Algorithm Fusion for Detecting Incidents on Singapore’s Central Expressway

Abstract

Many studies have focused mainly on the development of a single automatic incident detection algorithm to detect incident occurrences, and the performance obtained has often been mixed. In this study, an algorithm fusion method was developed using incident data collected from the Central Expressway in Singapore. This method explores the possibility of enhancing incident detection performance by combining the complementary advantages of a group of existing algorithms. It was found that the fused algorithm with the following options has outperformed the existing algorithms: Fusion Option II—selecting a combination of the best-performing algorithms, and Fusion Option III—applying different weightings to a group of algorithms. Compared with the existing dual variable/combined detector evaluation algorithms developed earlier for the same studied site, the fused algorithms performed significantly better, with false alarm rates between 0.2 and 1.0%. At a detection rate of 90%, these fused algorithms were able to reduce the false alarm rate by more than 55%. This algorithm fusion method had yielded promising performance and thus can serve as an alternative technique to the commonly practiced approach of either developing a new algorithm or applying the existing algorithms to detect expressway incident occurrences.