Publication details
Enhanced Scheduling for Real-Time Traffic Control
| Authors | |
|---|---|
| Year of publication | 2018 |
| Type | Article in Proceedings |
| Conference | 2018 IEEE Symposium Series on Computational Intelligence (SSCI) |
| MU Faculty or unit | |
| Citation | |
| web | https://ieeexplore.ieee.org/abstract/document/8628731 |
| Doi | http://dx.doi.org/10.1109/SSCI.2018.8628731 |
| Keywords | Scheduling; Traffic control; Signal control; Real-time |
| Description | 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. |