Title :
A vision-based approach to collision prediction at traffic intersections
Author :
Atev, Stefan ; Arumugam, Hemanth ; Masoud, Osama ; Janardan, Ravi ; Papanikolopoulos, Nikolaos P.
Author_Institution :
Dept. of Comput. Sci. & Eng., Univ. of Minnesota, Minneapolis, MN, USA
Abstract :
Monitoring traffic intersections in real time and predicting possible collisions is an important first step towards building an early collision-warning system. We present a vision-based system addressing this problem and describe the practical adaptations necessary to achieve real-time performance. Innovative low-overhead collision-prediction algorithms (such as the one using the time-as-axis paradigm) are presented. The proposed system was able to perform successfully in real time on videos of quarter-video graphics array (VGA) (320 × 240) resolution under various weather conditions. The errors in target position and dimension estimates in a test video sequence are quantified and several experimental results are presented.
Keywords :
computer vision; image sequences; monitoring; road traffic; traffic control; traffic information systems; collision prediction; collision warning system; quarter video graphics array resolution; target position estimation; traffic intersection monitoring; video sequence; vision based system; Automotive engineering; Hidden Markov models; Intelligent transportation systems; Real time systems; Road accidents; Road vehicles; Testing; Traffic control; Vehicle detection; Video sequences; Collision prediction; machine vision; real-time systems; tracking; traffic control (transportation);
Journal_Title :
Intelligent Transportation Systems, IEEE Transactions on
DOI :
10.1109/TITS.2005.858786
