A Survey of Autonomous Driving: <i>Common Practices and Emerging Technologies</i>

2020/01/01 by Ekim Yurtsever, Jacob Lambert, Alexander Carballo +1 · 47 citations
Computer Science · Engineering · Psychology · #Advanced Neural Network Applications #Autonomous Vehicle Technology and Safety #Human-Automation Interaction and Safety

paper · pdf · doi:10.1109/access.2020.2983149

openalex created_date 2019/06/27 · openalex publication_date 2020/01/01 · openalex updated_date 2026/07/28

Abstract

Automated driving systems (ADSs) promise a safe, comfortable and efficient driving experience. However, fatalities involving vehicles equipped with ADSs are on the rise. The full potential of ADSs cannot be realized unless the robustness of state-of-the-art is improved further. This paper discusses unsolved problems and surveys the technical aspect of automated driving. Studies regarding present challenges, high-level system architectures, emerging methodologies and core functions including localization, mapping, perception, planning, and human machine interfaces, were thoroughly reviewed. Furthermore, many state-of-the-art algorithms were implemented and compared on our own platform in a real-world driving setting. The paper concludes with an overview of available datasets and tools for ADS development.

Citations

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