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Affiliation
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Intelligent Transportation Research Center, Southeast University , Nanjing , 210096 , China. |
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Abstract
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OBJECTIVES: This paper aims to model fault in e-bike fatal crashes in a county-level city in China.
METHOD: Three-year crash data are retrieved from the crash reports (2012-2014) from the Taixing Police Department. A mixed logit models is introduced to explore significant factors associated with fault assignment, as well as accounting for similarity among fault assignment and heterogeneity within unobserved variables.
RESULTS: The modeling results indicate some interesting new findings. First, pre-crash behaviors of both drivers and e-bike riders are found to be significant to fault assignment. Second, bike lane and median types are significantly associated with e-bike rider fault commitment. Third, specific groups of e-bike riders (low-educated and older) and drivers (heavy good vehicles) are more likely to commit faults in e-bike crashes. Last, crash location and built environment have significant correlation with faulty behaviors of e-bike riders.
CONCLUSIONS: Safety countermeasures are proposed including: 1) the deployment of traffic design and control elements including physically-separated bike lanes, medians, video surveillance systems for e-bike riders, and left-turning treatments for non-motorists (e.g. a two-step e-bike left turning); 2) the amendment of the current traffic regulation on drunk e-bike riders and child e-bike passengers; 3) the development of a license system for specific e-bike rider groups (older and low-educated) and a safety campaign for drivers (to increase safety awareness when parking on-street or driving heavy good vehicles). Some interesting future research topics are also suggested: e-bike riders' behaviors at unsignalized intersections and mid-block openings, e-bike safety in suburban area, and an in-depth study of the effect of built environment on e-bike safety.
Language: en |