the crash and offence involvement of speeding offenders
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The crash and offence involvement of speeding offenders. Barry Watson Presentation to “Under the Radar” Traffic Offenders Conference 7 December 2011. CRICOS No. 00213J. Acknowledgements. ARC Linkage project partners: Queensland Department of Transport & Main Roads Queensland Police Service - PowerPoint PPT PresentationTRANSCRIPT
The crash and offence involvement of speeding offenders
Barry WatsonPresentation to “Under the Radar” Traffic Offenders Conference7 December 2011
CRICOS No. 00213J
AcknowledgementsARC Linkage project partners:
– Queensland Department of Transport & Main Roads
– Queensland Police Service
– Office of Economic & Statistical Research
CARRS-Q research team:– Adjunct Professor Vic Siskind
– Dr Judy Fleiter
– Angela Watson
– David Soole
Overview The role of speeding in crashes and
contributing factors to the behaviour The need to better understand speeding
offenders Characteristics of low-range, mid-range and
high-range offenders Links to other offending behaviour Implications for speed management policies
and practices
CRICOS No. 00213J
The speeding problem in Australia As in other countries, speeding is a major factor
contributing to road crashes in Australia Speeding is estimated to contribute to
approximately 25% of all fatalities Australia-wide Research indicates that speeding increases both
the incidence and severity of crashes Speeding is over-represented in:
− more severe crashes− crashes involving high-risk groups such as young
drivers, motorcycle riders, unlicensed drivers
CRICOS No. 00213J
Speed management in Australia Over the last 20 years, Australian jurisdictions
have adopted a ‘holistic’ approach to reducing speeding involving:– Road environment improvements (e.g. lower urban
speed limits, road treatments)
– Enforcement programs (e.g. traffic patrols, fixed & mobile speed cameras, point-to-point cameras)
– Education programs (e.g. mass media education)
– Intelligent Transport System (ITS) measures (e.g. vehicle activated and variable message signs)
Speeding offenders Historically, speeding drivers have been
considered a homogenous group In comparison to drink driving, there has
been little research focus on:– identifying the characteristics of high-range or
recidivist speeding offenders– better understanding the motivations of these
drivers– tailoring countermeasures to address this
group
Recidivist drink drivers (1)
International concern about recidivist drink drivers Strong relationship between repeat offending and
high-range BACs Not a homogenous group, but are more likely that
general drivers to:– consume greater amounts of alcohol, experience
alcohol-related problems and be alcohol-dependent– exhibit antisocial and deviant tendencies, aggression,
hostility, thrill-seeking– to have poor driving histories, to use drugs and a have
criminal history
Recidivist drink drivers (2)
These findings are consistent with the road safety maxim that: “people drive as they live”
Recidivist drink drivers appear resistant to traditional drink driving countermeasures
This has prompted the development of tailored countermeasures and sanctions such as:- Heavy fines and lengthy suspension periods- Rehabilitation programs- Alcohol ignition interlocks- Vehicle immobilisation, impoundment or forfeiture
Aim of the study
To inform the design and implementation of speeding countermeasures by: – examining the demographic characteristics and
traffic histories of speeding offenders– comparing the crash and offence histories of
low and mid-range offenders with high-range speeding offenders
– exploring potential predictors of high-range speeding offenders
Method (1)
The data was drawn from a larger study designed to evaluate the impact of speeding penalty changes
Traffic offence data from 1996 to 2007 was obtained for two cohorts of drivers: those convicted of speeding in May 2001 and May 2003
Data obtained included details of:– index offence– previous and subsequent traffic offences– demographic characteristics– licence type and class
Method (2)
Cases that were excluded from the analyses included:– Offenders not holding a Queensland licence, since
demographic and offence history data was missing
– Offenders with missing licence information (3.7%)
– Speed camera offences not attributed to individuals, but companies
There were no statistical differences between the two cohorts of offenders on key variables, so they were combined
Method (3)
Three classifications of offenders were determined ‘a priori’– Low-range: one offence less than 15km/hr over speed
limit during study timeframe– Mid-range: at least one offence more than 15km/hr over
the speed limit– High-range: 2 or more offences, with at least two being
30 km/hr or more over the speed limit
Due to the large sample size a more stringent alpha rate of .001 was selected and effect sizes examined
Low-range5.8%
Mid-range90.5%
High-range3.7%
Figure 1: Breakdown of offenders(n = 84,468)
Low-range Mid-range High-range
50.5%
65.1%
90.2%
49.5%
34.9%
9.8%
Male
Female
Low-range vs. high-range: 2 (1) = 1333.7, p < .001, c= .41Mid-range vs. high-range: 2 (1) = 840.4, p < .001, c= .10
Figure 2: Gender of offenders
Low-range Mid-range High-range
9.4%17.2%
40.5% 17 - 2425 - 2930 - 3940 - 4950 - 5960+
Low-range vs. high-range: 2 (6) = 2166.9, p < .001, c= .35Mid-range vs. high-range: 2 (6) = 1721.1, p < .001, c= .10
Figure 3: Age of offenders
Low-range Mid-range High-range
3.4% 4.1% 6.1%4.9% 9.4%
29.1%
91.7%86.5%
64.8%
Learner
Provisional
Open
Low-range vs. high-range: 2 (2) = 980.2, p < .001, c= .35Mid-range vs. high-range: 2 (2) = 1334.2, p < .001, c= .13
Figure 4: Offenders’ licence status
Low-range Mid-range High-range
70.4%64.8%
54.6%
18.5% 24.1%
38.5% Car only
Motorcycle
HV only
Car + HV
Low-range vs. high-range: 2 (3) = 430.7, p < .001, c= .23Mid-range vs. high-range: 2 (3) = 364.2, p < .001, c= .07
Figure 5: Offenders’ licence class
Low-range Mid-range High-range
1.4% 4.3%11.4%
98.6% 95.7%88.6%
Yes No
Low-range vs. high-range: 2 (1) = 376.9, p < .001, c= .22Mid-range vs. high-range: 2 (1) = 346.3, p < .001, c= .07
Figure 6: Drink driving offence history
Low-range Mid-range High-range
0.0% 1.4%8.3%
100.0% 98.6%91.7%
Yes No
Low-range vs. high-range: 2 (1) = 417.8, p < .001, c= .23Mid-range vs. high-range: 2 (1) = 876.3, p < .001, c= .11
Figure 7: Unlicensed driving offence history
Low-range Mid-range High-range
0.0% 3.4%9.0%
100.0% 96.6%91.0%
Yes No
Low-range vs. high-range: 2 (1) = 454.8, p < .001, c= .51Mid-range vs. high-range: 2 (1) = 271.8, p < .001, c= .06
Figure 8: Seat belt offence history
Low-range Mid-range High-range
0.0%
13.6%
36.5%
100.0%
86.4%
63.5%
Yes No
Low-range vs. high-range: 2 (1) = 2082.9, p < .001, c= .51Mid-range vs. high-range: 2 (1) = 1265.8, p < .001, c= .13
Figure 9: Other offence history
Figure10: Crash history
Low range Mid range High range0
102030405060708090
100
3% 6.3%14%
97% 93.7%86%
CrashNo Crash
Low-range vs. high-range: 2 (1) = 358.6, p < .001, c= .21Mid-range vs. high-range: 2 (1) = 286.2, p < .001, c= .06
Figure11: Vehicle type in crashes
Low range Mid range High range0
102030405060708090
100 90.5% 90.5% 91.7%
1.5% 4% 6%8% 5.5% 2.3%
CarMotorcycleHeavy vehicle
Low-range vs. high-range: 2 (1) = 13.7, p < .001, c= .16Mid-range vs. high-range: 2 (1) = 11.8, p = .003, c= .05
Figure13: Most at fault in crashes
Low range Mid range High range0
10
20
30
40
50
60
70
35.6%
47.3%
52.5%
64.4%
52.7%47.5%
Most at faultNot most at fault
Low-range vs. high-range: 2 (1) = 8.9, p = .003, c= .15Mid-range vs. high-range: 2 (1) = 3.0, p = .081, c= .03
Limitations Relied on data collected for administrative
purposes that can be incorrectly recorded or incomplete
The criteria for determining low, mid and high-range offending was somewhat arbitrary
Different classification of offenders may produce a different pattern of results
Implications for road safety (1)
Repeat, high-range speeding offenders are more likely to be male, younger, provisional licence holders and motorcycle riders
There is an association between repeat, high-range speeding and an increased involvement in crashes and other offences
Repeat, high-range speeding offenders appear to be a particularly problematic group of drivers
Mid-range speeding offenders also have an elevated involvement in offences and crashes
Implications for road safety (2)
Need to refine existing speed management strategies and consider tailored sanctions for repeat, high-range speeding offenders:− vehicle impoundment
− intelligent speed adaption (ISA)
− ongoing enhancement of rehabilitation programs The effectiveness of increased fines for repeat,
high-range offenders remains unclear Additional sanctions may also be warranted for
mid-range offenders
Implications for road safety (3)
Further research is required into:– the impact of current speed enforcement
practices and sanctions on the behaviour of mid-range and high-range offenders
– strategies to enhance the detection of speeding offenders (eg. point-to-point speed enforcement)
– the psychological and social factors contributing to speeding recidivism to inform public education and offender management programs
Mark your Diaries!
International Council on Alcohol, Drugs and Traffic Safety Conference (T2013)
25-28 August 2013, Brisbane