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) |
|---|---|
| Article number | 7558128 |
| Journal | IEEE Transactions on Intelligent Transportation Systems |
| Volume | PP |
| Issue number | 99 |
| DOIs | |
| State | Published - Sep 1 2016 |
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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 journal › Article
}
TY - JOUR
T1 - Optimal Control for Congestion Pricing
T2 - Theory, Simulation, and Evaluation
AU - Kachroo, Pushkin
AU - Gupta, Saumya
AU - Agarwal, Shaurya
AU - Ozbay, Kaan
PY - 2016/9/1
Y1 - 2016/9/1
N2 - 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.
AB - 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.
KW - chattering
KW - congestion pricing
KW - logit
KW - Optimal control
KW - saturation function
UR - http://www.scopus.com/inward/record.url?scp=85029019062&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85029019062&partnerID=8YFLogxK
U2 - 10.1109/TITS.2016.2601245
DO - 10.1109/TITS.2016.2601245
M3 - Article
VL - PP
JO - IEEE Transactions on Intelligent Transportation Systems
JF - IEEE Transactions on Intelligent Transportation Systems
SN - 1524-9050
IS - 99
M1 - 7558128
ER -