Dynamic Pricing for Managed Lanes with Multiple Entrances and Exits

Priced managed lanes are increasingly being used to better utilize the existing capacity of the roadway to relieve congestion and offer reliable travel time to road users. The authors investigate the optimization problem for pricing managed lanes with multiple entrances and exits which seeks to maximize the revenue and minimize the total system travel time (TSTT) over a finite horizon. The authors formulate the problem as a deterministic Markov decision process (MDP) and solve it using the value function approximation (VFA) method under different levels of aggregation. They compare the performance of the toll policies predicted by the VFA method against the myopic revenue policies which maximize the revenue only at the current time step and two heuristic policies based on the measured densities on the managed and general purpose (GP) lanes. The results are tested on two different test networks. The primary findings from the research suggest the usefulness of the VFA method in determining policies closer to the optimal. The converged objective value from the VFA method is better than other heuristics for both test networks. The authors also find that the rate of convergence is different for different levels of aggregation. Last, the findings indicate that the revenue-maximizing optimal policies follow the ``jam-and-harvest" behavior where the GP lane is pushed towards congestion in the earlier time steps to generate higher revenue in the later time steps, a characteristic not observed for the policies minimizing TSTT.

  • Supplemental Notes:
    • This paper was sponsored by TRB committee ABE25 Standing Committee on Congestion Pricing.
  • Authors:
    • Pandey, Venktesh
    • Boyles, Stephen D
  • Conference:
  • Date: 2018

Language

  • English

Media Info

  • Media Type: Digital/other
  • Features: Figures; References; Tables;
  • Pagination: 17p

Subject/Index Terms

Filing Info

  • Accession Number: 01660976
  • Record Type: Publication
  • Report/Paper Numbers: 18-06306
  • Files: TRIS, TRB, ATRI
  • Created Date: Feb 22 2018 9:19AM