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

• Main Authors: Ekim Yurtsever, Jacob Lambert, Alexander Carballo, Kazuya Takeda
• Format: Article
• Language: English
• Published: IEEE 2020-01-01
• Series: IEEE Access
• Subjects: Autonomous vehicles; control; robotics; automation; intelligent vehicles; intelligent transportation systems
• Online Access: https://ieeexplore.ieee.org/document/9046805/

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.