An Intelligent Model for Urban Demand-responsive Transport System Control

Abstract

Multi-agent simulation has been looked as an efficient tool for urban dynamic traffic services. However, the main problem is how to build an agent-based model for it. This research presents a multi-agent based demand responsive transport (DRT) services model, which adopts a practical multi-agents planning approach for urban DRT services control that satisfies the main constraints: minimize total slack time, travel time, waiting time, client’s special requests, and using minimum number of vehicle. In this paper, we propose an agent based multi-layer distributed hybrid planning model for the real-time problem which can solve this question. In the proposed method, an agent for each vehicle finds a set of routes by its local search, and selects a route by cooperation with other agents in its planning domain. By computational experiments, we examine the effectiveness of the proposed method.