¹School of Civil Engineering and Transportation, South China University of Technology, GuangZhou, Guangdong, 510640, China
²School of Electric Engineering and Automation, Jiangxi University of Science and Technology, Ganzhou, Jiangxi, 341000, China

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Abstract—This paper proposes a real-time traffic signal intelligent control method with transit-priority. The objective of this control method is to reduce the delays of passengers and special vehicles. Transit-priority is divided into the special transit-priority which is an absolute priority and the normal transit-priority which is a relative priority. When the detectors in the red phase detect special vehicles arrival, the phase will become a special phase, the current green phase must be interrupted, and the special phase will be run. After the special vehicles pass through, the next running phase selection will be done using the phase selection method with normal-transit-priority, by this time, the phase with more urgency will be selected. It embodies transit-priority idea. The green increase time of current phase is inferred by a fuzzy controller of which the inputs are the vehicles number of current phase and next phase. Multi-layer neural network is used to realize this fuzzy controller. Compared with fixed-time control method and the fuzzy control method, simulation research shows that this method obtains a good performance in decreasing the delays of passengers and special vehicles.

Index Terms—Traffic signal control, Transit-priority, Fuzzy Neural network, Traffic simulation

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Cite: Xianyan Kuang and Lunhui Xu, "Real-Time Traffic Signal Intelligent Control with Transit-Priority," Journal of Software vol. 7, no. 8, pp. 1738-1743, 2012.