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۱Modeling and Signal Control of Single Intersections by Fuzzy Logic Controller
نویسنده(ها): ،
اطلاعات انتشار: دوازدهمین کنفرانس دانشجویی مهندسی برق، سال
تعداد صفحات: ۶
State – space equations were applied to formulate the total wait time vehicles in traffic network at a single intersection in thes paper. The signal comtrol of a single intersection was then modeled as a discrete time optimal control problem . However , the results of qualitative analysis were used to design a fuzzy signal controller. The fuzzy logic controller (FLC) presented in thes paper simulates the control logic of experienced human traffic comtrollers such as polece officers. Simulation results open and close loop intersection show that the controller substantially reduces the total wait time vehecles compared to fixed – time comtrol.<\div>

۲Design of a Novel Expert System in Multilane Urban Traffic Network by Fuzzy Logic
نویسنده(ها): ،
اطلاعات انتشار: یازدهمین کنفرانس سیستم های فازی ایران، سال
تعداد صفحات: ۸
This paper presents a novel expert system in multilane urban traffic network by fuzzy logic. The modeling and controling of isolated signalized intersection is done by fuzzy sets theory. The controller is developed based on the waiting time and vehicles queue length at current green phase, and vehicles queue lengths at the other phases. The controller controls the traffic light timings and phase sequence to ensure smooth flow of traffic with minimal waiting time and queue length. Usually fuzzy traffic controllers are optimized to maximize traffic flows\minimize traffic waiting time under typical traffic conditions. Consequentially, these are not the optimal traffic controllers under exceptional traffic cases such as roadblocks and road accidents. In this research, we apply State–space equations to formulate the average waiting time vehicles in traffic network at fixed time control and propose a novel expert system by fuzzy modeling and new fuzzy traffic controller that can optimally control traffic flows under both normal and exceptional traffic conditions. In the end, by comparing the experimental result obtained by the Fixed–time Controller and Fuzzy Traffic Controller which improves significant performance for proposed fuzzy expert system, we confirmed the efficiency of our intelligent controller based fuzzy inference system.<\div>
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