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Unveiling the Blind Spots: A Critical Examination of Fairness in Autonomous Driving Systems
March 26, 2024, 4:49 a.m. | Xinyue Li, Zhenpeng Chen, Jie M. Zhang, Federica Sarro, Ying Zhang, Xuanzhe Liu
cs.CV updates on arXiv.org arxiv.org
Abstract: Autonomous driving systems have extended the spectrum of Web of Things for intelligent vehicles and have become an important component of the Web ecosystem. Similar to traditional Web-based applications, fairness is an essential aspect for ensuring the high quality of autonomous driving systems, particularly in the context of pedestrian detectors within them. However, there is an absence in the literature of a comprehensive assessment of the fairness of current Deep Learning (DL)-based pedestrian detectors. To …
abstract applications arxiv autonomous autonomous driving autonomous driving systems become blind cs.ai cs.cv cs.cy cs.se driving ecosystem fairness intelligent quality spectrum systems type vehicles web
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