Road Traffic Modeling and Management

By:   Fouzi Harrou (King Abdullah University of Science and Technology Saudi Arabia), Abdelhafid Zeroual (Associate Researcher, University of Guelma, Guelma, Algeria), Mohamad Mazen Hittawe (Research Scientist, King Abdullah University of Science and Technology, Saudi Arabia), Ying Sun (King Abdullah University of Science and Technology, Saudi Arabia)
Imprint:   Elsevier Science Publishing Co Inc
Country of Publication:   United States
Dimensions:   Height: 229mm,  Width: 152mm, 
Weight:   140g
ISBN:   9780128234327
ISBN 10:   0128234326
Pages:   268
Publication Date:   08 October 2021
Audience:   Professional and scholarly ,  Undergraduate
Format:   Paperback
Publisher's Status:   Active

Fouzi Harrou received the M.Sc. degree in telecommunications and networking from the University of Paris VI, France, and the Ph.D. degree in systems optimization and security from the University of Technology of Troyes (UTT), France. He was an Assistant Professor with UTT for one year and with the Institute of Automotive and Transport Engineering, Nevers, France, for one year. He was also a Postdoctoral Research Associate with the Systems Modeling and Dependability Laboratory, UTT, for one year. He was a Research Scientist with the Chemical Engineering Department, Texas A&M University at Qatar, Doha, Qatar, for three years. He is actually a Research Scientist with the Division of Computer, Electrical and Mathematical Sciences and Engineering, King Abdullah University of Science and Technology. He is the author of more than 150 refereed journals and conference publications and book chapters. He is co-author of the book ""Statistical Process Monitoring Using Advanced Data-Driven and Deep Learning Approaches: Theory and Practical Applications"" (Elsevier, 2020). Dr. Harrou’s research interests are in the area of statistical anomaly detection and process monitoring with a particular emphasis on data-driven, machine learning/deep learning methods. The algorithms developed in Dr. Harrou’s research are utilized in many applications to improve the operation of various environmental, chemical, and electrical systems. Zeroual Abdelhafid's research interests include traffic modeling, estimation and control, traffic monitoring and congestion detection, hybrid system applications, control, estimation, classification methodologies as well as deep-learning approaches. Mohamad Mazen HITTAWE is a Research Scientist at King Abdullah University of Science and Technology (KAUST). His research interests include machine learning, deep learning, anomaly detection and localization in the video, prediction and forecasting, and computer vision. Professor Ying Sun received her Ph.D. in Statistics from Texas A&M in 2011 followed by a two-year postdoctoral research position at the Statistical and Applied Mathematical Sciences Institute and at the University of Chicago. She was an Assistant Professor at the Ohio State University for a year before joining KAUST in 2014. At KAUST, Professor Sun established and leads the Environmental Statistics research group which works on developing statistical models and methods for complex data to address important environmental problems. She has made original contributions to environmental statistics, in particular in the areas of spatio-temporal statistics, functional data analysis, visualization, computational statistics, with an exceptionally broad array of applications. Professor Sun won two prestigious awards: the Early Investigator Award in Environmental Statistics presented by the American Statistical Association, and the Abdel El-Shaarawi Young Research Award from the International Environmetrics Society