Derivation of harmonised high-level safety requirements for self-driving cars using railway experience
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216275%3A25530%2F22%3A39919638" target="_blank" >RIV/00216275:25530/22:39919638 - isvavai.cz</a>
Výsledek na webu
<a href="https://www.nature.com/articles/s41598-022-26764-0" target="_blank" >https://www.nature.com/articles/s41598-022-26764-0</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1038/s41598-022-26764-0" target="_blank" >10.1038/s41598-022-26764-0</a>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Derivation of harmonised high-level safety requirements for self-driving cars using railway experience
Popis výsledku v původním jazyce
The development and manufacture of self-driving cars (SDCs) have triggered unprecedented challenges among car manufacturers and smart road operators to accelerate awareness and implementation of innovative technologies for cooperative, connected and automated mobility (CCAM), especially those with a high level of automation and safety. Safety improvement is a pre-requisite to justify and unleashing a mass deployment of connected and driverless cars to reach the goal of zero-accident in 2050 set by the European Commission. Behind these motivations a well-justified and widely acceptable high-level safety target for SDCs is mandatory. The aim of this article is to contribute to the derivation of an harmonised high-level safety target for SDCs, starting from the safety requirements and the state of the art achieved by train and airplane operations. The novelty of our approach is to leverage the Common Safety Method-Design Targets (CSM-DT) already adopted and widely accepted by the railway community. According to this approach, the derived, justified and harmonised high-level design safety target for SDCs, defined as the average probability of a dangerous failure PFSDC per 1 h, should be 1 × 10−7/h. An example of PFSDC allocation to individual SDC safety functions, including position determination based on Global Navigation Satellite System (GNSS), is described using a fault tree. The proposed methodology can speed up the validation and certification process needed to authorise the SDCs, by capitalising the know-how and best practices in use since many years for the train management.
Název v anglickém jazyce
Derivation of harmonised high-level safety requirements for self-driving cars using railway experience
Popis výsledku anglicky
The development and manufacture of self-driving cars (SDCs) have triggered unprecedented challenges among car manufacturers and smart road operators to accelerate awareness and implementation of innovative technologies for cooperative, connected and automated mobility (CCAM), especially those with a high level of automation and safety. Safety improvement is a pre-requisite to justify and unleashing a mass deployment of connected and driverless cars to reach the goal of zero-accident in 2050 set by the European Commission. Behind these motivations a well-justified and widely acceptable high-level safety target for SDCs is mandatory. The aim of this article is to contribute to the derivation of an harmonised high-level safety target for SDCs, starting from the safety requirements and the state of the art achieved by train and airplane operations. The novelty of our approach is to leverage the Common Safety Method-Design Targets (CSM-DT) already adopted and widely accepted by the railway community. According to this approach, the derived, justified and harmonised high-level design safety target for SDCs, defined as the average probability of a dangerous failure PFSDC per 1 h, should be 1 × 10−7/h. An example of PFSDC allocation to individual SDC safety functions, including position determination based on Global Navigation Satellite System (GNSS), is described using a fault tree. The proposed methodology can speed up the validation and certification process needed to authorise the SDCs, by capitalising the know-how and best practices in use since many years for the train management.
Klasifikace
Druh
J<sub>imp</sub> - Článek v periodiku v databázi Web of Science
CEP obor
—
OECD FORD obor
20202 - Communication engineering and systems
Návaznosti výsledku
Projekt
<a href="/cs/project/EF17_049%2F0008394" target="_blank" >EF17_049/0008394: Spolupráce Univerzity Pardubice a aplikační sféry v aplikačně orientovaném výzkumu lokačních, detekčních a simulačních systémů pro dopravní a přepravní procesy (PosiTrans)</a><br>
Návaznosti
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Ostatní
Rok uplatnění
2022
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název periodika
Scientific Reports
ISSN
2045-2322
e-ISSN
2045-2322
Svazek periodika
12
Číslo periodika v rámci svazku
1
Stát vydavatele periodika
GB - Spojené království Velké Británie a Severního Irska
Počet stran výsledku
13
Strana od-do
1-13
Kód UT WoS článku
000904416000026
EID výsledku v databázi Scopus
2-s2.0-85144637432