Litcius/Paper detail

Improving the Road and Traffic Control Prediction Based on Fuzzy Logic Approach in Multiple Intersections

Sadiqa Jafari, Zeinab Shahbazi, Yung-Cheol Byun

2022Mathematics27 citationsDOIOpen Access PDF

Abstract

Traffic congestion is a significant issue in many countries today. The suggested method is a novel control method based on multiple intersections considering the kind of traffic light and the duration of the green phase to determine the optimal balance at intersections by using fuzzy logic control, for which the balance should be adaptable to the unchanging behavior of time. It should reduce traffic volume in transport, average waits for each vehicle, and collisions between cars by controlling this balance in response to the typical behavior of time and randomness in traffic conditions. The proposed method is investigated at intersections using a sampling multi-agent system to set traffic light timings appropriately. The program is provided with many intersections, each of which is an independent entity exchanging information with the others. The stability per entity is proven separately. Simulation results show that Takagi–Sugeno (TS) fuzzy modeling performs better than Takagi–Sugeno (TS) fixed-time scheduling in decreasing the length of queueing times for vehicles.

Topics & Concepts

Fuzzy logicComputer scienceQueueing theoryRandomnessScheduling (production processes)Set (abstract data type)Stability (learning theory)Control (management)Real-time computingSimulationControl theory (sociology)Mathematical optimizationArtificial intelligenceMathematicsComputer networkMachine learningStatisticsProgramming languageTraffic control and managementTraffic Prediction and Management TechniquesTransportation Planning and Optimization
Improving the Road and Traffic Control Prediction Based on Fuzzy Logic Approach in Multiple Intersections | Litcius