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Stable local dynamics for day-to-day departure time choice

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  • Jin, Wen-Long

Abstract

Existing dynamical systems for day-to-day departure time choice are either unstable, or stable but assuming drivers to possess complete information and make decisions on both arrival and departure times. In this paper, we present a new dynamical system with local shifting of departure times, such that a driver only defers or advances his/her departure time to a time interval later or earlier with lower costs. We establish the asymmetrical upper bounds of the deferral and advance coefficients for the discrete model to be well-defined. We then derive the continuous version as a kinematic wave model and present some examples of symmetrical deferral and advance coefficients. We demonstrate that the stationary state of the dynamical system is the same as the user equilibrium, and the user equilibrium is proved with Lyapunov's second method to be stable for the symmetrical deferral and advance coefficients. With numerical examples, we verify the analytical results and examine the model's sensitivity to different factors with different combinations of heuristic asymmetrical coefficients and theoretically stable symmetrical coefficients. Both analytical and numerical results confirm that the new dynamical system is asymptotically stable in a stability region. This study provides some guidelines on how to derive new day-to-day dynamical system models of departure time user equilibrium. Such a dynamical system can potentially be applied to solve the general dynamic traffic assignment problem in the future.

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  • Jin, Wen-Long, 2021. "Stable local dynamics for day-to-day departure time choice," Transportation Research Part B: Methodological, Elsevier, vol. 149(C), pages 463-479.
    • Handle: RePEc:eee:transb:v:149:y:2021:i:c:p:463-479
    DOI: 10.1016/j.trb.2021.05.013
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    1. 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.

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