Enhanced Scheduling for Real-Time Traffic Control

被引:0
作者
Quang-Vinh Dang [1 ]
Rudova, Hana [1 ]
机构
[1] Masaryk Univ, Fac Informat, Brno, Czech Republic
来源
2018 IEEE SYMPOSIUM SERIES ON COMPUTATIONAL INTELLIGENCE (IEEE SSCI) | 2018年
关键词
scheduling; traffic control; signal control; real-time; SIGNAL CONTROL; OPTIMIZATION;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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.
引用
收藏
页码:578 / 585
页数:8
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