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

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.

2020 ◽  
Vol 8 (6) ◽  
pp. 3228-3231

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).


2020 ◽  
Vol 26 (2) ◽  
pp. 192-201
Author(s):  
Sri Redjeki Pudjaprasetya ◽  
Dear Michiko Noor

Traffic management of intersections is an important factor that can determine traffic density at the intersection, as well as its surrounding. Long traffic queues we encounter in daily life, were often caused by ineffectiveness of traffic lights management of the cross sections.In this article, an analytic study of traffic light management of a four-leg intersection, based on the kinematic LWR model, was presented. Comparison was based on observing the end of queues over three cycles of red-green lights, under the assumption of a constant traffic flux. On every leg of the intersection, the end of the queues were obtained from characteristic lines of the shock waves.From these observations, the three phase regulation was preferred over the four-phase one. Finally, a case study of Taman Sari - Baltos intersection located in Bandung City, Indonesia, was discussed. Parameter values used in these simulations were obtained from direct observation. 


Author(s):  
Norlezah Hashim ◽  
Fakrulradzi Idris ◽  
Ahmad Fauzan Kadmin ◽  
Siti Suhaila Jaapar Sidek

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.


2017 ◽  
Vol 2 (1) ◽  
pp. 27-30
Author(s):  
Hozan Khalid Hamarashid ◽  
Miran Hama Rahim Saeed ◽  
Soran Saeed

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.


Information ◽  
2019 ◽  
Vol 10 (3) ◽  
pp. 83 ◽  
Author(s):  
Majed Al-qutwani ◽  
Xingwei Wang

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.


2019 ◽  
Vol 4 (2) ◽  
pp. 261
Author(s):  
Muhammad Rozi Malim ◽  
Faridah Abdul Halim ◽  
Sherey Sufreney Abd Rahman

Traffic signal lights system is a signalling device located an intersection or pedestrian crossing to control the movement of traffic. The timing of traffic signal lights has attracted many researchers to study the problems involving traffic light management and looking for an inexpensive and effective solution that requires inexpensive changes in the infrastructures. A simple traffic lights system uses a pre-timed control setting based on the latest traffic data, and the setting could be manually changed. It is a common type of signal control and sometimes the setting was not correctly configured with the traffic data, thus leading to congestion at an intersection. Many mathematical strategies were applied to get an optimal setting. This study aims to model the traffic flow at Persiaran Kayangan and Persiaran Permai Intersection, Section 7, Shah Alam, as the case study, by using AnyLogic simulation software. The model was used to determine the best timings of traffic green lights that minimise the average time at the intersection and reduce traffic congestion. The findings showed that the best timings of traffic green lights for four directions at the intersection are 120 seconds, 75 seconds, 130 seconds and 100 seconds, respectively. These timings of green lights produced the lowest average time at the intersection (55.65 seconds).


2019 ◽  
Vol 256 ◽  
pp. 05002
Author(s):  
España Víctor ◽  
Chuchon Eddy ◽  
Caytuiro David ◽  
Iván Advincula ◽  
Mario Chauca

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.


Traffic Congestion is a major problem in many cities in India and other countries. Signal failure, lax regulation and traffic management have contributed to congestion of traffic. Some of the key issues with Indian cities is that the new network cannot be expanded further and that thus the only option left is better management and living standards It is therefore high time the issue of traffic congestion is to be dealt effectively Traffic control approaches include video data processing, infrared cameras, inductive loop tracking, wireless sensor network, etc. In our study, we use an infrared sensor that can be paired with the existing signaling network that can act as a portal to intelligent traffic management. Additionally, a smartphone application is connected to a centralized system that communicates with the local rescue department about a fire explosion site for further action. There's also a software application to provide the smart city's higher authorities with valuable information in graphic formats, which is helpful in future road planning. Automated traffic control and surveillance are essential for the use and maintenance of the highways.


2021 ◽  
Vol 13 (15) ◽  
pp. 8324
Author(s):  
Viacheslav Morozov ◽  
Sergei Iarkov

Present experience shows that it is impossible to solve the problem of traffic congestion without intelligent transport systems. Traffic management in many cities uses the data of detectors installed at controlled intersections. Further, to assess the traffic situation, the data on the traffic flow rate and its concentration are compared. Latest scientific studies propose a transition from spatial to temporal concentration. Therefore, the purpose of this work is to establish the regularities of the influence of traffic flow concentration in time on traffic flow rate at controlled city intersections. The methodological basis of this study was a systemic approach. Theoretical and experimental studies were based on the existing provisions of system analysis, traffic flow theory, experiment planning, impulses, probabilities, and mathematical statistics. Experimental data were obtained and processed using modern equipment and software: Traficam video detectors, SPECTR traffic light controller, Traficam Data Tool, SPECTR 2.0, AutoCad 2017, and STATISTICA 10. In the course of this study, the authors analyzed the dynamics of changes in the level of motorization, the structure of the motor vehicle fleet, and the dynamics of changes in the number of controlled intersections. As a result of theoretical studies, a hypothesis was put forward that the investigated process is described by a two-factor quadratic multiplicative model. Experimental studies determined the parameters of the developed model depending on the directions of traffic flow, and confirmed its adequacy according to Fisher’s criterion with a probability of at least 0.9. The results obtained can be used to control traffic flows at controlled city intersections.


Author(s):  
Rashi Maheshwari

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.


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