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 OPTIMIZATION OF MANAGEMENT OF URBAN LIGHTS WITH THE USE OF NEURAL NETWORKS

THE BULLETIN ◽  
2021 ◽  
Vol 389 (1) ◽  
pp. 14-17
Author(s):  
A.А. Suleimen ◽  
G.B. Kashaganova ◽  
G.B. Issayeva ◽  
B.R. Absatarova ◽  
M.C. Ibraev
Keyword(s):  
Neural Networks ◽  
Mathematical Model ◽  
Traffic Management ◽  
Urban Traffic ◽  
Control Parameters ◽  
Traffic Flows ◽  
Traffic Light ◽  
Traffic Lights ◽  
The Road ◽  
On The Road

One of the most pressing problems of large cities is the problem of traffic management of vehicles. The reason for this problem is an imperfect way to manage traffic flows. Traffic light regulation is of particular importance in traffic management. Most modern traffic light control systems operate at set time intervals and are not able to cope with the constantly changing situation on the road. A promising direction for solving this problem is to optimize the system using artificial neural networks. The advantage of neural networks is self-learning, which allows the system to adapt to the changing situation on the road. Despite numerous attempts, it has not yet been possible to obtain a high-quality mathematical model of urban traffic management. This model should determine the functional dependence of transport flow parameters on control parameters. Nowadays, traffic flows are regulated everywhere by means of traffic lights. If we can get a fairly accurate mathematical model of traffic flows, we can determine the optimal duration of the traffic signal phases to achieve the maximum capacity of the road network node. A fairly accurate mathematical model of traffic management that works in predictive mode will display an estimate of the optimal control parameters, as well as make correct decisions in emergency situations. Well-known mathematical models of road traffic take into account only the average values of traffic flows, and not the exact number of cars on each road section at a particular time.

Dynamic Routing of Emergency Vehicles with Traffic Management System and Implementation on CupCarbon for Smart Cities

2021 ◽  
Vol 9 (11) ◽  
pp. 1407-1412
Keyword(s):  
Traffic Congestion ◽  
Traffic Management ◽  
Management System ◽  
Smart Cities ◽  
Maximum Speed ◽  
Emergency Vehicle ◽  
Traffic Light ◽  
Emergency Vehicles ◽  
Traffic Management System ◽  
On The Road

The traffic congestion is one of the major problems in crowded cities, which causes people to spend hours on the road. In traffic congestion situations, finding alternate routes for emergency vehicles, which provides shortest travel time to nearby hospital is critically life-saving issue. In this paper, we propose a traffic management system and an algorithm for routing of an emergency vehicle. The algorithm uses distance between source and destination, maximum vehicle count, maximum speed, average speed, traffic light conditions on the roads, which are assumed to support vehicle-to-infrastructure (V2I) communication in 5G IoT network. Simulations are performed on CupCarbon IoT simulator platform for various test scenarios. The performance of the proposed emergency vehicle routing algorithm is compared against well known Link State algorithm. And, the results demonstrate the effectiveness of the proposed method.

scholarly journals PROGRAM OF LIGHT-FORMAT REGULATION ON THE BASIS OF CONTROLLED NETWORKS AND THE SATURATIONS’ FLOW: BASIC PRINCIPLES OF CALCULATION

2019 ◽  
Vol 16 (6) ◽  
pp. 680-691 ◽  
Author(s):  
A. N. Novikov ◽  
S. V. Eremin ◽  
A. G. Shevtsova
Keyword(s):  
Traffic Management ◽  
Optimization Problems ◽  
Light Regulation ◽  
Control Technique ◽  
Traffic Flows ◽  
Traffic Light ◽  
Two Phase ◽  
Traffic Lights ◽  
The Road ◽  
On The Road

Introduction. The paper deals with traffic light regulation. This task is always relevant. Thus, even for an ordinary intersection, depending on the intensity of traffic flows, the control cycles should differ significantly. This paper discusses all kinds of systems, namely, two-phase, three-phase, four-phase and others. In addition to solving optimization problems of regulation the authors propose to use the device managed network, which allows setting the configuration of the transport network as the base graph of the managed network, and then based on the parameterization of the graph of the throughput ability of the network to solve the optimization problem of selecting the control traffic and pedestrian flow.Methods and materials. For solving the problem of traffic management on the road network, the authors proposed to use the mechanisms of managed networks. As a result, the authors presented a technique based on the calculation of saturation flows, the main characteristic of the control technique, which was activated when there were no requests from the transport detectors to turn by the green signal.Results. The authors constructed a generalized simulation model of control phases of regulation based on the usage of controlled networks, depending on the intensity of traffic flows and formed a method of selecting modes of traffic lights for different traffic situations.Discussion and conclusions. The solution of the problem of traffic light regulation significantly affects the traffic management efficiency. The authors determine the main parameters based on the analysis of traffic light control methods. As a result of the calculation of the saturation flow and information about the intensity of traffic, the authors form the method of selecting the necessary modes of the phosphor object’s operation.The authors have read and approved the final manuscript. Financial transparency: the authors have no financial interest in the presented materials or methods. There is no conflict of interest.

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 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 Emergency Vehicle Priority Based System

2021 ◽  
pp. 377-382
Author(s):  
Sarfraz Ahmad ◽  
K. C. Maurya
Keyword(s):  
Traffic Congestion ◽  
Traffic Management ◽  
Green Light ◽  
Emergency Vehicle ◽  
Current Case ◽  
Traffic Lights ◽  
Current State ◽  
Emergency Vehicles ◽  
Vehicle Information ◽  
Police Cars

Every country's vehicular traffic is increasing, growing, and there is terrible traffic congestion at intersections. In the current case, most traffic lights have a fixed light sequence, so green light sequence is to determine with-out taking priority vehicles into account. As a result, priority crews such as police cars, ambulances, fire engines are still unable to perform, get stuck in traffic and come in late, which can result in the loss of valuable property and life, which does happen on occasion. The green light sequence is evaluated given the current state of traffic, without taking into account the existence of emergency vehicles. Our aim to this paper is to present a mechanism for scheduling emergency vehicles. It is provided to important such as access control protocol to convey emergency vehicle information to the Traffic Management Center (TMC) with time delay and to all alerts while using GPS techniques for acquiring emergency vehicle information. Only then is the emergency vehicle quickly dispatched, and the destination is reached on time. It would be helpful in the future for the prominence of casual vehicles.

Smart Cities: Study and Comparison of Traffic Light Optimization in Modern Urban Areas Using Artificial Intelligence

2018 ◽  
Vol 8 (2) ◽  
pp. 10
Author(s):  
Mustapha Kabrane ◽  
Salah-ddine Krit ◽  
Lahoucine El Maimouni
Keyword(s):  
Traffic Congestion ◽  
Urban Areas ◽  
Road Network ◽  
Smart Cities ◽  
Optimization Techniques ◽  
Traffic Light ◽  
Large Cities ◽  
Traffic Lights ◽  
The Road ◽  
Road Signs

In large cities, the increasing number of vehicles private, society, merchandise, and public transport, has led to traffic congestion. Users spend much of their time in endless traffic congestion. To solve this problem, several solutions can be envisaged. The interest is focused on the  system of road signs: The use of a road infrastructure is controlled by a traffic light controller, so it is a matter of knowing how to make the best use of the controls of this system (traffic lights) so as to make traffic more fluid. The values of the commands computed by the controller are determined by an algorithm which is ultimately, only solves a mathematical model representing the problem to be solved. The objective is to make a study and then the comparison on the optimization techniques based on artificial intelligence1 to intelligently route vehicle traffic. These techniques make it possible to minimize a certain function expressing the congestion of the road network. It can be a function, the length of the queue at intersections, the average waiting time, also the total number of vehicles waiting at the intersection

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 Railroad traffic light sensors to anticipate jams at junctions based on ATMega8

SinkrOn ◽  
2021 ◽  
Vol 6 (1) ◽  
pp. 144-156
Author(s):  
Amir Mahmud Husein ◽  
Alfredy Willim ◽  
Yandi Tumbur Nainggolan ◽  
Antonius Moses Simanggungsong ◽  
Prayoga Banjarnahor
Keyword(s):  
Traffic Congestion ◽  
Light Condition ◽  
Traffic Light ◽  
Infrared Sensors ◽  
Low Speed ◽  
The Road ◽  
Traffic Jams ◽  
Road Users ◽  
Railroad Crossings ◽  
On The Road

Traffic congestion is a problem that has long occurred in Indonesia, especially in big cities. Traffic congestion that occurs can cause various losses, one of which is time loss because it can only run at a very low speed. Then it will create a waste of energy, because going at low speed will require more fuel. Congestion is also able to increase the saturation of other road users, not only that traffic jams also have a bad impact on nature which causes air pollution. And there are many more impacts of traffic jams that can make traveling very uncomfortable. One of the locations of traffic jams often occurs on roads located around railroad crossings. Therefore, In this study, it is proposed to make a traffic light sensor adjacent to the train track to anticipate long traffic jams based on atmega8 and infrared sensors, with the stages of collecting data, recording transportation activities at the location of the jam, then designing a sensor device. The system built is to read the volume of vehicles on the road and prioritize the road with the highest volume of vehicles to get the green traffic light condition. Based on the results of the manufacture of infrared sensors and atmega8 can be tested to reduce the level of congestion at crossroads adjacent to the railroad.

scholarly journals RANCANG BANGUN PROTOTYPE SISTEM PENDETEKSI PELANGGARAN PADA ZEBRA CROSS DI LAMPU LALU LINTAS BERBASIS ARDUINO

Foristek ◽  
2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Uswatun Hasanah ◽  
Mery Subito ◽  
Muhammad Aristo Indrajaya
Keyword(s):  
Response Speed ◽  
Average Response ◽  
Traffic Light ◽  
Traffic Lights ◽  
The Road ◽  
Laser Sensors ◽  
Road Users ◽  
Traffic Violations ◽  
Road Intersections ◽  
On The Road

Current road users cannot be separated from the number of violators, therefore traffic lights are made to regulate traffic on the road. At traffic lights, there is also a zebra crossing which serves as a means of crossing the road for pedestrians. To minimize violations at road intersections, researchers designed a tool to detect traffic violations. Traffic violation detection tool is made in prototype form using a control system with Arduino nano and software. This traffic light system uses LDR and laser sensors to detect these violations by cutting the laser which sends light to the LDR. This tool is also equipped with a webcam camera that functions to photograph violations that occur and a buzzer that functions as a warning to officers and riders in the event of a violation with an average response speed of the webcam of 2.37 seconds and the average response speed of the buzzer is 0.4 seconds. . The snapshot from the webcam is saved automatically on your PC / Laptop.

Sign in / Sign up

Export Citation Format

Share Document