Fuzzy-theory-based social force model for simulating pedestrian choice of ticket gates in subway stations

Abstract Ticket gates are vital equipment within subway stations, which have also caused bottlenecks in pedestrian flow. The effective utilization of ticket gates can enhance the pedestrian traffic efficiency. Nevertheless, pedestrian choice of ticket gates has the characteristics of uncertainty and fuzziness. In this regard, we build a fuzzy-theory-based pedestrian choice model of ticket gates: the distance, queuing pedestrians and luggage are adopted as three input variables in the fuzzy logic method, and the probability of selecting each ticket gate is set as the output variable. On this basic, we employ social force model (SFM) to simulate the ticket gates selection process in subway stations. Simulation results demonstrate that the choice model based on fuzzy logic can capture pedestrian choice behavior of ticket gates well. In comparison to traditional choice strategies (choosing the nearest ticket gate or choosing the ticket gate with the fewest queuing pedestrians), the proposed choice model of ticket gates based on fuzzy logic has the higher passing efficiency and the utilization of ticket gates is more balanced. The outcomes of this research can provide substantial support for the humanized design and operation management of subway stations.