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Development of lane-precise “Ground Truth” maps for the objective Quality Assessment of automated driving functions

  • The focus of this publication is on the development of lane-precise “Ground Truth” (GT) maps for the objective quality evaluation of automated driving functions. Therefore, attention is paid to the proper measurement of road geometry. The road geometry forms the basic layer of the HD maps. A new map format Curved Regular Objects (CRO) is developed, which is based on the idea of OpenCRG®. For the evaluation of current Advanced Driver Assistance Systems (ADAS) an accurate High Definition (HD) maps as GT are necessary. This makes it possible to locate the high precision vehicle position and motion with centimeter accuracy. The aim is to achieve maximum accuracy of the absolute 3D positions when measuring lanes. This method for the generation of highly accurate GT maps promises an absolute accuracy of < ± 0.05 m. Various research activities benefit from the exact street reference at the Kempten University of Applied Sciences (UAS Kempten) in the Adrive Living Lab. First of all, the publication deals with the current Lane KeepingThe focus of this publication is on the development of lane-precise “Ground Truth” (GT) maps for the objective quality evaluation of automated driving functions. Therefore, attention is paid to the proper measurement of road geometry. The road geometry forms the basic layer of the HD maps. A new map format Curved Regular Objects (CRO) is developed, which is based on the idea of OpenCRG®. For the evaluation of current Advanced Driver Assistance Systems (ADAS) an accurate High Definition (HD) maps as GT are necessary. This makes it possible to locate the high precision vehicle position and motion with centimeter accuracy. The aim is to achieve maximum accuracy of the absolute 3D positions when measuring lanes. This method for the generation of highly accurate GT maps promises an absolute accuracy of < ± 0.05 m. Various research activities benefit from the exact street reference at the Kempten University of Applied Sciences (UAS Kempten) in the Adrive Living Lab. First of all, the publication deals with the current Lane Keeping Assistant Systems (LKAS). The accuracy of the vehicle’s localization on the GT map and an objective evaluation of the LKAS is shown. In addition, the CRO data is used as a virtual sensor for the steering assistant in real time. Another application is the Visual Range Finder (VRF), which requires less computation power by using the CRO data. In addition, a current LKAS camera sensor performance is evaluated using CRO maps.show moreshow less

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Metadaten
Author:Sebastian Michael Keidler, Daniel SchneiderORCiD, Johann Haselberger, Krishnakumar Mayannavar, Bernhard SchickORCiD
DOI:https://doi.org/10.51202/9783181023563-15
Identifier:978-3-18-092356-7 OPAC HS OPAC extern
Identifier:0083-5560 OPAC HS OPAC extern
Parent Title (German):17. VDI-Fachtagung Reifen - Fahrwerk - Fahrbahn: im Spannungsfeld von Sicherheit und Umwelt; VDI-Berichte Nr. 2356
Publisher:VDI-Verlag
Place of publication:Düsseldorf
Document Type:conference proceeding (article)
Conference:17. VDI-Fachtagung Reifen - Fahrwerk - Fahrbahn: im Spannungsfeld von Sicherheit und Umwelt: Hannover, 16. und 17. Oktober 2019
Language:English
Year of first Publication:2019
Tag:Ground Truth MB
advanced driver assistance systems; automated driving; driving experience; head-up display; human factor; human maschine interface; stress; workload
Number of pages:19 Seiten
First Page:15
Last Page:33
Institutes:Fakultät Maschinenbau
IFM - Institut für Fahrerassistenz und vernetzte Mobilität
Dewey Decimal Classification:6 Technik, Medizin, angewandte Wissenschaften / 62 Ingenieurwissenschaften
Research focus:FSP2: Mobilität
Publication Lists:Schick, Bernhard
Schneider, Daniel
Keidler, Sebastian Michael
Haselberger, Johann
Mayannavar, Krishnakumar
Research Project:Ground Truth Messsystem
Publication reviewed:begutachtet
Release Date:2020/08/12
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