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 .
DETAILED ACTION
This action is responsive to the amendment filed with RCE on 04/09/2026 (claimed foreign priority date 07/16/2021):
Claims 11 and 13-20 have been examined.
Claims 1-10 and 12 have been canceled by Applicant.
Claims 11, 13 and 15-20 have been amended by Applicant.
Legend: “Under BRI” = “under broadest reasonable interpretation;”
“[Prior Art/Analogous/Non-Analogous Art Reference] discloses through the invention” means “See/read entire document;” Paragraph [No..] = e.g., Para [0005] = paragraph 5; P = page, e.g., p4 = page 4; C = column, e.g. c3 = column 3;
Ln = line, e.g., ln25 = line 25; ln25-36 = lines 25 through 36.
Response to Amendment
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 (i.e., changing from AIA to pre-AIA ) 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.
1. Claims 11 and 13-20 are rejected under 35 U.S.C. 103 as being unpatentable over Amacker (US20200118425) in view of Viente (US20220067209).
As per claim 11, Amacker discloses through the invention (see entire document), a method for monitoring a region surrounding a first vehicle (see entire document, teaching these limitations/features particularly in abstract, Para [0048, 0058]), the method comprising:
receiving sensor data from at least one sensor of an assistance system of the first vehicle which describe the region surrounding the first vehicle at a measurement time (see entire document, particularly abstract, fig. 3, Para [0007, 0038, 0042, 0050, 0058, 0076-0084] – teaching acquisition module 220 that acquires sensor data from at least one infrastructure sensor 280 associated with the roadway segment at which the infrastructure system is situated; the acquisition module 220 that periodically acquires the sensor data 250, as taught in Para [0042] for example);
transmitting environmental model data from a data exchange device to the assistance system, wherein the environmental model data describe at least one part of the region surrounding the first vehicle (see entire document, teaching these limitations/features particularly in abstract, fig. 2, Para [0006-0007, 0013, 0019-0021, 0025, 0036, 0038-0056, 0060-0062, 0067-0070, 0076, 0078, 0082, 0084, 0094, 0102]); and
detecting vulnerable road users in the surrounding region on the basis of the sensor data and the environmental model data (see entire document, particularly abstract, fig. 5, Para [0021, 0039, 0063, 0066-0070] – teaching other hazards (e.g., erratic pedestrians, animals),
wherein
the environmental model data are continuously generated by the data exchange device and transmitted to the assistance system (see entire document, teaching these limitations/features particularly in Para [0047-0050, 0058]),
the environmental model data are generated such that they describe only static objects in the at least one part of the surrounding region (see entire document, teaching these limitations/features particularly in Para [0006, 0020, 0047-0052]),
the environmental model data are generated by the data exchange device using sensor data from environmental sensor of other vehicles, wherein the sensor data from other vehicles was transmitted to the data exchange device from the other vehicles and were recorded within a recording period prior to transmitting the environmental model data from the data exchange device to the assistance system of the first vehicle (see entire document, teaching these limitations/features particularly in fig. 1-2, 5-6, Para [0002-0003, 0055-0056, 0080, 0094] – teaching sensors of the vehicle that acquire the sensor data for a constrained time period when approaching a road segment (e.g., intersection, merge, etc.); vehicles equipped with sensors that facilitate perceiving other vehicles, obstacles, pedestrians, and additional aspects of a surrounding environment; the context module 230 that uses information communicate from the vehicles to confirm, label, or otherwise supplement observations of the infrastructure system 200; context module 230 that stores the roadway context 260 in an electronic storage medium for subsequent use, electronically communicates the roadway context 260 to one or more nearby vehicles, uses the roadway context 260 as a comparison against known elements to further train the learning module, and so on; sensor system 120 that acquires data of at least a portion of the external environment of the vehicle 100 (e.g., nearby vehicles); autonomous driving module(s) 160 that determine the location of obstacles, obstacles, or other environmental features including traffic signs, trees, shrubs, neighboring vehicles, pedestrians, etc.);
the detection of the vulnerable road users comprises the assistance system of the first vehicle determining characteristic distinguishing features between the sensor data from the at least one sensor of the assistance system of the first vehicle and the environmental model data (see entire document, teaching these limitations/features particularly in Para [0038, 0067]); and
wherein the method further comprises performing at least a partially automated driving function based at least in part on the detection of the vulnerable road users (see entire document, teaching these limitations/features particularly in fig. 1, Para [0071-0072, 0090] – teaching processor(s) 110, the infrastructure module 170, and/or the autonomous driving module(s) 160 operable to control the navigation and/or maneuvering of the vehicle 100 by controlling one or more of the vehicle systems 140 and/or components thereof).
Amacker does not explicitly disclose through the invention sensor data from at least one environmental sensor of each of at least two other vehicles that was transmitted to data exchange device from the at least two other vehicles and were recorded within a recording period prior to transmitting the environmental model data from the data exchange device to the assistance system of the first vehicle.
However, Viente discloses these limitations/features through the invention (see entire document), particularly in fig. 12, Para [0245-0252] – teaching server that uses one or more criteria for determining whether new data received from the vehicles should trigger an update to the model or trigger creation of new data; when the new data indicates that a previously recognized landmark at a specific location no longer exists, or is replaced by another landmark, the server that determine that the new data should trigger an update to the model; when the new data indicates that a road segment has been closed, and when this has been corroborated by data received from other vehicles, the server that determines that the new data should trigger an update to the model; the remote server that collects trajectories and landmarks from multiple clients (e.g., vehicles that travel along a common road segment); the server that matches curves using landmarks and creates an average road model based on the trajectories collected from the multiple vehicles; each vehicle that communicates with a remote server 1230 via one or more networks (e.g., over a cellular network and/or the Internet, etc.) through wireless communication paths 1235, as indicated by the dashed lines; each vehicle that transmits data to server 1230 and receives data from server 1230; server 1230 that collects data from multiple vehicles travelling on the road segment 1200 at different times, and that processes the collected data to generate an autonomous vehicle road navigation model, or an update to the model.
It would have been obvious to one of ordinary skill in the art, who is also a person of ordinary creativity, not an automation, before the effective filing date of the claimed invention, to modify the teaching of Amacker by incorporating, applying and utilizing the above steps, technique and features as taught by Viente who is in the same field of endeavor. A person of ordinary skill, ordinary creativity would have been motivated to do so, with a reasonable expectation of success, for the purpose of and/or in order to provide a navigational response based on, for example, an analysis of images captured by one or more of the cameras (see entire Viente document, particularly Para [0004]); to enhance a server-based system for processing vehicle navigation information for use in autonomous vehicle navigation (see entire Viente document, particularly Para [0006]).
Claim 12 canceled.
As per claim 13, Amacker further discloses through the invention (see entire document), measurement time of the sensor data from the at least one sensor of the assistance system of the first vehicle that temporally follows the recording period of the data from the at least two further sources (see entire document, teaching these limitations/features particularly in Para [0005-0006, 0018, 0019, 0028-0029, 0031, 0033, 0036, 0038].).
As per claim 14, Amacker further discloses through the invention (see entire document), recording period of the data from the at least two further sources within a predetermined maximum period (see entire document, teaching these limitations/features particularly in Para [0005-0006, 0018, 0019, 0028-0029, 0031, 0033]).
As per claim 15, Amacker further discloses through the invention (see entire document), when determining the characteristic distinguishing features for detecting the vulnerable road users, shapes and contours derived from the environmental model data compared with shapes and contours derived from the sensor data from the at least one sensor of the assistance system of the first vehicle. (see entire document, teaching these limitations/features particularly in fig. 5, Para [0021, 0038-0039, 0063, 0066-0070]).
As per claim 16, Amacker does not explicitly disclose through the invention, or is missing a confidence value for one of the vulnerable road users, which is determined during object detection inside the first vehicle, increased when a vulnerable road user described by the sensor data is located between the sensor and an object described by the environmental model data, wherein the object described by the environmental model data is at most partially described by the sensor data.
However, Viente discloses these limitations/features through the invention (see entire document), particularly in Para [0146, 0150, 0160, 0316] – teaching executing stereo image analysis module 404 to detect candidate objects (e.g., vehicles, pedestrians, road marks, traffic lights, road hazards, etc.) within the first and second plurality of images, filter out a subset of the candidate objects based on various criteria, and perform multi-frame analysis, construct measurements, and determine a confidence level for the remaining candidate objects.
It would have been obvious to one of ordinary skill in the art, who is also a person of ordinary creativity, not an automation, before the effective filing date of the claimed invention, to modify the teaching of Amacker by incorporating, applying and utilizing the above steps, technique and features as taught by Viente who is in the same field of endeavor. A person of ordinary skill, ordinary creativity would have been motivated to do so, with a reasonable expectation of success, for the purpose of and/or in order to provide a navigational response based on, for example, an analysis of images captured by one or more of the cameras (see entire Viente document, particularly Para [0004]); to enhance a server-based system for processing vehicle navigation information for use in autonomous vehicle navigation (see entire Viente document, particularly Para [0006]).
As per claim 17, Amacker does not explicitly disclose through the invention, or is missing a characteristic distinguishing features between the sensor data and the environmental model data for detecting the vulnerable road users not determined when a confidence value for a vulnerable road user, which is determined during object detection inside the first vehicle, exceeds a predefined plausibility threshold value.
However, Viente discloses these limitations/features through the invention (see entire document), particularly in Para [0139, 0146, 0150, 0156-0157, 0160, 0124, 0266, 0276, 0316, 0318, 0336, 0344, 0369].
It would have been obvious to one of ordinary skill in the art, who is also a person of ordinary creativity, not an automation, before the effective filing date of the claimed invention, to modify the teaching of Amacker by incorporating, applying and utilizing the above steps, technique and features as taught by Viente who is in the same field of endeavor. A person of ordinary skill, ordinary creativity would have been motivated to do so, with a reasonable expectation of success, for the purpose of and/or in order to provide a navigational response based on, for example, an analysis of images captured by one or more of the cameras (see entire Viente document, particularly Para [0004]); to enhance a server-based system for processing vehicle navigation information for use in autonomous vehicle navigation (see entire Viente document, particularly Para [0006]).
As per claim 18, Amacker discloses through the invention (see entire document), an assistance system for a first vehicle for monitoring a region surrounding the first vehicle (see entire document, teaching these limitations/features particularly in abstract, Para [0048, 0058]), comprising:
a sensor for providing sensor data which describe the region surrounding the first vehicle at a measurement time (see entire document, teaching these limitations/features particularly in abstract, fig. 3, Para [0007, 0038, 0042, 0050, 0058, 0076-0084]);
a communication apparatus for receiving environmental model data from a data exchange device, wherein the environmental model data describe at least one part of the region surrounding the first vehicle (see entire document, teaching these limitations/features particularly in abstract, fig. 2, Para [0006-0007, 0013, 0019-0021, 0025, 0036, 0038-0056, 0060-0062, 0067-0070, 0076, 0078, 0082, 0084, 0094, 0102]);
wherein the environmental model data are generated such that they describe only static objects in the at least one part of the surrounding region (see entire document, teaching these limitations/features particularly in Para [0006, 0020, 0047-0052]), and
the environmental model data are generated by the data exchange device using sensor data from environmental sensor of other vehicles, wherein the sensor data from other vehicles was transmitted to the data exchange device from the other vehicles and were recorded within a recording period prior to transmitting the environmental model data from the data exchange device to the assistance system of the first vehicle (see entire document, teaching these limitations/features particularly in fig. 1-2, 5-6, Para [0002-0003, 0055-0056, 0080, 0094] – teaching sensors of the vehicle that acquire the sensor data for a constrained time period when approaching a road segment (e.g., intersection, merge, etc.); vehicles equipped with sensors that facilitate perceiving other vehicles, obstacles, pedestrians, and additional aspects of a surrounding environment; the context module 230 that uses information communicate from the vehicles to confirm, label, or otherwise supplement observations of the infrastructure system 200; context module 230 that stores the roadway context 260 in an electronic storage medium for subsequent use, electronically communicates the roadway context 260 to one or more nearby vehicles, uses the roadway context 260 as a comparison against known elements to further train the learning module, and so on; sensor system 120 that acquires data of at least a portion of the external environment of the vehicle 100 (e.g., nearby vehicles); autonomous driving module(s) 160 that determine the location of obstacles, obstacles, or other environmental features including traffic signs, trees, shrubs, neighboring vehicles, pedestrians, etc.); and
a control unit (see entire document, teaching these limitations/features particularly in fig. 1, Para [0090]) configured to:
detect vulnerable road users in the surrounding region on the basis of the sensor data and the environmental model data, wherein the detection of the vulnerable road users comprises determining characteristic distinguishing features between the sensor data from the at least one sensor of the assistance system of the first vehicle and the environmental model data (see entire document, teaching these limitations/features particularly in Para [0038, 0067]); and
perform at least a partially automated driving function based at least in part on the detection of the vulnerable road users (see entire document, teaching these limitations/features particularly in fig. 1, Para [0071-0072, 0090] – teaching processor(s) 110, the infrastructure module 170, and/or the autonomous driving module(s) 160 operable to control the navigation and/or maneuvering of the vehicle 100 by controlling one or more of the vehicle systems 140 and/or components thereof).
Amacker does not explicitly disclose through the invention sensor data from at least one environmental sensor of each of at least two other vehicles that was transmitted to data exchange device from the at least two other vehicles and were recorded within a recording period prior to transmitting the environmental model data from the data exchange device to the assistance system of the first vehicle.
However, Viente discloses these limitations/features through the invention (see entire document), particularly in fig. 12, Para [0245-0252] – teaching server that uses one or more criteria for determining whether new data received from the vehicles should trigger an update to the model or trigger creation of new data; when the new data indicates that a previously recognized landmark at a specific location no longer exists, or is replaced by another landmark, the server that determine that the new data should trigger an update to the model; when the new data indicates that a road segment has been closed, and when this has been corroborated by data received from other vehicles, the server that determines that the new data should trigger an update to the model; the remote server that collects trajectories and landmarks from multiple clients (e.g., vehicles that travel along a common road segment); the server that matches curves using landmarks and creates an average road model based on the trajectories collected from the multiple vehicles; each vehicle that communicates with a remote server 1230 via one or more networks (e.g., over a cellular network and/or the Internet, etc.) through wireless communication paths 1235, as indicated by the dashed lines; each vehicle that transmits data to server 1230 and receives data from server 1230; server 1230 that collects data from multiple vehicles travelling on the road segment 1200 at different times, and that processes the collected data to generate an autonomous vehicle road navigation model, or an update to the model.
It would have been obvious to one of ordinary skill in the art, who is also a person of ordinary creativity, not an automation, before the effective filing date of the claimed invention, to modify the teaching of Amacker by incorporating, applying and utilizing the above steps, technique and features as taught by Viente who is in the same field of endeavor. A person of ordinary skill, ordinary creativity would have been motivated to do so, with a reasonable expectation of success, for the purpose of and/or in order to provide a navigational response based on, for example, an analysis of images captured by one or more of the cameras (see entire Viente document, particularly Para [0004]); to enhance a server-based system for processing vehicle navigation information for use in autonomous vehicle navigation (see entire Viente document, particularly Para [0006]).
As per claim 19, Amacker discloses through the invention (see entire document), a data exchange device, comprising:
a computing apparatus for continuously generating environmental model data which describe only static objects in at least one part of a region surrounding a first vehicle (see entire document, teaching these limitations/features particularly in Para [0006, 0020, 0047-0052]),
wherein the environmental model data are generated by the data exchange device using sensor data from environmental sensor of other vehicles, wherein the sensor data from other vehicles was transmitted to the data exchange device from the other vehicles and were recorded within a recording period prior to transmitting the environmental model data from the data exchange device to the assistance system of the first vehicle (see entire document, teaching these limitations/features particularly in fig. 1-2, 5-6, Para [0002-0003, 0055-0056, 0080, 0094] – teaching sensors of the vehicle that acquire the sensor data for a constrained time period when approaching a road segment (e.g., intersection, merge, etc.); vehicles equipped with sensors that facilitate perceiving other vehicles, obstacles, pedestrians, and additional aspects of a surrounding environment; the context module 230 that uses information communicate from the vehicles to confirm, label, or otherwise supplement observations of the infrastructure system 200; context module 230 that stores the roadway context 260 in an electronic storage medium for subsequent use, electronically communicates the roadway context 260 to one or more nearby vehicles, uses the roadway context 260 as a comparison against known elements to further train the learning module, and so on; sensor system 120 that acquires data of at least a portion of the external environment of the vehicle 100 (e.g., nearby vehicles); autonomous driving module(s) 160 that determine the location of obstacles, obstacles, or other environmental features including traffic signs, trees, shrubs, neighboring vehicles, pedestrians, etc.); and
a transmitting apparatus for transmitting the environmental model data to an assistance system of the first vehicle (see entire document, teaching these limitations/features particularly in abstract, fig. 2, Para [0006-0007, 0013, 0019-0021, 0025, 0036, 0038-0056, 0060-0062, 0067-0070, 0076, 0078, 0082, 0084, 0094, 0102]),
wherein the assistance system of the first vehicle detects vulnerable road users in a surrounding region of the first vehicle on a basis of sensor data from the at least one sensor of the assistance system of the first vehicle and the environmental model data (see entire document, particularly abstract, fig. 5, Para [0021, 0039, 0063, 0066-0070] – teaching other hazards (e.g., erratic pedestrians, animals),
wherein the assistance system of the first vehicle performs at least a partially automated driving function based at least in part on the detection of the vulnerable road users (see entire document, teaching these limitations/features particularly in fig. 1, Para [0071-0072, 0090] – teaching processor(s) 110, the infrastructure module 170, and/or the autonomous driving module(s) 160 operable to control the navigation and/or maneuvering of the vehicle 100 by controlling one or more of the vehicle systems 140 and/or components thereof).
Amacker does not explicitly disclose through the invention sensor data from at least one environmental sensor of each of at least two other vehicles that was transmitted to data exchange device from the at least two other vehicles and were recorded within a recording period prior to transmitting the environmental model data from the data exchange device to the assistance system of the first vehicle.
However, Viente discloses these limitations/features through the invention (see entire document), particularly in fig. 12, Para [0245-0252] – teaching server that uses one or more criteria for determining whether new data received from the vehicles should trigger an update to the model or trigger creation of new data; when the new data indicates that a previously recognized landmark at a specific location no longer exists, or is replaced by another landmark, the server that determine that the new data should trigger an update to the model; when the new data indicates that a road segment has been closed, and when this has been corroborated by data received from other vehicles, the server that determines that the new data should trigger an update to the model; the remote server that collects trajectories and landmarks from multiple clients (e.g., vehicles that travel along a common road segment); the server that matches curves using landmarks and creates an average road model based on the trajectories collected from the multiple vehicles; each vehicle that communicates with a remote server 1230 via one or more networks (e.g., over a cellular network and/or the Internet, etc.) through wireless communication paths 1235, as indicated by the dashed lines; each vehicle that transmits data to server 1230 and receives data from server 1230; server 1230 that collects data from multiple vehicles travelling on the road segment 1200 at different times, and that processes the collected data to generate an autonomous vehicle road navigation model, or an update to the model.
It would have been obvious to one of ordinary skill in the art, who is also a person of ordinary creativity, not an automation, before the effective filing date of the claimed invention, to modify the teaching of Amacker by incorporating, applying and utilizing the above steps, technique and features as taught by Viente who is in the same field of endeavor. A person of ordinary skill, ordinary creativity would have been motivated to do so, with a reasonable expectation of success, for the purpose of and/or in order to provide a navigational response based on, for example, an analysis of images captured by one or more of the cameras (see entire Viente document, particularly Para [0004]); to enhance a server-based system for processing vehicle navigation information for use in autonomous vehicle navigation (see entire Viente document, particularly Para [0006]).
As per claim 20, Amacker discloses through the invention (see entire document), a system for monitoring a region surrounding a first vehicle (see entire document, teaching these limitations/features particularly in abstract, Para [0048, 0058]), comprising:
(i) an assistance system (see entire document, teaching these limitations/features particularly in abstract, Para [0048, 0058]), comprising:
a sensor for providing sensor data which describe the region surrounding the first vehicle at a measurement time (see entire document, teaching these limitations/features particularly in abstract, fig. 3, Para [0007, 0038, 0042, 0050, 0058, 0076-0084]);
a communication apparatus for receiving environmental model data, wherein the environmental model data describe at least one part of the region surrounding the first vehicle (see entire document, teaching these limitations/features particularly in abstract, fig. 2, Para [0006-0007, 0013, 0019-0021, 0025, 0036, 0038-0056, 0060-0062, 0067-0070, 0076, 0078, 0082, 0084, 0094, 0102]); and
a control unit (see entire document, teaching these limitations/features particularly in fig. 1, Para [0090]) configured to:
detect vulnerable road users in the surrounding region on the basis of the sensor data from the at least one sensor of the assistance system of the first vehicle and the environmental model data, wherein the detection of the vulnerable road users comprises determining characteristic distinguishing features between the sensor data from the at least one sensor of the assistance system of the first vehicle and the environmental model data (see entire document, teaching these limitations/features particularly in Para [0038, 0067]); and
perform at least a partially automated driving function based at least in part on the detection of the vulnerable road users (see entire document, teaching these limitations/features particularly in fig. 1, Para [0071-0072, 0090] – teaching processor(s) 110, the infrastructure module 170, and/or the autonomous driving module(s) 160 operable to control the navigation and/or maneuvering of the vehicle 100 by controlling one or more of the vehicle systems 140 and/or components thereof); and
(ii) a data exchange device, comprising:
a computing apparatus for continuously generating the environmental model data which describe only static objects in at least one part of a region surrounding the first vehicle (see entire document, teaching these limitations/features particularly in Para [0006, 0020, 0047-0052]),
wherein the environmental model data are generated by the data exchange device using sensor data from environmental sensor of other vehicles, wherein the sensor data from other vehicles was transmitted to the data exchange device from the other vehicles and were recorded within a recording period prior to transmitting the environmental model data from the data exchange device to the assistance system of the first vehicle (see entire document, teaching these limitations/features particularly in fig. 1-2, 5-6, Para [0002-0003, 0055-0056, 0080, 0094] – teaching sensors of the vehicle that acquire the sensor data for a constrained time period when approaching a road segment (e.g., intersection, merge, etc.); vehicles equipped with sensors that facilitate perceiving other vehicles, obstacles, pedestrians, and additional aspects of a surrounding environment; the context module 230 that uses information communicate from the vehicles to confirm, label, or otherwise supplement observations of the infrastructure system 200; context module 230 that stores the roadway context 260 in an electronic storage medium for subsequent use, electronically communicates the roadway context 260 to one or more nearby vehicles, uses the roadway context 260 as a comparison against known elements to further train the learning module, and so on; sensor system 120 that acquires data of at least a portion of the external environment of the vehicle 100 (e.g., nearby vehicles); autonomous driving module(s) 160 that determine the location of obstacles, obstacles, or other environmental features including traffic signs, trees, shrubs, neighboring vehicles, pedestrians, etc.); and
a transmitting apparatus for transmitting the environmental model data to the assistance system (see entire document, teaching these limitations/features particularly in abstract, fig. 2, Para [0006-0007, 0013, 0019-0021, 0025, 0036, 0038-0056, 0060-0062, 0067-0070, 0076, 0078, 0082, 0084, 0094, 0102]).
Amacker does not explicitly disclose through the invention sensor data from at least one environmental sensor of each of at least two other vehicles that was transmitted to data exchange device from the at least two other vehicles and were recorded within a recording period prior to transmitting the environmental model data from the data exchange device to the assistance system of the first vehicle.
However, Viente discloses these limitations/features through the invention (see entire document), particularly in fig. 12, Para [0245-0252] – teaching server that uses one or more criteria for determining whether new data received from the vehicles should trigger an update to the model or trigger creation of new data; when the new data indicates that a previously recognized landmark at a specific location no longer exists, or is replaced by another landmark, the server that determine that the new data should trigger an update to the model; when the new data indicates that a road segment has been closed, and when this has been corroborated by data received from other vehicles, the server that determines that the new data should trigger an update to the model; the remote server that collects trajectories and landmarks from multiple clients (e.g., vehicles that travel along a common road segment); the server that matches curves using landmarks and creates an average road model based on the trajectories collected from the multiple vehicles; each vehicle that communicates with a remote server 1230 via one or more networks (e.g., over a cellular network and/or the Internet, etc.) through wireless communication paths 1235, as indicated by the dashed lines; each vehicle that transmits data to server 1230 and receives data from server 1230; server 1230 that collects data from multiple vehicles travelling on the road segment 1200 at different times, and that processes the collected data to generate an autonomous vehicle road navigation model, or an update to the model.
It would have been obvious to one of ordinary skill in the art, who is also a person of ordinary creativity, not an automation, before the effective filing date of the claimed invention, to modify the teaching of Amacker by incorporating, applying and utilizing the above steps, technique and features as taught by Viente who is in the same field of endeavor. A person of ordinary skill, ordinary creativity would have been motivated to do so, with a reasonable expectation of success, for the purpose of and/or in order to provide a navigational response based on, for example, an analysis of images captured by one or more of the cameras (see entire Viente document, particularly Para [0004]); to enhance a server-based system for processing vehicle navigation information for use in autonomous vehicle navigation (see entire Viente document, particularly Para [0006]).
RELEVANT PRIOR ART THAT WAS CITED BUT NOT APPLIED
The following relevant prior art references that were found, by the Examiner while performing initial and/or additional search, cited but not applied:
Xiao (US20200026280) – (see entire Xiao document, particularly abstract – teaching a system and method for autonomously transporting and delivering one or more commodities from drop-off point to recipient preferred environment; the system configured to analyze an authorized person's voice command or request and executes the request; the system that provides at least two modes of operation to deliver the commodities comprising mapped location delivery mode and human following delivery mode; the system configured to analyze the command and extract the delivery location; the system further configured to identify the location of the point of the interest based on object detection system and environment understanding system, to deliver the commodities; at human following delivery mode, the ADV that follows the recipient and saves the location or path data once the preferred environment located; at mapped location delivery mode, ADV that maneuvers itself to the destination location by retrieving information on recipient's previous history of delivering commodities).
Response to Arguments
1. Applicant’s arguments with respect to claims 11 and 13-20 have been considered but are moot because the arguments do not apply to any of the references being used in the current rejection.
2. Applicant’s arguments with respect to claims 11 and 13-20 have been considered but are moot in view of the new ground(s) of rejection.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Primary Examiner YURI KAN, P.E., whose phone number is 571- 270-3978. The examiner can normally be reached on Monday – Friday.
If attempts to reach the examiner by phone are unsuccessful, you may contact the examiner's supervisor, Mr. Jelani Smith, who can be reached on 571-270-3969. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of an application may be obtained from the Patent Application Information Retrieval (PAIR) system. Status information for published applications may be obtained from either Private PAIR or Public PAIR. Status information for unpublished applications is available through Private PAIR only. For more information about the PAIR system, see http://pair-direct.uspto.gov. Should you have questions on access to the Private PAIR system, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free).
If you would like assistance from a USPTO Customer Service Representative or access to the automated information system, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/YURI KAN, P.E./Primary Examiner, Art Unit 3662
Prosecution Insights