115
21 26 22 23 38 130
KSI Year 2009 2010 2011 2012 2013 Overall Total
2014
Fatal 2 0 0 0 1 3
KSI Total Serious 8 8 13 12 12 53
10 8 13 12 13 56
ROYAL BOROUGH OF WINDSOR AND MAIDENHEAD
APPENDICES
Collisions involving factors 601 and/or 602 (unsafe behaviour) - Windsor and Maidenhead roads (3.1.5.4)
Overall Total Slight 57 46 61 60 34 258
67 54 74 72 47 314
PAGE | 63
APPENDICES
4.3 Contributory Factor Groupings
Injudicious Action
Driver Errors or Reactions
Driver Impairment or Distraction
Behaviour or Inexperience
Other
Nervous Behaviour Nervous, uncertain or panic Learner or inexperienced driver/rider
Vehicle Defects Tyres illegal, defective or under-inflated Defective lights or indicators
Inexperience of driving on the left
Defective brakes
Unfamiliar with model of vehicle
Defective steering suspension
Traffic Contraventions Disobeyed automatic traffic signal Disobeyed double white lines
Manoeuvre Errors Poor turn or manoeuvre
Substance Impairments Impaired by alcohol
Failed to signal misleading signal
Impaired by drugs (illicit or medicinal)
Disobeyed ‘Give way’ or ‘Stop’ signs or markings
Passing too close to cyclist, horse rider or pedestrian
or
Disobeyed pedestrian crossing facility Illegal turn or direction of travel
Defective mirrors
Speed Choices Exceeding speed limit
Control Errors Sudden braking
Travelling too fast for conditions
Swerved
Distraction Driver using mobile phone Distraction in vehicle
Loss of control Close Following Following too close
Observation Error Failed to look properly Failed to judge other person’s path or speed
Junction Errors Junction overshoot
Fatigue Impairment Fatigue
Junction restart (moving off at junction)
PAGE | 64
Distraction outside vehicle Health Impairments Uncorrected, defective eyesight Illness or disability, mental or physical
Unsafe Behaviour Aggressive driving Careless, reckless or in a hurry
Pedal Cycle Behaviour Vehicle travelling along pavement Cyclist entering road from pavement
or
or
missing
Overloaded or poorly loaded vehicle or trailer Road Surface Poor or defective road surface Deposit on road (e.g. oil, mud, chippings) Slippery road (due to weather) Affected Vision Stationary or parked vehicle(s) Vegetation
Not displaying lights at night or in poor visibility
Road layout (e.g. bend, winding road, hill crest)
Cyclist wearing dark clothing at night Pedestrian Behaviour Crossing road masked by stationary or parked vehicle Failed to look properly
Buildings, road signs, street furniture Dazzling headlights Dazzling sun
Failed to judge vehicle’s path or speed Wrong use of pedestrian crossing facility
Spray from other vehicles
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
Vehicle blind spot
© ROAD SAFETY ANALYSIS
Rain, sleet, snow or fog
Visor or windscreen dirty or scratched