Testing autonomous vehicles and AI: perspectives and challenges from cybersecurity, transparency, robustness and fairness
Abstract This study aims to comprehensively explore the complexities of integrating Artificial Intelligence (AI) into Autonomous Vehicles (AVs), examining the challenges introduced by AI components and their impact on testing procedures. The research focuses on essential requirements for trustworthy...
Saved in:
| Main Authors: | , , , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
SpringerOpen
2025-07-01
|
| Series: | European Transport Research Review |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12544-025-00732-x |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849344862597414912 |
|---|---|
| author | David Fernández Llorca Ronan Hamon Henrik Junklewitz Kathrin Grosse Lars Kunze Patrick Seiniger Robert Swaim Nick Reed Alexandre Alahi Emilia Gómez Ignacio Sánchez Akos Kriston |
| author_facet | David Fernández Llorca Ronan Hamon Henrik Junklewitz Kathrin Grosse Lars Kunze Patrick Seiniger Robert Swaim Nick Reed Alexandre Alahi Emilia Gómez Ignacio Sánchez Akos Kriston |
| author_sort | David Fernández Llorca |
| collection | DOAJ |
| description | Abstract This study aims to comprehensively explore the complexities of integrating Artificial Intelligence (AI) into Autonomous Vehicles (AVs), examining the challenges introduced by AI components and their impact on testing procedures. The research focuses on essential requirements for trustworthy AI, including cybersecurity, transparency, robustness, and fairness. We first analyse the role of AI at the most relevant operational layers of AVs, and discuss the implications of the EU’s AI Act on AVs, highlighting the importance of the concept of a safety component. Using an expert opinion-based methodology, involving an interdisciplinary workshop with 21 academics and a subsequent in-depth analysis by a smaller group of experts, this study provides a state-of-the-art overview of the current landscape of vehicle regulation and standards, including ex-ante, post-hoc, and accident investigation processes, highlighting the need for new testing methodologies for both Advanced Driver Assistance Systems (ADAS) and Automated Driving Systems (ADS). The study also provides a detailed analysis of cybersecurity audits, explainability in AI decision-making processes and protocols for assessing the robustness and ethical behaviour of predictive systems in AVs. The analysis highlights significant challenges and suggests future directions for research and development of AI in AV technology, emphasising the need for multidisciplinary expertise. The study’s conclusions have relevant implications for the development of trustworthy AI systems, vehicle regulations, and the safe deployment of AVs. |
| format | Article |
| id | doaj-art-62f86a27e7d54112afcd2c13e15b0a25 |
| institution | Kabale University |
| issn | 1866-8887 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | European Transport Research Review |
| spelling | doaj-art-62f86a27e7d54112afcd2c13e15b0a252025-08-20T03:42:34ZengSpringerOpenEuropean Transport Research Review1866-88872025-07-0117112610.1186/s12544-025-00732-xTesting autonomous vehicles and AI: perspectives and challenges from cybersecurity, transparency, robustness and fairnessDavid Fernández Llorca0Ronan Hamon1Henrik Junklewitz2Kathrin Grosse3Lars Kunze4Patrick Seiniger5Robert Swaim6Nick Reed7Alexandre Alahi8Emilia Gómez9Ignacio Sánchez10Akos Kriston11European Commission, Joint Research CentreEuropean Commission, Joint Research CentreEuropean Commission, Joint Research CentreEPFL - Swiss Federal Institute of TechnologyUniversity of OxfordBASt - German Federal Highway Research InstituteNTSB. HowiItBroke.comReed MobilityEPFL - Swiss Federal Institute of TechnologyEuropean Commission, Joint Research CentreEuropean Commission, Joint Research CentreEuropean Commission, Joint Research CentreAbstract This study aims to comprehensively explore the complexities of integrating Artificial Intelligence (AI) into Autonomous Vehicles (AVs), examining the challenges introduced by AI components and their impact on testing procedures. The research focuses on essential requirements for trustworthy AI, including cybersecurity, transparency, robustness, and fairness. We first analyse the role of AI at the most relevant operational layers of AVs, and discuss the implications of the EU’s AI Act on AVs, highlighting the importance of the concept of a safety component. Using an expert opinion-based methodology, involving an interdisciplinary workshop with 21 academics and a subsequent in-depth analysis by a smaller group of experts, this study provides a state-of-the-art overview of the current landscape of vehicle regulation and standards, including ex-ante, post-hoc, and accident investigation processes, highlighting the need for new testing methodologies for both Advanced Driver Assistance Systems (ADAS) and Automated Driving Systems (ADS). The study also provides a detailed analysis of cybersecurity audits, explainability in AI decision-making processes and protocols for assessing the robustness and ethical behaviour of predictive systems in AVs. The analysis highlights significant challenges and suggests future directions for research and development of AI in AV technology, emphasising the need for multidisciplinary expertise. The study’s conclusions have relevant implications for the development of trustworthy AI systems, vehicle regulations, and the safe deployment of AVs.https://doi.org/10.1186/s12544-025-00732-xAutonomous vehiclesTrustworthy AITestingVehicle RegulationsCybersecurityTransparency |
| spellingShingle | David Fernández Llorca Ronan Hamon Henrik Junklewitz Kathrin Grosse Lars Kunze Patrick Seiniger Robert Swaim Nick Reed Alexandre Alahi Emilia Gómez Ignacio Sánchez Akos Kriston Testing autonomous vehicles and AI: perspectives and challenges from cybersecurity, transparency, robustness and fairness European Transport Research Review Autonomous vehicles Trustworthy AI Testing Vehicle Regulations Cybersecurity Transparency |
| title | Testing autonomous vehicles and AI: perspectives and challenges from cybersecurity, transparency, robustness and fairness |
| title_full | Testing autonomous vehicles and AI: perspectives and challenges from cybersecurity, transparency, robustness and fairness |
| title_fullStr | Testing autonomous vehicles and AI: perspectives and challenges from cybersecurity, transparency, robustness and fairness |
| title_full_unstemmed | Testing autonomous vehicles and AI: perspectives and challenges from cybersecurity, transparency, robustness and fairness |
| title_short | Testing autonomous vehicles and AI: perspectives and challenges from cybersecurity, transparency, robustness and fairness |
| title_sort | testing autonomous vehicles and ai perspectives and challenges from cybersecurity transparency robustness and fairness |
| topic | Autonomous vehicles Trustworthy AI Testing Vehicle Regulations Cybersecurity Transparency |
| url | https://doi.org/10.1186/s12544-025-00732-x |
| work_keys_str_mv | AT davidfernandezllorca testingautonomousvehiclesandaiperspectivesandchallengesfromcybersecuritytransparencyrobustnessandfairness AT ronanhamon testingautonomousvehiclesandaiperspectivesandchallengesfromcybersecuritytransparencyrobustnessandfairness AT henrikjunklewitz testingautonomousvehiclesandaiperspectivesandchallengesfromcybersecuritytransparencyrobustnessandfairness AT kathringrosse testingautonomousvehiclesandaiperspectivesandchallengesfromcybersecuritytransparencyrobustnessandfairness AT larskunze testingautonomousvehiclesandaiperspectivesandchallengesfromcybersecuritytransparencyrobustnessandfairness AT patrickseiniger testingautonomousvehiclesandaiperspectivesandchallengesfromcybersecuritytransparencyrobustnessandfairness AT robertswaim testingautonomousvehiclesandaiperspectivesandchallengesfromcybersecuritytransparencyrobustnessandfairness AT nickreed testingautonomousvehiclesandaiperspectivesandchallengesfromcybersecuritytransparencyrobustnessandfairness AT alexandrealahi testingautonomousvehiclesandaiperspectivesandchallengesfromcybersecuritytransparencyrobustnessandfairness AT emiliagomez testingautonomousvehiclesandaiperspectivesandchallengesfromcybersecuritytransparencyrobustnessandfairness AT ignaciosanchez testingautonomousvehiclesandaiperspectivesandchallengesfromcybersecuritytransparencyrobustnessandfairness AT akoskriston testingautonomousvehiclesandaiperspectivesandchallengesfromcybersecuritytransparencyrobustnessandfairness |