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Automated Testing of Ultrawideband Positioning for Autonomous Driving
RISE Research Institutes of Sweden.
RISE Research Institutes of Sweden, Safety and Transport, Electrification and Reliability.ORCID iD: 0000-0003-0363-1206
RISE Research Institutes of Sweden, Safety and Transport, Electrification and Reliability.ORCID iD: 0000-0002-6191-6253
Halmstad University, Sweden.
2020 (English)In: Journal of Robotics, ISSN 1687-9600, E-ISSN 1687-9619, Vol. 2020, article id 9345360Article in journal (Refereed) Published
Abstract [en]

Autonomous vehicles need accurate and dependable positioning, and these systems need to be tested extensively. We have evaluated positioning based on ultrawideband (UWB) ranging with our self-driving model car using a highly automated approach. Random drivable trajectories were generated, while the UWB position was compared against the Real-Time Kinematic Satellite Navigation (RTK-SN) positioning system which our model car also is equipped with. Fault injection was used to study the fault tolerance of the UWB positioning system. Addressed challenges are automatically generating test cases for real-time hardware, restoring the state between tests, and maintaining safety by preventing collisions. We were able to automatically generate and carry out hundreds of experiments on the model car in real time and rerun them consistently with and without fault injection enabled. Thereby, we demonstrate one novel approach to perform automated testing on complex real-time hardware.

Place, publisher, year, edition, pages
Hindawi Limited , 2020. Vol. 2020, article id 9345360
Keywords [en]
Automatic test pattern generation, Automation, Fault tolerance, Software testing, Ultra-wideband (UWB), Automated approach, Automated testing, Autonomous driving, Fault injection, Positioning system, Real time kinematic, Real-time hardware, Satellite navigation, Autonomous vehicles
National Category
Natural Sciences
Identifiers
URN: urn:nbn:se:ri:diva-43946DOI: 10.1155/2020/9345360Scopus ID: 2-s2.0-85079208712OAI: oai:DiVA.org:ri-43946DiVA, id: diva2:1394677
Available from: 2020-02-19 Created: 2020-02-19 Last updated: 2020-02-20Bibliographically approved

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Svensson, JoelVinter, Jonny

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