WO2023126695 - APPLICATION OF MEAN TIME BETWEEN FAILURE (MTBF) MODELS FOR AUTONOMOUS VEHICLES
National phase entry:
Publication Number
WO/2023/126695
Publication Date
06.07.2023
International Application No.
PCT/IB2022/057684
International Filing Date
16.08.2022
Title **
[English]
APPLICATION OF MEAN TIME BETWEEN FAILURE (MTBF) MODELS FOR AUTONOMOUS VEHICLES
[French]
APPLICATION DES MODÈLES DE TEMPS MOYEN ENTRE ÉCHECS (MTBF) DESTINÉE À DES VÉHICULES AUTONOMES
Applicants **
MOBILEYE VISION TECHNOLOGIES LTD.
Inventors
OBORIL, Fabian
FABRIS, Simone
SUSSMANN, Alon
BITON SHACK, Simcha
BUERKLE, Cornelius
Priority Data
63/295,618
31.12.2021
US
Application details
| Total Number of Claims/PCT | * |
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International Searching Authority |
EPO
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| Recordal of a Change of the Applicant's Name/Address |
Change of Applicant's Name and Address
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| Type of Assignment |
The Standard Agent's Assignment
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| Applicant's Legal Status |
Legal Entity
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| Entry into National Phase under |
Chapter I
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| Patent Delivery |
Send the Letters Patent by Courier
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| 译文 |
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Quotation for National Phase entry
| Country | Stages | Total | |
|---|---|---|---|
| China | Filing, Examination, Granting | 2653 | |
| EPO | Filing, Examination, Granting | 14071 | |
| Japan | Filing, Examination, Granting | 2431 | |
| South Korea | Filing, Examination, Granting | 2630 | |
| USA | Filing, Examination, Granting | 6140 |
Total:
27,925
The term for entry into the National Phase has expired. This quotation is for informational purposes only
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Abstract[English]
To receive authority certification for mass deployment of autonomous vehicles (AVs), manufacturers need to justify that their AVs operate safer than human drivers. This in turn creates the need to estimate and model the collision rate (failure rate) of an AV taking all possible errors and driving situations into account. In other words, there is the strong demand for comprehensive Mean Time between Failure (MTBF) models for AVs. The disclosure describes such a generic and scalable model that creates a link between errors in the perception system to vehicle-level failures (collisions). Using this model, requirements for the perception quality may then be derived based on the desired vehicle-level MTBF, or vice versa, to obtain an MTBF value given a certain mission profile and perception quality.[French]
Pour recevoir une certification d'autorité pour le déploiement en masse des véhicules autonomes (VA), les fabricants ont besoin de justifier que leurs VA réalisent leurs actions plus sûrement que les conducteurs humains. Ceci crée à son tour le besoin d'estimer et de modéliser la fréquence de collision (fréquence d'échec) d'un VA en prenant en compte toutes les erreurs et situations de conduite possibles. En d'autres termes, il y a une forte demande de modèles exhaustifs de temps moyen entre échecs (MTBF) pour les VA. La divulgation décrit un tel modèle générique et évolutif qui crée une liaison entre des erreurs dans le système de perception à des échecs au niveau du véhicule (collisions). À l'aide de ce modèle, des exigences liées à la qualité de perception peuvent ensuite être déduites sur la base du MTBF de niveau du véhicule souhaité, ou vice versa, pour obtenir une valeur MTBF étant donné un certain profil de mission et une certaine qualité de perception.