期刊
IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY
卷 24, 期 3, 页码 830-842出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TCST.2015.2468181
关键词
Optimization; perturbation analysis; stochastic hybrid systems (SHSs); traffic light control (TLC); traffic signal systems; transportation systems
资金
- National Science Foundation [CNS-1239021, IIP-1430145]
- Air Force Office of Scientific Research [FA9550-12-1-0113]
- Office of Naval Research [N00014-09-1-1051]
- Cyprus Research Promotion Foundation through the New Infrastructure Project [Strategic/0308/26]
- Directorate For Engineering
- Div Of Electrical, Commun & Cyber Sys [1239021] Funding Source: National Science Foundation
- Div Of Industrial Innovation & Partnersh
- Directorate For Engineering [1430145] Funding Source: National Science Foundation
We consider the traffic light control problem for a single intersection modeled as a stochastic hybrid system. We study a quasi-dynamic policy based on partial state information defined by detecting whether vehicle backlogs are above or below certain thresholds. The policy is parameterized by green and red cycle lengths as well as the road content thresholds. Using infinitesimal perturbation analysis, we derive online gradient estimators of a cost metric with respect to the controllable light cycles and threshold parameters and use these estimators to iteratively adjust all the controllable parameters through an online gradient-based algorithm so as to improve the overall system performance under various traffic conditions. The results obtained by applying this methodology to a simulated urban setting are also included.
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