VicRoads: Graduated Licensing for Motocyclist. A Discussion Paper (corrected 2011)

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Factors Associated with Motorcycle Crashes in New South Wales, Australia, 2004 to 2008 Article in Transportation Research Record Journal of the Transportation Research Board ¡ December 2011 DOI: 10.3141/2265-06

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FACTORS ASSOCIATED WITH MOTORCYCLE CRASHES IN NEW SOUTH WALES, AUSTRALIA, 2004-2008 TRB #11-3919 Corresponding Author Liz de Rome Research Fellow The George Institute for Global Health, The University of Sydney PO Box M201 Missenden Road Camperdown NSW 2050 Australia Tel: +61 2 9550 2292 Fax: +61 2 9657 0301 Email: lderome@georgeinstitute.org.au Teresa Senserrick, Ph.D. Deputy Director, Injury Division The George Institute for Global Health, The University of Sydney PO Box M201 Missenden Road Camperdown NSW 2050 Australia Tel: +61 2 9657 0361 Fax: +61 2 9657 0301 Email: tsenserrick@georgeinstitute.org.au Word count Abstract: Text: Tables * 5 Figures * 7 Total:

250 4,065 1250 1750 7065

Submission date 15 November 2010

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ABSTRACT Background This research aimed to identify factors associated with PTW crashes in New South Wales, Australia.

Methods Exploratory analysis was conducted on data from State crash, license and vehicle registration databases for 2004-2008.

Results Over the study period PTW registrations (+39%) and crashes (+17%) increased, but crash (215.9 to 180.9) and fatality crash (5.7 to 3.7) rates per 10,000 registered vehicles decreased.

Forty-one percent of PTW crashes were single-vehicle (SVC), 49% occurred on curves with road surface hazards contributing to 23%. SVCs accounted for 43% of all PTW fatalities.

Other vehicle drivers were deemed at-fault in 62% of multi-vehicle crashes, including 71% at intersections. T-junctions were the site of 30% of all MVCs. Riders were most likely to be atfault in rear-end (62%) and head-on (82%) crashes (82%). The majority of head-on crashes were not over-taking (69%) and of these 83% occurred on curves.

Supersports models had the highest crash rate per 10,000 registered motorcycles (284.6). Young riders were over-represented in crashes (9% registrations, 28% crashes) and unlicensed riders in fatal crashes (7% crashes, 26% fatal crashes). Unlicensed riders represented 41% of casualties not wearing helmets and 26% of all riders with illegal alcohol concentration.

Conclusion While PTW crash rates showed an encouraging decline, countermeasures are needed to protect the increasing numbers of riders. The analysis identified head-on, rear-end and intersection crashes as specific crash risk patterns to be targeted in education and training for riders and drivers, road treatments in high-risk locations, and interventions to address high-risk unlicensed riding.

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INTRODUCTION Motorcycle and scooter riders represent an increasing proportion of road traffic casualties around the world. This is due to a resurgence of riding of powered two-wheelers (PTWs) in high income countries and the increased motorization of low to middle income countries.(1-2) As vulnerable road users, riders of PTWs have high rates of serious injury and fatality.(3) Strategies to reduce the crash and injury risk of PTWs depend on the accurate identification of causes and risk patterns, including demographic and behavioral factors and exposure. Commonly used measures of exposure for PTWs include the numbers of licensed riders, vehicle kilometers/miles travelled and registered vehicles.(4) In New South Wales (NSW) registered vehicle counts have relatively low error and, while imperfect, are the best measure of exposure currently available. The age and gender of the registering owner is collected as part of the vehicle registration process in NSW, thus allowing for population based studies. The crash database, which is compiled from police crash reports, provides substantial detail on factors associated with reported crashes and controllers involved; therefore allowing exploration by a range of crash factors including crash severity, types of vehicles involved and contributing factors including road environment and road user behaviour.

It is also able to be linked to vehicle registration and license databases, allowing exploration by license status. Together these datasets offered a valuable opportunity to explore PTW crash factors in-depth based on routinely collected data by State authorities.

The objective of this research was to identify key risk factors for motorized two-wheel vehicle crashes and severity of crash in NSW during the five-year period 2004-2008, including rates and proportions by demographics, crash factors and behavioral factors.

METHODS Data Source and Variables Data for 2004-2008 were obtained from NSW State crash and registrations databases. Policereported crashes include those on public roads involving at least one moving vehicle, where any person is killed or injured or a vehicle is towed away.(5) The key vehicle is generally defined as the one considered to have played the major role in the crash.(6) This variable was utilised as a ‘best available’ proxy for at-fault status, acknowledging that this is not the intended use by RTA and in a small (unknown) number of scenarios the controller of the vehicle may not have been atfault.

Variables include demographic details (age, gender, license status of rider), crash severity (injury, fatality), number of vehicles (single/multi), vehicle type, at-fault status, crash type (e.g., overtaking, head-on), road type (intersection, speed zone), hazards (e.g., potholes), alignment (curved or straight), and behavioral factors (helmet, speeding, alcohol, rider/driver error). Age was coded into previously identified motorcycle crash risk groups: 17-25 (young riders), 26-39 and 40+ years.(7) NSW has a four-stage graduated licensing system for riders.(8) Applicants (16 years 9 months+) complete a two-day learn-to-ride course to obtain a learner license. They progress to a first intermediate license by completing a one-day riding course and operational skills test (minimum age 17). After 12 months they progress to a second intermediate license and after a further 24 months to full licensure. Learner and intermediate riders are subject to restrictions including motorcycle size and maximum speeds. Helmets are mandatory for all Australian riders.

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Common speed zones in NSW range from 30 to 110 km/h (18.6-68.4 mph) in 10 km (6.2 miles) increments. These were grouped into four categories: up to 50 (residential areas), 60 (main collector roads), 70-90 (divided roads, arterials) and 100+ km/h (highways, motorways).

PTWs in the registration database were classified into 9 vehicle types (see Table 2) based on make, model and engine displacement in cubic centimeters(cc).

Analyses Crash data was obtained in MS Access 2007 and registration data in MS Excel 2007. Files were linked using MS Access 2007 and descriptive analysis conducted using MS Excel 2007. A range of analyses were selected to feature differing crash associations with demographics, crash factors and behavioral factors. First the overall pattern of crashes from 2004 to 2008 were explored by number and percentage change over time and rates per 10,000 registered PTWs, including by age group, speed zone, alcohol (illegal BAC ≼ 0.05g/100mL). Second, crashes and crash rates by PTW type were calculated for 2008. Finally a range of factors by number, proportion and rate for 2004-2008 collectively were determined: single/multi-vehicle crashes, including by key vehicle, road alignment and crash type, rider/driver error, vehicle type, age group, road type; road type by license status and age group, including a focus on young riders and unlicensed riders.

RESULTS Crash patterns by year, 2004-2008 Crash and injury outcomes From 2004-2008 there were 12,257 crashes involving PTWs in NSW, including 305 fatal crashes. Over that period PTW registrations increased by 36% and the number of PTW crashes increased by 17% (Table 1), but the crash rate per 10,000 registered PTWs showed decreases for all crashes, injury and fatal crashes (Figure 1).

TABLE 1 Number of crashes involving PTWs and percentage over five-years in NSW, 2004-2008 Severity of crash Fatal Injury Non-casualty (tow away) Total

2004 n 60 2002 211 2273

2005 n 63 2019 216 2298

2006 n 66 2258 214 2538

2007 n 62 2196 239 2497

2008 n 54 2372 225 2651

% Change 2004-2008 -10 +18 +7 +17

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Crashes 250.0

211.0

Injury crashes

Fatal crashes

202.7

200.0 150.0 100.0

185.8

187.0

180.9

164.5

161.8

184.0

178.1

5.6

20.0 18.0 16.0 14.0 12.0 10.0 8.0 6.0 4.0 2.0 0.0

206.8

5.6

5.4

4.6

3.7

50.0 0.0 2004

2005

2006

2007

2008

FIGURE 1 Crash rates per 10,000 registered PTWs in NSW, 2004-2008 Age of Riders The average age of PTW riders in 2008 was 43 years. The number of registered owners aged 40+ increased by over 28,000 since 2004, whereas the number aged 26-39 increased by less than 8,000 and those aged 17-25 by only 2,189. By 2008, riders aged 40+ represented 57% of all registrations (Figure 2).

Under 26

26‐39

40+

Total registered PTWs

100%

146,583 133,512

90% 80% 70%

140,000

122,700 107,726

60%

113,388

120,000 57%

55%

54%

53%

51%

50% 33%

32%

32%

31%

30%

30% 10%

100,000 80,000

40% 20%

160,000

60,000 40,000

9%

9%

9%

8%

8%

20,000

0%

0 2004

2005

2006

2007

2008

FIGURE 2 Age of registered owners of PTWs in NSW, 2004-2008 Crash Rates by Age Group Despite overall decreases, crash rate for young riders remained much higher than for older groups. Riders aged 17-25 were involved in 28% of reported crashes over the five years. In 2008

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they had 606 crashes per 10,000 registered vehicles, compared to 211 crashes for riders aged 2639 and 115 crashes for those aged 40+. Figure 3 illustrates crash rates by age group.

17�25 684

673

26�39

40+

681 617

251

249

238 119

2004

116

2005

606

226 118

2006

211 113

2007

115

2008

FIGURE 3 Crash rate per 10,000 registered owners by age group in NSW, 2004-2008 Speed Zone Most PTW crashes (69%) occurred on roads zoned 60 km/h or less (37.3mph). Only 12% occurred in 100+ km/h (62.1mph) zones. A lower proportion (43%) of fatal PTW crashes occurred in areas zoned 60 km/h or less while 25% occurred in areas zoned 100+ km/h. The small numbers involved (~60 per year) meant no trends could be identified.

Alcohol Over 2004-2008, 3.2% of PTW crashes involved a rider with an illegal BAC compared to 2.4% of all vehicle crashes. Crashes where the rider had an illegal BAC accounted for 16.3% of all fatal PTW crashes, compared with 13.0% of all vehicle controllers in fatal crashes. When alcohol was involved in an PTW crash it was more likely to be the rider (4.7%) than other driver (0.5%) who had the illegal BAC. PTW vehicle class Sufficient information was available to classify 79% of the PTWs in reported crashes and 80% of PTWs in the 2008 registration database (Table 2). Whereas the average crash rate per 10,000 registered PTWs was183.9, this varied by class of PTW. The highest crash rates were for supersport (284.6) and scooters (262.4) followed by sport/unclad (247.8) and standard (247.0) motorcycles. Supersport were substantially over represented in fatal crashes (30.4%) but their fatal crash rate was comparable to that of dual purpose PTWs (9.62 vs 9.30).

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TABLE 2 Crash rate by classification of PTW using number of crashes per 10,000 registered PTWs in each classification, NSW, 2008 Crashed n

All crashes %

Registered n

%

All crash rate per 10,000

Supersport Scooter Sport/unclad Standard Sport/Touring Dual purpose Cruiser/custom Touring

503 205 337 219 221 47 257 115

(18.7) (7.6) (12.5) (8.1) (8.2) (1.7) (9.5) (4.3)

17675 7813 13601 8865 10995 3227 19522 11214

(12.1) (5.3) (9.3) (6.0) (7.5) (2.2) (13.3) (7.7)

284.6 262.4 247.8 247.0 201.0 145.6 131.6 102.6

Off road Other/Unclassified Grand Total

189 602 2695

(7.0) (21.0)

23586 30085

(16.1) (20.5)

80.1 200.1 183.9

Single and Multi-Vehicle Crashes Key Vehicle Crashes were categorised to distinguish between single-vehicle crashes (SVC) (41%) and multivehicle collisions (MVC) according to the key vehicle being either the rider (23%) or other driver (35%) (Figure 4).

Other driver key vehicle (n=935), Single vehicle 35% (n=1096), 41% Rider key vehicle (n=620), 23%

FIGURE 4 Key vehicle by crash category in NSW, 2004-2008

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The distribution of crash types as in Figure 4 is similar within PTW classifications, although scooters were more likely to be in MVCs due to the other vehicle and dual purpose bikes were more likely to have SVCs. TABLE 3 Crashes by vehicle classification and crash category, NSW, 2004-2008 Crash category** Supersport Scooter Sport/unclad Standard Sport/Touring Dual purpose Cruiser/custom Touring Off road Other*** Unclassified Total

SVC

874 189 420 461 404 91 475 127 410 51 1472 4974

39% 27% 39% 35% 39% 48% 41% 40% 42% 38% 45% 40%

MVC – Other driver key vehicle 849 366 427 569 408 68 452 120 383 40 977 4659

38% 52% 40% 43% 40% 36% 39% 38% 39% 30% 30% 37%

MVC – Rider key vehicle 535 146 226 304 218 31 222 73 189 42 844 2830

*Model details were available to classify an average of 74% of motorcycles involved in crashes 2004-2008

24% 21% 21% 23% 21% 16% 19% 23% 19% 32% 26% 23%

All crashes* 2258 701 1073 1334 1030 190 1149 320 982 133 3293 12463

** Crash category - SVC - Single Vehicle Crash, MVC Multi-Vehicle Crash ***Other category includes mopeds, mini-bikes, mobility vehicles, ATVs and other small classes and special usage vehicles.

Single-Vehicle Crash (SVC) Factors SVCs accounted for over two-fifths (43%) of all PTW rider and pillion fatalities. SVCs were almost equally likely to have occurred on curved as on straight road sections (49% vs. 51%), but most fatal SVCs (75%) occurred on curves.

Excessive speed for the conditions was identified as a contributing factor in almost half of all SVCs (Table 4). Road surface hazards, such as potholes, diesel or loose gravel on a sealed surface, were a contributing factor in almost one-fifth of these crashes. Such hazards were more commonly associated with crashes on curves than straight sections (23% vs 14%) and were a contributing factor in 10% of fatal crashes on curves. Animals on the road were identified as a contributing factor in a further 6% of SVCs. TABLE 4 Proportion of factors involved in single-vehicle crashes by road alignment in NSW, 2004-2008 (%) All single-vehicle crashes Excess speed for conditions Fatigue Road surface hazard Animal on the road 17-25 years Over 40 years

All crashes (n=4975) 100 48 15 18 6 26 36

On curves (n=2431) 49 84 12 23 3 23 40

On straight roads (n=2543) 51 13 17 14 9 29 32

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Multi-Vehicle Crash Factors The proportion of multi-vehicle PTW crashes remained constant from 2004-2008. Overall, the other driver was the key vehicle in 61% of all MVCs. Riders were most likely to play the major role in rear-end and head-on crashes. The PTW was the key vehicle in 62% of all rear-end PTW crashes (n= 1,326), which comprised 29% of all multi-vehicle crashes where a PTW was the key vehicle.

The PTW was also the key vehicle in 82% of all head-on crashes (n=630), including 88% of overtaking crashes (n=197) and 62% of not-overtaking crashes (n=433). The majority (83%) of head-on (not-overtaking) crashes occurred on curves. Figure 5 illustrates the types of crashes where the rider played the major role compared to the other driver.

Rider Other Vehicle door Rear‐end Pedestrian Overtaking Manoeuvring Loss control Lane‐change Intersection Head‐on Entering traffic

Other Driver

2% 0% 0% 1% 0% 1% 1% 0%

2% 3% 0%

29%

11%

7% 6% 8%

13% 10% 19% 15% 12%

48%

10% 10%

20%

30%

40%

50%

60%

.

FIGURE 5 At-fault vehicle in multi-vehicle collisions in NSW, 2004-2008 The most common errors by the other driver were failure to see or give way at an intersection (48%), changing lanes (19%) and entering traffic (10%). Collisions with heavy vehicles such as trucks comprised 4% of MVCs, but 18% of fatal MVCs. Crashes involving light trucks were more frequent (10%) and included 19% of fatal MVCs. By comparison, collisions with cars were far more common (79%), but accounted for a comparatively lower proportion of fatal collisions (59%).

Age Group Differences Young riders were more likely to be involved in MVC (63%) than SVC whereas just over half (54%) of crashes for 40+ riders were MVC. In addition, although the other driver was generally more likely to be the key vehicle (62%), young riders were more likely than older riders (42% vs. 34%) to be at-fault.

Intersection Crashes Over half (56%) of all MVCs occurred at intersections. PTWs were the key vehicle in 39% of all MVCs but only 30% of those at intersection. The other driver was the key vehicle in 70% of intersection crashes. Responsibility for non-intersection crashes was equally likely to be the rider (48%) or other driver (52%).

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Almost one-third (30%) of all PTW MVCs occurred at T-junctions, with the other driver the key vehicle in 70%. Cross roads accounted for 19% and roundabouts only 6% of collisions.

The other vehicle in intersection crashes was most likely to be a car (82%) or light truck (9%).

License Status Unlicensed riders were more likely to be the key vehicle in both intersection and non-intersection crashes(49% and 69%) than learners (30% and 47%), intermediate (27% and 44%) or fullylicensed (26% and 44%) riders. Riders from other Australian States were more likely than local, NSW-licensed, riders to be the key vehicle in both intersection and non-intersection crashes (Figure 6).

Intersection

80%

Non-Intersection 69%

70%

56%

60% 47%

50% 40% 30%

30%

49%

44%

33% 27%

48%

48%

44%

38% 30%

26%

20% 10% 0% Learner

Intermediate

Standard

Unlicensed Other state

Unknown

Total

FIGURE 6 Proportion of intersection and non-intersection multi-vehicle collisions with rider as key vehicle by license status in NSW, 2004-2008 Age Group On first comparison, the three selected age groups showed similar involvement in intersection crashes, however further division into sub-groups aged 17-20, 21-25, 40-59 and 60+ years revealed a different pattern. The youngest riders were most likely to be at-fault in intersection crashes (Figure 7). Riders aged 17-20 were at-fault in 50% of MVCs, including 42% of intersection and 61% of non-intersection crashes. This compared to 37%, 28% and 47% respectively for those aged 21-25.

Riders aged 60+ were also somewhat more likely to be at-fault in intersection and nonintersection crashes (32% and 50% respectively), although the total number of crashes involving this age group was relatively small (n=227).

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Intersection

Non-intersection

All crashes

61% 50%

47%

50%

46%

43%

42% 37% 28%

40%

36%

33%

28%

32%

23%

Under 21 (n=909)

21-25 (n=1315)

26-39 (n=2837)

40-59 (n=1900)

60+ (n=227)

FIGURE 7 Proportion of riders as key vehicle in intersection, non-intersection and all crashes by age group in NSW, 2004-2008 Crashes by License Status Unlicensed Riders Over half of all unlicensed riders were aged 17-25 (55%). They comprised 7.4% of all PTW crashes but 26% of all riders in fatal crashes. Unlicensed riders were more likely than licensed riders to be at-fault in a MVC (59% vs 34%) and in speed-related crashes (29% vs 23%). Nearly one-fifth (17%) of injured unlicensed riders were unhelmeted (or wearing an incorrectly fastened helmet), and accounted for 41% of all unhelmeted PTW casualties. In 2008, unlicensed riders comprised 26.0% of riders with illegal BAC (17.2% of unlicensed riders compared with 2.6% of licensed riders).

Crashes involving unlicensed riders were more likely than those with licensed riders to involve a pillion casualty (6.2% vs. 4.7%) and their pillion casualties were more likely to be unhelmeted (2.3% vs 0.1%). Unlicensed rider crashes accounted for 9.1% of all pillion casualties and 35.6% of all crashes in which a pillion casualty was not wearing a helmet.

Interstate and Overseas Riders Riders from other Australian or overseas jurisdictions represented 5% of all riders involved in crashes, 55% and were more likely to be at-fault in MVCs than those with NSW licenses (41% vs. 34%); although it must be noted that the large number of ‘unknown’ cases makes this interpretation tentative.

TABLE 5 Proportion of riders in crashes by license status and factors associated with crash in NSW, 2004-2008

All crashes

All riders

Learner

Intermediate

Standard

Unlicensed

(n=12465) 100

(n=1254) 10

(n=977) 8

(n=7038) 56

(n=917) 7

Other Unknown Jurisdiction (n=485) (n=1794) 4 14

DeRome & Senserrick Casualty crashes Fatal crashes MVC*(key vehicle) SVC Fatigue Speed Casualty without helmet Pillion casualty without helmet Pillion casualty Under 26 years Over 40 years

12

100 100 38 40 7 24

10 4 37 39 6 22

8 4 34 33 4 20

56 61 34 39 5 23

7 26 59 42 12 29

4 5 41 55 10 35

15 1 46 44 9 25

3

0

1

0

17

5

9

0 5 28 31

0 1 66 7

0 1 64 2

0 4 13 43

2 6 55 13

1 27 21 42

1 6 29 24

*MVC Multi-vehicle crashes/ SVC SingleVehicle crashes

DISCUSSION Over the study period 2004-2008, PTW registrations and crashes increased in NSW, however, crash, fatality and injury rates per 10,000 registered vehicles showed decreases. The reasons for the relative decline in crash rates has not been established, but may be part of the general decrease in all crashes over that period.(5) Several contributing factors may be speculated but are untested. These include improvements in emergency retrieval and treatment contributing to reduced fatalities,(9) but do not account for the relative reduction in crashes.

Mandatory helmet laws, compulsory rider training and random breath testing have been in place for many years. Educational programs aimed at rider and driver behaviour, together with the increased presence of motorcyclists on the road may be factors. As with the cited benefit of safety in numbers for cyclists,(10) research suggests driver error may be associated with lack of awareness in motorcycle crashes.(11-12) Riders aged 17-25 were the registered owners of only 9% of registered PTWs, but were involved in 28% of reported crashes. They were also more likely to be at-fault in MVCs than 40+ riders, particularly at intersections. While registered owner data does not account for unlicensed riders, there is evidence that registered owners aged 17-25 are likely to be a reasonable estimate of their age group in the rider population in NSW. A recent NSW study found the majority (84%) of learner riders aged 17-25 were the registered owner of their PTW with only 12% riding PTWs registered to another family member.(13) The majority of crashes occurred on roads zoned 60 km/h (37.3mph) or less, suggesting most occurred in predominantly residential areas. The relatively high crash rates for commuter machines such as scooters and standard bikes, is consistent with this and seems likely due to exposure in urban environments, however, travel data was not available.

The proportion of PTW crashes involving alcohol was higher than for all vehicle crashes, with the rider most likely to record the illegal BAC in a MVC. Crashes where the rider had an illegal BAC accounted for 16.3% of all fatal PTW crashes compared to 30% in the US.(14) The relatively lower proportion of motorcycle fatalities associated with alcohol in NSW may be partly attributed to the established random breath testing (RBT) program.(15) Other studies have commented that RBT results demonstrate that very few motorcyclists drink and ride and those that do are more likely to be unlicensed.(16) The 2007 injury rate in NSW is higher than in the US (166.5 vs 144.3) but the fatality rate is lower (4.7 vs 7.3).(14) The latter is likely due to the mandatory helmet requirements and high compliance in Australia.

Analysis of motorcycle crashes by crash type allows recognition of characteristic error patterns associated with different types of crashes which may be obscured when crash types are

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aggregated.(17-19) Their identification is valuable in the development of countermeasures.

PTWs had a much higher incidence of SVCs than has been found for cars (41% vs 24%).(20) While SVCs were equally likely on straight roads as curves, three-quarters of all fatal SVCs occurred on curves. Excessive speed for the conditions may have been a factor in almost half of all SVCs, with road surface hazards contributing to one-fifth, higher on curves and including one-tenth of fatalities on curves. There is evidence that such hazards can be reduced by road remediation programs designed to address hazards specific to motorcycles; such programs have achieved substantial reductions (37%) in rider casualty crashes after adjusting for exposure.(21) Other drivers were deemed at-fault in over 60% of MVCs, with almost half involving failure to see or give way to the rider at an intersection. T-junctions were the most dangerous intersection for PTWs, being the location of almost one-third of all multi-vehicle collisions. By comparison a somewhat smaller proportion of all vehicle crashes (25%) occur at T-junctions and 17% at cross roads, suggesting that this is unlikely to be due to greater exposure to T-junctions than other intersection types.(5) Similar findings in Malaysia have led to the development of specific engineering treatments to reduce such risks for PTWs.(22-23) In addition to SVCs, rider errors resulting in MVCs were more commonly rear-end and head-on (mostly not overtaking) crashes. Recognition of patterns of rider and driver errors can be used to inform countermeasures including advice to riders about appropriate speed, looking ahead, positioning on the road and maintaining crash avoidance space in rider education and licensing materials.(8) Recognition of the contribution of common patterns of driver errors in motorcycle crashes has also led to the inclusion of motorcycle awareness as a topic in driver education and licensing. Similarly the patterns of crash type by class of machine, provides an opportunity to target those specific segments of the rider population. The over representation of supersport models in crashes is consistent with that recently reported in relation to fatal crashes in the US for the same year,(24) however annual fatality rates by class were not computed for this study as the numbers are too small.

Unlicensed riders were substantially over-represented in fatal crashes (26%) despite being only 7% of all riders in crashes. Over half the unlicensed riders were aged between 17-25 years and constituted a substantial proportion of crash involved riders who engaged in high-risk activities: illegal alcohol, speeding and not wearing or incorrectly wearing a helmet. Further work is necessary to identify the factors associated with unlicensed riding, in order to determine ways of enfranchising these riders into the lawful riding community or to more effectively exclude them from the roads.

Limitations The analysis is based on crashes reported to police however due to under reporting of motorcycle crashes, this may only account for approximately 60% of serious crashes.(25) Crash rates based on 10,000 registered vehicles can be confounded by a range of factors such as vehicle kilometers travelled and urban, regional and rural riding environments. This information was not available and it is not possible to determine how the results may differ with their inclusion; however, we are working on a project to establish kilometers travelled from odometer readings recorded at annual registration so that this measure may be able to be applied in the future.

Conclusions and Implications While PTW crash rates showed an encouraging decline, more needs to be done to make motorcycling safer for the increasing proportion of people who choose this type of transport.

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Well known demographic and behavioural risk factors were confirmed including youth and inexperience, motorcycle type, unlicensed riding, excessive speed and alcohol. The analysis also identified risk factors associated with the road environment including relatively low-speed urban areas, T-junctions and road surface hazards on curves.

Specific crash risk patterns were also identified which could provide valuable information to be highlighted in rider and driver education programs. In MVCs, riders were most likely to be at-fault in rear-end and head-on collisions on curves when not overtaking. The other driver was most likely to be at-fault in intersection crashes, lane changing and entering traffic from parking or driveways.

These results indicate a need for further work to be undertaken to improve the safety of the road environment and both rider and driver behaviour. Auditing programs to address road hazards should target high risk areas, particularly curves on high frequency motorcycle routes.

Geo-mapping techniques could be applied to the crash data to identify high-risk locations. The high involvement of unlicensed riders, including non-use of helmets, speeding and alcohol involvement, indicates a need to target these high-risk riders outside of the licensing system.

Effective programs for other drivers to be aware and avoid PTW crashes are also needed.

ACKNOWLEDGMENTS This paper is drawn from the annual report prepared for the Motorcycle Council of NSW (MCC): www.roadsafety.mccofnsw.org.au) to help riders understand and manage their risks.

This paper includes some previously posted results as well as new results and data. We would like to thank the MCC and RTA for making these data available, however this paper does not necessarily reflect the views of either organization. We would also like to thank the National Roads and Motorists’ Association of NSW (NRMA) Motoring and Services Limited who cofund the website and Tom Brandon who assisted in analyzing data. The authors receive funding from a Road Safety Postgraduate Scholarships, NRMA ACT Road Safety Trust (de Rome) and Career Development Award, National Health and Medical Research Council of Australia (Senserrick).

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