Design and Simulation of Agent-Oriented Intersection
CSSE '08 Proceedings of the 2008 International Conference on Computer Science and Software Engineering - Volume 01
Neural Networks for Real-Time Traffic Signal Control
IEEE Transactions on Intelligent Transportation Systems
Distributed and cooperative fuzzy controllers for trafficintersections group
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Two-Stage Fuzzy Logic Controller for Signalized Intersection
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
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Every day growth of the vehicles has become one of the biggest problems of urbanism especially in major cities. This can waste people's time, increase the fuel consumption, air pollution, and increase the density of cars and vehicles. To improve this problem, we first designed a comprehensive model of urban traffic network in this article, using state space equations and SIMULINK Program MATLAB and then by using a novel algorithm, two fuzzy controllers for controlling traffic light in a two phase isolated intersection in the multi Variable Control System. In this system, types of sensors is video detection, they are placed strategically at incoming and outgoing legs lanes and the controller utilize the information received from these sensors to make optimal decisions to minimize the goal function. The simulation results show that TASFC Traffic Actuated Signal Fuzzy Control had a great improvement in 6 different traffic conditions such as certain, uncertain, using random data, and in 3 different traffic conditions using the real case study of EBADI-KASHANI intersection in Mashhad, Iran, in comparison with the fixed time controller, real operation of Australian SCATS system and FSCS Fuzzy Signal Control System system in previous work for estimation of the goal function which is minimizing the queue length and the delay time of the vehicles.