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 ({A figure is presented}-sim) was developed. An integral component of such system is a microscopic simulator, {A figure is presented}-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. {A figure is presented}-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 ({A figure is presented}-sim-fl). The {A figure is presented}-sim-fl uses the detector data as well as other link properties in flagging detecting incidents. The {A figure is presented}-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.