scholarly journals Dynamic Traffic Light Control

2020 ◽  
Vol 8 (6) ◽  
pp. 3228-3231
Keyword(s):  
Traffic Congestion ◽  
Traffic Management ◽  
Red Light ◽  
Traffic Monitoring ◽  
Intelligent Transport System ◽  
Light Control ◽  
Traffic Light ◽  
Traffic Lights ◽  
Traffic Light Control ◽  
Traffic Management System

Intelligent Transport System (ITS) is blooming worldwide. The Traditional Traffic management system is a tedious process and it requires huge man power, to overcome this we have proposed an automatic Traffic monitoring system that has effective fleet management. The current transportation system at intersections and junctions has Traffic Lights with Fixed durations which increase the unnecessary staying time which intern harms the environment. An Adaptive traffic light control is implemented using SUMO simulator, that changes the duration of Green and Red light according to the traffic flow. This is an effective and efficient way to reduce the Traffic congestion. The traffic congestion is determined by taking the object count using deep learning approach (Convolutional Neural Network).

Design of Intelligent Traffic Light Control System Based on Multi CPU

2014 ◽  
Vol 716-717 ◽  
pp. 1562-1566
Author(s):  
Wen Liang Wu
Keyword(s):  
Control System ◽  
Traffic Management ◽  
Control Process ◽  
Research Field ◽  
Light Control ◽  
Traffic Light ◽  
Traffic Lights ◽  
Traffic Light Control ◽  
Self Tuning ◽  
Core Problem

The intelligent traffic light control is the core problem in the intelligent traffic research field, in order to solve this problem, the intelligent traffic light control system is proposed based on multi CPU. In a multi processor system, aiming at the intelligent traffic light, the reasonable control is taken. In the intelligent traffic light control system, the related principles of multi processor system design and shared memory are elaborated in detail. The BP neural network self-tuning PID control algorithm is applied in the traffic lights control process, reasonable control of traffic lights is obtained. The experiment results show that the principle is applied in the intelligent traffic light control system, it can greatly improve the control accuracy, so it can meet the actual demand of intelligent traffic management.

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 Implementation of Fuzzy Mamdani Method for Traffic Lights Smart City in Rangkasbitung, Lebak Regency, Banten Province (Case Study of the Traffic Light T-junction, Cibadak, By Pas Sukarno Hatta Street)

KOMTEKINFO ◽  
2020 ◽  
Vol 7 (3) ◽  
pp. 176-185
Author(s):  
Dentik Karyaningsih ◽  
Robby Rizky
Keyword(s):  
Fuzzy Logic ◽  
Control System ◽  
Traffic Congestion ◽  
Fuzzy Logic Controller ◽  
Fuzzy Inference ◽  
Light Control ◽  
Traffic Light ◽  
Traffic Lights ◽  
Traffic Jams ◽  
Traffic Light Control

Traffic jams are a common sight that can be seen in almost all major cities in Indonesia. One of them is in Rangkasbitung City, Lebak Regency. This happens because the number of vehicles continues to increase. The traffic light control system implemented in Indonesia is a static preset time because the time of each phase is predetermined. This type of control system is still not effective in overcoming traffic congestion, especially at certain peak traffic jams. By using the Mamdani fuzzy logic system, it is possible to implement the human mindset into a system. Some rules can be set out in the fuzzy logic controller. The purpose of this study is to design a traffic light control system using fuzzy inference that regulates traffic based on its density. The data used are observations made at the research site. The conclusion of this study is to explain that the fuzzy mamdani method can solve existing problems in traffic congestion in Rangkasbitung City, Lebak Regency, Banten Province

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 An Efficient Adaptive Traffic Light Control System for Urban Road Traffic Congestion Reduction in Smart Cities

Information ◽  
2020 ◽  
Vol 11 (2) ◽  
pp. 119
Author(s):  
Dex R. ALEKO ◽  
Soufiene Djahel
Keyword(s):  
Control System ◽  
Travel Time ◽  
Traffic Congestion ◽  
Fixed Time ◽  
City Centre ◽  
Light Control ◽  
Traffic Light ◽  
Long Distance ◽  
Traffic Lights ◽  
Traffic Light Control

Traffic lights have been used for decades to control and manage traffic flows crossing road intersections to increase traffic efficiency and road safety. However, relying on fixed time cycles may not be ideal in dealing with the increasing congestion level in cities. Therefore, we propose a new Adaptive Traffic Light Control System (ATLCS) to assist traffic management authorities in efficiently dealing with traffic congestion in cities. The main idea of our ATLCS consists in synchronizing a number of traffic lights controlling consecutive junctions by creating a delay between the times at which each of them switches to green in a given direction. Such a delay is dynamically updated based on the number of vehicles waiting at each junction, thereby allowing vehicles leaving the city centre to travel a long distance without stopping (i.e., minimizing the number of occurrences of the ‘stop and go’ phenomenon), which in turn reduces their travel time as well. The performance evaluation of our ATLCS has shown that the average travel time of vehicles traveling in the synchronized direction has been significantly reduced (by up to 39%) compared to non-synchronized fixed time Traffic Light Control Systems. Moreover, the overall achieved improvement across the simulated road network was 17%.

scholarly journals Comparison of Game Theoretical Strategy and Reinforcement Learning in Traffic Light Control

2020 ◽  
Vol 48 (4) ◽  
pp. 313-319
Author(s):  
Jian Guo ◽  
István Harmati
Keyword(s):  
Reinforcement Learning ◽  
Public Transportation ◽  
Traffic Congestion ◽  
Learning Algorithm ◽  
Single Agent ◽  
Dynamic Environment ◽  
Light Control ◽  
Traffic Light ◽  
Traffic Lights ◽  
Traffic Light Control

Many traffic models and control methods have already been utilized in the public transportation system due to the increasing traffic congestion. Thus, an intelligent traffic model is formalized and presented to control multiple traffic light simultaneously and efficiently according to the distribution of vehicles from each incoming link (i.e. sections) in this paper. Compared with constant strategy, two methods are proposed for traffic light control, i.e., game theoretical strategy and reinforcement learning methods. Game theoretical strategy is generated in a game theoretical framework where incoming links are regarded as players and the combination of the status of traffic lights can be regarded as decisions made by these players. The cost function is evaluated and the strategy is produced with Nash equilibrium for passing maximum vehicles in an intersection. The other one is Single-Agent Reinforcement Learning (SARL), specifically with the Q-learning algorithm in this case, which is usually used in such a dynamic environment to control traffic flow so the traffic problem could be improved. Generally, the intersection is regarded as the centralized agent and controlling signal status is considered as the actions of the agent. The performance of these two methods is compared after simulated and implemented in a junction.

Application of Configuration Technology in Traffic Light Control System Based on PLC

2012 ◽  
Vol 151 ◽  
pp. 510-513 ◽  
Author(s):  
Yu Peng Yao ◽  
Ying Shi ◽  
Ji You Fei
Keyword(s):  
Control System ◽  
New Technology ◽  
Computer Control ◽  
Good Condition ◽  
Control Technology ◽  
Light Control ◽  
Traffic Light ◽  
Software Simulation ◽  
Traffic Lights ◽  
Traffic Light Control

Configuration technology is a new technology for monitoring in the current society; it is the result of the development of computer control technology. To traffic light control system, it is to combine the use of configuration technology and procedures related to PLC, and through software simulation and traffic lights light changes, traffic light control system could achieve the monitoring problem, and if the system is in good condition, its application can save a lot of labor powers and materials.

scholarly journals Automatic traffic light controller for emergency vehicle using peripheral interface controller

2019 ◽  
Vol 9 (3) ◽  
pp. 1788 ◽  
Author(s):  
Norlezah Hashim ◽  
Fakrulradzi Idris ◽  
Ahmad Fauzan Kadmin ◽  
Siti Suhaila Jaapar Sidek
Keyword(s):  
Traffic Congestion ◽  
Traffic Management ◽  
Emergency Situation ◽  
Light Signal ◽  
Emergency Vehicle ◽  
Traffic Light ◽  
Traffic Lights ◽  
The Road ◽  
Light Area ◽  
On The Road

Traffic lights play such important role in traffic management to control the traffic on the road. Situation at traffic light area is getting worse especially in the event of emergency cases. During traffic congestion, it is difficult for emergency vehicle to cross the road which involves many junctions. This situation leads to unsafe conditions which may cause accident. An Automatic Traffic Light Controller for Emergency Vehicle is designed and developed to help emergency vehicle crossing the road at traffic light junction during emergency situation. This project used Peripheral Interface Controller (PIC) to program a priority-based traffic light controller for emergency vehicle. During emergency cases, emergency vehicle like ambulance can trigger the traffic light signal to change from red to green in order to make clearance for its path automatically. Using Radio Frequency (RF) the traffic light operation will turn back to normal when the ambulance finishes crossing the road. Result showed the design is capable to response within the range of 55 meters. This project was successfully designed, implemented and tested.

scholarly journals Development of Model for Traffic Flows on Urban Street and Road Network

2019 ◽  
Vol 18 (1) ◽  
pp. 47-54
Author(s):  
D. V. Kapskiy ◽  
D. V. Navoy ◽  
P. A. Pegin
Keyword(s):  
Traffic Management ◽  
Management System ◽  
Road Network ◽  
Complex Structure ◽  
Large City ◽  
Intelligent Transport System ◽  
Light Cycle ◽  
Traffic Light ◽  
Level Model ◽  
Traffic Management System

The paper considers issues pertaining to creation of a model for controlling road traffic with the purpose to minimize delays on street and road network, which is proposed as an innovative one while developing an intelligent transport system of the large city that is Minsk. The developed model has a complex structure of algorithmic support. The first-level model has been implemented on the basis of fuzzy logic, for which a program has been developed and conditions have been determined, and operation of traffic light at a real local intersection of Minsk, which is included in the automated traffic management system, has been simulated. Innovation in the first-level model is an approach in determining conditions while detecting a fuzzy set without using a standard algorithm that is an algorithm of local flexible regulation. The paper proposes and investigates a model that works on the basis of operationally obtained parameters of traffic flow intensity at characteristic points (sections) of street and road network. Efficiency of the first-level model has been equal to 8 % due to optimization of a traffic light cycle (reduction of transport delays during passage of stop lines). Results of the simulation using the proposed computer program have made it possible to improve efficiency of traffic management on the studied highway (Logoysky trakt) in Minsk city of Minsk by 15 % due to decrease of delay level in case of unilateral coordination. The algorithm has been already implemented as part of the current automated traffic management system in the city of Minsk and it has shown its efficiency. However this efficiency can be increased if it is used together with an algorithm for searching maximum volume of motion in a cycle with a distributed intensity pulse. It has been planned to take into account this specific feature when increasing possibilities for algorithmization of traffic management.

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