Evaluation of Parking Guidance Information System with Multi-agent Based Simulation

This D.Phil. thesis presents an agent-based approach to evaluate economic effect of parking guidance information (PGI) system by modeling drivers’ behavior under different parking guidance scenarios: with PGI and without PGI. An agent-based model (ABM) is established to explicitly capture car following behavior, drivers parking space searching and decision behavior after received all various information. To explicitly capture and explore the PGI impact on drivers’ parking choice behavior, RP data are collected and the experiments have been conducted in year 2012 and 2013. During the experiments, there are three types of displayed information – Null information (PGI shows no information), ASL information (PGI shows the number of available space and location) and ECF information (PGI shows occupancy status information as empty, congested and full). Drivers’ behavior response to these three different types of displayed information are investigate for identify the main factors of choice model. It is suggested that that the walking distance factor significantly influence drivers’ parking choice under the effect of all displayed type of information. MNL model is applied to perform drivers’ parking search process under different scenarios of with PGI (ECF information/ ASL information) and without PGI. And the estimated result of MNL model indicated that both the effect of ECF information and ASL information are significantly affect drivers parking choice behavior especially for the drivers who choose to park at block D to block I. Besides, the significance of variable of walking distance, dummy variable of occupancy information and variable of number of available space justify the hypothesis that drivers are sensitive to above three variables. A new framework of sequential parking choice model is also presented in this thesis. The presented sequential choice model offers an alternative to the traditional approach to estimate parking choice behavior especially given an assumption of no specific defined variable given in expected utility. Then the estimated result of MNL model is adopted in agent-based simulation process to perform drivers’ parking choice behavior. The applied part of thesis aims to evaluate the effectiveness of PGI system and partly bridge the gap between parking choice behavior model under PGI system and economic evaluation methodology, with application to Shimizu parking area located in the Shin-tomei expressway (Japan). The study may be regarded as one of the few studies to integrate multi-agents activities of parking choice process, Poisson distribution, GIS and a detailed traffic micro-simulation for economic evaluation of with and without PGI system. The simulation results of the number of lost agent, average searching time of all agents can be applied to evaluate the economic benefit of PGI system.

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