Cross-Disciplinary Threats Mitigation Framework For Ai Autonomous Vehicles (cd-Ai-Avs-Tmf)

Despite the benefits such as road mobility and capacity enlargement, mortality lowering, and emissions drop, AI Autonomous Vehicles (AI-AVs) have introduced emerging threats that paired with cybersecurity threats, are changing the cybersecurity threat landscape. AI-AVs can be used as a moving intelligence collection for espionage and surveillance. They can be weaponized and operated for physical (logistical and transport) or furtive cyberattacks. AI-AVs have also introduced concerns about data privacy, governance, and ethical considerations. Therefore, it is crucial for both a domestic and foreign AI-AVs Cross-Disciplinary Mitigation Framework (CD-AI-AVs-TMF) to address the threats introduced by AI-AVs. This study emphasizes solutions to AI-AV threats and addresses them through the cross-disciplinary framework mitigation approach that prepares society, nations, and individuals for ongoing transportation advancements, the rise of AI applications, and their threats despite the revolutionary benefits. The researchers proposed CD-AI-AVs-TMF as a cross-disciplinary approach that converges the strategic and resilient approach, including the transport department road safety administration, and all the entities involved in the coalition such as AI-AV manufacturers, transport stakeholders, lawmakers, advocates for safety, academia, local, and foreign entities.