This book takes readers on a journey through the intricate web of contemporary transportation systems, offering unparalleled insights into the strategies, technologies, and methodologies shaping the movement of people and goods in urban landscapes.
This book takes readers on a journey through the intricate web of contemporary transportation systems, offering unparalleled insights into the strategies, technologies, and methodologies shaping the movement of people and goods in urban landscapes.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Yashaswi Karnati is a computer scientist with expertise in machine learning, computer vision and intelligent transportation systems. Having completed a PhD in Computer Science from the University of Florida, he has embarked on a career that sits at the intersection of academic excellence and industry innovation. He is currently working with NVIDIA Corporation, focusing on the development of digital twin technologies. Dhruv Mahajan completed his Ph.D. from the Department of Computer & Information Science & Engineering, University of Florida in May 2021. He is currently working on advancing Privacy Preserving Machine Learning techniques at Procter & Gamble. Tania Banerjee serves as a Research Assistant Scientist within the Department of Computer & Information Science & Engineering at the University of Florida. Her research interests are in the area Rahul Sengupta is a Ph.D. student at the Computer and Information Science Department at the University of Florida, Gainesville, USA. His research interests include applying Machine Learning models to sequential and time-series data, especially in the field of transportation engineering. Clay Packard is a principal software and systems engineer at HNTB with a focus in transportation technology. Clay provides technical leadership in systems planning, program and project development, and providing subject matter expertise to transportation agencies. Ryan Casburn, a traffic engineer with over five years of experience, boasts a lifelong passion for optimizing transportation systems. Fascinated by the dynamic interactions within these systems, he specializes in crafting practical solutions based on real-world behaviors rather than purely theoretical models. His diverse project portfolio spans microsimulation, signal retiming, and transportation planning, software development of user-friendly transportation analysis tools. Ryan's expertise and dedication make him a valuable asset in the realm of traffic engineering and integrated corridor management. Anand Rangarajan is Professor, Dept. of CISE, University of Florida. His research interests are machine learning, computer vision, medical and hyperspectral imaging and the science of consciousness. Jeremy Dilmore is the Transportation Systems Management and Operation Engineer for the Florida Department of Transportation District 5. He has 19 years of experience with the Department, with 13 of those years in Intelligent Transportation Systems and/or Transportation Systems Management and Operations. In this position he is responsible for leadingFDOTDistrict 5's technology efforts including working in the fields of signal timing optimization, managed lanes, simulation modeling, and connected and autonomous vehicles. Sanjay Ranka is a Distinguished Professor in the Department of Computer Information Science and Engineering at University of Florida. His current research interests are high performance computing and big data science with a focus on applications in CFD, healthcare and transportation. He has co-authored four books, 290+ journal and refereed conference articles. He is a Fellow of the IEEE and AAAS. He is an Associate Editor-in-Chief of the Journal of Parallel and Distributed Computing and an Associate Editor for ACM Computing Surveys, Applied Sciences, Applied Intelligence, IEEE/ACM Transactions on Computational Biology and Bioinformatics
Inhaltsangabe
Chapter 1 Introduction Chapter 2 Traffic Engineering and operations background Chapter 3 Integrated Corridor Management System Chapter 4 Traffic Data Modalities Chapter 5 Data Mining and Machine Learning Chapter 6 Traffic Simulation Frameworks for Data Generation Chapter 7 Intersection Detector Diagnostics Chapter 8 Intersector Performance Chapter 9 Interruption Detection Chapter 10 Estimating Turning Movement Counts Chapter 11 Coordinating Corridors Chapter 12 Modeling Input Output Behavior of Intersection Chapter 13 Modeling Measures of Effectiveness for Intersection Performance Chapter 14 Signal Timing Optimizations Chapter 15 Visualisation of Traffic Data
