2018Digital Signal ProcessingRequires access

Efficient Way to Control Road Traffic Using Fuzzy Logic

I. Gobi, Devender Kumar

Open publisher page 2 citations

Abstract

Traffic through road travel makes congestion in roads causes’ major problem to road users. This is due to regular use of vehicles through the cities and waits in traffic signal for a long time which makes traffic impasse. To manage this problem many traffic control system have been developed. Due to increase in vehicles the traffic controlling demand are high. To control these traffic new techniques was proposed and named as Efficient Road Traffic Controller (ERTC) which efficiently reduces congestion in traffic signal. The research model will control the traffic by the adjustment of time and phase of the traffic lights by the situation of traffic intersection and controlled by indication to the applying model. This paper gives a brief discussion of the procedures we adopted to develop an intelligent fuzzy control system for dealing with the road traffic congestion problem. Specialized node is used in the congestion road traffic which is known as Local Cognitive Node (LCN) implements the learning components and decision making. Fuzzy logic technology is used to develop the system with Cognitive sensor node where these nodes use learning mechanism to take decisions at LCN. The result of the Simulation of proposed system shows that problem of traffic congestion is efficiently reduced in the traffic network.

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What this paper is about

Traffic through road travel makes congestion in roads causes’ major problem to road users. This is due to regular use of vehicles through the cities and waits in traffic signal for a long time which makes traffic impasse. To manage this problem many traffic control system have been developed. Due to increase in vehicles the traffic controlling demand are high. To control these traffic new techniques was proposed and named as Efficient Road Traffic Controller (ERTC) which efficiently reduces congestion in traffic signal. The research model will control the traffic by the adjustment of time and phase of the traffic lights by the situation of traffic intersection and controlled by indication to the applying model. This paper gives a brief discussion of the procedures we adopted to develop an intelligent fuzzy control system for dealing with the road traffic congestion problem. Specialized node is used in the congestion road traffic which is known as Local Cognitive Node (LCN) implements the learning components and decision making. Fuzzy logic technology is used to develop the system with Cognitive sensor node where these nodes use learning mechanism to take decisions at LCN. The result of the Simulation of proposed system shows that problem of traffic congestion is efficiently reduced in the traffic network.

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Available abstract

Traffic through road travel makes congestion in roads causes’ major problem to road users. This is due to regular use of vehicles through the cities and waits in traffic signal for a long time which makes traffic impasse. To manage this problem many traffic control system have been developed. Due to increase in vehicles the traffic controlling demand are high. To control these traffic new techniques was proposed and named as Efficient Road Traffic Controller (ERTC) which efficiently reduces congestion in traffic signal. The research model will control the traffic by the adjustment of time and phase of the traffic lights by the situation of traffic intersection and controlled by indication to the applying model. This paper gives a brief discussion of the procedures we adopted to develop an intelligent fuzzy control system for dealing with the road traffic congestion problem. Specialized node is used in the congestion road traffic which is known as Local Cognitive Node (LCN) implements the learning components and decision making. Fuzzy logic technology is used to develop the system with Cognitive sensor node where these nodes use learning mechanism to take decisions at LCN. The result of the Simulation of proposed system shows that problem of traffic congestion is efficiently reduced in the traffic network.

Key concepts: Floating car data, Traffic congestion reconstruction with Kerner's three-phase theory, Computer science, Intersection (aeronautics), Traffic congestion, Network traffic control, Traffic optimization, Fuzzy logic

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