April 2, 2024, 7:42 p.m. | Sule Tekkesinoglu, Azra Habibovic, Lars Kunze

cs.LG updates on arXiv.org arxiv.org

arXiv:2404.00019v1 Announce Type: cross
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 the 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 …

abstract alignment arxiv autonomous autonomous vehicle autonomous vehicles avs cs.ai cs.hc cs.lg cs.ro current diverse explainability investigation research review roadmap stakeholders strategies systems type uncertainty vehicles

Data Architect

@ University of Texas at Austin | Austin, TX

Data ETL Engineer

@ University of Texas at Austin | Austin, TX

Lead GNSS Data Scientist

@ Lurra Systems | Melbourne

Senior Machine Learning Engineer (MLOps)

@ Promaton | Remote, Europe

C003549 Data Analyst (NS) - MON 13 May

@ EMW, Inc. | Braine-l'Alleud, Wallonia, Belgium

Marketing Decision Scientist

@ Meta | Menlo Park, CA | New York City