Analysis and Modeling of Pedestrian Crossing Behavior at Intersections

As an important part of urban traffic, urban signalized intersections have complex traffic flow and frequent accidents. As a weak traffic participant, the proportion of traffic accidents involving pedestrians has been high, and pedestrians are unsafe crossing at signalized intersections. The behavior abounds, seriously reducing the security of the intersection. Therefore, it is necessary to conduct an in-depth study on the pedestrian crossing characteristics. In this paper, based on the pedestrian crossing behavior at a signalized intersection, principal component analysis (PCA) is used to reduce the factors affecting pedestrian crossings. Finally, five impact factors are extracted from the eight variables: road environment factor, waiting behavior factor, herd behavior factor, arrival environmental factor, and self-characteristic factor. Secondly, based on the results of factor analysis, a pedestrian log violation regression model was established. According to the model results, the influence of impact factors on pedestrian crossing decision-making is analyzed. Then, suggestions on reducing pedestrian violation rate and improving pedestrian traffic environment are given from three aspects: road facility setting, pedestrian traffic control, and safety education measures.