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

IEEE Access · 2020 · Vol. 8 · pp. 58443–58469
Ekim YurtseverJacob LambertAlexander CarballoKazuya Takeda

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.

Autonomous Vehicle Technology and SafetyAdvanced Neural Network ApplicationsHuman-Automation Interaction and SafetyRobustness (evolution)Computer sciencePerceptionEmerging technologiesData scienceSystems engineeringHuman–computer interactionArtificial intelligenceEngineering
Citations
1,666
FWCI
85.18
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References
356
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A Survey of Autonomous Driving: <i>Common Practices and Emerging Technologies</i> · Scinovex