Smart mobile sensor application for road traffic analysis (Tari'ak)

Author(s):  
Aziz Barbar ◽  
Anis Ismail ◽  
Rami Khawandi
Author(s):  
Needhi U. Gaonkar

Abstract: Traffic analysis plays an important role in a transportation system for traffic management. Traffic analysis system using computer vision project paper proposes the video based data for vehicle detection and counting systems based on the computer vision. In most Transportation Systems cameras are installed in fixed locations. Vehicle detection is the most important requirement in traffic analysis part. Vehicle detection, tracking, classification and counting is very useful for people and government for traffic flow, highway monitoring, traffic planning. Vehicle analysis will supply with information about traffic flow, traffic summit times on road. The motivation of visual object detection is to track the vehicle position and then tracking in successive frames is to detect and connect target vehicles for frames. Recognising vehicles in an ongoing video is useful for traffic analysis. Recognizing what kind of vehicle in an ongoing video is helpful for traffic analysing. this system can classify the vehicle into bicycle, bus, truck, car and motorcycle. In this system I have used a video-based vehicle counting method in a highway traffic video capture using cctv camera. Project presents the analysis of tracking-by-detection approach which includes detection by YOLO(You Only Look Once) and tracking by SORT(simple online and realtime tracking) algorithm. Keywords: Vehicle detection, Vehicle tracking, Vehicle counting, YOLO, SORT, Analysis, Kalman filter, Hungarian algorithm.


Author(s):  
H. S. Mohana ◽  
M. Ashwathakumar

Traffic congestion and violation of traffic rules are very common in most of the road transport system. Continuous monitoring is becoming difficult. To improve the quality of road transport monitoring and control, the best possible alternative is machine vision. In this review, several works by researchers on traffic analysis are detailed, studied and reviewed critically for the purpose. Further, an attempt is made to classify the different road traffic analysis approaches available in the literature. Classification is based on principle used, algorithm adopted, techniques used, technology behind and other special considerations of the researchers.


2005 ◽  
Vol 10 (4) ◽  
pp. 315-332 ◽  
Author(s):  
E. Atkočiūnas ◽  
R. Blake ◽  
A. Juozapavičius ◽  
M. Kazimianec

The article presents an application of computer vision methods to traffic flow monitoring and road traffic analysis. The application is utilizing image-processing and pattern recognition methods designed and modified to the needs and constrains of road traffic analysis. These methods combined together gives functional capabilities of the system to monitor the road, to initiate automated vehicle tracking, to measure the speed, and to recognize number plates of a car. Software developed was applied in and approved with video monitoring system, based on standard CCTV cameras connected to wide area network computers.


2016 ◽  
Vol 8 (3) ◽  
pp. 63-74 ◽  
Author(s):  
Paul Fuxjaeger ◽  
Stefan Ruehrup ◽  
Thomas Paulin ◽  
Bernd Rainer

2010 ◽  
Vol 2 (2) ◽  
pp. 64-78
Author(s):  
H. S. Mohana ◽  
M. Ashwathakumar

Traffic congestion and violation of traffic rules are very common in most of the road transport system. Continuous monitoring is becoming difficult. To improve the quality of road transport monitoring and control, the best possible alternative is machine vision. In this review, several works by researchers on traffic analysis are detailed, studied and reviewed critically for the purpose. Further, an attempt is made to classify the different road traffic analysis approaches available in the literature. Classification is based on principle used, algorithm adopted, techniques used, technology behind and other special considerations of the researchers.


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