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The crash and offence involvement of speeding offenders

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

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The crash and offence involvement of speeding offenders

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  1. The crash and offence involvement of speeding offenders Barry Watson Presentation to “Under the Radar” Traffic Offenders Conference 7 December 2011 CRICOS No. 00213J

  2. Acknowledgements ARC 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

  3. 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

  4. 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

  5. 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)

  6. 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

  7. 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

  8. 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

  9. 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

  10. 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

  11. 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

  12. 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

  13. Figure 2: Gender of offenders Low-range vs. high-range: 2 (1)= 1333.7, p < .001, c=.41 Mid-range vs. high-range: 2 (1)= 840.4, p < .001, c= .10

  14. Figure 3: Age of offenders Low-range vs. high-range: 2 (6)= 2166.9, p < .001, c=.35 Mid-range vs. high-range: 2 (6)= 1721.1, p < .001, c= .10

  15. Figure 4: Offenders’ licence status Low-range vs. high-range: 2 (2)= 980.2, p < .001, c=.35 Mid-range vs. high-range: 2 (2)= 1334.2, p < .001, c= .13

  16. Figure 5: Offenders’ licence class Low-range vs. high-range: 2 (3)= 430.7, p < .001, c=.23 Mid-range vs. high-range: 2 (3)= 364.2, p < .001, c= .07

  17. Figure 6: Drink driving offence history Low-range vs. high-range: 2 (1)= 376.9, p < .001, c=.22 Mid-range vs. high-range: 2 (1)= 346.3, p < .001, c= .07

  18. Figure 7: Unlicensed driving offence history Low-range vs. high-range: 2 (1)= 417.8, p < .001, c=.23 Mid-range vs. high-range: 2 (1)= 876.3, p < .001, c= .11

  19. Figure 8: Seat belt offence history Low-range vs. high-range: 2 (1)= 454.8, p < .001, c=.51 Mid-range vs. high-range: 2 (1)= 271.8, p < .001, c= .06

  20. Figure 9: Other offence history Low-range vs. high-range: 2 (1)= 2082.9, p < .001, c=.51 Mid-range vs. high-range: 2 (1)= 1265.8, p < .001, c= .13

  21. Figure10: Crash history Low-range vs. high-range: 2 (1)= 358.6, p < .001, c= .21 Mid-range vs. high-range: 2 (1)= 286.2, p < .001, c= .06

  22. Figure11: Vehicle type in crashes Low-range vs. high-range: 2 (1)= 13.7, p < .001, c= .16 Mid-range vs. high-range: 2 (1)= 11.8, p = .003, c= .05

  23. Figure13: Most at fault in crashes Low-range vs. high-range: 2 (1)= 8.9, p = .003, c= .15 Mid-range vs. high-range: 2 (1)= 3.0, p = .081, c= .03

  24. 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

  25. 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

  26. 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

  27. 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

  28. Questions? b.watson@qut.edu.au Mark your Diaries! International Council on Alcohol, Drugs and Traffic Safety Conference (T2013) 25-28 August 2013, Brisbane

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