Predictive turning assistant

1. A method for assisting in turning a vehicle, the method comprises:

detecting or estimating that the vehicle is about to turn to a certain direction or is turning to the certain direction;

sensing a relevant portion of an environment of the vehicle to provide sensed information, wherein the relevant portion of the environment is positioned at a side of the vehicle that corresponds with the certain direction;

applying an artificial intelligence process on the sensed information to (i) detect objects within the relevant portion of the environment and (ii) estimate expected movement patterns of the objects within a time frame that ends with an expected completion of the turn of the vehicle;

determining, given an expected trajectory of the vehicle during the turn and the expected movement patterns of the objects, whether at least one of the objects is expected to cross the trajectory of the vehicle during the turn; and

responding to an outcome of the determining;

wherein the vehicle is autonomously driven over a predefined path that comprises the turn,

wherein the estimating occurs a predefined period before the turn,

wherein the responding comprises recalculating the predefined path of the autonomous vehicle and skipping the turn when determining that the at least one of the objects is expected to cross the trajectory of the vehicle during the turn.

2. The method according to claim 1 wherein the responding comprises calculating a risk associated with altering a movement of the vehicle without skipping the turn.

3. The method according to claim 1 , wherein the responding comprising alerting a driver of the vehicle.

4. The method according to claim 1 , wherein the detecting of the objects comprises generating sensed information signatures and searching for similar signatures that belong to reference cluster structures, wherein each reference cluster structure comprises reference signatures and metadata related to the reference signatures.

5. The method according to claim 4 wherein the finding of the similar signatures is followed by retrieving reference temporal signatures of the objects, and estimating the expected movement patterns of the objects based on the reference temporal signatures of the objects.

6. The method according to claim 1 wherein the estimating of the expected movement patterns of the objects is based on actual movements of the objects represented by the sensed information.

7. A non-transitory computer readable medium that stores instructions for:

detecting or estimating that a vehicle is about to turn to a certain direction or is turning to the certain direction;

sensing a relevant portion of an environment of the vehicle to provide sensed information, wherein the relevant portion of the environment is positioned at a side of the vehicle that corresponds with the certain direction;

applying an artificial intelligence process on the sensed information to (i) detect objects within the relevant portion of the environment and (ii) estimate expected movement patterns of the objects within a time frame that ends with an expected completion of the turn of the vehicle;

determining, given an expected trajectory of the vehicle during the turn and the expected movement patterns of the objects, whether at least one of the objects is expected to cross the trajectory of the vehicle during the turn; and

responding to an outcome of the determining;

wherein the vehicle is autonomously driven over a predefined path that comprises the turn,

wherein the estimating occurs a predefined period before the turn,

wherein the responding comprises recalculating the predefined path of the autonomous vehicle and skipping the turn when determining that the at least one of the objects is expected to cross the trajectory of the vehicle during the turn.

8. The non-transitory computer readable medium according to claim 7 , wherein the responding comprises calculating a risk associated with altering a movement of the vehicle without skipping the turn.

9. The non-transitory computer readable medium according to claim 7 , wherein the responding comprising alerting a driver of the vehicle.

10. The non-transitory computer readable medium according to claim 7 , wherein the detecting of the objects comprises generating sensed information signatures and searching for similar signatures that belong to reference cluster structures, wherein each reference cluster structure comprises reference signatures and metadata related to the reference signatures.

11. The non-transitory computer readable medium according to claim 10 , wherein the finding of the similar signatures is followed by retrieving reference temporal signatures of the objects, and estimating the expected movement patterns of the objects based on the reference temporal signatures of the objects.

12. The non-transitory computer readable medium according to claim 7 , wherein the estimating of the expected movement patterns of the objects is based on actual movements of the objects represented by the sensed information.

13. A computerized vehicle system that comprises a processor,

at least one sensor and a memory unit;

wherein the memory unit stores instructions executable by the processor;

wherein the processor is configured to detect or estimate that a vehicle is about to turn to a certain direction or is turning to the certain direction;

wherein the at least one sensor is configured to sense a relevant portion of an environment of the vehicle to provide sensed information, wherein the relevant portion of the environment is positioned at a side of the vehicle that corresponds with the certain direction;

wherein the processor is configured to apply an artificial intelligence process on the sensed information to (i) detect objects within the relevant portion of the environment and (ii) estimate expected movement patterns of the objects within a time frame that ends with an expected completion of the turn of the vehicle;

determine, given an expected trajectory of the vehicle during the turn and the expected movement patterns of the objects, whether at least one of the objects is expected to cross the trajectory of the vehicle during the turn; and

wherein the computerized vehicle system is configured to respond to an outcome of the determining;

wherein the vehicle is autonomously driven over a predefined path that comprises the turn,

wherein the processor is configured to perform the estimate a predefined period before the turn,

wherein the computerized vehicle system is configured to respond by recalculating the predefined path of the autonomous vehicle and skip the turn when the processor determines that the at least one of the objects is expected to cross the trajectory of the vehicle during the turn.

14. The computerized vehicle system according to claim 13 wherein the processor is configured to calculate a risk associated with altering a movement of the vehicle without skipping the turn.

15. The computerized vehicle system according to claim 13 comprising a communication unit that is configured to alert a driver of the vehicle.

16. The computerized vehicle system according to claim 13 wherein the processor is configured to detect the objects by generating sensed information signatures and searching for similar signatures that belong to reference cluster structures, wherein each reference cluster structure comprises reference signatures and metadata related to the reference signatures.

17. The computerized vehicle system according to claim 13 wherein the processor is configured to, following the finding of the similar signatures, retrieve reference temporal signatures of the objects, and estimate the expected movement patterns of the objects based on the reference temporal signatures of the objects.