Research On Driver-vehicle-road Factors Considered Driving Risk Evaluation Method

Vehicle driving safety is influenced by many factors, including drivers, vehicles, and road environments. The interactions among these factors are quite complex. Existing driving risk evaluation methods mostly only consider limited factors(vehicles nearby mostly) and are based on vehicle kinematics and dynamics. Consequently, it's difficult for them to adapt to increasingly complex traffic environments. To address aforementioned issue, this thesis researches on driver-vehicle-road factors considered driving risk evaluation method.Firstly, the influencing factors of driving risk are studied, and are classified into three categories: driver factors(“driver”), road user factors(“vehicle”) and road environment factors(“road”). Moreover, the interactions among these factors are analyzed.Afterwards, the similarities between driving risk and the concept of a field are analyzed. Based on the analysis and the artificial potential field theory, a new concept called the driving safety field is proposed. According to this concept and the study of influencing factors of driving risk and the interactions among them, a general model of driving safety field is constructed, which includes the following three parts: 1) a potential ffield, which is formed by non-moving objects on the roads, such as stopped vehicles; 2) a kinetic field, which is formed by the moving objects on roads, such as vehicles and pedestrians; and 3) a behavior field, which is formed by the drivers. This general model represe nts the influences of these factors on driving safety qualitatively. Based on related researches and considering some field theories and physical phenomena for reference, a specific model is constructed which represents the influences of traffic factors on driving safety quantitatively. Nevertheless, the model calibration methods are discussed, and as examples, some model parameters are calibrated according to the traffic accident data.Finally, applications of the driving safety field theory are proposed. As an example, a driving safety field based vehicle collision warning algorithm is proposed. And the validity of this algorithm is verified by a field experiment involving 24 drivers.Compared with existing driving risk evaluation methods, the driving safety field theory can reveal driver–vehicle–road interactions and their influences on driving safety, as well as predict driving safety trends owing to dynamic changes. In addition, the model can provide a new foundation for establishing driving safety measures and active vehicle control under complex traffic environments.