Traffic signal timing optimization in connected vehicles environment

Wan Li; Xuegang Jeff Ban

doi:10.1109/IVS.2017.7995896

Traffic signal timing optimization in connected vehicles environment

Wan Li, Xuegang Jeff Ban

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

27 Scopus citations

Abstract

We study the traffic signal control problem under the connected vehicle (CV) environment by assuming a fixed cycle length so that the proposed model can be extended readily for the coordination of multiple signals. The signal control problem is to minimize the weighted sum of total system fuel consumption and travel times. Due to the large dimension of the problem and the complexity of the nonlinear car-following model, we propose a Dynamic programming (DP) formulation by dividing the timing decisions into stages (one stage for a phase) and approximating the fuel consumption and travel time of a stage as functions of the state and decision variables of the stage. We also propose a two-step method, the end stage cost, and a branch and bound algorithm, to make sure that the obtained optimal solution can lead to the fixed cycle length. Numerical experiments are provided to test the performance of the proposed model using data generated by traffic simulation.

Original language	English
Title of host publication	IV 2017 - 28th IEEE Intelligent Vehicles Symposium
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1330-1335
Number of pages	6
ISBN (Electronic)	9781509048045
DOIs	https://doi.org/10.1109/IVS.2017.7995896
State	Published - Jul 28 2017
Externally published	Yes
Event	28th IEEE Intelligent Vehicles Symposium, IV 2017 - Redondo Beach, United States Duration: Jun 11 2017 → Jun 14 2017

Publication series

Name	IEEE Intelligent Vehicles Symposium, Proceedings

Conference

Conference	28th IEEE Intelligent Vehicles Symposium, IV 2017
Country/Territory	United States
City	Redondo Beach
Period	06/11/17 → 06/14/17

Funding

This research is partially funded by the National Science Foundation (NSF) grant CMMI-1719551. Any opinions, findings, and conclusions or recommendations expressed in this paper are those of the authors and do not necessarily reflect the views of the NSF.

Keywords

Branch and Bound
Connected Vehicles
Dynamic Programming
Fuel Consumption Models
Traffic Signal Optimization

Access to Document

10.1109/IVS.2017.7995896

Cite this

@inproceedings{77b1dd420013440dacd7b32f7188a3da,

title = "Traffic signal timing optimization in connected vehicles environment",

abstract = "We study the traffic signal control problem under the connected vehicle (CV) environment by assuming a fixed cycle length so that the proposed model can be extended readily for the coordination of multiple signals. The signal control problem is to minimize the weighted sum of total system fuel consumption and travel times. Due to the large dimension of the problem and the complexity of the nonlinear car-following model, we propose a Dynamic programming (DP) formulation by dividing the timing decisions into stages (one stage for a phase) and approximating the fuel consumption and travel time of a stage as functions of the state and decision variables of the stage. We also propose a two-step method, the end stage cost, and a branch and bound algorithm, to make sure that the obtained optimal solution can lead to the fixed cycle length. Numerical experiments are provided to test the performance of the proposed model using data generated by traffic simulation.",

keywords = "Branch and Bound, Connected Vehicles, Dynamic Programming, Fuel Consumption Models, Traffic Signal Optimization",

author = "Wan Li and Ban, {Xuegang Jeff}",

note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 28th IEEE Intelligent Vehicles Symposium, IV 2017 ; Conference date: 11-06-2017 Through 14-06-2017",

year = "2017",

month = jul,

day = "28",

doi = "10.1109/IVS.2017.7995896",

language = "English",

series = "IEEE Intelligent Vehicles Symposium, Proceedings",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "1330--1335",

booktitle = "IV 2017 - 28th IEEE Intelligent Vehicles Symposium",

}

Li, W & Ban, XJ 2017, Traffic signal timing optimization in connected vehicles environment. in IV 2017 - 28th IEEE Intelligent Vehicles Symposium., 7995896, IEEE Intelligent Vehicles Symposium, Proceedings, Institute of Electrical and Electronics Engineers Inc., pp. 1330-1335, 28th IEEE Intelligent Vehicles Symposium, IV 2017, Redondo Beach, United States, 06/11/17. https://doi.org/10.1109/IVS.2017.7995896

Traffic signal timing optimization in connected vehicles environment. / Li, Wan; Ban, Xuegang Jeff.
IV 2017 - 28th IEEE Intelligent Vehicles Symposium. Institute of Electrical and Electronics Engineers Inc., 2017. p. 1330-1335 7995896 (IEEE Intelligent Vehicles Symposium, Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Traffic signal timing optimization in connected vehicles environment

AU - Li, Wan

AU - Ban, Xuegang Jeff

PY - 2017/7/28

Y1 - 2017/7/28

N2 - We study the traffic signal control problem under the connected vehicle (CV) environment by assuming a fixed cycle length so that the proposed model can be extended readily for the coordination of multiple signals. The signal control problem is to minimize the weighted sum of total system fuel consumption and travel times. Due to the large dimension of the problem and the complexity of the nonlinear car-following model, we propose a Dynamic programming (DP) formulation by dividing the timing decisions into stages (one stage for a phase) and approximating the fuel consumption and travel time of a stage as functions of the state and decision variables of the stage. We also propose a two-step method, the end stage cost, and a branch and bound algorithm, to make sure that the obtained optimal solution can lead to the fixed cycle length. Numerical experiments are provided to test the performance of the proposed model using data generated by traffic simulation.

AB - We study the traffic signal control problem under the connected vehicle (CV) environment by assuming a fixed cycle length so that the proposed model can be extended readily for the coordination of multiple signals. The signal control problem is to minimize the weighted sum of total system fuel consumption and travel times. Due to the large dimension of the problem and the complexity of the nonlinear car-following model, we propose a Dynamic programming (DP) formulation by dividing the timing decisions into stages (one stage for a phase) and approximating the fuel consumption and travel time of a stage as functions of the state and decision variables of the stage. We also propose a two-step method, the end stage cost, and a branch and bound algorithm, to make sure that the obtained optimal solution can lead to the fixed cycle length. Numerical experiments are provided to test the performance of the proposed model using data generated by traffic simulation.

KW - Branch and Bound

KW - Connected Vehicles

KW - Dynamic Programming

KW - Fuel Consumption Models

KW - Traffic Signal Optimization

UR - http://www.scopus.com/inward/record.url?scp=85028040369&partnerID=8YFLogxK

U2 - 10.1109/IVS.2017.7995896

DO - 10.1109/IVS.2017.7995896

M3 - Conference contribution

AN - SCOPUS:85028040369

T3 - IEEE Intelligent Vehicles Symposium, Proceedings

SP - 1330

EP - 1335

BT - IV 2017 - 28th IEEE Intelligent Vehicles Symposium

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 28th IEEE Intelligent Vehicles Symposium, IV 2017

Y2 - 11 June 2017 through 14 June 2017

ER -

Traffic signal timing optimization in connected vehicles environment

Abstract

Publication series

Conference

Funding

Keywords

Access to Document

Other files and links

Fingerprint

Cite this