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Advancing explainable autonomous vehicle systems: A comprehensive review and research roadmap

Tekkesinoglu, Sule; Habibovic, Azra; Kunze, Lars

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Authors

Sule Tekkesinoglu

Azra Habibovic

Lars Kunze



Abstract

Given the uncertainty surrounding how existing explainability methods for autonomous vehicles (AVs) meet the diverse needs of stakeholders, a thorough investigation is imperative to determine the contexts requiring explanations and suitable interaction strategies. A comprehensive review becomes crucial to assess the alignment of current approaches with varied interests and expectations within the AV ecosystem. This study presents a review to discuss the complexities associated with explanation generation and presentation to facilitate the development of more effective and inclusive explainable AV systems. Our investigation led to categorising existing literature into three primary topics: explanatory tasks, explanatory information, and explanatory information communication. Drawing upon our insights, we have proposed a comprehensive roadmap for future research centred on (i) knowing the interlocutor, (ii) generating timely explanations, (ii) communicating human-friendly explanations, and (iv) continuous learning. Our roadmap is underpinned by principles of responsible research and innovation, emphasising the significance of diverse explanation requirements. To effectively tackle the challenges associated with implementing explainable AV systems, we have delineated various research directions, including the development of privacy-preserving data integration, ethical frameworks, real-time analytics, human-centric interaction design, and enhanced cross-disciplinary collaborations. By exploring these research directions, the study aims to guide the development and deployment of explainable AVs, informed by a holistic understanding of user needs, technological advancements, regulatory compliance, and ethical considerations, thereby ensuring safer and more trustworthy autonomous driving experiences.

Journal Article Type Article
Acceptance Date Jan 9, 2025
Online Publication Date Jan 22, 2025
Publication Date Jun 30, 2025
Deposit Date Apr 14, 2025
Publicly Available Date Apr 15, 2025
Journal ACM Transactions on Human-Robot Interaction
Electronic ISSN 2573-9522
Publisher Association for Computing Machinery (ACM)
Peer Reviewed Peer Reviewed
Volume 14
Issue 3
Article Number 39
DOI https://doi.org/10.1145/3714478
Public URL https://uwe-repository.worktribe.com/output/13669850
Publisher URL https://dl.acm.org/doi/10.1145/3714478#abstract
Other Repo URL https://arxiv.org/abs/2404.00019

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