Artificial intelligence techniques were applied to a traffic control problem on an urban road network and a method that optimizes signal timings was proposed. The method is separated into two processes, a training process and an optimization process. In the training process, two types of neural network model were used; a multilayer model and a Kohonen feature map model. The former model formed an input-output relationship between the timings and the objective function. The latter model improved the computational efficiency and the estimation precision. In the optimization process, to avoid the entrapment into a local minimum, two artificial intelligence methods were used; a Cauchy machine and a genetic algorithm. Signal timings were adjusted so as to minimize the total weighted sum of delay time and stop frequencies. The solutions were compared with those by a conventional method. The results here indicated that the AI models were useful for establishing advanced traffic control systems.<>
Artificial intelligence approach for optimizing traffic signal timings on urban road network
01.01.1994
326225 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
Artificial Intelligence Approach for Optimizing Traffic Signal Timings on Urban Road Network
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