System and method for detecting traffic anomalies

US6177885A · kind A · utility

Assignee

• Esco Electronics, Inc.

Inventors

• Roark D. Weil · Olivette, US
• Asdrubal Garcia-Ortiz · Chesterfield, US
• John R. Wootton · Chesterfield, US

Key dates

• Filing date: Nov 3, 1998
• Grant date: Jan 23, 2001
• Expiry date: Nov 3, 2018

Classification

• Technology area (CPC G): Physics
• CPC primary: G08G1/0104
• WIPO field: Control
• WIPO sector: Instruments

Abstract

A traffic incident detection system (10) includes both the collection and analysis of traffic data and employs a time-indexed traffic anomaly detection algorithm which partitions time into categories of "type of day," and "time of day". Using this partition, a fuzzy neuromorphic, unsupervised learning algorithm calibrates fuzzy sets as "normal" and "abnormal" for a plurality of traffic descriptors. Fuzzy composition techniques are used, on a per traffic lane basis, to combine multiple traffic descriptors in order to determine membership in a "normal" or "abnormal" lane status. Each lane status is then combined to determine the overall status of a road segment. Initial training of the algorithm occurs during the first few weeks after a sensor (12) is installed. On-line background training continues thereafter to continually tune and track seasonal changes affecting system performance.