This study explores the complexities of integrating Artificial Intelligence (AI) into Autonomous Vehicles (AVs), examining the challenges introduced by AI components and the impact on testing procedures, focusing on some of the essential requirements for trustworthy AI. Topics addressed include the role of AI at various operational layers of AVs, the implications of the EU's AI Act on AVs, and the need for new testing methodologies for Advanced Driver Assistance Systems (ADAS) and Automated Driving Systems (ADS). The study also provides a detailed analysis on the importance of cybersecurity audits, the need for explainability in AI decision-making processes and protocols for assessing the robustness and ethical behaviour of predictive systems in AVs. The paper identifies significant challenges and suggests future directions for research and development of AI in AV technology, highlighting the need for multidisciplinary expertise.

本研究探讨了将人工智能（AI）整合到自动驾驶汽车（AVs）中的复杂性，研究了AI组件引入的挑战以及对测试程序的影响，重点关注了可信AI的一些基本要求。涵盖了AI在AVs的各个操作层面上的作用、欧盟AI法案对AVs的影响以及ADAS和ADS的新测试方法的需求。本文还对网络安全审核的重要性、AI决策过程中的可解释性需求以及评估AVs中预测系统的稳健性和道德行为的协议进行了详细分析。该论文确定了重大挑战，并提出了AI在AV技术研究与发展中的未来方向，突出了跨学科专业知识的需求。

自动驾驶车辆与人工智能的测试：来自网络安全、透明度、稳健性和公平性的观点与挑战