A fuzzy clustering-based approach to automatic freeway incident detection and characterization

摘要

Automatic incident detection and characterization is urgently required in the development of advanced technologies used of reducing non-recurrent traffic congestion on freeways. This paper presents a new method which is constructed primarily on the basis of the fuzzy clustering theories to identify automatically freeway incidents. The proposed approach is capable of distinguishing the time-varying patterns of incident-induced traffic states form the patterns of incident-free traffic states, and characterizing incidents with respect to the onset and end time steps of incidents, incident location, the temporal and spatial change patterns of incident-related traffic variables in response to the impacts of incidents on freeway traffic flows in real time.