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A Macroscopic Traffic Model Based on the Safe Velocity at Transitions

Autor(en):


Medium: Fachartikel
Sprache(n): Englisch
Veröffentlicht in: Civil Engineering Journal, , n. 6, v. 7
Seite(n): 1060-1069
DOI: 10.28991/cej-2021-03091710
Abstrakt:

The increasing volume of vehicles on the road has had a significant impact on traffic flow. Congestion in urban areas is now a major concern. To mitigate congestion, an accurate model is required which is based on realistic traffic dynamics. A new traffic model is proposed based on the conservation law of vehicles which considers traffic dynamics at transitions. Traffic alignment to forward conditions is affected by the time and distance between vehicles. Thus, the well-known Lighthill, Whitham, and Richards (LWR) model is modified to account for traffic behavior during alignment. A model for inhomogeneous traffic flow during transitions is proposed which can be used to characterize traffic evolution. The performance of the proposed model is compared with the LWR model using the Greenshields and Underwood target velocity distributions. These models are evaluated using the Godunov technique and numerical stability is guaranteed by considering the Courant, Friedrich, and Lewy (CFL) condition. The results obtained show that the proposed model characterizes the flow more realistically, and thus can provide better insight into traffic behavior for use in controlling congestion and pollution levels, and improving public safety. 

Copyright: © 2021 Zawar Hussain Khan, Thomas Aaron Gulliver, Waheed Imran
Lizenz:

Dieses Werk wurde unter der Creative-Commons-Lizenz Namensnennung 4.0 International (CC-BY 4.0) veröffentlicht und darf unter den Lizenzbedinungen vervielfältigt, verbreitet, öffentlich zugänglich gemacht, sowie abgewandelt und bearbeitet werden. Dabei muss der Urheber bzw. Rechteinhaber genannt und die Lizenzbedingungen eingehalten werden.

  • Über diese
    Datenseite
  • Reference-ID
    10610620
  • Veröffentlicht am:
    08.06.2021
  • Geändert am:
    10.06.2021
 
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