Method and device of determining kinematics of a target

1. A method of determining kinematics of a target in relation to an ego vehicle, the method comprising:

selecting the target detected in a predetermined sensing zone;

generating a trace of the target based on position, heading, speed, and acceleration of the target;

predicting a curve the target is taking and calculating a radius of the curve using the generated trace;

projecting n paths created as abstract movement functions of a polynomial degree p depending on the calculated radius, in response to the trace having at least 2p−1 historical points;

at each further cycle, adding higher probabilities to paths projected in a previous measuring cycle which are equal with the newly projected ones and keeping the projected paths, if the radius remains the same as in the previous measuring cycle;

computing predicted kinematics values by utilizing a smoothing filter with current kinematics values;

comparing the predicted kinematics values with the kinematics values derived from the projected paths; and

determining final kinematics values based on the comparison of predicted kinematics values with the kinematics values derived from the projected paths;

wherein determining the final kinematics values comprises if the standard deviation of the kinematics values associated to the projected paths is close to the standard deviation of the kinematics values associated to the predicted paths, then the kinematic parameters are those associated to the projected paths, otherwise use the kinematics values associated to the predicted paths.

2. The method according to claim 1 , further comprising defining the abstract movement functions as Markov-chain matrices.

3. The method according to claim 1 , wherein the radius of the curve taken by target is obtained by polynomial regression using the generated trace.

4. The method according to claim 1 , wherein the smoothing filter used to compute the kinematics values associated to predicted paths is a Kalman filter.

5. The method according to claim 1 , wherein the smoothing filter used to compute the kinematics values associated to predicted paths is a low-pass filter.

6. A device for determining a kinematic of a target, comprising:

an interface adapted to receive sensor data related to the target, as well as ego vehicle kinematics data such as heading, position, speed and acceleration of the target;

an evaluation unit adapted to

predict a curve the target is taking and calculate a radius of the curve using the generated trace,

project n target paths expressed as abstract movement functions of a polynomial degree p depending on the calculated radius, after having a trace of at least 2p−1 historical points; at each further cycle, to add higher probabilities to the paths projected in a previous measuring cycle which are equal with the newly projected ones and to keep the projected paths, if the radius remains the same as in the previous measuring cycle,

compute current kinematics values using a smoothing algorithm, as predicted kinematics values,

compare the predicted kinematics values with the kinematics values resulted from the projected paths, and

determine final kinematics values;

wherein determining the final kinematics values comprises if the standard deviation of the kinematics values associated to the projected paths is close to the standard deviation of the kinematics values associated to the predicted paths, then the kinematic parameters are those associated to the projected paths, otherwise use the kinematics values associated to the predicted paths.

7. The device according to claim 6 , wherein the evaluation unit is adapted to define the abstract movement functions as Markov-chain matrices.

8. The device according to claim 7 , wherein the evaluation unit is adapted to output the determined kinematics data to a driving assistance system, as to assist functions including at least one of blind spot detection, lane change support, front traffic cross alert, and rear traffic cross alert.

9. A vehicle comprising:

a sensor system adapted to provide sensor data of surroundings of the vehicle;

a device for determining a kinematic of a target including

an interface adapted to receive sensor data related to the target, as well as ego vehicle kinematics data such as heading, position, speed, and acceleration of the target;

an evaluation unit adapted to

predict a curve the target is taking and calculate a radius of the curve using the generated trace,

project n target paths expressed as abstract movement functions of a polynomial degree p depending on the calculated radius, after having a trace of at least 2p−1 historical points; at each further cycle, to add higher probabilities to the paths projected in a previous measuring cycle which are equal with the newly projected ones and to keep the projected paths, if the radius remains the same as in the previous measuring cycle,

compute current kinematics values using a smoothing algorithm, as predicted kinematics values,

compare the predicted kinematics values with the kinematics values resulted from the projected paths, and

determine final kinematics values;

wherein determining the final kinematics values comprises if the standard deviation of the kinematics values associated to the projected paths is close to the standard deviation of the kinematics values associated to the predicted paths, then the kinematic parameters are those associated to the projected paths, otherwise use the kinematics values associated to the predicted paths; and

a driving assistance system configured to receive signals from the device.