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Governing autonomous vehicles: emerging responses for safety, liability, privacy, cybersecurity, and industry risks

arXiv 1807.05720 ↗First posted 16 Jul 2018cs.CY cs.AI cs.CRcited by 21

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Abstract (arXiv)

The benefits of autonomous vehicles (AVs) are widely acknowledged, but there are concerns about the extent of these benefits and AV risks and unintended consequences. In this article, we first examine AVs and different categories of the technological risks associated with them. We then explore strategies that can be adopted to address these risks, and explore emerging responses by governments for addressing AV risks. Our analyses reveal that, thus far, governments have in most instances avoided stringent measures in order to promote AV developments and the majority of responses are non-binding and focus on creating councils or working groups to better explore AV implications. The US has been active in introducing legislations to address issues related to privacy and cybersecurity. The UK and Germany, in particular, have enacted laws to address liability issues, other countries mostly acknowledge these issues, but have yet to implement specific strategies. To address privacy and cybersecurity risks strategies ranging from introduction or amendment of non-AV specific legislation to creating working groups have been adopted. Much less attention has been paid to issues such as environmental and employment risks, although a few governments have begun programmes to retrain workers who might be negatively affected.

Key facts. Cited by 21 papers in the map (data through 7 Oct 2026). First posted on arXiv 16 Jul 2018.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 3; 2022: 6; 2023: 5; 2024: 3; 2025: 3; 2026: 1.

21 papers.

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  1. 2023Milestones in Autonomous Driving and Intelligent Vehicles: Survey of Surveyscited by 75
  2. 2021Explainable Artificial Intelligence for Autonomous Driving: A Comprehensive Overview and Field Guide for Future Research Directionscited by 73
  3. 2022Towards Long-Tailed 3D Detectioncited by 40
  4. 2023Long-Tailed 3D Detection via Multi-Modal Fusioncited by 10
  5. 2021Towards a Robust and Trustworthy Machine Learning System Development: An Engineering Perspectivecited by 9
  6. 2024Autonomous Driving Small-Scale Cars: A Survey of Recent Developmentcited by 6
  7. 2022The Risks of Machine Learning Systemscited by 5
  8. 2022Privacy of Autonomous Vehicles: Risks, Protection Methods, and Future Directionscited by 4
  9. 2023Towards Safe Autonomy in Hybrid Traffic: Detecting Unpredictable Abnormal Behaviors of Human Drivers via Information Sharingcited by 3
  10. 2025A Principle of Targeted Intervention for Multi-Agent Reinforcement Learningcited by 3
  11. 2023Motion Comfort Optimization for Autonomous Vehicles: Concepts, Methods, and Techniquescited by 2
  12. 2022Advising Autonomous Cars about the Rules of the Roadcited by 1
9 more
  1. 2024Driving Towards Inclusion: A Systematic Review of AI-powered Accessibility Enhancements for People with Disability in Autonomous Vehiclescited by 1
  2. 2024Legal and ethical implications of applications based on agreement technologies: the case of auction-based road intersectionscited by 1
  3. 2025Safeguarding connected autonomous vehicle communication: Protocols, intra- and inter-vehicular attacks and defensescited by 1
  4. 2026SemLT3D: Semantic-Guided Expert Distillation for Camera-only Long-Tailed 3D Object Detectioncited by 1
  5. 2021From the Head or the Heart? An Experimental Design on the Impact of Explanation on Cognitive and Affective Trustcited by 0
  6. 2022The Self-Driving Car: Crossroads at the Bleeding Edge of Artificial Intelligence and Lawcited by 0
  7. 2022Towards human-compatible autonomous car: A study of non-verbal Turing test in automated driving with affective transition modellingcited by 0
  8. 2023Effect of roundabout design on the behavior of road users: A case study of roundabouts with application of Unsupervised Machine Learningcited by 0
  9. 2025Structured AI Decision-Making in Disaster Managementcited by 0