TY - JOUR
T1 - Contributing factors to motorcycle injury crashes in Victoria, Australia
AU - Allen, T.
AU - Newstead, S.
AU - Lenne, M. G.
AU - McClure, R.
AU - Hillard, P.
AU - Symmons, M.
AU - Day, L.
PY - 2017
Y1 - 2017
N2 - Introduction The increased popularity of powered two wheelers (PTWs) in Australia, combined with their vulnerability in the event of a crash, necessitates new strategies to prevent serious injury crashes. The purpose of this study was to use case-series data collected from a recent motorcycle case-control study to analyse contributing factors to crashes using a safe systems approach. Methods A total of 235 injured riders were recruited and completed a questionnaire-based interview, each followed by a detailed inspection of the case motorcycle and crash site by a trained crash investigator. Primary and secondary contributors to the crash were judged based on all available information sources. Analysis of the most frequent contributing factors included separation of cases into single and multi-vehicle crashes. A stepwise logistic regression was used to test for factors associated with human error for multi-vehicle crashes. Results Two thirds of crashes investigated involved another vehicle or road user(s). For multi-vehicle crashes the most common crash scenario involved another vehicle failing to give way to the rider, and the primary contributor was a perception failure or traffic scan error on the part of the other road user. A number of secondary factors were found to be significantly associated with human error type (other road user or rider error), including rider age, traffic density, inappropriate speed of the PTW, and a road design issue. For single vehicle crashes, the most common primary contributor was a misjudgement or control error on the part of the rider, with inappropriate speed as the most frequent secondary contributor. Conclusions Despite the complexity of factors involved in PTW crashes resulting in injury, a number of significant associations exist between road users as the primary contributing factor (rider or other road user) and secondary factors, including rider age, traffic density, speed and road design issues.
AB - Introduction The increased popularity of powered two wheelers (PTWs) in Australia, combined with their vulnerability in the event of a crash, necessitates new strategies to prevent serious injury crashes. The purpose of this study was to use case-series data collected from a recent motorcycle case-control study to analyse contributing factors to crashes using a safe systems approach. Methods A total of 235 injured riders were recruited and completed a questionnaire-based interview, each followed by a detailed inspection of the case motorcycle and crash site by a trained crash investigator. Primary and secondary contributors to the crash were judged based on all available information sources. Analysis of the most frequent contributing factors included separation of cases into single and multi-vehicle crashes. A stepwise logistic regression was used to test for factors associated with human error for multi-vehicle crashes. Results Two thirds of crashes investigated involved another vehicle or road user(s). For multi-vehicle crashes the most common crash scenario involved another vehicle failing to give way to the rider, and the primary contributor was a perception failure or traffic scan error on the part of the other road user. A number of secondary factors were found to be significantly associated with human error type (other road user or rider error), including rider age, traffic density, inappropriate speed of the PTW, and a road design issue. For single vehicle crashes, the most common primary contributor was a misjudgement or control error on the part of the rider, with inappropriate speed as the most frequent secondary contributor. Conclusions Despite the complexity of factors involved in PTW crashes resulting in injury, a number of significant associations exist between road users as the primary contributing factor (rider or other road user) and secondary factors, including rider age, traffic density, speed and road design issues.
UR - https://hdl.handle.net/1959.7/uws:72879
U2 - 10.1016/j.trf.2016.11.003
DO - 10.1016/j.trf.2016.11.003
M3 - Article
SN - 1873-5517
SN - 1369-8478
VL - 45
SP - 157
EP - 168
JO - Transportation Research Part F: Traffic Psychology and Behaviour
JF - Transportation Research Part F: Traffic Psychology and Behaviour
ER -