Fuzzy Q-Learning Traffic Light Control based on Traffic Flow and Pedestrian Number Estimated from Visual Information
محل انتشار: مجله مهندسی کامپیوتر و دانش، دوره: 2، شماره: 1
سال انتشار: 1398
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 458
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شناسه ملی سند علمی:
JR_CKE-2-1_005
تاریخ نمایه سازی: 3 اسفند 1398
چکیده مقاله:
A vision-based intelligent traffic control system is a robust framework that controls the traffic flow in real-time by estimating the traffic density near traffic lights. In thispaper, a traffic light control system based on fuzzy Qlearning is proposed according to the vehicle density and the pedestrian number estimated from the visual information.The aim of proposed approach is to minimize the pedestrian and the car waiting time and maximize throughput for an isolated 4-way traffic intersection. Also, the pedestriantraffic light is controlled based on the fuzzy logic. The states and actions of the Q-learning variables are set by a fuzzy algorithm which can be learned through environmentalinteractions. The system can detect the number of pedestrians and vehicles using visual information from cameras and machine vision algorithms. The fuzzy controlsystem can adjust the sequence of green phases to decrease the total waiting time and the mean of the queue length. The proposed algorithm was simulated for one hour for each of 14 different traffic conditions and was assessed and compared with the preset cycle time and vehicle actuated approaches. The results showed the proposed algorithmcould decrease the total waiting time and the mean of the queue length effectively.
کلیدواژه ها:
نویسندگان
Marjan Jalali Moghaddam
M. S. Computer Engineering Department, Amirkabir University of Technology, Tehran, Iran
Matin Hosseini
Assistant Professor, Computer Engineering Department, Amirkabir University of Technology, Tehran, Iran.
Reza Safabakhsh
Associate Professor, Computer Engineering Department, Amirkabir University of Technology, Tehran, Iran.