Details
| Originalsprache | Englisch |
|---|---|
| Titel des Sammelwerks | 2024 Kleinheubach Conference |
| ISBN (elektronisch) | 978-3-948571-12-2 |
| Publikationsstatus | Veröffentlicht - 2024 |
Abstract
Accurate measurement of vehicle angles, particularly pitch angles, is crucial for the safety and efficiency of modern vehicles. These angles affect vehicle dynamics such as acceleration and braking and are essential for adaptive headlight systems that adjust lighting based on vehicle pitch. Various methods exist for measuring vehicle pitch angles, including LiDAR, wheel sensors combined with inclinometers, and inertial measurement units or accelerometers in conjunction with wheel sensors. A cost-effective approach employs an algorithm that calculates real acceleration from vehicle speed and accounts for road inclination using only accelerometers. However, this algorithm only provides reliable results with accurate accelerometer data. Since accelerometers are prone to noise, signal processing requires filtering. Linear filters, which significantly smooth the signal, are unsuitable here as they can distort crucial signal information through over-smoothing. Instead, nonlinear filters offer a better solution. The Kuwahara filter, total variation filter, and bilateral filter are such nonlinear alternatives that reduce noise while preserving essential signal details, such as edges and features. Tests indicate that without adequate filtering, the average deviation in pitch angle is 1.4 degrees, with a maximum error of 19.4 degrees. With the use of the bilateral filter, this average error is reduced to 0.11 degrees and the maximum error to 1.2 degrees.
ASJC Scopus Sachgebiete
- Informatik (insg.)
- Computernetzwerke und -kommunikation
- Informatik (insg.)
- Angewandte Informatik
- Erdkunde und Planetologie (insg.)
- Geophysik
- Ingenieurwesen (insg.)
- Elektrotechnik und Elektronik
- Physik und Astronomie (insg.)
- Instrumentierung
- Physik und Astronomie (insg.)
- Strahlung
Zitieren
- Standard
- Harvard
- Apa
- Vancouver
- BibTex
- RIS
2024 Kleinheubach Conference. 2024.
Publikation: Beitrag in Buch/Bericht/Sammelwerk/Konferenzband › Aufsatz in Konferenzband › Forschung › Peer-Review
}
TY - GEN
T1 - Non-linear Filtering Techniques for Improving Accurate Vehicle Angle Determination
AU - Pfleiderer, Richard
AU - Ramsdorf, Jannes
AU - Boländer, Yannis
AU - Blume, Holger
N1 - Publisher Copyright: © 2024 Deutscher Landesausschuss in der Bundesrepublik Deutschland e.V.
PY - 2024
Y1 - 2024
N2 - Accurate measurement of vehicle angles, particularly pitch angles, is crucial for the safety and efficiency of modern vehicles. These angles affect vehicle dynamics such as acceleration and braking and are essential for adaptive headlight systems that adjust lighting based on vehicle pitch. Various methods exist for measuring vehicle pitch angles, including LiDAR, wheel sensors combined with inclinometers, and inertial measurement units or accelerometers in conjunction with wheel sensors. A cost-effective approach employs an algorithm that calculates real acceleration from vehicle speed and accounts for road inclination using only accelerometers. However, this algorithm only provides reliable results with accurate accelerometer data. Since accelerometers are prone to noise, signal processing requires filtering. Linear filters, which significantly smooth the signal, are unsuitable here as they can distort crucial signal information through over-smoothing. Instead, nonlinear filters offer a better solution. The Kuwahara filter, total variation filter, and bilateral filter are such nonlinear alternatives that reduce noise while preserving essential signal details, such as edges and features. Tests indicate that without adequate filtering, the average deviation in pitch angle is 1.4 degrees, with a maximum error of 19.4 degrees. With the use of the bilateral filter, this average error is reduced to 0.11 degrees and the maximum error to 1.2 degrees.
AB - Accurate measurement of vehicle angles, particularly pitch angles, is crucial for the safety and efficiency of modern vehicles. These angles affect vehicle dynamics such as acceleration and braking and are essential for adaptive headlight systems that adjust lighting based on vehicle pitch. Various methods exist for measuring vehicle pitch angles, including LiDAR, wheel sensors combined with inclinometers, and inertial measurement units or accelerometers in conjunction with wheel sensors. A cost-effective approach employs an algorithm that calculates real acceleration from vehicle speed and accounts for road inclination using only accelerometers. However, this algorithm only provides reliable results with accurate accelerometer data. Since accelerometers are prone to noise, signal processing requires filtering. Linear filters, which significantly smooth the signal, are unsuitable here as they can distort crucial signal information through over-smoothing. Instead, nonlinear filters offer a better solution. The Kuwahara filter, total variation filter, and bilateral filter are such nonlinear alternatives that reduce noise while preserving essential signal details, such as edges and features. Tests indicate that without adequate filtering, the average deviation in pitch angle is 1.4 degrees, with a maximum error of 19.4 degrees. With the use of the bilateral filter, this average error is reduced to 0.11 degrees and the maximum error to 1.2 degrees.
KW - bilateral filter
KW - kuwahara
KW - pitch angle
KW - total variation
KW - vehicle
UR - http://www.scopus.com/inward/record.url?scp=85211619902&partnerID=8YFLogxK
U2 - 10.23919/ieeeconf64570.2024.10739191
DO - 10.23919/ieeeconf64570.2024.10739191
M3 - Conference contribution
SN - 979-8-3315-4177-4
BT - 2024 Kleinheubach Conference
ER -