Optimal Control for Congestion Pricing

Theory, Simulation, and Evaluation

Pushkin Kachroo, Saumya Gupta, Shaurya Agarwal, Kaan Ozbay

Research output: Contribution to journalArticle

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 languageEnglish (US)
Article number7558128
JournalIEEE Transactions on Intelligent Transportation Systems
VolumePP
Issue number99
DOIs
StatePublished - Sep 1 2016

Fingerprint

Control theory
Cost functions
Costs
Conservation

Keywords

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

ASJC Scopus subject areas

  • Automotive Engineering
  • Mechanical Engineering
  • Computer Science Applications

Cite this

Optimal Control for Congestion Pricing : Theory, Simulation, and Evaluation. / Kachroo, Pushkin; Gupta, Saumya; Agarwal, Shaurya; Ozbay, Kaan.

In: IEEE Transactions on Intelligent Transportation Systems, Vol. PP, No. 99, 7558128, 01.09.2016.

Research output: Contribution to journalArticle

Kachroo, Pushkin ; Gupta, Saumya ; Agarwal, Shaurya ; Ozbay, Kaan. / Optimal Control for Congestion Pricing : Theory, Simulation, and Evaluation. In: IEEE Transactions on Intelligent Transportation Systems. 2016 ; Vol. PP, No. 99.
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