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A Survey of Autonomous Driving: Common Practices and Emerging Technologies

Ekim Yurtsever,Jacob Lambert,Alexander Carballo,K. Takeda

2019 · DOI: 10.1109/ACCESS.2020.2983149
IEEE Access · 1,756 Citations

TLDR

The technical aspect of automated driving is surveyed, with an overview of available datasets and tools for ADS development and many state-of-the-art algorithms implemented and compared on their own platform in a real-world driving setting.

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.