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Research on Residents’ Travel Behavior under Sudden Fire Disaster Based on Prospect Theory

Author

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  • Ciyun Lin

    (Department of Traffic Information and Control Engineering, Jilin University, Changchun 130022, China
    Jilin Engineering Research Center for ITS, Changchun 130022, China)

  • Kang Wang

    (Department of Traffic Information and Control Engineering, Jilin University, Changchun 130022, China
    Jilin Engineering Research Center for ITS, Changchun 130022, China)

  • Dayong Wu

    (Texas A&M Transportation Institute, Texas A&M University, College Station, TX 77843, USA)

  • Bowen Gong

    (Department of Traffic Information and Control Engineering, Jilin University, Changchun 130022, China
    Jilin Engineering Research Center for ITS, Changchun 130022, China)

Abstract

The decision-making process of travel behaviors under uncertainty and risk shall be analyzed in order to solve the emergency traffic management or evacuation problem under sudden fire disaster in a high-density urban environment. Firstly, this paper attempts to acquire the travel risk attitude thought online survey questionnaires. In the questionnaire, we focused on obtaining the traveler’s response thought set a scene and obtain the traveler’s risk attitude. Secondly, we explore the relationship between traveler’s personal attributes and risk attitudes through questionnaires. Finally, the questionnaire data were used to calibrate and adjust the parameters in the proposed prospect theory (PT) based model. Subsequently, the K-T model and Wang’s model were used to compare and verify the accuracy and validity of the proposed model. The results presented that the proposed model is more accurate and the largest prediction error of travel route selection behavior is only nine percent.

Suggested Citation

  • Ciyun Lin & Kang Wang & Dayong Wu & Bowen Gong, 2020. "Research on Residents’ Travel Behavior under Sudden Fire Disaster Based on Prospect Theory," Sustainability, MDPI, vol. 12(2), pages 1-21, January.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:2:p:487-:d:306577
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    References listed on IDEAS

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    1. Tversky, Amos & Kahneman, Daniel, 1992. "Advances in Prospect Theory: Cumulative Representation of Uncertainty," Journal of Risk and Uncertainty, Springer, vol. 5(4), pages 297-323, October.
    2. Di, Xuan & Liu, Henry X., 2016. "Boundedly rational route choice behavior: A review of models and methodologies," Transportation Research Part B: Methodological, Elsevier, vol. 85(C), pages 142-179.
    3. Carlo Giacomo Prato & Shlomo Bekhor & Cristina Pronello, 2012. "Latent variables and route choice behavior," Post-Print halshs-00733464, HAL.
    4. Helga Fehr-Duda & Manuele Gennaro & Renate Schubert, 2006. "Gender, Financial Risk, and Probability Weights," Theory and Decision, Springer, vol. 60(2), pages 283-313, May.
    5. Jou, Rong-Chang & Chen, Ke-Hong, 2013. "An application of cumulative prospect theory to freeway drivers’ route choice behaviours," Transportation Research Part A: Policy and Practice, Elsevier, vol. 49(C), pages 123-131.
    6. Henry Stott, 2006. "Cumulative prospect theory's functional menagerie," Journal of Risk and Uncertainty, Springer, vol. 32(2), pages 101-130, March.
    7. Neilson, William S & Stowe, Jill, 2002. "A Further Examination of Cumulative Prospect Theory Parameterizations," Journal of Risk and Uncertainty, Springer, vol. 24(1), pages 31-46, January.
    8. George Wu & Richard Gonzalez, 1996. "Curvature of the Probability Weighting Function," Management Science, INFORMS, vol. 42(12), pages 1676-1690, December.
    9. Carlo Prato & Shlomo Bekhor & Cristina Pronello, 2012. "Latent variables and route choice behavior," Transportation, Springer, vol. 39(2), pages 299-319, March.
    10. Bhat, Chandra R. & Dubey, Subodh K., 2014. "A new estimation approach to integrate latent psychological constructs in choice modeling," Transportation Research Part B: Methodological, Elsevier, vol. 67(C), pages 68-85.
    11. Mohammed Abdellaoui, 2000. "Parameter-Free Elicitation of Utility and Probability Weighting Functions," Management Science, INFORMS, vol. 46(11), pages 1497-1512, November.
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    Cited by:

    1. Ciyun Lin & Kang Wang & Dayong Wu & Bowen Gong, 2020. "Passenger Flow Prediction Based on Land Use around Metro Stations: A Case Study," Sustainability, MDPI, vol. 12(17), pages 1-22, August.

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