Travel time data obtained from vehicle re-identification systems is becoming increasingly available due to the implementation of various technologies such as license plate recognition, inductive loop signature systems, and Bluetooth-based wireless vehicle identification. These advances present an opportunity to develop and apply automated incident detection methods. However, travel time data and incident detection have both been traditionally focused on freeways and other free-flowing roads. This research developed an incident detection procedure to better support travel time data for arterials. The accuracy of the procedure was evaluated by comparing the results with reported incident data.
Incident detection methods have primarily fallen into three categories: roadway-based algorithms using loop detector data, probe-based using data from vehicles equipped with toll transponders or GPS receivers, and driver-based techniques that identify driver responses to incidents. The method developed in this research is considered a probe-based approach. However, most probe-based incident detection relies on travel time data and so this research is unique in that it uses a new method (vehicle re-identification) to support incident detection on arterials. The objective of the incident detection procedure is to correctly identify potential incidents as soon as possible, and to do so with a low false alarm rate.
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