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Constantinos Antoniou
Also published under:C. Antoniou
Affiliation
Chair of Transportation Systems Engineering, Technical University of Munich, Germany
Topic
Traffic Flow,Long Short-term Memory,Time Series,Convolutional Neural Network,Driver Behavior,Lane Change,Recurrent Neural Network,Traffic Data,Traffic Safety,Anomaly Detection,Average Speed,Decision Tree,Deep Learning,Deep Neural Network,Gaussian Mixture Model,High Penetration Rate,Intelligent Transportation Systems,Learning Algorithms,Mean Square Error,Multiple Imputation,Neural Network,Objective Function,Penetration Rate,Reduce Travel Time,Traffic Conditions,Traffic Congestion,Traffic Efficiency,Traffic Forecasting,Traffic Model,Travel Time,Trend Component,Vehicle Trajectory,Acceleration Profile,Acceleration Range,Acceleration Values,Accident Data,Adaptive Feature,Advanced Driver Assistance Systems,Anomaly Data,Area Loss,Artificial Neural Network,Automated Vehicles,Automotive Industry,Autonomous Vehicles,Average Silhouette Width,Average Travel Time,Back Propagation Neural Network,Beach Area,Bike-sharing,Bike-sharing Demand,
Biography
Constantinos Antoniou received the Diploma degree in civil engineering from NTUA in 1995, and the M.S. degree in transportation and the Ph.D. degree in transportation systems from MIT, in 1997 and 2004, respectively. He is a Full Professor with the Chair of Transportation Systems Engineering, Technical University of Munich (TUM), Germany. His research interests include data analytics, modeling and simulation of transportation systems, intelligent transport systems (ITS), calibration and optimization applications, road safety, and bbreak sustainable transport systems.