scholarly journals Optimization of Traffic Light Control Using Fuzzy Logic Sugeno Method

2020 ◽  
Vol 1 (2) ◽  
pp. 51-61
Author(s):  
Ria Yuliani Kartikasari
Keyword(s):  
Fuzzy Logic ◽  
Green Light ◽  
Major Influence ◽  
Traffic Light ◽  
The Road ◽  
Traffic Conditions ◽  
Smooth Flow ◽  
Traffic Light Control ◽  
Light Duration ◽  
On The Road

Congestion is one of the big problems around the world, especially for big cities. Intersections are the scene of congestion because the lane is the meeting point of two or more roads which has a major influence on the smooth flow of vehicles on the road network. This congestion occurs due to various factors, one of which is the statistical traffic light duration, which does not match traffic conditions. Based on this, there needs to be a development in the timing of a more adaptive green light. This study describes the design of a traffic light controller using the Sugeno method fuzzy logic. This study aims to design a green light duration calculation by applying fuzzy logic that results in adaptive traffic light duration at intersections, by entering the density of each intersection path, which is divided into 4 inputs, namely regulated lane density, opposing lane density I, and opposite lane density. II, the density of the opposite lane III, with the aim of the system being able to produce a duration that is in accordance with the current traffic situation with an output in the form of a green light duration on the regulated lane.

scholarly journals Ant Colony Optimization for Real Time Traffic Lights Control on a Single Intersection

2020 ◽  
Vol 14 (02) ◽  
pp. 196 ◽  
Author(s):  
Nouha Rida ◽  
Mohammed Ouadoud ◽  
Aberrahim Hasbi
Keyword(s):  
Road Traffic ◽  
Green Light ◽  
Optimal Solution ◽  
Ant Colony ◽  
Traffic Data ◽  
Traffic Light ◽  
Traffic Lights ◽  
The Road ◽  
Real Time Traffic ◽  
On The Road

In this paper, we present a new scheme to intelligently control the cycles and phases of traffic lights by exploiting the road traffic data collected by a wireless sensor network installed on the road. The traffic light controller determines the next phase of traffic lights by applying the Ant Colony Optimazation metaheuristics to the information collected by WSN. The objective of this system is to find an optimal solution that gives the best possible results in terms of reducing the waiting time of vehicles and maximizing the flow crossing the intersection during the green light. The results of simulations by the SUMO traffic simulator confirm the preference of the developed algorithm over the predefined time controller and other dynamic controllers.

scholarly journals TRAFFIC LIGHT CONTROL USING FUZZY LOGIC MAMDANI METHOD

2019 ◽  
Vol 3 (1) ◽  
pp. 1-10
Author(s):  
Paula Juniana ◽  
Lukman Hakim
Keyword(s):  
Fuzzy Logic ◽  
Control System ◽  
Traffic Congestion ◽  
Green Light ◽  
Light Control ◽  
Traffic Light ◽  
Additional Time ◽  
Traffic Lights ◽  
Traffic Jams ◽  
Traffic Light Control

Traffic congestion is a common occurrence in Indonesia. Traffic congestion is increasing from year to year, causing many things to happen, such as longer travel time, increased transportation costs, serious disruptions to transporting products, decreasing levels of work productivity, and wasteful use of labor energy. Congestion is also caused by a traffic light control system that is made with a fixed time so it can not detect the density of certain paths. Traffic lights in Indonesia, frequent damage that makes the density and the flow of his road vehicles can not be controlled. From these problems, conducted research to reduce the density of vehicles using infrared sensors and see the waiting time of the vehicle when the red light. The traffic light control system will use Fuzzy Logic Mamdani method. In Mamdani method by applying fuzzy into each variable and will be done matching between rule with condition which fulfilled to determine contents of output to be executed by prototype. This congestion detection will help the system in controlling the green light time by looking at stable, medium, and traffic jams. When the bottleneck starts to detect, the prototype will add a green light time according to the condition that is 0 seconds, 5 seconds, 10 seconds, and 15 seconds. However, when the streets are not detected by traffic jams, the green light will be back to normal at 15 seconds without additional time

scholarly journals Automated Density Based Traffic Light Control System using Arduino Platform

2019 ◽  
Vol 9 (1) ◽  
pp. 5269-5271
Keyword(s):  
Control System ◽  
Green Light ◽  
Fixed Time ◽  
Traffic Density ◽  
Light Control ◽  
Traffic Light ◽  
Light System ◽  
Time Period ◽  
Traffic Light Control ◽  
On The Road

In recent years, traffic Jams has become a serious problem across the globe. Current statistics reveals that, an average person spends around 4-6 months of his/her life by simply waiting for green light during traffic. Also when delay increases, it affects the commuters reach their destination so late resulting in severe consequences on day and day basis. In common, traffic can be controlled in several main junctions by incorporating either automated traffic light control system or through manual intervention by traffic police. However conventional traffic light system which involves fixed time slot allotted to each side of the junction is found to be poor efficient since it does not consider the varying traffic density. At certain instances, priority of the traffic system has to be changed dynamically based on more number of vehicles waiting on the road, arrival of VIP vehicles and ambulance vehicles etc. By considering the above facts, we have proposed an automated traffic light system which has inbuilt potential to prioritize the lane which is heavily congested. Our proposed system includes timer which runs for a specific time period and IR sensor is used to count the number of vehicles passing by during that time period. It also includes LED which is turned green on the lane with more number of vehicles. These peripherals were actuated based on the programming logic that is embedded in Arduino Mega platform. Finally, implementation results for the proposed system are provided in this paper.

Optimalisasi Lampu Lalu Lintas dengan Fuzzy Logic

2013 ◽  
Vol 5 (2) ◽  
pp. 58-62 ◽  
Author(s):  
Adhitya Yoga Yudanto ◽  
Marvin Apriyadi ◽  
Kevin Sanjaya
Keyword(s):  
Fuzzy Logic ◽  
Control System ◽  
Fuzzy Inference ◽  
System Control ◽  
Light Control ◽  
Traffic Light ◽  
Inference System ◽  
Traffic Lights ◽  
The Road ◽  
Traffic Light Control

The traffic lights problem is already commonly found in large cities. The traffic lights are supposed to control the flow of the road, but sometimes causes a congestion. This happens because the distribution of the time are all the same for all lines, without seeing the condition of the density of each lane. There’s one effort that can be done to overcome this problem, is to create a traffic light control system. With this system, the congestion that occurs around the traffic lights can be reduced. This system is using fuzzy logic. Fuzzy logic is one of computer science that studies about the value of truth that worth a lot. For example, a air conditioning system control subway Sendai in Japan. As for making a traffic light control system, the author using Fuzzy Inference System (FIS) that already exist in the application of MATLAB R2013a with Mamdani method. Index Terms —fuzzy logic, traffic lights, MATLAB.

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.

Traffic Light Control Based on the Road Image Analysis

2015 ◽  
pp. 669-685
Author(s):  
Obada M. A. Bani Issa ◽  
Venus W. Samawi ◽  
Jehad Q. Alnihoud
Keyword(s):  
Image Analysis ◽  
Light Control ◽  
Traffic Light ◽  
The Road ◽  
Traffic Light Control ◽  
On The Road

scholarly journals TRAFFIC LIGHT CONTROL USING FUZZY LOGIC MAMDANI METHOD

2019 ◽  
Vol 3 (1) ◽  
pp. 1-10
Author(s):  
Paula Juniana ◽  
Lukman Hakim
Keyword(s):  
Fuzzy Logic ◽  
Control System ◽  
Traffic Congestion ◽  
Green Light ◽  
Light Control ◽  
Traffic Light ◽  
Additional Time ◽  
Traffic Lights ◽  
Traffic Jams ◽  
Traffic Light Control

Traffic congestion is a common occurrence in Indonesia. Traffic congestion is increasing from year to year, causing many things to happen, such as longer travel time, increased transportation costs, serious disruptions to transporting products, decreasing levels of work productivity, and wasteful use of labor energy. Congestion is also caused by a traffic light control system that is made with a fixed time so it can not detect the density of certain paths. Traffic lights in Indonesia, frequent damage that makes the density and the flow of his road vehicles can not be controlled. From these problems, conducted research to reduce the density of vehicles using infrared sensors and see the waiting time of the vehicle when the red light. The traffic light control system will use Fuzzy Logic Mamdani method. In Mamdani method by applying fuzzy into each variable and will be done matching between rule with condition which fulfilled to determine contents of output to be executed by prototype. This congestion detection will help the system in controlling the green light time by looking at stable, medium, and traffic jams. When the bottleneck starts to detect, the prototype will add a green light time according to the condition that is 0 seconds, 5 seconds, 10 seconds, and 15 seconds. However, when the streets are not detected by traffic jams, the green light will be back to normal at 15 seconds without additional time

Driver's Reaction Time in Evaluation of the Road Capacity

2015 ◽  
Vol 725-726 ◽  
pp. 1212-1217 ◽  
Author(s):  
Anastasiya Shevtsova ◽  
Ivan Novikov ◽  
Alexey Borovskoy
Keyword(s):  
Reaction Time ◽  
Road Network ◽  
Light Regulation ◽  
Light Control ◽  
Traffic Light ◽  
The Road ◽  
Road Section ◽  
Road Capacity ◽  
Traffic Light Control ◽  
On The Road

The paper gives an overview of researches of foreign scientists to change the driver's reaction time, depending on various road conditions, namely regarding the change of studied magnitude when using traffic-light signalization. Previously, the authors have carried out researches of capacity of road section with traffic light regulation, which allowed to establish the dependence of this parameter from the driver's reaction time. This paper proposes calculation of the road capacity using a variety values of the driver's reaction time derived from the analysis. The values obtained allow us to conclude that the inclusion of psychophysiological characteristics of drivers (such as reaction time) will affect both on road capacity and on the different methods of organization/reorganization of road networks sectors, which use the value of road capacity in their implementation.This article analyzes foreign researches devoted to changing the reaction time of drivers on the road conditions. Besides, the effect of changing the driver's reaction time on capacity of the road network sector with traffic-light control was considered.

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