Office Action 1: Ex Parte Quayle Action (2024-12-19)

CLAIMS:
CLAIMS What we claim is:

1\. A method comprising:
identifying, by a processor, a maximum distance bound based on one or more objects around a vehicle;
for each of a plurality of candidate trajectories for the vehicle:
determining, by the processor, a velocity from the maximum distance bound at an ending time of the candidate trajectory;
determining, by the processor, an available distance for the candidate trajectory as a function of the determined velocity at the ending time of the candidate trajectory and a comfort deceleration parameter;
determining, by the processor, a target velocity for the candidate trajectory as a function of the available distance for the candidate trajectory, a difference between a distance at the ending time of the candidate trajectory and a distance of the maximum distance bound at the ending time of the candidate trajectory, and the comfort deceleration parameter; and
determining, by the processor, a velocity difference between the target velocity and a final velocity of the candidate trajectory at the ending time of the candidate trajectory;
selecting, by the processor, a first candidate trajectory of the plurality of candidate trajectories based on the velocity difference of the first candidate trajectory and the velocity differences of the other candidate trajectories of the plurality of candidate trajectories; and
operating, by the processor, the vehicle based on the selected first candidate trajectory.

2\. The method of claim 1, further comprising identifying, by the processor, the one or more objects around the vehicle;
generating, by the processor, one or more maximum distance bounds based on the one or more identified objects; and
consolidating the one or more generated maximum distance bounds into the maximum distance bound.

3\. The method of claim 1, wherein identifying the one or more objects comprises identifying, by the processor, one or more static or dynamic objects from images or LiDAR.

4\. The method of claim 1, wherein determining the velocity difference between the target velocity and the final velocity of the candidate trajectory at the ending time comprises:
comparing, by the processor, the target velocity with the determined velocity for the ending time of the candidate trajectory; and
selecting, by the processor, the target velocity responsive to determining the target velocity is lower than the determined velocity for the ending time of the candidate trajectory.

5\. The method of claim 1, wherein the plurality of candidate trajectories comprise minimum jerk trajectories.

6\. The method of claim 1, wherein identifying the one or more objects comprises identifying, by the processor, the one or more objects using one or more of camera system data, LiDAR system data, GNSS data, or IMU system data.

7\. The method of claim 1, wherein determining the target velocity comprises:
determining, by the processor, a total distance as a sum of the available distance for the candidate trajectory and the difference between the distance at the ending time of the candidate trajectory and the distance of the maximum distance bound at the ending time of the candidate trajectory; and
determining, by the processor, the target velocity as a function of the total distance and the comfort deceleration parameter.

8\. The method of claim 7, wherein the comfort deceleration parameter is a first deceleration parameter, and wherein determining the target velocity comprises:
determining, by the processor, a first target velocity as a function of the total distance and the comfort deceleration parameter, and, separately, a second target velocity using a ramp function on the total distance.

9\. The method of claim 8, wherein the determining the target velocity for the candidate trajectory comprises:
selecting, by the processor, the first target velocity as the target velocity for the candidate trajectory responsive to determining the first target velocity is lower than the second target velocity.

10\. The method of claim 1, wherein each of the plurality of candidate trajectories corresponds to a distance of the vehicle compared to an initial position of the vehicle when performing the method over time.

11\. The method of claim 1, comprising:
retrieving, by the processor, the plurality of candidate trajectories from memory by sampling, by the processor, trajectory velocities and durations for a defined range and step of time.

12\. A system comprising:
memory; and
one or more processors, wherein the one or more processors are configured to:
identify a maximum distance bound based on one or more objects around a vehicle;
for each of a plurality of candidate trajectories for the vehicle:
determining a velocity from the maximum distance bound at an ending time of the candidate trajectory;
determining an available distance for the candidate trajectory as a function of the determined velocity at the ending time of the candidate trajectory and a comfort deceleration parameter;
determining a target velocity for the candidate trajectory as a function of the available distance for the candidate trajectory, a difference between a distance at the ending time of the candidate trajectory and a distance of the maximum distance bound at the ending time of the candidate trajectory, and the comfort deceleration parameter; and
determining a velocity difference between the target velocity and a final velocity of the candidate trajectory at the ending time of the candidate trajectory; selecting a first candidate trajectory of the plurality of candidate trajectories based on the velocity difference of the first candidate trajectory and the velocity differences of the other candidate trajectories of the plurality of candidate trajectories; and
operating the vehicle based on the selected first candidate trajectory.

13\. The system of claim 12, wherein the one or more processors are further configured to:
identify the one or more objects around the vehicle;
generate one or more maximum distance bounds based on the one or more identified objects; and
consolidate the one or more generated maximum distance bounds into the maximum distance bound.

14\. The system of claim 12, wherein the one or more processors are configured to identify the one or more objects by identifying one or more static or dynamic objects from images or LiDAR.

15\. The system of claim 12, wherein each of the plurality of candidate trajectories corresponds to a distance of the vehicle compared to an initial position of the vehicle over time.

16\. The system of claim 12, wherein the one or more processors are further configured to:
retrieve the plurality of candidate trajectories from memory by sampling trajectory velocities and durations for a defined range and step of time.

17\. The system of claim 12, wherein the plurality of candidate trajectories comprise minimum jerk trajectories.

18\. A method comprising:
identifying, by a processor, a maximum distance bound based on one or more objects around a vehicle;
for each of a plurality of candidate trajectories for the vehicle:
determining, by the processor, a velocity from the maximum distance bound at an ending time of the candidate trajectory; determining, by the processor, a target velocity for the candidate trajectory based on the determined velocity for the candidate trajectory and a difference between a distance at the ending time of the candidate trajectory and a distance of the maximum distance bound at the ending time of the candidate trajectory; and
determining, by the processor, a velocity difference between the target velocity and a final velocity of the candidate trajectory at the ending time of the candidate trajectory;
selecting, by the processor, a first candidate trajectory of the plurality of candidate trajectories based on the velocity difference of the first candidate trajectory and the velocity differences of the other candidate trajectories of the plurality of candidate trajectories; and
operating, by the processor, the vehicle based on the selected first candidate trajectory.

19\. The method of claim 18, further comprising identifying, by the processor, the one or more objects around the vehicle;
generating, by the processor, one or more maximum distance bounds based on the one or more identified objects; and
consolidating the one or more generated maximum distance bounds into the maximum distance bound.

20\. The method of claim 18, wherein identifying the one or more objects comprises identifying, by the processor, one or more static or dynamic objects from images or LiDAR. 29 30 31 32 33 4889-9567-9311.1

OFFICE ACTION:
DETAILED ACTION
Notice of Pre-AIA  or AIA  Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claims
Claims 1-20 are pending in the application.
Drawings
The drawings are objected to because in Fig. 2, “Object Node” is referred to by 114 (which is found in Fig. 1 labeling “Object Node”, while in Fig.2, “Map Node” is referred to by 204 (different from the label found in Fig. 1, where “Mapping Node” is labeled with 116.  Is there a reason why Mapping Node is labeled with a different label in Fig. 2 than in claim 1?
The drawings are objected to as failing to comply with 37 CFR 1.84(p)(5) because they do not include the following reference sign(s) mentioned in the description:
Fig. 2: the description in [0041] mentions “an object node 202”. 202 is missing from Fig. 2 (see comments above.)
Fig. 6: 612 and 614 are missing. [0057] mentions “a trajectory distance 612” and “a specific duration (or “time” 614).”
Fig. 7a does not show what its description in [0061] states. See comments below.
Corrected drawing sheets in compliance with 37 CFR 1.121(d) are required in reply to the Office action to avoid abandonment of the application. Any amended replacement drawing sheet should include all of the figures appearing on the immediate prior version of the sheet, even if only one figure is being amended. The figure or figure number of an amended drawing should not be labeled as “amended.” If a drawing figure is to be canceled, the appropriate figure must be removed from the replacement sheet, and where necessary, the remaining figures must be renumbered and appropriate changes made to the brief description of the several views of the drawings for consistency. Additional replacement sheets may be necessary to show the renumbering of the remaining figures. Each drawing sheet submitted after the filing date of an application must be labeled in the top margin as either “Replacement Sheet” or “New Sheet” pursuant to 37 CFR 1.121(d). If the changes are not accepted by the examiner, the applicant will be notified and informed of any required corrective action in the next Office action. The objection to the drawings will not be held in abeyance.
Specification
The disclosure is objected to because of the following informalities:
[0041]: as mentioned above, 202 as a label is missing from Fig.2, where the object node is labeled 114.
[0049]:  “…consuming one or more distance and/or velocity bounds.”  Is this really the word wanted here?
[0061]: The situation shown in Fig. 7a does NOT show what is described here.  Note that the dotted line supposedly indicating the second step (determining the target velocity corresponding to the total distance) is not at a distance of 200 meters but something obviously short of it. Nor is “the target velocity is 15 m/s” what is pictured here.
[0066]: “position bound(trajectory end time) can be the position or distance of the maximum distance bound at the end of the candidate trajectory…” should probably be restated as “position bound(trajectory end time) can be the position or distance of the maximum distance bound at the end time of the candidate trajectory;…”
[0066]: “trajectory end position(trajectory end time) can be the position or distance of the vehicle relative to the initial position of the vehicle at the end of the candidate trajectory;…” is confusing because “initial position of the vehicle at the end of the candidate trajectory” makes no sense.  If this phrase has been interpreted correctly, it would be better stated as: “trajectory end position(trajectory end time) can be the position or distance of the vehicle at the end of the candidate trajectory, relative to the initial position of the vehicle;…”
[0066]: “the comfort deceleration parameter can be a or a defined value”; it looks like there is a word missing.
[0068]: “Using the slope of the maximum distance bound and transforming the slope into an available distance…” would seem to have a different interpretation of “available distance” than what is found in earlier paragraphs. Isn’t “available distance” supposed to be the distance necessary for a comfortably decelerating vehicle, starting at the final velocity of the trajectory, to reach zero? (as in [0059].)
[0072]: the second instance of “At step 812,…” should be “At step 814,..”
[0073]: The two mentions of “candidate trajectory” in line 2 should probably be “candidate trajectories”.
[0073]: “…at step 814,…” should be “…at step 816,…”
[0073]: “At step 816, the data processing system…”  should be “At step 818, the data processing system…”
Appropriate correction is required.
Allowable Subject Matter
Claims 1-20 allowed.
The following is an examiner’s statement of reasons for allowance: No applicable prior art was found. The closest art is US 2021/0089036 (Banzhaf) and US 2021/0034072 (Max. et al., hence Max). Banzhaf teaches a method and a device for calculating a trajectory of a vehicle through calculating a number of possible trajectories, but links the beginning and end of each of the trajectories to a fixed starting position and a fixed ending position, rather than the multiple ends of possible trajectories as is done by applicant.  Max teaches how to produce swarm trajectories for a specified lane of a roadway section, where each of the trajectories used in producing the swarm trajectory has different boundaries and constraints, which are taken into account when determining the swarm trajectory.
In particular, the following was not found in either of the above:  the consolidation of maximum distance/velocity bounds in one general maximum distance/velocity bound, then used to compare with a set of trajectories such that the final distance and velocity of a picked trajectory remained within bounds, with the further constraint that the vehicle is able to comfortably come to a stop from the final velocity.
Any comments considered necessary by applicant must be submitted no later than the payment of the issue fee and, to avoid processing delays, should preferably accompany the issue fee.  Such submissions should be clearly labeled “Comments on Statement of Reasons for Allowance.”
Conclusion
This application is in condition for allowance except for the following formal matters:
Correction of the diagrams and specification as outlined above.
Prosecution on the merits is closed in accordance with the practice under Ex parte Quayle, 25 USPQ 74, 453 O.G. 213, (Comm’r Pat. 1935).
A shortened statutory period for reply to this action is set to expire TWO (2) MONTHS from the mailing date of this letter. Extensions of time may be granted under  37 CFR 1.136 but in no case can any extension carry the date for reply to this Office action beyond the maximum period of SIX MONTHS set by statute (35 U.S.C. 133).


NEXT OFFICE ACTION: NOTICE OF ALLOWABILITY
Notice of Pre-AIA  or AIA  Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Allowable Subject Matter
Claims 1-20 allowed.
The following is an examiner’s statement of reasons for allowance: No applicable prior art was found.  In particular, the following was not found:  the consolidation of maximum distance/velocity bounds in one general maximum distance/velocity bound, then used to compare with a set of trajectories such that the final distance and velocity of a picked trajectory remained within bounds, with the further constraint that the vehicle is able to comfortably come to a stop from the final velocity. (This is the same explanation as was provided in the Quayle Action mailed 12/19/2024.)
Any comments considered necessary by applicant must be submitted no later than the payment of the issue fee and, to avoid processing delays, should preferably accompany the issue fee.  Such submissions should be clearly labeled “Comments on Statement of Reasons for Allowance.”
Conclusion

CITED REFERENCE SUMMARIES: Ref US20210034071A1: Claims:
A device for checking a calibration of surroundings sensors, wherein the surroundings sensors at least partially detect similar surroundings and each provide mutually time-synchronized sensor data, the device comprising: a control unit; wherein the control unit receives sensor data of the surroundings sensors, detecting periodic features at least for at least one distinguished area in the sensor data of the surroundings sensors belonging to the same surroundings, carrying out a transformation of the sensor data corresponding to the at least one distinguished area to a frequency domain at least for the at least one distinguished area, determining a frequency and/or a phase angle of the periodic features transformed to the frequency domain, and detecting a decalibration of the surroundings sensors based on a comparison of the determined frequencies and/or of the determined phase angles, and providing a result of the check.
wherein the control unit receives sensor data of the surroundings sensors, detecting periodic features at least for at least one distinguished area in the sensor data of the surroundings sensors belonging to the same surroundings, carrying out a transformation of the sensor data corresponding to the at least one distinguished area to a frequency domain at least for the at least one distinguished area, determining a frequency and/or a phase angle of the periodic features transformed to the frequency domain, and detecting a decalibration of the surroundings sensors based on a comparison of the determined frequencies and/or of the determined phase angles, and providing a result of the check.
The device of claim 1 , wherein the control unit further detects a decalibration in response to a frequency difference between the determined frequencies exceeding a predefined frequency threshold value and/or a phase difference between the determined phase angles exceeding a predefined phase threshold value.
The device of claim 1 , wherein the control unit further projects the sensor data of the surroundings sensors into an image space onto a velocity vector corresponding to a speed, and carries out the transformation to the frequency domain based on the projected sensor data.
The device of claim 1 , wherein the control unit further initiates the method of claim 6 when periodic features at least in the at least one distinguished area are detected in the sensor data) at least of one of the surroundings sensors.
A transportation vehicle, comprising: surroundings sensors; and at least one device according to claim 1 .
surroundings sensors; and
at least one device according to claim 1 .
A method for checking a calibration of surroundings sensors, wherein the surroundings sensors at least partially detect similar surroundings and each provide mutually time-synchronized sensor data; wherein periodic features at least for at least one distinguished area are detected in the sensor data of the surroundings sensors belonging to the same surroundings; wherein a transformation of the sensor data corresponding to the at least one distinguished area to a frequency domain is carried out at least for the at least one distinguished area; wherein a frequency and/or a phase angle of the periodic features is determined in the sensor data transformed to the frequency domain; wherein a decalibration of the surroundings sensors is detected based on a comparison of the determined frequencies and/or of the determined phase angles; and wherein a result of the check is provided.
wherein the surroundings sensors at least partially detect similar surroundings and each provide mutually time-synchronized sensor data;
wherein periodic features at least for at least one distinguished area are detected in the sensor data of the surroundings sensors belonging to the same surroundings;
wherein a transformation of the sensor data corresponding to the at least one distinguished area to a frequency domain is carried out at least for the at least one distinguished area;
wherein a frequency and/or a phase angle of the periodic features is determined in the sensor data transformed to the frequency domain;
wherein a decalibration of the surroundings sensors is detected based on a comparison of the determined frequencies and/or of the determined phase angles; and
wherein a result of the check is provided.
The method of claim 6 , wherein a decalibration is detected when a frequency difference between the determined frequencies exceeds a predefined frequency threshold value and/or when a phase difference between the determined phase angles exceeds a predefined phase threshold value.
The method of claim 6 , wherein the sensor data of the surroundings sensors are projected into an image space onto a velocity vector corresponding to a speed, wherein the transformation to the frequency domain takes place based on the projected sensor data.
The method of claim 6 , wherein the method begins when periodic features at least in the at least one distinguished area are detected in the sensor data of at least of one of the surroundings sensors.
The method of claim 6 , wherein at least one of the surroundings sensors is a camera, wherein the camera provides camera images as sensor data, and wherein a semantic segmentation of the camera images takes place, wherein the at least one distinguished area is recognized and detected based on the semantic segmentation.
Ref US20210089036A1: Claims:
- 10 . (canceled)
A method for calculating a trajectory of a vehicle, the method comprising: determining a starting position and a target position of the vehicle; generating a number of possible trajectories, which precisely interconnect the starting position and the target position; interlinking, for each possible trajectory, different path elements in different ways, to interconnect the starting position and the target position of the vehicle, wherein the path elements being interlinked so that a possible trajectory only has a discontinuous curvature characteristic at a node between two path elements, if the possible trajectory traces a change of direction at the node; and selecting a trajectory from the possible trajectories based on a characteristic of the possible trajectories.
determining a starting position and a target position of the vehicle;
generating a number of possible trajectories, which precisely interconnect the starting position and the target position;
interlinking, for each possible trajectory, different path elements in different ways, to interconnect the starting position and the target position of the vehicle, wherein the path elements being interlinked so that a possible trajectory only has a discontinuous curvature characteristic at a node between two path elements, if the possible trajectory traces a change of direction at the node; and
selecting a trajectory from the possible trajectories based on a characteristic of the possible trajectories.
The method of claim 11 , wherein the number of possible trajectories is generated by combining the different path elements with each other in different ways.
The method of claim 12 , wherein each of the possible trajectories is a predefined combination of the different path elements.
The method of claim 11 , wherein the different path elements include a curve element, and during the generation of the number of possible trajectories, the curve element is selected from one of the following: (i) an RS curve element, which describes a curve having a constant curve radius; (ii) an HC curve element, which is a combination of a curve having a constant radius and a curve having a radius increasing or decreasing over a stretch of path, with the characteristic of a minimum radius on the one side and an infinitely large radius on the other side; and (iii) a CC curve element, which is a combination of a curve having a constant radius and, in front of it or in back of it, in each instance, a curve having a radius increasing or decreasing over a stretch of path.
(i) an RS curve element, which describes a curve having a constant curve radius;
(ii) an HC curve element, which is a combination of a curve having a constant radius and a curve having a radius increasing or decreasing over a stretch of path, with the characteristic of a minimum radius on the one side and an infinitely large radius on the other side; and
(iii) a CC curve element, which is a combination of a curve having a constant radius and, in front of it or in back of it, in each instance, a curve having a radius increasing or decreasing over a stretch of path.
The method of claim 11 , wherein the different path elements include a curve element and a straight-line element.
The method of claim 11 , wherein in the selection of a trajectory from the possible trajectories, a length of the possible trajectories and/or a minimum number of changes in direction of the trajectories and/or a minimum change in curvature is the characteristic of the possible trajectories, on which the selection is based.
The method of claim 11 , wherein the path elements are interlinked in such a manner, that a possible trajectory always has a continuous curvature characteristic at a node between two path elements, if the possible trajectory describes a motion of the vehicle at the node, in an unchanging direction.
The method of claim 11 , wherein each of the path elements has a starting point and an end point; the path elements being adapted for use within a possible trajectory by shifting the starting point and the end point relative to each other.
The method of claim 11 , wherein apart from the starting position and the target position of the vehicle, at least one intermediate target position is defined.
A device for calculating a trajectory of a vehicle, comprising: a processing unit configured to perform the following: defining a starting position and a target position of the vehicle; generating a number of possible trajectories, which precisely interconnect the starting position and the target position; interlinking, for each possible trajectory, different path elements in different ways, to interconnect the starting position and the target position of the vehicle, wherein the path elements are interlinked so that a possible trajectory only has a discontinuous curvature characteristic at a node between two path elements, if the possible trajectory traces a change of direction at the node; and selecting a trajectory from the possible trajectories based on a characteristic of the possible trajectories.
a processing unit configured to perform the following: defining a starting position and a target position of the vehicle; generating a number of possible trajectories, which precisely interconnect the starting position and the target position; interlinking, for each possible trajectory, different path elements in different ways, to interconnect the starting position and the target position of the vehicle, wherein the path elements are interlinked so that a possible trajectory only has a discontinuous curvature characteristic at a node between two path elements, if the possible trajectory traces a change of direction at the node; and selecting a trajectory from the possible trajectories based on a characteristic of the possible trajectories.
defining a starting position and a target position of the vehicle;
interlinking, for each possible trajectory, different path elements in different ways, to interconnect the starting position and the target position of the vehicle, wherein the path elements are interlinked so that a possible trajectory only has a discontinuous curvature characteristic at a node between two path elements, if the possible trajectory traces a change of direction at the node; and
Ref US20210089036: Claims:
1-10. (canceled)
11. A method for calculating a trajectory of a vehicle, the method comprising:
determining a starting position and a target position of the vehicle; generating a number of possible trajectories, which precisely interconnect the starting position and the target position; interlinking, for each possible trajectory, different path elements in different ways, to interconnect the starting position and the target position of the vehicle, wherein the path elements being interlinked so that a possible trajectory only has a discontinuous curvature characteristic at a node between two path elements, if the possible trajectory traces a change of direction at the node; and selecting a trajectory from the possible trajectories based on a characteristic of the possible trajectories.
12. The method of claim 11, wherein the number of possible trajectories is generated by combining the different path elements with each other in different ways.
13. The method of claim 12, wherein each of the possible trajectories is a predefined combination of the different path elements.
14. The method of claim 11, wherein the different path elements include a curve element, and during the generation of the number of possible trajectories, the curve element is selected from one of the following:
(i) an RS curve element, which describes a curve having a constant curve radius; (ii) an HC curve element, which is a combination of a curve having a constant radius and a curve having a radius increasing or decreasing over a stretch of path, with the characteristic of a minimum radius on the one side and an infinitely large radius on the other side; and (iii) a CC curve element, which is a combination of a curve having a constant radius and, in front of it or in back of it, in each instance, a curve having a radius increasing or decreasing over a stretch of path.
15. The method of claim 11, wherein the different path elements include a curve element and a straight-line element.
16. The method of claim 11, wherein in the selection of a trajectory from the possible trajectories, a length of the possible trajectories and/or a minimum number of changes in direction of the trajectories and/or a minimum change in curvature is the characteristic of the possible trajectories, on which the selection is based.
17. The method of claim 11, wherein the path elements are interlinked in such a manner, that a possible trajectory always has a continuous curvature characteristic at a node between two path elements, if the possible trajectory describes a motion of the vehicle at the node, in an unchanging direction.
18. The method of claim 11, wherein each of the path elements has a starting point and an end point; the path elements being adapted for use within a possible trajectory by shifting the starting point and the end point relative to each other.
19. The method of claim 11, wherein apart from the starting position and the target position of the vehicle, at least one intermediate target position is defined.
20. A device for calculating a trajectory of a vehicle, comprising:
a processing unit configured to perform the following:
defining a starting position and a target position of the vehicle;
generating a number of possible trajectories, which precisely interconnect the starting position and the target position;
interlinking, for each possible trajectory, different path elements in different ways, to interconnect the starting position and the target position of the vehicle, wherein the path elements are interlinked so that a possible trajectory only has a discontinuous curvature characteristic at a node between two path elements, if the possible trajectory traces a change of direction at the node; and
selecting a trajectory from the possible trajectories based on a characteristic of the possible trajectories.
Ref US20210034072: Claims:
1-10. (canceled)
11. A method for generating a swarm trajectory in a central computer, comprising:
receiving, from a plurality of vehicles traveling a route segment, individual trajectories from each of the plurality of vehicles, wherein each trajectory comprises a parameter set based on one or more boundary conditions; processing the trajectories to generate a value for the trajectories relative to one or more configured parameter sets; generating the swarm trajectory based on the value, wherein the swarm trajectory comprises data configured to modify a vehicle driving trajectory; and transmitting the generated swarm trajectory.
12. The method of claim 11, wherein each of the individual trajectories comprise n-tuple information of a trajectory and parameter set.
13. The method of claim 12, wherein the one or more boundary conditions comprise a date, a day, a time of day interval, weather, parking situation and traffic condition.
14. The method of claim 11, wherein processing the trajectories to generate a value comprises processing the trajectories to obtain one of an average value or mean value of the trajectories relative to the one or more configured parameter sets.
15. The method of claim 14, wherein the one or more configured parameter sets comprises a combination of all of the one or more boundary conditions.
16. The method of claim 14, wherein the one or more configured parameter sets comprises a combination of some of the one or more boundary conditions.
17. The method of claim 11, wherein processing the trajectories to generate a value for the trajectories relative to one or more configured parameter sets comprises applying different weights to the boundary conditions.
18. A method for using a swarm trajectory for an ego-vehicle, comprising:
receiving, in a back-end computer, one or more boundary conditions determined by the ego-vehicle for a currently driven lane; processing, in the back-end computer, the one or more boundary conditions to determine that the one or more boundary conditions correspond with one or more stored boundary conditions; generating, in the back-end computer, at least one swarm trajectory for the currently driven lane based on the processing; and transmitting the at least one swarm trajectory to the ego vehicle, wherein the at least one swarm trajectory is configured to modify the driving trajectory of the ego-vehicle for the currently driven lane.
19. The method of claim 18, wherein the boundary conditions are determined by the ego-vehicle for a configured swarm trajectory.
20. The method of claim 18, wherein processing the one or more boundary conditions comprises determining differences between the one or more boundary conditions and the one or more stored boundary conditions, and, based on the determined differences, generating corrective boundary conditions for generating the at least one swarm trajectory.
21. The method of claim 18, wherein generating the at least one swarm trajectory comprises generating n-tuple information of a trajectory and parameter set.
22. The method of claim 18, wherein the one or more boundary conditions comprise a date, a day, a time of day interval, weather, parking situation and traffic condition.
23. A method for generating a swarm trajectory in a central computer, comprising:
receiving, from a plurality of vehicles traveling a route segment, individual trajectories from each of the plurality of vehicles, wherein each trajectory comprises n-tuple information of a trajectory and parameter set based on one or more boundary conditions; processing the trajectories to generate a value for the trajectories relative to one or more configured parameter sets; generating the swarm trajectory based on the value, wherein the swarm trajectory comprises data configured to modify a vehicle driving trajectory; and transmitting the generated swarm trajectory.
24. The method of claim 23, wherein the one or more boundary conditions comprise a date, a day, a time of day interval, weather, parking situation and traffic condition.
25. The method of claim 23, wherein processing the trajectories to generate a value comprises processing the trajectories to obtain one of an average value or mean value of the trajectories relative to the one or more configured parameter sets.
26. The method of claim 26, wherein th
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