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Drivers’ risk perception is vital to driving behavior and traffic safety. In the dynamic interaction of a driver-vehicle-environment system, drivers’ risk perception changes dynamically. This study focused on drivers’ risk perception at unsignalized intersections in China and analyzed drivers’ crossing behavior. Based on cognitive psychology theory and an adaptive neuro-fuzzy inference system, quantitative models of drivers’ risk perception were established for the crossing processes between two straight-moving vehicles from the orthogonal direction. The acceptable risk perception levels of drivers were identified using a self-developed data analysis method. Based on game theory, the relationship among the quantitative value of drivers’ risk perception, acceptable risk perception level, and vehicle motion state was analyzed. The models of drivers’ crossing behavior were then established. Finally, the behavior models were validated using data collected from real-world vehicle movements and driver decisions. The results showed that the developed behavior models had both high accuracy and good applicability. This study would provide theoretical and algorithmic references for the microscopic simulation and active safety control system of vehicles.

A large number of road traffic accidents occur each year in China, which results in huge losses to the safety of people’s lives and property. Among all accidents, the accident with over 10 fatalities in one accident is extraordinarily serious, which has immeasurable impact on the security. In this paper, we defined these accidents as serious fatal road traffic accidents (SF-RTAs). The aim of this study was to analyze SF-RTAs in China and its provinces and investigate the causes of SF-RTAs. Firstly, we described and analyzed the annual trend of SF-RTAs based on the data from 1990 to 2014. Then we analyzed region, time and accident type distribution characteristics of SF-RTAs during 2004-2014. Then the main factors influencing SF-RTAs were analyzed by linear regression and decision tree methods. Finally, we proposed corresponding control strategies for preventing SF-RTAs according to the analysis results. It is expected that the findings of this study are useful in indentifying effective prevention measures for serious fatal accidents in China, and protecting human lives and properties.