Dynamic data-driven local traffic state estimation and prediction

Transportation Research Part C: Emerging Technologies

Volumn 34, Issue , 2013, Pages 89-107

  Antoniou, Constantinos ^a   Koutsopoulos, Haris N ^b   Yannis, George ^a  

^a NATIONAL TECHNICAL UNIVERSITY OF ATHENS   (Greece)

^b ROYAL INSTITUTE OF TECHNOLOGY   (Sweden)

Author keywords

Classification; Clustering; Data driven approaches; Local speed prediction; Locally weighted regression; Markov process; Neural network; Traffic state prediction

Indexed keywords

CLASSIFICATION (OF INFORMATION); COMPUTATION THEORY; FORECASTING; HIGHWAY TRAFFIC CONTROL; MARKOV PROCESSES; NEURAL NETWORKS; STATE ESTIMATION; STREET TRAFFIC CONTROL; SUPERCONDUCTING MATERIALS;

CLUSTERING; DATA-DRIVEN APPROACH; LOCALLY WEIGHTED REGRESSION; SPEED PREDICTION; TRAFFIC STATE;

PREDICTIVE ANALYTICS;

ARTIFICIAL NEURAL NETWORK; CLUSTER ANALYSIS; ESTIMATION METHOD; MARKOV CHAIN; MOTORWAY; NUMERICAL MODEL; PREDICTION; TRAFFIC MANAGEMENT;

CALIFORNIA; IRVINE; ISRAEL; TEL AVIV; UNITED STATES;

EID: 84880355786     PISSN: 0968090X     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.trc.2013.05.012     Document Type: Article

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