Abstract

This research effort focused on the development of an automatic road incident detection and characterization system which will lead to the reduction of non-recurrent traffic congestion on freeways. An algorithmic methodology was developed for incorporation and enhancement of the existing South Carolina Department of Transportation (SCDOT) evacuation analysis system. Analysis of the existing system's input data helped determine the specific model needed. Investigation included a series of traffic analysis algorithms that consider: 1) identification of prevalent traffic flow conditions during a predetermined time window, 2) recognition of incident occurrence, 3) incident characterization, and 4) subsequent routing. The algorithmic methodology initially developed by Sheu (2002) was considerably expanded and adapted to the available SCDOT traffic data. This modified approach was then incorporated into a general system design document to establish definitions and descriptions of the proposed enhanced system. This initiative will provide traffic officials with relevant insights and expertise to detect and characterize emergency situations. It represents a significant improvement over the labor-intensive traffic monitoring systems currently used by many state DOTs, which lack automated capabilities for incident detection and characterization.

Recommended Citation

Moynihan, Gary P.; Fonseca, Daniel J.; Brumback, Terry; and Fernandes, Huston (2009) "Evacuation Decision Support System for Road Incident Detection and Characterization," Journal of Homeland Security and Emergency Management: Vol. 6 : Iss. 1, Article 48.
DOI: 10.2202/1547-7355.1527
Available at: http://www.bepress.com/jhsem/vol6/iss1/48