Dynamic Mixed Information Strategy for Heterogeneous Network Users and System Optimal Design

Current Dynamic Traffic Assignment (DTA) research typically considers non-competing groups of drivers seeking either Dynamic User Equilibrium (DUE) or Dynamic System Optimal (DSO) equilibrium. Real-world solutions for minimizing congestion by routing heterogeneous road users under mixed information frameworks require more reliable and robust methods for heterogeneous users' decision-making. This research provides a methodology for reducing congestion using the competing strategies of DUE and DSO seeking drivers. A realistic simulation of the responses of drivers to sudden road network perturbations is presented by applying Dynamic Traffic Assignment (DTA) to two groups of drivers; informed and uninformed. A navigation app provides within-day route suggestions to informed drivers using information about the time-varying decision-making habits of uninformed drivers. These within-day route suggestions cause some informed users to detour from their initially proposed routes in order to minimize network congestion and delays, pushing the system toward DSO equilibrium, while uninformed drivers make day-to-day (DTD) decisions which push the system toward DUE. Simulations considering varying fractions of informed drivers show that congestion is reduced by approximately 59.2% when 20% of drivers are informed, and is nearly eliminated when 80% of drivers are informed. The computational efficiency of this approach is also improved using shared memory multi-core parallelization.

Language

  • English

Media Info

  • Media Type: Digital/other
  • Features: Figures; References;
  • Pagination: 27p

Subject/Index Terms

Filing Info

  • Accession Number: 01764080
  • Record Type: Publication
  • Report/Paper Numbers: TRBAM-21-02070
  • Files: TRIS, TRB, ATRI
  • Created Date: Dec 23 2020 11:19AM