scholarly journals Designing a Smart Traffic Light Algorithm (HMS) Based on Modified Round Robin Algorithm

2017 ◽  
Vol 2 (1) ◽  
pp. 27-30
Author(s):  
Hozan Khalid Hamarashid ◽  
Miran Hama Rahim Saeed ◽  
Soran Saeed
Keyword(s):  
Traffic Congestion ◽  
Fixed Time ◽  
Traffic Load ◽  
Traffic Light ◽  
Traffic Jam ◽  
Traffic Lights ◽  
Traffic System ◽  
Light System ◽  
Smart Traffic ◽  
Fixed System

Nowadays, traffic light system is very important to avoid car crashes and arrange traffic load. In the Sulaimani City / Iraq, there are many traffic problems such as traffic congestion or traffic jam and the amount of time provided manually to the traffic light system. This is the main difficulty that we try to solve. The traffic lights exist but still do not manage traffic congestion due to the fixed time provided for each lane regardless of their different load. Therefore, we are proposing to change the traditional traffic system to smart traffic system (adaptive system). This paper Focuses on the existing system (fixed system), then propose the adaptive one. The main crucial side effects of the existing system are:   Emergency cases: congested traffics might block the way of emergencies for instance ambulance, which transports people to the hospital Wasting time of people generally and specially Delays, which lead people to not to be punctual, this means people arrive late to the work  Wasting more fuels as staying more in the traffics, which affects the environment by increasing pollution.

scholarly journals Smart Traffic Lights over Vehicular Named Data Networking

Information ◽  
2019 ◽  
Vol 10 (3) ◽  
pp. 83 ◽  
Author(s):  
Majed Al-qutwani ◽  
Xingwei Wang
Keyword(s):  
Traffic Congestion ◽  
Fixed Time ◽  
Light Signal ◽  
Vehicular Traffic ◽  
Named Data Networking ◽  
Traffic Light ◽  
Traffic Lights ◽  
Light System ◽  
Smart Traffic ◽  
Data Networking

The existing traffic light system fails to deal with the increase in vehicular traffic requirements due to fixed time programming. Traffic flow suffers from vehicle delay and congestion. A new networking technology called vehicular ad hoc networking (VANET) offers a novel solution for vehicular traffic management. Nowadays, vehicles communicate with each other (V2V), infrastructure (V2I), or roadside units (V2R) using IP-based networks. Nevertheless, IP-based networks demonstrate low performance with moving nodes as they depend on communication with static nodes. Currently, the research community is studying a new networking architecture based on content name called named data networking (NDN) to implement it in VANET. NDN is suitable for VANET as it sends/receives information based on content name, not content address. In this paper, we present one of VANET’s network applications over NDN, a smart traffic light system. Our system solves the traffic congestion issue as well as reducing the waiting time of vehicles in road intersections. This system replaces the current conventional system with virtual traffic lights (VTLs). Instead of installing traffic lights at every intersection, we utilize a road side unit (RSU) to act as the intersection controller. Instead of a light signal, the RSU collects the orders of vehicles that have arrived or will arrive at the intersection. After processing the orders according to the priority policy, the RSU sends an instant message for every vehicle to pass the intersection or wait for a while. The proposed system mimics a human policeman intersection controlling. This approach is suitable for autonomous vehicles as they only receive signals from the RSU instead of processing many images. We provide a map of future work directions for enhancing this solution to take into account pedestrian and parking issues.

scholarly journals Simulation of Traffic Optimization to Reduce Congestion

2019 ◽  
Vol 8 (11) ◽  
pp. 3780-3783
Keyword(s):  
Traffic Flow ◽  
Traffic Congestion ◽  
Flow Density ◽  
Traffic Light ◽  
Traffic Lights ◽  
Traffic System ◽  
Light System ◽  
Intelligent Traffic System ◽  
Traffic Optimization ◽  
Indian Cities

There has been an alarming increase in the number of vehicles on the Indian roads in the recent times, almost triple as that in 2005[10]. which obviously leads to traffic congestion on road and enhanced pollution, although there has been many reasons for the same but major one is unmanaged traffic light system as the current traffic light system is either manual or static timings of traffic lights regardless of the flow of traffic. There is a need for smart solution to the traffic light in Indian cities or to have ITS (Intelligent traffic system). Paper provides a solution based on camera feed at crossings for each lane, process the data through and allocates the “Green” time according to its traffic flow density using YOLO v3 and also takes care of starvation issue that might arise of the solution. As a result the flow of traffic on each lane is automatically optimized and the congestion that used to happen unnecessarily earlier is eliminated and results shows significant benefits in reducing traffic waiting time.

Smart Traffic Light System

2021 ◽  
Vol 9 (9) ◽  
pp. 679-686
Author(s):  
Rashi Maheshwari
Keyword(s):  
Traffic Congestion ◽  
Traffic Signals ◽  
Traffic Monitoring ◽  
Traffic Signal ◽  
Traffic Signal Control ◽  
Traffic Light ◽  
Mathematical Functions ◽  
Light System ◽  
Smart Traffic ◽  
And Control

Abstract: Traffic signal control frameworks are generally used to monitor and control the progression of cars through the intersection of roads. Moreover, a portable controller device is designed to solve the issue of emergency vehicles stuck in overcrowded roads. The main objective of this paper is to design and implement a suitable algorithm and its simulation for an intelligent traffic signal simulator. The framework created can detect the presence or nonappearance of vehicles within a specific reach by setting appropriate duration for traffic signals to react accordingly. By employing mathematical functions and algorithms to ascertain the suitable timing for the green signal to illuminate, the framework can assist with tackling the issue of traffic congestion. The explanation relies on recent fixed programming time. Keywords: Smart Traffic Light System, Smart City, Traffic Monitoring.

Smart Traffic Light Management Systems

2020 ◽  
Vol 11 (3) ◽  
pp. 22-47
Author(s):  
Aws Abed Al Raheem Magableh ◽  
Mohanad A. Almakhadmeh ◽  
Nawaf Alsrehin ◽  
Ahmad F. Klaib
Keyword(s):  
Law Enforcement ◽  
Traffic Congestion ◽  
Traffic Management ◽  
Video Data ◽  
Traffic Light ◽  
Infrared Sensors ◽  
Traffic Lights ◽  
Loop Detection ◽  
Light Management ◽  
Smart Traffic

Traffic congestion is a major concern in many cities. Failure to heed signals, poor law enforcement, and bad traffic light management are main factors that have led to traffic congestion. One of the most important problems in cities is the difficulty of further expanding the existing infrastructures. Having that in mind, the main accessible and available alternatives that could provide better management of the traffic lights is to use technological systems. There are many methods available for traffic management such as video data analysis, infrared sensors, inductive loop detection, wireless sensor networks, and a few other technologies. This research is focused on reviewing all these existing methods and studies using a systematic literature review (SLR). The SLR was intended to improve the synthesis of research by introducing a systematic process. This article aims at analyzing and assessing the existing studies against selected factors of comparison. The study achieves these aims by analyzing 78 main studies. The research outcomes indicated that there are decent numbers of studies that have been proposed in the area of smart traffic light management. However, less attention has been paid on the possibility of investigating the use of live traffic data to improve the accuracy of traffic management.

scholarly journals Network Traffic Lights with Telemetry and Wireless Connectivity Perimeter

2019 ◽  
Vol 256 ◽  
pp. 05002
Author(s):  
España Víctor ◽  
Chuchon Eddy ◽  
Caytuiro David ◽  
Iván Advincula ◽  
Mario Chauca
Keyword(s):  
Control Systems ◽  
Real Time ◽  
Network Traffic ◽  
Traffic Congestion ◽  
Vehicle Control ◽  
Traffic Light ◽  
Traffic Lights ◽  
The Creation ◽  
Research Document ◽  
Smart Traffic

The following research document seeks to show an alternative to vehicle control systems using existing technologies to develop a system that is efficient and reliable. The creation and operation of a traffic light network will be presented, which will be located in an area where there is traffic congestion. The following network will reorganize, optimize, and measure the vehicular flow in real time. In some countries, intelligent traffic lights have been implemented, with which they have obtained satisfactory benefits by improving the vehicular flow of the places where these systems are located; for this reason we consider it necessary to use smart traffic lights in our country.

scholarly journals Intelligent Traffic Congestion Control System using Machine Learning and Wireless Network

2020 ◽  
Vol 4 (2) ◽  
pp. 123
Author(s):  
Mohammed Abdulmaged Faraj ◽  
Najmadin Wahid Boskany
Keyword(s):  
Machine Learning ◽  
Wireless Network ◽  
Traffic Congestion ◽  
Low Cost ◽  
Fixed Time ◽  
Traffic Light ◽  
Traffic Lights ◽  
Radiofrequency Identification ◽  
Traffic Congestion Control ◽  
Traditional Approaches

Traffic congestion has become a big problem for most people because it increases noise, air pollution, and wasting time. Current normal traffic light system is not enough to manage the traffic problematic congestions because they operate on a fixed-time length plan. In recent years, internet of things led to introducing new models of intelligent traffic light systems; by utilizing different techniques such as predictive-based model, radiofrequency identification, and ultrasonic-based model. The most essential one of these techniques is depends of image processing and microcontroller communications. In this paper, we propose an intelligent, low cost, and efficient microcontroller circuit-based system for controlling cars in traffic light. This system can manage car traffics smarter than traditional approaches, it is capable to dynamically adjust timings of traffic signal. It can rapidly respond to traffic conditions to reduce traffic congestion. For implementing this system, a server, microcontroller board, cameras, as hardware and wireless network between traffic lights as infrastructure for communication are used. The system uses machine learning technique (i.e.,Yolov3 model and OpenCV) for decision depending on existence of emergency cars and number of cars. The experiment results show higher accuracy in managing traffic lights and recognizing the emergency cars.

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 The Necessity for a Sustainable Traffic Light System: The Case Study of el-Koura District Traffic Light System

2017 ◽  
Vol 2 (9) ◽  
pp. 42
Author(s):  
Najib Nicolas Gerges ◽  
Samer Mohammad Fawaz
Keyword(s):  
Traffic Congestion ◽  
Constant Speed ◽  
Speed Limit ◽  
Traffic Light ◽  
Negative Effects ◽  
Light System ◽  
Smart Traffic

Traffic congestion is one of the major problems that Lebanon agonizes from. In this case study, the main objective is to provide a smart traffic light system that can reduce congestion in addition to all of its negative effects. The method used for design was the Webster Method. The results are very favorable. The system was optimized to reduce traffic light stops and idle running times provided that the drivers abide by the speed limit on the roadway and try to maintain a constant speed. 

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).

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