An integrated framework to predict bus travel time and its variability using traffic flow data

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

Volumn 15, Issue 2, 2011, Pages 75-90

  Mazloumi, Ehsan ^a   Rose, Geoff ^a   Currie, Graham ^a   Sarvi, Majid ^a  

^a MONASH UNIVERSITY   (Australia)

Author keywords

Artificial Neural Networks; Australia; Bus Travel Times; GPS; Travel Time Prediction

Indexed keywords

ARTIFICIAL NEURAL NETWORK; AUSTRALIA; BUS TRAVEL TIMES; GPS; TRAVEL-TIME PREDICTION;

BUS TRANSPORTATION; BUSES; FORECASTING; NEURAL NETWORKS;

TRAFFIC CONGESTION;

ACCURACY ASSESSMENT; ARTIFICIAL NEURAL NETWORK; BUS TRANSPORT; DATA ACQUISITION; DATA SET; GPS; INTEGRATED APPROACH; PREDICTION; TEMPORAL VARIATION; TRAFFIC CONGESTION; TRAVEL TIME;

AUSTRALIA; MELBOURNE; VICTORIA [AUSTRALIA];

EID: 79957456341     PISSN: 15472450     EISSN: 15472442     Source Type: Journal    
DOI: 10.1080/15472450.2011.570109     Document Type: Article

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