Prediction of travel mode choice behavior preference under the impacts of congestion pricing based on ICLV model
ID:1648 View Protection:ATTENDEE Updated Time:2021-12-03 13:43:01 Hits:249 Poster Presentation

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Abstract
Psychological factors (latent variables) play a significant role in formation of travel mode choice behavior preference. An integrated choice and latent variable (ICLV) model, which integrates structural equation model (SEM) and mixed-logit (MXL) is proposed in this paper to predict the mode choice behavior under the impacts of congestion pricing. The model is estimated using stated preference travel mode choice data of over 1000 automobile travelers (including more habitual automobile travelers and less habitual automobile travelers) collected in Beijing inner districts. Results from the empirical application shows that the goodness of fit for the integrated choice and latent variable model is higher than that of the traditional mixed-logit model, which proves that latent variables have an obvious impact on mode choice behavior under the impacts of congestion pricing. This study provides insights for designing congestion pricing and illustrates the importance of developing complementary modules that target psychological factors to effectively promote mode shifts from automobile to sustainable travel modes in China.
Keywords
CICTP
Speaker
Yaping Li
Zhengzhou Universtiy of Aeronautics

Submission Author
Yaping Li Zhengzhou Universtiy of Aeronautics
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Important Date
  • Conference Date

    Dec 17

    2021

    to

    Dec 20

    2021

  • Dec 16 2021

    Contribution Submission Deadline

  • Dec 24 2021

    Registration deadline

Sponsored By
Chinese Overseas Transportation Association
Chang'an University
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