IEEE Access· 2020Q1· Review
A Survey of Autonomous Driving: <i>Common Practices and Emerging Technologies</i>
- 1,741citations
- Q1SCImago
- 2020year
Short summary
Despite promises of safety and efficiency, fatalities involving autonomous vehicles are increasing, highlighting a critical need to improve system robustness.
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Key points
- Fatalities involving autonomous vehicles are on the rise, indicating a gap in system robustness.
- The paper surveys common practices and emerging technologies in autonomous driving.
- Core functions reviewed include localization, mapping, perception, planning, and human-machine interfaces.
- State-of-the-art algorithms were implemented and compared in a real-world driving setting.
- An overview of datasets and tools for autonomous driving development is provided.
AI-generated from the title and abstract; the full text is not read.
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.
The authors' abstract, as published at the source. IEEE Access, 2020 · DOI ↗
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Field: Automotive Engineering
Automotive EngineeringEngineering