A fuzzy-based system for incident detection in urban street networks
Detecting incidents on urban streets or arterials using loop detector data is quite challenging. The pattern of the incident could be quite similar to non-incident cases as intersections get congested. This paper describes the development of a fuzzy logic for incident detection. An Integrated System for Incident Management ( -sim) was developed. An integral component of such system is a microscopic simulator, -sim-s, an object-oriented model that allows for virtual detector installations at different locations, modeling different intersection layouts, traffic control types and timing, and link characteristics. -sim-s was utilized to generate various incident scenarios and extracting associated detectors accumulative counts. A data clustering technique was utilized to consolidate the various incident scenarios into a single data set for the development of the Fuzzy Logic for incident detection at intersections ( -sim-fl). The -sim-fl uses the detector data as well as other link properties in flagging detecting incidents. The -sim-fl can be used to indicate the possibility of an incident, a stalled vehicle, or a sort of traffic disturbance. The devised logic was validated using separate simulation-based incident scenarios.
incident detection intersections fuzzy logic validation accident patterns simulation modeling neurofuzzy logic calibration real-time system