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

Pushkin Kachroo; Saumya Gupta; Shaurya Agarwal; Kaan Ozbay

doi:10.1109/TITS.2016.2601245

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

Pushkin Kachroo, Saumya Gupta, Shaurya Agarwal, Kaan Ozbay

Research output: Contribution to journal › Article › peer-review

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.

Original language	English (US)
Pages (from-to)	1234-1240
Number of pages	7
Journal	IEEE Transactions on Intelligent Transportation Systems
Volume	18
Issue number	5
DOIs	https://doi.org/10.1109/TITS.2016.2601245
State	Published - May 2017

Keywords

Optimal control
chattering
congestion pricing
logit
saturation function

ASJC Scopus subject areas

Automotive Engineering
Mechanical Engineering
Computer Science Applications

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10.1109/TITS.2016.2601245

Cite this

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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.",

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

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Keywords

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