BICYCLE AND MOTOR VEHICLE CRASH CHARACTERISTICS

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

Project Sponsored By ii MONASH UNIVERSITY ACCIDENT RESEARCH CENTRE

MONASH UNIVERSITY ACCIDENT RESEARCH CENTRE REPORT DOCUMENTATION PAGE Report No. Report Date ISBN Pages 5 September 6 736 3 9 3 + 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: +6 3 995 437, Fax: +6 3 995 4363 BICYCLE AND MOTOR VEHICLE CRASH CHARACTERISTICS: TO 4 DATA iii

iv MONASH UNIVERSITY ACCIDENT RESEARCH CENTRE

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

CONTENTS Page No.. INTRODUCTION.... BACKGROUND.... PROJECT MOTIVATION AND AIMS.... CRASH DATA.... COLLISIONS INVOLVING BICYCLES.... COLLISIONS INVOLVING BICYCLES AND MOTOR VEHICLES...4 3. BICYCLE CRASH CHARACTERISTICS...4 3. TEMPORAL CHARACTERISTICS...4 3.. Week day of crash...4 3.. Time of crash...6 3..3 Month of crash...7 3. MOTOR VEHICLE CHARACTERISTICS...8 3.. Motor vehicle market group categories...8 3.3 ROAD USER MOVEMENT CHARACTERISTICS... 3.4 LOCATION CHARACTERISTICS... 3.4. Horizontal road alignment... 3.4. Vertical road alignment... 3.4.3 Light conditions... 3.4.4 Road surface... 3.4.5 Road condition...3 3.4.6 Speed zone...3 4. BICYCLE RIDER CHARACTERISTICS...4 4. BICYCLE RIDER DEMOGRAPHICS...4 4.. Sex...4 4.. Age...5 4. BICYCLE RIDER INJURY SEVERITY CHARACTERISTICS...7 4.. Injury severity by state...7 4.. Injury severity by year of crash...8 4..3 Injury severity by sex...8 4..4 Injury severity by age...8 4..5 Injury severity by time of crash... 4..6 Injury severity by collision partner market group... 4..7 Injury severity by speed zone...3 4..8 Injury severity by group road user movement...4 5. COLLIDING MOTORIST CHARACTERISTICS...5 5. COLLIDING MOTORIST DEMOGRAPHICS...5 5.. Sex...5 5.. Age...6 5. COLLIDING MOTORIST INJURY CHARACTERISTICS...7 5.. Injury severity by state...7 5.. Motorists injury severity by bicyclist injury severity...7 6. DISCUSSION...8 6. SUMMARY OF CHARACTERISTICS OF BICYCLE AND MOTOR VEHICLE COLLISIONS...8 6.. Type of crash...8 BICYCLE AND MOTOR VEHICLE CRASH CHARACTERISTICS: TO 4 DATA vii

6.. Temporal characteristics...8 6..3 Bicycle riders...8 6..4 Bicycle riders seriously injured...9 6..5 Motorists...9 7. CONCLUSIONS...9 8. ASSUMPTIONS AND QUALIFICATIONS...9 8. ASSUMPTIONS...9 9. 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

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

. 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 845 9.5 984.3 96.53 8 8.7 876 9.85 4,43 Western Australia 579 8.87 635.7 68 9.8 594 9.36 65.5 3,68 South Australia 575.97 59.5 597.77 53 8.7 467 7.3,74 3,4 9.39 3,.47 3,66.8,957 8.85 3,.47 5,685 MONASH UNIVERSITY ACCIDENT RESEARCH CENTRE

Figure : Number of bicyclists involved in crashes by state and year of crash Number of bicyclists 35 3 5 5 5 3 4 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 93.78 35.67 4,83 9.73 5 4.8 5, Queensland 54.9 5.9 3,759 89.8 3 7.69 4,85 Western Australia 35. 4.48,837 98.7.3,887 South Australia 93 3.45 5.56,473 9.69 6 4.3,697 75.84 4.76 3,9 9.8 69 4.6 4,98 BICYCLE AND MOTOR VEHICLE CRASH CHARACTERISTICS: TO 4 DATA 3

. 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 93 9.9 878 8.7,6.3 96 9.6,8.35 4,83 Queensland 73 9.47 846.5 759.9 68 8.4 74 9.69 3,759 Western Australia 54 8.47 58.48 575.7 556 9.6 6.8,837 South Australia 58.54 54.9 555.44 457 8.48 4 6.6,473,696 9.39,847.48,95.9,6 8.85,83.37 3,9 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 3. 3.. 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

Table 4: Week day of crash N % Day of Week Unknown*,473 7.79 Sunday 986 7.9 Monday,668. Tuesday,99 3.73 Wednesday,933 3.9 Thursday,959 4.9 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

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 474 3.4 6 am to 8 am,88 3.8 8 am to am,9 4.5 am to midday,64 9.9 Midday to pm,7 9.4 pm to 4 pm,55 8.35 4 pm to 6 pm,773 9.95 6 pm to 8 pm, 8.65 8 pm to midnight 5 3.6 3,9 Figure 3: Percentage of bicycle crashes by time of day 8 6 4 8 6 4 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

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 * 6,596 47.45 January 579 4.7 February 78 5.7 March 864 6. April 64 4.35 May 693 4.99 June 473 3.4 July 488 3.5 August 55 3.96 September 56 3.7 October 58 4.9 November 68 4.5 December 6 4.39 3,9 * Queensland and Western Australia unknown Figure 4: Percentage of bicycle crashes by month of year 7 6 % crashes 5 4 3 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Month BICYCLE AND MOTOR VEHICLE CRASH CHARACTERISTICS: TO 4 DATA 7

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 www.fcai.com.au 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

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,8 43.63,438 38.5,7 39. 4,653 4.7 Four Wheel Drive - Compact 73.5 4. 4.48 57.37 Four Wheel Drive - Large 84.74 5.33 9 3. 5.97 Four Wheel Drive - Medium 7.45 8.48 39.37 7. Commercial - Ute 6 3.3 44 6.49 8 4.6 5 4.57 Commercial - Van 65.35 6.6 3.9 56.37 Large,56.85 878 3.36 55 9.4,485.74 Luxury 4.39 3.9 9 3.7 4 3.69 Medium 7 4.8 73 4.6 33 4.69 53 4.49 People Mover 47.97 48.8 8.99 3.8 Small 469 9.7 4.64 34.98,9.58 Light 8 4.3 48 6.6 37 8.35 693 6.6 Sport 73.5 4.6 3.6 43.5 4,83 3,759,837,48 BICYCLE AND MOTOR VEHICLE CRASH CHARACTERISTICS: TO 4 DATA 9

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) 3,3 8.89 Vehicles from opposing directions,367.96 Vehicles from same direction,39.9 Manoeuvring 3,95 7.96 Overtaking 95.83 On path 79 6.9 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

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.. 4,768 98.68 64.3 4,83 Queensland.. 3,354 89.3 45.77 3,759 Western Australia 76 6.,76 8.3 385 3.57,837 South Australia 4.6,345 94.8 4 5.,473 8.9,743 9.67 978 7.4 3,9 3.4. 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..,99 79.6 68 6.7 63.68 96.55 3,759 Western Australia 3.95,67 7.86 588.73 7.47..,837 South Australia 5., 89.45 98 8..8 38.54,473 7.9 7,7 8.7,394 5.37 53.69 34.48 9,69 Excludes Victoria BICYCLE AND MOTOR VEHICLE CRASH CHARACTERISTICS: TO 4 DATA

3.4.3 Light conditions Table : Light conditions by state Light conditions Unknown Daylight Dawn/Dusk Darkness N % N % N % N % N % State Victoria 3.48 3,748 77.57 487.8 574.88 4,83 Queensland.3 3, 83. 8 6.7 399.6 3,759 Western Australia 4.48,44 84.74 38 4.86 53 8.9,837 South Australia.., 85. 95 3.84 76.6,473 77.55,374 8.8 948 6.8,5.8 3,9 3.4.4 Road surface Table : Road surface by state Road surface Unknown Sealed Unsealed N % N % N % N % State Queensland.9 3,74 99.55 6.6 3,759 Western Australia 75.64,74 96.6.74,837 South Australia.4,46 99.56.4,473 87.96 8,945 98.63 37.4 9,69 Excludes Victoria MONASH UNIVERSITY ACCIDENT RESEARCH CENTRE

3.4.5 Road condition Table 3: Road condition by state Road condition Unknown Wet Dry N % N % N % N % State Victoria 73.5 378 7.8 4,38 9.67 4,83 Queensland.9 3 6. 3,58 93.59 3,759 Western Australia 7.5 6 7.97,54 89.53,837 South Australia.. 53 6.9,3 93.8,473 55. 987 7.,759 9.78 3,9 3.4.6 Speed zone Table 4: Speed zone N % Speed zone Unknown 98 7.6 75 Km/H and under,96 87. 76 Km/H and over 84 5.93 3,9 BICYCLE AND MOTOR VEHICLE CRASH CHARACTERISTICS: TO 4 DATA 3

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 3,785 78.33 4,83 Queensland.3 65 7.35 3,95 8.34 3,759 Western Australia 77 6.4 454 6.,6 77.76,837 South Australia 47.9 398 6.9,8 8.,473 69.94,58 8.,4 79.95 3,9 4 MONASH UNIVERSITY ACCIDENT RESEARCH CENTRE

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 5 3. 7.86 885 3.9 45 7.9,53. -5 years 39.8 9.5 9.67.44 88.63 6-4 years 86 7.84 84.35 4 4.8 84.48,46 7.3 5-9 years 5.76 655 7.4 67 9.4 3 8.6,655.9-5 years 63.89 457.6 3 8.8 37.4,69.65 6-9 years 5.39 93 7.79 6 5.7 8.98,79 8.48 3-39 years 954 9.74 69 6.47 364.83 46 6.8,353 6.93 4-49 years 585. 4.9 47 8.7 335 3.55,577.34 5-59 years 339 7. 4 5.96 35 4.76 69 6.83 867 6.4 6+ years 58 5.34 7 4.58 6 3.74 9 3.68 67 4.5 4,83 3,759,837,473 3,9 BICYCLE AND MOTOR VEHICLE CRASH CHARACTERISTICS: TO 4 DATA 5

Table 7: Bicycle rider age grouping by sex Sex Unknown Female Male N % N % N % N % Age group Unknown 45 6. 83.96, 7.3,53-5 years...73 68 77.7 88 6-4 years 4.7 45 7.66,977 8.7,46 5-9 years 6.36 4.93,435 86.7,655-5 years.. 463 8.6,56 7.4,69 6-9 years.7 33 5.7 874 74.3,79 3-39 years 4.7 476.3,873 79.6,353 4-49 years.6 4 4.,35 85.73,577 5-59 years 3.35 39 6.3 75 83.6 867 6+ years 4.64 7.3 55 88.4 67 69.94,58 8.,4 79.95 3,9 6 MONASH UNIVERSITY ACCIDENT RESEARCH CENTRE

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 3,373 7.39,49 9.6 4,79 Queensland,457 67.6,96 3.74 3,653 Western Australia,466 75.4 478 4.59,944 South Australia,83 87.8 69.9,8 9,9 73.4 3,36 6.96,47 BICYCLE AND MOTOR VEHICLE CRASH CHARACTERISTICS: TO 4 DATA 7

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,83 75.84 583 4.6,43,873 74.95 66 5.5,499,85 7.7 77 9.73,597 3,73 7.39 657 7.6,38 4,858 7.96 74 8.4,58 9,9 73.4 3,36 6.96,47 4..3 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 58 9.63 6 9.38 64 Female,78 74.94 596 5.6,378 Male 7,69 7.48,76 7.5,9 9,9 73.4 3,36 6.96,47 4..4 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

Table : Bicycle rider injury severity by age grouping Injured Injury Severity Killed or seriously injured N % N % N % Age group Unknown 644 85.9 4.8 756-5 years 44 5.38 4 47.6 84 6-4 years,6 7.55 677 9.45,99 5-9 years, 7.7 44 8.8,563-5 years,5 75.8 378 4.7,59 6-9 years 844 76.5 59 3.48,3 3-39 years,65 74.66 56 5.34, 4-49 years,9 73.4 399 6.76,49 5-59 years 569 68.3 65 3.77 834 6+ years 37 6.79 3 38. 6 9,9 73.4 3,36 6.96,47 Figure 5: Injury severity by age group 6 5 Injury severity % 4 3-5 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

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 6 76.9 5 3.8 Midnight to 6 am 83 63.7 65 36.83 448 6 am to 8 am,4 7.53 456 7.47,66 8 am to am,47 77.8 44.9,8 am to midday 853 75.96 7 4.4,3 Midday to pm 87 7.5 36 7.49,3 pm to 4 pm,694 73.9 598 6.9,9 4 pm to 6 pm,786 7.9 664 7.,45 6 pm to 8 pm 768 7.7 35 9.73,93 8 pm to midnight 8 6.44 69 37.56 45 9,9 73.4 3,36 6.96,47 Figure 6: Injury severity by time of day 4 35 Injury severity % 3 5 5 5 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

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,966 7.6,35 9.4 4, Four Wheel Drive Compact (4WDC) 5 7.4 4 7.59 45 Four Wheel Drive - Large (4WDL) 38 68.66 63 3.34 Four Wheel Drive - Medium (4WDM) 84 74.34 9 5.66 3 Commercial - Ute (CU) 37 63.3 78 36.7 485 Commercial - Van (CV) 96 67.3 47 3.87 43 Large (L),64 7.79 67 9.,94 Luxury (LX) 76 7.77 4 9.3 39 Medium (M) 39 67.58 53 3.4 47 People Mover (PM) 73 64.6 4 35.4 3 Small (S) 779 7.7 34 8.73,93 Light (SL) 447 73.4 6 6.6 69 Sport (SP) 8 63.8 48 36.9 3 7,96 7.3 3,93 9.77,389 Figure 7: Bicycle rider serious injury by vehicle market group 8 7 6 5 % 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

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

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. 4..7 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 485 74.96 6 5.4 647 75 Km/H and under 8,56 73.9,879 6.9,35 76 Km/H and over 468 59.3 3 4.68 789 9,9 73.4 3,36 6.96,47 Figure 9: Bicycle rider injury severity by speed zone (%) 45 4 35 3 5 5 5 75 Km/h and under 76 Km/h and over BICYCLE AND MOTOR VEHICLE CRASH CHARACTERISTICS: TO 4 DATA 3

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,86 87. 69.9,85 Pedestrian (on foot or in toy/pram) 3 6 4 5 Vehicles from adjacent directions (intersections only),4 7.44 883 9.56,987 Vehicles from opposing directions 88 64.4 46 35.76,89 Vehicles from same direction,569 7.77 648 9.3,7 Manoeuvring,39 7.64 87 8.36,846 Overtaking 6 7.9 4 7.9 86 On path 56 7.7 9 7.3 696 Off path on straight 64 73.87 58 6.3 Off path on curve 5. 6 75. 8 Passenger and miscellaneous 6 53.33 4 46.67 3 9,9 73.4 3,36 6.96,47 4 MONASH UNIVERSITY ACCIDENT RESEARCH CENTRE

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 533.3,635 33.84,664 55.3 4,83 Queensland 39 8.,388 36.9,6 54.86 3,759 Western Australia 43 8.57,75 4.4,49 5.,837 South Australia 55.3 876 35.4,34 54.7,473,34 9.64 5,74 36.5 7,487 53.86 3,9 BICYCLE AND MOTOR VEHICLE CRASH CHARACTERISTICS: TO 4 DATA 5

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 58.4 445.84 589.76 596 4., 5.9-5 years.... 5.8.. 5.37 6-4 years...3 9... 9.9 5-9 years 5 4.66 6 5.75 398 4.3 4 5.66 979 7.4-5 years 63.89 469.48 56 8.54 6.55,879 3.5 6-9 years 386 7.99 37 8.7 449 5.83 45 5.86,87 9.6 3-39 years,34.4 736 9.58 339.95 4 6.6,5 8.6 4-49 years 8 6.97 653 7.37 4.7 49 6.94,3 4.48 5-59 years 63.48 49 3.9 74.6 3.58,48.65 6+ years 559.57 44.7.. 99 8.5,98 8.6 4,83 3,759,837,473 3,9 6 MONASH UNIVERSITY ACCIDENT RESEARCH CENTRE

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 4,76 98.55 57.8 3.7 4,83 Queensland 3,74 98.8 39.4 6.6 3,759 Western Australia,79 98.38 37.3 9.3,837 South Australia,458 99.39 5.6..,473 3,75 98.73 48.6 8. 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 9,34 73.5 3,99 6.75,333 Injured 7 6. 45 38.79 6 Killed or seriously injured 4 8.8 8 8.8 9,9 73.4 3,36 6.96,47 BICYCLE AND MOTOR VEHICLE CRASH CHARACTERISTICS: TO 4 DATA 7

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 7 6. 45 38.79 6 Killed Or seriously injured 4 8.8 8 8.8 75 54.35 63 45.65 38 6. 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. 6..3 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

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. 6..5 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

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

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

Temporal characteristics Table A.: Month of accident Month of accident Frequency Percent January 399 8.6 February 489. March 55.4 April 38 7.9 May 467 9.66 June 35 6.73 July 35 6.3 August 35 7.8 September 339 7. October 388 8.3 November 45 8.59 December 49 8.67 483 Table A.: Day of week Day of week Frequency Percent Sunday 493. Monday 688 4.4 Tuesday 8 6.8 Wednesday 783 6. Thursday 85 6.87 Friday 76 4.8 Saturday 55.87 483 Table A.3: Time of day Time of day Frequency Percent Unknown 5. Midnight to 6 am 7.47

Time of day Frequency Percent 6 am to 8 am 49.4 8 am to am 836 7.3 am to midday 465 9.6 Midday to pm 437 9.4 pm to 4 pm 77 4.63 4 pm to 6 pm 4.78 6 pm to 8 pm 58. 8 pm to midnight 37 4.9 483 Bicycle rider behaviour Table A.4: Helmet use Helmet Use Frequency Percent Seatbelt worn. Crash helmet worn 384 67.96 Crash helmet not worn 63 3.6 Not appropriate 8.7 Unknown 98 8.79 483 Table A.5: Lamp usage Lamp usage Frequency Percent Not applicable 59 5.9 Yes 593.7 No 8 6.8 Unknown 98 9. 483

Table A.6: Blood Alcohol Content Blood Alcohol Content Frequency Percent Not tested / none 486 99.67. 6..4..58..68..69..9..4..6..63..35. 483 Accident nature and site features Table A.7: Accident type Accident type Frequency Percent Collisn with veh 4673 96.7 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 7.63 483

Table A.8: Road type Road Type Frequency Percent Unknown 8.58 Alley. Arcade. Avenue 8 3.77 Boulevard 6.33 Circle. Circuit. Close 4.8 Court 4.85 Crescent 44.9 Drive.5 Esplanade. Freeway 37.77 Freeway east 6. Freeway west.4 Gardens. Grove 4.9 Highway 585. Highway east 54. Highway west 43.89 Lane 7.35 Parade 66.37 Parade west. Place 4.5 Place east. Promenade.4 Rise. Road 894 39. Road east 3.6

Road Type Frequency Percent Road north. Road south. Road west 6. Square south. Street 597 33.5 Street east 4.8 Street ext. Street north 3.6 Street south. Street west.4 Strip. Terrace 3.6 Toll way.4 Way 7.35 483 Table A.9: Road geometry Road geometry Frequency Percent Cross intersection 35 7.96 T-intersection 453 3.7 Y-intersection 34.7 Multiple intersection. Not at intersection 89 39.3 Unknown. 483

Table A.: Road character Controlling for road character=straight Road character Road character (N / % / Row % / Column %) Driveway or crossover 865 6.9 6.5 Divided road 859 38.99 99.73 39.3 Median opening(not at interstn).. Driveway or crossover 38.8.8 4763 99.9 5..7 5. 865 6.9 864 39.9. 38.8 4768 Controlling for Road character=curve Road character Road character (N / % / Row % / Column %). Driveway or crossover. 56 87.5 87.5 Divided road 7.94.94 Median opening(not at interstn. Driveway or crossover.56.56 64..... 56 87.5 7.94.56 64

Table A.: Road surface conditions Road surface conditions Road surface conditions (N / % / Row % / Column %) Wet Dry 4379 9.63 99.95 9.66 Wet 378 7.8 7.83 Muddy.. Unknown 7.49.49 483 99.96.4.5.4 438 9.67 378 7.8. 7.49 483 Table A.: Traffic controls Traffic controls Frequency Percent No control 336 64.9 Stop-go lights 53.8 Flashing lights.4 Out of order 3.6 Pedestrian lights 4.5 Pedestrian crossing 38.79 Railway crossing gates & booms 4.8 Roundabout 35 7.4 Stop sign 9 3.97 Give way sign 398 8.4 School - no flags 4.8 Police. Other.46 Unknown 35.79

Traffic controls Frequency Percent 483 Table A.3: Number of vehicles involved Number of Vehicles Involved Frequency Percent 449 9.96 3 94 6.8 4 7.56 5 4.8 6 5. 7. 483 Table A.4: Speed zone at accident site Speed zone at accident site Frequency Percent 4 km/hh 4.83 5 km/hr 74.3 6 km/hr 957 6. 7 km/hr 86 5.9 8 km/hr 66 5.5 9 km/hr 8.7 km/hr 3.73 km/hr 6. Other speed limit.4 Camping ground/off rd. Not known 6.4 483 Table A.5: Hit run accident Hit run accident Frequency Percent No 4337 89.76 Yes 495.4

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) 84 5.93 Two right turning (intersections only) 5.3 Right/left far (intersections only).5 Left near (intersections only) 86 3.88 Left/right far (intersections only). Two left turning (intersections only). Other adjacent (intersections only).4 Head on (not overtaking) 86.79 Right through 549.46 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 -5 7.5 Rear end(vehicles in same lane) 7 4.74 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

Definition for classifying accidents Frequency Percent Left turn sideswipe 4 4.47 Other same direction-manouevres not included in dcas 3-37.44 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 586.3 Vehicle off footpath strikes veh on carriageway 63.79 Other manoeuvring not included in dcas 4-48 5.3 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 5-54 3.6 Vehicle collides with vehicle parked on left of road 7.35 Vehicle strikes door of parked/stationary vehicle 389 8. 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 7-75.4 Off right bend into object/parked vehicle. Off left bend into object/parked vehicle.4

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) 44 3. 8.9 7.4 Right far (intersections only) 3.7 5..67 Left far (intersections only) 3.48 74.9.8 Right near (intersections only) 54.3 9..77 Two right turning (intersections only) 6.3 4.3 Right/left far (intersections only) 8.7 66.67.4 Left near (intersections only) 9.4..98 Left/right far (intersections only) Bicycle DCA reference (N / % / Row % / Column %) Not known which vehicle was number Vehicle. 5.4 357 7.45 7.4 3.4 39.8 75..4 8.7 5.8.9 7 4.74 79.93 8.9 9.9 6.33 4.8 33.33.5 63 3.4 87.63 5.95..4 Not involved in initial event 8.7.57 7.48 3.6.6.8 4.8.5 3.74..4. 59.6 5.9 3.65 84 5.93 5.3.5 86 3.88.

Definition for classifying accidents (DCA) Vehicle Two left turning (intersections only)..5 Other adjacent (intersections only).3 55..57 Head on (not overtaking) 56.7 65..88 Right through 54.3 9.84.77 Left through 6.3 75..3 Right/left. One veh turning right the other left 4.8 66.67 Right/right. Both vehs from opposite directions turning right Other opposing manoeuvres not included in DCAs -5.. 5..5.4 8.57. Rear end (vehicles in same lane) 38.79 6.74.95 Left rear 9.4 7.37.98 Right rear 7.5.88.36 Lane side swipe (vehicles in parallel lanes) 47.98 9.58.4 Lane change right (not overtaking) 3.5 85.83 5.9 Lane change left (not overtaking).5.6.6 Right turn sideswipe 54.3 79.4.77 Left turn sideswipe 5..34.6 Bicycle DCA reference (N / % / Row % / Column %) Not known which vehicle was number Vehicle 9.9 45..33 8.58 3.56. 477 9.95 86.89 7.4.4 5..7.4 33.33.7 3.6 75.. 3.6 4.86. 74 3.63 76.65 6.36 8.7 9.63.9 3.48 7.88.84 83 3.8 76.5 6.68 7.35 4.7.6 93.94 8.3 3.4 4.9.59.5 6 4.3 96.6 7.5. 4.9 Not involved in initial event.4.33.87 8.38 3.8 6.8. 4.9.93 5.3 6.6 4..4 6.5.87. 4.7 9.35 8.7 7.8 7.48 3.6.4.8..4 86.79 549.46 8.7 6.3 4.8 7.5 7 4.74 7.56 3.67 4 5..5 3.36 68.4 4 4.47

Definition for classifying accidents (DCA) Other same direction-manouevres not included in DCA3-37 Vehicle 6.3 8.57.3 U turn 4.9 3.33.7 Leaving parking Entering parking..33.5 Reversing in stream of traffic. 33.33.5 Reversing into fixed object/parked vehicle Vehicle strikes another veh while emerging from driveway 6.63.5 6.47 Vehicle off footpath strikes veh on carriageway 569.87 9.8 9.4 Other manoeuvring not included in DCAs 4-48 8.7 53.33.4 Head on (overtaking) 6.3 6.3 Pulling out (overtaking).3 64.7.57 Cutting in (overtaking)..5 Pulling out -rear end..5.5 Other overtaking manoeuvres not included in DCAs 5-54. 33.33.5 Vehicle collides with vehicle parked on left of road 7.35.87 Vehicle strikes door of parked/stationary vehicle 347 7.4 89. 7.83 Bicycle DCA reference (N / % / Row % / Column %) Not known which vehicle was number Vehicle.3 5.38.4 43.9 7.67.57 6.54.95 4.88 97.67.53.4 66.67.7..4 457 9.54 77.99 6.69 4.83 6.53.46 5. 33.33.8 4.8 4.5 6.3 35.9. 4.8 8.5 7.5 87.5.6.4 66.67.7 36.75 9.5.3 Not involved in initial event 4.8 9.5 3.74 3.6 5..8 3.6.5.8 4.8.65 3.74.4 3.33.87 6.3.54 5.6.44 6.5 6.54 43.9 3.6. 586.3 63.79 5.3. 7.35 5. 8.7 3.6 7.35 389 8.

Definition for classifying accidents (DCA) Vehicle Temporary road works..5 Struck object on carriageway..5 Other on path..5 Off carriageway to left.4 95.4.3 Left off carriageway into object/parked vehicle 5. 6.5.6 Off carriageway to right.4. Right off carriageway into object/parked vehicle.4. Out of control on carriageway (on straight) 4.7 98. 5.34 Off end of road/t-intersection Other accidents-off straight not included in DCAs 7-75. 5.5 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 3.6.5 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. 4.76.93 3.6 37.5.8.4.89.87..93..93 3.6 6.8....44 8.7.4.4 6...4..4.4. 3.6 5.

Definition for classifying accidents (DCA) Vehicle 946 4.6 Weather and light conditions Table A.8: Light conditions Bicycle DCA reference (N / % / Row % / Column %) Not known which vehicle was number Vehicle 738 57.4. Not involved in initial event 7.3 479 Light conditions Frequency Percent Day 3748 77.57 Dusk/dawn 487.8 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 3.48 483 Table A.9: Weather conditions Weather condition Clear 449 9.9 99.53 93.48 Raining 4 4.43 98.7 4.46 Snowing.. Fog.. Smoke.. Dust.4.4 Strong 6 winds. 6. Weather condition (N / % / Row % / Column %) Clear Raining Fog Dust.4.4.4.4.4.4 Strong winds 6.33.35 8 4.8.83 Unknown.. 45 93.36 8 4.5....4.

Unknown 79.63.64 483 99.4.4.4.4.4.4. 79.63 483

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) 348 7.6 68.37.3 Right far (intersections only) 37.77 7.5. Left far (intersections only).4 64.5.59 Right near (intersections only) 4.9 7.77 5.96 Two right turning (intersections only) 9.9 6.7 Right/left far (intersections only). 83.33.3 Left near (intersections only) 5 3.5 8.8 4.48 Left/right far (intersections only)..3 Two left turning (intersections only)..3 Other adjacent (intersections only).3 55..33 Head on (not overtaking) 48. 55.8.4. 5.7..7 6 3.36 3.63.35 5.3 8.85.6.3 35.48.78 83.73 9.3 5.85 6.3 4.4.4 6.67.4 35.73 8.8.47 9.9 45..63 38.79 44.9.68..4. 59.6 5.9 3.65 84 5.93 5.3.5 86 3.88...4 86.79

Definition for classifying accidents (DCA) Right through 359 7.49 65.39.64 Left through 5. 6.5.5 Right/left. One veh turning right the other left 5. 83.33.5 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 9 3.96 34.6 3.39 4.8. 7.5. Rear end(vehicles in same lane) 58 3.3 69.6 4.68 Left rear.44 77.78.6 Right rear 4.5 75..7 Lane side swipe (vehicles in parallel lanes) 87 3.9 77.9 5.54 Lane change right (not overtaking) 68.4 56.67. Lane change left (not overtaking) 8.69 7.68.4 Right turn sideswipe 45.94 66.8.33 Left turn sideswipe 73 3.6 8.84 5.3 Other same direction-manoeuvres not included in DCAs 3-37 4.9 66.67.4 U turn 37.77 6.67. Leaving parking.4 76.9.59 3.6 37.5.. 6.67.7 69.44 3.4 4.86 6.3..4 8.7 5..56 53..8 3.74 5.9 43.33 3.66 3.67 8.3.6 3.48 33.8.6 4.86 9.6.89 7.5 33.33.49 3.48 38.33.6 6.3 3.8.4 549.46 8.7 6.3 4.8 7.5 7 4.74 7.56 3.67 4 5..5 3.36 68.4 4 4.47.44 6.5 6.54

Definition for classifying accidents (DCA) Entering parking 35.73 8.4.4 Reversing in stream of traffic 3.6.9 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 8.7 8.6.56 47 8.9 7.87.66 Vehicle off footpath strikes veh on carriageway 4 8.6 67.. Other manoeuvring not included in DCAs 4-48.3 73.33.33 Head on (overtaking) 6.3 6.8 Pulling out (overtaking) 4.9 8.35.4 Cutting in (overtaking) 4.8 8. Pulling out -rear end 5. 6.5.5 Other overtaking manoeuvres not included in DCAs 5-54.4 66.67.6 Vehicle collides with vehicle parked on left of road 6.3 35.9.8 Vehicle strikes door of parked/stationary vehicle 85 5.95 73.6 8.45 Temporary road works..3 Struck object on carriageway..3 Other on path..3 59 3.3 7.3. 4.9 3.79 4.6 4.8 6.67.8 4.8 4.8 3.6 7.65...7 3.6 37.5.. 33.33.7.3 64.7.78 4.7 6.74 7.33 43.9 3.6. 586.3 63.79 5.3. 7.35 5. 8.7 3.6 7.35 389 8....

Definition for classifying accidents (DCA) Off carriageway to left 5.3 7.43.44 Left off carriageway into object/parked vehicle 7.5 87.5. Off carriageway to right. 5.3 Right off carriageway into object/parked vehicle.4.6 Out of control on carriageway (on straight) 79.65 74.53.34 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 6.3 8.57.4. 5.3 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.4 66.67.6 Unknown - no details on manoeuvres of road users in accident 3.6 6.9 3373 7.39..5.7. 5.7 7.56 5.47.9..7. 5.7..7. 5.7.4.4. 33.33.7.4 4.4 49 9.6.44 8.7.4.4 6...4..4.4. 3.6 5. 479

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

Temporal characteristics Table A.: Day of week Day of week Frequency Percent Sunday 94 7.8 Monday 557 4.8 Tuesday 65 6.9 Wednesday 66 7.56 Thursday 6 6.55 Friday 6 6.3 Saturday 4.93 Helmet use Table A.: Helmet use Helmet use Frequency Percent Unknown 554 4.74 Worn 689 7.53 Not worn 55 3.7 Not applicable.3 Accident nature and site features Table A.3: Accident type Accident type Frequency Percent Hit parked vehicle 8 5.8 Angle 75 7.49 Rear-end 8 4.79 Head-on 65.73 Sideswipe 486.93 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

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 357 94.97 3 48 3.94 4 3.8 5.9 Table A.5: Divided Road Divided road Frequency Percent N 45 63.98 Y 354 36. Table A.6: On/off carriageway On/off carriageway Frequency Percent Other/unknown 578 4.98 On carriageway 957 5.6 Off carriageway 4 5.96 Table A.7: Road feature Road feature Frequency Percent Other 7.45 Cross intersection 639 7. T-junction 7 9.98 Y-junction 8. Multiple road 6.6 Interchange 3.85 Roundabout 3 8.3

Road feature Frequency Percent Bridge/causeway 3.35 Median opening 5.4 Merge lane 6.6 Not applicable 584 4.4 Table A.8: Traffic controls Traffic controls Frequency Percent Police.5 Road/rail workers.5 Operating traffic lights 444.8 Stop sign 55 4. Give way 63 6.76 Pedestrian crossing 67.78 School crossing-flags only.3 Miscellaneous 9.4 No traffic control 449 65.5 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 7.9 3 km/hr 5.3 4 km/hh 3. 5 km/hr 654 7.4 6 km/hr 587 68.8 7 km/hr 6 4.6 8 km/hr 38 3.67 9 km/hr.5 km/hr 7.86 km/hr.5

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) 348 9.6 Right far (intersections only) 4.6 Left far (intersections only) 83. Right near (intersections only) 5 6.65 Two right turning (intersections only) 4.64 Right/left far (intersections only) 8.74 Left near (intersections only) 79 4.76 Other adjacent (intersections only) 7 6.4 Head on (not overtaking) 76. Right through 35 9.3 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 -5 4. Rear end(vehicles in same lane) Left rear 4 3.3 3.35 Right rear 5.4 Lane side swipe (vehicles in parallel lanes) Lane change right (not overtaking) Lane change left (not overtaking) Right turn sideswipe 55 6.78 8.48 4.64 43 3.8 Left turn sideswipe 93 5.3 Other same direction-manouevres not included in DCAs 3-37 9.77 U turn.7 Leaving parking 6.43 Entering parking 3.35

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 59 4.3 Vehicle off footpath strikes veh on carriageway 447.89 Other manoeuvring not included in DCAs 4-48 36 8.67 Head on (overtaking) 4. Pulling out (overtaking).3 Cutting in (overtaking) 3.8 Other overtaking manoeuvres not included in DCAs 5-54 9.4 Vehicle collides with vehicle parked on left of road 54.44 Vehicle strikes door of parked/stationary vehicle 43 3.8 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 7-75.5 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 3 83. Dawn/dusk 8 6.7 Darkness lighted 39 8.49 Darkness unlighted 8.3 Unknown.3

Road Conditions Table A.: Vertical alignment Vertical alignment of road Frequency Percent Level 99 79.6 Grade 68 6.7 Crest 63.68 Dip 96.55 Table A.3: Horizontal alignment Horizontal alignment of road Frequency Percent Straight 3354 89.3 Curve-view obstructed 99.63 Curve-view open 36 8.4 Table A.4: Road surface conditions Road surface conditions Frequency Percent Sealed-Dry 35 93.43 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 3.8..3.4 Cross traffic(intersections only) 8 5.97 63.74 8.87 Right far (intersections only) 37. 9.5.5 Killed or seriously injured 4 3.39 36.6.37 3.8 7.5.5 3.8.3 34 9.36 4.9

Definition for classifying accidents (DCA) Injury severity (N / % / Row % / Column %) Injured Left far (intersections only) 58.59 7.6.36 Right near (intersections only) 55 4.4 6.5 6.3 Two right turning (intersections only) 7.47 7.83.69 Right/left far (intersections only) 5.4 53.57.6 Left near (intersections only) 34 3.67 75.8 5.45 Other adjacent (intersections only) 43 3.9 63.56 5.8 Head on (not overtaking) 38.4 5.55 Right through 9 6. 63.48 8.9 Left through 8. 8.33 Right/left. One veh turning right the other left 7.9 63.64 Right/right. Both vehs from opposite directions turning right Other opposing manoeuvres not included in DCAs -5.8 3.8..5 5.8 Rear end(vehicles in same lane) 63.7 58.33.56 Left rear.3 84.6.45 Right rear 9.5 6.37 Lane side swipe (vehicles in parallel lanes) 54 4. 6. 6.7 Killed or seriously injured 3.63 8.4.9 93.55 37.5 7.78 7.9 9.7.59 3.36 46.43.9 44. 4.7 3.68 8.4 36.44 6.86 38.4 5 3.8 6 3.45 36.5.54.5.7 4. 36.36.33.5 5.7 45.3 4.67 3.76.5 5.38.7 6.6 4.5 98.68 38.89 8.9 8. 48 6.79 4.66 8.77 78 4.87 5 6.6 76.8 345 9.44.7.3 3.8 4. 8.96 3.36 5.4 5 6.9

Definition for classifying accidents (DCA) Injury severity (N / % / Row % / Column %) Injured Lane change right (not overtaking).33 7.59.49 Lane change left (not overtaking) 6.44 7.73.65 Right turn sideswipe 9.49 64.54 3.7 Left turn sideswipe 53 4.9 79.7 Other same direction-manouevres not included in DCAs 3-37 6.3 5.68 86.. U turn 5.4 5. Leaving parking.3 68.75.45 Entering parking.33 9.3.49 Parked vehicles only.3.4 Reversing in stream of traffic.5 66.67.8 Vehicle strikes another veh while emerging from driveway 5.87 67.3 4.7 Vehicle off footpath strikes veh on carriageway 34 8.3 68.3.37 Other manoeuvring not included in DCAs 4-48 39 6.54 75.6 9.73 Head on (overtaking).3 5..4 Pulling out (overtaking).7 83.33.4 Cutting in (overtaking).3 33.33.4 Killed or seriously injured 5.4 9.4.4 6.6 7.7.5 5.37 35.46 4.8 4.9.73 3.34 4. 3.79.33 5.4 5.4 5.4 3.5.4.3 7.69.8.3 33.33.8 5.4 3.69 4.6 4 3.86 3.69.79 79.6 4.84 6.6 3.8 75..5.5 6.67.7.5 66.67.7 7.47.6 4 3.86 93 5.8 9.79.7 6.44 3.36.3 3.8 56 4.7 445.8 38 8.7 4..33 3.8

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 6.6 66.67.4 37. 68.5.5 Vehicle strikes door of parked/stationary vehicle 97.66 69.9 3.95 Struck object on carriageway.5.8 Left off carriageway into object/parked vehicle.6 56.4.9 Right off carriageway into object/parked vehicle.5 66.67.8 Other accidents-off straight not included in DCAs 7-75.5.8 Off right bend into object/parked vehicle.3 5.4 Load or missile struck vehicle.5 66.67.8 Other accidents not classifiable elsewhere 3.8 33.33. 457 67.6 Killed or seriously injured 3.8 33.33.5 7.47 3.48.4 43.8 3.7 3.6 7.47 43.59.4.3 33.33.8.3 5.8.3 33.33.8 6.6 66.67.5 96 3.74 9.5 54.48 4 3.83.5 39.7 3.8.5.5 3.8 9.5 3653

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

Temporal characteristics Table A3.: Day of week Day of week Frequency Percent Sunday 99 7. Monday 43 4.9 Tuesday 49 7.34 Wednesday 49 7.7 Thursday Friday 5 8.4 435 5.33 Saturday 76 9.73 Helmet use TableA3.: Helmet use Helmet use Frequency Percent 584 9.8 Worn 5 8.85 Not Worn.7 Accident nature and site features Table A3.3: Number of units involved Number of units involved Frequency Percent 785 98.7 49.73 3 3. Table A3.4: Accident type Accident type Frequency Percent Mid block 49 5. Intersection 39 49.3 Cycle path.4 Roads open to public access.74 Location not known 5.8

Table A3.5: MR nature code MR Nature Code Frequency Percent Unknown 45 4.8 Rear end 8 7.33 Head on 3.9 Sideswipe same dirn 437 5.4 Right angle 497 5.77 Right turn thru 98 6.98 Hit pedestrian.4 Hit obj.78 Non collision 38.34 Table A3.6: MR type code MR Type Code Frequency Percent Unknown 94 67. Involving overtaking 88 6.63 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 79 98.38 Overturns 38.34 Falls from moving veh 3. Other non-collision 5.8

Table A3.8: First object hit First Object Hit Frequency Percent Not applicable 87 99.65 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 836 99.96 Kerb when stated as cause.4 Table A3.: Carriageway Carriageway Frequency Percent 3.9 L 53 8.8 R 9 4.9 S 74 76.63 Table A3.: Road works site Road Works Site Frequency Percent 37 43.6 No 59 56. Yes 8.8

Table A3.: Road features Road feature Frequency Percent Unknown 739 6.5 4-way intx 443 5.6 3-way intx (t-junction) 78 7.49 Intx > 4 legs.7 Roundabout 8 6.38 Median opening.78 Rail xing 4.4 Bridge 7.5 Driveway 644.7 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 75 9.69 Stop sign 43 8.57 Give way sign 384 3.54 Zebra crossing.39 Rail xing - boomgates 3. Rail xing - flashing lights only.4 School crossing.35 No sign or control 868 65.84 Pointsman.4 Traffic lights & give way sign.4 Mid block traffic lights 3.

Table A3.4: Traffic control functioning Traffic Control Functioning Frequency Percent 5 88.47 Yes 37.53 Table A3.5: Speed zone at accident site Speed zone at accident site Frequency Percent Not known 94 3. km/hr.7 5 km/hr.4 3 km/hr.4 4 km/hh 63. 5 km/hr 5 7.66 6 km/hr 38 4. 7 km/hr 3 4.58 8 km/hr 58.4 9 km/hr.4 km/hr 9.3 km/hr 8.8 Table A3.6: Road user movement Road user movement Frequency Percent Intx: other 88 3. Intx: thru - thru 54 7.77 Intx: right - thru 48.69 Intx: left - thru 86 3.3 Intx: thru - right 44 5.8 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

Road user movement Frequency Percent Opposite dirn: thru - right 96 6.9 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 33 4.69 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 3 4.34 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 355.5 Manoeuv: leaving parking 7.5 Manoeuv: parking 3. Manoeuv: parking veh only.4 Manoeuv: reversing in traffic 8.8 Manoeuv: leaving driveway 79 6.3 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

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 85 3. Clear 439 85.97 Raining 5 3.7 Fog / smoke / dust 5.8 Overcast 7.8 Fog / mist.7 Table A3.8: Light conditions Light conditions Frequency Percent unknown 4.48 Daylight 44 84.74 Dawn or dusk 38 4.86 Dark - street lights on 4 7.9 Dark - street lights off.39 Dark - street lights not provided 8.63

Road conditions Table A3.9: Road condition Road Condition Frequency Percent Unknown 7.5 Wet 6 7.97 Dry 54 89.53 Table A3.: Road alignment Road alignment Frequency Percent Unknown 76 6. Curve 385 3.57 Straight 76 8.3 Table A3.: Road gradient Road gradient Frequency Percent Unknown 3.95 Level 67 7.86 Crest of hill 7.47 Slope 588.73 Table A3.: Road surface conditions Road surface conditions Frequency Percent Unknown 75.64 Sealed 74 96.6 Unsealed.74

Bicycle rider injury severity Table A3.3: Serious injury by road user movement Road user movement (RUM) Intx: other 46.37 74.9 3.4 Intx: thru - thru 8 4.4 74.7 9. Intx: right - thru.8 8.77.43 Intx: left - thru 4.6 85.7.86 Intx: thru - right 69 3.55 69. 4.7 Intx: right - right.5 9.9.68 Intx: left - right 6.3.4 Intx: thru - left 64 3.9 8.5 4.37 Opposite dirn: other.5.7 Opposite dirn: head on 8.4 6.54.55 Opposite dirn: thru - right 6 5.45 67.95 7.3 Opposite dirn: right - left 3.5. Opposite dirn: thru - left 4. 66.67.7 Opposite dirn: u - turn.5.7 Same dirn: other 4..7 Injury severity (N / % / Row % / Column %) Killed or seriously Injured injured 6.8 5.8 3.35 98 5.4 5.93.5 5.6 9.3.5 7.36 4.9.46 3.59 3. 6.49.5 9.9. 4.7 7.95.93 5.6 38.46.5 5.57 3.5.46. 33.33.4 6 3.9 378 9.44 6.34 49.5 5.4.57 6.3 78 4..5 3.67 56 8. 3.5 6.3.5 4.

Road user movement (RUM) Same dirn: same lane rear end 64 3.9 6.38 4.37 Same dirn: same lane left rear.57 9.67.75 Same dirn: same lane right rear.57 84.6.75 Same dirn: same lane u - turn 4. 8.7 Same dirn: parallel lanes - s/swipe 63 3.4 75. 4.3 Same dirn: change lanes - right.6 57.4.8 Same dirn: change lanes - left.57 73.33.75 Same dirn: parallel lanes - turn right s/swipe Injury severity (N / % / Row % / Column %) Killed or seriously Injured injured 4.6 39.6 8.79.3 66.67.5 Same dirn: parallel lanes - turn left s/swipe 6 3.9 86. 4.3 Manoeuv: other 79 9. 8.. Manoeuv: leaving parking 6.3.4 Manoeuv: parking 3.5. Manoeuv: reversing in traffic.5 33.33.7 Manoeuv: leaving driveway 8 4.7 75.7 5.53 Manoeuv: from footway 44 7.4 7. 9.8 Overtaking: other.5.7.5 8.33.. 5.38.4.5..8 5. 4.39 9.46 4.86.88 4. 6.67.84.57 33.33.3.5 3.89.9 39. 7.89 8.6. 66.67.4 6.34 4.3 5.44 56.88 8..7 6 5.45.6 3.67 5.6 84 4.3.8 5.77 33.7 7 3.7 8. 6.3 3.5 3.5 7 5.5.9.5

Road user movement (RUM) Overtaking: pulling out.5.7 Overtaking: cutting in.5.7 Overtaking: into right turn.5 83.33.68 On path: other 3.5 5. On path: parked 6.8 76.9.9 On path: accident or breakdown.5 33.33.7 On path: open car door 56.88 9.8 3.8 Off path on straight: off left cway.5.7 Off path on straight: off left cway obj 6.3.4 Off path on straight: off right cway obj. 66.67.4 Off path on straight: lost control on cway 4.3 9.3.64 Off path on curve: off right bend in obj Misc: passenger fell in / from veh.5 33.33.7 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. 6.67.4 3.5 5.63 5.6 3.8.5. 66.67.4 5.6 8..5.5 33.33.. 7.69.4.5.. 66.67.4. 5.4 466 478 944.5.5.6 6.3.8 3.5 6 3.4.5 6.3 3.5 6.34.5 3.5.5.5 4.

Road user movement (RUM) Injury severity (N / % / Row % / Column %) Killed or seriously Injured injured 75.4 4.59

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

Temporal Characteristics Table A4.: Month of crash Month of crash Frequency Percent January 8 7.8 February 9 9.6 March 3.6 April 8.98 May 6 9.4 June 48 5.98 July 83 7.4 August 98 8. September 77 7.6 October 94 7.84 November 3 8.6 December 9 7.7 Table A4.: Time of crash Time of crash Frequency Percent Midnight to 6 am 34.37 6 am to 8 am 7.96 8 am to am 445 7.99 am to midday 4 9.6 Midday to pm 9 8.86 pm to 4 pm 367 4.84 4 pm to 6 pm 575 3.5 6 pm to 8 pm 35 9.5 8 pm to midnight 3 4.6

Helmet use Table A4.3: Helmet use Helmet use Frequency Percent 39 5.85 Worn 776 7.8 Not worn 43 5.78 Unknown 6 6.55 Accident nature and site features Table A4.4: Accident type Accident type Frequency Percent Rear end 4 8.65 Hit fixed object.8 Side swipe 485 9.6 Right angle 6 46.95 Head on 64.59 Roll over 3. Right turn 99.9 Hit parked vehicle 46 5.9 Hit object on road.4 Left road - out of control.4 Other 97 3.9 Table A4.5: Traffic controls Traffic controls Frequency Percent Traffic signals 365 4.76 Rail xing - boom.4 Rail xing - flashing.8 Stop sign 4.45 Give way sign 4.4 No control 734 7. Roundabout 57 6.35 Other 4.6

Table A4.6: Other road features Other road features Frequency Percent Bridge, culvert, causeway 6.4 Road works 7.8 Driveway or entrance 66 6.7 Road hump or slow point 8.73 Median opening (not at i/s) 9.36 Not applicable 37 9.46 Unknown 3. Table A4.7: Road geometry Road geometry Frequency Percent Interchange.8 Cross road 638 5.8 Y-Junction 7.8 T-Junction 783 3.66 Multiple 33.33 Rail xing.4 Rail crossing.8 Divided road 53.5 Not divided 4 6.66 One way.8 Freeway.8 Pedestrian crossing 4.6 Other 55.

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 35.4 5 km/hr.8 km/hr 3. 5 km/hr 3.53 4 km/hh 33.33 5 km/hr 9.8 6 km/hr 937 78.33 7 km/hr 39.58 8 km/hr 66.67 9 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 46 99.56 Unsealed.4 Unknown.4 Table A4.: Road moisture condition Road Moisture condition Frequency Percent Wet 53 6.9 Dry 3 93.8

Table A4.: Vertical alignment Vertical road alignment Frequency Percent Level 89.45 Crest of hill.8 Bottom of hill 38.54 Slope 98 8. Unknown 5. Table A4.: Horizontal road alignment Horizontal road alignment Frequency Percent Straight road 345 94.8 Curved, view obscured 4.6 Curved, view open 84 3.4 Unknown 4.6 Weather and light conditions Table A4.3: Weather Weather Frequency Percent Raining 97 3.9 Not raining 376 96.8 Table A4.4: Light condition Light condition Frequency Percent Daylight 85. Dawn/Dusk 95 3.84 Night 76.6 Apparent error Table A4.5: Responsible entity Responsible entity Frequency Percent Driver rider 45 99. Passenger 9.77 Other 3.

Table A4.6: Apparent error Apparent error Frequency Percent Excessive speed.4 Fail to stand.8 Fail to keep left 34.37 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 4 9.75 No errors 75 68.94 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 468 99.8 Disobey - traffic lights.4 Inattention.8 D.U.I..8

APPENDIX 5 BICYCLE AND PEDESTRIAN CRASH CHARACTERISTICS CRASHES DURING -4

Colliding pedestrian characteristics Pedestrian demographics Sex Table A5.: Pedestrian sex by state Pedestrian sex Unknown Female Male N % N % N % N % State Victoria 5 5.38 6 65.59 7 9.3 93 Queensland.. 37 68.5 7 3.48 54 Western Australia.86 57.4 4 4 35 South Australia.8 64 68.8 8 3. 93 7.55 8 66.8 86 3.7 75 Table A5.: Pedestrian age grouping by state Victoria State Queensland Western Australia South Australia N % N % N % N % N % Age group Unknown.75.. 8.86 4 5.5 3.64-5 years 3 3.3 3.7 3 8.57 4 4.3 4.36 6-4 years 7 7.53 7.96.86.. 5 5.45 5-9 years 5 5.38.85 3 8.57 6 6.45 5 5.45-5 years 7 7.53 3.7...8 3.64 6-9 years 6 6.45 4 7.4 5.7.5 4 5.9 3-39 years.9 7.96 5 4.9 8 8.6 3.64 4-49 years.83 3 5.56 6 7.4 8 9.35 38 3.8 5-59 years 8 9.35 4 7.4 7 4 5.8 53 9.7 6+ years 4 5.5 4 44.44.. 6 7. 54 9.64 93 54 35 93 75

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 35 8.4 8 8.6 43 Queensland 4 7 6 3 Western Australia 5 6.5 3 37.5 8 South Australia 3 9.86 7.4 4 67 78.8 8.8 85 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 7 79.4 7.59 34 Killed or seriously injured 77.78 6. 7 48 78.69 3.3 6

APPENDIX 6 BICYCLE AND MOTORCYCLE CRASH CHARACTERISTICS CRASHES DURING -4

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 3 8.57 5.7 3 85.7 35 Queensland 5. 44 88. 5 Western Australia 7.4.. 3 9.86 4 South Australia 3.33 3.33 73.33 5 9.65 5 4.39 98 85.96 4 Age Table A6.: Motorcyclist age grouping by state State Victoria Queensland Western Australia South Australia N % N % N % N % N % Age group Unknown 5 4.9 6. 4.9 3 6 4.4 6-4 years.... 4.9...75 5-9 years 3 8.57. 3.43 6.67 8 7. -5 years.86 4 8. 4 8.57 4 6.67 3.8 6-9 years 7 6. 4.9 6.67 6 4.4 3-39 years 3 8.57 6. 7.4 6.67 9.65 4-49 years 8.86... 4 6.67 3.8 5-59 years 8.86 3 6..... 9.65 6+ years.. 3 6... 6.67 4 3.5 35 5 4 5 4

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) 9 9.9 Vehicles from opposing directions 6 6.6 Vehicles from same direction. Manoeuvring 3 3.3 Overtaking 3 3.3 On path. Off path on straight 6 6.6 99 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 7 58.6 4.38 9 Queensland 3 6.5 8 37.5 48 Western Australia 9 69.3 4 3.77 3 South Australia 7 63.64 4 36.36 63 6.38 38 37.6

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 3 77.5 9.5 4 Killed or seriously injured 3 3.8 76.9 3 34 64.5 9 35.85 53 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. 7 63.64 4 36.36 Vehicles from adjacent directions (intersections only) 63.6 7 36.84 9 Vehicles from opposing directions 75. 4 5. 6 Vehicles from same direction 3 65. 7 35. Manoeuvring 7 58.6 4.38 9 Overtaking 66.67 33.33 3 On path.. Off path on straight.. 63 6.38 38 37.6