rider crash report-3

8/8/2019 Rider Crash Report-3

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Motorcycle Crasheswww.devon.gov.uk/roadsafe/motorcycles.html

A scoping study looking at motorbike

crash data in Devon 1996-2001


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An exploratory data analysis of fatal and seriousmotorcycle collisions within Devon between 1996 and

2001

Paul HewsonRoad Safety Data Analyst and Research Officer

Environment Directorate

Devon County Council

September 15th 2002

Published by Devon County Council

August 2003

ISBN 1-85522-894-7


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Contents

1 Executive Summary 1

I Background 3

2 Overview 5

2.1 Published research . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

2.1.1 Young riders . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

2.1.2 Multivariate study . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

2.1.3 Previous work in Europe . . . . . . . . . . . . . . . . . . . . . . . . . 6

2.1.4 Behavioural research . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

2.1.5 Helmets and Clothing . . . . . . . . . . . . . . . . . . . . . . . . . . 8

2.1.6 Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

2.2 Current U.K. research . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

2.2.1 Looked but failed to see patterns . . . . . . . . . . . . . . . . . . . 9

2.2.2 Older motorcyclists . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

2.2.3 Multivariateanalysis . . . . . . . . . . . . . . . . . . . . . . . . . . 10

2.2.4 In-depth study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

2.2.5 On-the-spotstudy . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

3 General Trends 11

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ii CONTENTS

3.1 National Trends . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

3.1.1 Rider exposure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

3.1.2 Collision Rates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

3.1.3 Devon Trends . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15

II Devon Stats 19 19

4 Temporal Patterns 21

4.1 Temporal collision patterns . . . . . . . . . . . . . . . . . . . . . . . . . . . 21

4.1.1 Weekend and weekday comparisons . . . . . . . . . . . . . . . . . . . 21

4.1.2 Times and sizes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23

4.2 Seasonal Variations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29

4.3 Weather and road surface . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30

4.4 Road and Junction Type . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36

4.4.1 Junction Types . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36

4.4.2 Road Classifications . . . . . . . . . . . . . . . . . . . . . . . . . . . 36

5 Causation patterns 41

5.1 External factors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41

5.1.1 Other vehicles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41

5.1.2 Road Defects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41

5.2 Collision patterns . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45

5.2.1 Fatalities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46

5.2.2 Serious collisions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48

5.2.3 Small machines and mopeds . . . . . . . . . . . . . . . . . . . . . . . 49

5.2.4 Timings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49


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CONTENTS iii

6 Age and Gender 55

6.1 Comparing riders with the involved car drivers . . . . . . . . . . . . . . . . . 55

6.2 Rider Age and Collision Severity . . . . . . . . . . . . . . . . . . . . . . . . . 57

7 Conclusions 61

7.1 General . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61

7.2 Young riders . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61

7.3 Older riders . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62

7.4 Other Road Users . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62

7.5 Further data analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62

Acknowledgements 65


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iv CONTENTS


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Chapter 1

Executive Summary

This work is intended to make an initial exploratory data analysis of STATs 19 informationrecorded on motorcycle collisions within Devon where there was either a fatal or seriously injured motorcyclist. Where possible, this is contrasted with results reported in the extensiveresearch literature on motorcycle collisions and causations. It is hoped that this will providea framework at least for identifying where further research effort should be directed. Sometentative suggestions for possible countermeasures, based more on the literature than the localdata, are also made.

Some of the most striking observations, either from the literature or from the collision data are

as follows:

Informal training with the sole aim of increasing experience with a given machine mayhave a value.

Targeted training at teenagers / moped riders is clearly necessary. Whilst it is unclearhow this may be made attractive to those selecting scooters on the basis of fashion, thoseseeking cheap mobility may be more amenable to suitably priced training of a appropriatetype. Some people in this age group are provided scooters by statutory bodies, it may bepossible to oblige some additional training as a condition of the provision of the machine.

There is strong evidence that the peak age for fatal casualties is somewhat high (30 -40 year olds, and higher than the corresponding peak for serious casualties, and there isevidence of leisure riders being over-represented. This is being researched by Leeds Univer-sity so discussion with them may be beneficial before taking this work too much further.One obvious piece of supplementary information would be to go through the coronersreports to determine the type of bike involved in these collisions. This is something thathas changed over time, for example Woodward (1983a) demonstrated how motorcyclefatalities used to peak around 20 years of age.

Careful consideration needs to be given to the Integrated Transport possibilities of TwoWheeled Motor Vehicles (TWMVs). It appears that riders could do a lot more to improve

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2 CHAPTER 1. EXECUTIVE SUMMARY

their own safety, which implies that careful riders do not experience quite the same levelof risk as the RAGB overall estimate of risk for motorcyclists. It should be noted thatthe officially estimated risk per kilometre for motorcycles is currently lower than for pedal

cycles, and we are working very hard to promote pedal cycling. Wilson (1984) also arguesthat the overall car collision rate includes a higher proportion of lower risk drivers thanthe motorcycle collision rates, which are dominated by high risk young riders. The risk toa trained and cautious motorcyclist could therefore be much lower than the overall figuresuggests.

There is scope for further work on classifying roads where fatalities take place. For exam-ple, the IT available does not yet allow geographic profiling of single vehicle loss of controlcollisions yet it may be possible to highlight areas of the network that perhaps should beavoided by inexperienced riders or which require a specific road safety intervention.

There is still scope for dealing withlooked but did not seecollisions, and any efforts inthis regard would affect more than just TWMVs. There are claims that police drivers canbe taught to look and see a little better, this therefore raises the question of whether aflavour of this training can be introduced into any course offered in any context by DevonCounty Council, and also whether more general educational activity can be directed tothis end.

It is hoped that this work will stimulate discussion with partners and other stakeholders who haveexperience of motorcycling, training, collisions or behaviour. This data analysis can be modifiedin the light of further questions that may arise, in particular it may benefit from contrasting

matched motorcyclist demographic groups with car-drivers, and it may also prove necessary toinclude a random sample of slight collisions. One thing that is very clear from the data analysisis that there is not a single homogenous group ofproblemmotorcyclists. There appears to bea wide range of styles, behaviours, attitudes and machines. It could be extremely unhelpful toextrapolate opinions about how to deal with a perceived problem group (such as theborn-againbiker) with known problem groups (currently young riders on mopeds).


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Part I

Background

3


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Chapter 2

Overview

2.1 Published research

Horswill and Helman (2002) suggest that motorcyclists experience 9.3 times more risk per unittime than car drivers and 7.9 times more risk per unit distance than car drivers (based on analysisof STATs 19 data for 1997 - 1999 and National Travel Survey data for a similar period). Theysuggest three reasons for the disparity in risk:

Physical vulnerability (both due to less mechanical protection and less machine stability) Behaviour of others (where both sensory conspicuity and cognitive conspicuity are com-

ponents)

Behaviour of themselves

Most countermeasures have concentrated on factors that can be changed by the motorcyclist.For example, sensory conspicuity (making the motorbike easier to distinguish from its backgroundby daylight running lights or clothing choice) have been investigated in some depth, whereascognitive conspicuity or the ability of others to interpret the actions of a motorcyclist, have not

been much influenced. The Hurt study (Hurt Jr. et al., 1981) showed that the car involvedin a car - motorcycle collision was less likely to be familiar with motorcycles. This exploratorydata analysis will confirm that violations of a motorcyclists right of way (by vehicles turninginto or emerging from a side road) contribute considerably to the casualty toll within Devon.Ideally the countermeasures considered will examine the potential of both collision participantsto reduce the likelihood of a crash.

2.1.1 Young riders

Reeder et al. (1995) demonstrated the importance of unlicensed riding and borrowed bikes

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6 CHAPTER 2. OVERVIEW

amongst young riders in New Zealand. Of 217 motorcyclists, 72% had borrowed a friends bike,86% had ridden on public roads before being licensed. This puts later work on the importanceof familiarity into context (Mullin et al., 2000) and would be a fascinating piece of information

to have for young Devon riders.

2.1.2 Case Controlled (multivariate) Study

Most of the case-controlled road safety research recently appears to have originated from Aus-tralia or New Zealand. In a motorcycling context, Mullin et al. (2000) consider age and experi-ence as protective factors against motorcycle collision involvement. They suggest:

the association between age and lower risk of motorcycle injury was confirmed little evidence that experience, either on a motorbike or in a car are protective once

allowance has been made for age

familiarity with the specific motorcycle is the only experience measure having a protectiveeffect

Mullin et al. (2000) therefore make some clear recommendations in relation to age; continuingthe age stratification of licensing requirements, with the additional condition of introducingconditions that encourage use of a familiar machine. However, if there is evidence to supportthis locally, there is a clear role for increasing experience without necessarily the requirementto have particularly formal training sessions. It may therefore be possible to deliver trainingpackages that have wider appeal.

2.1.3 Previous work in Europe

There has been little published research in relation to motorcycle collision data in Britain fornearly two decades. Woodward (1983a) considered collisions in Nottinghamshire, and briefly

considered national trends Woodward (1983b) in relation to motorcycle collisions. It is notewor-thy that this was written at a time that motorcycle collisions were on the increase nationally. Atthat time, motorcycle fatalities were associated with riders from lower Socio-Economic Statusgroups, dominated by late night urban collisions with a frequent alcohol involvement. Fatalitiespeaked at age 20. The current situation in Devon appears very different from that depicted byWoodward two decades ago. It is also fair to note that one of the seminal studies on motorcyclecollisions conducted in the U.S. (the Hurt Study) is also now two decades old (Hurt Jr. et al.,1981).

Slightly more recent work in Germany Wick et al. (1998) based on hospital admissions in 1992suggested that collisions were peaking amongst 25 - 29 year olds, and now these were predom-inantly 3pm - 10pm at weekends, over 2

3of the bikes were in excess of 500cc. In this particular


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2.1. PUBLISHED RESEARCH 7

work, 40% of the drivers felt responsible for the collision, mainly through speeding or riskyovertaking, although 75% of the collisions appeared to involve violations of the motorcyclistsright of way. Significantly, there was only one case recorded where alcohol seemed to contribute.

About a third of the motorcyclists had passed their test within the last two years, but amongstthe third who had held a licence for over 8 years few rode a bike regularly.

Even more recent work in the U.K. Lynam et al. (2001), examining 717 police reports of fatalmotorcycle collisions suggested that a high proportion were single vehicle loss of control, oftenlinked with excessive speed, alcohol or careless behaviour. Where other road users were judgedresponsible, the most common factors werefailed to give way,poor turn or manoeuvre, oftenassociated with a failure to judge the riders path or speed. There was an interesting contrastbetween collisions when the motorcyclist was judged primarily responsible, in that mean speedwas estimated at 57mph, and collisions where the other road user was primarily responsible,where the mean speed was estimated at 43 mph. Lynam et al. (2001) noted that the age of

otherroad users responsible for motorcycle collisions peaked between 30 and 60, but the scantevidence in this study suggests that may be artefactual. However, what was noted was that inlower severity collisions, excessive speed on the part of the motorcyclists was less likely to berecorded, andlooked but did not seemore likely to be reported.

2.1.4 Behavioural research

Rutter et al. (1998) describe a national postal survey of motorcyclists which revealed that UKmotorcyclists tended to have an over-optimistic view of the risk they were exposed to. Therewas some realism, in that younger riders and prolific risk takers were aware that they were moreat risk that the average motorcyclist, albeit their assessments of their risk and average riskwere wildly over-optimistic. Personal knowledge of another motorcyclist who had been killed orseriously injured increased their assessments of overall risk, without altering the over-optimisticassessment of their own riding ability. Some aspects of this work were complex and difficultto interpret, but one significant finding was that higher assessment of risk at time 1 predictedhigher levels of safety abandonment at time 2. This may reflect on the selection of motorcyclistsin the study group, but there are some clear cautions in this work.

There is some Australian data available via the LTSN at Glasgow University. A data set intended

for undergraduate projects is described. The original project was conducted in Australia as anattempt to determine whether riders premiums should increase or not following a collision. Ineffect this was meant to indicate whether riders learnt from a collision. By questionnaire, riderswere asked:

Time subject has ridden a motorcycle for

Had collision , Never had collision

Time until first collision occurred

Size of bike ridden in first collision
http://www.ltsn.gla.ac.uk/resources/choiceprojects/index.asp?product=92


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Injured in first collision, not injured

Had second collision , no second collision

Time until second collision occurred

Size of bike ridden in second collision

Injured in second collision, not injured

However, there is much more careful and detailed research available. In E.S.P.R.C. fundedresearch, Horswill and Helman (2001) set up laboratories to assess driving and riding behaviour,

and compared matched groups of motorcyclists and car drivers in a laboratory setting simulatingcar driving and riding a bike and also subjected the participants to a battery of standard tests inrelation to attitudes, sensation seeking and so on (for which the participants were given 15).In total, they compared three demographically matched groups; motorcyclists riding simulatedmotorbikes, motorcyclists driving simulated cars and car drivers driving simulated cars. Theysuggested that there was little difference between the groups in terms of general measures ofsensation seeking and social motives, or attitudes towards driving and riding. The differenceswere found amongst riders when riding a machine such that:

Motorcyclists on laboratory motorcycles took more risks in terms of speed / attitudes andgap acceptance / overtaking than either of the other two groups.

Motorcyclists in laboratory cars took less risks with gap acceptance / overtaking thancar-drivers.

It was noted that there were significant numbers of motorcycling enthusiasts in the study group,and that overall the study group had a younger than average and higher mileage than averagemembership, also containing larger numbers of advanced trained drivers / riders than may have

been anticipated. However, this work tends to suggest that motorcyclists may not be an aberrantgroup, but that they may exhibit slightly riskier behaviour when riding.

2.1.5 Motorcycle helmets and protective clothing

For the purposes of this study, helmet wearing and protective clothing issues will not be con-sidered. There are a number of papers examining the methodology required to demonstratethe effectiveness of motorcyclists wearing helmets (e.g. Greenlander (1994), Weiss (1994)). Itshould, however, be noted that a consultation period has recently closed in connection withopacity of helmet visors.


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2.2. CURRENT U.K. RESEARCH 9

2.1.6 Collision data recommendations

The United States has been the source of much of the existing literature, in particular the

National Highways Transport Safety Agency. Of specific interest on this site are details of riderattitude research and OECD collision data collection recommendations. However, in practice,police collision data in the UK will remain confined to the instructions given in STATs 20 andthere may be little scope to influence collection requirements.

2.2 Current U.K. research

There are a number of current research projects which have a bearing on analysis of motorcycle

collisions. It may be useful to summarise current DfT projects, and closely related work to seewhere there is overlap or potential for some collaborative working.

2.2.1 Looked but failed to see patterns

DfT project S240M examines Looked but Failed to See collision causations. The study hasbeen commissioned with a literature review, and to examine whether the phenomenon is genuine.If there is evidence to support the existence of this phenomenon the project obviously aims tosee whether it is amenable to research. If amenable to research, the project would be conducted

with a view to developing countermeasures. The project was let to Ivan Brown associatesand was due for completion in November 2001. Martin Langham and Graham Hole of theUniversity of Sussex are also interested inLooked but Failed to Seeerrors. Based on analysisof Sussex Police data, they have suggested that motorcycle collisions involving another vehicletend to occur at uncontrolled junctions in uncongested urban environments. Within that, theyhave suggested that they believe T junctions are over-represented but roundabouts are under-represented. Examination of thedriverinvolved in the collision suggests that there is no peakamongst younger drivers, which they suggest implies that this causation has a proneness thatdoes not reduce with experience. They further suggested that studies from fatal collision recordsimply that conspicuity enhancers do significantly reduce the chances of a serious collision but

their evidence for this is not given. Their research suggests that looked but failed to see is areflection of the rarity of two wheel motor vehicles on the road, and drivers being unaccustomedto having to check for their presence before initiating a manoeuvre. This is rather differentto other theories that suggest looked but failed to see is characterised by a subconsciousassessment of the risk the other object poses to the driver.

2.2.2 Older motorcyclists

Leeds University have been awarded project S501B The Older Motorcyclist. This project waslet on the premise that killed and seriously injured casualties amongst riders in the 30 - 59 age
http://www.cogs.susx.ac.uk/users/martinl/summary.htmlhttp://www.nhtsa.dot.gov/people/injury/pedbimot/motorcycle/00-NHT-212-motorcycle/research9-11.html


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group have increased gradually in the last decade. Other than age, little information is availableon rider characteristics particularly in relation to skills, experience history or exposure and thisproject seeks to remedy this knowledge gap.

2.2.3 Multivariate analysis

Project S501F Multivariate analysis of existing data on factors affecting the accident risk ofMotorcyclists is mentioned but few details are given; likewise there is a project listed, S501G,Scoping study on Motorcycle Training to review the content and practice of existing trainingprovision and identify gaps in knowledge. These two projects have the greatest potential foroverlap with the work initiated here. Although few details are given, it may be possible thatProject S501F wishes to use the methodology of Mullin et al. (2000).

2.2.4 In-depth study

New project, S501A, In-depth study of motorcycle and work-related accidents has been letto Nottingham University, and intends to take a detailed analysis of police road collision filessampled from Nottinghamshire, Derbyshire and Leicestershire Police Forces for 3 - 5 years andwill focus on fatal and serious collisions with under-sampling of slight collisions. The aims ofthe research are to identify the incidence of particular factors such as errors, violations or ridingstyle by age, gender, experience, type of vehicle, manoeuvre, time and location type. It also

aims to identify potential countermeasures and estimate their effectiveness and to report allthis work in an accessible manner. As with the previous two studies, there is some potential foroverlap with the work initiated here.

2.2.5 On-the-spot study

Finally, one particularly interesting project, the On the Spot Study is being run from Lough-borough and Crowthorne. Despite repeated attempts to make contact, it has not been possible

to speak with the project manager to discuss the possibility of some collaborative work.
http://www.vsrc.org.uk/research/ots.htm


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Chapter 3

General Trends in MotorcycleCollisions

3.1 National Trends over Time (collisions and owner-ship)

As far as fatalities are concerned, it is quite striking how motorcycle fatalities tend to mirror

motorcycle ownership. Figure 3.1 contrasts this with the overall picture for national road fatal-ities, which have fallen consistently, independently of traffic growth (not shown) or population.However, this graph suggests that owning a motorbike has a fatal risk rate of 1 in 1000, whichis somewhere in the region of 14 thousand times more likely to occur than a lottery jackpotwin.

Whilst motorcycle collisions have been falling recently, this appears to be more due to a fall inownership. The close linkage between ownership and collision rates was suggested twenty yearsago Woodward (1983b). The actual risk of fatal collision involvement seems to have alteredlittle in several decades, despite improving safety technology and legislation. However, consid-

ering overall bike ownership figures is relatively simplistic, and there are significant differencesbetween various types of motorcycle. DfT data breaks down ownership into a number of smallercategories based solely on engine size. This doesnt differentiate the style of bikes, for exampleit doesnt differentiate touring or racing bikes, scooters or small motorbikes. Data up until 2000is presented in figure 3.2.

Whilst it is possible to identify omissions in this data, for example touring and sports bikes are notdifferentiated within a given size range, it is still considerably more detailed than the informationavailable from Stats 19. In the official collision reporting system, the only information availableon size is whether a bike was above or below 125 cc, and whether it was a moped or not. Moreinformation may be available from Coroners reports in the event of a fatal collision, but theinformation of the size and type of bike included within collision reports is inadequate.

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12 CHAPTER 3. GENERAL TRENDS

Motorcycle collisions and ownership

Year

RegisteredMotorb

ikes(1000)

1940 1960 1980 2000

0

500

1000

1500

Year

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0

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1500

FatalMotorcycle

Collisions

Overall population and overall road collisions

Year

Population(Million)

1940 1960 1980 2000

0

10

20

30

40

50

60

Year

1940 1960 1980 2000

0

2000

4000

6000

8000

FatalRoadCollisions

Figure 3.1: National trends in Motorcycle and All Road Fatalities


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3.1. NATIONAL TRENDS 13

q

q

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q qq

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Year

Num



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Figure 3.3: Estimated annual mileage for different motorbikes. Source: DfT PersonalMobility Factsheet 10

3.1.1 Rider exposure

Up until 2000 it can be seen that there are considerable increases in the numbers of largeregistered motorbikes, and up until the late 1990s an almost corresponding fall in the numbersof registered small bikes. However, the decline in terms of small motorbikes seems to havereversed in 1999 and 2000. It is interesting to contrast this immediately with the trends inreported motorcycle collisions in Devon over the last decade.

National data in figure 3.3 suggests that larger bikes cover more mileage in a year than smallbikes. It is not clear whether this extra mileage is for example motorway riding (which wouldbe safer), longer commuter runs, or how much is leisure runs. If the images presented inMotorcycling magazines are accurate, riders will travel considerable distances on Motorwaysand other Trunk Roads to attend more fun rides on minor roads. One would assume thatthe hazards presented getting to and from the funvenue were considerably lower than thoseexperienced on the more challenging ride.

3.1.2 Collision Rates

One salient reminder from combining exposure data and collision data is that over the lastfifteen years or so, the estimates suggest that the risk has reduced for motorcycles (and actuallybeen overtaken by pedal cycles) as depicted by figure 3.4.

The national travel survey is run on a three year rolling program, and the data estimates donot yet reflect recent increases in registered motorbikes. However, some key points are thathouseholds with cars are more likely to have motorcycles than households without. It is difficultto assess the value of some of the information reported from the NTS, but average motorcycle
http://www.transtat.dft.gov.uk/facts/ntsfacts/motorcyc/motorcyc.htmhttp://www.transtat.dft.gov.uk/facts/ntsfacts/motorcyc/motorcyc.htm


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Figure 3.4: Collision rates by modal group. Source: DfT Personal Transport Accidents:Motorcycles

trips, whether measured by distance or time taken have increased over the last couple of decades.However, this is a very bland observation. It will become clear from this study that there area number of sub-groups of motorcyclists. An increase in trip length could be due to increasedcommuting, increased leisure use or an increase in one and decrease in the other provided theincrease in one overwhelms the other.

There are however some interesting observations on motorcyclists. On average, motorcycliststend to take fewer, longer trips than has previously been the case. Also, this mileage makes up asmaller proportion of their overall mileage (most of which is presumably carried out in the car).However, there is one particularly interesting comment in the NTS which seems to be borneout by investigation of the data, namely that an unspecified number of motorbikes (many) arestored during the Winter.

Figure 3.5 suggests that leisure riding takes up a relatively small proportion of motorcycle usage.Research elsewhere on performance indicators (Hewson, 2002) suggests that motorbike owner-ship is a much better predictor of collision involvement than the population based performanceindicators (and early work in the UK used rainfall levels as a proxy for ownership levels). There

is some evidence from the National Travel Survey (figure 3.6) to support this, and in particularthere is evidence that motorcycle usage in rural areas is relatively high.

3.1.3 Medium term trends in Devon

Unlike the national trend, there has been little increase in motorcycle fatalities in Devon ina decade. Whilst it is possible to claim that Devon is actually safer for motorcyclists thanper-capita performance indicators suggest Hewson (2002), it remains the case that almost aquarter of all fatalities on Devons roads are motorcyclists. Horswill and Helman (2001) makea strong case that this is simply a reflection of the lack of mechanical protection available
http://www.transtat.dft.gov.uk/facts/accident/mcycle/mcycle98.htmhttp://www.transtat.dft.gov.uk/facts/accident/mcycle/mcycle98.htm


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Figure 3.5: Recorded uses of Motorcycles. Source: DfT Personal Mobility Factsheet 10

Figure 3.6: Motorbike usage by area type. Source: DfT Personal Mobility Factsheet 10
http://www.transtat.dft.gov.uk/facts/ntsfacts/motorcyc/motorcyc.htmhttp://www.transtat.dft.gov.uk/facts/ntsfacts/motorcyc/motorcyc.htm


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Fatal Motorcycle Collisions

YearNumberoffata

lcollisions

q q q q q q q q q q05

1015

20

1992 1994 1996 1998 2000

125

1992 1994 1996 1998 2000

q q q q q q q q q q

1992 1994 1996 1998 2000

Moped

Figure 3.7: Ten year trend in Fatal Motorbike collisions in Devon

when riding a motorbike, rather than suggestive of increased risk taking behaviour. However,

approximately ten fatalities a year is a scale of injury that merits careful attention as to possiblecountermeasures.

It would appear from figure 3.7 that Devon does not echo the national picture in terms of fatalmotorcycle collisions. Whilst the figures for fatalities are unacceptably high, there is no evidenceto suggest an increase in the last decade. This may simply reflect that the numbers of fatalitiesare relatively small. What is quite striking from the data, however, in figure 3.8 is the recentincreases in the numbers of slight and serious collisions recorded on small motorbikes. It hasbeen assumed that this is reflective on the recent increase in ownership of small bikes, conjecturemay even suggest that this reflects on the way these fashionable machines are reaching riderswho previously wouldnt have considered motorcycles. This arising trend in motorcycle collisionshowever clearly needs monitoring, and if it proves to be sustained will require specific attention.Reeder et al. (1995) suggested that unlicensed riding and riding on borrowed bikes was commonamong young riders on small machines.


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Year

Numberofreportedcollisions


100

200

300

19921994199619982000

125

Fatal

q q q q q q q q q q

19921994199619982000

Moped

Fatal

q q q q q q q q qq

125

Serious


100

200

300

Moped

Serious

q q q q q q q qq

q

0

100

200

300

125

Slight

19921994199619982000

q q q q q q q q q q

Moped

Slight

Figure 3.8: Ten year trend in Motorbike collisions in Devon by severity and motorbike size


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Part II

Review of Stats 19 data on Collisionswithin Devon

19


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Chapter 4

Overall temporal patterns relating toreported motorcycle collisions

Data was extracted for motorcycle collisions reported between 1996 and 2001 inclusive. Atpresent, data relating to either fatal or serious collisions have been classified. The collisiondescriptions have been categorised after Fleury and Brenac (2001). It is hoped that an investi-gation of this data will inform the requirements for more detailed research. With the exceptionof comparisons betweenblameworthyandnon-blameworthydrivers / riders, most of this datarepresents a description of collision reporting, rather than risk factors.

4.1 Temporal patterns in reported motorcycle colli-sions

Figure 4.2 shows that as with the local data (figure 4.1), national data also reports most fataland serious collisions on a Sunday. These seems to concur with the idea that there is an over-representation of leisure riders in the reported collisions. There are no significant differences inthe numbers of fatal collisions reported on the various weekdays, however when considering the

type of bike involved, figure 4.3 suggests that smaller bikes (mopeds and bikes below 125cc)are less involved on a Sunday. This also supports the idea that non-commuting bikes are over-represented in the reported collisions.

4.1.1 Weekend and weekday comparisons

Patterns of collision reporting in terms of hour of day and day of week are difficult to analyse fully.Simple evidence of this can be found by comparing the weekday time patterns with the weekendtime patterns (figure 4.4), but this in itself may still be an over-simplification. It is quite clearthat the peaks occur at different times at weekends than when compared with weekdays. There

21


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22 CHAPTER 4. TEMPORAL PATTERNS

Sun Mon Tues Weds Thur Fri Sat

KSI Collisions by weekday

0

20

40

60

80

100 Fatal

Serious

Figure 4.1: Reported Motorcycle Collisions 1996 - 2001 by severity and weekday of occur-rence


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4.1. TEMPORAL COLLISION PATTERNS 23

Figure 4.2: Day on which motorcycle collisions were reported Source: DfT Personal Trans-port Accidents: Motorcycles

seem to be rush-hour collision peaks apparent on weekdays, however on weekends collisionsseem to peak mid afternoon.

Figures 4.5 and 4.6 represent one attempt to depict the temporal data in more than one di-mension. Two dimensional kernel density estimation has been used in order to smooth thedata presented Venables and Ripley (1999). Figure 4.5 denotes a reversed-heat colour image, inwhich the redder a colour is drawn, the higher the proportion of collisions reported on that dayand at that time. Contour lines have also been plotted over this data (just to help emphasisethe very high peak in fatal and serious collisions early on Sunday afternoons). It is very clearthat there is a dominant peak occurring after Sunday lunchtimes, but this early afternoon peakcan also be seen later in the week. Figure 4.6 also depicts this information. Sunday is at therear of the chart, with Saturday at the front and the intermediate days in between. Again, thelunchtime peak in collisions can be seen, this more than overwhelms the smaller late afternoonpeak.

4.1.2 Comparison of time patterns between different bike sizes

It is very clear from figure 4.7 that small bikes are notably more involved in rush-hour collisions,whilst there is a clear lunch-time collision peak for the larger machines. It would be of greatinterest to compare the relative exposures of the two types of bikes. This however does providea strong hint that there are problems associated with riding at times that are neither associatedwith commuting rush-hours nor, unlike previous history Woodward (1983b), associated with


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KSI Collisions by motorbike type

0

20

40

60

80

100>125cc


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0000 0300 0600 0900 1200 1500 1800 2100

Weekend Collisions

0

5

10

15

20

0000 0300 0600 0900 1200 1500 1800 2100

Weekday Collisions

0

10

20

30

40

Figure 4.4: Reported Motorcycle Collisions 1996 - 2001 contrasting weekend and weekdaytime patterns


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Proportion of motorcycle

collisions by weekday and hour

Sun Mon Tue Wed Thur Fri Sat

2100

1800

1500

1200

0900

0600

0300

Figure 4.5: Reported Motorcycle Collisions 1996 - 2001: Image plot showing proportion ofcollisions happening on a given weekday at a given time


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Weekd

ay(Sun.

toSat

.)

Hour

Prop

ortio

nofc

ollis

ionsrep

o

rted

Proportion of motorcycle

collisions by weekday and hour

Figure 4.6: Reported Motorcycle Collisions 1996 - 2001: Image plot showing proportion ofcollisions happening on a given weekday at a given time


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0000 0300 0600 0900 1200 1500 1800 2100

Bike Type involvement by hour of day

0

10

20

30

40

>125cc


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4.2. SEASONAL VARIATIONS 29

Jan Mar May Jul Sep Nov

KSI Collisions by month

0

10

20

30

40

50

60FatalSerious

Figure 4.8: Reported Motorcycle Collisions 1996 - 2001 severity by month

pub closing hours.

4.2 Seasonal Variations

Figure 4.8 suggests that there are clear seasonal peaks in collision occurrence. This concordswith national data (figure 4.9), and also tends to contrast with overall collision causations(predominantly car collisions) which peak as the clocks change and winter sets in October.This does tend to suggest that there may be significant numbers of motorcyclists who only rideduring better weather. This may have little bearing on the existence of mature leisure riders,but clearly suggests that there are numbers of motorcyclists who do not have regular all yearround experience.


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Figure 4.9: National seasonal patterns in reported collisions. Source: DfT Personal Trans-port Accidents: Motorcycles

Fine Fine / windy Fog Other Rain Rain / windy SnowLarge 411 8 5 7 32 2 1

Moped 22 0 0 4 2 0 0Small 24 0 0 2 4 0 0

Table 4.1: Reported Motorcycle Collisions 1996 - 2001; Reported Weather and MotorbikeType

4.3 The effect of weather and road surface conditions

According to figure 4.10 there are no emergent patterns in terms of the weather, other thanit generally appears fine or fine / windy. There is very little month on month difference inthe proportion of collisions reported under different weather conditions. As one would assumedeteriorating weather during the winter months, this may well be consistent with the idea thatmotorcyclists are avoiding inclement weather.

It is very clear that more winter collisions happen on wet road surfaces (figure 4.11), whichseems to confirm the idea that bikes tend to be ridden in good weather conditions. It mustbe emphasised that given the wetter road surfaces in winter, one would anticipate greatercollision involvement and therefore this again suggests an over-involvement of leisure riders.This observation has also surprised other researchers considering motorcycle safety Horswill andHelman (2001) and really does suggest how much of a problem there may be with leisure riding.


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4.3. WEATHER AND ROAD SURFACE 31


Collisions by Month, reported weather

0

10

20

30

40

50

60FineFine / WindyFog

OtherRainRain / Windy

Figure 4.10: Reported Motorcycle Collisions 1996 - 2001; reported weather and month

Dry Ice Mud Oil WetLarge 345 4 1 1 115

Moped 21 0 0 0 7Small 23 0 0 0 7

Table 4.2: Reported Motorcycle Collisions 1996 - 2001; Road surface conditions and mo-torbike type


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Collisions by Month, reported road surface conditions

0

10

20

30

40

50

60Dry

IceMudOilWet

Figure 4.11: Reported Motorcycle Collisions 1996 - 2001; reported road surface and month


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FineFine /windy Fog Other Rain

Rain /windy Snow

Bike size involvement on different road types

0

100

200

300

400

>125cc< 125cc

Moped

Figure 4.12: Reported Motorcycle Collisions 1996 - 2001; Reported Weather and CollisionSeverity


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Dry Ice Mud Oil Wet

Bike size involvement on different road surfaces

0

50

100

150

200

250

300

350>125cc< 125cc

Moped

Figure 4.13: Reported Motorcycle Collisions 1996 - 2001; Road surface conditions andmotorbike type


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Dry Ice Mud Oil Wet

Severity on different road surfaces

0

50

100

150

200

250

300

350FatalSerious

Figure 4.14: Reported Motorcycle Collisions 1996 - 2001; Road Surface and Collision Sever-ity

As seen in figure 4.12 or table 4.1 there is very little evidence to contrast all weather commuterbikes (small bikes) with the larger bikes (fine weather sports bikes) but the classifications areextremely broad. Given the breadth of bikes that can be found above 125cc in size it could wellbe that there are numbers of commuter machines, touring machines and sports machines all ofwhich could have differing usage patterns according to weather conditions.

Perhaps of more interest than the types of bikes experiencing collisions in different road surfaceconditions is to examine the severity of these collisions (figure 4.14, table 4.3). Collisionsreported in the wet are two percent more likely to be fatal than collisions reported in the dry(figure 4.4). This does not seem noteworthy. This does not imply that there are not more fataland serious collisions in the wet, rather that they are no more likely to be fatal under theseconditions. It may be necessary to attempt to relate this to exposure.


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Dry Ice Mud Oil WetFatal 41 0 0 0 17

Serious 348 4 1 1 112

Table 4.3: Reported Motorcycle Collisions 1996 - 2001; Road Surface and Collision Severity

Dry Ice Mud Oil WetFatal 11 0 0 0 13

Serious 89 100 100 100 87

Table 4.4: Reported Motorcycle Collisions 1996 - 2001; Percent of fatalities according toweather conditions

4.4 Road and Junction Type

4.4.1 Junction Types

Figure 4.15 reports collisions by junction type. There are several disparities with the localcomparison (shown in figure 4.16, although it must be remembered that figure 4.15 includesslight collisions).

There are clearly more fatal and serious collisions in Devon (figure 4.16) which are reportedto have occurred on the open road, away from junctions, than is the case for all severitymotorcycle collisions reported nationally (figure 4.16. About half as many of Devons fatal andserious collisions are reported atT or Staggeredjunctions, and numbers of reported collisionsin Devon at many of the junction types are too modest to make meaningful comparisons. Onestriking over-representation in Devon is thePrivate Drive or entrancecategory. This suggeststhat things like farm entrances, garden centres, lay-bys and so on are more common collisionlocations for fatal and serious collisions in Devon than might have been expected.

4.4.2 Road Classifications

Figure 4.17 depicts national data regarding the road classification on which collisions werereported. The exact analogies havent yet been analysed locally, this is currently under con-sideration. In terms of the initial letter of the road classification, some data is reported fromDevon.

Both figure 4.18 and table 4.5 give the same information, namely that mopeds are seen moreoften in collisions on U roads, large bikes seen more often in collisions on A roads and Mo-torways. This may reflect on different usage patterns, and these may have a bearing on theseverity of collision involvement.


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4.4. ROAD AND JUNCTION TYPE 37

Figure 4.15: Collisions by Junction Type, Source: DfT Personal Transport Accidents:Motorcycles

A D Rural UrbanLarge 34 3 259 170

Moped 1 0 7 20Small 1 0 11 18

Table 4.5: Reported Motorcycle Collisions 1996 - 2001; Road Classification and Bike Size


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Cross roads

Miniroundabout

Multiple junction

Not at junction

Other junction

Private drive or entrance

Roundabout

Slip road

T or staggered junction

Y junction

Junction types where collisions

have been reported

0 50 100 150 200 250

FatalSerious

7%

0%

0%

51%

4%

12%

4%

2%

19%

1%

Figure 4.16: Reported Motorcycle Collisions 1996 - 2001; Bike collisions by junction type


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4.4. ROAD AND JUNCTION TYPE 39

Figure 4.17: Motorbike collisions reported nationally on different road classifications.Source: DfT Personal Transport Accidents: Motorcycles

In connection with the type of road on which the various sized bikes report collisions, it can beseen from figure ?? and table ?? that collisions on unclassified roads are less likely to be fatal

collisions than on other roads. This raises more questions than it answers, but does introduce apoint worthy of further consideration. It is possible to anticipate different types of motorcyclists,and different types of riding styles. The type of riding style perhaps most associated with acommuter on urban unclassified roads may be very different from that associated with a leisurerider on a fast sports machine. If this view is accepted, the differences in proportion of fatalcollisions seen on different classes of roads may have more to do with the preponderance ofriding styles seen than with the road per se.
http://www.transtat.dft.gov.uk/facts/accident/mcycle/mcycle98.htm


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A D Rural Urban

Bike size involvement on different road types

0

50

100

150

200

250

>125cc

< 125ccMoped

Figure 4.18: Reported Motorcycle Collisions 1996 - 2001; Road Classification and Bike Size


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Chapter 5

Causation patterns

5.1 External factors

5.1.1 Other vehicles

The simplest factor of interest in determining collision cause is the identity of any other ve-hicles involved. Figure 5.1 suggests that the numbers of single vehicle motorcycle collisionsare particularly high. This is extensively reported in other work, e.g. Hurt Jr. et al. (1981).

Conversely, figure 5.2 suggests that motorcycles are much less likely to injure most other vehicleoccupants. It is of little surprise that the pedal cyclist in a pedal cycle - motorcycle collisionis more likely to be injured than the motorcyclist. What has not been studied is the injury topedestrian road users. This study as it relates to Devon collision data only considers injuredmotorcyclists, but there have been fatalities to Car Drivers and Pedestrians in connection withmotorcycle collisions, and clearly there are also a range of injuries reported by the whole rangeof road users in connection with motorcycle collisions.

5.1.2 Road Defects

There is strong motorcycling anecdote that highways defects and poorly maintained highwaysare responsible for large numbers of collisions. Whilst it must be borne in mind that figure 5.3reports fatal and serious collisions (which are all highly undesirable) it is quite clear that in mostcases there was no reported defect. What this chart does not show is how many near-missesmotorcyclists have with road defects, and how much stress and compensatory riding in required.

41


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42 CHAPTER 5. CAUSATION PATTERNS

Bus

Car

Goods

HGV

LGV

Motorbike

NK

Pedal cycle

Pedal Cycle

PSC

Tractor

No other vehicle

Type of other vehicle involved

0 50 100 150 200 250 300

6

304

32

3

4

10

1

4

1

1

11

147

Figure 5.1: Reported Motorcycle Collisions 1996 - 2001; Other vehicle involvement


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5.1. EXTERNAL FACTORS 43

Figure 5.2: Motorbike casualties in relation to other vehicle. Source: DfT Personal Trans-port Accidents: Motorcycles


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None reported

Animals

Vehicle Defect

Slippery

Object

Mud

Gravel

Leaves

Highways Defect

Diesel

Cow Dung

Blow Out

Reported Road Defects

0 100 200 300 400 500

502

6

1

1

1

3

3

2

2

1

1

1

Figure 5.3: Reported Motorcycle Collisions 1996 - 2001; Reported Defects


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5.2. COLLISION PATTERNS 45

Lossofcontrolandleftroad

Vehicleemergingfroms

ideroad

Cutupbyvehicleturningintosideroad

Headoncuttingcorner

Failedtostopforvehicleinfront

Overtakenvehicleturnedintopath

Knockforknockheadon

Headonwhilstovertaking

Negligentvulnerableroaduser

Carelessovertakingbyothervehicle

Conflictwhilstovertaking

Motorbikeemergingfroms

ideroad

U

Turn

Animal

Largepileup

Hitinrear

Onewayerror

Hitparkedvehicles

Clippedbyvehicletravellingopposite

Unknown

ReversingHGV

Motorbikeattemptedrightexit

Carreversedintomotorbike

um

ero

o

sons

0

20

40

60

80

100

120

1

40

0

20

40

60

80

100

CumulativePercentage

Figure 5.4: Reported Motorcycle Collisions 1996 - 2001; Classified collision patterns

5.2 Collision patterns

Based on the police text descriptions, an attempt has been made to classify the manoeuvreresponsible for the collision.

The aim of a Paretodiagram is to try and depict the 80:20 rule. The bar chart is arrangedin order of how commonly each collision pattern was recorded, and the actual number of occur-rences is recorded on the right hand axis. A single curve, depicting the cumulative percentageof all collisions explained by reading from left to right is superimposed. It is possible to see howmany of the causation patterns explain 80% of collisions. In systems with less human factorsinvolved, most effort would be directed towards dealing with these 80% of collisions. However,given that human systems are more complex, countermeasures may have to be applied wherethey can be devised, but this chart may still be useful in suggesting the likely impact of anycountermeasures.

The top four-fifths of all collisions seem to be:


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Loss of control and left road

Vehicle emerging from side road

Cut up by vehicle turning into side road

Head on cutting corner

Shunt

Overtaken vehicle turned into path

Knock for knock head on

Head on whilst overtaking

The second and third most common collision type appear to be largely the responsibility ofthe other road user. Presumably these reflect the looked but did not see type of collision.Whilstknock for knock head onis ambivalent, all remaining collision types, including the mostcommon, the single vehicle pattern loss of control and left road are largely within the ridersown domain.

Looked but did not seecollisions raise a number of points. Horswill and Helman (2002) dividethis into cognitive and sensory conspicuity. Clearly countermeasures aimed at other road usersare important, and some current work by Graham Hole and Martin Langham suggests that this

may be possible. Without shifting responsibility, questions have to be asked as to how ridingstyles, conspicuity of clothing and lighting may help riders to avoid these types of collisions.

5.2.1 Collision patterns reported in fatal collisions

Four fifths of all fatal collisions, according to the descriptions presented in 5.5, have beenclassified with the following patterns:



U Turn

Shunt



Careless overtaking by other vehicle


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Losso

fcon

tro

lan

dleftroa

d

Hea

doncu

ttingco

rner

U

Turn

Fa

ile

dtos

top

forve

hiclein

fron

t

Ve

hicleemerg

ing

from

side

roa

d

Hea

donw

hils

toverta

king

Care

lessoverta

king

byo

therve

hicle

An

ima

l

Neg

ligen

tvu

lnera

bleroad

user

Cu

tup

byve

hicleturn

ing

intos

ideroa

d

Con

flictw

hils

toverta

king

Un

kn

own

Overta

kenve

hicleturne

dinto

pa

th

Largepi

leup

Hitin

rear

Revers

ing

HGV

Onewayerror

Mo

torb

ikeemerg

ing

from

sideroa

d

Mo

torb

ikea

ttemp

tedrigh

tex

it

Knoc

kfor

knoc

khea

don

Hitparke

dveh

icles

Clippe

dbyve

hicletrave

llingoppos

ite

Carreverse

dintomo

torb

ike

um

ero

o

sons

0

5

10

15

0

20

40

60

80

100

Cumu

lative

Percen

tage

Figure 5.5: Reported Motorcycle Collisions 1996 - 2001; Classified collision patterns forfatal collisions


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Lossofcontrolandleftroad

Vehicleemergingfroms

ideroad

Cutupbyvehicleturningintosideroad

Headoncuttingcorner

Overtakenvehicleturnedintopath

Knockforknockheadon

Failedtostopforvehicleinfront

Headonwhilstovertaking

Negligentvulnerableroaduser

Carelessovertakingbyothervehicle

Conflictwhilstovertaking

Motorbikeemergingfroms

ideroad

Largepileup

Animal

U

Turn

Hitinrear

Onewayerror

Hitparkedvehicles

Clippedbyvehicletravellingopposite

ReversingHGV

Motorbikeattemptedrightexit

Carreversedintomotorbike

Unknown

NumberofCollisions

0

20

40

60

80

100

12

0

0

20

40

60

80

100

CumulativePercentage

Figure 5.6: Reported Motorcycle Collisions 1996 - 2001; Classified collision patterns forserious collisions

It can be seen in the fatal collisions that they are more dominated by collision patterns thatappear to be entirely within the control of the rider. Whilst vehicles emerging from side roadsis still a significant contributor, it is not as prominent as with all collisions, and it is difficult toaccurately assess careless overtaking by other vehicle from the brief descriptions in the Stats

19 report.

5.2.2 Collision patterns reported in serious collisions

Figure 5.6 is basically the same as 5.4, as Serious collisions are the most common type ofcollision. Again, the most common four-fifths of serious collisions have been classified as havingthe following patterns:



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Knock for knock head on

Shunt


5.2.3 Collision patterns reported in small motorbike and mopedcollisions

It is possible to extract the four-fifths most common collision patterns from figure 5.7. Whilst thenumbers of reported collisions in this category are much smaller, it is clear that proportionatelymore of the collisions are within the remit of the other driver. This raised several questionsabout the perspicuity and conspicuity of the small motorbike rider, and how the lack of ridingexperience may put them in situations where they are threatened by other road users. It impliesthe need for some kind of training work to improve defensive riding techniques, which possibly

includes consideration of road positioning.


Loss of control



Motorbike emerging from side road

Hit in rear

5.2.4 Timings of the most common collision patterns

Figure 5.8 seems to imply that single vehicle loss of control collisions are most commonly re-ported around mid-day and tea-time, whereas being hit by an emerging vehicle is most commonmid-afternoon to late afternoon. It may be that the numbers are too small to draw any defini-tive conclusions about this, but this reveals an interesting picture when combined with theinformation regarding the weekday on which collisions were reported.


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Ve

hicleemerg

ing

from

side

roa

d

Losso

fcon

tro

lan

dleft

roa

d

Cu

tup

byve

hicleturn

ing

intos

ide

roa

d

Overta

kenve

hicleturne

dinto

pa

th

Mo

torb

ikeemerg

ing

from

side

roa

d

Hitin

rear

Fa

ile

dtos

top

forve

hiclein

fron

t

Revers

ing

HGV

Neg

ligen

tvu

lnera

bleroad

user

Knoc

kfor

knoc

khea

don

Hitparke

dveh

icles

Hea

doncu

ttingcorner

Con

flictw

hils

toverta

king

Clippe

dbyve

hicletrave

llingopp

os

ite

Care

lessoverta

king

byo

therve

hicle

An

ima

l

Unkn

own

U

Turn

Oneway

error

Mo

torb

ikea

ttemp

tedrigh

tex

it

Largepi

leup

Hea

donw

hils

toverta

king

Carreverse

dintomoto

rbike

Num

bero

fCo

llision

s

0

5

10

15

0

20

40

60

80

100

Cumu

lative

Percenta

ge

Figure 5.7: Reported Motorcycle Collisions 1996 - 2001; Classified collision patterns forsmall bike and moped collisions


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0000 0200 0400 0600 0800 1000 1200 1400 1600 1800 2000 2200


0

2

4

6

8

10

12

0000 0200 0400 0600 0800 1000 1200 1400 1600 1800 2000 2200


0

5

10

15

0000 0200 0400 0600 0800 1000 1200 1400 1600 1800 2000 2200


0

1

2

3

4

5

6

Figure 5.8: Reported Motorcycle Collisions 1996 - 2001; Hourly patterns for top threecollision types


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0

5

10

1520

25

30

35



0

5

10

15



0

2

4

6

8

10

12

Figure 5.9: Reported Motorcycle Collisions 1996 - 2001; Daily patterns for top three colli-sion types


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As may have been anticipated, figure 5.9 suggests that Sunday is the most common day forsingle vehicle loss of control collisions. This is consistent with the idea that leisure riders are atincreased risk.


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Chapter 6

Age and Gender of collisionparticipants

6.1 Comparing riders with the involved car drivers

Figure 6.1: Relative risk of collision involvement. Source: DfT Personal Transport Acci-dents: Motorcycles

55


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56 CHAPTER 6. AGE AND GENDER

0 20 40 60 80

0.

00

0.0

2

0.

04


0 20 40 60 80

0.

00

0.0

2

0.

04


0 20 40 60 80

0.

00

0.0

2

0.

04


Figure 6.2: Reported Motorcycle Collisions 1996 - 2001; Age of riders in the three mostcommon collision types

0 20 40 60 80

0.

00

0.

02

0.

04


0 20 40 60 80

0.

00

0.

02

0.

04


0 20 40 60 80

0.

00

0.

02

0.

04


Figure 6.3: Reported Motorcycle Collisions 1996 - 2001; Age profile for the other driver in

the three most common collision types (excluding single vehicle collisions)

One of the few concrete pieces of information that is readily available from the data is the age ofboth the motorbike rider and also the age of the driver of the other vehicle (where applicable).It is also possible to combine this information with the collision classifications described inthe previous chapter. This allows a comparison between responsible participants, and non-responsible participants. Contrasting the two helps to control for the overall age structure ofthe driving and riding population. As has been reported in other road safety contexts, this work

can be extended using Bradley-Terry models Li and Kim (2000).

Figure 6.3 should contrast a random sample of motorists (those hit by motorcycles involved in acollision as a result of ahead on cutting cornertype of collision) and two categories oflookedbut did not seemotorists (those hitting motorcycles having emerged from side roads and thoseturning into side roads). Lynam et al. (2001) suggested that 30 - 60s were mainly responsibleforlooked but did not seecollisions, but these figures actually tend to suggest that the reasonfor their apparent over-involvement is simply that they are the most likely age of driver to be onthe road at the same time as motorcycles. Some work has been done on matching by Horswilland Helman (2001), and it would be possible to follow this up with Bradley-Terry models (e.g.Li and Kim (2000)) to confirm whether there is any evidence of over-involvement of riders anddrivers of different ages.


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6.2. RIDER AGE AND COLLISION SEVERITY 57

Age of riders in fatal and serious collisionsAge of riders in fatal and serious collisions

50 0 50 100 150

10

20

30

40

50

60

70

80

90100

Fatal Serious

Figure 6.4: Reported Motorcycle Collisions 1996 - 2001; Age, bike size and reported collisionseverity

6.2 Rider Age and Collision Severity

Figure 6.4 presents a very interesting picture. It seems to contrast with Mullin et al. (2000) asthe data from Devon suggests that the chances of a fatal collision relative to a serious collisionappear to increase with age.However, Mullin et al. (2000) suggested that age was protective.It would also be interesting to compare this with the similar patterns for car drivers, as Horswilland Helman (2001) suggest that injured motorcyclists tend to have the same age profile asinjured drivers. Whilst these are raw numbers and do not take account of exposure, only onepeak can be representative of the most exposed riders. It also appears to contrast with thefindings of Rutter and Quine (1996) that younger riders are more likely to be killed or seriously

injured. We have little adequate data on exposure within Devon. We do know that there hasbeen a dramatic recent increase in slight collisions amongst younger riders on smaller machines.However, the elevated peak age for fatally injured riders appears anomalous, and is consistentwith the idea that there are a sub-group of riders whose behaviour differs significantly frommany other injured riders and is putting them at enhanced risk of being involved in a fatalcollision.

Figure 6.5 seems to confirm that riders on the larger bikes are largely responsible for the peaknumbers of 30-something fatal and serious collisions. Moped collisions predominantly involveyounger riders. The scales on this graph may be slightly deceptive, in that there are far morecollisions reported on larger bikes than either mopeds or small motorcycles. The delayed peakin fatalities is therefore not simply due to migration of riders from small to large machines.


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Severity and Age (large bikes)Severity and Age (large bikes)

50 0 50 100 150

0

10

20

30

40

50

60

70

80

100

Fatal Serious

Severity and Age (small bikes)Severity and Age (small bikes)

5 0 5 10 15

0

10

20

30

40

50

60

70

80

100

Fatal Serious

Severity and Age (mopeds)Severity and Age (mopeds)

5 0 5 10 15

0

10

20

30

40

50

60

70

80

100

Fatal Serious

Figure 6.5: Reported Motorcycle Collisions 1996 - 2001; Age, bike size and reported collisionseverity

F MFatal 2 56

Serious 36 430

Table 6.1: Reported Motorcycle Collisions 1996 - 2001; Gender and reported collisionseverity

Figure 6.6 along with table 6.1 demonstrate the considerable disparity between male rider in-volvement and female rider involvement. Whilst sensible control for exposure is not possible,there are 12 times as many fatal and seriously injured male riders, National Travel Survey datasuggests male riders take 6 times as many trips as females. There is an implication in this graph,which cannot be verified without further work, that female riders are at less risk of involvement

in a fatal or serious motorcycle collision.

It may be of some interest to compare the age profiles of male and female riders involved inserious and fatal motorcycle collisions. Both genders collision profile peaks in the 20s, whichmay simply be reflective of exposure. However, female collisions seem to tail off quicker andthere is no later peak of fatal collisions. Again, it must be emphasised very strongly that this isnot exposure adjusted data, more females may give up riding after their 20s. However, it doeshighlight an apparent problem with male 30 somethings who are more likely than most to beinvolved in fatal collisions.


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6.2. RIDER AGE AND COLLISION SEVERITY 59

F M

Severity and Gender

0

100

200

300

400

Fatal

Serious

Figure 6.6: Reported Motorcycle Collisions 1996 - 2001; Gender and reported collisionseverity


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Severity and Age (Males)Severity and Age (Males)

50 0 50 100 150

0

10

20

30

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Fatal Serious

Severity and Age (Females)Severity and Age (Females)

5 0 5 10 15

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30

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Fatal Serious

Figure 6.7: Reported Motorcycle Collisions 1996 - 2001; Age, gender and reported collisionseverity


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Chapter 7

Conclusions

7.1 General

One feature which may be distinct to Devon is that there are more Fatal and Serious collisionsreported on the open road than is seen with all-severity collisions reported nationally. If thecomparison is valid there are also more collisions at private drives and similar junctions. Thisneeds to be confirmed, as there is a simple educational message in terms of being cautious nearthese types of junctions.

It is quite clear that researchers at Reading University have developed a set of simulator scenariosdesigned to assess motorcycling and driving behaviour, hazard assessment, risk taking and soon. This could form a valuable addition to the services offered by the Devon Drivers Centre.This would offer both the potential for third party research and individual feedback on behaviourpatterns. If this was the kind of facility that could be taken into schools it may overcome someof the barriers to training participation.

7.2 Young riders

It has to be stated, that whilst not over-represented in the fatal collisions, young riders are arapid growth area in terms of powered two-wheel collision involvement.

Research from outside the UK suggests that familiarity with a particular machine is an importantprotective factor, yet other studies point to unlicensed riding and borrowing of motorcyclesbeing commonplace. Given the age of this group there should therefore be some potential forinfluencing the education curriculum with a view to communicating this message. It may alsobe possible at the same time to collect data to confirm whether this is an issue in Devon ornot. Ways of increasing experience in a controlled road environment may also be of value.There may be a synergy of interests with the various motorcycling organisations in providing

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62 CHAPTER 7. CONCLUSIONS

a partially controlled environment which doesnt quite have the formality of schemes such asBikesafe. Incentives to encourage participation are likely to be a problem. There is considerablepotential with this target audience for innovative methods of communication, and it should be

borne in mind that small motorcycles or mopeds may be addressing social exclusion issues interms of access to work, leisure and services.

7.3 Older riders

There is strong evidence that within the collision data, male 30-somethings are over-represented.In particular, they appear to be over-represented in terms of fatal collision involvement, and thisinvolvement seems to include excessive numbers of collisions that could be prevented by the

rider alone. Two possibilities for further work (which may be duplicated elsewhere such as atLeeds University) are:

Trawl through coroners records to obtain full details on the type, style and size or bikeridden

Case controlled study on driver collision history and possibly driver attitudes.

7.4 Other Road Users

There is ample evidence to suggest thatlooked but did not seecollisions are still very common.Interestingly, what little research exists on motorcycle conspicuity is inconclusive, but there isevidence thatlookingcan be taught. There are therefore issues in terms of what DDC trainingcan be enhanced in this regard, even if this represents a very small part of the driving pool (forexample Pass Plus). Three quarters of motorbike collisions involve collisions with other vehicles,a sizeable number of which are looked but did not see type collisions. There may also besome scope for teaching road positioning techniques that makes motorcycles more visible andless prone to this type of collision.

7.5 Further data analysis

If suitable IT were made available, the following points would be worth following up:

More detailed geographical investigation of the collision types and where they occur (forexample it would be of great interest to identify problem leisure runs and also identify thenature of the private drives over-represented in the local data).


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7.5. FURTHER DATA ANALYSIS 63

Potential for data mining

motorcycle casualty data

|Motorbike.Impact=Animal,Head on cutting corner,U Turn,Unknown

Month=Dec,Feb,Jan,Mar,May,Sep

Serious

58/466

Serious

22/42

Fatal

13/7

Serious

9/35

Serious

36/424

Figure 7.1: Reported Motorcycle Collisions 1996 - 2001; Simple example of recursive par-titioning with motorcycle collision data

Comparison with slight motorcycle collisions

Comparison with car collisions, possibly by randomly selecting collisions from demograph-ically matched car drivers

Multivariate investigation of collision patterns (for example figure 7.1).

Figure 7.1 gives a very simple example of the type of multivariate investigation that could beconducted by the use of recursive partitioning (Therneau and Atkinson, 1997) which is onetechnique that has been applied in a data mining context. In this case, U Turns, Collisionswith Animals, and unknown collisions during predominantly winter months appear to be char-acteristically fatal. This type of research could also profitably be applied to the OTS typedata.


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64 CHAPTER 7. CONCLUSIONS


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Acknowledgements

The Motorcycle data has been supplied by Devon and Cornwall Constabulary and is basedon the local version of the Stats 19 reporting system.

Audrey Haslam has helped locate and order a number of the research papers.

The R software Ihaka and Gentleman (1996) has been used to analyse the data, in partic-ular using the Sweave functions to create a literately programmed report processed withLATEX. Credit is therefore due to rather a lot of developers who make all of this best ofclasssoftware available under a range of free software licences.

Feedback on data presented at both the Road Safety Group team meeting, and an initialtask forcemeeting at the Devon Drivers Centre in May has helped influence the directionof this report.

The University of Exeter has assisted in the provision of the computational facilities re-

quired for this investigation.

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http://www.r-project.org/


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66 ACKNOWLEDGEMENTS


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