Modeling Risk Degree of Conflicts between Crossing Pedestrians and Vehicles at Signalized Intersections

To quantitatively evaluate the safety of pedestrian crossing and to quantify the risk degree of traffic conflicts between crossing pedestrian and vehicle at signalized intersection, this paper conducted the risk degree model of crossing pedestrian and vehicle based on the features of pedestrian crossing behavior and the theory of conflict. The SMOK clustering algorithm based on the fuzzy cluster analysis method is used. Evaluation analysis process and results of risk degree model is demonstrated in the case studies of six signalized intersections in Nanjing City of China with the manual data collection method on video, which gives acquisition and calculation method of the evaluation indexes of TTC, PET, DST and validates the practicality of proposed model. The result shows that three indexes (TTC, PET, DST) play a significant role in clustering analysis and the frequency and severity of conflicts differs according to different types of conflict.