Using GPS Probe Speed Data to Estimate the Attribution of Speeding on Casualty Crashes: A Case Study in Queensland

Author:

Soole David1,O'Hern Steve2,Cameron Max3,Peiris Sujanie3,Newstead Stuart3ORCID,Anderson Warren1,Smith Tracey1

Affiliation:

1. Department of Transport and Main Roads – Queensland, Brisbane, Australia

2. Monash University Accident Research Centre, Melbourne, Australia; Transport Research Centre VERNE, Tampere University, Tampere, Finland

3. Monash University Accident Research Centre, Melbourne, Australia

Abstract

While the relationship between vehicle speed and crash risk and severity are well understood, precise quantifications of the attribution of speeding to casualty crashes remains more elusive, due in part to the lack of reliable network-wide speed survey data. A relatively new source of network-wide speed data is Global Positioning System (GPS) probe data. This paper explores the feasibility of using this data, along with existing crash risk estimates, to determine the proportion of casualty crashes attributable to travelling at various speeds above the posted limit on Queensland roads. Findings were generally consistent with other data sources, highlighting the danger associated with high-level speeding (more than 20 km/h over the speed limit), estimating that up to 32.5% of all casualty crashes were attributable to this behaviour. Analyses also showed the risks associated with low-level speeding (1-10km/h over the limit), with up to 19.2% of all casualty crashes estimated to be attributable to such behaviour. The implications of these findings on road safety are discussed. Notwithstanding the limitations of GPS speed probe data, the findings suggest that it represents a promising source of network-wide speed data for estimating the attribution of speeding in casualty crashes. Efforts should be made to improve the reliability of this data by increasing the representativeness of vehicles contributing to the data.

Publisher

Australasian College of Road Safety

Subject

Safety Research,Social Sciences (miscellaneous),Transportation,Safety, Risk, Reliability and Quality

Reference25 articles.

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2. Bessler, S., & Paulin, T. (2013). Literature Study on the State of the Art of Probe Data Systems in Europe. FTW Telecommunications Research Center. https://www.semanticscholar.org/paper/Literature-Study-on-the-State-of-the-Art-of-Probe-Bessler-Paulin/3cf5ef3c2e08b84f0c3a41f890d7704ce356a50c

3. Cameron, M. H. (2013). Use of Kloeden et al’s relative risk curves and confidence limits to estimate crashes attributable to low- and high-level speeding. Journal of the Australasian College of Road Safety, 24(3), 40–52. https://journalofroadsafety.org/article/32960

4. Cameron, M. H. (2015). Estimating crashes attributable to low and high level speeding: Melbourne compared with Perth and urban Queensland. Journal of the Australasian College of Road Safety, 26(3), 19–32. https://journalofroadsafety.org/article/32095

5. Department of Transport and Main Roads – Queensland. (2018). Vehicle Speeds on Queensland Roads – May 2016. Queensland Government.

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