Method of and system for generating trajectory for self-driving car (SDC)

1. A method for generating a trajectory for a self-driving car (SDC), the SDC being associated with an electronic device, the method executable by the electronic device, the method comprising:

determining, by the electronic device, a presence of at least one third-party object around the SDC;

determining, by the electronic device, a current third-party object location;

generating, by the electronic device, a plurality of predicted trajectories for the third-party object based on the current third-party object location, at least one of the plurality of trajectories including a maneuver executable, by the third-party object, at a future third-party object location as part of executing the at least one of the plurality of trajectories;

calculating, for the at least one of the plurality of trajectories including the maneuver executable at the future third-party object location, a respective braking profile associated with the third-party object,

the respective braking profile being indicative of a speed adjustment maneuver of the third-party object to enable the third-party object to execute the maneuver at the future third-party object location, and

the respective braking profile including at least one of a maximum associated acceleration value and a maximum associated jerk value of the third-party object when executing the maneuver;

in response to the at least one of the maximum associated acceleration value and the maximum associated jerk value of the respective braking profile being above a respective pre-determined threshold value, eliminating an associated one of the at least one of the plurality of trajectories from future processing;

determining, by the electronic device, an SDC trajectory based on remaining ones of the plurality of predicted trajectories for the third-party object.

2. The method of claim 1 , wherein the third-party object is one of a plurality of third-party objects located in around the SDC.

3. The method of claim 2 , wherein the method is executed for each of the plurality of third-party objects.

4. The method of claim 2 , wherein the method further comprises selecting the third-party object from the plurality of third-party objects and executing the method only for the third-party object.

5. The method of claim 4 , wherein the selecting the third-party object from the plurality of third-party objects comprises applying a selection rule.

6. The method of claim 5 , wherein the selection rule is indicative of a driver associated with the third-party object being likely to be a traffic rules offender.

7. The method of claim 1 , wherein the pre-determined threshold is indicative of the maneuver executable at the future third-party object location being improbable.

8. The method of claim 7 , wherein the maneuver executable at the future third-party object location being improbable is indicative of the maneuver being physically impossible given the braking profile.

9. The method of claim 1 , wherein the pre-determined threshold is determined using a kinematic model.

10. The method of claim 9 , wherein the kinematic model is based on a most abrupt braking profile.

11. The method of claim 9 , wherein the kinematic model is based on at least one of: a minimum braking profile, an average braking profile, and a most abrupt braking profile.

12. The method of claim 1 , wherein the respective pre-determined threshold value for the maximum associated acceleration value is +/−3 m/sec 2 .

13. The method of claim 1 , wherein the third-party object is a dynamic third-party object.

14. The method of claim 1 , wherein the plurality of predicted trajectories for the third-party object based on the current third-party object location is a plurality of maneuvers, by the third-party object, wherein

a given one of the plurality of maneuvers is executable at a respective one of future third-party object locations, and wherein the method is executable for each of the future third-party object locations.

15. An electronic device comprising:

a processor;

a communication interface for communicating with a sensor mounted on a Self-Driving Car (SDC);

the processor being configured to:

determine, by the electronic device, a presence of at least one third-party object around the SDC;

determine a current third-party object location;

generate a plurality of predicted trajectories for the third-party object based on the current third-party object location, at least one of the plurality of trajectories including a maneuver executable, by the third-party object, at a future third-party object location as part of executing the at least one of the plurality of trajectories;

calculate, for the at least one of the plurality of trajectories including the maneuver executable at the future third-party object location, a respective braking profile associated with the third-party object,

the respective braking profile being indicative of a speed adjustment maneuver of the third-party object to enable the third-party object to execute the maneuver at the future third-party object location, and

the respective braking profile including at least one of a maximum associated acceleration value and a maximum associated jerk value of the third-party object when executing the maneuver;

in response to the at least one of the maximum associated acceleration value and the maximum associated jerk value of the respective braking profile being above a respective pre-determined threshold value, eliminate an associated one of the at least one of the plurality of trajectories from future processing;

determine an SDC trajectory based on remaining ones of the plurality of predicted trajectories for the third-party object.

16. The electronic device of claim 15 , wherein the processor is further configured to select the third-party object from a plurality of third-party objects based on a selection rule.

17. The electronic device of claim 15 , wherein the processor, to determine the pre-determined threshold, is further configured to have access to a kinematic model.