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

Rongge Guo, Mauro Vallati, Yutong Wang, Hui Zhang, Yuanyuan Chen, Fei-Yue Wang

Research output: Contribution to journalArticlepeer-review


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 it presents.
Original languageEnglish
Article number10368346
Number of pages4
JournalIEEE Transactions on Intelligent Vehicles
Early online date21 Dec 2023
Publication statusE-pub ahead of print - 21 Dec 2023

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