01366497

Component

Traffic data of multiple vehicle types are important for pavement design, traffic operations and traffic control. For the complex traffic in developing countries, no suitable tool is available for collecting such data. Considering the importance of these data and problems of traffic data collection, a new video-based traffic data collection system for multiple vehicle types is developed. This image processing-based system can track and classify vehicles under mixed traffic conditions. The type and speed of every passing vehicle are recognized. It is worth mentioning that this system takes the cross-lane vehicles into consideration and takes some measures to reduce the classification errors caused by vehicle occlusions. Finally, the flows and mean speeds of multiple vehicle types are output. This system was tested under four different weather conditions. The accuracy of vehicle counting was 97.4% and the error of vehicle classification was 8.3%. The correlation coefficient of speeds detected by this system and radar gun was 0.898 and the mean error of speed detection by this system was only 2.3 km/h. This indicates that this system is reliable for collecting traffic data of multiple vehicle types.

This paper was sponsored by TRB committee ABJ35 Highway Traffic Monitoring

01362476

12-1340

English

18p

2012

Transportation Research Board 91st Annual Meeting

Digital/other

Figures; Photos; References; Tables

Automatic data collection systems; Automatic vehicle detection and identification systems; Image processing; Reliability (Statistics); Traffic data; Vehicle mix

Data and Information Technology; Highways; I71: Traffic Theory

Transportation Research Board Annual Meeting 2012 Paper #12-1340

TRIS, TRB

Feb 8 2012 5:01PM