Vertaisarvioitu alkuperäisartikkeli tai data-artikkeli tieteellisessä aikakauslehdessä (A1)

Development and experimental validation of high performance embedded intelligence and fail-operational urban surround perception solutions of the PRYSTINE project




Julkaisun tekijät: Novickis Rihards, Levinskis Aleksandrs, Fescenko Vitalijs, Kadikis Roberts, Ozols Kaspars, Ryabokon Anna, Schorn Rupert, Koszescha Jochen, Solmaz Selim, Stettinger Georg, Adu-Kyere Akwasi, Halla-Aho Lauri, Nigussie Ethiopia, Isoaho Jouni

Kustantaja: MDPI

Julkaisuvuosi: 2022

Journal: Applied Sciences

Tietokannassa oleva lehden nimi: Applied Sciences (Switzerland)

Volyymi: 12

Julkaisunumero: 1

ISSN: 2076-3417

DOI: http://dx.doi.org/10.3390/app12010168

Rinnakkaistallenteen osoite: https://research.utu.fi/converis/portal/detail/Publication/68506318


Tiivistelmä

Automated Driving Systems (ADSs) commend a substantial reduction of human-caused road accidents while simultaneously lowering emissions, mitigating congestion, decreasing energy consumption and increasing overall productivity. However, achieving higher SAE levels of driving automation and complying with ISO26262 C and D Automotive Safety Integrity Levels (ASILs) is a multi-disciplinary challenge that requires insights into safety-critical architectures, multi-modal perception and real-time control. This paper presents an assorted effort carried out in the European H2020 ECSEL project—PRYSTINE. In this paper, we (1) investigate Simplex, 1oo2d and hybrid fail-operational computing architectures, (2) devise a multi-modal perception system with fail-safety mechanisms, (3) present a passenger vehicle-based demonstrator for low-speed autonomy and (4) suggest a trust-based fusion approach validated on a heavy-duty truck.


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Last updated on 2022-30-03 at 09:36