Evaluation of Novel Safety Concepts for Automotive Perception in Real-World Environments

Philipp Stelzer; Andreas Strasser; Josef Steinbaeck; Christian Steger; Markus Schratter; Norbert Druml

doi:10.1109/MoRSE50327.2021.9766013

Evaluation of Novel Safety Concepts for Automotive Perception in Real-World Environments

Philipp Stelzer, Andreas Strasser, Josef Steinbaeck, Christian Steger, Markus Schratter, Norbert Druml

Research output: Chapter in Book/Report/Conference proceeding › Conference paper › peer-review

Abstract

Safety is one of the most important topics regarding Automated-Driving in the Automotive Domain. In the last years, LiDAR, Radar and Vision Cameras became the most relevant Environmental Perception Sensors for enabling safe and robust Automated-Driving. All of these systems offers specific strengths and weaknesses in specific situations such as bright sunlight or heavy rain. Therefore, these systems requires specific Fail-Operational concepts to allow robust and safe driving in urban and rural environments.
In this publication, we are depicting Real-World evaluation of Safety Concepts and Fail-Operational functionality of a Sensor Fusion Platform that offers Radar, 3D Flash LiDAR and Vision Cameras. We verified our platform in specific driving situations such as driving from an urban parking environment into bright sunlight with the dynamic adaption of the confidence range that depicts reliable data.

Original language	English
Title of host publication	2021 IEEE International Conference on Mechatronics, Robotics and Systems Engineering
Number of pages	16
DOIs	https://doi.org/10.1109/MoRSE50327.2021.9766013
Publication status	Published - 2021
Event	2021 IEEE International Conference on Mechatronics, Robotics and Systems Engineering: MoRSE 2021 - Virtuell, Indonesia Duration: 17 Nov 2021 → 19 Nov 2021

Conference

Conference	2021 IEEE International Conference on Mechatronics, Robotics and Systems Engineering
Abbreviated title	MoRSE 2021
Country/Territory	Indonesia
City	Virtuell
Period	17/11/21 → 19/11/21

Access to Document

10.1109/MoRSE50327.2021.9766013

Evaluation of Novel Safety Concepts for Automotive Perception in Real-World EnvironmentsAccepted author manuscript, 3.7 MB

1 Finished
1 Active

Hardware/Software-Codesign
Steger, C., Seifert, C., Stelzer, P., Fiala, G. & Basic, F.
1/01/95 → …
Project: Research area
PRYSTINE - Programmable Systems for Intelligence in Automobiles
Steger, C., Strasser, A. & Stelzer, P.
1/05/18 → 30/04/21
Project: Research project

Evaluation of Novel Safety Concepts for Automotive Perception in Real-World Environments
Philipp Stelzer (Speaker)
2021
Activity: Talk or presentation › Talk at conference or symposium › Science to science

Cite this

Stelzer, P, Strasser, A, Steinbaeck, J, Steger, C, Schratter, M & Druml, N 2021, Evaluation of Novel Safety Concepts for Automotive Perception in Real-World Environments. in 2021 IEEE International Conference on Mechatronics, Robotics and Systems Engineering. 2021 IEEE International Conference on Mechatronics, Robotics and Systems Engineering, Virtuell, Indonesia, 17/11/21. https://doi.org/10.1109/MoRSE50327.2021.9766013

@inproceedings{99e9a1230297406a9ed208b3140188f4,

title = "Evaluation of Novel Safety Concepts for Automotive Perception in Real-World Environments",

abstract = "Safety is one of the most important topics regarding Automated-Driving in the Automotive Domain. In the last years, LiDAR, Radar and Vision Cameras became the most relevant Environmental Perception Sensors for enabling safe and robust Automated-Driving. All of these systems offers specific strengths and weaknesses in specific situations such as bright sunlight or heavy rain. Therefore, these systems requires specific Fail-Operational concepts to allow robust and safe driving in urban and rural environments.In this publication, we are depicting Real-World evaluation of Safety Concepts and Fail-Operational functionality of a Sensor Fusion Platform that offers Radar, 3D Flash LiDAR and Vision Cameras. We verified our platform in specific driving situations such as driving from an urban parking environment into bright sunlight with the dynamic adaption of the confidence range that depicts reliable data.",

author = "Philipp Stelzer and Andreas Strasser and Josef Steinbaeck and Christian Steger and Markus Schratter and Norbert Druml",

year = "2021",

doi = "10.1109/MoRSE50327.2021.9766013",

language = "English",

booktitle = "2021 IEEE International Conference on Mechatronics, Robotics and Systems Engineering",

note = "2021 IEEE International Conference on Mechatronics, Robotics and Systems Engineering : MoRSE 2021, MoRSE 2021 ; Conference date: 17-11-2021 Through 19-11-2021",

}

TY - GEN

T1 - Evaluation of Novel Safety Concepts for Automotive Perception in Real-World Environments

AU - Stelzer, Philipp

AU - Strasser, Andreas

AU - Steinbaeck, Josef

AU - Steger, Christian

AU - Schratter, Markus

AU - Druml, Norbert

PY - 2021

Y1 - 2021

N2 - Safety is one of the most important topics regarding Automated-Driving in the Automotive Domain. In the last years, LiDAR, Radar and Vision Cameras became the most relevant Environmental Perception Sensors for enabling safe and robust Automated-Driving. All of these systems offers specific strengths and weaknesses in specific situations such as bright sunlight or heavy rain. Therefore, these systems requires specific Fail-Operational concepts to allow robust and safe driving in urban and rural environments.In this publication, we are depicting Real-World evaluation of Safety Concepts and Fail-Operational functionality of a Sensor Fusion Platform that offers Radar, 3D Flash LiDAR and Vision Cameras. We verified our platform in specific driving situations such as driving from an urban parking environment into bright sunlight with the dynamic adaption of the confidence range that depicts reliable data.

AB - Safety is one of the most important topics regarding Automated-Driving in the Automotive Domain. In the last years, LiDAR, Radar and Vision Cameras became the most relevant Environmental Perception Sensors for enabling safe and robust Automated-Driving. All of these systems offers specific strengths and weaknesses in specific situations such as bright sunlight or heavy rain. Therefore, these systems requires specific Fail-Operational concepts to allow robust and safe driving in urban and rural environments.In this publication, we are depicting Real-World evaluation of Safety Concepts and Fail-Operational functionality of a Sensor Fusion Platform that offers Radar, 3D Flash LiDAR and Vision Cameras. We verified our platform in specific driving situations such as driving from an urban parking environment into bright sunlight with the dynamic adaption of the confidence range that depicts reliable data.

U2 - 10.1109/MoRSE50327.2021.9766013

DO - 10.1109/MoRSE50327.2021.9766013

M3 - Conference paper

BT - 2021 IEEE International Conference on Mechatronics, Robotics and Systems Engineering

T2 - 2021 IEEE International Conference on Mechatronics, Robotics and Systems Engineering

Y2 - 17 November 2021 through 19 November 2021

ER -

Evaluation of Novel Safety Concepts for Automotive Perception in Real-World Environments

Abstract

Conference

Access to Document

Fingerprint

Projects

Hardware/Software-Codesign

PRYSTINE - Programmable Systems for Intelligence in Automobiles

Activities

Evaluation of Novel Safety Concepts for Automotive Perception in Real-World Environments

Cite this