Repeat speeding offenders from an Australian perspective Dr Judy Fleiter Road Safety Network: CIHR Team inTransdisciplinary Studies in DWI Onset, Persistence, Prevention and Treatment, Douglas Mental Health University Institute, Montreal 2 August 2012

CRICOS No. 00213J

Acknowledgements

 Co-researchers – Barry Watson, Vic Siskind, Angela Watson  Australian Research Council – Department of Transport and Main Roads – Queensland Police Service – Office of Economic and Statistical Research  National Health and Medical Research Council Asia-Australia Postdoctoral Research Fellowship

Overview

 Speeding and crash involvement in Australia  Speeding recidivist research in Queensland  Implications for future speed management

Australia = 22.8 million people Queensland = 4.5 million people Land area = 1.7 million km 2 Driver’s licences = 3.1 million Reg.vehicles = 4.3 million

Australia

Brisbane

Australian Road Deaths: Improvements from 1970-2010

30.4 deaths/100,000 people 6.1 deaths/100,000 people With a 2-fold increase in vehicles & 50% growth in population

Improvements in Road Safety in Queensland since 1967

Speed management in Australia

 Strong reliance on traffic law enforcement programs: − traffic laws (eg. speed limits) − traffic policing (eg. speed cameras) − sanctions (eg. fines, demerit points, licence loss)

Speeding enforcement in Queensland

   History: – 1997: – 2003: – 2007: – 2010: – 2011: Mobile speed cameras (highly visible, randomly deployed around selected ‘crash’ sites) Penalties for speeding substantially increased Fixed ‘blackspot’ speed cameras and increase in mobile speed camera sites Covert speed cameras introduced Point-to-point (average) speed cameras operational on 1 section of highway north of Brisbane Policing supported by mass-media education Evaluations of mobile speed cameras indicate: − 34% reduction in fatal crashes within 2km of sites − 42% reduction in serious casualty crashes within 2km Newstead, 2006; Cameron, 2008; Carnis, Rakotonirainy & Fleiter, 2008

Focus of Traffic Policing • The Fatal 4

– Speeding – Drink driving – Fatigue – driving while tired – Non-use of Seatbelts

Percentage of fatalities involving speeding drivers/riders in Queensland: 12 months ending January 2006 -2011 30 25 20 % 15 10 5 0 2006 2007 2008 2009 Year 2010 2011 Queensland Department of Transport and Main Roads, 2011 CRICOS No. 00213J

Percentage of speeding infringements per penalty category, Queensland

60 50 40 30 20 10 0 40,3 < 13 50,7 7,6 1 13-20 21-30 31-40 Km/hour above the speed limit 0,4 40+ Queensland Transport, 2008

Speeding offenders...

• Are they all the same?

• Does increasing penalties make any difference?

• What else do they do?

• What might best change their driving behaviour?

Background to recidivism research project

 In April 2003, Queensland introduced changes to the speeding penalty regime: – Increased monetary fines – Automatic licence suspension for high range speeding (for >40 km/h over the speed limit) – Increased the number of offence bands/categories  The stated rationale for this change was to deter speeding behaviour

Speeding penalty changes

Speeding offences and penalties in Qld prior to 17 April, 2003

Offence

<15 km/hr over speed limit 15-29 km/hr over speed limit 30-44 km/hr over speed limit >44 km/hr over speed limit

Fine

$90 $135 $180 $255

Demerit Points

1 3 4 6

Speeding offences and penalties in Qld from 17 April, 2003

Offence

<13 km/hr over speed limit 13-20 km/hr over speed limit 21-29 km/hr over speed limit 30-40 km/hr over speed limit >40 km/hr over speed limit

Fine

$100 $150 $250 $300 $700

Demerit Points

1 3 4 6 8 + 6 months suspension

The effectiveness of increases in speeding penalties

 Limited international research into effectiveness of different speeding penalties  Increasing speeding penalties severity (in isolation) has been found to produce very few impacts on behaviour in Sweden (1982 & 1987) and Norway (1995-2004)  Need to consider impact of speeding penalties in: – deterring the general population from speeding (

general deterrence

) – reducing recidivism among offenders (

specific deterrence

) Watson

et al

. 2010

Speeding recidivism research

 Our research aimed to:  examine the specific deterrent impact of the changes  profile speeding offenders/recidivists

Method

(1)

 Crash and offence data from 1996 to 2007 obtained for two cohorts of drivers:  58,000 drivers convicted of speeding in May 2001  53,000 drivers convicted of speeding in May 2003  Data obtained included details of: – index offence – previous and subsequent traffic crashes and offences – demographic characteristics – licence type and class

Method

(2)

 Final sample for current analyses excluded interstate and international licence holders: – 2001 pre-penalty change cohort (n = 46,681) – 2003 post-penalty change cohort (n = 42,180)  Speeding offence records for two years after the index offence were examined  Distinction between:  

Absolute

specific deterrence – the total prevention of re-offending

Marginal

specific deterrence – a reduction in re-offending

Measures of recidivism

In the follow up period:

1. Proportion of all offenders detected re-offending

(Absolute specific deterrence)

2. Average number of offences

(Absolute and marginal specific deterrence)

3. Length of delay to re-offence

among re-offenders (Marginal specific deterrence)

4. Average number of re-offences

among re offenders (Marginal specific deterrence) CRICOS No. 00213J

Overall impact of penalty change

Measure of recidivism Hypotheses Outcome

Overall proportion of re-offending in the follow up period Reduction in the proportion who re offend after penalty change  Overall frequency of re-offending in the follow up period Length of delay to re-offence among re-offenders Average number of re-offences committed by those who re offended Reduction in average number of offences committed (overall) after penalty change Among those who re-offend, longer delay to re-offence after penalty change Among those who re-offend, reduction in the average number of re-offences after penalty change    Watson

et al

. 2010

Potential influencing factors – differential effects 1. Index offence severity 2. Offence history

1. Index Offence Severity



Low-range offences:

those from the lowest offence category



High-range offences:

those that were 30km/hr or greater over the speed limit



Mid-range offences:

all other offences

Effects of index offence severity

 Compared to those with mid- and low-range offences, those with

high-range index offence

had a significantly: − greater proportion re-offending; − higher average number of offences; and − higher average number of re-offences.

 No differential effects of penalty change

2. Offence History



Low-range offenders:

no speeding offences prior to index 

High-range offenders:

2 or more speeding offences prior to index, where at least two were 30 km/hr or greater over the speed limit 

Mid-range offenders:

all other offenders

Effects of offence history

 Compared to mid- and low-range offenders,

high-range offenders

had a significantly: −greater proportion re-offending; −higher average number of offences; −fewer days until re-offence; and −higher average number of re-offences.

 No differential effects of penalty change

Potential Confounding Factors 1. Intensity of speed enforcement

– Speed enforcement hours

2. Community perceptions

– Annual community attitudes surveys

3. Driving exposure

– Fuel sales

1. Intensity of speed enforcement

Speed enforcement Measure* 2001 Cohort period May 2001 – April 2003 2003 Cohort period May 2003 – April 2005 Percentage change

Hours of operation 414,699 594,093 43% Number of offences detected 1,170,373 1,121,735 Detection rate 2.82

1.89

* Includes all speed camera and radar based speed enforcement - 4%

2. Community perceptions

 The trend in self-reported exposure (self and others) to speed cameras was stable from 1998 to 2005.

 Reported awareness of penalty changes: – 69% in 2003 (year of change) – 39% in 2004  However, knowledge of the penalty changes varied in terms of accuracy.

Pre-penalty change

3. Driving exposure

Time period May 2001 – April 2003 Litres sold* 4,515,314,862 %change Post-penalty change May 2003 – April 2005 5,902,016,763 30.71% increase *All fuel types sold by fuel retail outlets in Queensland There was an increase in fuel sales from 2001-03 to 2003-05 period. As such, the results obtained in the study would not appear to be due to any reduction in driving exposure.

Speeding recidivists

Speeding recidivist profiling

(1)  Examined demographic characteristics, traffic offence histories and criminal histories of speeding offenders  Compared characteristics and offence histories of low and mid-range offenders with high-range, repeat speeding offenders

Speeding recidivist profiling

(2)  Utilised the data from the speeding penalty change study for the combined 2001 and 2003 cohorts (because no differences on key variables of interest)  Examined five years of traffic offence history, prior to the index speeding offence  Examined lifetime criminal history Watson

et al

. 2009

Speeding recidivist profiling

(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: two or more offences, with at least two being 30 km/hr or more over the speed limit (i.e. high range, repeat offenders)

Breakdown of offenders

(n = 84,468)

High-range 3,7% Low-range 5,8% Mid-range 90,5%

Profiling results

(1)

• Significant differences between

high-range offenders

compared to

low- and mid-range offenders

• Demographics - High-range offenders more likely:

– Male – Younger – Hold Provisional licence – Hold Motorcycle licence

Profiling results

(2)

Traffic History

•

High-range offenders

more likely than

low- and mid-range offenders

to have committed: – Alcohol – Unlicensed driving – Dangerous driving – Seatbelt, and – ‘Other’ traffic offences in the 5 years prior to index offence

Crash history

97% 93.7% 100 90 80 70 60 50 40 30 20 10 0 3% 6.3% 14% 86% Low range Mid range High range

Low-range vs. high-range:



2 (1) = 358.6, p < .001, Mid-range vs. high-range:



2 (1) = 286.2, p < .001,



c

= .21



c

= .06

Crash No Crash

Criminal histories

  1000 offenders selected – 300 random sample of low-range – 300 random sample of mid-range – 400 random sample of high-range Data provided by Queensland Police Service  Overall, 30.5% had at least one criminal offence – 15.9% property (eg. stealing, break and enter) – 14.9% drug offences – 10.2% offences against order (eg. public nuisance) – 7.3% offences against the person (eg. assault) – 7.2% traffic offences (ie. those requiring attendance at court) – 4.6% regulation offences (eg. prostitution, liquor licensing)

Comparison of criminal histories

Low-range offenders

Overall Criminal history Property* Drug* Person* Traffic* Order* Regulation*

7.0%

38.1%

14.3%

14.3%

52.4% 14.3%

4.8% Standardised residuals +/- 1.96 bolded *% of those with criminal history

Mid-range offenders 21.0%

44.4%

36.5%

15.9% 28.6% 28.6%

3.2% High-range offenders 55.2%

44.3%

53.8%

27.1%

19.5% 36.7% 19.5%

Conclusions for recidivism research

 The introduction of more severe speeding penalties in Queensland appears to have had an absolute specific deterrent effect and reduced re-offending in the following two years  However, the change appears to have had little impact on the overall frequency of re-offending among those who did re-offend  Further research into the effectiveness of speeding penalties and sanctions needed

Conclusions for recidivism research

 High-range, repeat speeding offenders appear to be a problematic group of drivers  They are substantially different from low- and mid range offenders on many demographic, traffic and criminal history factors  Need to consider innovative, tailored strategies for reducing recidivism among high-range, repeat offenders

Speed management priorities

(1)

 Reduce opportunities to avoid detection and punishment by: − identifying best mix of automatic and manned enforcement − investigating individuals who accumulate large amount of demerit points (NSW & Victoria) − developing better detection of speeding motorcyclists − implementing innovative strategies like point-to-point (average) enforcement which identifies persistent speeding over longer distances

Speed management priorities

(2)

 Implement and evaluate innovative sanctions for reducing speeding recidivism − vehicle impoundment − intelligent speed adaption (ISA) − behaviour change/rehabilitation programs

Speed management priorities

(3)

 Innovative communication strategies needed to: − challenge perception that speeding is okay and that everyone speeds − address community perceptions of enforcement tolerances − challenge perception that low level speeding is safe − encourage voluntary use of ISA (private and fleet vehicles) − learn from success of others… Fleiter & Watson, 2012

Merci.

Thank you for the opportunity to be here today. Do you have any questions?

[email protected]

Mark your Diaries!

International Council on Alcohol, Drugs and Traffic Safety Conference (ICADTS T2013) August 2013, Brisbane Convention and Exhibition Centre

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Transportation Research Part F: Traffic Psychology and Behaviour, 13, 49-62.

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