A reinforcement learning approach for distance‐based dynamic tolling in the stochastic network environment

Feng Zhu · Satish V. Ukkusuri

33 citations0/0 files storedJournal of Advanced Transportation

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Transportation Planning and Optimization Traffic control and management Traffic Prediction and Management Techniques

Abstract

Summary This paper proposes a novel dynamic tolling model based on distance and accounts for uncertain traffic demand and supply conditions. The distance‐based tolling controller is modeled as an intelligent agent interacting within the stochastic network environment dynamically by taking actions, which are to decide different distance‐based tolling rates of vehicles. The distance‐based tolls are determined according to various metrics, for example, total traffic flow throughput, delay time, vehicular emissions, which are set as objectives in the modeling framework. The optimal tolling rate is determined by an R‐Markov Average Reward Technique based reinforcement learning algorithm. In the numerical case study, we test the proposed tolling scheme on a benchmark test network—the Sioux Falls network—where specified links are candidate toll links. The result shows that the total travel time of tolling links reduces by 25% over simulation runs. Copyright © 2014 John Wiley & Sons, Ltd.

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2011Traffic congestion pricing methodologies and technologies 2005Mathematical and Economic Theory of Road Pricing 2003Simulation-Based Optimization: Parametric Optimization Techniques and Reinforcement Learning 2002A cell-based variational inequality formulation of the dynamic user optimal assignment problem 2003A cell-based simultaneous route and departure time choice model with elastic demand 2002The propagation of uncertainty through travel demand models: An exploratory analysis 2000Private toll roads: Competition under various ownership regimes 1997Analysis of the time-varying pricing of a bottleneck with elastic demand using optimal control theory

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2020Hierarchical density-based clustering methods for tolling zone definition and their impact on distance-based toll optimization 2018Dynamic pricing for managed lanes with multiple entrances and exits 2023Predictive distance-based road pricing — Designing tolling zones through unsupervised learning 2015Emission Modeling and Pricing in Dynamic Traffic Networks 2018Multiagent Reinforcement Learning Algorithm for Distributed Dynamic Pricing of Managed Lanes

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