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

Part I. Methods.  1. Introduction.  2. Data collection and analyses.  3. Geographic information systems and spatial analysis.  4. Optimisation.  5. Multi-agent simulation with machine learning.  6. Reliability and resilience.  7. Evaluation.  Part II. Applications.  8. Autonomous Vehicles and Robots.  9. Access management and pricing.  10. Environmental sustainability.  11. Disruption of Networks.  12. Future directions. 

ICT, IoT. AI, AVs, and robots, can be used with data to model, plan and evaluate an efficient and sustainable urban freight transport system, using tools such as the Physical Internet and dynamic road pricing. With global case studies this forms a graduate textbook and a reference for urban planning and logistics management practitioners.

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 lã-