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 .
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 94 and 119 and 123 are rejected under 35 U.S.C. 103 as being unpatentable over U.S. Patent No.: 8,849,494 B1 to Herbach which was filed on 3-15-13 (hereinafter “Herbach”) which is prior to the effective date of 3-20-18 and assigned to Waymo™ and in view of U.S. Patent Application Pub. No.: US 2013/0110368 A1 to Zagorski and in view of NPL, Eshed, Ohn-bar, On surveillance for safety critical events: In-vehicle video networks for predictive driver assistance systems, Computer Vision and Image Understanding, Science Direct, Volume 134, https://reader.elsevier.com/reader/sd/pii/S1077314214002070?token=B721DF1921B8E7588D22109EC181A37CA91AF12BEA520F8187CBF5B6A014BC694D0AA2EB00DF0920B3E7485046EA723E&originRegion=us-east-1&originCreation=20220929164535 (2015)(hereinafter “Eshed”).
In regard to claim 94, 119 and 123, Herbach discloses “94. (New) A navigation system for a host vehicle, the system comprising:
al least one processor comprising circuitry and a memory, wherein the memory incudes instructions that when executed by the circuitry cause the at least one processor to: (See FIG. 15a that shows a touchscreen 1500 where a new proposed trajectory 1550 in FIG. 15b can be made for the vehicle 1530 to avoid the object 1542 and FIG. 15c where the speed 1562 may also be altered; see FIG. 19A, block 1901; see Col. 22, lines 28 to 67; see Col. 24, lines 1-65)”.
receive at least one image acquired by an image capture device,
the at least one image being representative of an environment of the host vehicle; (see col. 6, lines 18 to 39) (see LIDAR unit 1626 in FIG. 16 and camera 1628 and obstacle detector 1630-1634 where the vehicle approaches the items and detects the items) (see col. 6, lines 18 to 39) (see LIDAR unit 1626 in FIG. 16 and camera 1628 and obstacle detector 1630-1634 where the vehicle approaches the items and detects the items) (see col. 6, lines 18 to 39) (see LIDAR unit 1626 in FIG. 16 and camera 1628 and obstacle detector 1630-1634 where the vehicle approaches the items and detects the items)
analyze the at least one image to identify a navigational state associated with the host vehicle:
determine, based on the navigational state, (see FIG. 10, where the av may be processing the data incorrectly and may become stuck and the remote operator cancels the information and intervenes in block 1030; see col. 4, lines 37 to 40 where the at least one high-level, polygonal or polyhedral representation of an object that obstructs the first trajectory or point cloud representation of the object in the point cloud is ignored and cancelled so the vehicle can drive with the new trajectory and ignore the old incorrect trajectory; see col. 11, line 35). (see FIG. 10, where the av may be processing the data incorrectly and may become stuck and the remote operator cancels the information and intervenes in block 1030; see col. 4, lines 37 to 40 where the at least one high-level, polygonal or polyhedral representation of an object that obstructs the first trajectory or point cloud representation of the object in the point cloud is ignored and cancelled so the vehicle can drive with the new trajectory and ignore the old incorrect trajectory; see col. 11, line 35).
Herbach is silent but Zagorski teaches “…a navigational action for the host vehicle based on a policy that maps possible navigational actions to sensed states,
wherein the navigational action is based on at least
one safety constraint applicable for the navigational state,
wherein the at least one safety constraint includes
a safety distance constraint associated with the host vehicle, (See paragraph 21 to 25 where the desired stopping distance is provided as Dstopping can this is determined as to whether this can be achieved and if not then an avoidance threshold is determined and if it cannot be avoided in block 122 then the maximum braking capability is provided in block 116; however if the relative distance is smaller however, if the distance is sufficiently large in block 114, then a sub maximum braking can be provided to avoid and if the deceleration avoidance value is larger then a deceleration is provided or if not then the maximum braking is provided in blocks 102-124 and 116);
It would have been obvious for one of ordinary skill in the art at the time the invention was made to combine the disclosure of Herbach with the teachings of Zagorski since Zagorski teaches that a parameter can be placed around a following vehicle. The vehicle distance and the speed can be recorded. See abstract. Then the vehicle can determine 1. A minimum collision avoidance distance in block 114 and then if this is relative distance is less than a threshold and a maximum braking can be still applied to decelerate the vehicle in block 116. However, if this is not smaller than a minimum value then 2. an avoidance deceleration can be provided to avoid the vehicle in blocks 120-124. This can provide increased safety and to prevent a rear end accident. See paragraphs 21-28 of Zagorski.
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Eshed teaches “….wherein the safety distance constraint is based on
a determined speed of the host vehicle and
a determined speed of a detected target object;
and cause at least one adjustment of a navigational actuator of the host vehicle to implement the determined navigational action. (see page 132 -136 where the vehicle host vehicle can scan the driver and then detect an overtaking event and see table 1 where a velocity and acceleration inputs V can be taken and previous overtaking acceleration events and videos are stored; see FIG. 13 where the vehicle overtaking acceleration is shown )
It would have been obvious for one of ordinary skill in the art at the time the invention was made to combine the disclosure of Herbach with the teachings of ESHED since ESHED teaches that a video can monitor a driver for certain signals including head cues in FIG. 3 and head movements and occlusion and poor lighting conditions. Additionally, a lane can also be examined using a lidar sensor. This can provide cues for how to control the autonomous operation of the vehicle for increase safety and provide a sudden intense braking when needed to avoid an accident based on a distance. See section 1 and 2-5.2.
The primary reference is silent but Herbach teaches “…and wherein determining the navigational action includes
identifying a plurality of future navigational states of the host
vehicle and analyzing each of the plurality of future
navigational states to determine a respective cost of each of
the plurality of future navigational states, the navigational
action being determined based on a comparison of the
respective costs, wherein analyzing each of the plurality of
future navigational states to determine the respective cost of
each of the plurality of future navigational states includes
applying a function to each of the plurality of future
navigational states; and
cause at least one adjustment of a navigational actuator of the host
vehicle to implement the determined navigational action”. ”. (see FIG. 15c where the av 1530 is traveling at a position on route 7 with a trajectory 1540 and then a revised trajectory 1550 to avoid the obstacle from the UI 1510 at the expert center and at acquisition time is recorded as August 4, 2013 at 5:24 PDT); (see FIG. 15c where the av 1530 is traveling at a position on route 7 with a trajectory 1540 and then a revised trajectory 1550 to avoid the obstacle from the UI 1510 at the expert center); (see also FIG. 6-8 where the host vehicle and the target vehicle are shown as blocks 610, 614 and the trajectory of the host vehicle may indicate a collision if an original trajectory 630 is followed to destination point 632 and a revised trajectory can be input 836 that avoids the collision) (see FIG. 15c where the vehicle 1530 is about to enter the virtual space and output on the display and will collide with the cow 1542 and instead the av is controlled to move according to a different spline trajectory 1550 and 1564)
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Claims 95-97 and 120 and 124 are rejected under 35 U.S.C. 103 as being unpatentable over U.S. Patent No.: 8,849,494 B1 to Herbach which was filed on 3-15-13 (hereinafter “Herbach”) which is prior to the effective date of 3-20-18 and assigned to Waymo™ and in view of U.S. Patent Application Pub. No.: US 2013/0110368 A1 to Zagorski and in view of NPL, Eshed, Ohn-bar, On surveillance for safety critical events: In-vehicle video networks for predictive driver assistance systems, Computer Vision and Image Understanding, Science Direct, Volume 134, https://reader.elsevier.com/reader/sd/pii/S1077314214002070?token=B721DF1921B8E7588D22109EC181A37CA91AF12BEA520F8187CBF5B6A014BC694D0AA2EB00DF0920B3E7485046EA723E&originRegion=us-east-1&originCreation=20220929164535 (2015)(hereinafter “Eshed”).
In regard to claim 95 and 120 and 124, Herbach discloses “…95. {New} The system of claim 94, wherein the determined navigational action is further based on a projected trajectory of the host vehicle and a projected trajectory of the target object”. (see FIG. 15c where the av 1530 is traveling at a position on route 7 with a trajectory 1540 and then a revised trajectory 1550 to avoid the obstacle from the UI 1510 at the expert center and at acquisition time is recorded as August 4, 2013 at 5:24 PDT); (see FIG. 15c where the av 1530 is traveling at a position on route 7 with a trajectory 1540 and then a revised trajectory 1550 to avoid the obstacle from the UI 1510 at the expert center); (see also FIG. 6-8 where the host vehicle and the target vehicle are shown as blocks 610, 614 and the trajectory of the host vehicle may indicate a collision if an original trajectory 630 is followed to destination point 632 and a revised trajectory can be input 836 that avoids the collision) (see FIG. 15c where the vehicle 1530 is about to enter the virtual space and output on the display and will collide with the cow 1542 and instead the av is controlled to move according to a different spline trajectory 1550 and 1564)
Zagorski teaches 96. (New) The system of claim 94, wherein the safety distance constraint comprises a safe longitudinal distance to the target vehicle or a safe lateral distance to a target vehicle”. (see FIG. 3 where the relative distance is less than a minimum collision avoidance distance in block 114-124; see also paragraph 25 where target vehicle velocity (v.sub.TAR) or acceleration (a.sub.TAR), relative velocity (.DELTA.v) or acceleration (.DELTA.a), etc.) and provide a minimum collision avoidance distance (d.sub.MINAVOID) and/or a desired stopping distance (d.sub.STOPPING) as output. Such data structures may also take other conditions into account, such as those involving current road conditions, weather conditions, the performance or capability of the host vehicle brake system, etc. In a different embodiment, the method employs an algorithmic approach to determine the minimum collision avoidance distance (d.sub.MINAVOID) and/or the desired stopping distance (d.sub.STOPPING), as opposed to using a lookup table or the like. These and other suitable techniques may be used to determine such distances, including the exemplary techniques disclosed in U.S. patent application Ser. No. 13/032,694, which is owned by the present assignee and whose contents are hereby incorporated by reference.) (see block 114 where based on the current speed there is a relative distance Delta D that is a minimum collision distance; and If the distance is less than the minimum distance then a maximum braking capability is provided in block 116; and if the distance is sufficiently larger then a deceleration avoidance value sis provided and compared to a threshold in block 102-122 and then a deceleration is provided in block 124 and if thee value is a no in block 122 then a maximum braking is provided in block 116).
Zagorski teaches “…97. (New) The system of claim 96, wherein the safety distance constraint further comprises a safe longitudinal distance to the target vehicle or a safe lateral distance to the target vehicle. (see block 114 where based on the current speed there is a relative distance Delta D that is a minimum collision distance; and If the distance is less than the minimum distance then a maximum braking capability is provided in block 116; and if the distance is sufficiently larger then a deceleration avoidance value sis provided and compared to a threshold in block 102-122 and then a deceleration is provided in block 124 and if thee value is a no in block 122 then a maximum braking is provided in block 116).
It would have been obvious for one of ordinary skill in the art at the time the invention was made to combine the disclosure of Herbach with the teachings of Zagorski since Zagorski teaches that a parameter can be placed around a following vehicle. The vehicle distance and the speed can be recorded. See abstract. Then the vehicle can determine 1. A minimum collision avoidance distance in block 114 and then if this is relative distance is less than a threshold and a maximum braking can be still applied to decelerate the vehicle in block 116. However, if this is not smaller than a minimum value then 2. an avoidance deceleration can be provided to avoid the vehicle in blocks 120-124. This can provide increased safety and to prevent a rear end accident. See paragraphs 21-28 of Zagorski.
Claims 98-99 and 121 and 125 are rejected under 35 U.S.C. 103 as being unpatentable over U.S. Patent No.: 8,849,494 B1 to Herbach which was filed on 3-15-13 (hereinafter “Herbach”) which is prior to the effective date of 3-20-18 and assigned to Waymo™ and in view of U.S. Patent Application Pub. No.: US 2013/0110368 A1 to Zagorski and in view of NPL, Eshed, Ohn-bar, On surveillance for safety critical events: In-vehicle video networks for predictive driver assistance systems, Computer Vision and Image Understanding, Science Direct, Volume 134, https://reader.elsevier.com/reader/sd/pii/S1077314214002070?token=B721DF1921B8E7588D22109EC181A37CA91AF12BEA520F8187CBF5B6A014BC694D0AA2EB00DF0920B3E7485046EA723E&originRegion=us-east-1&originCreation=20220929164535 (2015)(hereinafter “Eshed”) and in view of U.S. Patent No.: 9,849,852B1 to Larner that was filed in 9-4-15.
Herbach discloses that the vehicle can be on a straight road and then pull off to the side if there is an object and is silent but Lardner teaches 98. (New) The system of claim 95, wherein the safety constraint can include a road curvature constraint. (see FIG. 7 where a bike 610 is determined and a pedestrian is determined at 620 and then a path of the vehicle is shown as 702 and where the vehicle can later determine that the vehicle will collided with a first future location of the objects 712 and 722 as x, y and z points in FIG. 7)
It would have been obvious for one of ordinary skill in the art before the invention was made to combine the disclosure of HERBACH and the teachings of Lardner since Lardner teaches that by predicting a trajectory behavior of the autonomous vehicle and the trajectory behavior of the objects then a collision can be predicted even when the vehicle does not actually sense the vehicle and can use future behavior. This can give the processor more time to control the vehicle to avoid the accident or to provide a restraint mechanism to prevent a vehicle accident and if there is an accident to minimize the damage. See Col. 15, line 1 to Col. 16, line 54.
In regard to claim 98 and 121 and 125, Lardner teaches “…99. (New) The system of claim 94, wherein the target object comprises a detected
pedestrian associated with the navigational state, and wherein the safety distance
constraint prevents the host vehicle from entering a buffer zone around the pedestrian.. (see FIG. 7 where a bike 610 is determined and a pedestrian is determined at 620 and then a path of the vehicle is shown as 702 and where the vehicle can later determine that the vehicle will be collided with a first future location of the objects 712 and 722 as x, y and z points in FIG. 7)
It would have been obvious for one of ordinary skill in the art before the invention was made to combine the disclosure of HERBACH and the teachings of Lardner since Lardner teaches that by predicting a trajectory behavior of the autonomous vehicle and the trajectory behavior of the objects then a collision can be predicted even when the vehicle does not actually sense the vehicle and can use future behavior. This can give the processor more time to control the vehicle to avoid the accident or to provide a restraint mechanism to prevent a vehicle accident and if there is an accident to minimize the damage. See Col. 15, line 1 to Col. 16, line 54.
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Claim 100 is rejected under 35 U.S.C. 103 as being unpatentable over U.S. Patent No.: 8,849,494 B1 to Herbach which was filed on 3-15-13 (hereinafter “Herbach”) which is prior to the effective date of 3-20-18 and assigned to Waymo™ and in view of U.S. Patent Application Pub. No.: US 2013/0110368 A1 to Zagorski and in view of NPL, Eshed, Ohn-bar, On surveillance for safety critical events: In-vehicle video networks for predictive driver assistance systems, Computer Vision and Image Understanding, Science Direct, Volume 134, https://reader.elsevier.com/reader/sd/pii/S1077314214002070?token=B721DF1921B8E7588D22109EC181A37CA91AF12BEA520F8187CBF5B6A014BC694D0AA2EB00DF0920B3E7485046EA723E&originRegion=us-east-1&originCreation=20220929164535 (2015)(hereinafter “Eshed”) in view of U.S. Patent No.: 10,421,453 B2 to Ferguson et al. filed in 2016
Herbach is silent but Ferguson teaches 1 00. (New) The system of claim 99, wherein the buffer zone is based on at least one of a projected trajectory of the pedestrian or a relative motion between the detected pedestrian and the host vehicle (see FIG. 6 where the vehicle can move toward the intersection 100 and the second vehicle can have candidate paths through the intersection 671, 672 and 673; see col. 14, lines 50 to 67 where a threshold value of 15 percent and below can be discarded as not reliable; whereas in FIG. 9 all possible future trajectories are taken in block 930 based on a set of possible actions and then a likelihood of each based on the contextual information is taken and then a final future trajectory is based on the likelihood and for each trajectory in blocks 910—960 where low probability events under 15 percent are discarded to simplify the number of trajectories based on contextual data)
It would have been obvious for one of ordinary skill in the art before the invention was made to combine the disclosure of HERBACH and the teachings of FERGUSON since FERGUSON teaches that by predicting a trajectory behavior of the autonomous vehicle and the trajectory behavior of the other vehicles and also a probability that the vehicle will move in a particular trajectory over others, then this can allow the instant vehicle to keep away from likely FUTURE trajectories was in advance. This can give the processor more time to control the vehicle to avoid the accident and then move faster for unlikely trajectories. For example, it is very unlikely that the vehicle can back up or move on the sidewalk but it is very likely 85 percent that they can move on the turning lane and the instant vehicle should slow considerably and keep away from the likely path.
Claim 101 is rejected under 35 U.S.C. 103 as being unpatentable over U.S. Patent No.: 8,849,494 B1 to Herbach which was filed on 3-15-13 (hereinafter “Herbach”) which is prior to the effective date of 3-20-18 and assigned to Waymo™ and in view of U.S. Patent Application Pub. No.: US 2013/0110368 A1 to Zagorski and in view of NPL, Eshed, Ohn-bar, On surveillance for safety critical events: In-vehicle video networks for predictive driver assistance systems, Computer Vision and Image Understanding, Science Direct, Volume 134, https://reader.elsevier.com/reader/sd/pii/S1077314214002070?token=B721DF1921B8E7588D22109EC181A37CA91AF12BEA520F8187CBF5B6A014BC694D0AA2EB00DF0920B3E7485046EA723E&originRegion=us-east-1&originCreation=20220929164535 (2015)(hereinafter “Eshed”) in view of U.S. Patent No.: 10,421,453 B2 to Ferguson et al. filed in 2016 and in view of U.S. Patent Application Pub. No.; US 2012/0283907 A1 to Lee (hereafter “LEE ‘907 publication”).
Lee teaches “…1 01. (New) The system of claim 100, wherein the projected trajectory of the pedestrian is determined from a speed or a heading of the detected pedestrian.. ; (see figure 2 where the vehicle state is estimated in block 210 and a lane marking is detected in block 206 and where a predicted path generation is provided and a lane change is desired and input in blocks 214-208); (See FIG. 4 where a predicted path is determined in block 406 and a desired path 404 is provided; see FIG. 5 where the driver provides a request for automatic lane centering in block 506; and a path generation is provided in block 514 and a prediction is made 516 and a differential braking for a lane control 528 and the vehicle is provided along the desired path 404; see paragraph 54-60)
It would have been obvious for one of ordinary skill in the art at the time of the effective disclosure was made to combine the disclosure of HERBACH with the teachings of the LEE ‘907 publication since the LEE ‘907 publication teaches that a lane centering can be engaged by the driver in block 507. Then a path of the vehicle can be generated and a number of lane markings can be detected. A lane change can also be provided in block 212. Then a differential braking controller and steering control can provide a supervisory control along the new path of the vehicle to change a lane. A yaw of the vehicle can be determined and control so the vehicle can smoothly and gradually change the lanes. See paragraphs 34-40 and claims 1-12 and summary of the invention of Gupta.
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Claims 102-107 are rejected under 35 U.S.C. 103 as being unpatentable over U.S. Patent No.: 8,849,494 B1 to Herbach which was filed on 3-15-13 (hereinafter “Herbach”) which is prior to the effective date of 3-20-18 and assigned to Waymo™ and in view of U.S. Patent Application Pub. No.: US 2013/0110368 A1 to Zagorski and in view of NPL, Eshed, Ohn-bar, On surveillance for safety critical events: In-vehicle video networks for predictive driver assistance systems, Computer Vision and Image Understanding, Science Direct, Volume 134, https://reader.elsevier.com/reader/sd/pii/S1077314214002070?token=B721DF1921B8E7588D22109EC181A37CA91AF12BEA520F8187CBF5B6A014BC694D0AA2EB00DF0920B3E7485046EA723E&originRegion=us-east-1&originCreation=20220929164535 (2015)(hereinafter “Eshed”) and in view of U.S. Patent No.: 9766626 B2 to Zhu et al. that was filed in 2012 and is assigned to Waymo™
In regard to claim 102, and 131, Zhu teaches “…1 02. (New) The system of claim 100, wherein the relative motion between the
detected pedestrian and the host vehicle is based on a projected trajectory of the host
vehicle. (see FIG. 6 where a person 610 is detected in an intersection and moving in a direction of arrow B) (see FIG. 6 where a person 610 is detected in an intersection and moving in a direction of arrow B) (see col. 14, lines 1-16 where a warning is provided that a collision is imminent to the driver and see element B in FIG. 4 where the user is moving in direction B and the vehicle is moving in the direction C and the other vehicle is moving in the direction a2, and a1; see col. 10, lines 47 to col. 11, line 14)”
In regard to claim 103, and 132, Zhu teaches “..03. (New) The system of claim 94, wherein the navigational action is further based
on at least one possible driving trajectory for the host vehicle, and wherein each of the
at least one possible driving trajectory is associated with a respective future navigational
state. (see col. 14, lines 1-16 where a warning is provided that a collision is imminent to the driver and see element B in FIG. 4 where the user is moving in direction B and the vehicle is moving in the direction C and the other vehicle is moving in the direction a2, and a1; see col. 10, lines 47 to col. 11, line 14)
It would have been obvious for one of ordinary skill in the art before the invention was effectively filed to combine the disclosure of HERBACH with the teachings of ZHU of WAYMO™ since ZHU teaches that in an intersection of FIG. 6 an autonomous vehicle can detect a pedestrian in the cross walk and classify it based on the head and body 600 and then using a model, the AV can predict a likely future behavior of the pedestrian (path B in FIG. 6) and then control the AV accordingly to avoid the accident and collision but also avoid all of the likely model based trajectories (path B, C, A etc). This can provide an improved pedestrian position model of a future trajectory B and then it can avoid a “future behavior” using path A2 to provide improved collision avoidance. See abstract and claims 1-19 of Zhu.
Zhu teaches “…1 04. (New) The system of claim 103, wherein the navigational action is further based
on a cost associated with a trajectory of the target object.. (see col. 14, lines 1-16 where a warning is provided that a collision is imminent to the driver and see element B in FIG. 4 where the user is moving in direction B and the vehicle is moving in the direction C and the other vehicle is moving in the direction a2, and a1; see col. 10, lines 47 to col. 11, line 14)”
It would have been obvious for one of ordinary skill in the art before the invention was effectively filed to combine the disclosure of HERBACH with the teachings of ZHU of WAYMO™ since ZHU teaches that in an intersection of FIG. 6 an autonomous vehicle can detect a pedestrian in the cross walk and classify it based on the head and body 600 and then using a model, the AV can predict a likely future behavior of the pedestrian (path B in FIG. 6) and then control the AV accordingly to avoid the accident and collision but also avoid all of the likely model based trajectories (path B, C, A etc). This can provide an improved pedestrian position model of a future trajectory B and then it can avoid a “future behavior” using path A2 to provide improved collision avoidance. See abstract and claims 1-19 of Zhu.
Zhu teaches “…1 05. (New) The system of claim 94, wherein a first future navigational state of the
plurality of future navigational states is associated with a first cost having a first value
and a second future navigational state of the plurality of future navigational states is
associated with a second cost having a second value, and wherein the first value and
the second value are calculated according to a cost function. (see col. 14, lines 1-16 where a warning is provided that a collision is imminent to the driver and see element B in FIG. 4 where the user is moving in direction B and the vehicle is moving in the direction C and the other vehicle is moving in the direction a2, and a1; see col. 10, lines 47 to col. 11, line 14)”
It would have been obvious for one of ordinary skill in the art before the invention was effectively filed to combine the disclosure of HERBACH with the teachings of ZHU of WAYMO™ since ZHU teaches that in an intersection of FIG. 6 an autonomous vehicle can detect a pedestrian in the cross walk and classify it based on the head and body 600 and then using a model, the AV can predict a likely future behavior of the pedestrian (path B in FIG. 6) and then control the AV accordingly to avoid the accident and collision but also avoid all of the likely model based trajectories (path B, C, A etc). This can provide an improved pedestrian position model of a future trajectory B and then it can avoid a “future behavior” using path A2 to provide improved collision avoidance. See abstract and claims 1-19 of Zhu.
Zhu teaches “…106. (New) The system of claim 105, wherein navigational action is determined based
on a comparison of the first value to the second value. (see col. 14, lines 1-16 where a warning is provided that a collision is imminent to the driver and see element B in FIG. 4 where the user is moving in direction B and the vehicle is moving in the direction C and the other vehicle is moving in the direction a2, and a1; see col. 10, lines 47 to col. 11, line 14)”
It would have been obvious for one of ordinary skill in the art before the invention was effectively filed to combine the disclosure of HERBACH with the teachings of ZHU of WAYMO™ since ZHU teaches that in an intersection of FIG. 6 an autonomous vehicle can detect a pedestrian in the cross walk and classify it based on the head and body 600 and then using a model, the AV can predict a likely future behavior of the pedestrian (path B in FIG. 6) and then control the AV accordingly to avoid the accident and collision but also avoid all of the likely model based trajectories (path B, C, A etc). This can provide an improved pedestrian position model of a future trajectory B and then it can avoid a “future behavior” using path A2 to provide improved collision avoidance. See abstract and claims 1-19 of Zhu.
Zhu teaches “…107. (New) The system of claim 94, wherein the navigational action is based on a
change in the respective costs over a time-dependent quantity. (see col. 14, lines 1-16 where a warning is provided that a collision is imminent to the driver and see element B in FIG. 4 where the user is moving in direction B and the vehicle is moving in the direction C and the other vehicle is moving in the direction a2, and a1; see col. 10, lines 47 to col. 11, line 14)”
It would have been obvious for one of ordinary skill in the art before the invention was effectively filed to combine the disclosure of HERBACH with the teachings of ZHU of WAYMO™ since ZHU teaches that in an intersection of FIG. 6 an autonomous vehicle can detect a pedestrian in the cross walk and classify it based on the head and body 600 and then using a model, the AV can predict a likely future behavior of the pedestrian (path B in FIG. 6) and then control the AV accordingly to avoid the accident and collision but also avoid all of the likely model based trajectories (path B, C, A etc). This can provide an improved pedestrian position model of a future trajectory B and then it can avoid a “future behavior” using path A2 to provide improved collision avoidance. See abstract and claims 1-19 of Zhu.
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Claim 108 is rejected under 35 U.S.C. 103 as being unpatentable over U.S. Patent No.: 8,849,494 B1 to Herbach which was filed on 3-15-13 (hereinafter “Herbach”) which is prior to the effective date of 3-20-18 and assigned to Waymo™ and in view of U.S. Patent Application Pub. No.: US 2013/0110368 A1 to Zagorski and in view of NPL, Eshed, Ohn-bar, On surveillance for safety critical events: In-vehicle video networks for predictive driver assistance systems, Computer Vision and Image Understanding, Science Direct, Volume 134, https://reader.elsevier.com/reader/sd/pii/S1077314214002070?token=B721DF1921B8E7588D22109EC181A37CA91AF12BEA520F8187CBF5B6A014BC694D0AA2EB00DF0920B3E7485046EA723E&originRegion=us-east-1&originCreation=20220929164535 (2015)(hereinafter “Eshed”) and in view of Zhu and in view of United States Patent No.: US8954252B1 to Urmson et al. that is assigned to Waymo™ that was filed in 2012 (hereinafter “Urmson”).
Urmson teaches “….108. (New) The system of claim 107, wherein the time-dependent quantity is based on
a future state of the host vehicle.. (see FIG. 6b and 6c where the vehicle can indicate that the user can cross the path of the vehicle or the pedestrian cannot cross and should not walk into the front of the vehicle; see col. 12, line 33 to col. 13, line 33) (See col, 9, line 10-45 where the vehicle can provide a text message on the screen that the user can move in front of the vehicle and cross the cross walk)
It would have been obvious for one of ordinary skill in the art at the time of the invention to combine the disclosure of the primary reference to HERBACH and the teachings of Urmson since Urmson teaches that a path of movement of both the vehicle and the pedestrian in FIG. 9 can be determined and the vehicle can indicate to the pedestrian to not walk in front of the vehicle or to walk so a safe coordination between the speed of the vehicle and the trajectory of the pedestrian can be accomplished. See col. 12, line 33 to col. 33, line 33 and FIG.9 of Urmson.
Claims 109 and 122 and 128 are rejected under 35 U.S.C. 103 as being unpatentable over U.S. Patent No.: 8,849,494 B1 to Herbach which was filed on 3-15-13 (hereinafter “Herbach”) which is prior to the effective date of 3-20-18 and assigned to Waymo™ and in view of U.S. Patent Application Pub. No.: US 2013/0110368 A1 to Zagorski and in view of NPL, Eshed, Ohn-bar, On surveillance for safety critical events: In-vehicle video networks for predictive driver assistance systems, Computer Vision and Image Understanding, Science Direct, Volume 134, https://reader.elsevier.com/reader/sd/pii/S1077314214002070?token=B721DF1921B8E7588D22109EC181A37CA91AF12BEA520F8187CBF5B6A014BC694D0AA2EB00DF0920B3E7485046EA723E&originRegion=us-east-1&originCreation=20220929164535 (2015)(hereinafter “Eshed”) and in view of Zhu and in view of United States Patent No.: US8954252B1 to Urmson et al. that is assigned to Waymo™ that was filed in 2012 (hereinafter “Urmson”) and in view of U.S. Patent No.: 10,421,453 B2 to Ferguson et al. filed in 2014
In regard to claim 109 and 122 and 128, Ferguson teaches “…1 09. (New) The system of claim 94, wherein the at least one safety constraint further
comprises at least one of: a buffer time increasing an arrival time of the host vehicle
relative to a leaving time of the target object at an intersection point; or a give way
designation assigned to the target object, the give way designation requiring the host
vehicle to give way to the target object.. (see FIG. 7c where the vehicle is the object 714 and the object trajectories are shown and 720-1, 720-2 and 730 and 740 with each of the trajectories being shown as having a probability (10 to 20 percent) of being executed with some going straight and some turning left and some turning right with the bounding box shown the cross walks being in front of the vehicle where an object may move into as 530 and 532 and an unnumbered cross walk in front of 714)
See motivation above.
Claims 110-111 are rejected under 35 U.S.C. 103 as being unpatentable over U.S. Patent No.: 8,849,494 B1 to Herbach which was filed on 3-15-13 (hereinafter “Herbach”) which is prior to the effective date of 3-20-18 and assigned to Waymo™ and in view of U.S. Patent Application Pub. No.: US 2013/0110368 A1 to Zagorski and in view of NPL, Eshed, Ohn-bar, On surveillance for safety critical events: In-vehicle video networks for predictive driver assistance systems, Computer Vision and Image Understanding, Science Direct, Volume 134, https://reader.elsevier.com/reader/sd/pii/S1077314214002070?token=B721DF1921B8E7588D22109EC181A37CA91AF12BEA520F8187CBF5B6A014BC694D0AA2EB00DF0920B3E7485046EA723E&originRegion=us-east-1&originCreation=20220929164535 (2015)(hereinafter “Eshed”) and in view of Zhu and in view of U.S. Patent App. Pub. No.: US 2017/0031361 A1 to Olson which was filed in 2015.
Olson teaches 1110. (New) The system of claim 94, wherein the navigational action comprises a lane
change.. (see paragraph 60-70 and 67);
It would have been obvious for one of ordinary skill in the art before the effective filing date of the disclosure to combine the disclosure of the primary reference and the teachings of OLSON since OLSON teaches that a machine learning neural network can study traffic data. The model can identify traffic data and behavior data. The model can then assign a number of trajectories of where a vehicle may move to and a probability being associated with each possible trajectory. Then a simulation can be run and a host vehicle policy can be taken for issuing better and safer control commands based on the planned and likely trajectory of the vehicle and other non-host vehicles. A change and point of change can also be taken. The Bayesian information criterion is a known approximation that avoids marginalizing over the policy parameters and provides a principled penalty against complex policies 46 by assuming a Gaussian posterior model around the estimated parameters. Thus, only the ability to fit policies 46 to the observed data is required, which can be achieved via a maximum likelihood estimation (MLE) method. This can provide for identification of trajectory results that are likely and or if there is an anomalous condition using a Gaussian model in paragraph 70 and equation 15. See paragraph 60-70 of Olson.
Olson teaches “…111. (New) The system of claim 94, wherein the target object comprises a detected
stationary object, and wherein the safety distance constraint prevents the host vehicle
from colliding with the stationary object. (see paragraph 60-70 and 64);
It would have been obvious for one of ordinary skill in the art before the effective filing date of the disclosure to combine the disclosure of the primary reference and the teachings of OLSON since OLSON teaches that a machine learning neural network can study traffic data. The model can identify traffic data and behavior data. The model can then assign a number of trajectories of where a vehicle may move to and a probability being associated with each possible trajectory. Then a simulation can be run and a host vehicle policy can be taken for issuing better and safer control commands based on the planned and likely trajectory of the vehicle and other non-host vehicles. A change and point of change can also be taken. The Bayesian information criterion is a known approximation that avoids marginalizing over the policy parameters and provides a principled penalty against complex policies 46 by assuming a Gaussian posterior model around the estimated parameters. Thus, only the ability to fit policies 46 to the observed data is required, which can be achieved via a maximum likelihood estimation (MLE) method. This can provide for identification of trajectory results that are likely and or if there is an anomalous condition using a Gaussian model in paragraph 70 and equation 15. See paragraph 60-70 of Olson.
Claim 112 is rejected under 35 U.S.C. 103 as being unpatentable over U.S. Patent No.: 8,849,494 B1 to Herbach which was filed on 3-15-13 (hereinafter “Herbach”) which is prior to the effective date of 3-20-18 and assigned to Waymo™ and in view of U.S. Patent Application Pub. No.: US 2013/0110368 A1 to Zagorski and in view of NPL, Eshed, Ohn-bar, On surveillance for safety critical events: In-vehicle video networks for predictive driver assistance systems, Computer Vision and Image Understanding, Science Direct, Volume 134, https://reader.elsevier.com/reader/sd/pii/S1077314214002070?token=B721DF1921B8E7588D22109EC181A37CA91AF12BEA520F8187CBF5B6A014BC694D0AA2EB00DF0920B3E7485046EA723E&originRegion=us-east-1&originCreation=20220929164535 (2015)(hereinafter “Eshed”) and in view of Zhu and in view of U.S. Patent App. Pub. No.: US 2017/0031361 A1 to Olson which was filed in 2015 and in view of Ferguson.
Ferguson discloses “112. (New) The system of claim 94, wherein the at least one safety constraint further
includes a take way designation assigned to the target object.”. (See col. 16, lines 20 to col. 18, line 25) (see FIG. 7c where the vehicle 580 can move according to 730, 740, 720 and 71 and 780 and 710 has a 20 percent probability and 720 has a 20 percent probability and 740)
See motivation above.
Claims 113-114 are rejected under 35 U.S.C. 103 as being unpatentable over U.S. Patent No.: 8,849,494 B1 to Herbach which was filed on 3-15-13 (hereinafter “Herbach”) which is prior to the effective date of 3-20-18 and assigned to Waymo™ and in view of U.S. Patent Application Pub. No.: US 2013/0110368 A1 to Zagorski and in view of NPL, Eshed, Ohn-bar, On surveillance for safety critical events: In-vehicle video networks for predictive driver assistance systems, Computer Vision and Image Understanding, Science Direct, Volume 134, https://reader.elsevier.com/reader/sd/pii/S1077314214002070?token=B721DF1921B8E7588D22109EC181A37CA91AF12BEA520F8187CBF5B6A014BC694D0AA2EB00DF0920B3E7485046EA723E&originRegion=us-east-1&originCreation=20220929164535 (2015)(hereinafter “Eshed”) and in view of U.S. Patent No.: 9766626 B2 to Zhu et al. that was filed in 2012 and is assigned to Waymo™ and in view of Ferguson.
Ferguson discloses “113. (New) The system of claim 112, wherein the take way designation is based on at
least one of a detected traffic sign or traffic light. ”. (See col. 16, lines 20 to col. 18, line 25 where there is a stop sign and light and intersection and where the vehicle must stop at the stop sign) (see FIG. 7c where the vehicle 580 can move according to 730, 740, 720 and 71 and 780 and 710 has a 20 percent probability and 720 has a 20 percent probability and 740)
See motivation statement above.
Ferguson discloses “114. (New) The system of claim 94, wherein the determined navigational action gives
way to the target object based on an observed rule break by the target object.. ”. (See FIG. where there is a four way stop and the vehicle will stop and allow the pedestrians to cross and estimate the likely paths; see col. 16, lines 20 to col. 18, line 25) (see FIG. 7c where the vehicle 580 can move according to 730, 740, 720 and 71 and 780 and 710 has a 20 percent probability and 720 has a 20 percent probability and 740).
See motivation statement above.
Claims 115-118 are rejected under 35 U.S.C. 103 as being unpatentable over U.S. Patent No.: 8,849,494 B1 to Herbach which was filed on 3-15-13 (hereinafter “Herbach”) which is prior to the effective date of 3-20-18 and assigned to Waymo™ and in view of U.S. Patent Application Pub. No.: US 2013/0110368 A1 to Zagorski and in view of NPL, Eshed, Ohn-bar, On surveillance for safety critical events: In-vehicle video networks for predictive driver assistance systems, Computer Vision and Image Understanding, Science Direct, Volume 134, https://reader.elsevier.com/reader/sd/pii/S1077314214002070?token=B721DF1921B8E7588D22109EC181A37CA91AF12BEA520F8187CBF5B6A014BC694D0AA2EB00DF0920B3E7485046EA723E&originRegion=us-east-1&originCreation=20220929164535 (2015)(hereinafter “Eshed”) and in view of Ferguson.
In regard to claim 133, and 115, Ferguson discloses “…115. (New) The system of claim 94, wherein the at least one safety constraint includes
at least one of a plurality of safety constraints that are assigned a different priority based
on the navigational state or a second safety distance constraint associated with a
second target object. (see FIG. 7c where the vehicle is the object 714 and the object trajectories are shown and 720-1, 720-2 and 730 and 740 with each of the trajectories being shown as having a probability (10 to 20 percent) of being executed with some going straight and some turning left and some turning right with the bounding box shown the cross walks being in front of the vehicle where an object may move into as 530 and 532 and an unnumbered cross walk in front of 714; the first channel is shown as the road having a shape and an intersection as shown in FIG. 7c, a second channel shows the trajectories as 4 different trajectories, a third channel shows the probability of the each trajectory; a fifth channel shows the cross walks and a stop sign with shading)”
See motivation statement above.
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In regard to claim 116 and 134, Ferguson discloses “…116. (New) The system of claim 94, wherein the navigational action is based on a
determination that the target object is changing lanes.. (see FIG. 7c where the vehicle is the object 714 and the object trajectories are shown and 720-1, 720-2 and 730 and 740 with each of the trajectories being shown as having a probability (10 to 20 percent) of being executed with some going straight and some turning left and some turning right with the bounding box shown the cross walks being in front of the vehicle where an object may move into as 530 and 532 and an unnumbered cross walk in front of 714)”.
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Ferguson teaches “…117. (New) The system of claim 116, wherein the determination that the target vehicle
is changing lanes is based on the speed and a determined heading of the target object.. (see vehicle 100 scanning vehicle 714 in the path of the vehicle 100) (see FIG. 7c where the vehicle is the object 714 and the object trajectories are shown and 720-1, 720-2 and 730 and 740 with each of the trajectories being shown as having a probability (10 to 20 percent) of being executed with some going straight and some turning left and some turning right with the bounding box shown the cross walks being in front of the vehicle where an object may move into as 530 and 532 and an unnumbered cross walk in front of 714)
Ferguson teaches “..118. (New) The system of claim 116, wherein the at least one processing device is
further programmed to determine that the target object will likely cut into a lane of the host vehicle, and wherein the navigational action comprises a reduction in the speed of the host vehicle.. (see FIG. 7c where the vehicle is the object 714 and the object trajectories are shown and 720-1, 720-2 and 730 and 740 with each of the trajectories being shown as having a probability (10 to 20 percent) of being executed with some going straight and some turning left and some turning right with the bounding box shown the cross walks being in front of the vehicle where an object may move into as 530 and 532 and an unnumbered cross walk in front of 714; the first channel is shown as the road having a shape and an intersection as shown in FIG. 7c, a second channel shows the trajectories as 4 different trajectories, a third channel shows the probability of the each trajectory; a fifth channel shows the cross walks and a stop sign with shading) and where the vehicle will stop”
See motivation statements above.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP §§ 706.02(l)(1) - 706.02(l)(3) for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/process/file/efs/guidance/eTD-info-I.jsp.
Claims 94-125 are rejected under obviousness double patenting in view of claim 1-30 of U.S. Patent No.: 11077845 that recites “a system for navigating a host vehicle, the system comprising:
at least one processing device within the host vehicle, the at least one processing device comprising circuitry and a memory, wherein the
memory includes instructions that when executed by the circuitry cause
the at least one processing device to:
receive at least one image acquired by an image capture device, the at least one image being
representative of an environment of the host vehicle;
determine, based on at least one stored driving policy, a planned
navigational action for accomplishing a navigational goal of the host vehicle;
analyze the at least one image to identify a target vehicle in the environment of the host vehicle;
determine a next-state distance between the host vehicle and the
target vehicle that would result if the planned navigational action was taken;
determine a current speed of the host vehicle;
determine a current speed of the target vehicle and assume a
maximum braking rate capability of the target vehicle based on at least one recognized characteristic of the target vehicle determined based on analysis of the at least one image;
determine that the host vehicle can be stopped within a host vehicle stopping distance that is less than the determined next-state distance summed together with a target vehicle travel distance determined based on the current speed of the target vehicle and the assumed maximum braking rate capability of the target vehicle, wherein the determination is based on the determined current speed of the host vehicle and at a predetermined sub-maximal braking rate that is less than a maximum braking rate capability of the host vehicle; and
implement the planned navigational action based on the determination”.
The only difference is in claim of the present claims it recites a safety distance constraint based on a determined speed of the object and the host vehicle. The claims recite a number of future states that are provided to analyze a collision risk and then can provide a braking.
The claims are otherwise identical.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JEAN PAUL CASS whose telephone number is (571)270-1934. The examiner can normally be reached Monday to Friday 7 am to 7 pm; Saturday 10 am to 12 noon.
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/JEAN PAUL CASS/Primary Examiner, Art Unit 3668
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