Transportation has always been an important aspect of human civilization. With the rapid increase in economy, more and more vehicles are running in the urban traffic networks and bring some problems to the cities, such as traffic congestion, delay, pollution and accidents. In order to solve these problems, we need to maximize the utilization of existing roads. With the development of artificial intelligence technology, expert systems, fuzzy logics, neural networks and genetic algorithms are applied in traffic signal control field to overcome the deficiency of traditional traffic signal control systems. In order to find an urban traffic signal control algorithm with better performance to minimize traffic delays, fuzzy logic control and adaptive dynamic programming are studied. Main works and contributions of this paper are: 1. An adaptive dynamic programming method for optimizing green light times of a single traffic intersection is designed. Simulation results show that adaptive dynamic programming is suitable for solving such nonlinear discrete system control problems. 2. A fuzzy logic traffic signal controller is designed for a single intersection. This controller considers vehicle queues of four phases, and adopts the advantages of actuated control strategies. In order to solve signal control problems under various traffic conditions, the fuzzy logic controller and actuated controller are tested under constant traffic flows and flow with sudden changes. Simulation results show that this fuzzy logic controller performs better in reducing traffic delay than the actuated controller. 3. Adaptive dynamic programming is used to optimize the above fuzzy logic controller. A fuzzy logic controller with adaptive dynamic programming optimization (ADPFLC) is designed and studied under the same traffic conditions with the original fuzzy logic controller (FLC). Simulation results show that the ADPFLC performs better than the original FLC. 4. The advantages, disadvantages, and some other problems of fuzzy logic control and adaptive dynamic programming using in traffic signal control are summarized.
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