Dynamic pricing for managed lanes with multiple entrances and exits |
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| Institution: | 1. Department of Civil and Environmental Engineering, University of Delaware, United States;2. John A. Reif, Jr. Department of Civil and Environmental Engineering, New Jersey Institute of Technology, United States;1. Master of Urban Planning, Harvard University, USA;2. Civil and Environmental Engineering, Stanford University, USA;3. Urban Planning and Public Policy, Harvard University, USA;1. The University of Texas at Austin, 301 E. Dean Keeton St. Stop C1761, Austin, TX, 78712, USA;2. University of New South Wales, Sydney, NSW, 2052, Australia;3. Ben-Gurion University of the Negev, Beer-Sheva, Israel;1. Institute for Transport Studies, University of Leeds, Leeds, England, United Kingdom;2. Ulster Business School, University of Ulster, Newtownabbey, Northern Ireland, United Kingdom;3. Dept. of Industrial Engineering and Management, Ben-Gurion University of the Negev, Israel |
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| Abstract: | 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. In this paper, we 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. We propose a lane choice model where travelers make online decisions at each diverge point considering all routes on a managed lane network. We formulate the problem as a deterministic Markov decision process and solve it using the value function approximation (VFA) method for different initializations. We compare the performance of the toll policies predicted by the VFA method against the myopic revenue policy which maximizes the revenue only at the current timestep and two heuristic policies based on the measured densities on the managed and general purpose lanes (GPLs). We test the results on four different test networks. The primary findings from our research suggest the usefulness of the VFA method for determining dynamic tolls. The best-found objective value from the method at its termination is better than other heuristics for all test networks with average improvements in the objective ranging between 10% and 90% for revenue maximization and 0–27% for TSTT minimization. Certain VFA initializations obtain best-found toll profiles within first 5–50 iterations which warrants computational time savings. Our findings also indicate that the revenue-maximizing optimal policies follow the “jam-and-harvest” behavior where the GPLs are 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. |
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| Keywords: | Managed lanes Dynamic pricing Route choices Approximate dynamic programming Value function approximation |
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