Enhanced Scheduling for Real-Time Traffic Control

DANG, Vinh Quang and Hana RUDOVÁ. Enhanced Scheduling for Real-Time Traffic Control. In 2018 IEEE Symposium Series on Computational Intelligence (SSCI). Bengaluru, India: IEEE, 2018, p. 578-585. ISBN 978-1-5386-9276-9. Available from: https://dx.doi.org/10.1109/SSCI.2018.8628731.

Basic information

Original name

Enhanced Scheduling for Real-Time Traffic Control

Authors

DANG, Vinh Quang (704 Viet Nam, guarantor, belonging to the institution) and Hana RUDOVÁ (203 Czech Republic, belonging to the institution)

Edition

Bengaluru, India, 2018 IEEE Symposium Series on Computational Intelligence (SSCI), p. 578-585, 8 pp. 2018

Publisher

IEEE

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Other information

Language

English

Type of outcome

Stať ve sborníku

Field of Study

10201 Computer sciences, information science, bioinformatics

Country of publisher

United States of America

Confidentiality degree

není předmětem státního či obchodního tajemství

Publication form

printed version "print"

References:

URL

RIV identification code

RIV/00216224:14330/18:00103562

Organization unit

Faculty of Informatics

ISBN

978-1-5386-9276-9

DOI

http://dx.doi.org/10.1109/SSCI.2018.8628731

UT WoS

000459238800079

Keywords in English

Scheduling; Traffic control; Signal control; Real-time

Tags

International impact, Reviewed

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Abstract

V originále

Traffic signal control in road networks is a practical problem which has been widely studied. In this paper, we present an approach for traffic signal control extending ideas of schedule-driven coordination in the system Surtrac. The traffic signal control problem of one intersection is modeled as a parallel machine scheduling problem based on aggregation of traffic flow data. The solution procedure for each parallel machine scheduling problem is based on a forward dynamic programming search. All connected intersections form a distributed system of communicating intersections. The objective is to construct a traffic control sequence for each intersection and minimize the total cumulative delay of all vehicles in the traffic network. Simulation results for a grid network from the SUMO simulator demonstrate the performance of the proposed approach in comparison to the Surtrac system solving the problem using single machine scheduling. The results show a significant improvement in the total cumulative delay given the increase of computational time which is acceptable in real-time processing.