Title: A personalized spatial cognitive road network for agent-based modeling of pedestrian evacuation simulation: a case study in Hong Kong
Abstract:In this article, we study the spatial knowledge issue of pedestrians while simulating their routing behaviors in agent-based simulation research. As the data collected from a field survey conducted in...In this article, we study the spatial knowledge issue of pedestrians while simulating their routing behaviors in agent-based simulation research. As the data collected from a field survey conducted in a real event case exposed, we proposed a personalized spatial cognitive road network (PSCRN) model, which assumes that different pedestrians hold different probabilities of recognizing a particular road for evacuation due to different spatial cognition under the incomplete spatial knowledge hypothesis. The multivariate binary logistic regression method was applied to identify the linkage between the predictors selected and the response probability variable quantitatively, and the Hosmer–Lemeshow statistic was used to test the regression model. Thus, in agent-based simulations for a given pedestrian, the PSCRN model could predict the recognized roads that the pedestrian was able to take for evacuation with respect to the diversity of spatial cognition lying in the public rather than every road as the complete spatial knowledge hypothesis assumes.Read More