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US6300865B1 Expired / Lapsed US ⏱️ 0.0 years remaining

Process for detecting the road conditions ahead for motor vehicles

Assignee: Mercedes Benz Group AG
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Filing: 1997-05-07
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Granted: 2001-10-09
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Expires: 2017-05-07
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Abstract

Abstract A process for recognizing the course of the road ahead for a motor vehicle shall be provided, in which the velocity of the vehicle is determined and the position and the velocity of objects located ahead are determined by rigid search antennas oriented in the direction of travel via a radar sensor system, and which makes possible a simple, forward-looking recognition of the course of the road by special evaluation of the measured position and velocity data available. The roadside-specific targets are filtered out of the fixed target by the threshold value comparison of the fixed target amplitudes, and the current distances between the vehicle and the side of the road are determined in discrete angle ranges by ordering filtration. The distances from the side of the road, estimated for each angle range, are sent as characteristics to a classifier for the prediction of the curve type lying ahead, and they are used as support values for a nonlinear regression to obtain a curvature parameter of the curve.

Inventors

  • 👤 Thomas Fechner
  • 👤 Rainer Hach

Bibliographic Details

Application Number —
Jurisdiction US
Data Source google_patents
Last Synchronized 2026-10-26 19:45
CPC Classifications
B; B62; B62D; B62D1/00; B62D1/24; B62D1/28; G; G01; G01S; G01S13/00; G01S13/88; G01S13/93; G01S13/931; G05; G05D; G05D1/00; G05D1/02; G05D1/021; G05D1/0257; G01S2013/9327; G01S2013/93271; Y; Y10; Y10S; Y10S367/00; Y10S367/909

Claims Analysis

Total Claims: 10
Claim 1
Independent Claim 215 words
A process for recognizing the course of the road ahead for a motor vehicle, the process comprising the steps of; determining the velocity of the motor vehicle; determining the position and velocity of objects located ahead of the vehicle by a radar sensor system with rigidly oriented antennas; separating fixed objects out of the objects located ahead of the vehicle, said separating being performed in a plurality of discrete angle ranges; determining current distances between a side of the road and the motor vehicle from the fixed objects and using the determined current distances as characteristics for a nonlinear regression; determining the objects which are specific of the side of the road from among the fixed objects in the discrete angle ranges by a threshold value comparison of radar target amplitudes; filtering, with an ordering filter, the object with a shortest distance out of the roadside-specific objects determined in each of the discrete angle ranges over a plurality of consecutive measurement cycles; using the filtered object from said ordering filter to determine the distance between the side of the road and the motor vehicle in each of the discrete angle range; and using the objects determined in the discrete angle ranges as characteristics for an adaptive prediction of a curve type using a curve classifier.
Claim 2
Dependent Claim 215 words
A process for recognizing the course of the road ahead for a motor vehicle, the process comprising the steps of; determining the velocity of the motor vehicle; determining the position and velocity of objects located ahead of the vehicle by a radar sensor system with rigidly oriented antennas; separating fixed objects out of the objects located ahead of the vehicle, said separating being performed in a plurality of discrete angle ranges; determining current distances between a side of the road and the motor vehicle from the fixed objects and using the determined current distances as characteristics for a nonlinear regression; determining the objects which are specific of the side of the road from among the fixed objects in the discrete angle ranges by a threshold value comparison of radar target amplitudes; filtering, with an ordering filter, the object with a shortest distance out of the roadside-specific objects determined in each of the discrete angle ranges over a plurality of consecutive measurement cycles; using the filtered object from said ordering filter to determine the distance between the side of the road and the motor vehicle in each of the discrete angle range; and using the objects determined in the discrete angle ranges as characteristics for an adaptive prediction of a curve type using a curve classifier.
Claim 3
Dependent Claim 43 words
The process in accordance with claim 1 , wherein a model-based Kalman filter, whose model is based on a priori knowledge of dynamics of courses of roads, is used to smoothen said distances between the side of the road and the motor vehicle.
Claim 4
Dependent Claim 56 words
The process in accordance with claim 2 , wherein a correction signal, which is obtained by comparison of a current curve type of the motor vehicle with a curve type which is predicted by the curve classifier and is time-delayed corresponding to the current velocity of the motor vehicle is sent continuously to the curve classifier.
Claim 5
Dependent Claim 18 words
The process in accordance with claim 2 , wherein the curve classifier is formed by a neuronal network.
Claim 6
Dependent Claim 56 words
The process in accordance with claim 1 , wherein a correction signal, which is obtained by comparison of a current curve type of the motor vehicle with a curve type which is predicted by the curve classifier and is time-delayed corresponding to the current velocity of the motor vehicle is sent continuously to the curve classifier.
Claim 7
Dependent Claim 18 words
The process in accordance with claim 5 , wherein the curve classifier is formed by a neuronal network.
Claim 8
Dependent Claim 18 words
The process in accordance with claim 1 , wherein the curve classifier is formed by a neuronal network.
Claim 9
Dependent Claim 25 words
The process in accordance with claim 7 , wherein weights of the neuronal network are preset once by an off-line adaptation based on example situations.
Claim 10
Dependent Claim 35 words
The process in accordance with claim 7 , wherein the weights of the neuronal network, predetermined on a basis of example situations before being put into operation, are corrected by the correction signal during operation.

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USPTO Annuity & Maintenance Windows

Annuity Stage Window Opens Payment Deadline Surcharge Period Until Estimated Fee Status
3.5 Years (Year 4) 2004-10-08 2005-04-09 2005-10-09 $2000.00 Window Closed / Lapsed
7.5 Years (Year 8) 2008-10-08 2009-04-09 2009-10-09 $3760.00 Window Closed / Lapsed
11.5 Years (Year 12) 2012-10-08 2013-04-09 2013-10-09 $7700.00 Window Closed / Lapsed

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