Chapter
Jan 13, 2020
Sixth International Conference on Transportation Engineering

Analysis of Competitive Public Transport Adjustment Strategy Based on Multi-Alternative Decision Field Theory

Publication: ICTE 2019

ABSTRACT

Aiming at the problem of excessive competition between urban rail transit and the parallel conventional bus, this paper, from the perspective of travelers, establishes a decision-making behavior analysis model of competitive public transport modes based on multi-alternative decision filed theory (MDFT). Selecting the competitive transit modes between the two campuses of Southwest Jiaotong University as experimental scenario, this paper analyzes the decision-making process of travelers and the selected probability of each scheme by means of computer simulation. The results illustrate that MDFT theory and model can reasonably reflect the decision-making process of the traveler and effectively calculate the selected probability of each scheme, which confirms the validity of the model. Then, the model is applied to analyze the real decision-making case that travelers make a choice from rail transit and the parallel conventional bus. According to the analysis of simulation results, some adjustment strategies are proposed for competitive rail transit and conventional buses. Eventually, the adjustment strategies can be verified to coordinate the rail transit and the conventional bus properly, and improve the efficiency of the public transportation system.

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REFERENCE

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Information & Authors

Information

Published In

Go to ICTE 2019
ICTE 2019
Pages: 151 - 161
Editors: Xiaobo Liu, Ph.D., Southwest Jiaotong University, Qiyuan Peng, Ph.D., Southwest Jiaotong University, and Kelvin C. P. Wang, Ph.D., Oklahoma State University
ISBN (Online): 978-0-7844-8274-2

History

Published online: Jan 13, 2020

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Authors

Affiliations

Yiyuan Zhang [email protected]
National United Engineering Laboratory of Integrated and Intelligent Transportation, School of Transportation and Logistics, Southwest Jiaotong Univ., 999 Xi’an Rd., Pidu District, Chengdu 611756, P.R. China. E-mail: [email protected]
National United Engineering Laboratory of Integrated and Intelligent Transportation, School of Transportation and Logistics, Southwest Jiaotong Univ., 999 Xi’an Rd., Pidu District, Chengdu 611756, P.R. China. E-mail: [email protected]
National United Engineering Laboratory of Integrated and Intelligent Transportation, School of Transportation and Logistics, Southwest Jiaotong Univ., 999 Xi’an Rd., Pidu District, Chengdu 611756, P.R. China (corresponding author). E-mail: [email protected]

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