Real Time Freeway Incident Detection
The US Department of Transportation (US-DOT) estimates that over half of all congestion events are caused by highway incidents rather than by rush-hour traffic in big cities. Real-time incident detection on freeways is an important part of any modern traffic control center operation because it offers an opportunity to maximize road system performance. An effective incident detection and management operation cannot prevent incidents, however, it can diminish the impacts of non-recurring congestion problems. The main purpose of real-time incident detection is to reduce delay and the number of secondary accidents, and to improve safety and travel information during unusual traffic conditions. The purpose of this project is to evaluate two recently developed automatic incident detection algorithms. The majority of automatic incident detection algorithms are focused on identifying traffic incident patterns but may not adequately investigate possible similarities in patterns observed under incident-free conditions. When traffic demand exceeds road capacity, the traffic speed decreases significantly and the traffic enters a highly unstable regime often referred to as “stop-and-go” conditions. The most challenging part of real-time incident detection is recognition of traffic pattern changes when incidents happen during stop-and-go conditions. This work describes a case study evaluation of two recently evolved incident detection methods using data from the Dallas, Texas traffic control center.
- Record URL:
- Summary URL:
-
Supplemental Notes:
- This document was sponsored by the U.S. Department of Transportation, University Transportation Centers Program.
-
Corporate Authors:
University of Texas, Austin
Center for Transportation Research, 1616 Guadalupe Street
Austin, TX United States 78701-1255Southwest Region University Transportation Center
Texas A&M University
3135 TAMU
College Station, TX United States 77843-3135Research and Innovative Technology Administration
1200 New Jersey Avenue, SE
Washington, DC United States 20590 -
Authors:
- Motamed, Moggan
- Machemehl, Randy
- Publication Date: 2014-4
Language
- English
Media Info
- Media Type: Digital/other
- Features: Figures; References; Tables;
- Pagination: 42p
Subject/Index Terms
- TRT Terms: Algorithms; Case studies; Congestion management systems; Freeways; Incident detection; Real time information; Traffic control; Traffic flow
- Geographic Terms: Dallas (Texas)
- Subject Areas: Highways; Operations and Traffic Management; I73: Traffic Control;
Filing Info
- Accession Number: 01530899
- Record Type: Publication
- Report/Paper Numbers: SWUTC/14/600451-00083-1, 600451-00083-1
- Contract Numbers: DTRT12-G-UTC06
- Files: UTC, TRIS, RITA, ATRI, USDOT
- Created Date: Jul 24 2014 3:15PM