Optimal Control for Congestion Pricing: Theory, Simulation, and Evaluation

Authors

Pushkin Kachroo, University of Nevada, Las VegasFollow
S Gupta, University of Nevada, Las VegasFollow
S Agarwal, California State University, Los AngelesFollow
K Ozbay, New York UniversityFollow

Document Type

Article

Publication Date

1-1-2016

Publication Title

IEEE Transactions on Intelligent Transportation Systems

Volume

PP

Issue

99

Abstract

This paper presents a mathematical framework for dynamic congestion pricing. The objective is to calculate an optimal toll using the optimal control theory. The problem consists of tolled lanes or routes and alternate non-tolled lanes or routes. The model is developed using a traffic conservation law, the queuing theory, and fundamental macroscopic relationships. A logit model is used for establishing the relationship between the price and the driver's choice behavior. We design a cost function and then use Hamilton-Jacobi-Bellman equation to derive an optimal control law that uses real-time information to determine an optimal tolling price. Simulations are performed to demonstrate the performance of this optimal control congestion-pricing algorithm. © 2016 IEEE.

Keywords

chattering; congestion pricing; logit; Optimal control; saturation function

Language

English

Repository Citation

Kachroo, P., Gupta, S., Agarwal, S., Ozbay, K. (2016). Optimal Control for Congestion Pricing: Theory, Simulation, and Evaluation. IEEE Transactions on Intelligent Transportation Systems, PP(99),
http://dx.doi.org/10.1109/TITS.2016.2601245