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.

scholarly journals Adaptive Traffic Management System using CNN (YOLO)

2021 ◽  
Vol 9 (VI) ◽  
pp. 3726-3732
Author(s):  
B. Sowmya
Keyword(s):  
Real Time ◽  
Traffic Flow ◽  
Traffic Control ◽  
Traffic Congestion ◽  
Traffic Management ◽  
Object Identification ◽  
Traffic Signal ◽  
Traffic Density ◽  
Loop Control ◽  
Control Framework

The huge number of vehicles on the roadways is making congestion a significant problem. The line longitudinal vehicle waiting to be processed at the crossroads increases quickly, and the traditionally used traffic signals are not able to program it properly. Manual traffic monitoring may be an onerous job since a number of cameras are deployed over the network in traffic management centers. The proactive decision-making of human operators, which would decrease the effect of events and recurring road congestion, might contribute to the easing of the strain of automation.The traffic control frameworks in India are now needed as it is an open-loop control framework, without any input or detection mechanism. Inductive loops and sensors employed in existing technology used to detect the number of passing vehicles. The way traffic lights are adapted is highly inefficient and costly in this existing technology. The aim was to build a traffic control framework by introducing a system for detection ,which gives an input to the existing system (closed loop control system) in order to adapt to the changing traffic density patterns and to provide the controller with a crucial indication for ongoing activities. By this technique, the improvement of the signals on street is extended and thus saves time by preventing traffic congestion. This study proposes an algorithm for real-time traffic signal control, depending on the traffic flow. In reality, the features of competitive traffic flow at the signposted road crossing are used by computer vision and by machine learning. This is done by the latest, real-time object identification, based on convolutional Neural Networks network called You Look Once (YOLO). Traffic signal phases are then improved by data acquired in order to allow more vehicles to pass safely over minimal wait times, particularly the line long and the time of waiting per vehicle.This adjustable traffic signal timer is used to calculate traffic density utilizing YOLO object identification using live pictures of cameras in intervals and adjusts the signal timers appropriately, therefore decreasing the road traffic congestion, ensuring speedier transit for persons, and reducing fuel consumption. The traffic conditions will improve enormously at a relatively modest cost. Inductive loops are a viable but costly approach. This method thereby cuts expenses and outcomes quickly.

scholarly journals A Smart Traffic Control System Using Image Processing: A Review

2020 ◽  
Vol 55 (1) ◽  
Author(s):  
Shaimaa Abbas Fahdel Al-Abaid
Keyword(s):  
Image Processing ◽  
Control System ◽  
Traffic Control ◽  
Traffic Congestion ◽  
Traffic Accidents ◽  
Traffic Density ◽  
Image Processing Techniques ◽  
Traffic Control System ◽  
On The Road ◽  
Processing Techniques

The global population and number of vehicles on the road are continuously increasing. Currently, most countries around the world face traffic problems. One of the major causes of such problems is ineffective traffic management such as greenhouse emissions, traffic accidents, health damages and time spent, resulting in frequent traffic congestion at major intersections. Therefore, an effective management system is needed to smartly handle traffic congestion on streets, highways, and roads. In the present study, we aimed to evaluate different traffic control systems and their image processing techniques to help manage traffic density. We created a model for a traffic control system based on information received from images of roads taken by a video camera and image processing techniques used to control traffic congestion on roads.

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.

scholarly journals Circuitry and Proof of Concept for an Adaptive Traffic Control System

2021 ◽  
Vol 9 (VI) ◽  
pp. 4063-4067
Author(s):  
M Vaishnavi
Keyword(s):  
Image Processing ◽  
Control System ◽  
Open Source ◽  
Real Time ◽  
Traffic Control ◽  
Proof Of Concept ◽  
The Road ◽  
Traffic Control System ◽  
On The Road ◽  
Adaptive Traffic Control

This paper illustrates the circuitry and proof of concept of a novel density based traffic mitigating system for the vehicles. The intention of this paper is to make an adaptive signalling system, which can be optimally used in real-time. This project is accomplished with the help of NVIDIA Jetson Nano and utilizes python for image processing as open source in order to measure the size of the traffic on the road.

scholarly journals IoT Based Traffic Control System using Image Processing

2021 ◽  
Vol 9 (VII) ◽  
pp. 317-321
Author(s):  
Mr. Sachin Tyagi
Keyword(s):  
Image Processing ◽  
Control System ◽  
Real Time ◽  
Traffic Control ◽  
Traffic Management ◽  
Raspberry Pi ◽  
Traffic System ◽  
Traffic Efficiency ◽  
Real Time Traffic ◽  
Traffic Control System

In the current scenario we can see that the traffic jam has become a serious problem in rapidly growing cities (As per their population) of India by which there is increase in air pollution, Fuel consumption as well as vehicular density. So there is a requirement to find a new way for traffic controlling traffic system which will be managed through real time IoT based traffic control system using image processing. This is a smart traffic management system that is designed to control real time traffic system which consist of components of Raspberry Pi, Pi camera. Raspberry pi is the key component which is used to control all performance multitasking. By using cameras, we monitor different lanes constantly. Image processing is used to examine detection and counting no. of vehicles in different lanes. It increases the traffic efficiency and clearance. The signal light will be decided as per the no. of vehicle count using image processing.

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 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 The Dynamic Control of the Light Signalling Device in Real-Time

2019 ◽  
Vol 292 ◽  
pp. 03014
Author(s):  
Jan Mrazek ◽  
Lucia Duricova Mrazkova ◽  
Martin Hromada ◽  
Jana Reznickova
Keyword(s):  
Real Time ◽  
Traffic Control ◽  
Dynamic Control ◽  
Traffic Density ◽  
Light Signaling ◽  
Dynamic Traffic ◽  
Real Time Control ◽  
Real Time Traffic ◽  
Time Control ◽  
Control Dynamic

The article is focused on the issue of interval on a light signaling device. Light signaling devices operate on different systems by means of which they are controlled. The control problem is a very static setting that does not respond to real-time traffic. Important variables for dynamic real-time control are traffic density in a selected area along with average speed. These variables are interdependent and can be based on dynamic traffic control. Dynamic traffic control ensures smoother traffic through major turns. At the same time, the number of harmful CO2 emitted from the means of transport should be reduced to the air. When used in low operation, power consumption should be reduced.

scholarly journals PENGARUH SUKARELAWAN PENGATUR LALU LINTAS TERHADAP KINERJA SIMPANG TAK BERSINYAL GANESHA SURAKARTA

2019 ◽  
Vol 19 (2) ◽  
pp. 133-142
Author(s):  
Gus Maelan Irfana ◽  
Nurul Hidayati ◽  
Sri Sunarjono
Keyword(s):  
Traffic Control ◽  
Traffic Congestion ◽  
Motor Vehicle ◽  
Positive Influence ◽  
Degree Of Saturation ◽  
Highway Capacity ◽  
Highway Capacity Manual ◽  
The Road ◽  
On The Road ◽  
The City

Abstract Traffic congestion in the City of Surakarta gave rise to a phenomenal figure among motor vehicle drivers, called the Traffic Control Volunteers or abbreviated as Supeltas. This Supeltas is present on the road to help organize the movement of traffic, as happened at the Surakarta Ganesha Unsignalized Intersection. This study aims to determine the influence of the existence of Supeltas on capacity, degree of saturation, delay, and queuing opportunities that occur at the intersection. The analysis was carried out using the 1997 Indonesian Highway Capacity Manual. The results showed that the intersection without Supeltas had a capacity of 3,114.03 pcu/hour and a degree of saturation of 1.47, while the same intersection but with Supeltas had a capacity of 3,136.81 pcu/hour and a degree of saturation of 1.51. These results indicate that Supeltas has a positive influence on the performance of the intersection. Nevertheless, the degree of saturation in the location increased due to the increase in traffic volume as well as increased capacity. Keywords: unsignalized intersection, intersection performance, intersection capacity, degree of saturation  Abstrak Kemacetan lalu lintas di Kota Surakarta memunculkan sosok fenomenal di kalangan pengendara kendaraan bermotor, yang disebut Sukarelawan Pengatur Lalu Lintas atau disingkat Supeltas. Supeltas ini hadir di jalan untuk membantu mengatur pergerakan lalu lintas, seperti yang terjadi di Simpang Tak Bersinyal Ganesha Surakarta. Penelitian ini bertujuan untuk menentukan pengaruh keberadaan Supeltas terhadap kapasitas, derajat kejenuhan, tundaan, dan peluang antrian yang terjadi di simpang tersebut. Analisis dilakukan dengan menggu-nakan Manual Kapasitas Jalan Indonesia 1997. Hasil analisis menunjukkan bahwa simpang tanpa Supeltas memiliki kapasitas sebesar 3.114,03 smp/jam dan derajat kejenuhan 1,47, sedangkan simpang yang sama tetapi dengan Supeltas memiliki kapasitas sebesar 3.136,81 smp/jam dan derajat kejenuhan 1,51. Hasil tersebut menunjukkan bahwa Supeltas mempunyai pengaruh positif terhadap kinerja simpang. Meskipun demikian, derajat kejenuhan di lokasi tersebut meningkat karena bertambahnya volume lalu lintas di samping kapasitas yang juga meningkat. Kata-kata kunci: simpang tak bersinyal, kinerja simpang, kapasitas simpang, derajat kejenuhan

scholarly journals Mixed Vehicular Traffic Flow Model on an Inclined Multilane Road

2020 ◽  
Vol 5 (7) ◽  
pp. 331-342
Author(s):  
Delina Mshai Mwalimo ◽  
Mary Wainaina ◽  
Winnie Kaluki
Keyword(s):  
Traffic Flow ◽  
Traffic Congestion ◽  
Traffic Management ◽  
Flow Model ◽  
Free Flow ◽  
Traffic Density ◽  
Fundamental Diagram ◽  
Traffic Flow Model ◽  
The Road ◽  
Slow Moving

This study outlines the Kerner’s 3 phase traffic flow theory, which states that traffic flow occurs in three phases and these are free flow, synchronized flow and wide moving jam phase. A macroscopic traffic model that is factoring road inclination is developed and its features discussed. By construction of the solution to the Rienmann problem, the model is written in conservative form and solved numerically. Using the Lax-Friedrichs method and going ahead to simulate traffic flow on an inclined multi lane road. The dynamics of traffic flow involving cars(fast moving) and trucks(slow moving) on a multi-lane inclined road is studied. Generally, trucks move slower than cars and their speed is significantly reduced when they are moving uphill on an in- clined road, which leads to emergence of a moving bottleneck. If the inclined road is multi-lane then the cars will tend to change lanes with the aim of overtaking the slow moving bottleneck to achieve free flow. The moving bottleneck and lanechange ma- noeuvres affect the dynamics of flow of traffic on the multi-lane road, leading to traffic phase transitions between free flow (F) and synchronised flow(S). Therefore, in order to adequately describe this kind of traffic flow, a model should incorporate the effect of road inclination. This study proposes to account for the road inclination through the fundamental diagram, which relates traffic flow rate to traffic density and ultimately through the anticipation term in the velocity dynamics equation of macroscopic traffic flow model. The features of this model shows how the moving bottleneck and an incline multilane road affects traffic transistions from Free flow(F) to Synchronised flow(S). For a better traffic management and control, proper understanding of traffic congestion is needed. This will help road designers and traffic engineers to verify whether traffic properties and characteristics such as speed(velocity), density and flow among others determines the effectiveness of traffic flow.

Sign in / Sign up

Export Citation Format

Share Document