Agent-Based Pedestrian Activity Simulation in Shopping Environments Using a Choice Network Approach

Abstract

Most of current approaches for processing agent-based pedestrian activity simulations propose movement choice networks. Choice mechanisms include where to stop, in what order, and which overall route to take. In our network approach, the movement choice network is approximated using a lattice of irregular cells representing streets and shops. In this approach, cell centroids are considered the nodes of an implicit movement network. A pedestrian agent is located in a node and can move on the implicit movement network to other nodes and is situated randomly in the cell related to that node. In this paper, the focus is on the generation of the movement network and the underlying behavioral rules that conducts the activation of pedestrians on the network representing a shopping environment.