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 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 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 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).

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 Performance Analysis of V2V and V2I LiFi Communication Systems in Traffic Lights

2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
Author(s):  
Gerardo Hernandez-Oregon ◽  
Mario E. Rivero-Angeles ◽  
Juan C. Chimal-Eguía ◽  
Arturo Campos-Fentanes ◽  
Jorge G. Jimenez-Gallardo ◽  
...  
Keyword(s):  
Mobile Communications ◽  
Communication Systems ◽  
Vehicular Networks ◽  
Low Cost ◽  
Red Light ◽  
Green Light ◽  
Mathematical Expression ◽  
Traffic Light ◽  
Safe Driving ◽  
Traffic Lights

Vehicular networks is a key technology for efficiently communicating both user’s devices and cars for timely information regarding safe driving conditions and entertaining applications like social media, video streaming, and gaming services, among others. In view of this, mobile communications making use of cellular resources may not be an efficient and cost-effective alternative. In this context, the implementation of light-fidelity (LiFi) in vehicular communications could be a low-cost, high-data-rate, and efficient-bandwidth usage solution. In this work, we propose a mathematical analysis to study the average throughput in a road intersection equipped with a traffic light that operates as a server, which is assumed to have LiFi communication links with the front lights of the vehicles waiting for the green light. We further assume that the front vehicle (the car next to the traffic light) is able to communicate to the car immediately behind it by using its own tail lights and the front lights of such vehicle, and so on and so forth. The behavior of the road junction is modeled by a Markov chain, applying the Queueing theory with an M/M/1 system in order to obtain the average queue length. Then, Little’s theorem is applied to calculate the average waiting delay when the red light is present in the traffic light. Finally, the mathematical expression of the data throughput is derived.

scholarly journals Real-Time Adaptive Traffic Signals Using Rate-Monotonic Scheduling

2019 ◽  
Vol 29 ◽  
pp. 03002 ◽  
Author(s):  
Mãdãlin-Dorin Pop
Keyword(s):  
Real Time ◽  
Intelligent Transportation Systems ◽  
Traffic Congestion ◽  
Traffic Signals ◽  
Fixed Time ◽  
Transportation Systems ◽  
Real Time Scheduling ◽  
Traffic Lights ◽  
Rate Monotonic ◽  
Rate Monotonic Scheduling

The studies and real situations shown that the traffic congestion is one of nowadays highest problems. This problem wassolved in the past using roundabouts and traffic signals. Taking in account the number of cars that is increasing continuously, we can see that past approaches using traffic lights with fixed-time controller for traffic signals timing is obsolete. The present and the future is the using of Intelligent Transportation Systems. Traffic lights systems should be aware about realtime traffic parameters and should adapt accordingly to them. The purpose of this paper is to present a new approach to control traffic signals using rate-monotonic scheduling. Obtained results will be compared with the results obtained by using others real-time scheduling algorithms.

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 Adaptive real time traffic prediction using deep neural networks

2019 ◽  
Vol 8 (2) ◽  
pp. 107
Author(s):  
Parinith R Iyer ◽  
Shrutheesh Raman Iyer ◽  
Raghavendran Ramesh ◽  
Anala M.R. ◽  
K.N. Subramanya
Keyword(s):  
Traffic Congestion ◽  
Noise Pollution ◽  
Fixed Time ◽  
Detection Algorithm ◽  
Steady Increase ◽  
Traffic Light ◽  
Pollution Levels ◽  
Real Time Traffic ◽  
Commute Time ◽  
Network Object

<span lang="EN-US">The ever-increasing sale of vehicles and the steady increase in population density in metropolitan cities have raised many growing concerns, most importantly commute time, air and noise pollution levels. Traffic congestion can be alleviated by opting using adaptive traffic light systems, instead of fixed-time traffic signals. In this paper, a system is proposed which can detect, classify and count vehicles passing through any traffic junction using a single camera (as opposed to multi-sensor approaches). The detection and classification are done using SSD Neural Network object detection algorithm. The count of each class (2-wheelers, cars, trucks, buses etc.) is used to predict the signal green-time for the next cycle. The model self-adjusts every cycle by utilizing weighted moving averages. This system works well because the change in the density of traffic on any given road is gradual, spanning multiple traffic stops throughout the day.</span>

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