IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v12y2024i2p291-d1320209.html
   My bibliography  Save this article

Research on the Route Choice Behavior of Urban Freight Vehicles Based on GPS Data

Author

Listed:
  • Lili Zheng

    (School of Transportation, Jilin University, No. 5988 Renmin Street, Changchun 130022, China)

  • Tian Gao

    (Automotive Engineering Research Institute, BYD Automobile Industry Co., Ltd., No. 3009 BYD Road, Shenzhen 518118, China)

  • Lin Meng

    (Jilin Provincial Transportation Administration, No. 2518 Jie-fang Road, Changchun 130021, China)

  • Tongqiang Ding

    (School of Transportation, Jilin University, No. 5988 Renmin Street, Changchun 130022, China)

  • Wenhao Chen

    (School of Transportation, Jilin University, No. 5988 Renmin Street, Changchun 130022, China)

Abstract

In order to provide urban freight vehicles with navigation routes that better align with their travel preferences, it is necessary to analyze the patterns and characteristics of their route choices. This paper focuses on freight vehicles traveling within the city and examines their route selection behavior. Through an analysis of the GPS data collected from freight truck journeys in Changchun, China, this study outlines the characteristics of freight vehicle travel within the city. Variables that may influence their route selection behavior are defined as feature factors. The study employs the DBSCAN algorithm to identify the hotspots in origin–destination pairs for freight truck travel in Changchun. It also utilizes Breadth First Search Link Elimination to generate a set of route choices and constructs route selection behavior models based on Multinomial Logit and Path Size Logit. Based on the research findings, during navigation within the city road network, these vehicles exhibit a preference for side roads, a tendency to favor right turns at intersections, and a propensity to choose routes with lower duplication compared to alternative options. The study’s conclusions offer theoretical support for guiding urban freight vehicle routes and planning and managing freight traffic within the city.

Suggested Citation

  • Lili Zheng & Tian Gao & Lin Meng & Tongqiang Ding & Wenhao Chen, 2024. "Research on the Route Choice Behavior of Urban Freight Vehicles Based on GPS Data," Mathematics, MDPI, vol. 12(2), pages 1-17, January.
  • Handle: RePEc:gam:jmathe:v:12:y:2024:i:2:p:291-:d:1320209
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/12/2/291/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2227-7390/12/2/291/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Theo Arentze & Tao Feng & Harry Timmermans & Jops Robroeks, 2012. "Context-dependent influence of road attributes and pricing policies on route choice behavior of truck drivers: results of a conjoint choice experiment," Transportation, Springer, vol. 39(6), pages 1173-1188, November.
    2. Frejinger, E. & Bierlaire, M. & Ben-Akiva, M., 2009. "Sampling of alternatives for route choice modeling," Transportation Research Part B: Methodological, Elsevier, vol. 43(10), pages 984-994, December.
    3. Broach, Joseph & Dill, Jennifer & Gliebe, John, 2012. "Where do cyclists ride? A route choice model developed with revealed preference GPS data," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(10), pages 1730-1740.
    4. Daniel McFadden & Kenneth Train, 2000. "Mixed MNL models for discrete response," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(5), pages 447-470.
    5. Daniel Kahneman & Amos Tversky, 2013. "Prospect Theory: An Analysis of Decision Under Risk," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 6, pages 99-127, World Scientific Publishing Co. Pte. Ltd..
    6. Wen, Chieh-Hua & Koppelman, Frank S., 2001. "The generalized nested logit model," Transportation Research Part B: Methodological, Elsevier, vol. 35(7), pages 627-641, August.
    7. Shlomo Bekhor & Moshe Ben-Akiva & M. Ramming, 2006. "Evaluation of choice set generation algorithms for route choice models," Annals of Operations Research, Springer, vol. 144(1), pages 235-247, April.
    8. Hess, Stephane & Quddus, Mohammed & Rieser-Schüssler, Nadine & Daly, Andrew, 2015. "Developing advanced route choice models for heavy goods vehicles using GPS data," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 77(C), pages 29-44.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Hamzeh Alizadeh & Bilal Farooq & Catherine Morency & Nicolas Saunier, 2018. "On the role of bridges as anchor points in route choice modeling," Transportation, Springer, vol. 45(5), pages 1181-1206, September.
    2. Eran Ben-Elia & Ido Erev & Yoram Shiftan, 2008. "The combined effect of information and experience on drivers’ route-choice behavior," Transportation, Springer, vol. 35(2), pages 165-177, March.
    3. Li, Dawei & Feng, Siqi & Song, Yuchen & Lai, Xinjun & Bekhor, Shlomo, 2023. "Asymmetric closed-form route choice models: Formulations and comparative applications," Transportation Research Part A: Policy and Practice, Elsevier, vol. 171(C).
    4. Lemp, Jason D. & Kockelman, Kara M., 2012. "Strategic sampling for large choice sets in estimation and application," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(3), pages 602-613.
    5. Ben-Elia, Eran & Shiftan, Yoram, 2010. "Which road do I take? A learning-based model of route-choice behavior with real-time information," Transportation Research Part A: Policy and Practice, Elsevier, vol. 44(4), pages 249-264, May.
    6. Mai, Tien & Bastin, Fabian & Frejinger, Emma, 2017. "On the similarities between random regret minimization and mother logit: The case of recursive route choice models," Journal of choice modelling, Elsevier, vol. 23(C), pages 21-33.
    7. Paleti, Rajesh, 2018. "Generalized multinomial probit Model: Accommodating constrained random parameters," Transportation Research Part B: Methodological, Elsevier, vol. 118(C), pages 248-262.
    8. Ida, Takanori & Goto, Rei & Takahashi, Yuko & Nishimura, Shuzo, 2011. "Can economic-psychological parameters predict successful smoking cessation?," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 40(3), pages 285-295, May.
    9. Biondi, Beatrice & Cornelsen, Laura & Mazzocchi, Mario & Smith, Richard, 2020. "Between preferences and references: Asymmetric price elasticities and the simulation of fiscal policies," Journal of Economic Behavior & Organization, Elsevier, vol. 180(C), pages 108-128.
    10. Dam, Tien Thanh & Ta, Thuy Anh & Mai, Tien, 2022. "Submodularity and local search approaches for maximum capture problems under generalized extreme value models," European Journal of Operational Research, Elsevier, vol. 300(3), pages 953-965.
    11. Florian Heiss & Stephan Hetzenecker & Maximilian Osterhaus, 2019. "Nonparametric Estimation of the Random Coefficients Model: An Elastic Net Approach," Papers 1909.08434, arXiv.org, revised Sep 2019.
    12. Na Zhang & Zijia Wang & Feng Chen & Jingni Song & Jianpo Wang & Yu Li, 2020. "Low-Carbon Impact of Urban Rail Transit Based on Passenger Demand Forecast in Baoji," Energies, MDPI, vol. 13(4), pages 1-18, February.
    13. Peter Davis & Pasquale Schiraldi, 2014. "The flexible coefficient multinomial logit (FC-MNL) model of demand for differentiated products," RAND Journal of Economics, RAND Corporation, vol. 45(1), pages 32-63, March.
    14. Mai, Tien & Frejinger, Emma & Bastin, Fabian, 2015. "A misspecification test for logit based route choice models," Economics of Transportation, Elsevier, vol. 4(4), pages 215-226.
    15. Xie, Erhao, 2021. "Empirical properties and identification of adaptive learning models in behavioral game theory," Journal of Economic Behavior & Organization, Elsevier, vol. 191(C), pages 798-821.
    16. Hong Fu & Yuehua Zhang & Yinuo An & Li Zhou & Yanling Peng & Rong Kong & Calum G. Turvey, 2022. "Subjective and objective risk perceptions and the willingness to pay for agricultural insurance: evidence from an in-the-field choice experiment in rural China," The Geneva Risk and Insurance Review, Palgrave Macmillan;International Association for the Study of Insurance Economics (The Geneva Association), vol. 47(1), pages 98-121, March.
    17. Fosgerau, Mogens, 2007. "Using nonparametrics to specify a model to measure the value of travel time," Transportation Research Part A: Policy and Practice, Elsevier, vol. 41(9), pages 842-856, November.
    18. Yao, Rui & Bekhor, Shlomo, 2022. "A variational autoencoder approach for choice set generation and implicit perception of alternatives in choice modeling," Transportation Research Part B: Methodological, Elsevier, vol. 158(C), pages 273-294.
    19. Shanjiang Zhu & David Levinson, 2011. "A Portfolio Theory of Route Choice," Working Papers 000096, University of Minnesota: Nexus Research Group.
    20. Li, Baibing & Hensher, David A., 2017. "Risky weighting in discrete choice," Transportation Research Part B: Methodological, Elsevier, vol. 102(C), pages 1-21.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jmathe:v:12:y:2024:i:2:p:291-:d:1320209. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.