Title :
Development of Dual-Station Automated Expressway Incident Detection Algorithms
Author :
Mak, Chin Long ; Fan, Henry S L
Author_Institution :
Duffill Watts Pte. Ltd., Singapore
Abstract :
Most automated expressway incident detection algorithms were successfully developed using loop-based traffic occupancy from their local conditions. However, the performance of these algorithms was not satisfactory on sites that have installed a video-based detector system. Due to different traffic detector technologies and varying driving behaviors from one region to another, it is of interest to develop an algorithm that uses video-based data. This paper used a total of 160 incidents collected along the 15-km central expressway (CTE) in Singapore to develop two new dual-station algorithms: the combined detector evaluation (CODE) and the flow-based CODE algorithms. On average, the flow-based CODE algorithm yielded better performance than the CODE in terms of average reduced false alarms of about 16%. Measures were also taken to ensure that the algorithms were properly developed and assessed. It was found that the CODE algorithm can detect, on average, up to 57% of the incidents faster than those of existing detection methods on CTE.
Keywords :
automated highways; video signal processing; Singapore; dual-station algorithm; dual-station automated expressway incident detection; flow-based CODE algorithm; flow-based combined detector evaluation algorithms; loop-based traffic occupancy; video-based data; video-based detector system; Change detection algorithms; Detection algorithms; Detectors; Intelligent transportation systems; Mobile handsets; Smart cameras; Surveillance; Time measurement; Traffic control; Vehicle driving; Incident detection; intelligent transportation systems; traffic management; video cameras;
Journal_Title :
Intelligent Transportation Systems, IEEE Transactions on
DOI :
10.1109/TITS.2007.903433