Real Time Traffic Control: A Soft Computing Approach
نویسنده
چکیده
This paper describes Soft Computing approach to modeling time-dependent (dynamic, real time) transportation phenomenon characterized by uncertainty. The proposed “intelligent” control systems that are based on a combination of fuzzy logic (or neural networks) and mathematical programming (or heuristic) techniques make “on line” control decisions of the highest quality. In the first step of the proposed model, the best control strategies are developed off line for many different traffic patterns. These strategies are developed using mathematical programming or heuristic approach. In the second step, learning from the best strategies, fuzzy rule base is created from numerical data (or neural network is trained). Applications of the systems are considered for the stochastic vehicle routing, and real-time traffic control at the isolated intersection. Key-Words: Uncertainty Modeling, Fuzzy Sets, Neural Networks, Transportation, Traffic
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