@article{guo_sustainability_2024,
	title = {Sustainability {Opportunities} and {Ethical} {Challenges} of {AI}-{Enabled} {Connected} {Autonomous} {Vehicles} {Routing} in {Urban} {Areas}},
	issn = {2379-8904, 2379-8858},
	url = {https://ieeexplore.ieee.org/document/10368346/},
	doi = {10.1109/TIV.2023.3345661},
	abstract = {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 optimisation, 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/Decentralised 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 the ethical implications and challenges it presents.},
	language = {en},
	urldate = {2024-01-23},
	journal = {IEEE Transactions on Intelligent Vehicles},
	author = {Guo, Rongge and Vallati, Mauro and Wang, Yutong and Zhang, Hui and Chen, Yuanyuan and Wang, Fei-Yue},
	year = {2024},
	pages = {1--4},
}

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