LINK AS AN AGGREGATE ALTERNATIVE: A CONTINUOUS RECURSIVE LOGIT REPRESENTATION OF PEDESTRIAN BEHAVIOR
Pacific Southwest Region University Transportation Center
The objective of this study is to propose a new model of mode, route, and path choice behavior of pedestrians under the recursive logit modeling framework which follows the random utility maximization theory. A main issue tackled in this study is about how to handle the fact that paths for pedestrians are essentially continuous in space and thus the path enumeration is almost impossible, making difficult to develop a consistent measure of economic welfare for both "route" behavior in a network and "path" choice behavior in a continuous space. To overcome this issue, we consider each pedestrian link as an aggregate alternative of infinite pedestrian paths, where the link utility is defined as the expected maximum utility of all possible pedestrian paths. Since the choice set generation problem in the discrete choice context becomes the problem of specifying an appropriate probability density function in the continuous choice context, we introduce the path density function which is constructed from a primitive free-flow pedestrian behavior model in a continuous space, where geometric conditions of the link are taken into account. We show an empirical strategy to estimate the parameters in the proposed model, and confirm the feasibility of the proposed model through a numerical study.
Makoto Chikaraishi is an Associate Professor at the Graduate School of International Development and Cooperation, Hiroshima University, Japan. His main research interests include understanding and modeling of activity-travel behavior, mathematical modeling of urban systems, and the relevant policy analyses with a particular focus on environmental and social risk management. He is currently working on research projects on the evaluation of the impacts of shared and/or automated vehicle on activity and travel behavior in disadvantaged areas, theoretical and empirical investigations on the value of mobility, and the application of artificial intelligence technologies for transport demand-supply management.