Latest revision as of 12:27, 12 February 2021

Abstract

Presently, in the event of a failure in Automated Driving Systems, control architectures rely on hardware redundancies over software solutions to assure reliability or wait for human interaction in takeover requests to achieve a minimal risk condition. As user confidence and final acceptance of this novel technology are strongly related to enabling safe states, automated fall-back strategies must be assured as a response to failures while the system is performing a dynamic driving task. In this work, a fail-operational control architecture approach and dead-reckoning strategy in case of positioning failures are developed and presented. A fail-operational system is capable of detecting failures in the last available positioning source, warning the decision stage to set up a fall-back strategy and planning a new trajectory in real time. The surrounding objects and road borders are considered during the vehicle motion control after failure, to avoid collisions and lane-keeping purposes. A case study based on a realistic urban scenario is simulated for testing and system verification. It shows that the proposed approach always bears in mind both the passenger&rsquo

s safety and comfort during the fall-back maneuvering execution.

Document type: Article

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The different versions of the original document can be found in:

• http://dx.doi.org/10.3390/s20020442 under the license https://creativecommons.org/licenses/by

• http://dx.doi.org/10.3390/s20020442 under the license http://creativecommons.org/licenses/by/3.0/

• http://dx.doi.org/10.3390/s20020442 under the license https://creativecommons.org/licenses/by/4.0

• http://europepmc.org/articles/PMC7014171 under the license https://creativecommons.org/licenses/by/4.0/

• http://hdl.handle.net/11556/854

• https://www.mdpi.com/1424-8220/20/2/442/pdf under the license http://creativecommons.org/licenses/by/4.0/

• https://dblp.uni-trier.de/db/journals/sensors/sensors20.html#Matute-PeaspanR20,

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7014171,

https://www.mdpi.com/1424-8220/20/2/442,

https://www.mdpi.com/1424-8220/20/2/442/pdf,

http://dsp.tecnalia.com/handle/11556/854,

https://doi.org/10.3390/s20020442,

https://academic.microsoft.com/#/detail/2999156422 under the license cc-by

• https://www.mdpi.com/1424-8220/20/2/442,

https://doaj.org/toc/1424-8220

• https://www.mdpi.com/1424-8220/20/2/442/pdf,

http://dx.doi.org/10.3390/s20020442

under the license https://creativecommons.org/licenses/by/4.0/