00676572

Component

http://onlinepubs.trb.org...trr/1994/1453/1453-008.pdf

https://scholar.google.co...Wang&publication_year=1994

Freeway incidents often occur unexpectedly and cause undesirable traffic congestion, mobility loss, and environmental pollution even where computerized traffic management systems are installed and in operation. Automatic incident detection, being one of the primary functions of computerized freeway traffic management systems, must be able to detect all freeway incidents as soon as possible with minimum false alarms. In a study that evaluated the applications of fuzzy set theory to improve existing incident detection algorithms, the potential system performance was compared with that of conventional systems using real-world volume and occupancy data that were collected earlier. The potential benefits and needed improvements in the existing incident detection algorithms to take advantage of the promising fuzzy set methodology are summarized.

This paper appears in Transportation Research Record No. 1453, Intelligent Transportation Systems: Evaluation, Driver Behavior, and Artificial Intelligence. Distribution, posting, or copying of this PDF is strictly prohibited without written permission of the Transportation Research Board of the National Academy of Sciences. Unless otherwise indicated, all materials in this PDF are copyrighted by the National Academy of Sciences. Copyright © National Academy of Sciences. All rights reserved

01401256

English

p. 75-82

1994

Transportation Research Record

0309060613

Figures (7) ; References (22) ; Tables (1)

Algorithms; Freeways; Fuzzy sets; Highway traffic; Improvements; Incident detection

Highways; Operations and Traffic Management; I73: Traffic Control

TRIS, TRB

Apr 13 1995 12:00AM

• APPLICATIONS OF ARTIFICIAL NEURAL NETWORKS TO INTELLIGENT VEHICLE-HIGHWAY SYSTEMS
• CRITERIA AND METHODS FOR EVALUATING INTELLIGENT TRANSPORTATION SYSTEM PLANS AND OPERATIONAL TESTS
• EFFECT OF MODELING ASSUMPTIONS ON EVOLUTION OF QUEUES IN A SINGLE CORRIDOR
• FRAMEWORK FOR EVALUATING INTELLIGENT VEHICLE-HIGHWAY SYSTEMS
• INFLUENCE OF TRAFFIC INFORMATION ON DRIVERS' ROUTE CHOICE BEHAVIOR
• MODELS OF COMMUTERS' INFORMATION USE AND ROUTE CHOICE: INITIAL RESULTS BASED ON SOUTHERN CALIFORNIA COMMUTER ROUTE CHOICE SURVEY
• REGIONAL APPROACH TO STRATEGIC INTELLIGENT VEHICLE HIGHWAY SYSTEM PLANNING IN ORANGE COUNTY
• SHORT-TERM TRAFFIC FLOW PREDICTION: NEURAL NETWORK APPROACH
• URBAN RAIL CORRIDOR CONTROL THROUGH MACHINE LEARNING: AN INTELLIGENT VEHICLE-HIGHWAY SYSTEM APPROACH
• USE OF SYSTEM CHARACTERISTICS TO DEFINE CONCEPTS FOR AUTOMATED HIGHWAY SYSTEMS