Trustworthy Intelligent Vehicle Systems Based on TRUE Autonomous Organizations and Operations: A New Perspective
Xiaolong Liang, Juanjuan Li, Rui Qin, Fei–Yue Wang · IEEE Transactions on Intelligent Vehicles · 2024
Intelligent Vehicles (IVs), integrating sensing, communication, and computing technologies, have immense potential to elevate efficiency, reduce traffic accidents, and diminish emissions. However, since faulty decisions made by IVs may endanger the safety of people's lives and property, improper trust in these automated systems could potentially lead to significant risks and problems. The trust issues in IVs stems not only from technological immaturity but also from the inability of automation systems to handle complex social relationships. TRUE Autonomous Organizations and Operations (TAOs), underpinned by blockchain and smart contracts, propose a code-governed, trustworthy humanmachine collaboration model, offering a promising approach to tackle those challenges. This paper introduces TAOs into IVs to propose an innovative human-machine collaboration system namely IV-TAOs, aiming to enhance the trustworthiness between humans and IVs. The architecture of IV-TAOs is formulated, with an exploration of both their characteristics and associated risk issues. This work provides a new perspective on addressing the trust issues encompassing but not confined solely within the context of intelligent vehicles.