EP 4073782 A4 20240117 - PERCEPTION ERROR MODELS
Title (en)
PERCEPTION ERROR MODELS
Title (de)
WAHRNEHMUNGSFEHLERMODELLE
Title (fr)
MODÈLES D'ERREUR DE PERCEPTION
Publication
Application
Priority
- US 201916708019 A 20191209
- US 2020062602 W 20201130
Abstract (en)
[origin: WO2021118822A1] Techniques for determining an error model based on vehicle data and ground truth data are discussed herein. To determine whether a complex system (which may be not capable of being inspected) is able to operate safely, various operating regimes (scenarios) can be identified based on operating data. To provide safe operation of such a system, an error model can be determined that can provide a probability associated with perception data and a vehicle can determine a trajectory based on the probability of an error associated with the perception data.
IPC 8 full level
G09B 9/042 (2006.01); B60W 30/095 (2012.01); G06F 11/36 (2006.01); G06F 30/20 (2020.01); G06V 20/56 (2022.01)
CPC (source: EP)
G06F 11/3664 (2013.01); G06F 11/3684 (2013.01); G06F 30/20 (2020.01); G06V 20/56 (2022.01); G09B 9/042 (2013.01); G06F 11/3696 (2013.01)
Citation (search report)
- [IY] US 2018336297 A1 20181122 - SUN XING [US], et al
- [Y] US 2017286570 A1 20171005 - KIM BAEKGYU [US], et al
- [Y] XUE GUANGTAO ET AL: "Pothole in the Dark: Perceiving Pothole Profiles with Participatory Urban Vehicles", IEEE TRANSACTIONS ON MOBILE COMPUTING, IEEE SERVICE CENTER, LOS ALAMITOS, CA, US, vol. 16, no. 5, 1 May 2017 (2017-05-01), pages 1408 - 1419, XP011644842, ISSN: 1536-1233, [retrieved on 20170403], DOI: 10.1109/TMC.2016.2597839
- See references of WO 2021118822A1
Designated contracting state (EPC)
AL AT BE BG CH CY CZ DE DK EE ES FI FR GB GR HR HU IE IS IT LI LT LU LV MC MK MT NL NO PL PT RO RS SE SI SK SM TR
DOCDB simple family (publication)
WO 2021118822 A1 20210617; CN 114787894 A 20220722; EP 4073782 A1 20221019; EP 4073782 A4 20240117; JP 2023504506 A 20230203
DOCDB simple family (application)
US 2020062602 W 20201130; CN 202080084729 A 20201130; EP 20900042 A 20201130; JP 2022533057 A 20201130