Explainable artificial intelligence for autonomous driving: A comprehensive overview and field guide for future research directions

S Atakishiyev, M Salameh, H Yao, R Goebel - arXiv preprint arXiv …, 2021 - arxiv.org
Autonomous driving has achieved significant milestones in research and development over
the last decade. There is increasing interest in the field as the deployment of self-operating …

A review of trustworthy and explainable artificial intelligence (xai)

V Chamola, V Hassija, AR Sulthana, D Ghosh… - IEEe …, 2023 - ieeexplore.ieee.org
The advancement of Artificial Intelligence (AI) technology has accelerated the development
of several systems that are elicited from it. This boom has made the systems vulnerable to …

Milestones in autonomous driving and intelligent vehicles: Survey of surveys

L Chen, Y Li, C Huang, B Li, Y Xing… - IEEE Transactions …, 2022 - ieeexplore.ieee.org
Interest in autonomous driving (AD) and intelligent vehicles (IVs) is growing at a rapid pace
due to the convenience, safety, and economic benefits. Although a number of surveys have …

Perception task offloading with collaborative computation for autonomous driving

Z Xiao, J Shu, H Jiang, G Min… - IEEE Journal on …, 2022 - ieeexplore.ieee.org
Autonomous driving has so far received numerous attention from academia and industry.
However, the inevitable occlusion is a great menace to safety and reliable driving. Existing …

" Help Me Help the AI": Understanding How Explainability Can Support Human-AI Interaction

SSY Kim, EA Watkins, O Russakovsky, R Fong… - Proceedings of the …, 2023 - dl.acm.org
Despite the proliferation of explainable AI (XAI) methods, little is understood about end-
users' explainability needs and behaviors around XAI explanations. To address this gap and …

Milestones in autonomous driving and intelligent vehicles—Part I: Control, computing system design, communication, HD map, testing, and human behaviors

L Chen, Y Li, C Huang, Y Xing, D Tian… - … on Systems, Man …, 2023 - ieeexplore.ieee.org
Interest in autonomous driving (AD) and intelligent vehicles (IVs) is growing at a rapid pace
due to the convenience, safety, and economic benefits. Although a number of surveys have …

Driving with llms: Fusing object-level vector modality for explainable autonomous driving

L Chen, O Sinavski, J Hünermann, A Karnsund… - arXiv preprint arXiv …, 2023 - arxiv.org
Large Language Models (LLMs) have shown promise in the autonomous driving sector,
particularly in generalization and interpretability. We introduce a unique object-level …

Explainability of deep vision-based autonomous driving systems: Review and challenges

É Zablocki, H Ben-Younes, P Pérez, M Cord - International Journal of …, 2022 - Springer
This survey reviews explainability methods for vision-based self-driving systems trained with
behavior cloning. The concept of explainability has several facets and the need for …

[HTML][HTML] Xair: A systematic metareview of explainable ai (xai) aligned to the software development process

T Clement, N Kemmerzell, M Abdelaal… - Machine Learning and …, 2023 - mdpi.com
Currently, explainability represents a major barrier that Artificial Intelligence (AI) is facing in
regard to its practical implementation in various application domains. To combat the lack of …

Why did the AI make that decision? Towards an explainable artificial intelligence (XAI) for autonomous driving systems

J Dong, S Chen, M Miralinaghi, T Chen, P Li… - … research part C …, 2023 - Elsevier
User trust has been identified as a critical issue that is pivotal to the success of autonomous
vehicle (AV) operations where artificial intelligence (AI) is widely adopted. For such …