Exploring relationships between microscopic kinetic parameters of tires under normal driving conditions, road characteristics and accident types

• DOI: 10.1016/j.jsr.2021.05.010
• Publication Date: 2021-06-09T12:23:16Z
• Authors: Changjian Zhang; Jie He; Xintong Yan; Ziyang Liu; Yikai Chen; Hao Zhang
• Keywords: Automobile Driving; China; Logistic Models; Emotions; 0502 economics and business; 05 social sciences; 11. Sustainability; Accidents, Traffic; Humans; 3. Good health

Freeway accidents are a leading cause of death in China, which also triggers substantial economic loss and an emotional burden to society. However, the internal mechanism of how microscopic kinetic parameters of vehicles influenced by road characteristics determine the occurrence of different types of accidents has not been explicitly studied. This research aimed to explore the "link role" of tire microscopic kinetic parameters in road characteristic variables and traffic accidents to aid in facilitating the traffic design and management, and thus to prevent traffic accident.A mountain freeway in Zhejiang Province, China was used as the research object and the data used in this paper were obtained through a real-time vehicle experiment. Multiple estimation models, including the standard ordered logit (SOL) model, fixed parameters logit (FPL) model, and random parameters logit (RPL) model were established.The findings show that road characteristics will affect the longitudinal kinetic characteristics of the vehicle and, consequently, map the level of risk of rear-end accidents. Driving compensation effects were also identified in this paper (i.e., the drivers tend to be more cautious in complicated driving circumstances). Another finding relating to the mountain freeway is that different tunnel characteristics (e.g., tunnel entrance and tunnel exit) have different effects on different types of traffic accidents. Practical Applications: The framework proposed in this article can provide new insight for researchers to enlarge the research subjects of both explanatory and outcome variables in accident analysis. Future research could be implemented to consider more driving conditions.