Ascertaining a trajectory for a first vehicle while taking into consideration the drive behavior of a second vehicle

1. A processor unit ( 3 ) for determining a trajectory for a first vehicle ( 1 ) under consideration of driving behavior of a second vehicle ( 18 ), wherein the second vehicle ( 18 ) is traveling ahead of the first vehicle ( 1 ), the processor unit ( 3 ) configured for:

accessing speed data of the second vehicle ( 18 ), the speed data generated by a sensor ( 24 ) of the first vehicle ( 1 ) the speed data including a temporal progression of actual speeds of the second vehicle ( 18 ) determined by the sensor ( 24 ) of the first vehicle ( 1 );

accessing a first speed limit value that applies for a first route section ( 22 ) on which the second vehicle ( 18 ) is traveling;

accessing a second speed limit value that applies for a second route section ( 23 ) on which the second vehicle ( 18 ) will travel in the future;

generating, from the temporal sequence of the actual speed of the second vehicle ( 18 ), a function with respect to time of a relative speed deviation of the actual speed of the second vehicle ( 18 ) from the first speed limit value;

determining a mean relative speed deviation from the function with respect to time of the relative speed deviation;

creating a driving behavior profile of the second vehicle ( 18 ) based on the speed data and the mean relative speed deviation;

making a prediction about future driving behavior of the second vehicle ( 18 ) based on the driving behavior profile of the second vehicle ( 18 ) in that a future speed of the second vehicle ( 18 ) on the second route section ( 23 ) is determined as a function of the mean relative speed deviation and the second speed limit value; and

determining a trajectory for the first vehicle ( 1 ) by executing an MPC algorithm ( 13 ), which includes a longitudinal dynamic model ( 14 ) of the first vehicle ( 1 ) and a cost function ( 15 ), such that the cost function ( 15 ) is minimized, wherein the prediction about the future driving behavior of the second vehicle ( 18 ) is taken into account as a constraint in the determination of the trajectory.

2. The processor unit ( 3 ) of claim 1 , wherein the processor unit ( 3 ) is configured for:

chronologically storing discrete-time relative speed deviations of the actual speed of the second vehicle ( 18 ) from the first speed limit value in a data set for an established time period; and

from the chronologically stored, discrete-time relative speed deviations, generating the function with respect to time of the relative speed deviation of the actual speed of the second vehicle ( 18 ) from the first speed limit value.

3. The processor unit ( 3 ) of claim 1 , wherein the processor unit ( 3 ) is configured for:

determining a mean acceleration of the second vehicle ( 18 ) from the first derivative of the function with respect to time of the speed deviation with respect to time;

creating the driving behavior profile of the second vehicle ( 18 ) based on the mean acceleration of the second vehicle ( 18 ); and

making the prediction about the future driving behavior of the second vehicle ( 18 ) based on the driving behavior profile of the second vehicle ( 18 ) in that a future acceleration of the second vehicle ( 18 ) on the first route section ( 22 ) is determined as a function of the mean acceleration, the mean relative speed deviation, and the second speed limit value.

4. The processor unit ( 3 ) of claim 3 , wherein the processor unit ( 3 ) is configured for:

determining a mean jerk of the second vehicle ( 18 ) from the second derivative of the function with respect to time of the speed deviation with respect to time;

creating the driving behavior profile of the second vehicle ( 18 ) based on the mean jerk of the second vehicle ( 18 ); and

making the prediction about the future driving behavior of the second vehicle ( 18 ) based on the driving behavior profile of the second vehicle ( 18 ), in that a future jerk of the second vehicle ( 18 ) on the first route section ( 22 ) is determined as a function of the mean jerk, the mean acceleration, the mean relative speed deviation, and the second speed limit value.

5. The processor unit ( 3 ) of claim 3 , wherein the processor unit ( 3 ) is configured for

determining a maximum acceleration of the second vehicle ( 18 ) from the first derivative of the function with respect to time of the speed deviation with respect to time;

determining a maximum jerk of the second vehicle ( 18 ) from the second derivative of the function with respect to time of the speed deviation with respect to time;

creating the driving behavior profile of the second vehicle ( 18 ) based on the maximum acceleration and based on the maximum jerk of the second vehicle ( 18 ); and

making the prediction about the future driving behavior of the second vehicle ( 18 ) based on the driving behavior profile of the second vehicle ( 18 ) in that an emergency brake application of the second vehicle ( 18 ) is detected as a function of the maximum acceleration and the maximum jerk.

6. The processor unit ( 3 ) of claim 1 , wherein the processor unit ( 3 ) is configured for making a prediction about the future driving behavior of the second vehicle ( 18 ) for each execution of the MPC algorithm ( 13 ) to determine the trajectory for the first vehicle ( 1 ).

7. A driver assistance system ( 16 ) for carrying out a driver assistance function of a first vehicle ( 1 ) under consideration of driving behavior of a second vehicle ( 18 ) traveling ahead of the first vehicle ( 1 ), the driver assistance system ( 16 ) configured for:

accessing a trajectory for the first vehicle ( 1 ) determined by the processor unit ( 3 ) of claim 1 ; and

carrying out a driver assistance function of the first vehicle ( 1 ) by utilizing the trajectory for the first vehicle ( 1 ).

8. A first vehicle ( 1 ), comprising:

a sensor ( 24 ) configured for generating speed data of a second vehicle ( 18 ) traveling ahead of the first vehicle ( 1 );

the processor unit ( 3 ) of claim 1 ; and

a driver assistance system ( 16 ) for carrying out a driver assistance function of the first vehicle ( 1 ) under consideration of driving behavior of the second vehicle ( 18 ) traveling ahead of the first vehicle ( 1 ), the driver assistance system ( 16 ) configured for accessing a trajectory for the first vehicle ( 1 ) determined by the processor unit ( 3 ) and for carrying out a driver assistance function of the first vehicle ( 1 ) by utilizing the trajectory for the first vehicle ( 1 ).

9. A method for determining a trajectory for a first vehicle ( 1 ) under consideration of the driving behavior of a second vehicle ( 18 ) traveling ahead of the first vehicle ( 1 ), the method comprising:

generating speed data of the second vehicle ( 18 ), the speed data comprising a temporal sequence of actual speeds of the second vehicle ( 18 ) determined by the sensor ( 24 ) of the first vehicle ( 1 );

accessing a first speed limit value that applies for a first route section ( 22 ) on which the second vehicle ( 18 ) is traveling;

accessing a second speed limit value that applies for a second route section ( 23 ) on which the second vehicle ( 18 ) will travel in the future;

generating a function with respect to time of a relative speed deviation of the actual speed of the second vehicle ( 18 ) from the first speed limit value from the temporal sequence of the actual speed of the second vehicle ( 18 );

determining a mean relative speed deviation from the function with respect to time of the relative speed deviation;

creating a driving behavior profile of the second vehicle ( 18 ) based on the speed data and the mean relative speed deviation;

making a prediction about the future driving behavior of the second vehicle ( 18 ) based on the driving behavior profile of the second vehicle ( 18 ) in that a future speed of the second vehicle ( 18 ) on the second route section ( 23 ) is determined as a function of the mean relative speed deviation and the second speed limit value; and

determining a trajectory for the first vehicle ( 1 ) by executing an MPC algorithm ( 13 ), which includes a longitudinal dynamic model ( 14 ) of the first vehicle ( 1 ) and a cost function ( 15 ), such that the cost function ( 15 ) is minimized, wherein the prediction about the future driving behavior of the second vehicle ( 18 ) is taken into account as a constraint in the determination of the trajectory.

10. A computer program product ( 11 ) for determining a trajectory for a first vehicle ( 1 ) under consideration of the driving behavior of a second vehicle ( 18 ) traveling ahead of the first vehicle ( 1 ), wherein the computer program product ( 11 ), when run on a processor unit ( 3 ), instructs the processor unit ( 3 ) to:

access speed data of the second vehicle ( 18 ), the speed data generated by a sensor ( 24 ) of the first vehicle ( 1 ), the speed data comprising a temporal sequence of actual speeds of the second vehicle ( 18 ) determined by the sensor ( 24 ) of the first vehicle ( 1 );

access a first speed limit value that applies for a first route section ( 22 ) on which the second vehicle ( 18 ) is traveling;

access a second speed limit value that applies for a second route section ( 23 ) on which the second vehicle ( 18 ) will travel in the future;

generate, from the temporal sequence of the actual speed of the second vehicle ( 18 ), a function with respect to time of a relative speed deviation of the actual speed of the second vehicle ( 18 ) from the first speed limit value;

determine a mean relative speed deviation from the function with respect to time of the relative speed deviation;

create a driving behavior profile of the second vehicle ( 18 ) based on the speed data and the mean relative speed deviation;

make a prediction about the future driving behavior of the second vehicle ( 18 ) based on the driving behavior profile of the second vehicle ( 18 ) in that a future speed of the second vehicle ( 18 ) on the second route section ( 23 ) is determined as a function of the mean relative speed deviation and the second speed limit value; and

determine a trajectory for the first vehicle ( 1 ) by executing an MPC algorithm ( 13 ), which includes a longitudinal dynamic model ( 14 ) of the first vehicle ( 1 ) and a cost function ( 15 ) to be minimized, such that the cost function ( 15 ) is minimized, wherein the prediction about the future driving behavior of the second vehicle ( 18 ) is taken into account as a constraint in the determination of the trajectory.