Evolutionary Pathways, Key Challenges, and Future Prospects of Human-Centered Collaborative Autonomous Driving Systems

LIU Xiaobo; DONG Ni; YAN Xuedong

doi:10.3969/j.issn.0258-2724.20260022

Volume 61 Issue 3

Jun. 2026

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Journal of Southwest Jiaotong University > 2026 > 61(3): 656-672.

LIU Xiaobo, DONG Ni, YAN Xuedong. Evolutionary Pathways, Key Challenges, and Future Prospects of Human-Centered Collaborative Autonomous Driving Systems[J]. Journal of Southwest Jiaotong University, 2026, 61(3): 656-672. doi: 10.3969/j.issn.0258-2724.20260022

Citation:

LIU Xiaobo, DONG Ni, YAN Xuedong. Evolutionary Pathways, Key Challenges, and Future Prospects of Human-Centered Collaborative Autonomous Driving Systems[J]. Journal of Southwest Jiaotong University, 2026, 61(3): 656-672. doi: 10.3969/j.issn.0258-2724.20260022

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Evolutionary Pathways, Key Challenges, and Future Prospects of Human-Centered Collaborative Autonomous Driving Systems

doi: 10.3969/j.issn.0258-2724.20260022

LIU Xiaobo^{1, 2
,},
DONG Ni^{1, 2
,},
YAN Xuedong^{1
,
,}

1.
School of Transportation and Logistics, Southwest Jiaotong University, Chengdu 611756, China
2.
Sichuan Provincial Key Laboratory of Intelligent Integrated Transportation, Southwest Jiaotong University, Chengdu 611756, China

Received Date: 16 Jan 2026
Rev Recd Date: 13 Apr 2026
Publish Date: 16 Apr 2026

Abstract

Abstract

With the development of autonomous driving systems, the increasingly prominent bottleneck of “long-tail scenarios” demonstrates that the technology-driven “automation substitution” approach lacks a complete definition of human roles, human-machine relationships, and system ethics. First, the evolutionary pathways of autonomous driving systems from “tool-based assistance” to “automation-led” and ultimately to “collaborative control” were traced, and the fundamental transformation of the human-machine relationship from one-way control to two-way collaboration was elucidated. Secondly, to address key challenges that restrict the improvement of collaborative efficiency, such as the establishment and maintenance of dynamic trust mechanisms, the real-time optimal allocation of control permissions, and the construction of two-way collaborative interaction paradigms, their inherent logic, influencing factors, and existing bottlenecks at the levels of cognitive mechanisms, control theory, and interaction design were expounded on. Finally, developing human state perception and modeling technologies based on multi-source fusion, exploring adaptive collaborative control architectures based on real-time evaluation, and realizing the interaction paradigm shift from “one-way notification” to “two-way collaboration” were systematically proposed, which refined the future development pathways of autonomous driving systems. Through a review of existing theories, technical routes, and application cases, systematic theoretical support and practical references are provided for promoting the development of understandable, trustworthy, and widely acceptable “human-centered collaborative” autonomous driving systems.
- human-centered collaboration,
- autonomous driving system,
- human driver,
- human-machine collaboration,
- interaction paradigm

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References(136)

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Evolutionary Pathways, Key Challenges, and Future Prospects of Human-Centered Collaborative Autonomous Driving Systems

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