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End-to-end Autonomous Driving: Challenges and Frontiers
April 23, 2024, 4:44 a.m. | Li Chen, Penghao Wu, Kashyap Chitta, Bernhard Jaeger, Andreas Geiger, Hongyang Li
cs.LG updates on arXiv.org arxiv.org
Abstract: The autonomous driving community has witnessed a rapid growth in approaches that embrace an end-to-end algorithm framework, utilizing raw sensor input to generate vehicle motion plans, instead of concentrating on individual tasks such as detection and motion prediction. End-to-end systems, in comparison to modular pipelines, benefit from joint feature optimization for perception and planning. This field has flourished due to the availability of large-scale datasets, closed-loop evaluation, and the increasing need for autonomous driving algorithms …
arxiv autonomous autonomous driving challenges cs.ai cs.cv cs.lg cs.ro driving frontiers type
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