DETAILED CORRESPONDENCE
This action is in response to the filing of the Amendments on 04/27/2026. Claims 22 and 30 are cancelled. The Terminal Disclaimer filed on 04/27/2026 has been accepted.
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 Objections
Applicant is advised that should claim 37 be found allowable, claim 38 will be objected to under 37 CFR 1.75 as being a substantial duplicate thereof. When two claims in an application are duplicates or else are so close in content that they both cover the same thing, despite a slight difference in wording, it is proper after allowing one claim to object to the other as being a substantial duplicate of the allowed claim. See MPEP § 608.01(m).
Claim Rejections - 35 USC § 103
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.
Claim(s) 21, 23 - 25, 29, 31 – 33, 37, 38 and 40 are rejected under 35 U.S.C. 103 as being unpatentable over Browning (US 20180005407) in view of Russell (US 20200192365).
Claim 21, Browning discloses computer-implemented method comprising:
receiving a previously-generated surfel map representing a driving environment in which a vehicle is located, the surfel map comprising a plurality of surfels generated by a plurality of other vehicles obtaining sensor data in the environment, each surfel corresponding to a respective different location in the environment in which a vehicle is located; [see at least p0021 – p0022, p0038 and p0080 and also see Fleet vehicles in Fig 12 - storage system may be provided with a vehicle to store a collection of submaps that represent a geographic area where the vehicle may be driven. A programmatic interface may be provided to receive submaps and submap updates independently of other submaps; Still further, in some examples, a submap provides a data structure that can carry one or more data layers which fulfill a data consumption requirement of a vehicle when the vehicle is autonomously navigated through an area of a road segment. The data layers of the submap can include, or may be based on, sensor information collected from a same or different vehicle (or other source) which passed through the same area on one or more prior instances; Each of the stored submaps 105 may include data layers corresponding to multiple types of information about a corresponding road segment; According to some examples, the localization layer 306 may provide a three-dimensional point cloud of imagelets and/or surfels. Depending on the implementation, the imagelets or surfels may represent imagery captured through Lidar, stereoscopic cameras, a combination of two-dimensional cameras and depth sensors, or other three-dimensional sensing technology];
receiving, in real-time from one or more sensors, sensor data of the environment in which the vehicle is located; [see at least p0039 - to identify the likely submap for an initial location of the vehicle 10. In one implementation, the submap processing component 120 implements the start component 122 as a coarse or first-pass process to compare the submap feature set 113 of an initially retrieved submap against a current sensor state 493, as determined from one or more sensor interfaces or components of the vehicle's sensor system 492. The start logic 114 may perform the comparison to identify, for example, a current submap 145 of the initial set which contains the feature of a landmark detected as being present in the current sensor state 493 of the vehicle 10];
determining, based on comparing the representation of the environment in the surfel map to the sensor data received from the one or more sensors, that the environment in which the vehicle is located includes a change; [see at least p0045 and p0153 - the submap processing component 120 can include perception component 124 which provides perception output 129 representing objects that are detected (through analysis of the current sensor state 493) as being present in the area of the road network. The perception component 124 can determine the perception output to include, for example, a set of objects (e.g., dynamic objects, road features, etc.). In determining the perception output 129, the perception component 124 can compare detected objects from the current sensor state 493 with known and static objects identified with the submap feature set 113. The perception component 124 can generate the perception output 129 to identify (i) static objects which may be in the field of view, (ii) non-static objects which may be identified or tracked, (iii) an image representation of the area surrounding a vehicle with static objects removed or minimized, so that the remaining data of the current sensor state 493 is centric to dynamic objects; Similarly, the perceived geometric differential may reflect a difference in a geometric attribute (e.g., height, width, footprint or shape) of an object or feature that is depicted in the current image data 1043, as compared to the depiction of the object or feature with the corresponding imagelets of the point cloud 1035].
Browning does not specifically disclose a change that introduces an occlusion of a line of sight between a location of the vehicle and an area of interest; and based on determining that the change in the environment introduces the occlusion, generating an updated path for the vehicle that establishes a line of sight between the one or more sensors of the vehicle and the area of interest.
However, Russell discloses a method for operating an autonomous vehicle. Teaching, occlusions may include one or more areas that are blocked by the plurality of objects from a field of view of the vehicle 100 during the first time interval. These blocked areas may be identified based on the relationship between the locations. In particular, blocked areas may include areas that fall behind a current or predicted location of the given object of the plurality of objects from the point of view of the vehicle 100. The field of view of the vehicle 100 may be defined by the sensors of and the sensor data generated by the perception system 172. The field of view may include areas in the sensor data within an angular range extending from the location of the vehicle 100 and within a distance from the location of the vehicle 100. Any lane segments that are in the one or more areas may be determined to be occluded during the first time interval.
Russell discloses that the computing device 110 on vehicle 100 projects a field of view, see Fig 8A, which shows occlusions may include one or more areas that are blocked by the plurality of objects from a field of view of the vehicle 100 during the first time interval. These blocked areas may be identified based on the relationship between the locations. In particular, blocked areas may include areas that fall behind a current or predicted location of the given object of the plurality of objects from the point of view of the vehicle 100. The field of view of the vehicle 100 may be defined by the sensors of and the sensor data generated by the perception system 172. The field of view may include areas in the sensor data within an angular range extending from the location of the vehicle 100 and within a distance from the location of the vehicle 100. Any lane segments that are in the one or more areas may be determined to be occluded during the first time interval. Here the vehicle 720 when brought into a position (Fig 8A) which is a change in the environment, truck 710 occludes 720 from AV 100. The vehicle 100 may have a planned maneuver 702 to cross one or more lanes of road 220. The planned maneuver 702 of the vehicle, illustrated as a dashed line, includes a left turn from lane portion 253A into lane portion 256A of road 220. In the maneuver 702, the vehicle 100 has to cross lanes 252 and 254 of the road 220 [see Fig 7]. The plurality of objects may include moving and/or stationary objects. In particular, the plurality of objects may include other road users, such as vehicles, bicycles, or pedestrians, or may include other types of obstructions, such as buildings, posts, trees, or construction tools. As shown in FIG. 7, a truck 710 and a sedan 720 are in the vehicle's environment. The computing device 110 may detect, using the perception system 172, the truck 710 and the sedan 720 travelling in lanes 252 and 254, respectively, and classify both the truck 710 and the sedan 720 as road users. The computing device 110 may also identify approximate dimensions and speeds of the truck 710 and the sedan 720 using the perception system 172. The determination of occluded lane segments may therefore be repeated as needed until the driving instruction is determined for the vehicle [see Figs, 7 – 8B and p0061 – p0074].
It would have been obvious before the effective date of the claimed invention to one of ordinary skill in the art to modify the device in Browning to include a change that introduces an occlusion of a line of sight between a location of the vehicle and an area of interest; and based on determining that the change in the environment introduces the occlusion, generating an updated path for the vehicle that establishes a line of sight between the one or more sensors of the vehicle and the area of interest, as suggested and taught by Russell with a reasonable expectation of success, for the purpose of providing a detection system configured to detect objects in an environment of the autonomous vehicle, and one or more computing devices in communication with the detection system, thus improving safety and providing a more efficient self-driving system that does not need to recalculate paths as often due to the object behavior being different from what was predicted. In addition, the self-driving system may adjust predictions quicker and react quicker to the objects in its vicinity.
Claim 29 is similarly rejected as Claim 21, see above.
Claim 37 is similarly rejected as Claim 21, see above.
Claim 38 is similarly rejected as Claim 21, see above.
Claim 23, Browning discloses the method of claim 21, wherein the area of interest corresponds to a location from which cross traffic, pedestrians, or cyclists are predicted to originate [see at least p0069 - described with some other examples, the sensor analysis determinations 265 can include object detection regarding the formation of instantaneous road conditions (e.g., new road hazard), as well as pattern detection regarding traffic behavior (e.g., lane formation, turn restrictions in traffic intersections, etc.)].
Claim 31 is similarly rejected as Claim 23, see above.
Claim 39 is similarly rejected as Claim 23, see above.
Claim 24, Browning discloses the method of claim 21, but is silent to wherein determining that the environment in which the vehicle is located includes a change comprises determining that the environment includes a parked vehicle that occludes the line of sight.
However, Russell discloses the computing device 110 detects a plurality of objects in the vehicle's environment, for instance, using sensor data from the perception system 172. The sensor data may also include characteristics of each object, such as the object's size, shape, speed, orientation, direction, etc. The plurality of objects may include moving and/or stationary objects. In particular, the plurality of objects may include other road users, such as vehicles, bicycles, or pedestrians, or may include other types of obstructions, such as buildings, posts, trees, or construction tools. As shown in FIG. 7, a truck 710 and a sedan 720 are in the vehicle's environment. The Examiner interprets the objects broadly to include a parked vehicle [see p0057 and Fig 6 of Russell].
It would have been obvious before the effective date of the claimed invention to one of ordinary skill in the art to modify the device in Browning to include determining that the environment in which the vehicle is located includes a change comprises determining that the environment includes a parked vehicle that occludes the line of sight, as suggested and taught by Russell, with a reasonable expectation of success, for the purpose of providing predictive behavior to avoid hazards when the view from the vehicle being driven is obstructed or restricted.
Claim 32 is similarly rejected as Claim 24, see above.
Claim 40 is similarly rejected as Claim 24, see above.
Claim 25, Browning discloses the method of claim 21, but is silent to wherein generating the updated path for the vehicle to travel comprises causing the vehicle to move forward a predetermined amount.
However, Russell discloses the computing device 110 determines a timing for the planned maneuver 702 for the vehicle 100 to make an unprotected left turn across intersection 230 onto the multi-lane road 220. As the reaction time of sedan 720 is predicted to be the end of the first time interval, the computing device 110 determines the timing for the planned maneuver 702 to be after the first time interval. The Examiner interprets the planned move of 702 to cross the intersection, a predetermined amount moving forward [see Fig 7, p0073].
It would have been obvious before the effective date of the claimed invention to one of ordinary skill in the art to modify the device in Browning to include wherein generating an updated path for the vehicle to travel comprises causing the vehicle to move forward a predetermined amount, as suggested and taught by Russell, with a reasonable expectation of success, for the purpose of providing a detection system configured to detect objects in an environment of the autonomous vehicle, and one or more computing devices in communication with the detection system, thus improving safety and providing a more efficient self-driving system that does not need to recalculate paths as often due to the object behavior being different from what was predicted. In addition, the self-driving system may adjust predictions quicker and react quicker to the objects in its vicinity.
Claim 33 is similarly rejected as Claim 25, see above.
Claims 26 and 34 are rejected under 35 U.S.C. 103 over Browning (US 20180005407) in view of Russell (US 20200192365) and KIM (US 20190056749).
Claim 26, Browning discloses the method of claim 21, but is silent to wherein generating the updated path for the vehicle to travel comprises causing the vehicle to advance a portion of the vehicle beyond an object in the environment.
However, Kim discloses a method of generating a route for a vehicle to depart from a parked state based on measured object information. The present disclosure may further provide a method of securing the safety of a user by controlling a door of a vehicle based on object information [see p0009].
Further, the controller 850 may determine whether it is possible to generate a route to an empty space between the objects OB1423 and OB1424, when the object OB1423 and OB1424 exist in the route through which the vehicle performs parking out by moving forward. The controller 850 may determine whether the object OB1423 and OB1424 exists in the space occupied by the vehicle 100 when moving forward, based on the information related to the object OB1423 and OB1424.
For example, the controller 850 may determine whether the object OB1423 and OB1424 exists in the space occupied by the vehicle 100 when moving forward, based on the cross section having the largest area among the cross section perpendicular to the traveling direction of the vehicle 100.
When it is determined that the object OB1423 and OB1424 does not exist in the space occupied by the vehicle 100 when moving forward and a route to an empty space between the objects OB1423 and OB1424 can be generated, the controller 850 may generate a route A1440 through which the vehicle 100 steers to perform parking out. When there is a moving object OB1423, the controller 850 may determine whether it is possible to generate a route to an empty space between the objects OB1423 and OB1424, based on distance and speed information with respect to the moving object OB1423. T
The controller 850 may determine whether the moving object OB1423 enters into the space occupied when moving forward and the entering time, based on the distance and the speed information with respect to the moving object OB1423 The controller 850 may determine whether it is possible to generate a route to an empty space between the objects OB1423 and OB1424, based on information on whether the moving object OB1423 enters into the space occupied when moving forward and the entering time [see p0464 – o0469 and Fig 14B].
It would have been obvious before the effective date of the claimed invention to one of ordinary skill in the art to modify the device in Browning as modified to include wherein generating the updated path for the vehicle to travel comprises causing the vehicle to advance a portion of the vehicle beyond an object in the environment, as suggested and taught by Kim, with a reasonable expectation of success, for the purpose of providing a system to determine whether the object is located in a space through which the vehicle passes based on the vehicle traveling in a forward direction.
Claim 34 is similarly rejected as Claim 26, see above.
Claims 27 and 35 are rejected under 35 U.S.C. 103 over Browning (US 20180005407) in view of Russell (US 20200192365) and Karasev (US 20200272148).
Claim 27, Browning discloses the method of claim 21, but is silent to wherein generating the updated path for the vehicle to travel comprises causing the vehicle to move forward an amount corresponding to a change in dimensions of an object based on the sensor data.
However, Karasev discloses a non-limiting list of objects may include obstacles in an environment, including but not limited to pedestrians, animals, cyclists, trucks, motorcycles, other vehicles, or the like. Such objects in the environment have a “geometric pose” (which may also be referred to herein as merely “pose”) comprising a location and/or orientation of the overall object relative to a frame of reference. In some examples, pose may be indicative of a position of an object (e.g., pedestrian), an orientation of the object, or relative appendage positions of the object. Geometric pose may be described in two-dimensions (e.g., using an x-y coordinate system) or three-dimensions (e.g., using an x-y-z or polar coordinate system), and may include an orientation (e.g., roll, pitch, and/or yaw) of the object [see p0009].
Further teaching, a prediction system of a computing device of the autonomous vehicle can include a machine learning model trained to output data that can be used to generate one or more predicted trajectories of objects proximate to the autonomous vehicle. For example, the machine learning model can output coordinates (e.g., x-coordinates and y-coordinates) associated with the object (e.g., a third-party vehicle) at one or more times in the future (e.g., 1 second, 2 seconds, 3 seconds, etc.). In some examples, the machine learning model can output coordinates associated with the object as well as probability information associated with each coordinate [see at least p0016].
It would have been obvious before the effective date of the claimed invention to one of ordinary skill in the art to modify the device in Browning as modified to include, wherein generating the updated path for the vehicle to travel comprises causing the vehicle to move forward an amount corresponding to a change in dimensions of an object based on the sensor data, as suggested and taught by Karasev, with a reasonable expectation of success, for the purpose of providing a perception system for the autonomous vehicle to recognize objects in the environment so that the autonomous vehicle can plan a safe route through the environment.
Claim 35 is similarly rejected as Claim 27, see above.
Claims 28 and 36 are rejected under 35 U.S.C. 103 over Browning (US 20180005407) in view of Russell (US 20200192365) and Jafari Tafti (US 20180348767).
Claim 28, Browning discloses the method of claim 21, but is silent to wherein generating the updated path for the vehicle to travel comprises generating an updated driving plan that causes the vehicle to change lanes.
However, Jafari Tafti discloses a processor-implemented method for automated driving of a vehicle includes the steps of receiving, by one or more data processors, vehicle state data, map data, and vehicle object environment data, generating, by the one or more data processors, a first trajectory path that is optimal with respect to the vehicle state data, the map data, and the vehicle object environment data, determining, by the one or more data processors [see Summary].
Further disclosing, FIG. 4 illustrates components of a trajectory refining system 112 which may be embedded within the controller 34. Inputs to the trajectory refining system 112 may be received from the trajectory planning system 100, the sensor system 28, other control modules (not shown) associated with the autonomous vehicle 10, the communication system 36, and/or determined/modeled by other sub-modules (not shown) within the controller 34. Threat assessment module 118 reviews and checks the updated trajectory for possible collisions with obstacles and/or vehicles. Checking the updated trajectory includes reviewing sensor data received from the sensor fusion module 102 for possible collisions with detected obstacles and/or vehicles. For example, the module 122 can generate a lane change trajectory, if needed. The updated trajectories generated by modules 120, 122 are also reviewed and checked by the threat assessment module 118 for possible collisions with obstacles and/or vehicles [see Fig 4, p0066 – p0068, p0082].
It would have been obvious before the effective date of the claimed invention to one of ordinary skill in the art to modify the device in Browning as modified to include, but is silent to wherein generating the updated path for the vehicle to travel comprises generating an updated driving plan that causes the vehicle to change lanes, as suggested and taught by Jafari Tafti, with a reasonable expectation of success, for the purpose of providing trajectory planning that improves the computational efficiency of trajectory planning to generate a safe and feasible trajectory that satisfies the known constraints.
Claim 36 is similarly rejected as Claim 28, see above.
Response to Arguments
Applicant’s arguments with respect to all claim(s) have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
The examiner has pointed out particular references contained in the prior art of record in the body of this action for the convenience of the applicant. Although the specified citations are representative of the teachings in the art and are applied to the specific limitations within the individual claim, other passages and figures may apply as well. Applicant should consider the entire prior art as applicable as to the limitations of the claims. It is respectfully requested from the applicant, in preparing the response, to consider fully the entire references as potentially teaching all or part of the claimed invention, as well as the context of the passage as taught by the prior art or disclosed by the examiner.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to RENEE LAROSE whose telephone number is (313)446-4856. The examiner can normally be reached on Monday - Friday 8:30am - 5:00pm EST.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Abby Lin can be reached on (571) 270-3976. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/Renee LaRose/Examiner, Art Unit 3657
/SOHANA TANJU KHAYER/Primary Examiner, Art Unit 3657
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