Table 3.
Ethical dilemmas in Autonomous vehicles.
| Title | Overview | Ethical Concerns |
|---|---|---|
| The Future of Transportation: Ethical, Legal, Social and Economic Impacts of Self-driving Vehicles in the Year 2025 [43] | Summarises the numerous ethical, legal, societal, and economic effects that may arise while implementing self-driving vehicles by 2025, including concerns about individuality, confidentiality, accountability, privacy, and data security. | Security and damage prevention, autonomy, responsibility, rights, data privacy insurance, and discrimination. |
| Ethical issues in focus by the autonomous vehicles industry [44] | Reviews AVs ethical stories published in scientific papers and business reports by organizations holding California AV testing permits. | Raises concerns over cybersecurity, safety, accountability, human carelessness, and control concerns. |
| Self-Driving Vehicles—an Ethical Overview [45] | Offers a thorough discussion on the ethical concerns that realistic self-driving car technologies offer. Highlights strong arguments in favor of and against driverless cars and safety necessities for the road traffic system. | Responsibility, public attitudes, safety, control, information, and social Justice |
| The Future of Automated Vehicles in Canada [46] | Outlines the Transportation and Road Safety Ministries report on adoption of AV on public roads having short, medium, and long-term policy ramifications. Also identifies possibilities, limitations, and strategies for fostering collaboration both domestically and abroad. | The following issues were mentioned: road safety, standards and rules cannot be created separately, innovation needs to be encouraged, privacy issues, education and awareness, technological expertise, traffic laws and requirement of updated traffic rules. |
| Cybersecurity Challenges in the uptake of Artificial Intelligence in Autonomous Driving [47] | Discusses the key ideas underlying the cybersecurity of AI for autonomous vehicles. | The following issues were summarized: lack of knowledge and data validation techniques for the AI system, encryption and authentication issues, and flaws in security design. |