Abstract: In order to study the traffic characteristics of pedestrian crossing the street without signal control further, data on motion of incoming vehicle during the process of pedestrian crossing the street were collected by using a Lidar, and effects of external factors on pedestrian crossing decision and those of the psychological needs of pedestrians on safe crossing were taken into consideration. The parameters, including the distance between the pedestrian and the incoming vehicle, the velocity of the vehicle and the gap for crossing, were analyzed for two decision results, crossing directly and crossing after waiting. The above parameters were used to build a psychological distance model for the pedestrian crossing the street safely and a multivariate Logistic regression decision model. The effectiveness of the two models was evaluated. The results show that the probability of crossing the street for the pedestrian increases when the distance between the pedestrian and the incoming vehicle grows, the velocity of the vehicle decreases, and the gap of crossing becomes larger, that with the same gap of crossing, as the velocity grows, the probability of crossing gets larger, that the effectiveness of the models is great, and that the research results can provide a basis for the optimization of the on-board pedestrian warning system.

Key words: crossing decision, without signal control, behavioral characteristics, acceptance gap, multivariate Logistic regression