AI and Grand Challenges for ITS: Parallel Transportation Systems and Transportation 5.0

Fei-yue Wang1

  • 1Institute of Automation, Chinese Academy of Sciences

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Plenary Session

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09:30 - 10:30 | Mon 28 Oct | Great Room I - IV | MoB-P1

Keynote #1

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Abstract

With the fast development of Artificial Intelligence (AI), big data, cloud computing, social computing, and IoT technologies, Intelligent Transportation Systems are evolving rapidly into a class of the most comprehensive Cyber-Physical-Social Systems, which provide a wide range of challenges and opportunities for traffic management and control. Especially, although AI and R&D in ITS has achieved its historic prominence, the long-standing question of "Where is the Intelligence in ITS" hasn't been satisfactorily addressed yet. In this talk, I will present our perspective and work on how to enable ITS truly smart, effective and efficient, within the framework of Transportation 5.0 and Parallel Transportation Systems (PTS) based on the ACP approach. The basic ideas of PTS are: 1) modelling and representing real transportation systems using artificial transportation systems; 2) analyzing and evaluating traffic situations by computational experiments; and 3) controlling and managing transportation systems by parallel execution through interaction of real and artificial transportation systems. The ACP based PTS provide a platform to generate big data from small data and then reduce big data to small intelligence for specific tasks via various AI methods, which enables seamless integration of AI techniques into transportation operations. I shall outline concepts, methodology and techniques of parallel transportation systems, its corresponding hardware/software platforms, as well as real-world applications in China over the last decade.

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