Method for detecting and characterizing a driving behavior of a driver or an autopilot in a transportation vehicle, control unit and transportation vehicle
A method for detecting and characterizing a driving behavior of a driver or an autopilot in a transportation vehicle which has at least one acceleration sensor used to record data points which indicate a lateral acceleration and a longitudinal acceleration of the transportation vehicle over a time interval, and a control unit used to generate an image space as a GG diagram from the data points of at least one sub-section of the time interval. The image space is transformed by the control unit by a transformation into a parameter space and coordinates of accumulation points in the parameter space are acquired by the control unit. From the coordinates of the accumulation points, by using a classification algorithm, the control unit determines a classification value and/or a classification profile relating to the driving behavior.
1. A control unit comprising:
a processor; and
a program having a program code for carrying out a method for detecting and characterizing a driving behavior of a driver or an autopilot in a transportation vehicle when the program code is executed on the processor, the method comprising:
generating an image space as a GG diagram from data points of at least one subsection of a time interval, wherein the data points are recorded by at least one acceleration sensor and indicate a lateral acceleration and a longitudinal acceleration of the transportation vehicle over the time interval;
transforming the image space by a transformation into a parameter space, wherein the transformation is a Hough transform or a Radon transform;
acquiring coordinates of accumulation points in the parameter space; and
determining a classification value and/or a classification profile relating to the driving behavior using a classification algorithm based on the coordinates of the accumulation points.
2. The control unit of claim 1 , wherein the coordinates of the parameter space are parameters of a straight line.
3. The control unit of claim 1 , wherein the coordinates of the parameter space are coordinates of a center of a circle and a radius of a circle.
4. The control unit of claim 1 , further comprising smoothing and/or filtering the values of the lateral acceleration and the values of the longitudinal acceleration of at least one sub-section of the time interval by the control unit.
5. The control unit of claim 1 , further comprising transmitting the classification value and/or the classification profile to a driver assistance system and/or an external central computer.
6. The control unit of claim 1 , wherein the at least one sub-section of the time interval is determined by the control unit as a function of predefined geographical data and/or on values of the lateral acceleration and/or longitudinal acceleration.
7. The control unit of claim 1 , wherein the classification algorithm comprises a support vector machine and/or an artificial neural network.
8. A transportation vehicle comprising:
a control unit that includes a processor and a program having a program code for carrying out a method for detecting and characterizing a driving behavior of a driver or an autopilot in a transportation vehicle when the program code is executed on the processor, the method comprising:
generating an image space as a GG diagram from data points of at least one subsection of a time interval, wherein the data points are recorded by at least one acceleration sensor and indicate a lateral acceleration and a longitudinal acceleration of the transportation vehicle over the time interval;
transforming the image space by a transformation into a parameter space, wherein the transformation is a Hough transform or a Radon transform;
acquiring coordinates of accumulation points in the parameter space; and
determining a classification value and/or a classification profile relating to the driving behavior using a classification algorithm based on the coordinates of the accumulation points.
9. The transportation vehicle of claim 8 , wherein the coordinates of the parameter space are parameters of a straight line.
10. The transportation vehicle of claim 8 , wherein the coordinates of the parameter space are coordinates of a center of a circle and a radius of a circle.
11. The transportation vehicle of claim 8 , further comprising smoothing and/or filtering the values of the lateral acceleration and the values of the longitudinal acceleration of at least one sub-section of the time interval by the control unit.
12. The transportation vehicle of claim 8 , further comprising transmitting the classification value and/or the classification profile to a driver assistance system and/or an external central computer.
13. The transportation vehicle of claim 8 , wherein the at least one sub-section of the time interval is determined by the control unit as a function of predefined geographical data and/or on values of the lateral acceleration and/or longitudinal acceleration.
14. The transportation vehicle of claim 8 , wherein the classification algorithm comprises a support vector machine and/or an artificial neural network.
15. A method for detecting and characterizing a driving behavior of a driver or an autopilot in a transportation vehicle, the method comprising:
recording data points by at least one acceleration sensor, wherein the data points indicate a lateral acceleration and a longitudinal acceleration of the transportation vehicle over a time interval;
generating an image space, by a control unit, as a GG diagram from the data points of at least one sub-section of the time interval;
transforming the image space, by the control unit, by a transformation into a parameter space, wherein the transformation is a Hough transform or a Radon transform; and
acquiring coordinates of accumulation points in the parameter space by the control unit, wherein the control unit determines a classification value and/or a classification profile relating to the driving behavior by a classification algorithm from the coordinates of the accumulation points.
16. The method of claim 15 , wherein the coordinates of the parameter space are parameters of a straight line.
17. The method of claim 15 , wherein the coordinates of the parameter space are coordinates of a center of a circle and a radius of a circle.
18. The method of claim 15 , further comprising smoothing and/or filtering the values of the lateral acceleration and the values of the longitudinal acceleration of at least one subsection of the time interval by the control unit.
19. The method of claim 15 , further comprising transmitting the classification value and/or the classification profile to a driver assistance system and/or an external central computer.
20. The method of claim 15 , wherein the at least one sub-section of the time interval is determined by the control unit as a function of predefined geographical data and/or on values of the lateral acceleration and/or longitudinal acceleration.
21. The method of claim 15 , wherein the classification algorithm comprises a support vector machine and/or an artificial neural network.