Abstract

Automated driving systems (ADSs) promise a safe, comfortable and efficient\ndriving experience. However, fatalities involving vehicles equipped with ADSs\nare on the rise. The full potential of ADSs cannot be realized unless the\nrobustness of state-of-the-art improved further. This paper discusses unsolved\nproblems and surveys the technical aspect of automated driving. Studies\nregarding present challenges, high-level system architectures, emerging\nmethodologies and core functions: localization, mapping, perception, planning,\nand human machine interface, were thoroughly reviewed. Furthermore, the\nstate-of-the-art was implemented on our own platform and various algorithms\nwere compared in a real-world driving setting. The paper concludes with an\noverview of available datasets and tools for ADS development.\n

Keywords

Robustness (evolution)Computer sciencePerceptionEmerging technologiesData scienceSystems engineeringHuman–computer interactionArtificial intelligenceEngineering

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Publication Info

Year
2020
Type
article
Volume
8
Pages
58443-58469
Citations
1536
Access
Closed

Social Impact

Social media, news, blog, policy document mentions

Citation Metrics

1536
OpenAlex
52
Influential
1433
CrossRef

Cite This

Ekim Yurtsever, Jacob Lambert, Alexander Carballo et al. (2020). A Survey of Autonomous Driving: <i>Common Practices and Emerging Technologies</i>. IEEE Access , 8 , 58443-58469. https://doi.org/10.1109/access.2020.2983149

Identifiers

DOI
10.1109/access.2020.2983149
arXiv
1906.05113

Data Quality

Data completeness: 84%