Bicycle crash statistics revealed that, in 2015, 12 bicyclists died and 107 bicyclists were seriously injured in Victoria. It is necessary to understand the bicyclists’ serious casualty problem in order to reduce the number of fatalities and serious injuries in bicycle-involved crashes on the road network. Although a number of studies have investigated the effects of road, environmental, vehicle and human demographic characteristics on number and severity of bicycle crashes, limited research has been conducted to investigate the effects of these parameters on bicycle fatal and serious injury crashes using random parameter modelling technique. Furthermore, there are very few studies conducted in Australia. This study examined the effects of human demographics, road, environmental and crash characteristics on severity of bicycle crashes in Victoria, Australia. Additionally, this study will compare the results obtained from applying random parameter and fixed parameter binary logistic regression modelling techniques. The road crash information system (RCIS) database is used to develop the models. The levels of the dependent variable were ‘fatal and serious injury’ and ‘non-fatal and serious injury’. The results confirmed that the random parameter binary logit model yielded a better result. Further, the results showed that crash time, bicyclist’s age, helmet use, speed zone, lighting condition, bicyclist’s intent, other road user’s intent and traffic control for other road user’s approach, were the significant variables affecting the severity of bicycle crashes.
|Published - 2017
|Australasian Transport Research Forum 2017 - University of Auckland, Auckland, New Zealand
Duration: 27 Nov 2017 → 29 Nov 2017
Conference number: 39th
|Australasian Transport Research Forum 2017
|27/11/17 → 29/11/17