Crowd Sensing Intelligence for ITS: Participants, Methods, and Stages

The construction of transportation 5.0 or the so-called society-centered intelligent transportation systems (ITS) has aroused higher requirements for the intelligent sensing capability to seamlessly integrate Cyber-Physical-Social Systems (CPSS). Crowd Sensing Intelligence (CSI), as a promising paradigm, leverages the collective intelligence of heterogeneous sensing resources to gather data and information from CPSS. The authors' first Distributed/Decentralized Hybrid Workshop on Crowd Sensing Intelligence (DHW-CSI) has been focused on principles and high-level processes of organizing and operating CSI. This letter reports the discussion results of the second DHW-CSI addressing the participants, methods, and stages of CSI for ITS. The authors categorized sensing participants into three kinds, i.e., biological, digital, and robotic. Then the authors summarized three methods to enable sensing intelligence, i.e., foundation models, scenarios engineering, and human-oriented operating systems. Finally, the authors anticipated that the progression of CSI will experience three stages, from algorithmic intelligence to linguistic intelligence, and eventually to imaginative intelligence.

• Record URL:
  http://dx.doi.org/10.1109/TIV.2023.3284046
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/23798858
• Supplemental Notes:
  • Copyright © 2023, IEEE.
• Authors:
  • Zhao, Yong
  • Hu, Cong
  • Zhu, Zhengqiu
  • Qiu, Sihang
  • Chen, Bin
  • Jiao, Peng
  • Wang, Fei-Yue
• Publication Date: 2023-6

Language

• English

Media Info

• Media Type: Web
• Features: Figures; References;
• Pagination: pp 3541-3546
• Serial:
  • IEEE Transactions on Intelligent Vehicles
  • Volume: 8
  • Issue Number: 6
  • Publisher: Institute of Electrical and Electronics Engineers (IEEE)
  • ISSN: 2379-8858
  • Serial URL: http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=7274857

Subject/Index Terms

• TRT Terms: Autonomous vehicles; Crowds; Intelligent transportation systems; Internet of things; Machine learning; Sensors
• Subject Areas: Data and Information Technology; Highways; Vehicles and Equipment;

Filing Info

• Accession Number: 01909373
• Record Type: Publication
• Files: TRIS
• Created Date: Feb 22 2024 4:14PM