Accident Detection System Using Dynamic Fuzzy Logic Control

2015 ◽  
Author(s):  
Khaled Al-Rasheed ◽  
Abdulrahman Al-Kandari
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Control ◽  
Detection System ◽  
Logic Control ◽  
Accident Detection

scholarly journals Implementation of Dynamic Fuzzy Logic Control of Traffic Light with Accident Detection and Action System using iTraffic Simulation

2018 ◽  
Vol 10 (1) ◽  
pp. 100 ◽  
Author(s):  
Abdulrahman Abdullah Alkandari ◽  
Imad Fakhri Al-Shaikhli
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Control ◽  
Detection System ◽  
Traffic Light ◽  
The Road ◽  
Action System ◽  
Logic Control ◽  
Traffic Light Control ◽  
Dynamic Hybrid ◽  
Accident Detection

Traffic is one of the most common issues in the big cities around the world. Thus, develop and improve the traffic light control systems became the focus of recent studies. To solve the problem, we proposed a dynamic hybrid fuzzy logic control system that is further branched into two separate systems: An Accident Detection system and an Action system that is intended to solve the congestion related to the vehicular traffic. The primary target of this paper is to discuss the Action system, which depends on the Accident Detection system. This paper explained the two parts of the Action system. It showed the improvement of the Action system with %9.32 in total car crossed. It also presented different scenarios using iTraffic simulation and description of each scenario is displayed with details about the road variables and the simulation results with and without the action system.

scholarly journals Accident Detection Traffic Light System with Dynamic Fuzzy Logic Control Using FuzzyTech Program and iTraffic Simulation

2015 ◽  
Vol 1 (1) ◽  
Author(s):  
Faisal AlAwadhi ◽  
Mohammed Ali Yousef ◽  
Abdulrahman Al-Kandari
Keyword(s):  
Fuzzy Logic ◽  
Hybrid System ◽  
Detection System ◽  
Traffic Signal Control ◽  
Traffic Light ◽  
Action System ◽  
Logic Control ◽  
Fuzzy Logic Theory ◽  
Traffic Signal Control Systems ◽  
Accident Detection

The development of traffic signal control systems has become one of the most important topics in this era. Traffic light controllers need to be improved continuously to solve the traffic problems. This paper discussed the proposed hybrid system and demonstrated how the system works from the beginning of the first flag “decrease of cross ratio” until the end of the action system. The proposed system was divided into three main parts: The proposed algorithm (Dynamic Webster with dynamic Cycle Time), Accident Detection System using fuzzy logic theory and Action System depending on Detection System. The focus of this paper is to discuss the accident detection system of the proposed hybrid system, which depended on fuzzy logic and its components. This paper also presented the results of FuzzyTech Software with different scenarios plotting the inputs outputs and the showcases the 3D plot for each one of them for detecting the accident. In addition, it presented results to measure the False Alarm Rate the Accident Detection Rate using FuzzyTech program.

Sistem Kontrol Optimal Fuzzy-Particle Swarm Optimization

2018 ◽  
Vol 9 (1) ◽  
pp. 1-5
Author(s):  
Fachrudin Hunaini ◽  
Imam Robandi ◽  
Nyoman Sutantra
Keyword(s):  
Fuzzy Logic ◽  
Particle Swarm Optimization ◽  
Control System ◽  
Membership Function ◽  
Fuzzy Logic Control ◽  
Particle Swarm ◽  
Optimization Method ◽  
Swarm Optimization ◽  
Motion Error ◽  
Logic Control

Fuzzy Logic Control (FLC) is a reliable control system for controlling nonlinear systems, but to obtain optimal fuzzy logic control results, optimal Membership Function parameters are needed. Therefore in this paper Particle Swarm Optimization (PSO) is used as a fast and accurate optimization method to determine Membership Function parameters. The optimal control system simulation is carried out on the automatic steering system of the vehicle model and the results obtained are the vehicle's lateral motion error can be minimized so that the movement of the vehicle can always be maintained on the expected trajectory

Implementation of Fuzzy Logic Control on Battery Charging System

2019 ◽  
Vol 3 (1) ◽  
pp. 118-126 ◽  
Author(s):  
Prihangkasa Yudhiyantoro
Keyword(s):  
Complex System ◽  
Fuzzy Logic ◽  
Fuzzy Logic Control ◽  
Expert Knowledge ◽  
Experimental Result ◽  
Rule Base ◽  
Battery Charging ◽  
Charging System ◽  
Logic Control ◽  
Charging Control

This paper presents the implementation fuzzy logic control on the battery charging system. To control the charging process is a complex system due to the exponential relationship between the charging voltage, charging current and the charging time. The effective of charging process controller is needed to maintain the charging process. Because if the charging process cannot under control, it can reduce the cycle life of the battery and it can damage the battery as well. In order to get charging control effectively, the Fuzzy Logic Control (FLC) for a Valve Regulated Lead-Acid Battery (VRLA) Charger is being embedded in the charging system unit. One of the advantages of using FLC beside the PID controller is the fact that, we don’t need a mathematical model and several parameters of coefficient charge and discharge to software implementation in this complex system. The research is started by the hardware development where the charging method and the combination of the battery charging system itself to prepare, then the study of the fuzzy logic controller in the relation of the charging control, and the determination of the parameter for the charging unit will be carefully investigated. Through the experimental result and from the expert knowledge, that is very helpful for tuning of the  embership function and the rule base of the fuzzy controller.

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