scholarly journals Traffic Controlling System

2021 ◽  
Vol 9 (10) ◽  
pp. 1507-1512
Author(s):  
Rajvi Chokshi
Keyword(s):  
Real Time ◽  
Traffic Management ◽  
Processing Technique ◽  
Image Processing Technique ◽  
Reference Image ◽  
Present System ◽  
Real Time Traffic ◽  
Traffic Management System ◽  
On The Road ◽  
Evaluation Matrix

Abstract: In the present era, the population of people living in cities and the number of vehicles on the road is growing by the day. The necessity to govern lanes, thruways, and streets has become a significant concern as the urban population and, as a result, the number of vehicles has grown. Today's traffic framework places minimal emphasis on real-time traffic conditions, resulting in inefficient traffic management systems. Therefore, to overcome such limitations or drawbacks of the present system, the current research proposes a smart and efficient traffic management system that can analyze real-time traffic and take appropriate action. This is achieved by the application of an image processing technique, that would capture the real-time pictures of the paths to compare with the reference image of the path. The evaluation matrix is created to decide the amount of time each light must be on. In addition, an evaluation matrix is created. The purpose of the evaluation matrix is to determine how long each light must be turned on. The MATLAB 7.8 was used to perform the study.

scholarly journals Mobile Road Traffic Management System Using Weighted Sensor

2017 ◽  
Vol 11 (5) ◽  
pp. 147 ◽  
Author(s):  
Solomon Adegbenro Akinboro ◽  
Johnson A Adeyiga ◽  
Adebayo Omotosho ◽  
Akinwale O Akinwumi
Keyword(s):  
Real Time ◽  
Traffic Control ◽  
Urban Areas ◽  
Traffic Management ◽  
Management System ◽  
Road Traffic ◽  
Traffic Information ◽  
Traffic Light ◽  
Real Time Traffic ◽  
Traffic Management System

<p><strong>Vehicular traffic is continuously increasing around the world, especially in urban areas, and the resulting congestion ha</strong><strong>s</strong><strong> be</strong><strong>come</strong><strong> a major concern to automobile users. The popular static electric traffic light controlling system can no longer sufficiently manage the traffic volume in large cities where real time traffic control is paramount to deciding best route. The proposed mobile traffic management system provides users with traffic information on congested roads using weighted sensors. A prototype of the system was implemented using Java SE Development Kit 8 and Google map. The model </strong><strong>was</strong><strong> simulated and the performance was </strong><strong>assessed</strong><strong> using response time, delay and throughput. Results showed that</strong><strong>,</strong><strong> mobile devices are capable of assisting road users’ in faster decision making by providing real-time traffic information and recommending alternative routes.</strong></p>

scholarly journals Design and Development of Traffic Control System using Image Processing

2021 ◽  
Vol 9 (VI) ◽  
pp. 3247-3252
Author(s):  
G. Kalyan
Keyword(s):  
Image Processing ◽  
Real Time ◽  
Traffic Control ◽  
Traffic Congestion ◽  
Traffic Management ◽  
Red Light ◽  
Traffic Density ◽  
The Road ◽  
Real Time Traffic ◽  
On The Road

Traffic congestion is now a big issue. Although it seems to penetrate throughout the world, urban towns are the ones which are most effected. And it is expanding in nature that it is necessary to understand the density of roads in real time to better regulate signals and efficient management of transport. Various traffic congestions, such as limited capacity, unrestricted demand, huge Red Light waits might occur. While insufficient capacity and unlimited demand are somehow interconnected, their delay in lighting is difficult to encode and not traffic dependant. The necessity to simulate and optimise traffic controls therefore arises in order to better meet this growing demand. The traffic management of information, ramp metering, and updates in real-time has been frequently used in recent years for image processing and monitoring systems. An image processing can also be used for the traffic density estimation. This research describes the approach for the computation of real-time traffic density by image processing for using live picture feed from cameras. It focuses also on the algorithm for the transmission of traffic signals on the road according to the density of vehicles and therefore aims to reduce road congestion, which reduces the number of accidents.

Cloud IoT-Based Mobile Agent Framework for Real-Time Traffic Information Acquisition, Storage, and Retrieval

2019 ◽  
pp. 14-33
Author(s):  
Md Abdullah al Forhad ◽  
Md Nadim ◽  
Md. Rahatur Rahman ◽  
Shamim Akhter
Keyword(s):  
Real Time ◽  
Traffic Management ◽  
Management System ◽  
Traffic Information ◽  
Weather Data ◽  
Storage And Retrieval ◽  
Traffic Routing ◽  
Real Time Traffic ◽  
Traffic Management System ◽  
Vehicle Information

Traffic is an inevitable problem for metro cities around the globe. Intelligent traffic management system helps to improve the traffic flow by detecting congestions or incidents and suggesting appropriate actions on traffic routing. A new and dynamic internet-based decision-making tool for traffic management system was proposed and implemented in authors' previous works. The tool needs weather, road, and vehicle-related integrated information from different data repositories. Several online web portals host real-time weather data streams. However, road and vehicle information are missing in those portals. In addition, their coverage is limited to city-level congregate information but precise road segment-based information is necessary for real-time TMS decision. Internet of things (IoT)-based online sensors can be a solution for this circumstance. As a consequence, in this chapter, an IoT-based framework is proposed and implemented with several remote mobile agents. Agents are securely interconnected to the cloud, and able to collect and exchange data through wireless communication.

scholarly journals Robust Real-Time Traffic Surveillance with Deep Learning

2021 ◽  
Vol 2021 ◽  
pp. 1-18
Author(s):  
Jessica Fernández ◽  
José M. Cañas ◽  
Vanessa Fernández ◽  
Sergio Paniego
Keyword(s):  
Deep Learning ◽  
Real Time ◽  
Traffic Management ◽  
Spatial Association ◽  
Real Data ◽  
Weather Conditions ◽  
Research Area ◽  
Vehicle Tracking ◽  
Real Time Traffic ◽  
On The Road

Real-time vehicle monitoring in highways, roads, and streets may provide useful data both for infrastructure planning and for traffic management in general. Even though it is a classic research area in computer vision, advances in neural networks for object detection and classification, especially in the last years, made this area even more appealing due to the effectiveness of these methods. This study presents TrafficSensor, a system that employs deep learning techniques for automatic vehicle tracking and classification on highways using a calibrated and fixed camera. A new traffic image dataset was created to train the models, which includes real traffic images in poor lightning or weather conditions and low-resolution images. The proposed system consists mainly of two modules, first one responsible of vehicle detection and classification and a second one for vehicle tracking. For the first module, several neural models were tested and objectively compared, and finally, the YOLOv3 and YOLOv4-based network trained on the new traffic dataset were selected. The second module combines a simple spatial association algorithm with a more sophisticated KLT (Kanade–Lucas–Tomasi) tracker to follow the vehicles on the road. Several experiments have been conducted on challenging traffic videos in order to validate the system with real data. Experimental results show that the proposed system is able to successfully detect, track, and classify vehicles traveling on a highway on real time.

Intelligent Traffic Signal Monitoring System Using Image Processing

2021 ◽  
pp. 173-195
Author(s):  
SureshKumar M. ◽  
Anu Valliammai R.
Keyword(s):  
Real Time ◽  
Monitoring System ◽  
Traffic Management ◽  
Traffic Signal ◽  
Traffic Light ◽  
The Road ◽  
Real Time Traffic ◽  
Traffic Intersection ◽  
Signal Monitoring ◽  
On The Road

This project aims at making an intelligent traffic signal monitoring system that makes decisions based on real-time traffic situations. The choices will be such that the traditional red, green, or amber lighting scheme is focused on the actual number of cars on the road and the arrival of emergency services rather than using pure timing circuits to control car traffic by using what the traffic appears like via smart cameras to capture real-time traffic movement pictures of each direction. The control system will modify the traffic light control parameters dynamically in various directions due to changes in traffic flow, thus increasing the traffic intersection efficiency and ensuring improved traffic management. This work involves performing a traffic management study of the city.

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