Autonomous Vehicles on the Edge: A Survey on Autonomous Vehicle Racing
The rising popularity of self-driving cars has led to the emergence of a new research field in recent years: Autonomous racing. Researchers are developing software and hardware for high-performance race vehicles which aim to operate autonomously on the edge of the vehicle’s limits: High speeds, high accelerations, low reaction times, highly uncertain, dynamic, and adversarial environments. This paper represents the first holistic survey that covers the research in the field of autonomous racing. The authors focus on the field of autonomous racecars only and display the algorithms, methods, and approaches used in the areas of perception, planning, control, and end-to-end learning. Further, with an increasing number of autonomous racing competitions, researchers now have access to high-performance platforms to test and evaluate their autonomy algorithms. This survey presents a comprehensive overview of the current autonomous racing platforms, emphasizing the software-hardware co-evolution to the current stage. Finally, based on additional discussion with leading researchers in the field, the authors conclude with a summary of open research challenges that will guide future researchers in this field.
- Record URL:
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/issn/26877813
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Supplemental Notes:
- © 2022 The Authors.
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Authors:
- Betz, J
- Zheng, H
- Liniger, A
- Rosolia, U
- Karle, P
- Behl, M
- Krovi, V
- Mangharam, R
- Publication Date: 2022
Language
- English
Media Info
- Media Type: Web
- Features: References;
- Pagination: pp 458-488
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Serial:
- IEEE Open Journal of Intelligent Transportation Systems
- Volume: 3
- Publisher: Institute of Electrical and Electronics Engineers (IEEE)
- ISSN: 2687-7813
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Publication flags:
Open Access (libre)
Subject/Index Terms
- TRT Terms: Autonomous vehicles; Race cars; Racing; Vehicle design
- Subject Areas: Highways; Safety and Human Factors; Vehicles and Equipment;
Filing Info
- Accession Number: 01866567
- Record Type: Publication
- Files: TRIS
- Created Date: Dec 5 2022 3:10PM