1. Abdel-Basset, M., Gamal, A., Moustafa, N., Abdel-Monem, A., & El-Saber, N.
(2021). A Security-by-Design Decision-Making Model for Risk Management in
Autonomous Vehicles. IEEE Access, 9, 107657–107679.
https://doi.org/10.1109/access.2021.3098675
Title: A Security-by-Design Decision-Making Model for Risk Management in
Autonomous Vehicles Author: Abdel-Basset, M.; Gamal, A.; Moustafa, N.; Abdel-Monem,
A.; El-Saber, N. Year of Publication: 2021 Journal: IEEE Access Methodology: The article
proposes a Security-by-Design Decision-Making Model for Risk Management in
Autonomous Vehicles. Research Design: The study likely involves theoretical analysis
and conceptual modeling to develop the decision-making model. Keypoints of the
study:
1. The article presents a novel decision-making model for managing risks in
autonomous vehicles.
2. The proposed model follows a Security-by-Design approach, emphasizing
security measures from the early stages of development.
3. The model aims to enhance the overall security of autonomous vehicles, making
them more resilient to potential cyber threats.
4. By integrating security measures into the design phase, the model seeks to
minimize risks during the vehicle's operational lifespan.
5. The study likely discusses various risk management strategies and their
implementation within the proposed model.
6. The research findings could have implications for the autonomous vehicle
industry, encouraging safer and more secure vehicle deployments.
2. Affia, A. O., Matulevičius, R., & Tõnisson, R. (2021). Security Risk Estimation and
management in Autonomous Driving Vehicles. Lecture Notes in Business
Information Processing, 11–19. https://doi.org/10.1007/978-3-030-79108-7_2
Title: Security Risk Estimation and Management in Autonomous Driving Vehicles
Authors: Affia, A. O.; Matulevičius, R.; Tõnisson, R. Year of Publication: 2021 Journal:
Lecture Notes in Business Information Processing Methodology: The article likely
focuses on security risk estimation and management in the context of autonomous
driving vehicles. Research Design: The study may involve a combination of literature
review, data analysis, and conceptual frameworks to address security risks in
autonomous driving vehicles. Keypoints of the study:
1. The article examines security risk estimation and management specific to
autonomous driving vehicles.
2. It likely discusses various types of security risks that autonomous vehicles may
face, including cyber-attacks and potential vulnerabilities.
3. The study might propose methodologies or models for estimating and
quantifying security risks in the context of autonomous vehicles.
4. The authors may present a framework for managing and mitigating security risks
to ensure safer autonomous vehicle operations.
5. The research could provide insights into the challenges of securing autonomous
driving vehicles and suggest potential solutions.
6. The findings may have practical implications for stakeholders involved in the
development and deployment of autonomous driving technology, including
manufacturers, policymakers, and regulators.
3. Ahn, J. H. (2017). A study on the liability legal system and insurance system
concerning autonomous vehicles. Korean Insurance Law Association, 11(1), 247–
263. https://doi.org/10.36248/kdps.2017.11.1.247
Title: A study on the liability legal system and insurance system concerning autonomous
vehicles Author: Ahn, J. H. Year of Publication: 2017 Journal: Korean Insurance Law
Association Methodology: The article is likely a legal and policy study that explores the
liability and insurance aspects related to autonomous vehicles. Research Design: The
study may involve legal analysis, literature review, and examination of existing insurance
systems and liability frameworks. Keypoints of the study:
1. The article delves into the legal implications of autonomous vehicles, focusing on
liability issues that may arise in case of accidents or incidents involving selfdriving cars.
2. It likely examines the current legal system in place and evaluates its suitability to
handle the unique challenges presented by autonomous vehicle technologies.
3. The study might explore how existing insurance systems address liability
concerns and assess their effectiveness in covering autonomous vehicle-related
risks.
4. The author could propose potential legal and insurance policy changes to
accommodate the emerging autonomous vehicle industry.
5. The research may discuss the roles and responsibilities of various stakeholders,
such as manufacturers, drivers, and insurers, in an autonomous vehicle context.
6. The findings may offer insights into the legal and regulatory hurdles that need to
be addressed to ensure a smooth and safe transition to autonomous vehicles.
4. Anderson, J., Kalra, N., Stanley, K., & Morikawa, J. (2018). Rethinking Insurance
and Liability in the Transformative Age of Autonomous Vehicles.
https://doi.org/10.7249/cf383
Title: Rethinking Insurance and Liability in the Transformative Age of Autonomous
Vehicles Authors: Anderson, J.; Kalra, N.; Stanley, K.; Morikawa, J. Year of Publication:
2018 DOI: https://doi.org/10.7249/cf383
Methodology: The article likely involves a comprehensive analysis and examination of
insurance and liability issues related to autonomous vehicles. Research Design: The
study may include a combination of literature review, case studies, and policy analysis to
rethink insurance and liability frameworks.
Keypoints of the study:
1. The article addresses the challenges and opportunities posed by the emergence
of autonomous vehicles with regard to insurance and liability.
2. It likely discusses the shifting landscape of liability, examining how responsibility
for accidents may transition from drivers to manufacturers or other entities in the
autonomous vehicle ecosystem.
3. The study may explore the implications of self-driving technology on the
traditional auto insurance industry and propose potential changes to insurance
models.
4. The authors may assess the need for new types of insurance products or the
adaptation of existing ones to accommodate autonomous vehicles' risks.
5. The research could highlight the potential impacts of autonomous vehicle safety
on insurance claim frequencies and overall risk management strategies.
6. The findings might offer policy recommendations and considerations for
policymakers, insurers, and other stakeholders to adapt to the transformative age
of autonomous vehicles effectively.
5. Atkinson, K. (2020). Autonomous cars: A driving force for change in motor liability
and insurance. SCRIPT-ed, 17(1), 125-151.
https://doi.org/10.2966/scrip.170120.125
Title: Autonomous cars: A driving force for change in motor liability and insurance
Author: Atkinson, K. Year of Publication: 2020 Journal: SCRIPT-ed Volume: 17 Issue: 1
Pages: 125-151 DOI: https://doi.org/10.2966/scrip.170120.125
Methodology: The article likely involves legal and policy analysis to explore the impact
of autonomous cars on motor liability and insurance. Research Design: The study may
include a combination of literature review, examination of legal frameworks, and
analysis of insurance industry trends.
Keypoints of the study:
1. The article discusses the influence of autonomous cars on the motor liability
landscape, considering how self-driving technology may change the traditional
notions of liability and responsibility in case of accidents.
2. It likely examines the potential shifts in liability from drivers to manufacturers,
software developers, or other entities involved in the design and operation of
autonomous vehicles.
3. The study may explore the role of insurance in the context of autonomous cars,
considering how insurance models might need to adapt to the changing risk
profiles of self-driving vehicles.
4. The author may analyze legal challenges and developments related to motor
liability and insurance in response to the rise of autonomous cars.
5. The research could also discuss the implications of autonomous vehicle
technology on accident prevention and how it may influence insurance claim
patterns.
6. The findings may offer insights into the legal and insurance industry's readiness
for the transformative changes brought about by autonomous cars.
6. de Miguel, M. Á., Moreno, F. M., Marín-Plaza, P., Al-Kaff, A., Palos, M., Martín, D.,
Encinar-Martín, R., & García, F. (2020). A Research Platform for Autonomous
Vehicles Technologies Research in the Insurance Sector. Applied Sciences, 10(16),
5655. https://doi.org/10.3390/app10165655
Title: A Research Platform for Autonomous Vehicles Technologies Research in the
Insurance Sector Authors: de Miguel, M. Á.; Moreno, F. M.; Marín-Plaza, P.; Al-Kaff, A.;
Palos, M.; Martín, D.; Encinar-Martín, R.; García, F. Year of Publication: 2020
Methodology: The article likely presents the development and implementation of a
research platform for studying autonomous vehicles technologies in the context of the
insurance sector. Research Design: The study may involve the design and deployment of
a research platform, possibly including data collection, analysis, and collaboration with
insurance industry stakeholders.
Keypoints of the study:
1. The article describes the creation of a research platform specifically designed to
investigate autonomous vehicles technologies.
2. The platform is likely focused on the insurance sector, indicating that the study
aims to explore how autonomous vehicle technologies impact insurance
operations and risk assessment.
3. The authors may explain the features and capabilities of the research platform,
which could involve data analytics, simulations, or real-world testing related to
autonomous vehicles and their interaction with insurance policies.
4. The study might discuss the potential benefits of the research platform, such as
facilitating data-driven decision-making for insurance companies or helping them
develop customized policies for autonomous vehicles.
5. The authors could highlight the collaborative nature of the platform, involving
partnerships between researchers, insurance industry experts, and autonomous
vehicle technology developers.
6. The findings may offer insights into the opportunities for the insurance sector to
adapt and innovate in response to the evolving landscape of autonomous
vehicles.
7. Dietrich, M. (2021). Addressing inequal risk exposure in the development of
automated vehicles. Ethics and Information Technology, 23(4), 727-738.
https://doi.org/10.1007/s10676-021-09610-1
Title: Addressing Inequal Risk Exposure in the Development of Automated Vehicles
Author: Dietrich, M. Year of Publication: 2021 Journal: Ethics and Information
Technology Volume: 23 Issue: 4 Pages: 727-738 DOI: https://doi.org/10.1007/s10676021-09610-1
Methodology: The article likely employs ethical analysis and policy considerations to
examine the issue of unequal risk exposure in the development of automated vehicles.
Research Design: The study may involve a combination of theoretical exploration, case
studies, and ethical reasoning to address the topic.
Keypoints of the study:
1. The article discusses the ethical concerns related to the development of
automated vehicles, particularly focusing on the unequal distribution of risks.
2. It likely explores how different societal groups or communities may bear varying
levels of risk and potential harm as a result of autonomous vehicle technologies.
3. The study may analyze the potential consequences of these inequalities in risk
exposure and how they could impact public trust and acceptance of automated
vehicles.
4. The author might propose ethical frameworks or policy recommendations aimed
at addressing and mitigating the unequal risk distribution in autonomous vehicle
development.
5. The research could discuss the responsibilities of various stakeholders, such as
manufacturers, policymakers, and regulators, in ensuring fairness and equity in
the deployment of automated vehicles.
6. The findings may offer insights into the ethical challenges and considerations that
need to be taken into account as autonomous vehicle technology advances.
8. Dixit, A., Kumar Chidambaram, R., & Allam, Z. (2021). Safety and Risk Analysis of
Autonomous Vehicles Using Computer Vision and Neural Networks. Vehicles,
3(3), 595–617. https://doi.org/10.3390/vehicles3030036
Title: Safety and Risk Analysis of Autonomous Vehicles Using Computer Vision and
Neural Networks Authors: Dixit, A.; Kumar Chidambaram, R.; Allam, Z. Year of
Publication: 2021 Journal: Vehicles Volume: 3 Issue: 3 Pages: 595–617 DOI:
https://doi.org/10.3390/vehicles3030036
Methodology: The article likely involves a technical approach, utilizing computer vision
and neural networks for safety and risk analysis of autonomous vehicles. Research
Design: The study may include data collection, experimentation, and analysis of
computer vision and neural network models applied to autonomous vehicle safety.
Keypoints of the study:
1. The article presents a safety and risk analysis methodology for autonomous
vehicles.
2. The study likely uses computer vision techniques to process visual data from
sensors and cameras mounted on autonomous vehicles.
3. It may involve the application of neural networks for analyzing and interpreting
the data to identify potential safety hazards and assess risk levels during
autonomous vehicle operations.
4. The authors might discuss the effectiveness and accuracy of the computer vision
and neural network-based approach in detecting and responding to potential
risks in real-time.
5. The research could highlight the role of advanced technologies in enhancing the
safety and reliability of autonomous vehicles.
6. The findings may offer insights into the ongoing research and development
efforts to improve the safety of autonomous vehicles using cutting-edge
technologies in computer vision and artificial intelligence.
9. Dimia Iberraken, Lounis Adouane, & Denis, D. (2019). Reliable Risk Management
for Autonomous Vehicles based on Sequential Bayesian Decision Networks and
Dynamic Inter-Vehicular Assessment. https://doi.org/10.1109/ivs.2019.8813800
Title: Reliable Risk Management for Autonomous Vehicles based on Sequential Bayesian
Decision Networks and Dynamic Inter-Vehicular Assessment Authors: Dimia Iberraken,
Lounis Adouane, Denis, D. Year of Publication: 2019 DOI:
https://doi.org/10.1109/ivs.2019.8813800
Methodology: The article likely involves the development and evaluation of a risk
management system for autonomous vehicles. Research Design: The study may include
the design and implementation of Sequential Bayesian Decision Networks (SBDNs) and
Dynamic Inter-Vehicular Assessment (DIVA) methods for risk assessment.
Keypoints of the study:
1. The article proposes a risk management system tailored for autonomous vehicles.
2. The study likely involves the application of Sequential Bayesian Decision
Networks, which are probabilistic graphical models used for decision-making
under uncertainty, to analyze and predict risks in real-time.
3. It may include the Dynamic Inter-Vehicular Assessment (DIVA) method, which
could refer to a dynamic approach for assessing risk considering interactions
between multiple autonomous vehicles.
4. The authors might discuss the reliability and effectiveness of the proposed risk
management system in enhancing the safety of autonomous vehicles.
5. The research could address the challenges of risk assessment and management in
the context of highly dynamic and uncertain environments with autonomous
vehicles.
6. The findings may offer insights into advanced risk management techniques and
technologies to ensure safer and more reliable autonomous vehicle operations.
10. Fan, C., & Xu, X. (2019). Influences of Autonomous Cars on the Insurance Market
from the Perspectives of Insurance Companies and Auto Insurance Agencies.
Journal of Applied Finance and Banking, 9(4), 11-35.
11. Hoshino, A. (2021). Impact of automated driving technology on Japanese
Automobile Insurance Market. The Korean-Japanese Economic and Management
Association, 92, 123–141. https://doi.org/10.46396/kjem.92.9
12. Kester, J. (2022). Insuring future automobility: A qualitative discussion of British
and Dutch car insurer’s responses to connected and automated vehicles.
Research in Transportation Business & Management, 100903.
https://doi.org/10.1016/j.rtbm.2022.100903
13. Lazányi, K. (2023). Perceived Risks of Autonomous Vehicles. Risks, 11(2), 26.
https://doi.org/10.3390/risks11020026
14. Mora, L., Wu, X., & Panori, A. (2020). Mind the gap: Developments in autonomous
driving research and the sustainability challenge. Journal of Cleaner Production,
275, 124087. https://doi.org/10.1016/j.jclepro.2020.124087
15. Morando, M. M., Tian, Q., Truong, L. T., & Vu, H. L. (2018). Studying the Safety
Impact of Autonomous Vehicles Using Simulation-Based Surrogate Safety
Measures. Journal of Advanced Transportation, 2018, 1–11.
https://doi.org/10.1155/2018/6135183
16. Murphy, F., Pütz, F., & Mullins, M. (2019). Driving to a future without accidents?
Connected automated vehicles’ impact on accident frequency and motor
insurance risk. Environment Systems and Decisions, 39(4), 383–395.
https://doi.org/10.1007/s10669-019-09739-x
17. Murphy, F., Pütz, F., Mullins, M., & O'Malley, L. (2019). Connected automated
vehicles and insurance: Analyzing future market-structure from a business
ecosystem perspective. Technology in Society, 59, 101182.
https://doi.org/10.1016/j.techsoc.2019.101182
18. Pattinson, J.-A., Chen, H., & Basu, S. (2020). Legal issues in automated vehicles:
critically considering the potential role of consent and interactive digital
interfaces. Humanities and Social Sciences Communications, 7(1).
https://doi.org/10.1057/s41599-020-00644-2
19. Parkinson, S., Ward, P., Wilson, K., & Miller, J. (2017). Cyber threats facing
autonomous and connected vehicles: Future challenges. IEEE transactions on
intelligent transportation systems, 18(11), 2898-2915.
20. Pütz, F., Murphy, F., & Mullins, M. (2019). Driving to a future without accidents?
Connected automated vehicles’ impact on accident frequency and motor
insurance risk. Environment Systems and Decisions, 39(4), 383–395.
https://doi.org/10.1007/s10669-019-09739-x
21. Pütz, F., Murphy, F., Mullins, M., & O'Malley, L. (2019). Connected automated
vehicles and insurance: Analysing future market-structure from a business
ecosystem perspective. Technology in Society, 59, 101182.
https://doi.org/10.1016/j.techsoc.2019.101182
22. Ryan, M. (2019). The future of transportation: Ethical, legal, social and economic
impacts of self-driving vehicles in the year 2025. Science and Engineering Ethics,
26(3), 1185-1208. https://doi.org/10.1007/s11948-019-00130-2
23. Settembre-Blundo, D., González-Sánchez, R., Medina-Salgado, S., & GarcíaMuiña, F. E. (2021). Flexibility and resilience in corporate decision making: A new
sustainability-based risk management system in uncertain times. Global Journal
of Flexible Systems Management, 22(S2), 107-132.
https://doi.org/10.1007/s40171-021-00277-7
24. Sheehan, B., Murphy, F., Mullins, M., & Ryan, C. (2019). Connected and
autonomous vehicles: A cyber-risk classification framework. Transportation
Research Part A: Policy and Practice, 124, 523–536.
https://doi.org/10.1016/j.tra.2018.06.033
25. Shannon, D., Jannusch, T., David‐Spickermann, F., Mullins, M., Cunneen, M., &
Murphy, F. (2021). Connected and autonomous vehicle injury loss events:
Potential risk and actuarial considerations for primary insurers. Risk Management
and Insurance Review, 24(1), 5–35. https://doi.org/10.1111/rmir.12168
26. Strong, A., & Baker, S. (2015). How will autonomous vehicle technologies affect
driver liability and overall insurance? Autonomous Passenger Vehicles.
https://doi.org/10.1049/ic.2015.0064
27. Taeihagh, A., & Lim, H. S. (2018). Governing autonomous vehicles: Emerging
responses for safety, liability, privacy, cybersecurity, and industry risks. Transport
Reviews, 39(1), 103-128. https://doi.org/10.1080/01441647.2018.1494640
28. Vellinga, N. (2019). Automated driving: Liability of the software producer and the
producer of the automated vehicle. SSRN Electronic Journal.
https://doi.org/10.2139/ssrn.3567779
29. Wang, D., Fu, W., Song, Q., & Zhou, J. (2022). Potential risk assessment for safe
driving of autonomous vehicles under occluded vision. Scientific Reports, 12(1).
https://doi.org/10.1038/s41598-022-08810-z