Simulation of pedestrian-vehicle interference in railway station drop-off area based on cellular automata

In a drop-off area of railway station, serious interference between pedestrians and vehicles affects the traffic efficiency of the area, and causes traffic safety problems. However, research on the interference between vehicles and pedestrians in the drop-off area has not been fully explored. To deal with this problem, this paper proposes an interference model of pedestrians and vehicles in the drop off area based on cellular automata model, in which the decision-making behavior of pedestrians and the yield behavior of vehicles are both considered. To be more practical, the effect of pedestrian herding on crossing decision and the impact of the pedestrians in the waiting area on vehicle yield are also considered. The proposed model is verified by the traffic flow of Beijing West Railway Station and the traffic characteristics of the drop-off area are analyzed. In addition, the sensitivity analysis results show that pedestrians with impatience and herd mentality will aggravate the delays of vehicles. Furthermore, three strategies are proposed and verified to improve the efficiency and safety of the drop-off area. Simulation experiments indicate that adding one more drop-off lane can increase vehicle outflow by more than 40%, guiding the vehicle to choose the entrance lane can make greater use of the transportation capacity of the drop off area, and greater efficiency and safety can be achieved by directing vehicles with more passengers into the inner drop-off lane. (C) 2021 Elsevier B.V. All rights reserved.

Automated summary

This paper proposes an interference model of pedestrians and vehicles in the drop off area based on cellular automata model, considering the decision-making behavior of pedestrians and the yield behavior of vehicles. Through research, it was found that pedestrians with impatience and herd mentality will exacerbate vehicle delays, and three strategies were proposed to improve the situation.