Agent-Based Modeling and Simulation for the Bus-Corridor Problem in a Many-to-One Mass Transit System

Author:

Xie Qinmu1,Ma Shoufeng1,Jia Ning1,Gao Yang1

Affiliation:

1. Institute of Systems Engineering, College of Management and Economics, Tianjin University, Tianjin 300072, China

Abstract

With the growing problem of urban traffic congestion, departure time choice is becoming a more important factor to commuters. By using multiagent modeling and the Bush-Mosteller reinforcement learning model, we simulated the day-to-day evolution of commuters’ departure time choice on a many-to-one mass transit system during the morning peak period. To start with, we verified the model by comparison with traditional analytical methods. Then the formation process of departure time equilibrium is investigated additionally. Seeing the validity of the model, some initial assumptions were relaxed and two groups of experiments were carried out considering commuters’ heterogeneity and memory limitations. The results showed that heterogeneous commuters’ departure time distribution is broader and has a lower peak at equilibrium and different people behave in different pattern. When each commuter has a limited memory, some fluctuations exist in the evolutionary dynamics of the system, and hence an ideal equilibrium can hardly be reached. This research is helpful in acquiring a better understanding of commuter’s departure time choice and commuting equilibrium of the peak period; the approach also provides an effective way to explore the formation and evolution of complicated traffic phenomena.

Funder

National Natural Science Foundation of China

Publisher

Hindawi Limited

Subject

Modeling and Simulation

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