Exploring Factors Associated with Cyclist Injury Severity in Vehicle-Electric Bicycle Crashes Based on a Random Parameter Logit Model

Electric bicyclists are vulnerable road users and play an important role in traffic safety. The focus of this research is on analyzing cyclists’ injury severity vehicle-electric bicycle collisions. It exploratory analysis that was conducted based samples obtained from video data provided by the police Xi’an China. Three types include fatal, injury, property-damage-only (PDO). A random parameter logit (RPL) model specified to gain more insights into factors related level, including human behaviors, vehicle characteristics, roadway attributes, environmental conditions. Some not included previous were introduced study, especially precrash behaviors drivers cyclists. direct pseudo-elasticity effects variables compared investigate stability individual estimates categories. results indicated significantly increment probability fatal accidents as follows: driver violation (speeding, red-light violation, driving opposite direction), cyclist violation), day time (nighttime), visibility restrictions (fixed obstacles), type (larger bus, small truck, larger truck). Based these findings, we suggested measures such strengthening law enforcement installing cameras, implementing zero tolerance for violations, promoting education completing training courses cyclists, enhancing safety awareness through educational activities. can provide a theoretical basis formulating strategies improve