Pedestrian Risk Assessment and Early Warning Algorithm Based on Psychological Safety Distance

To realize an accurate risk assessment of dynamic and random vulnerable road users under the traffic environment of mixed traffic, this paper proposed a pedestrian risk assessment model considering pedestrian psychological safety distance based on the theory of the driving safety field. First, the concept of psychological safety distance, including psychological safety passing distance and psychological safety braking distance, was proposed by considering whether moving vehicles would endanger the psychological safety of pedestrians, and its possible influencing factors were mined through a questionnaire survey for numerical analysis. Then, the psychological safety distance was integrated into the driving safety field theory, and a dynamic evaluation model of pedestrian risk was established. Based on this, a hierarchical early warning algorithm for typical pedestrian crossing scenes was proposed. Finally, the application effect of the early warning algorithm in a typical pedestrian crossing scene was analyzed by carrying outa PC-Crash simulation experiment. The results show that ① on road sections without traffic lights, when pedestrians face a moving vehicle, the required psychological safety travel distance is not less than 50 m, and the psychological safety braking distance is generally distributed between 5 and 20 m. Factors such as vehicle type, pedestrian's gender and age, will all have an impact on the value of psychological safety distance; ② under the action of the hierarchical early warning algorithm, the minimum braking deceleration required to ensure the psychological safety of pedestrians is distributed between 0 and 3 m•s-2.Compared with existing research methods, the pedestrian early warning algorithm can effectively ensure the psychological safety of pedestrians and stability of driving while avoiding accidents, and can provide a new development perspective for the design of automobile active safety early warning systems. © 2022, Editorial Department of China Journal of Highway and Transport. All right reserved.