Neural Network Models For Automated Detection Of Non-recurring Congestion

Abstract: 

This research addressed the first year of a proposed multi-year research effort that would investigate, assess, and develop neural network models from the field of artificial intelligence for automated detection of non- recurring congestion in integrated freeway and signalized surface street networks. In this research, spatial and temporal traffic patterns are recognized and classified by an artificial neural network.

Author: 
Ritchie, Stephen G.
Cheu, Ruey L.
Publication date: 
June 1, 1993
Publication type: 
Research Report
Citation: 
Ritchie, S. G., & Cheu, R. L. (1993). Neural Network Models For Automated Detection Of Non-recurring Congestion (No. UCB-ITS-PRR-93-5). https://escholarship.org/uc/item/6r89f2hw