Traffic signal using smart agent system

Traffic signal - Traffic signal using smart agent system http/ signal using smart agent system-a0182288460

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Traffic signal using smart agent system INTRODUCTION Most urban areas nowadays experience severe traffic jams on street networks. As the traffic congestion spreads, there is a need to apply intelligent algorithms to diminish the waste of time, air pollution, and so on. Therefore, a traffic control system seeks to minimize the delay experienced by vehicle travelling through a road network of intersections by manipulating the traffic signal plans. There are various levels of sophistication in traffic signal control system using fuzzy traffic control. Agent-oriented fuzzy traffic control is a useful tool in designing traffic signal timing plans adaptively (1). In fact, agent technology was begun in the 1950s. Agent is a software that user achieves automatically wanting work. In particular, this is a concept that has been studied for a long time in artificial intelligence. From the late 1980s, a boundary that is an agent has been detached with artificial intelligence and exposed to individual study subject. Agent products have appeared since the early 1990s (2). A multi- agent system consists of multiple agents who are autonomous and make their decisions independently. By this definition, we rule out those systems where a central planner or designer controls the decision processes of local agents. If the agents' actions do not affect each others' outcomes, then we may as well consider the agents' situations independently (3). A multi-agent system offer certain advantages for problem solving : faster response, increased flexibility, robustness, resource sharing, and better adaptability (4), (5). Traffic signal control is also one of these applications (6), (7). A lot of technical research (8), (9), (10), (11) present fuzzy systems for a multi-way single intersection. In spite of traffic signal using fuzzy system, the control problem for network intersections still is an important issue in the field of traffic engineering (12). Fuzzy logic is derived from fuzzy set theory dealing with reasoning that is approximate rather than precisely deduced from classical predicate logic . It can be thought of as the application side of fuzzy set theory dealing with well thought out real world expert values for a complex problem (14). In 1990's, application of this method are widely used all over the world. The FLC (fuzzy logic control) uses three linguistic input variables and one linguistic output. The fuzzy input variables are the passed time of the current interval, the number of vehicles crossing an intersection during the green phase, and the length of queuing from the red direction. The extension time calculated using 27 fuzzy rules is the output. This FLC was simulated at less critical intersections. Gomide et al. proposed a FLC with adaptive strategies
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This note was uploaded on 01/25/2011 for the course EE 1001 taught by Professor Panda during the Spring '10 term at National University of Singapore.

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Traffic signal - Traffic signal using smart agent system http/ signal using smart agent system-a0182288460

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