Multiclass multilane model for freeway traffic mixed with connected automated vehicles and regular human-piloted vehicles

Tianlu Pan, William H.K. Lam, Agachai Sumalee, Renxin Zhong

Research output: Journal article publicationJournal articleAcademic researchpeer-review

10 Citations (Scopus)

Abstract

In view of the advantages and a promising market prospect of the emerging connected automated vehicles (CAVs), it will be very likely that the roadway is shared by CAVs and RHVs in the near future. To support traffic control design, this paper develops a multiclass multilane cell transmission model (CTM) to simulate traffic flow dynamics mixed with CAVs and RHVs by capturing the interaction between the two vehicle classes. First, headway distributions and variations in the fundamental diagram with respect to different penetration rates of CAVs are quantified. Then, the minimum headway acceptance criteria are determined for the lane changing (LC) maneuvers proposed by CAVs and RHVs with consideration on drivers’ anticipation. Finally, the cell-lane-specific multiclass flow conservation law is developed to propagate traffic flow and density considering the vehicle LC maneuvers. Numerical simulations explore the potential operational capacity increase, delay reduction, and traffic flow smoothing under several penetration scenarios.

Original languageEnglish
JournalTransportmetrica A: Transport Science
DOIs
Publication statusAccepted/In press - 1 Jan 2019

Keywords

  • capacity variation
  • connected automated vehicle (CAV)
  • multiclass multilane cell transmission model
  • penetration rate
  • Vehicle automation and communication system (VACS)

ASJC Scopus subject areas

  • Transportation
  • Engineering(all)

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