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Urban Freight Analytics: Big Data, Models, and Artificial Intelligence - Hardcover

 
9781032199368: Urban Freight Analytics: Big Data, Models, and Artificial Intelligence

Synopsis

Urban Freight Analytics examines the key concepts associated with the development and application of decision support tools for evaluating and implementing city logistics solutions. New analytical methods are required for effectively planning and operating emerging technologies including the Internet of Things (IoT), Information and Communication Technologies (ICT), and Intelligent Transport Systems (ITS).

The book provides a comprehensive study of modelling and evaluation approaches to urban freight transport. It includes case studies from Japan, the US, Europe, and Australia that illustrate the experiences of cities that have already implemented city logistics, including analytical methods that address the complex issues associated with adopting advanced technologies such as autonomous vehicles and drones in urban freight transport.

Also considered are future directions in urban freight analytics, including hyperconnected city logistics based on the Physical Internet (PI), digital twins, gamification, and emerging technologies such as connected and autonomous vehicles in urban areas. An integrated modelling platform is described that considers multiple stakeholders or agents, including emerging organisations such as PI companies and entities such as crowd-shippers as well as traditional stakeholders such as shippers, receivers, carriers, administrators, and residents.

This book

  • Presents procedures for evaluating city logistics technologies and policy measures
  • Provides an overview of advanced modelling approaches, including agent-based model and machine learning
  • Highlights the essential features of optimisation and simulation models applied to city logistics
  • Discusses how models incorporating more uncertainty and dynamic data can be used to improve the sustainability and resilience of urban freight systems

The book is ideal for graduate students in civil and environmental engineering and logistics management, urban planners, transport engineers, and logistics specialists.

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About the Author

Eiichi Taniguchi is a Professor Emeritus of Kyoto University, Japan. He has performed research on transport and logistics systems focusing on city logistics for sustainable, liveable and resilient cities. He is a founder and President of Institute for City Logistics. He published 23 books and over 240 academic papers on urban freight transport and Intelligent Transport Systems. His recent research covers city logistics based on big data, artificial intelligence, autonomous vehicles, robots and the collaboration of stakeholders.

Russell G. Thompson is a Professor in Transport Engineering at the University of Melbourne where he leads the Physical Internet Lab. Russell was a founding Director and has been the Vice President of the Institute for City Logistics based in Kyoto since 1999. His research areas are City Logistics, Physical Internet (PI), resilient transport systems and intelligent transport systems. Russell has published over 15 books and 150 refereed publications in the field of urban freight.

Ali G. Qureshi is an associate professor in Department of Urban Management at Kyoto University, Japan. His research interests are related with exact and heuristics optimization of different variants of vehicle routing and facility location problems, and their integration in different frameworks such as multi-agent systems, and their application in evaluation of city logistics measures. He regularly contributes high quality research papers in leading international and regional (Asia-Pacific) journals and in peer reviewed conferences related with his areas of research.

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