01334197

Component

This paper evaluates a video-based traffic monitoring system developed at Clemson University that is capable of collecting vehicle count, speed, and classification data. In contrast with traditional video-based approaches based upon virtual detection zones, the system relies upon a combination of computer vision techniques to track vehicles through the series of image frames. Vehicles are classified using an algorithm that calculates a vehicle’s length, width, and height. The system is evaluated based on its ability to collect volume, speed, and classification data using more than 90 hours of traffic data collected from installations along highways in New York, Maryland, and South Carolina. The evaluation is performed with respect to sensors installed at the locations, where available, as well as with respect to ground truth obtained by manually viewing the video. The system’s performance is measured under different environmental conditions, at different times of day/night, with and without shadows, and with cameras both low and high off the ground. Overall, the system is able to produce counts hourly per-lane counts with less than 5% error, with the error reducing to less than 0.5% when aggregated over a 24-hour period. Average speeds are estimated with less than 1 mph error, and vehicles are classified into three length-based bins with less than 3% error.

The DVD lists the title of this paper as: Evaluation of Computer-Vision Tracking System for Collecting Traffic Data.

01329018

11-4162

English

17p

2011

Transportation Research Board 90th Annual Meeting

DVD

Figures; Maps; Photos; References (17) ; Tables (5)

Computer vision; Data collection; Sensors; Tracking systems; Traffic counting; Traffic data; Traffic surveillance

Maryland; New York (State); South Carolina

Data and Information Technology; Highways; History; Operations and Traffic Management; I72: Traffic and Transport Planning

Transportation Research Board Annual Meeting 2011 Paper #11-4162

TRIS, TRB

Feb 17 2011 6:46PM