Enhancing Traffic Flow Using Computer Vision Based - Dynamic Traffic Light Control and Lane Management (original) (raw)

Traffic control system by using Image Processing

Object detection is very important in intelligent transport systems implementation. Counting the number of vehicles can help in controlling the traffic flow. Intelligent transportation systems are required to control the traffic automatically and seamlessly. There are many algorithms for object detection but are not very accurate as compared to the state-of-the-art algorithm YOLO. The YOLO (You only look once) algorithm is used to predict the class of an object which is based on regression and it predicts bounding box and classes for complete image in a single iteration. The proposed system is a web-based application which will be depending on a camera for video input. The video will be processed and will be classified based on classes. The proposed system calculates the number of vehicles. The count of vehicles will be used to change traffic lights on traffic signals. Different locations and variations of roads are processed to check the accuracy and efficiency of the system. The test results indicate that our system works efficiently in sufficient ambient light. The system is simple and very easy to implement.

Traffic Control System using Image Processing

International Journal for Research in Applied Science and Engineering Technology

The current traffic control system in Indian cities can be improved as it does not take into consideration the randomness in the traffic density. A large amount of time is being wasted at the signal even though there is no traffic because the timings for red and green light are fixed for all the lanes, irrespective of the traffic density. Currently the traffic signals have fixed signal timings which change every 30sec to 120sec. Such timings which are predetermined are inadequate for real time applications of the traffic control system. In order to control the traffic in efficient way we use image processing to analyze the traffic density on a particular lane and accordingly change the signal time.

REAL TIME TRAFFIC LIGHT CONTROL USING IMAGE PROCESSING

As the problem of urban traffic congestion spreads, there is a pressing need for the introduction of advanced technology and equipment to improve the state-of-the-art of traffic control. Traffic problems nowadays are increasing because of the growing number of vehicles and the limited resources provided by current infrastructures. The simplest way for controlling a traffic light uses timer for each phase. Another way is to use electronic sensors in order to detect vehicles, and produce signal that cycles. We propose a system for controlling the traffic light by image processing. The system will detect vehicles through images instead of using electronic sensors embedded in the pavement. A camera will be installed alongside the traffic light. It will capture image sequences. The image sequence will then be analyzed using digital image processing for vehicle detection, and according to traffic conditions on the road traffic light can be controlled..

INTELLIGENT TRAFFIC CONTROL USING IMAGE PROCESSING

In modern life we have to face with many problems one of which is traffic congestion becoming more serious day after day. It is said that the high tome of vehicles, the scanty infrastructure and the irrational distribution of the development are main reasons for augmented traffic jam. The major cause leading to traffic jam is the high number of vehicle which was caused by the population and the development of economy. To unravel this problem, the government should encourage people to use public transport or vehicles with small size such as bicycles or make tax on personal vehicles. Particularly, in some Asian countries such as Viet Nam, the local authorities passed law limiting to the number of vehicles for each family. The methods mentioned above are really efficient in fact. That the inadequate infrastructure cannot handle the issue of traffic is also a decisive reason. The public conveyance is available and its quality is very bad, mostly in the establishing countries. Besides, the highway and roads are incapable of meeting the requirement of increasing number of vehicle. Instead of working on roads to accommodate the growing traffic various techniques have been devised to control the traffic on roads like embedded controllers that are installed at the junction. "Intelligent traffic control using image processing" technique that we propose overcomes all the limitations of the earlier (in use) techniques used for controlling the traffic. Earlier in automatic traffic control use of timer had a drawback that the time is being wasted by green light on the empty. This technique avoids this problem. Upon comparison of various edge detection algorithms, it was inferred that Canny Edge Detector technique is the most efficient one. The project demonstrates that image processing is a far more efficient method of traffic control as compared to traditional techniques. The use of our technique removes the need for extra hardware such as sound sensors. The increased response time for these vehicles is crucial for the prevention of loss of life. Major advantage is the variation in signal time which control appropriate traffic density using Image matching. The accuracy in calculation of time due to single moving camera depends on the registration position while facing road every time. Output of our code clearly indicated some expected results. It showed matching in almost every interval that were decided as lots of traffic, more traffic and less traffic. (iii)

Intelligent Traffic Control System using Image Processing

2016

Traffic congestion is becoming more and more serious day by day. Main reasons for augmented traffic jam are increasing number of vehicles, the poor infrastructure and no proper distribution. The main reason for traffic is increased number of vehicles and increased number of population and development of country as whole. Management of traffic in India is a tough job and only manual efforts cannot solve this serious issue. We need a system to handle this situation more effectively. We need a dynamic system that is capable of controlling traffic as well as avoid congestion of roads, known as Intelligent Traffic Control System. In this project, we are dealing with traffic via image processing. Using different types of image processing algorithms, the vehicles can be detected on basis of which traffic lights can switch.

Traffic Image Processing System

2015

Traffic flow never remains the same on any given time of the day, varying substantially from morning to evening, generally peaking in the evening office hours. A common man has to face different traffic conditions in his daily routine from nerve racking traffic jams to almost empty roads. The fixed nature of the traffic lights fail to take this in to account and all this leads to increase in waiting time for every vehicle and thus wasting precious time. This increase in waiting time has a cascading effect on fuel consumption too and thereby having severe consequences on the environment. In this article, we shed light on these issues and present a dynamic system that overcomes all these drawbacks. We make use of web cameras mounted on street lights to capture still images of the traffic which then undergo a series of steps related to Image Processing and Image Analysis. Finally, we calculate the traffic volume and operate the traffic light's timer accordingly. All this is automa...

Machine Vision Algorithms Applied to Dynamic Traffic Light Control

Dyna (Medellin, Colombia)

This paper presents a fuzzy traffic controller that in an autonomous, centralized and efficient way, manages vehicular traffic flow in a group of intersections. The system uses a computer vision algorithm to detect the number of cars in images captured by a set of strategically placed cameras at every intersection. Using this information, the system selects the sequence of actions that optimize traffic flow within the control area, in a simulated scenario. The results obtained show that the system reduces the delay times for each vehicle by 20% and that the controller is able to adapt smoothly to different flow changes.

A Smart Traffic Control System Using Image Processing: A Review

Journal of Southwest Jiaotong University, 2020

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.

Methods for Effective Traffic Control using Image Processing

2018

As the issue of urban action blockage spreads, there is a pressing necessity for the introduction of pattern setting advancement and apparatus to upgrade the best in class of development control. Development issues now a days are growing an immediate consequence of the people increases and moreover number of vehicles also augments and the compelled resources given by current structures. The minimum troublesome course to control a development light uses clock for each stage. Another course is to use electronic sensors with the true objective to recognize vehicles, and make hail that cycles. By and by, the best way for movement controlling and watching is using picture getting ready. The structure will perceive vehicles through pictures instead of using electronic sensors introduced in the black-top. A CCTV camera will be presented close by of the action light. It will get picture groupings. The image gathering will then be destitute down using modernized picture dealing with for vehi...