A Two-Stage Fuzzy Logic Control Method of Traffic Signal Based on Traffic Urgency Degree

Abstract

City intersection traffic signal control is an important method to improve the efficiency of road network and alleviate traffic congestion. This paper researches traffic signal fuzzy control method on a single intersection. A two-stage traffic signal control method based on traffic urgency degree is proposed according to two-stage fuzzy inference on single intersection. At the first stage, calculate traffic urgency degree for all red phases using traffic urgency evaluation module and select the red light phase with large traffic urgency as the next phase to switch. At the second stage, green delay of the current green phase is determined by fuzzy inference based on the amount of vehicles of current green phase and next green phase. The average vehicle delays are used to evaluate the performance of the fuzzy signal controller. Finally, comparisons have been made with pretimed controller and fuzzy logic controller without considering the urgency of red phase. Simulation results show the performance of our proposed method.

Improving traffic and emergency vehicle clearence at congested intersections using fuzzy inference engine

“…Other remarkable works in this area include [6][7][8][9][10][11] in which the designed fuzzy controllers reduced the average waiting time of vehicles as compared to pre-timed traditional systems. A two -stage fuzzy traffic signal control method [12] was suggested and compared with pre timed control method.…”

“…This made the system less complex and ease of physical implementation. The cost and complexity of the systems [12][13][14][15][16][17][18][19] due to large scale of inputs required was taken care in the proposed design as the system requires inputs in terms of the traffic volume sensed at each lane and detection of EMV. The proposed system in this paper is designed in a way to achieve simplicity in collection of inputs and easy implementation for both busy and underutilized intersection.…”

A Survey of Intelligent Transportation Systems

“…The results indicated that the developed control system has a potential to improve operations at intersections. Also, in 2014, Ge [25] proposed a fuzzy control system for a single four phases simple intersection to specify the next phase to switch based on the urgency degree that was calculated through the red phases. The average vehicle delays were used to measure the control system performance.…”

An Adaptive Fuzzy-Logic Traffic Control System in Conditions of Saturated Transport Stream

“…That is, it is necessary to find such parameters of the traffic control system that the total delay at the crossroads is minimal [ 12 , 13 ]: or under the constraints where f ∗ ( u i 13 , λ i 13 ) and f pn ∗ ( u i 13 , l i 13 ) are the delay evaluation function and penalty function for the length of queue in front of the stop line of the traffic light in directions 1 and 3, respectively; f ∗ ( u i 24 , λ i 24 ) and f pn ∗ ( u i 24 , l i 24 ) are the delay evaluation function and penalty function for the length of queue in front of the stop line of the traffic light in directions 2 and 4, respectively; u i is the duration of green signal of traffic light in the i-stage ; q i left(13) , q i arriv(13) , q i left(24) , and q i arriv(24) are the number of vehicles entered and left the control zone at the crossroad in the i th phase, respectively; u min and u max are the minimum and maximum duration of the green signal of the traffic light, respectively; l i 13 and l i 24 are the length of the queue in front of the stop line at directions 1 and 3 and 2 and 4 in the i th stage, respectively; L max is the maximum allowed length of the queue in front of the stop line.…”