吉林大学学报(工学版) ›› 2018, Vol. 48 ›› Issue (4): 1029-1036.doi: 10.13229/j.cnki.jdxbgxb20170561

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Mixed Logit model for understanding travel mode choice behavior of megalopolitan residents

LUAN Xin1, DENG Wei1, CHENG Lin1, CHEN Xin-yuan2,3   

  1. 1.School of Transportation, Southeast University, Nanjing 211189, China;
    2.The Institute of Transport Studies, Monash University, Melbourne VIC3168, Australia;
    3.Department of Civil Engineering, Monash University, Melbourne VIC3168, Australia
  • Received:2017-06-01 Online:2018-07-01 Published:2018-07-01

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Abstract: In order to alleviate the conflicts of traffic supply and demand, improve the resident trip structure and mode, multiple variables impacting the travel mode choice were defined based on the random utility maximization theory with Nanjing City as a specific case. Mixed Logit (ML) model was established for analyzing and interpreting the influence and interaction mechanism of behavioral characteristics among household properties, individual attributes, trip information and the locations of trip ODs. The outcomes of ML model were analyzed by statistic regression. Results show that competitiveness of slow modes (non-motorized transport) become better if the time requirement is not high. However, with travel time increasing, the advantages op the slow modes are gradually weaken. Moreover, in suburbs and long distance trips, public transports (including metro) become more attractive to passengers. The results of statistic regression may help urban planners and transportation policy makers to integrate limited road resources systematically to ensure the resident travel comfortable, convenient and efficient.

Key words: engineering of communications and transportation system, travel mode choice, mixed Logit model, structure optimization of residents' trips, policy orientation

CLC Number: 

  • U491.1
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