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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
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    References listed on IDEAS

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    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.
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    Citations

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    Cited by:

    1. Wenyun Tang & Lin Cheng, 2015. "Analyzing Multiday Route Choice Behavior using GPS Data," Working Papers 000135, University of Minnesota: Nexus Research Group.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    15. 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.
    16. 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.
    17. 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.
    18. 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.

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