Hybrid Dynamic Route Planning Model for Pedestrian Microscopic Simulation at Subway Station

Abstract

To make agents’ route decision-making behaviours as real as possible, this paper proposes a layered navigation algorithm, emphasizing the coordinating of the global route planning at strategic level and the local route planning at tactical level. Specifically, by an improved visibility graph method, the global route is firstly generated based on static environment map. Then, a new local route planning (LRP) based on dynamic local environment is activated for multipath selection to allow pedestrian to respond changes at a real-time sense. In particular, the LRP model is developed on the basis of a passenger’s psychological motivation. The pedestrians’ individual preferences and the uncertainties existing in the process of evaluation and choice are fully considered. The suitable local path can be generated according to an estimated passing time. The LRP model is applied to the choice of ticket gates at a subway station, and the behaviours of gate choosing and rechoosing are investigated. By utilizing C++, the layered navigation algorithm is implemented. The simulation results exhibit agents’ tendency to avoid congestion, which is often observed in real crowds.

Three-Layers Model of Pedestrian in 2D Complex Space

“…Asano calculate the shortest path and obtains the desired walking direction [14]. Gao designed the LRP model to select the route [15].…”

A Fuzzy-Theory-Based Cellular Automata Model for Pedestrian Evacuation From a Multiple-Exit Room

“…Mesmer and Bloebaum [43] further introduced Bayesian game theory into the exit selection model. Gao et al [44] adopted the Logit method to determine the route by taking the distance factor and density factor into consideration. Liu et al [45] and Fu et al [46] also pointed out that the distance and density were two important factors to determine the selection of exit.…”