DESIGN OF NEURAL NETWORK MODELS FOR LANE-BLOCKING PATTERNIDENTIFICATION IN ARTERIAL STREETS

摘要

Recent research has shown the good potential of artificial neural network (ANN)rnbased incident detection models in detecting the presence of an incident. Beside incidentrnpresence, incident information that including detailed incident location and severity is morernvaluable to traffic management and control in urban area. This paper presents four differentrndesigns of ANN models in identifying arterial street incidents involving lane blockages, withrnthe objectives of not only detecting the incidents but also classifying the lane-blockingrnpatterns. The performances of the models in detecting both incident case and identifyingrnlane-blocking pattern were compared in this paper.