TY - GEN
T1 - A video processing system for automated traffic data collection of gap size for roundabouts
AU - Dinh, Hai
AU - Tang, Hua
PY - 2017/6/12
Y1 - 2017/6/12
N2 - Traffic data collection and analysis is essential for designing roundabouts and improving safety at roundabouts. One of the main interested traffic data for roundabouts is often gap size. However, manual collection of gaps size by human operators is extremely laborious. In this work, we developed a system/tool to allow data mining of the recorded videos for automated extraction of gap size. The developed system has two main modules. The tracking module is used to derive raw data, which are vast amount of resulting outputs of vehicle trajectories for all tracked vehicles, which provide rich information for traffic data extraction as the trajectories give the position, size, shape and speed of the vehicle at each time moment. A post-processing data mining module is then used to automatically extract the interested traffic data. The extracted gap size has been compared to ground truth manual measurements and it is shown that an accuracy of almost 100% has been achieved. Compared to manual inspection, the proposed system/tool significantly saves time and cost.
AB - Traffic data collection and analysis is essential for designing roundabouts and improving safety at roundabouts. One of the main interested traffic data for roundabouts is often gap size. However, manual collection of gaps size by human operators is extremely laborious. In this work, we developed a system/tool to allow data mining of the recorded videos for automated extraction of gap size. The developed system has two main modules. The tracking module is used to derive raw data, which are vast amount of resulting outputs of vehicle trajectories for all tracked vehicles, which provide rich information for traffic data extraction as the trajectories give the position, size, shape and speed of the vehicle at each time moment. A post-processing data mining module is then used to automatically extract the interested traffic data. The extracted gap size has been compared to ground truth manual measurements and it is shown that an accuracy of almost 100% has been achieved. Compared to manual inspection, the proposed system/tool significantly saves time and cost.
UR - http://www.scopus.com/inward/record.url?scp=85021812258&partnerID=8YFLogxK
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U2 - 10.1109/CCECE.2017.7946597
DO - 10.1109/CCECE.2017.7946597
M3 - Conference contribution
AN - SCOPUS:85021812258
T3 - Canadian Conference on Electrical and Computer Engineering
BT - 2017 IEEE 30th Canadian Conference on Electrical and Computer Engineering, CCECE 2017
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 30th IEEE Canadian Conference on Electrical and Computer Engineering, CCECE 2017
Y2 - 30 April 2017 through 3 May 2017
ER -