Purpose In recent years, the rapid advancement of artificial intelligence (AI) has injected new momentum into the field of autonomous driving, fundamentally reshaping the development model of its ecosystem. However, existing research remains largely fragmented, lackcing a systematic examination of the dynamic interplay between technology, security and governance. It particularly overlooks the collaborative challenges faced by diverse stakeholders in data sharing and responsibility-sharing. This paper aims to explore the AI-driven autonomous driving ecosystem across four key dimensions: core technology, network security, government regulation and ecological synergy. Design/methodology/approach Bibliometric analysis reveals a three-stage progression: “core technology - system integration - ecological regulation.” Findings Previous studies indicate that the deep integration of AI technologies, such as deep learning and federated learning, not only accelerates the intelligentization of autonomous driving but also introduces new challenges within the ecosystem, including data governance and liability determination. However, cybersecurity concerns dominate, with issues such as data breaches, model attacks and other risks, highlighting the urgent need for a multilayered defense system. Furthermore, the value co-creation mechanism within the ecosystem remains underdeveloped, with insufficient collaboration between car manufacturers, tech companies, users and government bodies. This lack of synergy has resulted in significant data silos and inefficient cross-industry collaboration. Originality/value This paper aims to build a more open, secure and efficient autonomous driving ecosystem. It proposes an integrated three-tier analytical framework and constructs a collaborative governance model involving enterprises, industries, governments and society. Focusing on technological evolution, policy optimization and enhanced ecosystem synergy, the model seeks to achieve a delicate balance between innovation and societal acceptance. It provides both theoretical foundations and practical pathways to resolve the aforementioned coordination challenges and realize equilibrium between technological innovation and social acceptance.
Li et al. (Mon,) studied this question.