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 Office action is in response to application filed on 5/14/2025. Claim(s) 1-20 is/are pending.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claim(s) 1-6 is/are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor, or for pre-AIA the applicant regards as the invention.
Claim(s) 1 recite(s) the limitation “wherein the pre-installed sensors are configured to remotely control the one or more vehicles within the operating area”. This limitation is unclear and thus, the claim(s) is/are indefinite. Applicant’s specification describes that sensor data is sent to a central unit which then sends control commands to a vehicle’s control unit based on the sensor data [0026]. However, this is not what is claimed. At the time of filing, sensors were not understood to be capable of controlling vehicle, and thus, the claim is indefinite. For the purposes of examination, the examiner is interpreting the scope of the limitation to be that “the one or more vehicles” are remotely controlled “within the operating area” based on data from the “pre-installed sensors”.
Dependent claims inherit rejections of the claims they depend upon.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale or otherwise available to the public before the effective filing date of the claimed invention.
Claim(s) 7, 10-11 is/are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Chiba et al. (US 20240400102 A1).
Regarding claim 7, Chiba teaches A system for remote control of one or more vehicles, the system comprising:
one or more surveillance cameras (“camera 10”, Fig. 1) configured to capture images of an operating area (“At least one camera 10 is installed in a space where the vehicle 40 is conveyed.”, [0020], “the first sensor is a stationary camera”, [0054], “The server 30 transmits a control instruction for causing the vehicle 40 to travel by itself to the vehicle 40.”, [0022]); and
a central control unit (“server 30”, Fig. 1) configured to:
receive one or more images from the one or more surveillance cameras (“the camera 10 that acquires an image of the vehicle 40 as the spatial information of the vehicle 40”, [0019], “Information on which the server 30 creates the control instruction is based is information on the position of the vehicle 40. The position of the vehicle 40 can be calculated from the spatial information of the vehicle 40.”, [0022]);
identify one or more vehicles in the one or more images (“The first vehicle position calculation unit 301 performs predetermined object recognition processing on the video acquired from the infrastructure camera 10 and recognizes the vehicle 40 included in the video.”, [0033], see also “When the vehicle 40 is in the imaging area CMR1, the server 30 can calculate the position of the vehicle 40 from the video.”, [0027]);
establish and maintain a connection, via one or more interfaces, with one or more engine control units (ECU) of the one or more vehicles (“The communication device 35 is wirelessly connected to a receiver 45 of the vehicle 40. The vehicle 40 includes an actuator control unit 401. The actuator control unit 401 controls the drive actuator, the brake actuator, and the steering actuator in accordance with the received control instruction.”, [0039]);
receive vehicle sensor data from the one or more vehicles (“when the first sensor is a stationary camera, the second sensor may be a vehicle LiDAR. A radar may be used as the second sensor. The radar may be installed or mounted on a vehicle.”, [0054]);
generate one or more paths based on the vehicle sensor data (“The server 30 transmits a control instruction for causing the vehicle 40 to travel by itself to the vehicle 40.”, [0022], “The control instruction can be generated using at least one of the position of the vehicle 40 calculated from the video acquired by the camera 10 (hereinafter, may be referred to as a first vehicle position) and the position of the vehicle 40 calculated from the three-dimensional information acquired by the LiDAR 20 (hereinafter, may be referred to as a second vehicle position).”, [0025], “When the vehicle 40 advances to the scanning region LDR, the server 30 can calculate the position of the vehicle 40 from the three-dimensional information. When the vehicle 40 has advanced to the imaging area CMR2, the server 30 can calculate the position of the vehicle 40 from the video again. In the present embodiment, the server 30 generates the control instruction based on one of the first vehicle position and the second vehicle position.”, [0027); and
remotely control the one or more vehicles along the one or more paths (“The vehicle 40 may include a remote driving kit for realizing remote manual driving by a remote operator. If the vehicle 40 is provided with a remote operation kit, the conveyance of the vehicle 40 may be switched from self-propelled conveyance by transmission of a control instruction to conveyance by remote manual operation when the positional deviation is outside the allowable range.”, [0052]).
Regarding claim 10, Chiba teaches The system of claim 7, wherein the one or more surveillance cameras are configured to generate one or more video streams, wherein the one or more video streams are transmitted to the central control unit, and wherein generating one or more paths is additionally based upon the one or more video streams (“the server 30 receives the video as the first spatial information from the camera 10”, [0022], “The control instruction can be generated using at least one of the position of the vehicle 40 calculated from the video acquired by the camera 10 (hereinafter, may be referred to as a first vehicle position)”, [0025]).
Regarding claim 11, Chiba teaches The system of claim 7, wherein the central control unit is further configured to:
establish connections with one or more vehicles; and
initialize and receive sensor data and/or video streams from the one or more vehicles (“As represented by the flow F100, in the camera 10, step S101 is executed. In step S101, a video including the vehicle 40 is acquired. The acquired video is transmitted to the server 30.”, [0043], “the second sensor may be a vehicle LiDAR.”, [0054]).
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.
The factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied 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.
Claim(s) 8 is/are rejected under 35 U.S.C. 103 as being unpatentable over Chiba et al. (US 20240400102 A1) in view of Chen et al. (US 20190212749 A1).
Regarding claim 8, Chiba teaches The system of claim 7,
However, Chen teaches
wherein the vehicle sensor data is received from one or more vehicle sensors with an ASIL-B level (“The camera types for the cameras may include, but are not limited to, digital cameras that may be adapted for use with the components and/or systems of the vehicle 140. The camera(s) may operate at automotive safety integrity level (ASIL) B”, [0166], “The vehicle 140 may further include RADAR sensor(s) 860. The RADAR sensor(s) 860 may be used by the vehicle 140 for long-range vehicle detection, even in darkness and/or severe weather conditions. RADAR functional safety levels may be ASIL B.”, [0227], “The ultrasonic sensor(s) 862 may operate at functional safety levels of ASIL B.”, [0231], “The LIDAR sensor(s) 864 may be functional safety level ASIL B.”, [0232]).
Thus, it would have been obvious to one of ordinary skill in the art before the effective filing date to modify the invention of Chiba with the teachings of Chen such that the one or more vehicle sensors of Chiba have an ASIL-B level, as suggested by Chen, with a reasonable expectation of success. The motivation for doing so would be to guarantee the vehicle sensors are operated at a predetermined level of safety, as suggested by Chen (see citations of Chen above).
Claim(s) 1, 4, 6, 9, 12, 14, 16-18, 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Chiba et al. (US 20240400102 A1) in view of Hazelton et al. (US 20160231746 A1).
Regarding claim 12, Chiba teaches The system of claim 7,
However, Hazelton teaches
wherein the central control unit is further configured to receive a map of the operating area (“A variety of data sources can be used for the central map database. For example, the Waze application provides navigational mapping for vehicles. Such navigational maps include transient information about travel conditions and hazards uploaded by individual users. Such maps can also extract location and speed information from computing devices located within the vehicle, such as a smart phone, and assess traffic congestion by comparing the speed of various vehicles to the posted speed limit for a designated section of roadway.”, [0263], see also [0173]).
Thus, it would have been obvious to one of ordinary skill in the art before the effective filing date to modify the invention of Chiba with the teachings of Hazelton such that the central control unit of Chiba is further configured to receive a map of the operating area, as suggested by Hazelton, with a reasonable expectation of success. The motivation for doing so would be to allow the central control unit to “to identify other vehicles, to identify potential hazards” [0261], as taught by Hazelton.
Regarding claim 14, Chiba teaches A method for remote control of one or more vehicles, the method comprising:
receiving sensor data from one or more sensors installed in an operating area (“the camera 10 that acquires an image of the vehicle 40 as the spatial information of the vehicle 40”, [0019], “At least one camera 10 is installed in a space where the vehicle 40 is conveyed.”, [0020], “the first sensor is a stationary camera”, [0054], “The server 30 transmits a control instruction for causing the vehicle 40 to travel by itself to the vehicle 40…Information on which the server 30 creates the control instruction is based is information on the position of the vehicle 40. The position of the vehicle 40 can be calculated from the spatial information of the vehicle 40.”, [0022]);
identifying a vehicle of the one or more vehicles corresponding to the sensor data, thereby generating an identified vehicle (“The first vehicle position calculation unit 301 performs predetermined object recognition processing on the video acquired from the infrastructure camera 10 and recognizes the vehicle 40 included in the video.”, [0033], see also “When the vehicle 40 is in the imaging area CMR1, the server 30 can calculate the position of the vehicle 40 from the video.”, [0027]);
establishing and maintaining, via one or more interfaces with an engine control unit (ECU) of the identified vehicle, a connection with the identified vehicle (“The communication device 35 is wirelessly connected to a receiver 45 of the vehicle 40. The vehicle 40 includes an actuator control unit 401. The actuator control unit 401 controls the drive actuator, the brake actuator, and the steering actuator in accordance with the received control instruction.”, [0039]);
receiving vehicle sensor data from the identified vehicle (“when the first sensor is a stationary camera, the second sensor may be a vehicle LiDAR. A radar may be used as the second sensor. The radar may be installed or mounted on a vehicle.”, [0054]);
generating one or more paths based upon the vehicle sensor data, wherein generating the one or more paths is based on vehicle sensor data (“The server 30 transmits a control instruction for causing the vehicle 40 to travel by itself to the vehicle 40.”, [0022], “The control instruction can be generated using at least one of the position of the vehicle 40 calculated from the video acquired by the camera 10 (hereinafter, may be referred to as a first vehicle position) and the position of the vehicle 40 calculated from the three-dimensional information acquired by the LiDAR 20 (hereinafter, may be referred to as a second vehicle position).”, [0025], “When the vehicle 40 advances to the scanning region LDR, the server 30 can calculate the position of the vehicle 40 from the three-dimensional information. When the vehicle 40 has advanced to the imaging area CMR2, the server 30 can calculate the position of the vehicle 40 from the video again. In the present embodiment, the server 30 generates the control instruction based on one of the first vehicle position and the second vehicle position.”, [0027).
However, Hazelton teaches
wherein the one or more paths are based upon the vehicle sensor data corresponding to objects with a size below a predetermined cutoff size (“vehicle radar systems ignore small objects detected by the radar module 30A. By way of example and not limitation, small objects include curbs, lamp-posts, mail-boxes, and the like. For general navigation systems, these small objects are typically not relevant to determining when the next turn should be made an operator of the vehicle…the controller 120A may be configured to classify the object 16A as small when a magnitude of the reflection signal 112A associated with the object 16A is less than a signal-threshold. The system may also be configured to ignore an object classified as small if the object is well away from the roadway, more than five meters (5 m) for example.”, [0181]).
Thus, it would have been obvious to one of ordinary skill in the art before the effective filing date to modify the invention of Chiba with the teachings of Hazelton such that the generating of the one or more paths of Chiba is based on vehicle sensor data of objects of a size below a predetermined threshold, as suggested by Hazelton, with a reasonable expectation of success. The motivation for doing so would be to disregard objects that are not relevant to determining the navigation instruction of the vehicle, as taught by Hazelton [0181].
Regarding claim 1, Chiba teaches A system for remote control of one or more vehicles, the system comprising:
a sensor infrastructure, the sensor infrastructure comprising:
pre-installed sensors (“camera 10”, Fig. 1) in an operating area, wherein the pre-installed sensors are configured to remotely control the one or more vehicles within the operating area (“At least one camera 10 is installed in a space where the vehicle 40 is conveyed.”, [0020], “the first sensor is a stationary camera”, [0054], “The server 30 transmits a control instruction for causing the vehicle 40 to travel by itself to the vehicle 40.”, [0022])); and
a central control unit (“server 30”, Fig. 1) configured to:
receive infrastructure sensor data from the sensor infrastructure (“the camera 10 that acquires an image of the vehicle 40 as the spatial information of the vehicle 40”, [0019], “Information on which the server 30 creates the control instruction is based is information on the position of the vehicle 40. The position of the vehicle 40 can be calculated from the spatial information of the vehicle 40.”, [0022]);
identify the one or more vehicles based upon the infrastructure sensor data (“The first vehicle position calculation unit 301 performs predetermined object recognition processing on the video acquired from the infrastructure camera 10 and recognizes the vehicle 40 included in the video.”, [0033], see also “When the vehicle 40 is in the imaging area CMR1, the server 30 can calculate the position of the vehicle 40 from the video.”, [0027]);
establish and maintain a connection, via one or more interfaces, with one or more engine control units (ECU) of the one or more vehicles to be remotely controlled, thereby creating one or more connected vehicles (“The communication device 35 is wirelessly connected to a receiver 45 of the vehicle 40. The vehicle 40 includes an actuator control unit 401. The actuator control unit 401 controls the drive actuator, the brake actuator, and the steering actuator in accordance with the received control instruction.”, [0039]);
receive vehicle sensor data from the one or more connected vehicles (“when the first sensor is a stationary camera, the second sensor may be a vehicle LiDAR. A radar may be used as the second sensor. The radar may be installed or mounted on a vehicle.”, [0054]);
generate one or more paths for remotely controlling the one or more connected vehicles, wherein the one or more paths are based upon the vehicle sensor data(“The server 30 transmits a control instruction for causing the vehicle 40 to travel by itself to the vehicle 40.”, [0022], “The control instruction can be generated using at least one of the position of the vehicle 40 calculated from the video acquired by the camera 10 (hereinafter, may be referred to as a first vehicle position) and the position of the vehicle 40 calculated from the three-dimensional information acquired by the LiDAR 20 (hereinafter, may be referred to as a second vehicle position).”, [0025], “When the vehicle 40 advances to the scanning region LDR, the server 30 can calculate the position of the vehicle 40 from the three-dimensional information. When the vehicle 40 has advanced to the imaging area CMR2, the server 30 can calculate the position of the vehicle 40 from the video again. In the present embodiment, the server 30 generates the control instruction based on one of the first vehicle position and the second vehicle position.”, [0027); and
remotely control the one or more connected vehicles along the one or more paths (“The vehicle 40 may include a remote driving kit for realizing remote manual driving by a remote operator. If the vehicle 40 is provided with a remote operation kit, the conveyance of the vehicle 40 may be switched from self-propelled conveyance by transmission of a control instruction to conveyance by remote manual operation when the positional deviation is outside the allowable range.”, [0052]).
However, regarding claim 1, and similarly claims 9 and 17, Hazelton teaches
wherein the one or more paths are based upon the vehicle sensor data corresponding to objects having a size greater than a predetermined cutoff size (“The controller 120A may be configured or programmed to determine the object-location 128A of the object 16A on the map 122A of the area 18A based on the vehicle-location 126A of the vehicle 10A on the map 122A, the image signal 116A, and the reflection signal 112A. That is, the controller 120A may add details to the preprogrammed map in order to identify various objects to assist the system 110A avoid colliding with various objects and keep the vehicle 10A centered in the lane or roadway on which it is traveling. As mention before, prior radar based system may ignore small objects. However, in this example, the controller 120A classifies the object as small when the magnitude of the reflection signal 112A associated with the object 16A is less than a signal-threshold. Accordingly, small objects such as curbs, lamp-posts, mail-boxes, and the like can be remembered by the system 110A to help the system 110A safely navigate the vehicle 10A.”, [0182]).
Thus, it would have been obvious to one of ordinary skill in the art before the effective filing date to modify the invention of Chiba with the teachings of Hazelton such that the generating of the one or more paths of Chiba is based on vehicle sensor data of objects of a size greater than a predetermined threshold, as suggested by Hazelton, with a reasonable expectation of success. The motivation for doing so would be such that “small objects such as curbs, lamp-posts, mail-boxes, and the like can be remembered by the system…to help the system…safely navigate the vehicle” [0182], as taught by Hazelton [0181].
Regarding claim 4, Chiba in view of Hazelton teaches The system of claim 1, and Hazelton further teaches wherein the central control unit is further configured to determine a size of each of the objects (“the controller 120A may have further capabilities to estimate the parameters of the detected object(s) including, for example, the object position and velocity vectors, target size, and classification, e.g., vehicle verses pedestrian”, [0156]).
Thus, it would have been obvious to one of ordinary skill in the art before the effective filing date to further modify the invention of Chiba with the teachings of Hazelton such that the central control unit of Chiba is further configured to determine a size of each of the objects, as suggested by Hazelton, with a reasonable expectation of success. The motivation for doing so would be such that a server remote from the vehicle generating paths for the vehicle, as taught by Chiba, is able to disregard objects that are not relevant to determining the navigation instruction of the vehicle, as taught by Hazelton [0181].
Regarding claim 6, Chiba in view of Hazelton teaches The system of claim 1, and Chiba further teaches wherein the one or more paths are further based upon infrastructure sensor data corresponding to objects having a size greater than the predetermined cutoff size (“At least one camera 10 is installed in a space where the vehicle 40 is conveyed. Specifically, the camera 10 is disposed at a position where the camera 10 can look down on the conveyance route of the vehicle 40 from the departure place PI to the destination P2.”, [0020], “The server 30 transmits a control instruction for causing the vehicle 40 to travel by itself to the vehicle 40…Information on which the server 30 creates the control instruction is based is information on the position of the vehicle 40. The position of the vehicle 40 can be calculated from the spatial information of the vehicle 40. Therefore, the server 30 receives the video as the first spatial information from the camera 10”, [0022]).
Regarding claim 16, Chiba in view of Hazelton teaches The method of claim 14, and Chiba further teaches wherein the one or more sensors comprise one or more surveillance cameras (“At least one camera 10 is installed in a space where the vehicle 40 is conveyed.”, [0020], “the first sensor is a stationary camera”, [0054]), wherein the sensor data comprises one or more images (“first sensor included in the self-propelled conveyance system 2 is the camera 10 that acquires an image of the vehicle 40 as the spatial information of the vehicle 40”, [0019]), wherein the method of performed by a central control unit additionally configured to remotely control the vehicle along the one or more paths (“The server 30 transmits a control instruction for causing the vehicle 40 to travel by itself to the vehicle 40.”, [0022], (“The vehicle 40 may include a remote driving kit for realizing remote manual driving by a remote operator. If the vehicle 40 is provided with a remote operation kit, the conveyance of the vehicle 40 may be switched from self-propelled conveyance by transmission of a control instruction to conveyance by remote manual operation when the positional deviation is outside the allowable range.”, [0052]).
Regarding claim 18, Chiba in view of Hazelton teaches The method of claim 14, and Chiba further teaches wherein the method further comprises receiving one or more video streams from one or more one video cameras installed in the identified vehicle, and wherein generating one or more paths is additionally based upon the one or more video streams (“the server 30 receives the video as the first spatial information from the camera 10”, [0022], “The control instruction can be generated using at least one of the position of the vehicle 40 calculated from the video acquired by the camera 10 (hereinafter, may be referred to as a first vehicle position)”, [0025]).
Regarding claim 20, Chiba in view of Hazelton teaches The method of claim 14, and Chiba further teaches wherein the vehicle comprises a plurality of vehicles, and wherein the identified vehicle comprises a plurality of identified vehicles (“A self-propelled conveyance system that transports a vehicle by self-propelling is known. As a conventional technique related to the self-propelled conveyance system, for example, a technique disclosed in JP2022-134583A can be cited. JP2022-134583A discloses a technique for remotely controlling a plurality of micromobility vehicles traveling in an automatic operation area by a fixed infrastructure device. The fixed infrastructure device includes a LiDAR that detects a target in a detection range defined in the automatic operation area. The fixed infrastructure device generates a travel route of a micromobility vehicle traveling within the detection range using detection information of objects detected by the LiDAR, and transmits a control command based on the travel route to the micromobility vehicle.”, [0003]).
Chiba discloses in the Background a conveyance system for transporting a plurality of vehicles in an operation area. The invention of Chiba is directed to a conveyance system for transporting a vehicle in an operation area. It would have been obvious to one of ordinary skill in the art before the effective filing date that the invention of Chiba would be implemented in an operating area comprising a plurality of vehicles, with a reasonable expectation of success. The motivation for doing so would be to implement the method of Chiba “for remotely controlling a plurality of micromobility vehicles traveling in an automatic operation area” as suggested in the Background. This would achieve the predictable result of remote controlling multiple vehicles and would only require routine skill in the art. KSR International Co. v. Teleflex Inc. (KSR), 550 U.S. 398, 82 USPQ2d 1385 (2007)
Claim(s) 2, 5, 13, 15, 19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Chiba et al. (US 20240400102 A1) in view of Hazelton et al. (US 20160231746 A1) in view of Chen et al. (US 20190212749 A1).
Regarding claim 2, and similarly claim 15, Chiba in view of Hazelton teaches The system of claim 1,
However, Chen teaches
wherein the vehicle sensor data is received from one or more vehicle sensors with an ASIL-B level (“The camera types for the cameras may include, but are not limited to, digital cameras that may be adapted for use with the components and/or systems of the vehicle 140. The camera(s) may operate at automotive safety integrity level (ASIL) B”, [0166], “The vehicle 140 may further include RADAR sensor(s) 860. The RADAR sensor(s) 860 may be used by the vehicle 140 for long-range vehicle detection, even in darkness and/or severe weather conditions. RADAR functional safety levels may be ASIL B.”, [0227], “The ultrasonic sensor(s) 862 may operate at functional safety levels of ASIL B.”, [0231], “The LIDAR sensor(s) 864 may be functional safety level ASIL B.”, [0232]).
Thus, it would have been obvious to one of ordinary skill in the art before the effective filing date to modify the invention of Chiba in view of Hazelton with the teachings of Chen such that the one or more vehicle sensors of Chiba have an ASIL-B level, as suggested by Chen, with a reasonable expectation of success. The motivation for doing so would be to guarantee the vehicle sensors are operated at a predetermined level of safety, as suggested by Chen (see citations of Chen above).
Regarding claim 5, and similarly claim 19, Chiba in view of Hazelton teaches The system of claim 1, and Hazelton further teaches wherein the central control unit is further configured to receive a map of the operating area(“A variety of data sources can be used for the central map database. For example, the Waze application provides navigational mapping for vehicles. Such navigational maps include transient information about travel conditions and hazards uploaded by individual users. Such maps can also extract location and speed information from computing devices located within the vehicle, such as a smart phone, and assess traffic congestion by comparing the speed of various vehicles to the posted speed limit for a designated section of roadway.”, [0263], see also [0173]).
Thus, it would have been obvious to one of ordinary skill in the art before the effective filing date to further modify the invention of Chiba with the teachings of Hazelton such that the central control unit of Chiba is further configured to receive a map of the operating area, as suggested by Hazelton, with a reasonable expectation of success. The motivation for doing so would be to allow the central control unit to “to identify other vehicles, to identify potential hazards” [0261], as taught by Hazelton.
Regarding claim 13, Chiba in view Hazelton teaches The system of claim 12,
However, regarding claims 5, 13, and 19, Chen teaches
wherein generating one or more paths comprises utilizing a machine learning model configured to receive the map of the operating area and the vehicle sensor data and generate the one or more paths (“map data representing a basic depiction of an intersection (e.g., a screenshot of the intersection from a 2D GPS application) may be input into the machine learning model(s) in addition to the sensor data. The machine learning model(s) may use the map data to generate the recommended vehicle trajectory that includes making a turn once an intersection that corresponds to the map data is identified from the sensor data.”, [0101], “The method 600, at block B610, includes determining vehicle control data. For example, the machine learning model(s) 516 may compute and/or determine the vehicle control information 520 based on the inputs 504 (e.g., the sensor information 510, the map information 514, the status information 512, the left control operand 506, the right control operand 508, and/or other inputs 504).”, [0146]).
Thus, it would have been obvious to one of ordinary skill in the art before the effective filing date to modify the invention of Chiba in view of Hazelton with the teachings of Chen such that the generating the one or more paths of Chiba comprises utilizing a machine learning model which uses a map of the operating area and vehicle sensor data as inputs to generate the one or more paths, as suggested by Chen, with a reasonable expectation of success. This would achieve the predictable result of planning the vehicle’s path using the well-known application of machine learning models known to be used in autonomous vehicle technology. KSR International Co. v. Teleflex Inc. (KSR), 550 U.S. 398, 82 USPQ2d 1385 (2007)
Claim(s) 3 is/are rejected under 35 U.S.C. 103 as being unpatentable over Chiba et al. (US 20240400102 A1) in view of Hazelton et al. (US 20160231746 A1) in view of Shi et al. (US 20220126870 A1).
Regarding claim 3, Chiba in view of Hazelton teaches The system of claim 1,
Hazelton teaches “small objects include curbs, lamp-posts, mail-boxes, and the like” [0181].
Further, Shi teaches
wherein the predetermined cutoff size is between 30 and 50 cm (“The one or more processors 170 execute the operations associated with the under-chassis object detection module 165 that allow the system to determine that the autonomous vehicle may pass over a small object, such as road debris, traffic cones, and other objects of a size that allows the vehicle's chassis to pass over the object while the vehicle is on the road.”, [0022], “The autonomous truck may be able to detect objects with height between two predetermined lengths (e.g.,…20 cm (8 in) and 30 cm (11.8 in))…such an object may be determined to be a medium-sized object. A medium-sized object may be any of: an animal, remains of an animal, a conveyance, parts of a conveyance, a ladder, a box, a disabled conveyance, a bag of any content, and any debris that conforms to the predetermined size range for a medium-sized object.”, [0039], “An autonomous truck may be able to detect objects with height between two predetermined lengths (e.g.,…between 30 cm (11.8 in) and 50 cm (19.62 in))…such an object may be identified as a large object. A large object may be any of: an animal, remains of an animal, a conveyance, parts of a conveyance, a ladder, a box, a disabled conveyance, a bag of any content, and any debris that conforms to the predetermined size range for a large object.”, [0040], “In response to identifying an object, an autonomous truck may alter its trajectory, stop all together, or determine that it is safe to proceed along its original path or route…For detected static objects, an autonomous truck may straddle, or pass over, object which are shorter than the ground clearance of the truck's front bumper and narrower than the minimum wheel inside spacing across all of the autonomous truck's axles.”, [0042]).
Thus, it would have been obvious to one of ordinary skill in the art before the effective filing date to modify the invention of Chiba in view of Hazelton with the teachings of Shi such that the predetermined cutoff size of Chiba is between 20 and 30 cm [0039] or between 30 and 50 cm [0040], as suggested by Chen, with a reasonable expectation of success. The motivation for doing so would be to “to determine that the autonomous vehicle may pass over a small object, such as road debris, traffic cones, and other objects of a size that allows the vehicle's chassis to pass over the object while the vehicle is on the road” [0022], as taught by Shi.
Conclusion
The prior art made of record and not relied upon is considered pertinent to Applicant's disclosure: See Notice of References Cited.
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/AMELIA VORCE/ Primary Examiner, Art Unit 3666
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