Dynamic pricing for managed lanes with multiple entrances and exits

作     者：Pandey, Venktesh Boyles, Stephen D. 

作者机构：Univ Texas Austin Dept Civil Architectural & Environm Engn Austin TX 78712 USA 

出 版 物：《TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES》 (运输研究C部分：新兴技术)

年 卷 期：2018年第96卷第Nov.期

页      面：304-320页

核心收录：

学科分类：08[工学] 0823[工学-交通运输工程] 

基　　金：Data-Supported Transportation Operations and Planning University Transportation Center National Science Foundation Div Of Civil, Mechanical, & Manufact Inn Directorate For Engineering Funding Source: National Science Foundation 

主　　题：Managed lanes Dynamic pricing Route choices Approximate dynamic programming Value function approximation 

摘      要：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 (GPIs). 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.