Objective: Traffic deaths involving e-bike (electric bike) riders are increasing in China. This study aims to quantitatively investigate the association between e-bike rider casualty and impact speed in electric bike-passenger vehicle collisions based on China in-depth accident study data. Methods: According to the collision location and driving direction of the e-bike and the vehicle, electric bike-passenger vehicle collisions are divided into five collision types: frontal collision, e-bike side collision, vehicle side collision, scrape collision and rear-end collision. Since e-bike side collision (the side of e-bike impacted with the front of vehicle) is the leading type and has the highest likelihood of severe or fatal injury in all collision types, e-bike side collisions are further selected to build the casualty risk functions of e-bike rider in relation to the rider age and the impact speed (vehicle impact speed and e-bike impact speed). Results: The analysis results show that, as for e-bike side collisions and e-bike impact speed is 20 km/h, the fatality risk of riders is approximately 2.9% at vehicle impact speed of 30 km/h, 23% at 50 km/h, 50% at 60 km/h, and 90% at 80 km/h. Rider age is also significantly associated with a higher risk of severe and fatality injury. The e-bike impact speed is not significantly associated with the severe and fatality risk in e-bike side collisions. Conclusions: The findings of this study provide meaningful insights to formulate effective policies especially for speed limit management to improve the safety of e-bikes.

Research efforts have been made to understand tunnels’ traffic safety. Most of the previous studies have not considered the different features of tunnels with different ranges of length comprehensively. Generally, three- or four-zone approach has been adopted, with which the entrance and exit parts of a tunnel are considered symmetrical in the safety analysis. This study employs a seven-zone analytic approach for the safety investigation of 18 expressway tunnels with length ranging from 2 to 3 km. The results reveal that the crash rate increases firstly for the entrance zone, then decreases for the midzone and again increases at the exit zone. The high crash rates at the access, entrance, and transition zones are attributed to rear-end crashes. Although single-vehicle crashes take place in the mid and exit zones (1) at the tunnel entrance: failure to maintain safe distance; (2) in the midarea: failure to maintain safe distance, fatigue driving, overspeeding, and improper lane change; and (3) at the tunnel exit: overspeeding and improper lane change mainly contribute to the crash occurrence. Friedman test was performed to test the significance of the contributing factors. The crash occurrence mechanism is discussed for the selected long tunnels. Finally, engineering and policy countermeasures are recommended to improve traffic safety in expressway tunnels.

This study proposes a random parameter bivariate probit model to analyze risk factors on the crash injury severity of both motorcycle riders and passengers in a single modeling framework. The proposed model can not only account for the underlying correlation of common factors affecting the rider and its pillion passenger simultaneously, but also can capture the unobserved heterogeneity across crash samples. The case analysis is based on 3665 motorcycle-carrying-passenger crashes in Hunan province of China. Model comparisons show that the proposed random parameter bivariate probit model outperforms two conventional models in the goodness-of-fit. The results of parameter estimations show that, age and gender differences in passengers pose significant effects on injury severity of the rider in crashes. Specifically, when carrying a vulnerable passenger including women, children and elders, the rider is less likely to sustain severe injuries. But for injury severity of the passenger, these vulnerable passengers are more likely to suffer from severe injuries. Apart form age and gender attributes, factors including collision objects, helmet use, drunk riding, night without lights, peak periods, high-speed roads have significant effects on rider injury and/or passenger injury. Relevant suggestions to alleviate the injury severity for motorcycle-carrying-passengers crashes are recommended.

Motorcycle crashes have been a significant cause of death and serious injury in urban regions, which has a negative effect on the development of sustainable urban transportation. In this study, two logit models, one model for illegal motorcyclist behaviors and the other for crash injury severity, are developed using urban motorcycle crashes in Hunan Province, China. The two developed models could allow us to simultaneously identify significant factors related to specific illegal behaviors and the severity level of crashes. The results show that illegal motorcyclist behaviors, including unlicensed riding, drunk riding, and improper overtaking/lane changes, are more likely to cause serious injuries or death. Young motorcyclists are associated with a higher likelihood of illegal behaviors, while old motorcyclists are associated with a higher likelihood of serious injuries or death. Night conditions without street lights are significantly associated with a higher probability of illegal motorcyclist behaviors as well as higher injury severity. Crashes caused by drunk riding have the highest likelihood of fatal/severe injury. Based on these findings, efficient interventions are recommended to curb illegal motorcyclist behaviors and alleviate crash injury severity.