Neural Network Models For Automated Detection Of Non-recurring Congestion

Stephen G. Ritchie and Ruey L. Cheu

Institute of Transportation Studies, Research Reports, Working Papers, Proceedings from Institute of Transportation Studies, UC Berkeley

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.

Keywords: Neural networks (Computer science); Traffic congestion; Detectors; Disabled vehicles on express highways (search for similar items in EconPapers)
Date: 1993-01-01
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Citations: View citations in EconPapers (2)

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