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Simulation study of vehicle travel time on route with signals considering comprehensive influencing factors

Author

Listed:
  • Lv, Wei
  • Zhou, Xu
  • Fang, Zhiming
  • Huo, Feizhou
  • Li, Xiaolian

Abstract

Vehicle travel time is widely regarded as an important performance of the road traffic as well as a significant decision factors for travelers. While the travel time is variable because of the stochastic factors such as traffic flow, signals, and some other emergency conditions. Considering the dynamic characteristics of road traffic flow and the importance of shortening travel time for emergency transport task, in this paper, a basic vehicle travel time model based on empirical velocity–density function is established, in which the travel time is divided into road running time and signal waiting time. Simulations based on the basic model are conducted to investigate the comprehensive effect of the multiple factors on the travel time, such as traffic density, number of signals, circle time, green ratio and offset time between adjacent signals. A green-wave traffic objective-oriented method is also explored to achieve the shortest travel time. The results demonstrate that plateaus and sloped plateaus would appear under the comprehensive influence of both traffic density and traffic light number or signal parameters. It is found there is a minimum traffic time with a certain offset time under different traffic density when the traffic lights on a route do not change synchronously. The fitting formula and theoretical formula for the optimal offset time are also proposed, which can be used to achieve green-wave traffic in a practical case.

Suggested Citation

  • Lv, Wei & Zhou, Xu & Fang, Zhiming & Huo, Feizhou & Li, Xiaolian, 2019. "Simulation study of vehicle travel time on route with signals considering comprehensive influencing factors," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 530(C).
    • Handle: RePEc:eee:phsmap:v:530:y:2019:i:c:s037843711930809x
    DOI: 10.1016/j.physa.2019.121389
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    Cited by:

    1. Shao, Feng & Shao, Hu & Wang, Dongle & Lam, William H.K. & Cao, Shuhan, 2023. "A generative model for vehicular travel time distribution prediction considering spatial and temporal correlations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 621(C).
    2. Shao, Feng & Shao, Hu & Wang, Dongle & Lam, William H.K., 2024. "A multi-task spatio-temporal generative adversarial network for prediction of travel time reliability in peak hour periods," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 638(C).

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