Sustainability Opportunities and Ethical Challenges of AI-Enabled Connected Autonomous Vehicles Routing in Urban Areas

The advent of Connected Autonomous Vehicles (CAVs) paves the way to a new era of urban traffic control and management, driven by Artificial Intelligence (AI)-enabled strategies. This advancement promises significant improvements in infrastructure use optimization, traffic delay reduction, and overall sustainability. The autonomous driving capabilities of CAVs, coupled with the communication technology, allow vehicles to play an active role in urban traffic control: they can follow tailored instructions and can act as highly accurate moving sensors for traffic authorities. However, such improved capabilities come at the cost of unprecedented vulnerabilities to cyber exploitation, and with the concrete potential to increase social and economic disparities. As an extension of TIV-DHW (Distributed/Decentralized Hybrid Workshop) on ERS (Ethics, Responsibility, and Sustainability), this letter explores how the AI-enabled routing methodology can enhance urban transportation sustainability while also discussing its ethical implications and challenges.

• Record URL:
  http://dx.doi.org/10.1109/TIV.2023.3345661
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/23798858
• Supplemental Notes:
  • Copyright © 2024, IEEE.
• Authors:
  • Guo, Rongge
  • Vallati, Mauro
  • Wang, Yutong
  • Zhang, Hui
  • Chen, Yuanyuan
  • Wang, Fei-Yue
• Publication Date: 2024-1

Language

• English

Media Info

• Media Type: Web
• Features: References;
• Pagination: pp 55-58
• Serial:
  • IEEE Transactions on Intelligent Vehicles
  • Volume: 9
  • Issue Number: 1
  • 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; Connected vehicles; Machine learning; Routing; Sustainable transportation; Traffic control
• Subject Areas: Data and Information Technology; Highways; Operations and Traffic Management; Vehicles and Equipment;

Filing Info

• Accession Number: 01918644
• Record Type: Publication
• Files: TRIS
• Created Date: May 16 2024 4:37PM