Observational studies of pedestrian flows

Abstract

Walking is an environmentally friendly mode of transportation. A better understanding of pedestrian activities and effective planning of walking facilities are particularly important for densely populated Asian cities like Hong Kong. Empirical studies on pedestrian flows can be classified as controlled experiments and observational surveys. Controlled experiments are flexible and can be designed to fulfill the requirements of specific studies and eliminate influence from unrelated factors. Observational surveys provide data for pedestrian movements in different types of walking facilities. This thesis aims to develop a mathematical model for multidirectional pedestrian flows based on knowledge obtained from both a controlled experiment and observational surveys on three different walking facilities. Bayesian inference is adopted for model calibration, as it can combine the prior information from the controlled experiment and the observed data from the observational surveys.

The proposed model is based on Drake’s (1967) model of traffic flow. However, multidirectional pedestrian flows are much more complicated than the unidirectional and bidirectional flows. Therefore, instead of relating the speed of a pedestrian stream solely to pedestrian density, the flow ratio and intersecting angles between streams are introduced as factors that may influence stream speed. The proposed model takes the form of a set of structural equations rather than a single deterministic function.

By applying Bayesian inference, the proposed model is calibrated with the three sets of observed data respectively, based on the prior distribution specified by the controlled experiment results. Finally, pedestrian movements in three different walking facilities are analyzed based on the properties of the calibrated model.