Issues related to motorcycle safety in China have not received enough research attention. As such, the causal relationship between injury outcomes of motorcycle crashes and potential risk factors remains unknown. This study intended to investigate the injury risk of motorcyclists involved in road traffic crashes in China. To account for the ordinal nature of response outcomes and unobserved heterogeneity, a mixed ordered logit model was employed. Given that the crash occurrence process is different between intersections and non-intersections, separate models were developed for these locations to independently estimate the impacts of various contributing factors on motorcycle riders’ injury severity. The analysis was based on the police-reported crash dataset obtained from the Traffic Administration Bureau of Hunan Provincial Public Security Ministry. Factors associated with a substantially higher probability of fatalities and severe injuries included motorcycle riders older than 60 years, the absence of helmets, motorcycle riders identified to be equal duty, and when a motorcycle collided with a heavy vehicle during the night time without lighting. Crashes occurred along county roads with curve and slope alignment or at regions with higher GDP were associated with an elevated risk of fatality of motorcycle riders, while unsignalized intersections were related to less severe injuries. Findings of this study are beneficial in forming several targeted countermeasures for motorcycle safety in China, including designing roads with appropriate road delineation and street lighting, strict enforcement for speeding and red light violations, promoting helmet usage, and improving the conspicuity of motorcyclists.

In recent years, the proportion of rural road fatalities in the country is gradually increasing, among which the traffic safety problems are particularly prominent in the town-rural area and the town-center area. Based on the relevant accident data in Hunan Province in recent years, the chi-square test was conducted to obtain the correlation degree between each risk factor and accident severity based on gender stratification. Then, a binary logistic model was established to obtain the significant factors that affect the accident severity in the town-rural area and the town-center area, respectively. Based on the significant factors, relevant safety improvement measures were proposed for the key areas. The results show that severe accidents were significantly related to single-vehicle factors, motorcycle factors, and intersections factors in the town-rural area. In the town-center area, severe accidents were significantly related to elderly age, single-vehicle factors, and nighttime factors. The study obtained the risk factors in key areas, which can provide a reference for the improvement of traffic safety in key areas of rural roads, to ensure the safety and sustainability of rural traffic.

The network operation of the subway can reduce the number of passenger transfers and improve subway operation efficiency. Based on the subway smart card data, this paper proposes an optimal design method for the cross-line operation scheme of subway trains. The method firstly calculates the OD matrix between subway stations, the passenger section flow, and the transfer flow according to the passenger smart card data. It then optimizes the design of the subway train cross-line operation plan, including determining the routing type of cross-line operation and the number of trains running. Finally, for the lines with cross-line operation conditions in the urban subway system, we design the cross-line operation schemes under all possible combinations. According to the volume of the cross-line passenger flow that the cross-line trains can carry, the top-ranked operation plans are preferably recommended. Taking the Chengdu subway network as an example, the research results show that, in the Chengdu subway network, the North Railway Station, Xibo City Station, and South Railway Station bear the highest transfer demand. The transfer demands that can be undertaken by cross-line trains are 23,934, 16,710, and 13,024 trips per hour, respectively. This shows that the proposed design method can accurately and reasonably screen out the transfer stations and lines with an urgent need for cross-line trains.