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.