Indian Journal of Science and Technology

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Fuzzy Logic Based Traffic Signal Control


Affiliations
1 Computer Science and Engineering, Ajay Kumar Garg Engineering College, Ghaziabad – 201009, Uttar Pradesh, India
 

Traffic congestion is a huge problem in many big cities around the world. This traffic congestion can affect the economy of a country, increase cost, slow down development and increase the environmental pollution. This research deals with the development of fuzzy logic based traffic signal which has dynamic cycle length. Development of such type of traffic signal is based on fuzzy logic. The traffic signal control system considers the uncertainty and vagueness of information about the input and output parameter values of the system. Fuzzy logic can easily handle such type of vagueness and uncertainty. The input parameters which are applied on fuzzy logic based traffic signal control are traffic density and traffic flow. The fuzzy traffic signal controller uses the input parameters and applies these inputs to fuzzy inference system to calculate the cycle length. The simulation is carried out using MATLAB software. The inference system used in fuzzy logic system is Mamdani inference system. According to the traffic conditions the cycle length of traffic signal is changed which decreases the waiting time of vehicles at the intersection.
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  • Fuzzy Logic Based Traffic Signal Control

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Authors

Nidhi Sharma
Computer Science and Engineering, Ajay Kumar Garg Engineering College, Ghaziabad – 201009, Uttar Pradesh, India
Shashank Sahu
Computer Science and Engineering, Ajay Kumar Garg Engineering College, Ghaziabad – 201009, Uttar Pradesh, India

Abstract


Traffic congestion is a huge problem in many big cities around the world. This traffic congestion can affect the economy of a country, increase cost, slow down development and increase the environmental pollution. This research deals with the development of fuzzy logic based traffic signal which has dynamic cycle length. Development of such type of traffic signal is based on fuzzy logic. The traffic signal control system considers the uncertainty and vagueness of information about the input and output parameter values of the system. Fuzzy logic can easily handle such type of vagueness and uncertainty. The input parameters which are applied on fuzzy logic based traffic signal control are traffic density and traffic flow. The fuzzy traffic signal controller uses the input parameters and applies these inputs to fuzzy inference system to calculate the cycle length. The simulation is carried out using MATLAB software. The inference system used in fuzzy logic system is Mamdani inference system. According to the traffic conditions the cycle length of traffic signal is changed which decreases the waiting time of vehicles at the intersection.

References





DOI: https://doi.org/10.17485/ijst%2F2018%2Fv11i23%2F114380