BICYCLE AND MOTOR VEHICLE CRASH CHARACTERISTICS

Transcription

1 BICYCLE AND MOTOR VEHICLE CRASH CHARACTERISTICS by Linda Watson Max Cameron Report No. 5 September 6

2 Project Sponsored By ii MONASH UNIVERSITY ACCIDENT RESEARCH CENTRE

3 MONASH UNIVERSITY ACCIDENT RESEARCH CENTRE REPORT DOCUMENTATION PAGE Report No. Report Date ISBN Pages 5 September Appendices Title and sub-title: Bicycle and motor vehicle crash characteristics Author(s) Type of Report & Period Covered Watson, L.M.& Cameron, M.H. Summary Report, -4 Sponsoring Organisations - This project was funded as contract research by the following organisation: Amy Gillett Foundation Abstract: This report describes the characteristics of crashes involving bicycles and motor vehicles and was based on data on police reported crashes in Victoria, Queensland, Western Australia and South Australia during -4. Crashes involving 3,9 bicycle riders were matched to colliding motor vehicles and their drivers. These collisions were used to describe characteristics of bicycle crash circumstances, demographics and serious injury outcomes of both bicycle riders and motorists involved. Results of the research has been valuable in providing insight into understanding bicycle and motor vehicle collisions resulting in injury to the bicycle rider. Directions for further research have been suggested. Key Words: (IRRD except when marked*) Accident, Bicycle, Bicycle Rider, Cyclist, Collision, Crash, Injury, Motorcyclist, Motor Vehicle, Motorist, Pedestrian, Road User, Vehicle, Chart Disclaimer: This Report is produced for the purposes of providing information concerning the safety of vehicles involved in crashes. It is based upon information provided to the Monash University Accident Research Centre by VicRoads, the Transport Accident Commission, the New South Wales Roads and Traffic Authority, NRMA Ltd, Queensland Transport and the Western Australian Department of Main Roads. Reproduction of this page is authorised Monash University Accident Research Centre Building 7, Monash University Victoria 38, Australia. Telephone: , Fax: BICYCLE AND MOTOR VEHICLE CRASH CHARACTERISTICS: TO 4 DATA iii

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5 EXECUTIVE SUMMARY This study is an exploratory one to characterise bicycle and motor vehicle crashes. It is based on real crashes reported to police from Victoria, Queensland, South Australia and Western Australia during -4. Crashes involving bicycle riders were identified and 3,9 bicycle riders matched to colliding motor vehicles and their drivers. These collisions were used to describe characteristics of bicycle crash circumstances, demographics and serious injury outcomes of both bicycle riders and motorists involved. Crashes of vehicles from adjacent directions at intersections predominate along with events involving manoeuvres of either vehicle such as u-turns and entering or leaving parking. The crash occurred on the straight for 9.7% of crashes and 98.6% of crashes occurred on sealed roads. Monday to Friday were the most common days for crashes to occur, with crashes being least frequent on Saturdays and Sundays. Crashes were more likely to occur in the time periods pm to 6pm and 6am to am than any other time of the day with crash frequencies highest from pm to 6pm. Crashes were more common in February and March with a decline apparent during the winter months. Overall 8% of crashes involved male bicycle riders. Bicycle riders aged 6 to 9 years were involved in crashes the most followed by bicyclists aged to 9 years. Crash involvement for these age groups was 9.% and.% respectively. Overall 54% of crashes involved male motorists and 36.5% of crashes involved female motorists. Motorists aged 3 to 39 years were involved in crashes the most followed by motorists aged 4 to 49 years and to 5 years. Crash involvement for these age groups was 8.%, 4.5% and 3.5% respectively. In general, crashes involving bicycle riders are seldom reported to the Police unless someone is killed or injured (usually the bicyclist) hence only injury crashes are considered in this report. Serious injury is defined as an injury requiring admission to hospital or death. The rate of bicycle riders killed or seriously injured has remained relatively constant over the period to 4 and the average risk of death or serious injury for bicycle riders involved in the reportable crashes used in this study is around 7%. Injury severity remains relatively static for to 49 year old bicycle riders with the risk of serious injury for those aged under increasing inversely with age. Similarly the risk of serious injury increases with age for 5 year olds and above. In summary, results of the research has been valuable in providing insight into understanding bicycle and motor vehicle collisions resulting in injury to the bicycle rider. Directions for further research have also been suggested.. BICYCLE AND MOTOR VEHICLE CRASH CHARACTERISTICS: TO 4 DATA v

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7 CONTENTS Page No.. INTRODUCTION.... BACKGROUND.... PROJECT MOTIVATION AND AIMS.... CRASH DATA.... COLLISIONS INVOLVING BICYCLES.... COLLISIONS INVOLVING BICYCLES AND MOTOR VEHICLES BICYCLE CRASH CHARACTERISTICS TEMPORAL CHARACTERISTICS Week day of crash Time of crash Month of crash MOTOR VEHICLE CHARACTERISTICS Motor vehicle market group categories ROAD USER MOVEMENT CHARACTERISTICS LOCATION CHARACTERISTICS Horizontal road alignment Vertical road alignment Light conditions Road surface Road condition Speed zone BICYCLE RIDER CHARACTERISTICS BICYCLE RIDER DEMOGRAPHICS Sex Age BICYCLE RIDER INJURY SEVERITY CHARACTERISTICS Injury severity by state Injury severity by year of crash Injury severity by sex Injury severity by age Injury severity by time of crash Injury severity by collision partner market group Injury severity by speed zone Injury severity by group road user movement COLLIDING MOTORIST CHARACTERISTICS COLLIDING MOTORIST DEMOGRAPHICS Sex Age COLLIDING MOTORIST INJURY CHARACTERISTICS Injury severity by state Motorists injury severity by bicyclist injury severity DISCUSSION SUMMARY OF CHARACTERISTICS OF BICYCLE AND MOTOR VEHICLE COLLISIONS Type of crash...8 BICYCLE AND MOTOR VEHICLE CRASH CHARACTERISTICS: TO 4 DATA vii

8 6.. Temporal characteristics Bicycle riders Bicycle riders seriously injured Motorists CONCLUSIONS ASSUMPTIONS AND QUALIFICATIONS ASSUMPTIONS REFERENCES...3 APPENDICES APPENDIX. Victorian bicycle and motor vehicle crash characteristics, additional tables APPENDIX. Queensland bicycle and motor vehicle crash characteristics, additional tables APPENDIX 3. Western Australian bicycle and motor vehicle crash characteristics, additional tables APPENDIX 4. South Australian bicycle and motor vehicle crash characteristics, additional tables APPENDIX 5. Bicycle and pedestrian crash characteristics APPENDIX 6. Bicycle and motorcycle crash characteristics viii MONASH UNIVERSITY ACCIDENT RESEARCH CENTRE

9 BICYCLE AND MOTOR VEHICLE CRASHES Victorian, Queensland, Western Australian and South Australian crashes occurring during -4. INTRODUCTION. Background Bicycle riders together with pedestrians and motorcyclists are among the most vulnerable road users. Previous research (Newstead et al, 4b) on unprotected road users found the average risk of death or serious injury for unprotected road users involved in reportable crashes is around 35%. For drivers of light vehicles, the highest average risk of death or serious injury in a reported crash is around % in single vehicle crashes or about one third the risk of an unprotected road user. This compares with an average serious injury risk of only.3% for light vehicle drivers in crashes with other light vehicles, only one fifteenth the risk of an unprotected road user. Interpreting this in a total serious road trauma context shows the relative importance of reducing crashes involving unprotected road users compared to crashes involving light vehicle drivers. The Amy Gillett Foundation has been established to promote a safe and harmonious relationship between cyclists and motorists. To facilitate this aim an exploratory study has been undertaken to characterise crashes between bicycle riders and motorists.. Project Motivation and Aims In order for the Amy Gillett Foundation to inform its marketing and awareness strategy data from bicyclist and motorist incidents for the period to 4 was gathered to characterise crashes. Of particular interest are: Age and gender of each cyclist and motorist involved in an incident Weather conditions at the time of the accident Time of day and month of the accident Location Level of injury Cause of incident With this information a better understanding of bicycle crash characteristics was obtained, including age/gender groups for both cyclists and motorists involved in incidents, times of the day/year crashes occur, and weather conditions. The Foundation s Marketing Advisory Group will use this information to develop effective and targeted key messages and awareness campaigns. BICYCLE AND MOTOR VEHICLE CRASH CHARACTERISTICS: TO 4 DATA

10 . CRASH DATA Data from Victoria, Queensland, South Australia and Western Australia covering police reported crashes during the years -4 was used in this project. In general, crashes involving unprotected road users such as pedestrians, bicyclists and motorcyclists are seldom reported to the Police unless someone is killed or injured (usually the unprotected road user) hence only serious injury risk is considered in this report. It was not possible to use the to 4 records from New South Wales crash data because as a result of coding changes a reliable measure of injury severity was not available for the years 999 onwards. In addition, a subset of the data including vehicle market group, used to produce the crashworthiness and aggressivity ratings of Newstead et al (6) was used. The method of selecting appropriate cases from the data source is briefly detailed here.. Collisions Involving Bicycles Bicycle riders injured in a collision were identified in each of Victoria, Queensland, South Australia and Western Australia using variables identifying unit type or road user type. The combined data reported in Table shows a total of 5,685 bicyclists were involved in police reported crashes of all crash types in Victoria, Queensland, South Australia and Western Australia during each of the years -4. These bicycle crashes are displayed graphically in Figure. In order to obtain the subset of the crash data where a bicycle rider was involved in a collision with a motor vehicle a matching process was required to identify impacting units. Impacting units once identified, were then categorised into one of four types. Four categories were used, being bicycle collisions involving motor vehicles, motorcycles, pedestrians and other. Bicycle riders, pedestrians, motor vehicles and motorcyclists are all coded as units in each of the states. In addition some states code objects involved in collisions, such as trees or posts as units. It is these matched units that fall into the category other. This category, if combined with bicycle records that were unable to be matched in the matching process would provide a full description of all other bicycle crash types. These crash types are not described further in this report. Table : Numbers of bicyclists injured in crashes in Victoria, Queensland, South Australia and Western Australia during each of the years -4. Year of crash 3 4 N % N % N % N % N % N % State Victoria,43 9., 8.33,55.5,48 9.9,5.4 5,46 Queensland ,43 Western Australia ,68 South Australia ,74 3, ,.47 3,66.8, ,.47 5,685 MONASH UNIVERSITY ACCIDENT RESEARCH CENTRE

11 Figure : Number of bicyclists involved in crashes by state and year of crash Number of bicyclists Year of crash VIC QLD WA SA TOTAL Table describes the breakdown by crash type of the 4,98 bicycle riders matched to colliding units. Of interest for this report is the 3,9 bicycle riders matched to motor vehicles and it is this data that is described in the remaining sections of this report. Additional tables, some particular to each state are included in Appendices to 4. Appendices 5 and 6 provide a basic insight into bicycle collisions with pedestrians and motorcycle riders respectively. Table : Collision partner by state Colliding unit Pedestrian Motorcycle Motor vehicle Other N % N % N % N % N % State Victoria , , Queensland , ,85 Western Australia , ,887 South Australia , , , ,98 BICYCLE AND MOTOR VEHICLE CRASH CHARACTERISTICS: TO 4 DATA 3

12 . Collisions Involving Bicycles and motor vehicles The distribution of the 3,9 crashes between bicycle riders and motor vehicles by state and year of crash is described in Table 3. Table 3: Crashes between bicyclists and motorists by state Year of crash 3 4 N % N % N % N % N % N % State Victoria , ,8.35 4,83 Queensland ,759 Western Australia ,837 South Australia ,473, ,847.48,95.9,6 8.85, ,9 3. BICYCLE CRASH CHARACTERISTICS 3. Temporal characteristics The days of the week and the months when crashes occurred are summarised in Tables 4 and 6 respectively and described graphically in Figures and 4. The times of the day when crashes occurred are summarised in Table 5 and described graphically in Figure Week day of crash Monday to Friday were the most common days for crashes to occur, with crashes being least frequent on Saturdays and Sundays. 4 MONASH UNIVERSITY ACCIDENT RESEARCH CENTRE

13 Table 4: Week day of crash N % Day of Week Unknown*, Sunday Monday,668. Tuesday, Wednesday, Thursday, Friday,76.67 Saturday, 8.7 3,9 *Day of week unknown for South Australia Figure : Percentage of bicycle crashes by day of week 5 5 SUNDAY MONDAY TUESDAY THURSDAY FRIDAY SATURDAY WEDNESDAY BICYCLE AND MOTOR VEHICLE CRASH CHARACTERISTICS: TO 4 DATA 5

14 3.. Time of crash Crashes were more likely to occur in the time periods pm to 6pm and 6am to am than any other time of the day with crash frequencies highest from pm to 6pm. Table 5 shows crash frequencies by time of day in detail and Figure 3 displays this information graphically. Table 5: Time of crash N % Time of crash Unknown 8. Midnight to 6 am am to 8 am, am to am,9 4.5 am to midday, Midday to pm,7 9.4 pm to 4 pm, pm to 6 pm, pm to 8 pm, pm to midnight ,9 Figure 3: Percentage of bicycle crashes by time of day Midnight to 6 am 6 am to 8 am 8 am to am am to midday Midday to pm Time of day pm to 4 pm 4 pm to 6 pm 6 pm to 8 pm 8 pm to midnight 6 MONASH UNIVERSITY ACCIDENT RESEARCH CENTRE

15 3..3 Month of crash Table 6 shows the frequency of crash occurrence by month for states Victoria and South Australia and Figure 4 displays this graphically. Crashes were more common in February and March with a decline apparent during the winter months. Table 6: Month of crash N % Month of crash Unknown * 6, January February March April May June July August September October November December ,9 * Queensland and Western Australia unknown Figure 4: Percentage of bicycle crashes by month of year 7 6 % crashes Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Month BICYCLE AND MOTOR VEHICLE CRASH CHARACTERISTICS: TO 4 DATA 7

16 3. Motor vehicle characteristics 3.. Motor vehicle market group categories In the most recent update of the vehicle safety ratings (Newstead et al, 6) rated vehicles were classified into one of 3 market group classifications, comprising 8 classes of regular passenger car, 3 classes of four wheel drive (4WD) vehicle (also known as Sports Utility Vehicles) and classes of light commercial vehicle. The market groups defined are based heavily on those used by the Federal Chamber of Automotive Industries (FCAI) for reporting Australian vehicle sales as part of their VFACTS publication (see for further details). The market groups were defined as follows. Passenger Cars Light Small Medium Large People Movers Sports Luxury Passenger car, hatch or sedan 3 or 4 cylinder engine, up to,5 cc. Passenger car, hatch, sedan or wagon, 4 cylinder engine,,5 cc -,9 cc. Passenger car, hatch, sedan or wagon, 4 cylinder engine,,9 cc upward. Passenger car, hatch, sedan or wagon, 6 or 8 cylinder engine. Passenger usage seating capacity > 5 people. Coupe or convertible Highly specified passenger cars, coupe, convertible, hatch, sedan or wagon. Four Wheel Drive Vehicles (high ground clearance, off road wagon) 4WD Compact 4WD Medium 4WD Large Index rating < 55 (typically less than 7kg tare mass) Index rating 55 < 7 (typically between 7kg and kg tare mass) Index rating > 7 (typically greater than kg tare mass) Light Commercial Vehicles Van Utility Blind & window vans. Two and four wheel drive, normal control (bonnet), utility, cab chassis and crewcabs. The classification of 4WD vehicles is based on an index developed by VFACTS that considers gross vehicle mass, maximum engine torque and the availability of a dual range transmission. The index typically classifies the vehicles roughly by tare mass as indicated on the classifications above. Some departures from the VFACTS classification have been made in presenting the ratings in this study. VFACTS defines a luxury 4WD category based on vehicle price as well as classifying sports cars priced above the luxury car tax threshold as luxury vehicles. Here, the luxury 4WDs have been distributed amongst the 3 defined 4WD categories based on tare mass, as the information for computing the classification index used by VFACTS was not available at the time of the study. All sports cars have been classified as such, regardless of price. There have also been some departures from the classification principles defined above for certain vehicle models that have a range of engine sizes and hence fall across two different defined categories. These are typically passenger vehicles and include, for example, cars like the Toyota Camry that come fitted with a large 4 cylinder engine in some variants and a 6 cylinder engine in other variants. In these cases, a value judgement has been made for each vehicle model individually based on the other vehicle models with which each typically competes in the market place. 8 MONASH UNIVERSITY ACCIDENT RESEARCH CENTRE

17 Table 7 summarises the distribution of bicycle crashes by vehicle market group for vehicles where this information is available. Further research on exposure is required to identify if any market group is over or under represented and thus poses a greater or lesser risk of collision with a bicycle rider. Table 7: Colliding motor vehicle market group by state State Victoria Queensland Western Australia N % N % N % N % Vehicle market group Unknown, , , , Four Wheel Drive - Compact Four Wheel Drive - Large Four Wheel Drive - Medium Commercial - Ute Commercial - Van Large, , Luxury Medium People Mover Small ,9.58 Light Sport ,83 3,759,837,48 BICYCLE AND MOTOR VEHICLE CRASH CHARACTERISTICS: TO 4 DATA 9

18 3.3 Road user movement characteristics Table 8 describes the collision types with respect to the general movement of the bicycle and vehicle involved in the initial event. Crashes of vehicles from adjacent directions at intersections predominate along with events involving manoeuvres of either vehicle such as u-turns and entering or leaving parking. For more detailed definitions for classifying accidents (DCAs) refer to Tables A.6 and A.7 in Appendix for Victoria and Tables A. in Appendix for Queensland. Table A3.6 in Appendix 3 has more detailed road user movements (RUMs) for Western Australia. South Australian crash data does not include DCAs or RUMs so is excluded from this grouped summary. However South Australian crash data does include information on accident type (Table A4.4 in Appendix 4) which provides some information on road user movements. Table 8: Grouped road user movements and definitions for classifying accidents by state N % Grouped Definition for classifying accidents Unknown 57.5 Pedestrian (on foot or in toy/pram) 9.8 Vehicles from adjacent directions (intersections only) 3, Vehicles from opposing directions, Vehicles from same direction,39.9 Manoeuvring 3, Overtaking On path Off path on straight 46.5 Off path on curve.9 Passenger and miscellaneous 38.33,48 Excludes South Australia MONASH UNIVERSITY ACCIDENT RESEARCH CENTRE

19 3.4 Location characteristics 3.4. Horizontal road alignment The crash occurred on the straight for 9.7% of crashes. Table 9 shows horizontal road alignment by state. Table 9: Horizontal road alignment by state Road horizontal alignment Unknown Straight Curve N % N % N % N % State Victoria.. 4, ,83 Queensland.. 3, ,759 Western Australia 76 6., ,837 South Australia 4.6, , , , Vertical road alignment Table : Vertical road alignment by state Road vertical alignment Unknown Level Grade Crest Dip N % N % N % N % N % N % State Queensland.., ,759 Western Australia 3.95, ,837 South Australia 5., , ,7 8.7, ,69 Excludes Victoria BICYCLE AND MOTOR VEHICLE CRASH CHARACTERISTICS: TO 4 DATA

20 3.4.3 Light conditions Table : Light conditions by state Light conditions Unknown Daylight Dawn/Dusk Darkness N % N % N % N % N % State Victoria , ,83 Queensland.3 3, ,759 Western Australia 4.48, ,837 South Australia.., , , ,5.8 3, Road surface Table : Road surface by state Road surface Unknown Sealed Unsealed N % N % N % N % State Queensland.9 3, ,759 Western Australia 75.64, ,837 South Australia.4, , , ,69 Excludes Victoria MONASH UNIVERSITY ACCIDENT RESEARCH CENTRE

21 3.4.5 Road condition Table 3: Road condition by state Road condition Unknown Wet Dry N % N % N % N % State Victoria , ,83 Queensland , ,759 Western Australia , ,837 South Australia ,3 93.8, , , Speed zone Table 4: Speed zone N % Speed zone Unknown Km/H and under, Km/H and over ,9 BICYCLE AND MOTOR VEHICLE CRASH CHARACTERISTICS: TO 4 DATA 3

22 4. BICYCLE RIDER CHARACTERISTICS 4. Bicycle rider demographics 4.. Sex Overall 8% of crashes involved male bicycle riders. Table 5 details the sex and state origin of the involved bicycle riders. Table 5: Bicycle rider sex by state Sex Unknown Female Male N % N % N % N % State Victoria 33.68,4.99 3, ,83 Queensland , ,759 Western Australia , ,837 South Australia ,8 8., ,58 8., ,9 4 MONASH UNIVERSITY ACCIDENT RESEARCH CENTRE

23 4.. Age The ages of bicycle riders involved in crashes are summarised in Table 6. Bicycle riders aged 6 to 9 years were involved in crashes the most followed by bicyclists aged to 9 years. Crash involvement for these age groups was 9.% and.% respectively. Table 6: Bicycle rider age grouping by state State Victoria Queensland Western Australia South Australia N % N % N % N % N % Age group Unknown , years years , years , years , years , years , years , years years ,83 3,759,837,473 3,9 BICYCLE AND MOTOR VEHICLE CRASH CHARACTERISTICS: TO 4 DATA 5

24 Table 7: Bicycle rider age grouping by sex Sex Unknown Female Male N % N % N % N % Age group Unknown , 7.3,53-5 years years , , years , ,655-5 years ,56 7.4, years , years , , years , , years years ,58 8., ,9 6 MONASH UNIVERSITY ACCIDENT RESEARCH CENTRE

25 4. Bicycle rider injury severity characteristics In general, crashes involving bicycle riders are seldom reported to the Police unless someone is killed or injured (usually the bicyclist) hence only injury crashes are considered here. Serious injury is defined as an injury requiring admission to hospital or death. The severity outcome to bicycle riders are summarised in Tables 8 to 5 by a number of demographic and crash characteristics. 4.. Injury severity by state The average risk of death or serious injury for bicycle riders involved in the reportable crashes used in this study is around 7%. The South Australian rate of 3 % is considerably less and requires further investigation. Table 8: Bicycle rider injury severity by state Injured Injury Severity Killed or seriously injured N % N % N % State Victoria 3, , ,79 Queensland, , ,653 Western Australia, ,944 South Australia, ,8 9, , ,47 BICYCLE AND MOTOR VEHICLE CRASH CHARACTERISTICS: TO 4 DATA 7

26 4.. Injury severity by year of crash Table 9 displays bicycle rider injury severity by year of crash. The rate of bicycle riders killed or seriously injured has remained relatively constant over the period to 4. Table 9: Bicycle rider injury severity by year of crash Injured Injury Severity Killed or seriously injured N % N % N % Year of crash, ,43, ,499, ,597 3, ,38 4, ,58 9, , , Injury severity by sex Table details injury severity by bicycle rider sex. Table : Bicycle rider injury severity by sex Injured Injury Severity Killed or seriously injured N % N % N % Sex Unknown Female, ,378 Male 7, ,76 7.5,9 9, , , Injury severity by age Injury severity remains relatively static for to 49 year old bicycle riders with the risk of serious injury for those aged under increasing inversely with age. Similarly the risk of serious injury increases with age for 5 year olds and above. 8 MONASH UNIVERSITY ACCIDENT RESEARCH CENTRE

27 Table : Bicycle rider injury severity by age grouping Injured Injury Severity Killed or seriously injured N % N % N % Age group Unknown years years, , years, ,563-5 years, , years , years, , 4-49 years, , years years , , ,47 Figure 5: Injury severity by age group 6 5 Injury severity % years 6-4 years 5-9 years -5 years 6-9 years 3-39 years 4-49 years 5-59 years 6+ years Age group BICYCLE AND MOTOR VEHICLE CRASH CHARACTERISTICS: TO 4 DATA 9

28 4..5 Injury severity by time of crash Table : Bicycle rider injury severity by time of crash Injured Injury Severity Killed or seriously injured N % N % N % Time Unknown Midnight to 6 am am to 8 am, ,66 8 am to am, ,8 am to midday ,3 Midday to pm ,3 pm to 4 pm, ,9 4 pm to 6 pm, ,45 6 pm to 8 pm ,93 8 pm to midnight , , ,47 Figure 6: Injury severity by time of day 4 35 Injury severity % Midnight to 6 am 6 am to 8 am 8 am to am am to midday Midday to pm pm to 4 pm 4 pm to 6 pm 6 pm to 8 pm 8 pm to midnight Time of day MONASH UNIVERSITY ACCIDENT RESEARCH CENTRE

29 4..6 Injury severity by collision partner market group Table 3 details injury severity outcome by impacting vehicle market group. This information is displayed graphically in Figure 7. Table 3: Bicycle rider injury severity by collision partner market group Injured Injury severity Killed or seriously injured N % N % N % Vehicle market group Unknown, , , Four Wheel Drive Compact (4WDC) Four Wheel Drive - Large (4WDL) Four Wheel Drive - Medium (4WDM) Commercial - Ute (CU) Commercial - Van (CV) Large (L), ,94 Luxury (LX) Medium (M) People Mover (PM) Small (S) ,93 Light (SL) Sport (SP) , , ,389 Figure 7: Bicycle rider serious injury by vehicle market group % 4 3 4WDC 4WDL4WDM CU CV L LX M PM SL L SP Vehicle market group Injured Killed or seriously injured BICYCLE AND MOTOR VEHICLE CRASH CHARACTERISTICS: TO 4 DATA

30 Previous research (Newstead et al, 4b) on unprotected road users found the average risk of death or serious injury for unprotected road users involved in reportable crashes is around 35%. The unprotected road users were pedestrians, bicyclists and motorcyclists with pedestrians being the primary unprotected road user because the majority of unprotected road users involved in police reported crashes are pedestrians. The measure of aggressivity towards unprotected road users in this study was the risk of serious injury given some injury was sustained. Given this, the aggressivity measure used for unprotected road users is in effect an estimate of the risk of death or serious injury to an unprotected road user given involvement in a reportable crash. Aggressivity injury severity on unprotected road users by impact vehicle market group found in this study is shown in Figure 8 together with 95%confidence intervals. Figure 8: Aggressivity injury severity on unprotected road users by impact vehicle market group (with 95% confidence limits) 43.% 4.% 39.% Injury Severity 37.% 35.% 33.% 3.% 9.% Four Wheel Drive Commercial Large Luxury Medium Passenger Vans Small Sports Impact Vehicle Market Group The injury outcome for an unprotected road user as a result of a collision with a 4WD vehicle was estimated to be significantly more severe than the outcome of a collision with a vehicle from either the large, medium or small market groups. Similarly the unprotected road user injury outcome is significantly more severe as a result of a collision with a commercial vehicle than a vehicle from either the large or medium vehicle market groups. The high aggressivity of 4WD vehicles towards unprotected road users has been identified in many studies now and is believed to be a result of the geometric properties of these vehicles. Such properties include high frontal structures combined with hard contact surfaces often featuring the presence of a bull bar (Attwell and Glase, ). Similar features can also be found on many commercial vehicles and passenger vans, also explaining the high aggressivity of these vehicle classes. It is unlikely that relative mass is a specific vehicle feature determining vehicle aggressivity in unprotected road user crashes given all vehicle classes are orders of magnitude heavier than the typical unprotected road user, of which pedestrians make up the majority. Comparing the aggressivity of small, medium and large cars reveals a trend to decreasing aggressivity with increasing vehicle size. This is possibly a result of longer bonnet structures on larger cars meaning the unprotected road user is more likely to impact the softer bonnet area on these vehicles than hit the harder windscreen and a-pillar area of the car. This is particularly relevant for the vulnerable head region of the unprotected road user and is generally supported in a review by McLean (996). MONASH UNIVERSITY ACCIDENT RESEARCH CENTRE

31 For drivers of light vehicles, the highest average risk of death or serious injury in a reported crash was around % in single vehicle crashes or about one third the risk of an unprotected road user. This compares with an average serious injury risk of only.3% for light vehicle drivers in crashes with other light vehicles, only one fifteenth the risk of an unprotected road user. Interpreting this in a total serious road trauma context shows the relative importance of reducing crashes involving unprotected road users compared to crashes involving light vehicle drivers. Table 3 and Figure 7 show similar outcomes to this previous research for bicycle riders although the magnitude of market group differences appears to be smaller Injury severity by speed zone Bicycle rider injury severity by speed zone is shown in Table 4 and displayed graphically in Figure 9. Table 4: Bicycle rider injury severity by speed zone Injured Injury Severity Killed or seriously injured N % N % N % Speed zone Unknown Km/H and under 8, , ,35 76 Km/H and over , , ,47 Figure 9: Bicycle rider injury severity by speed zone (%) Km/h and under 76 Km/h and over BICYCLE AND MOTOR VEHICLE CRASH CHARACTERISTICS: TO 4 DATA 3

32 4..8 Injury severity by group road user movement Table 5: Bicycle rider injury severity by grouped road user movements and definitions for classifying accidents Injured Injury Severity Killed or seriously injured N % N % N % Grouped road user movements and definition for classifying accidents Unknown, ,85 Pedestrian (on foot or in toy/pram) Vehicles from adjacent directions (intersections only), ,987 Vehicles from opposing directions ,89 Vehicles from same direction, ,7 Manoeuvring, ,846 Overtaking On path Off path on straight Off path on curve Passenger and miscellaneous , , ,47 4 MONASH UNIVERSITY ACCIDENT RESEARCH CENTRE

33 5. COLLIDING MOTORIST CHARACTERISTICS 5. Colliding motorist demographics 5.. Sex Table 6 details sex by state for motorists colliding with bicycle riders. Overall 54% of crashes involved male motorists and 36.5% of crashes involved female motorists. Table 6: Motorist sex by state Colliding unit sex Unknown Female Male N % N % N % N % State Victoria 533.3, , ,83 Queensland 39 8., , ,759 Western Australia ,75 4.4,49 5.,837 South Australia , ,473, , , ,9 BICYCLE AND MOTOR VEHICLE CRASH CHARACTERISTICS: TO 4 DATA 5

34 5.. Age Table 7 shows motorists aged 3 to 39 years were involved in crashes the most followed by motorists in age groupings 4 to 49 years and to 5 years. Crash involvement for these age groups was 8.%, 4.5% and 3.5% respectively. Table 7: Motorist age grouping by state State Victoria Queensland Western Australia South Australia N % N % N % N % N % Age group Unknown , years years years years , years , years, , years , years , years , ,83 3,759,837,473 3,9 6 MONASH UNIVERSITY ACCIDENT RESEARCH CENTRE

35 5. Colliding motorist injury characteristics 5.. Injury severity by state Table 9: Motorist injury severity by state Injury Severity Unknown Injured Killed or seriously injured N % N % N % N % State Victoria 4, ,83 Queensland 3, ,759 Western Australia, ,837 South Australia, ,473 3, ,9 5.. Motorists injury severity by bicyclist injury severity Tables 3 and 3 detail motorist injury outcome when involved in a collision with a bicycle rider. Table 3: Motorist injury by bicyclist injury severity (all motorists) Injured Bicyclist injury severity Killed Or seriously injured N % N % N % Motorist injury severity Not injured 9, , ,333 Injured Killed or seriously injured , , ,47 BICYCLE AND MOTOR VEHICLE CRASH CHARACTERISTICS: TO 4 DATA 7

36 Table 3: Motorist injury severity by bicyclist injury severity (injured motorists only) Injured Bicyclist injury severity Killed or seriously injured N % N % N % Motorist injury severity Injured Killed Or seriously injured DISCUSSION 6. Summary of characteristics of bicycle and motor vehicle collisions There were 3,9 crashes involving bicycle riders and motor vehicles in the period to 4. The crash data has been studied in a descriptive manner, focussing on investigation to identify those factors that may contribute to crash occurrence or injury severity. Further research is required to test whether the factors identified truly increase crash risk or are simply common characteristics of the bicycle rider, motorist, vehicles and locations involved and a reflection of exposure. This is an important step in developing countermeasures to address the problem. The crashes had the following characteristics: 6.. Type of crash Crashes of vehicles from adjacent directions at intersections predominate along with events involving manoeuvres of either vehicle such as u-turns and entering or leaving parking. The crash occurred on the straight for 9.7% of crashes and 98.6% of crashes occurred on sealed roads. 6.. Temporal characteristics Monday to Friday were the most common days for crashes to occur, with crashes being least frequent on Saturdays and Sundays. Crashes were more likely to occur in the time periods pm to 6pm and 6am to am than any other time of the day with crash frequencies highest from pm to 6pm. Crashes were more common in February and March with a decline apparent during the winter months Bicycle riders Overall 8% of crashes involved male bicycle riders. Bicycle riders aged 6 to 9 years were involved in crashes the most followed by bicyclists aged to 9 years. Crash involvement for these age groups was 9.% and.% respectively. 8 MONASH UNIVERSITY ACCIDENT RESEARCH CENTRE

37 6..4 Bicycle riders seriously injured In general, crashes involving bicycle riders are seldom reported to the Police unless someone is killed or injured (usually the bicyclist) hence only injury crashes are considered in this report. Serious injury is defined as an injury requiring admission to hospital or death. The rate of bicycle riders killed or seriously injured has remained relatively constant over the period to 4 and the average risk of death or serious injury for bicycle riders involved in the reportable crashes used in this study is around 7%. Injury severity remained relatively static for to 49 year old bicycle riders with the risk of serious injury for those aged under increasing inversely with age. Similarly the risk of serious injury increases with age for 5 year olds and above Motorists Overall 54% of crashes involved male motorists and 36.5% of crashes involved female motorists. Motorists aged 3 to 39 years were involved in crashes the most followed by motorists aged 4 to 49 years and to 5 years. Crash involvement for these age groups was 8.%, 4.5% and 3.5% respectively. 7. CONCLUSIONS Results of research reported here have been able to describe characteristics of bicycle crash circumstances, demographics and serious injury outcomes of both bicycle riders and motorists involved and has also been valuable in providing insight into understanding bicycle and motor vehicle collisions resulting in injury to the bicycle rider. Directions for further research have also been suggested. 8. ASSUMPTIONS AND QUALIFICATIONS The results and conclusions presented in this report are based on a number of assumptions and warrant a number of qualifications that the reader should note. These are as follows. 8. Assumptions It has been assumed that: Victorian, Western Australian, Queensland and South Australian Police crash reports accurately recorded driver and bicycle rider injury, hospitalisation and death and that there was no bias in reporting injury at any level. Crashed vehicle registration numbers were recorded accurately on Police crash reports and that they correctly identified the crashed vehicles in the Victorian, NSW, Western Australian and Queensland vehicle registers. Further, it was also assumed that vehicle identification numbers and make and model details were accurately recorded in the vehicle registers. Information contained in the Police crash records allowed accurate matching of both vehicles involved in crashes between motor vehicles, pedestrians and motorcyclists with bicycle riders for the purpose of describing crashes. BICYCLE AND MOTOR VEHICLE CRASH CHARACTERISTICS: TO 4 DATA 9

38 9. REFERENCES Attwell, R. and Glase, K. (). Bull bars and road trauma. Report Number CR, Australian Transport Safety Bureau, Canberra, Australia. Cameron, M.H., Newstead, S.V. & Le, C.M. (998) Rating the aggressivity of Australian passenger vehicles towards other vehicle occupants and unprotected road users, Proceedings, International IRCOBI Conference on the Biomechanics of Impact, Gothenborg, Sweden. McLean, A.J. (996) Pedestrian friendly vehicle front structures: A review of the literature. Report Number CR66, Australian Transport Safety Bureau, Canberra, Australia. Newstead, S., Cameron, M.H. Watson, L., & Delaney, A. (3) Vehicle Crashworthiness and Aggressivity Ratings and Crashworthiness by Year of Manufacture: Victoria and NSW Crashes During 987- Queensland and Western Australia Crashes During 99-, Report No. 96, Monash University Accident Research Centre, Melbourne, Australia. Newstead, S., Cameron, M., and Watson, L. (4a) Vehicle Crashworthiness Ratings and Crashworthiness by Year of Manufacture: Victoria and NSW Crashes During 987- Queenslan, Western Australian and New ZealandCrashes During 99-, Report No., Monash University Accident Research Centre, Melbourne, Australia. Newstead, S., Watson, L., Delaney, A. and. Cameron, M. (4b) Crashwothiness and aggressivity of the Australian light vehicle fleet by major crash type, Report No. 7, Monash University Accident Research Centre, Melbourne, Australia. Newstead, S., Cameron, M.H. and Watson, L. (5) Vehicle Safety Ratings Estimated from Police Reported Crash Data: 5 Update: Australian and New Zealand Crashes During 987-3, Report No. 4, Monash University Accident Research Centre, Melbourne, Australia. Newstead, S., Watson, L. and Cameron, M.H. (6) Vehicle Safety Ratings Estimated from Police Reported Crash Data: 6 Update: Australian and New Zealand Crashes During 987-4, Report No. 48, Monash University Accident Research Centre, Melbourne, Australia. SAS Inc. (989) SAS STAT Users Guide, Version 6, Fourth Edition, Volume. Carey, NC: SAS Institute. 3 MONASH UNIVERSITY ACCIDENT RESEARCH CENTRE

39 APPENDIX VICTORIAN BICYCLE AND MOTOR VEHICLE CRASH CHARACTERISTICS ADDITIONAL TABLES VICTORIAN CRASHES DURING -4

40

41 Temporal characteristics Table A.: Month of accident Month of accident Frequency Percent January February 489. March 55.4 April May June July August September October November December Table A.: Day of week Day of week Frequency Percent Sunday 493. Monday Tuesday Wednesday Thursday Friday Saturday Table A.3: Time of day Time of day Frequency Percent Unknown 5. Midnight to 6 am 7.47

42 Time of day Frequency Percent 6 am to 8 am am to am am to midday Midday to pm pm to 4 pm pm to 6 pm pm to 8 pm pm to midnight Bicycle rider behaviour Table A.4: Helmet use Helmet Use Frequency Percent Seatbelt worn. Crash helmet worn Crash helmet not worn Not appropriate 8.7 Unknown Table A.5: Lamp usage Lamp usage Frequency Percent Not applicable Yes No Unknown

43 Table A.6: Blood Alcohol Content Blood Alcohol Content Frequency Percent Not tested / none Accident nature and site features Table A.7: Accident type Accident type Frequency Percent Collisn with veh Struck pedestrian 6. Collision fixed obj.3 Collision other obj 8.7 Vehicle overturn 3.6 Fall from/in moving veh 4.8 No col & no obj hit

44 Table A.8: Road type Road Type Frequency Percent Unknown 8.58 Alley. Arcade. Avenue Boulevard 6.33 Circle. Circuit. Close 4.8 Court 4.85 Crescent 44.9 Drive.5 Esplanade. Freeway Freeway east 6. Freeway west.4 Gardens. Grove 4.9 Highway 585. Highway east 54. Highway west Lane 7.35 Parade Parade west. Place 4.5 Place east. Promenade.4 Rise. Road Road east 3.6

45 Road Type Frequency Percent Road north. Road south. Road west 6. Square south. Street Street east 4.8 Street ext. Street north 3.6 Street south. Street west.4 Strip. Terrace 3.6 Toll way.4 Way Table A.9: Road geometry Road geometry Frequency Percent Cross intersection T-intersection Y-intersection 34.7 Multiple intersection. Not at intersection Unknown. 483

46 Table A.: Road character Controlling for road character=straight Road character Road character (N / % / Row % / Column %) Driveway or crossover Divided road Median opening(not at interstn).. Driveway or crossover Controlling for Road character=curve Road character Road character (N / % / Row % / Column %). Driveway or crossover Divided road Median opening(not at interstn. Driveway or crossover

47 Table A.: Road surface conditions Road surface conditions Road surface conditions (N / % / Row % / Column %) Wet Dry Wet Muddy.. Unknown Table A.: Traffic controls Traffic controls Frequency Percent No control Stop-go lights 53.8 Flashing lights.4 Out of order 3.6 Pedestrian lights 4.5 Pedestrian crossing Railway crossing gates & booms 4.8 Roundabout Stop sign Give way sign School - no flags 4.8 Police. Other.46 Unknown 35.79

48 Traffic controls Frequency Percent 483 Table A.3: Number of vehicles involved Number of Vehicles Involved Frequency Percent Table A.4: Speed zone at accident site Speed zone at accident site Frequency Percent 4 km/hh km/hr km/hr km/hr km/hr km/hr 8.7 km/hr 3.73 km/hr 6. Other speed limit.4 Camping ground/off rd. Not known Table A.5: Hit run accident Hit run accident Frequency Percent No Yes 495.4

49 Hit run accident Frequency Percent 483 Table A.6: Definition for classifying accidents Definition for classifying accidents Frequency Percent Ped near side. Ped hit by vehicle from the right. Veh strikes ped on footpath,median,traffic island.4 Ped struck walking to/from or boarding/alighting vehicle. Cross traffic(intersections only) 59.6 Right far (intersections only) 5.9 Left far (intersections only) 3.65 Right near (intersections only) Two right turning (intersections only) 5.3 Right/left far (intersections only).5 Left near (intersections only) Left/right far (intersections only). Two left turning (intersections only). Other adjacent (intersections only).4 Head on (not overtaking) Right through Left through 8.7 Right/left. One veh turning right the other left 6.3 Right/right. Both vehs from opposite directions turning right 4.8 Other opposing manoeuvres not included in dcas Rear end(vehicles in same lane) Left rear 7.56 Right rear 3.67 Lane side swipe (vehicles in parallel lanes) 4 5. Lane change right (not overtaking).5 Lane change left (not overtaking) 3.36 Right turn sideswipe 68.4

50 Definition for classifying accidents Frequency Percent Left turn sideswipe Other same direction-manouevres not included in dcas U turn 6.5 Leaving parking 6.54 Entering parking 43.9 Reversing in stream of traffic 3.6 Reversing into fixed object/parked vehicle. Vehicle strikes another veh while emerging from driveway Vehicle off footpath strikes veh on carriageway Other manoeuvring not included in dcas Head on (overtaking). Pulling out (overtaking) 7.35 Cutting in (overtaking) 5. Pulling out -rear end 8.7 Other overtaking manoeuvres not included in dcas Vehicle collides with vehicle parked on left of road 7.35 Vehicle strikes door of parked/stationary vehicle Temporary roadworks. Struck object on carriageway. Other on path. Off carriageway to left.44 Left off carriageway into object/parked vehicle 8.7 Off carriageway to right.4 Right off carriageway into object/parked vehicle.4 Out of control on carriageway (on straight) 6. Off end of road/t-intersection. Other accidents-off straight not included in dcas Off right bend into object/parked vehicle. Off left bend into object/parked vehicle.4

51 Definition for classifying accidents Frequency Percent Out of control on carriageway (on bend).4 Fell in/from vehicle. Load or missile struck vehicle 3.6 Unknown - no details on manoeuvres of road users in accident 5. Table A.7: Definition by classifying accidents by bicycle DCA reference For DCA descriptions refer to Vic Roads DCA chart at appendix end Definition for classifying accidents (DCA) Vehicle Ped near side. Ped hit by vehicle from the right..5 Veh strikes ped on footpath, median, traffic island. 5 Ped struck walking to/from or boarding/alighting vehicle.5..5 Cross traffic (intersections only) Right far (intersections only) Left far (intersections only) Right near (intersections only) Two right turning (intersections only) Right/left far (intersections only) Left near (intersections only) Left/right far (intersections only) Bicycle DCA reference (N / % / Row % / Column %) Not known which vehicle was number Vehicle Not involved in initial event

52 Definition for classifying accidents (DCA) Vehicle Two left turning (intersections only)..5 Other adjacent (intersections only) Head on (not overtaking) Right through Left through Right/left. One veh turning right the other left Right/right. Both vehs from opposite directions turning right Other opposing manoeuvres not included in DCAs Rear end (vehicles in same lane) Left rear Right rear Lane side swipe (vehicles in parallel lanes) Lane change right (not overtaking) Lane change left (not overtaking) Right turn sideswipe Left turn sideswipe Bicycle DCA reference (N / % / Row % / Column %) Not known which vehicle was number Vehicle Not involved in initial event

53 Definition for classifying accidents (DCA) Other same direction-manouevres not included in DCA3-37 Vehicle U turn Leaving parking Entering parking Reversing in stream of traffic Reversing into fixed object/parked vehicle Vehicle strikes another veh while emerging from driveway Vehicle off footpath strikes veh on carriageway Other manoeuvring not included in DCAs Head on (overtaking) Pulling out (overtaking) Cutting in (overtaking)..5 Pulling out -rear end..5.5 Other overtaking manoeuvres not included in DCAs Vehicle collides with vehicle parked on left of road Vehicle strikes door of parked/stationary vehicle Bicycle DCA reference (N / % / Row % / Column %) Not known which vehicle was number Vehicle Not involved in initial event

54 Definition for classifying accidents (DCA) Vehicle Temporary road works..5 Struck object on carriageway..5 Other on path..5 Off carriageway to left Left off carriageway into object/parked vehicle Off carriageway to right.4. Right off carriageway into object/parked vehicle.4. Out of control on carriageway (on straight) Off end of road/t-intersection Other accidents-off straight not included in DCAs Off right bend into object/parked vehicle Off left bend into object/parked vehicle.4. Out of control on carriageway (on bend).4. Fell in/from vehicle..5 Load or missile struck vehicle Unknown - no details on manoeuvres of road users in accident.4 4. Bicycle DCA reference (N / % / Row % / Column %) Not known which vehicle was number Vehicle. 5.4 Not involved in initial event

55 Definition for classifying accidents (DCA) Vehicle Weather and light conditions Table A.8: Light conditions Bicycle DCA reference (N / % / Row % / Column %) Not known which vehicle was number Vehicle Not involved in initial event Light conditions Frequency Percent Day Dusk/dawn Dark st lights on 5.35 Dark st lights off 9.9 Dark no st lights 4.87 Dark st lights unk 3.48 Unknown Table A.9: Weather conditions Weather condition Clear Raining Snowing.. Fog.. Smoke.. Dust.4.4 Strong 6 winds. 6. Weather condition (N / % / Row % / Column %) Clear Raining Fog Dust Strong winds Unknown

56 Unknown

57 Bicycle rider injury severity Table A.: Bicycle rider injury severity by DCA Definition for classifying accidents (DCA) Ped near side. Ped hit by vehicle from the right..3 Veh strikes ped on footpath,median,traffic island. 5.3 Ped struck walking to/from or boarding/alighting vehicle Bicycle rider injury severity (N / % / Row % / Column %) Killed or seriously Injured injured Cross traffic(intersections only) Right far (intersections only) Left far (intersections only) Right near (intersections only) Two right turning (intersections only) Right/left far (intersections only) Left near (intersections only) Left/right far (intersections only)..3 Two left turning (intersections only)..3 Other adjacent (intersections only) Head on (not overtaking)

58 Definition for classifying accidents (DCA) Right through Left through Right/left. One veh turning right the other left Right/right. Both vehs from opposite directions turning right Other opposing manoeuvres not included in DCAs - 5 Bicycle rider injury severity (N / % / Row % / Column %) Killed or seriously Injured injured Rear end(vehicles in same lane) Left rear Right rear Lane side swipe (vehicles in parallel lanes) Lane change right (not overtaking) Lane change left (not overtaking) Right turn sideswipe Left turn sideswipe Other same direction-manoeuvres not included in DCAs U turn Leaving parking

59 Definition for classifying accidents (DCA) Entering parking Reversing in stream of traffic Reversing into fixed object/parked vehicle..3 Vehicle strikes another veh while emerging from driveway Bicycle rider injury severity (N / % / Row % / Column %) Killed or seriously Injured injured Vehicle off footpath strikes veh on carriageway Other manoeuvring not included in DCAs Head on (overtaking) Pulling out (overtaking) Cutting in (overtaking) Pulling out -rear end Other overtaking manoeuvres not included in DCAs Vehicle collides with vehicle parked on left of road Vehicle strikes door of parked/stationary vehicle Temporary road works..3 Struck object on carriageway..3 Other on path

60 Definition for classifying accidents (DCA) Off carriageway to left Left off carriageway into object/parked vehicle Off carriageway to right. 5.3 Right off carriageway into object/parked vehicle.4.6 Out of control on carriageway (on straight) Off end of road/t-intersection Other accidents-off straight not included in DCAs 7-75 Bicycle rider injury severity (N / % / Row % / Column %) Killed or seriously Injured injured Off right bend into object/parked vehicle Off left bend into object/parked vehicle. 5.3 Out of control on carriageway (on bend) Fell in/from vehicle..3 Load or missile struck vehicle Unknown - no details on manoeuvres of road users in accident

61

62

63 APPENDIX QUEENSLAND BICYCLE AND MOTOR VEHICLE CRASH CHARACTERISTICS ADDITIONAL TABLES QUEENSLAND CRASHES DURING -4

64

65 Temporal characteristics Table A.: Day of week Day of week Frequency Percent Sunday Monday Tuesday Wednesday Thursday Friday Saturday 4.93 Helmet use Table A.: Helmet use Helmet use Frequency Percent Unknown Worn Not worn Not applicable.3 Accident nature and site features Table A.3: Accident type Accident type Frequency Percent Hit parked vehicle Angle Rear-end Head-on Sideswipe Hit fixed obstruct/temp object 3.8 Fall from moving vehicle 3.35 Motor/pedal cycle overturn/fall/drop 7.45 Hit pedestrian 5.3 Hit animal 3.8

66 Accident type Frequency Percent Struck by external load 3.8 Collision crash.3 Non-collision crash.3 Other.9 Table A.4: Number of units involved Number of units involved Frequency Percent Table A.5: Divided Road Divided road Frequency Percent N Y Table A.6: On/off carriageway On/off carriageway Frequency Percent Other/unknown On carriageway Off carriageway Table A.7: Road feature Road feature Frequency Percent Other 7.45 Cross intersection T-junction Y-junction 8. Multiple road 6.6 Interchange 3.85 Roundabout 3 8.3

67 Road feature Frequency Percent Bridge/causeway 3.35 Median opening 5.4 Merge lane 6.6 Not applicable Table A.8: Traffic controls Traffic controls Frequency Percent Police.5 Road/rail workers.5 Operating traffic lights Stop sign Give way Pedestrian crossing School crossing-flags only.3 Miscellaneous 9.4 No traffic control Table A.9: Speed zone at accident site Speed zone at accident site Frequency Percent km/hr.7 5 km/hr 3.8 km/hr km/hr km/hh 3. 5 km/hr km/hr km/hr km/hr km/hr.5 km/hr 7.86 km/hr.5

68 Table A.: Definition for classifying accidents Definition for classifying accidents (DCA) Frequency Percent Unknown - no details on manoeuvres of road users in accident 57.5 Ped on footpath struck by veh entering/leaving driveway.3 Any manoeuvre involving ped not included in DCAs -8.5 Cross traffic(intersections only) Right far (intersections only) 4.6 Left far (intersections only) 83. Right near (intersections only) Two right turning (intersections only) 4.64 Right/left far (intersections only) 8.74 Left near (intersections only) Other adjacent (intersections only) Head on (not overtaking) 76. Right through Left through.9 Right/left. One veh turning right the other left.9 Right/right. Both vehs from opposite directions turning right 3.8 Other opposing manoeuvres not included in DCAs Rear end(vehicles in same lane) Left rear Right rear 5.4 Lane side swipe (vehicles in parallel lanes) Lane change right (not overtaking) Lane change left (not overtaking) Right turn sideswipe Left turn sideswipe Other same direction-manouevres not included in DCAs U turn.7 Leaving parking 6.43 Entering parking 3.35

69 Definition for classifying accidents (DCA) Frequency Percent Parked vehicles only.3 Reversing in stream of traffic 3.8 Vehicle strikes another veh while emerging from driveway Vehicle off footpath strikes veh on carriageway Other manoeuvring not included in DCAs Head on (overtaking) 4. Pulling out (overtaking).3 Cutting in (overtaking) 3.8 Other overtaking manoeuvres not included in DCAs Vehicle collides with vehicle parked on left of road Vehicle strikes door of parked/stationary vehicle Struck object on carriageway.5 Left off carriageway into object/parked vehicle 4.6 Right off carriageway into object/parked vehicle 3.8 Other accidents-off straight not included in DCAs Off right bend into object/parked vehicle.5 Load or missile struck vehicle 3.8 Other accidents not classifiable elsewhere 9.4 Light conditions Table A.: Light conditions Light conditions Frequency Percent Daylight Dawn/dusk Darkness lighted Darkness unlighted 8.3 Unknown.3

70 Road Conditions Table A.: Vertical alignment Vertical alignment of road Frequency Percent Level Grade Crest Dip Table A.3: Horizontal alignment Horizontal alignment of road Frequency Percent Straight Curve-view obstructed Curve-view open Table A.4: Road surface conditions Road surface conditions Frequency Percent Sealed-Dry Sealed-Wet 3 6. Unsealed-Dry 6.6 Unknown.9 Bicycle rider injury severity Table A.5: Injury severity by definition for classifying accidents Definition for classifying accidents (DCA) Unknown - no details on manoeuvres of road users in accident Any manoeuvre involving ped not included in DCAs -8 Injury severity (N / % / Row % / Column %) Injured Cross traffic(intersections only) Right far (intersections only) Killed or seriously injured

71 Definition for classifying accidents (DCA) Injury severity (N / % / Row % / Column %) Injured Left far (intersections only) Right near (intersections only) Two right turning (intersections only) Right/left far (intersections only) Left near (intersections only) Other adjacent (intersections only) Head on (not overtaking) Right through Left through Right/left. One veh turning right the other left Right/right. Both vehs from opposite directions turning right Other opposing manoeuvres not included in DCAs Rear end(vehicles in same lane) Left rear Right rear Lane side swipe (vehicles in parallel lanes) Killed or seriously injured

72 Definition for classifying accidents (DCA) Injury severity (N / % / Row % / Column %) Injured Lane change right (not overtaking) Lane change left (not overtaking) Right turn sideswipe Left turn sideswipe Other same direction-manouevres not included in DCAs U turn Leaving parking Entering parking Parked vehicles only.3.4 Reversing in stream of traffic Vehicle strikes another veh while emerging from driveway Vehicle off footpath strikes veh on carriageway Other manoeuvring not included in DCAs Head on (overtaking) Pulling out (overtaking) Cutting in (overtaking) Killed or seriously injured

73 Definition for classifying accidents (DCA) Other overtaking manoeuvres not included in DCAs 5-54 Vehicle collides with vehicle parked on left of road Injury severity (N / % / Row % / Column %) Injured Vehicle strikes door of parked/stationary vehicle Struck object on carriageway.5.8 Left off carriageway into object/parked vehicle Right off carriageway into object/parked vehicle Other accidents-off straight not included in DCAs Off right bend into object/parked vehicle Load or missile struck vehicle Other accidents not classifiable elsewhere Killed or seriously injured

74

75 APPENDIX 3 WESTERN AUSTRALIAN BICYCLE AND MOTOR VEHICLE CRASH CHARACTERISTICS ADDITIONAL TABLES WESTERN AUSTRALIAN CRASHES DURING -4

76

77 Temporal characteristics Table A3.: Day of week Day of week Frequency Percent Sunday Monday Tuesday Wednesday Thursday Friday Saturday Helmet use TableA3.: Helmet use Helmet use Frequency Percent Worn Not Worn.7 Accident nature and site features Table A3.3: Number of units involved Number of units involved Frequency Percent Table A3.4: Accident type Accident type Frequency Percent Mid block Intersection Cycle path.4 Roads open to public access.74 Location not known 5.8

78 Table A3.5: MR nature code MR Nature Code Frequency Percent Unknown Rear end Head on 3.9 Sideswipe same dirn Right angle Right turn thru Hit pedestrian.4 Hit obj.78 Non collision Table A3.6: MR type code MR Type Code Frequency Percent Unknown Involving overtaking Involving parking 3.88 Involving animal.4 Involving pedestrian 5.8 Entering / leaving driveway 69.7 Table A3.7: No collision code No collision code Frequency Percent Not applicable Overturns Falls from moving veh 3. Other non-collision 5.8

79 Table A3.8: First object hit First Object Hit Frequency Percent Not applicable Sec pole.4 Other pole.4 Tree.7 Kerb when stated as cause.7 Veh parked off cway 4.4 Table A3.9: Second object hit Second Object Hit Frequency Percent Unknown Kerb when stated as cause.4 Table A3.: Carriageway Carriageway Frequency Percent 3.9 L R S Table A3.: Road works site Road Works Site Frequency Percent No Yes 8.8

80 Table A3.: Road features Road feature Frequency Percent Unknown way intx way intx (t-junction) Intx > 4 legs.7 Roundabout Median opening.78 Rail xing 4.4 Bridge 7.5 Driveway Mid block latm device (slow pt sp hump etc.) 4.4 Pedestrian refuge island.39 Table A3.3: Traffic controls Traffic controls Frequency Percent Unknown 6.9 Intersection traffic lights Stop sign Give way sign Zebra crossing.39 Rail xing - boomgates 3. Rail xing - flashing lights only.4 School crossing.35 No sign or control Pointsman.4 Traffic lights & give way sign.4 Mid block traffic lights 3.

81 Table A3.4: Traffic control functioning Traffic Control Functioning Frequency Percent Yes Table A3.5: Speed zone at accident site Speed zone at accident site Frequency Percent Not known km/hr.7 5 km/hr.4 3 km/hr.4 4 km/hh km/hr km/hr km/hr km/hr km/hr.4 km/hr 9.3 km/hr 8.8 Table A3.6: Road user movement Road user movement Frequency Percent Intx: other Intx: thru - thru Intx: right - thru Intx: left - thru Intx: thru - right Intx: right - right 6.56 Intx: left - right 8.8 Intx: thru - left 3.95 Opposite dirn: other 3. Opposite dirn: head on 3.9

82 Road user movement Frequency Percent Opposite dirn: thru - right Opposite dirn: right - left 6. Opposite dirn: thru - left 4.49 Opposite dirn: u - turn.7 Same dirn: other 8.8 Same dirn: same lane rear end Same dirn: same lane left rear 5.88 Same dirn: same lane right rear.74 Same dirn: same lane u - turn 6. Same dirn: parallel lanes - s/swipe Same dirn: change lanes - right 3.6 Same dirn: change lanes - left 9.67 Same dirn: parallel lanes - turn right s/swipe 4.48 Same dirn: parallel lanes - turn left s/swipe 3.5 Manoeuv: other Manoeuv: leaving parking 7.5 Manoeuv: parking 3. Manoeuv: parking veh only.4 Manoeuv: reversing in traffic 8.8 Manoeuv: leaving driveway Manoeuv: from footway 3. Overtaking: other.7 Overtaking: pulling out.4 Overtaking: cutting in.4 Overtaking: into right turn 8.63 On path: other 6. On path: parked 9. On path: accident or breakdown 4.4 On path: open car door 7.47

83 Road user movement Frequency Percent Off path on straight: off left cway 3. Off path on straight: off left cway obj 3.46 Off path on straight: off right cway obj 6. Off path on straight: lost control on cway 35.3 Loss of control: left turn - intx.4 Off path on curve: off right bend in obj.7 Misc: passenger fell in / from veh 5.8 Misc: load struck veh.4 Misc: parked car ran away.7 Misc: veh movement unknown 7.5 Pedest: other.4 Weather and light conditions Table A3.7: Atmospheric conditions Atmospheric Condition Frequency Percent Unknown Clear Raining Fog / smoke / dust 5.8 Overcast 7.8 Fog / mist.7 Table A3.8: Light conditions Light conditions Frequency Percent unknown 4.48 Daylight Dawn or dusk Dark - street lights on Dark - street lights off.39 Dark - street lights not provided 8.63

84 Road conditions Table A3.9: Road condition Road Condition Frequency Percent Unknown 7.5 Wet Dry Table A3.: Road alignment Road alignment Frequency Percent Unknown Curve Straight Table A3.: Road gradient Road gradient Frequency Percent Unknown 3.95 Level Crest of hill 7.47 Slope Table A3.: Road surface conditions Road surface conditions Frequency Percent Unknown Sealed Unsealed.74

85 Bicycle rider injury severity Table A3.3: Serious injury by road user movement Road user movement (RUM) Intx: other Intx: thru - thru Intx: right - thru Intx: left - thru Intx: thru - right Intx: right - right Intx: left - right Intx: thru - left Opposite dirn: other.5.7 Opposite dirn: head on Opposite dirn: thru - right Opposite dirn: right - left 3.5. Opposite dirn: thru - left Opposite dirn: u - turn.5.7 Same dirn: other 4..7 Injury severity (N / % / Row % / Column %) Killed or seriously Injured injured

86 Road user movement (RUM) Same dirn: same lane rear end Same dirn: same lane left rear Same dirn: same lane right rear Same dirn: same lane u - turn Same dirn: parallel lanes - s/swipe Same dirn: change lanes - right Same dirn: change lanes - left Same dirn: parallel lanes - turn right s/swipe Injury severity (N / % / Row % / Column %) Killed or seriously Injured injured Same dirn: parallel lanes - turn left s/swipe Manoeuv: other Manoeuv: leaving parking Manoeuv: parking 3.5. Manoeuv: reversing in traffic Manoeuv: leaving driveway Manoeuv: from footway Overtaking: other

87 Road user movement (RUM) Overtaking: pulling out.5.7 Overtaking: cutting in.5.7 Overtaking: into right turn On path: other On path: parked On path: accident or breakdown On path: open car door Off path on straight: off left cway.5.7 Off path on straight: off left cway obj Off path on straight: off right cway obj Off path on straight: lost control on cway Off path on curve: off right bend in obj Misc: passenger fell in / from veh Misc: load struck veh.5.7 Misc: parked car ran away.5.7 Misc: veh movement unknown. 5.4 Injury severity (N / % / Row % / Column %) Killed or seriously Injured injured

88 Road user movement (RUM) Injury severity (N / % / Row % / Column %) Killed or seriously Injured injured

89 APPENDIX 4 SOUTH AUSTRALIAN BICYCLE AND MOTOR VEHICLE CRASH CHARACTERISTICS ADDITIONAL TABLES SOUTH AUSTRALIAN CRASHES DURING -4

90

91 Temporal Characteristics Table A4.: Month of crash Month of crash Frequency Percent January February March 3.6 April 8.98 May June July August September October November December Table A4.: Time of crash Time of crash Frequency Percent Midnight to 6 am am to 8 am am to am am to midday Midday to pm pm to 4 pm pm to 6 pm pm to 8 pm pm to midnight 3 4.6

92 Helmet use Table A4.3: Helmet use Helmet use Frequency Percent Worn Not worn Unknown Accident nature and site features Table A4.4: Accident type Accident type Frequency Percent Rear end Hit fixed object.8 Side swipe Right angle Head on Roll over 3. Right turn 99.9 Hit parked vehicle Hit object on road.4 Left road - out of control.4 Other Table A4.5: Traffic controls Traffic controls Frequency Percent Traffic signals Rail xing - boom.4 Rail xing - flashing.8 Stop sign 4.45 Give way sign 4.4 No control Roundabout Other 4.6

93 Table A4.6: Other road features Other road features Frequency Percent Bridge, culvert, causeway 6.4 Road works 7.8 Driveway or entrance Road hump or slow point 8.73 Median opening (not at i/s) 9.36 Not applicable Unknown 3. Table A4.7: Road geometry Road geometry Frequency Percent Interchange.8 Cross road Y-Junction 7.8 T-Junction Multiple Rail xing.4 Rail crossing.8 Divided road 53.5 Not divided One way.8 Freeway.8 Pedestrian crossing 4.6 Other 55.

94 Table A4.8: Speed zone at accident site Speed zone at accident site Frequency Percent 5 km/hr.4 6 km/hr.4 km/hr km/hr.8 km/hr 3. 5 km/hr km/hh km/hr km/hr km/hr km/hr km/hr.49 km/hr 6.5 km/hr 9.36 Not known 4.6 Road conditions Table A4.9: Road seal Road seal Frequency Percent Sealed Unsealed.4 Unknown.4 Table A4.: Road moisture condition Road Moisture condition Frequency Percent Wet Dry

95 Table A4.: Vertical alignment Vertical road alignment Frequency Percent Level Crest of hill.8 Bottom of hill Slope Unknown 5. Table A4.: Horizontal road alignment Horizontal road alignment Frequency Percent Straight road Curved, view obscured 4.6 Curved, view open Unknown 4.6 Weather and light conditions Table A4.3: Weather Weather Frequency Percent Raining Not raining Table A4.4: Light condition Light condition Frequency Percent Daylight 85. Dawn/Dusk Night 76.6 Apparent error Table A4.5: Responsible entity Responsible entity Frequency Percent Driver rider Passenger 9.77 Other 3.

96 Table A4.6: Apparent error Apparent error Frequency Percent Excessive speed.4 Fail to stand.8 Fail to keep left Change lanes to endanger 37.5 Fail to give way right.4 Incorrect turn 4.57 Follow too closely.89 Overtake without due care 7.69 Disobey - traffic lights 4.7 Disobey - stop sign 8.3 Disobey - give way sign 9.77 Incorrect or no signal.4 Inattention No errors Other 4.6 D.U.I. 5.6 Vehicle fault 3. Died sick or asleep at wheel.4 Brake failure.4 Fail to give way 78.4 Table A4.7: Subsidiary error Subsidiary error Frequency Percent None identified Disobey - traffic lights.4 Inattention.8 D.U.I..8

97 APPENDIX 5 BICYCLE AND PEDESTRIAN CRASH CHARACTERISTICS CRASHES DURING -4

98

99 Colliding pedestrian characteristics Pedestrian demographics Sex Table A5.: Pedestrian sex by state Pedestrian sex Unknown Female Male N % N % N % N % State Victoria Queensland Western Australia South Australia Table A5.: Pedestrian age grouping by state Victoria State Queensland Western Australia South Australia N % N % N % N % N % Age group Unknown years years years years years years years years years

100 Pedestrian and bicycle rider injury severity Table A5.3: Bicyclist injury severity colliding with pedestrians by state Injured Bicyclist injury severity Killed or seriously injured N % N % N % State Victoria Queensland Western Australia South Australia Table A5.4: Pedestrian injury severity by bicyclist injury severity Injured Bicyclist injury severity Killed or seriously injured N % N % N % Pedestrian injury severity Injured Killed or seriously injured

101 APPENDIX 6 BICYCLE AND MOTORCYCLE CRASH CHARACTERISTICS CRASHES DURING -4

102

103 Colliding motorcycle rider characteristics Motorcycle rider demographics Sex Table A6.: Motorcycle rider sex by state Motorcyclist sex Unknown Female Male N % N % N % N % State Victoria Queensland Western Australia South Australia Age Table A6.: Motorcyclist age grouping by state State Victoria Queensland Western Australia South Australia N % N % N % N % N % Age group Unknown years years years years years years years years

104 Road user movement Table A6.3: Grouped road user movements and definitions for classifying accidents by state N % Grouped Definition for classifying accidents Unknown. Vehicles from adjacent directions (intersections only) Vehicles from opposing directions Vehicles from same direction. Manoeuvring Overtaking On path. Off path on straight Participant injury severity Table A6.4: Bicyclist injury severity colliding with motorcyclists by state Injured Bicyclist injury severity Killed or seriously injured N % N % N % State Victoria Queensland Western Australia South Australia

105 Table A6.5: Motorcyclist injury severity by bicyclist injury severity Injured Bicyclist injury severity Killed or seriously injured N % N % N % Motorcyclist injury severity Injured Killed or seriously injured Table A6.6: Bicyclist Injury severity by grouped road user movements and definitions for classifying accidents Injured Injury Severity Killed or seriously injured N % N % N % Grouped road user movements and definition for classifying accidents Vehicles from adjacent directions (intersections only) Vehicles from opposing directions Vehicles from same direction Manoeuvring Overtaking On path.. Off path on straight