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End-To-End Planning of Autonomous Driving in Industry and Academia: 2022-2023

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arxiv 2401.08658 v2 pith:UX34EQ2O submitted 2023-12-26 cs.RO cs.AI

Gongjin Lan , Qi Hao This is my paper · ORCID
classification cs.ROcs.AI
keywords end-to-endplanningacademiaautonomousdrivingindustrystate-of-the-artincluding
verification ladder T0 review T1 audit T2 compute T3 formal

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This paper aims to provide a quick review of the methods including the technologies in detail that are currently reported in industry and academia. Specifically, this paper reviews the end-to-end planning, including Tesla FSD V12, Momenta 2023, Horizon Robotics 2023, Motional RoboTaxi 2022, Woven Planet (Toyota): Urban Driver, and Nvidia. In addition, we review the state-of-the-art academic studies that investigate end-to-end planning of autonomous driving. This paper provides readers with a concise structure and fast learning of state-of-the-art end-to-end planning for 2022-2023. This article provides a meaningful overview as introductory material for beginners to follow the state-of-the-art end-to-end planning of autonomous driving in industry and academia, as well as supplementary material for advanced researchers.

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