Predictive suspension control for a vehicle using a stereo camera sensor

US9987898B2 · US · B2

Patent metadata
FieldValue
Publication numberUS-9987898-B2
Application numberUS-201615361632-A
CountryUS
Kind codeB2
Filing dateNov 28, 2016
Priority dateDec 1, 2015
Publication dateJun 5, 2018
Grant dateJun 5, 2018

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  1. Title

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  2. Abstract

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  5. First independent claim

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Abstract

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Embodiments of the invention address the area of predictive suspension control system for a vehicle, particularly a two-wheel vehicle such as a motor cycle or a scooter. The system includes a stereo sensor unit which for generating image data, a computing unit which extracts a relevant image portion from the image data based on future vehicle path data, and calculates road unevenness on a future vehicle path of the vehicle based on the generated image data. A suspension control unit generates an adaptation signal for adapting the suspension based on the calculated road unevenness. The computing unit adapts a search direction of a stereo algorithm or a correlation area of the stereo algorithm based on a lean angle of the vehicle to generate the three-dimensional partial image data from the relevant image portion, and fits a road model to the three-dimensional partial image data to calculate the road unevenness.

First claim

Opening claim text (preview).

The invention claimed is: 1. A system for adapting a suspension of a vehicle, the system comprising: a stereo sensor unit configured to generate image data, a computing unit configured to extract a relevant image portion from the image data based on future vehicle path data, and to calculate a road unevenness on a future vehicle path of the vehicle based on the generated image data, a suspension control unit configured to generate an adaptation signal for adapting the suspension based on the calculated road unevenness, and wherein the computing unit is configured to adapt a search direction of a stereo algorithm or a correlation area of the stereo algorithm based on a lean angle of the vehicle to generate three-dimensional partial image data from the relevant image portion, and to fit a road model to the three-dimensional partial image data to calculate the road unevenness. 2. The system according to claim 1 , wherein the stereo sensor unit is a stereo camera. 3. The system according to claim 1 , wherein the stereo sensor unit is configured to generate the image data which images an area in a driving direction of the vehicle. 4. The system according to claim 1 , wherein the system comprises a vehicle path estimation unit configured to calculate future vehicle path data from at least one of vehicle dynamic data and vehicle geometry data. 5. The system according to claim 1 , wherein the system comprises a vehicle path estimation unit configured to calculate future vehicle path data based on the lean angle and a vehicle speed. 6. The system according to claim 5 , wherein the system comprises a lean angle estimation unit configured to determine the lean angle based on data from a gyroscope, a previous lean angle determined a predetermined time before, or visual odometry. 7. The system according to claim 1 , wherein the stereo algorithm is a block-matching algorithm or a semi-global matching algorithm. 8. The system according to claim 1 , wherein the image data comprises a first image and a second image, and that the computing unit is configured to generate three-dimensional partial image data by transforming the relevant portion of the first image to the second image based on a previous road model estimation. 9. The system according to claim 8 , wherein the first image is a left image and the second image is a right image, or the first image is a right image and the second image is a left image. 10. The system according to claim 7 , wherein the computing unit is configured to adapt at least one of a filter size, a filter shape, and a filter orientation of the stereo algorithm based on the lean angle. 11. The system according to claim 8 , wherein the computing unit is configured to rotate the first image and the second image. 12. The system according to claim 1 , wherein the road model is a planar model. 13. The system according to claim 1 , wherein the computing unit is configured to determine uneven road sections based on the three-dimensional partial image data and the road model. 14. The system according to claim 1 , wherein the computing unit is configured to calculate a three-dimensional elevation map based on the three-dimensional partial image data and the road model. 15. The system according to claim 1 , wherein the computing unit is configured to calculate the road unevenness based on a distance of each data point of the three-dimensional partial image data to a corresponding model data point of the fitted road model. 16. The system according to claim 1 , wherein the suspension control unit is configured to generate the adaptation signal further based on a distance of the vehicle at a time when generating the image data to a detected unevenness in the future vehicle path, based on a vehicle velocity. 17. The system according to claim 1 , wherein the suspension control unit is configured to generate the adaptation signal further taking into account an influence of the calculated road unevenness in the future vehicle path of the vehicle. 18. The system according to claim 1 , wherein the computing unit is configured to calculate the road unevenness as a three-dimensional road surface profile, and that the suspension control unit is configured to generate the adaptation signal as a suspension adaptation profile over time based on the three-dimensional road surface profile. 19. The system according to claim 1 , wherein the vehicle is a two-wheel vehicle. 20. A method for adapting a suspension of a vehicle, the method comprising the steps of: generating, by a stereo sensor unit, image data, extracting, by a computing unit, a relevant image portion from the image data based on future vehicle path data, calculating, by the computing unit, three-dimensional partial image data by using a stereo algorithm, adapting a search direction of the stereo algorithm or a correlation area of the stereo algorithm to generate three-dimensional image data based on a lean angle of the vehicle, fitting, by the computing unit, a road model to the three-dimensional partial image data to calculate a road unevenness based on the three-dimensional partial image data, and generating, by a suspension control unit, an adaptation signal for adapting the suspension based on the calculated road unevenness. 21. A computer program embodied on a non-transitory computer-readable medium, said computer-readable medium including program-code thereupon, said program-code, when executed on a computer or digital signal processor, executing the method according to claim 20 .

Assignees

Inventors

Classifications

  • Indexing codes relating to the regulated action or device · CPC title

  • Cycles; Motorcycles · CPC title

  • Acceleration or inclination sensors (characterised by the use of gyroscopes B60G21/08) · CPC title

  • characterised by the type of sensor or the arrangement thereof {(B60G17/01941 takes precedence)} · CPC title

  • Speed · CPC title

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What does patent US9987898B2 cover?
Embodiments of the invention address the area of predictive suspension control system for a vehicle, particularly a two-wheel vehicle such as a motor cycle or a scooter. The system includes a stereo sensor unit which for generating image data, a computing unit which extracts a relevant image portion from the image data based on future vehicle path data, and calculates road unevenness on a futur…
Who is the assignee on this patent?
Honda Res Inst Europe Gmbh
What technology area does this patent fall under?
Primary CPC classification B60G17/0165. Mapped technology areas include Operations & Transport.
When was this patent published?
Publication date Tue Jun 05 2018 00:00:00 GMT+0000 (Coordinated Universal Time) (B2). Legal status and post-grant events are not shown on this page.
What related patents are in patentsdb?
We list 3 related publications on this page (citations in our corpus or others sharing the same primary CPC).