IDEAS home Printed from https://ideas.repec.org/p/cdl/itsrrp/qt53d2t6df.html
   My bibliography  Save this paper

Exploration Of Driver Route Choice With Advanced Traveler Information Using Neural Network Concepts

Author

Listed:
  • Yang, Hai
  • Kitamura, Ryuichi
  • Jovanis, Paul P.
  • Vaughn, Kenneth M.
  • Abdel-aty, Mohammed A.
  • Reddy, Prasuna Dvg

Abstract

A model of drivers' route choice behavior under advanced traveler information systems (ATIS) is developed based on data collected from learning experiments using interactive computer simulation. A neural network model is used as a convenient modeling technique in the analysis. Results indicated that most subjects made route choices based mainly on their recent experiences. Results also demonstrated that route choice behavior is related to the personal characteristics as well as the characteristics of the respective routes. Travel experiences had less effect on route choice and the results indicate that the prediction accuracy of the model, the acceptance rate of advice, and the quality of advice are closely related.

Suggested Citation

  • Yang, Hai & Kitamura, Ryuichi & Jovanis, Paul P. & Vaughn, Kenneth M. & Abdel-aty, Mohammed A. & Reddy, Prasuna Dvg, 1993. "Exploration Of Driver Route Choice With Advanced Traveler Information Using Neural Network Concepts," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt53d2t6df, Institute of Transportation Studies, UC Berkeley.
    • Handle: RePEc:cdl:itsrrp:qt53d2t6df
    as

    Download full text from publisher

    File URL: https://www.escholarship.org/uc/item/53d2t6df.pdf;origin=repeccitec
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Iida, Yasunori & Akiyama, Takamasa & Uchida, Takashi, 1992. "Experimental analysis of dynamic route choice behavior," Transportation Research Part B: Methodological, Elsevier, vol. 26(1), pages 17-32, February.
    2. Vaughn, Kenneth M. & Abdel-aty, Mohamed A. & Kitamura, Ryichi & Jovanis, Paul P. & Yang, Hai, 1993. "Experimental Analysis And Modeling Of Sequential Route Choice Under ATIS In A Simple Traffic Network," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt8hs4x4ng, Institute of Transportation Studies, UC Berkeley.
    3. Adler, Jeffrey L. & Recker, Wilfred W. & McNally, Michael G., 1992. "A Conflict Model and Interactive Simulator (FASTCARS) for Predicting Enroute Driver Behavior in Response to Real-Time Traffic Condition Information," University of California Transportation Center, Working Papers qt5044j167, University of California Transportation Center.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Nijkamp, Peter & Reggiani, Aura & Tsang, Wai Fai, 2004. "Comparative modelling of interregional transport flows: Applications to multimodal European freight transport," European Journal of Operational Research, Elsevier, vol. 155(3), pages 584-602, June.
    2. Wenyun Tang & Lin Cheng, 2015. "Analyzing Multiday Route Choice Behavior using GPS Data," Working Papers 000135, University of Minnesota: Nexus Research Group.
    3. William Lam & K. Chan, 2001. "A model for assessing the effects of dynamic travel time information via variable message signs," Transportation, Springer, vol. 28(1), pages 79-99, February.
    4. Hongcheng Gan & Xin Ye, 2013. "Investigation of drivers' diversion responses to urban freeway variable message signs displaying freeway and local street travel times," Transportation Planning and Technology, Taylor & Francis Journals, vol. 36(8), pages 651-668, December.
    5. Zhong, Shiquan & Zhou, Lizhen & Ma, Shoufeng & Jia, Ning, 2012. "Effects of different factors on drivers’ guidance compliance behaviors under road condition information shown on VMS," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(9), pages 1490-1505.
    6. Yang, Hai & Meng, Qiang, 2001. "Modeling user adoption of advanced traveler information systems: dynamic evolution and stationary equilibrium," Transportation Research Part A: Policy and Practice, Elsevier, vol. 35(10), pages 895-912, December.
    7. Chen, Ting-Yu & Chang, Hsin-Li & Tzeng, Gwo-Hshiung, 2001. "Using a weight-assessing model to identify route choice criteria and information effects," Transportation Research Part A: Policy and Practice, Elsevier, vol. 35(3), pages 197-224, March.
    8. Richard H. M. Emmerink & Paul van Beek, 1997. "Empirical Analysis of Work Schedule Flexibility: Implications for Road Pricing and Driver Information Systems," Urban Studies, Urban Studies Journal Limited, vol. 34(2), pages 217-234, February.
    9. Richard H. M. Emmerink & Peter Nijkamp & Piet Rietveld & Jos N. Van Ommeren & Richard H. M. Emmerink & Peter Nijkamp & Piet Rietveld & Jos N. Van Ommeren, 2004. "Variable Message Signs and Radio Traffic Information: An Integrated Empirical Analysis of Drivers’ Route Choice Behaviour," Chapters, in: Location, Travel and Information Technology, chapter 16, pages 343-361, Edward Elgar Publishing.
    10. Ye, Hongbo & Xiao, Feng & Yang, Hai, 2021. "Day-to-day dynamics with advanced traveler information," Transportation Research Part B: Methodological, Elsevier, vol. 144(C), pages 23-44.
    11. Chan, K. S. & Lam, William H. K., 2002. "Optimal speed detector density for the network with travel time information," Transportation Research Part A: Policy and Practice, Elsevier, vol. 36(3), pages 203-223, March.
    12. Hai Yang, 1999. "Evaluating the benefits of a combined route guidance and road pricing system in a traffic network with recurrent congestion," Transportation, Springer, vol. 26(3), pages 299-322, August.
    13. Li, Pengbo & Tian, Lijun & Xiao, Feng & Zhu, Hongwei, 2022. "Can day-to-day dynamic model be solved analytically? New insights on portraying equilibrium and accommodating autonomous vehicles," Transportation Research Part B: Methodological, Elsevier, vol. 166(C), pages 374-395.
    14. Zheng Zhu & Xiqun Chen & Chenfeng Xiong & Lei Zhang, 2018. "A mixed Bayesian network for two-dimensional decision modeling of departure time and mode choice," Transportation, Springer, vol. 45(5), pages 1499-1522, September.
    15. Jiang, Yanqun & Wong, S.C. & Ho, H.W. & Zhang, Peng & Liu, Ruxun & Sumalee, Agachai, 2011. "A dynamic traffic assignment model for a continuum transportation system," Transportation Research Part B: Methodological, Elsevier, vol. 45(2), pages 343-363, February.
    16. Malavasi, Gabriele & Ricci, Stefano, 2001. "Simulation of stochastic elements in railway systems using self-learning processes," European Journal of Operational Research, Elsevier, vol. 131(2), pages 262-272, June.
    17. Emmerink, Richard H. M. & Verhoef, Erik T. & Nijkamp, Peter & Rietveld, Piet, 1998. "Information policy in road transport with elastic demand: Some welfare economic considerations," European Economic Review, Elsevier, vol. 42(1), pages 71-95, January.
    18. Lu, Jing & Meng, Yucan & Timmermans, Harry & Zhang, Anming, 2021. "Modeling hesitancy in airport choice: A comparison of discrete choice and machine learning methods," Transportation Research Part A: Policy and Practice, Elsevier, vol. 147(C), pages 230-250.

    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. Terry E. Daniel & Eyran J. Gisches & Amnon Rapoport, 2009. "Departure Times in Y-Shaped Traffic Networks with Multiple Bottlenecks," American Economic Review, American Economic Association, vol. 99(5), pages 2149-2176, December.
    2. Pietro Guarnieri & Lorenzo Spadoni, 2024. "Norms and anti-coordination: elicitation and priming in an El Farol Bar Game experiment," Discussion Papers 2024/303, Dipartimento di Economia e Management (DEM), University of Pisa, Pisa, Italy.
    3. Emmerink, R., 1993. "Effects of information in road transport networks with recurrent congestion," Serie Research Memoranda 0065, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
    4. Xu, Xiangdong & Qu, Kai & Chen, Anthony & Yang, Chao, 2021. "A new day-to-day dynamic network vulnerability analysis approach with Weibit-based route adjustment process," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 153(C).
    5. Morgan, John & Orzen, Henrik & Sefton, Martin, 2009. "Network architecture and traffic flows: Experiments on the Pigou-Knight-Downs and Braess Paradoxes," Games and Economic Behavior, Elsevier, vol. 66(1), pages 348-372, May.
    6. Meneguzzer, Claudio, 2022. "Day-to-day dynamics in a simple traffic network with mixed direct and contrarian route choice behaviors," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 603(C).
    7. Linde, Jona & Sonnemans, Joep & Tuinstra, Jan, 2014. "Strategies and evolution in the minority game: A multi-round strategy experiment," Games and Economic Behavior, Elsevier, vol. 86(C), pages 77-95.
    8. David Watling & Giulio Cantarella, 2015. "Model Representation & Decision-Making in an Ever-Changing World: The Role of Stochastic Process Models of Transportation Systems," Networks and Spatial Economics, Springer, vol. 15(3), pages 843-882, September.
    9. Rapoport, Amnon & Gisches, Eyran J. & Daniel, Terry & Lindsey, Robin, 2014. "Pre-trip information and route-choice decisions with stochastic travel conditions: Experiment," Transportation Research Part B: Methodological, Elsevier, vol. 68(C), pages 154-172.
    10. Qi, Hang & Jia, Ning & Qu, Xiaobo & He, Zhengbing, 2023. "Investigating day-to-day route choices based on multi-scenario laboratory experiments, Part I: Route-dependent attraction and its modeling," Transportation Research Part A: Policy and Practice, Elsevier, vol. 167(C).
    11. Sinuany-Stern, Z. & Stern, E. & Sfaradi, Z. & Holm, E., 1997. "The effect of information on commuters' behavior: A comparative micro-simulation approach," European Journal of Operational Research, Elsevier, vol. 96(3), pages 455-470, February.
    12. Adler, Jeffery L. & Recker, Wilfred W. & McNally, Michael G., 1992. "Using Interactive Simulation to Model Driver Behavior Under ATIS," University of California Transportation Center, Working Papers qt5180r2r6, University of California Transportation Center.
    13. Tang, Yue & Gao, Song & Ben-Elia, Eran, 2017. "An exploratory study of instance-based learning for route choice with random travel times," Journal of choice modelling, Elsevier, vol. 24(C), pages 22-35.
    14. Martin L. Hazelton & David P. Watling, 2004. "Computation of Equilibrium Distributions of Markov Traffic-Assignment Models," Transportation Science, INFORMS, vol. 38(3), pages 331-342, August.
    15. Adler, Jeffrey L. & McNally, Michael G. & Recker, Wilfred W., 1993. "Interactive Simulation for Modeling Dynamic Driver Behavior in Response to ATIS," University of California Transportation Center, Working Papers qt07g69621, University of California Transportation Center.
    16. Pietro Dindo & Jan Tuinstra, 2011. "A Class of Evolutionary Models for Participation Games with Negative Feedback," Computational Economics, Springer;Society for Computational Economics, vol. 37(3), pages 267-300, March.
    17. Linde, Jona & Gietl, Daniel & Sonnemans, Joep & Tuinstra, Jan, 2023. "The effect of quantity and quality of information in strategy tournaments," Journal of Economic Behavior & Organization, Elsevier, vol. 211(C), pages 305-323.
    18. Chen, Jin-Yong & Jiang, Rui & Li, Xin-Gang & Hu, Mao-Bin & Jia, Bin & Gao, Zi-You, 2019. "Morning commute problem with queue-length-dependent bottleneck capacity," Transportation Research Part B: Methodological, Elsevier, vol. 121(C), pages 184-215.
    19. Brownstone, David & McBride, Michael & Kong, Si-Yuan & Mahmassani, Amine, 2017. "Experimental Studies for Traffic Incident Management," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt6kx670mv, Institute of Transportation Studies, UC Berkeley.
    20. Chidambaram, Bhuvanachithra & Janssen, Marco A. & Rommel, Jens & Zikos, Dimitrios, 2014. "Commuters’ mode choice as a coordination problem: A framed field experiment on traffic policy in Hyderabad, India," Transportation Research Part A: Policy and Practice, Elsevier, vol. 65(C), pages 9-22.

    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:cdl:itsrrp:qt53d2t6df. 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: Lisa Schiff (email available below). General contact details of provider: https://edirc.repec.org/data/itucbus.html .

    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.