A hybrid tree approach to modeling alternate route choice behavior with online information

Journal of Intelligent Transportation Systems: Technology, Planning, and Operations

Volumn 14, Issue 4, 2010, Pages 209-219

  Lee, Chanyoung ^a   Ran, Bin ^b   Yang, Fan ^c   Loh, Wei Yin ^d  

^a University of South Florida   (United States)

^b University of Wisconsin Madison   (United States)

^c City College of the City University of New York   (United States)

^d UNIVERSITY OF WISCONSIN MADISON   (United States)

Author keywords

Advanced Traveler Information Systems; Artificial Neural Networks; Data Mining; Driver Compliance; Hybrid Tree; Logistic Regression; Variable Message Signs

Indexed keywords

ADVANCED TRAVELER INFORMATION SYSTEMS; ARTIFICIAL NEURAL NETWORK; DRIVER COMPLIANCE; HYBRID TREE; LOGISTIC REGRESSION; VARIABLE-MESSAGE SIGNS;

HIGHWAY ENGINEERING; HIGHWAY TRAFFIC CONTROL; INFORMATION SYSTEMS; INTELLIGENT SYSTEMS; LAWS AND LEGISLATION; NEURAL NETWORKS; REGRESSION ANALYSIS; TRANSPORTATION ROUTES; TREES (MATHEMATICS);

DATA MINING;

ADVANCED TRAVELER INFORMATION SYSTEM; COMPLIANCE; DATA MINING; DATA SET; INTELLIGENT TRANSPORTATION SYSTEM; LOGISTICS; NUMERICAL MODEL; REGRESSION ANALYSIS; ROUTING; TRANSPORTATION PLANNING;

UNITED STATES;

EID: 78249246776     PISSN: 15472450     EISSN: 15472442     Source Type: Journal    
DOI: 10.1080/15472450.2010.516229     Document Type: Article

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