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A general stochastic process for day-to-day dynamic traffic assignment: Formulation, asymptotic behaviour, and stability analysis

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  • Cantarella, Giulio E.
  • Watling, David P.

Abstract

This paper presents a general modelling approach to day-to-day dynamic assignment to a congested network through discrete-time stochastic and deterministic process models including an explicit modelling of users’ habit as a part of route choice behaviour, through an exponential smoothing filter, and of their memory of network conditions on past days, through a moving average or an exponentially smoothing filter. An asymptotic analysis of the mean process is carried out to provide a better insight. Results of such analyses are also used for deriving conditions, about values of the system parameters, assuring that the mean process is dissipative and/or converges to some kind of attractor. Numerical small examples are also provided in order to illustrate the theoretical results obtained.

Suggested Citation

  • Cantarella, Giulio E. & Watling, David P., 2016. "A general stochastic process for day-to-day dynamic traffic assignment: Formulation, asymptotic behaviour, and stability analysis," Transportation Research Part B: Methodological, Elsevier, vol. 92(PA), pages 3-21.
  • Handle: RePEc:eee:transb:v:92:y:2016:i:pa:p:3-21
    DOI: 10.1016/j.trb.2016.05.005
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    References listed on IDEAS

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    Cited by:

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    2. Li, Ruijie & Liu, Xiaobo & Nie, Yu (Marco), 2018. "Managing partially automated network traffic flow: Efficiency vs. stability," Transportation Research Part B: Methodological, Elsevier, vol. 114(C), pages 300-324.
    3. 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).
    4. Vittorio Astarita & Ciro Caliendo & Vincenzo Pasquale Giofrè & Isidoro Russo, 2020. "Surrogate Safety Measures from Traffic Simulation: Validation of Safety Indicators with Intersection Traffic Crash Data," Sustainability, MDPI, vol. 12(17), pages 1-21, August.
    5. Satsukawa, Koki & Wada, Kentaro & Iryo, Takamasa, 2020. "Reprint of “Stochastic stability of dynamic user equilibrium in unidirectional networks: Weakly acyclic game approach”," Transportation Research Part B: Methodological, Elsevier, vol. 132(C), pages 117-135.
    6. Guo, Ren-Yong & Szeto, W.Y., 2018. "Day-to-day modal choice with a Pareto improvement or zero-sum revenue scheme," Transportation Research Part B: Methodological, Elsevier, vol. 110(C), pages 1-25.
    7. Barroso, Joana Maia Fernandes & Albuquerque-Oliveira, João Lucas & Oliveira-Neto, Francisco Moraes, 2020. "Correlation analysis of day-to-day origin-destination flows and traffic volumes in urban networks," Journal of Transport Geography, Elsevier, vol. 89(C).
    8. Ren-Yong Guo & Hai Yang & Hai-Jun Huang, 2018. "Are We Really Solving the Dynamic Traffic Equilibrium Problem with a Departure Time Choice?," Transportation Science, INFORMS, vol. 52(3), pages 603-620, June.
    9. 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).
    10. Satsukawa, Koki & Wada, Kentaro & Iryo, Takamasa, 2019. "Stochastic stability of dynamic user equilibrium in unidirectional networks: Weakly acyclic game approach," Transportation Research Part B: Methodological, Elsevier, vol. 125(C), pages 229-247.
    11. Liu, Peng & Liao, Feixiong & Tian, Qiong & Huang, Hai-Jun & Timmermans, Harry, 2020. "Day-to-day needs-based activity-travel dynamics and equilibria in multi-state supernetworks," Transportation Research Part B: Methodological, Elsevier, vol. 132(C), pages 208-227.
    12. Santos Sánchez-Cambronero & Fernando Álvarez-Bazo & Ana Rivas & Inmaculada Gallego, 2021. "Dynamic Route Flow Estimation in Road Networks Using Data from Automatic Number of Plate Recognition Sensors," Sustainability, MDPI, vol. 13(8), pages 1-30, April.
    13. Zhong, R.X. & Xie, X.X. & Luo, J.C. & Pan, T.L. & Lam, W.H.K. & Sumalee, A., 2020. "Modeling double time-scale travel time processes with application to assessing the resilience of transportation systems," Transportation Research Part B: Methodological, Elsevier, vol. 132(C), pages 228-248.
    14. Borja Alonso & Vittorio Astarita & Luigi Dell’Olio & Vincenzo Pasquale Giofrè & Giuseppe Guido & Marcella Marino & William Sommario & Alessandro Vitale, 2020. "Validation of Simulated Safety Indicators with Traffic Crash Data," Sustainability, MDPI, vol. 12(3), pages 1-22, January.
    15. Guo, Ren-Yong & Yang, Hai & Huang, Hai-Jun & Li, Xinwei, 2018. "Day-to-day departure time choice under bounded rationality in the bottleneck model," Transportation Research Part B: Methodological, Elsevier, vol. 117(PB), pages 832-849.
    16. Sun, Mingmei, 2023. "A day-to-day dynamic model for mixed traffic flow of autonomous vehicles and inertial human-driven vehicles," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 173(C).

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