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
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 3/18/2026 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Response to Arguments
Applicant's arguments filed 12/12/2025 have been fully considered but they are not persuasive. Applicant asserts as follows:
Applicant respectfully submits that Levinson in view of Urano fails to teach or reasonably suggest the features of independent claims 1 and 4. In particular, Levinson in view of Urano fails to teach or reasonably suggest the features regarding "generating the path plan includes: ... generating target data that is the recognition data with reduced accuracy and generating the path plan that can be generated using the target data in a case where the remaining capacity is equal to or less than a predetermined amount", as recited in amended independent claims 1 and 4.
Levinson is directed to a system for storing data to manage the amount of data stored and/or transferred over a network. Levinson, Para. [0011]. Specifically, Levinson stores event data based on a first storage rule that indicates that the data is to be preserved and a second storage rule that indicates that the data may be stored until memory of the vehicle is full or reaches a specified storage level. Id. at Para. [0019]. However, the reduction of the accuracy of Levinson relates to how long the data is stored rather than generating a path plan based on target data that is the recognition data with reduced accuracy in a case where the remaining capacity is equal to or less than a predetermined amount.
Urano is directed to reducing the "accuracy" of data that is sent to a remove instruction apparatus 1 where a remote commander R issues remove instructions. Urano, Paras. [0070]-[0071]. However, the remote apparatus 1 is remote from the remote autonomous driving vehicle 2 and the remote commander R issues remote instructions for controlling the remote autonomous driving vehicle 2. Therefore, the remote commander R of the remove apparatus 1 inputs a remote instruction based on the reduced accuracy of the data.
Examiner includes the above sections of Applicant arguments, appearing to primarily summarize the content of the cited references, to give context to the following sections.
As such, Applicant respectfully submits that the combination of Levinson and Urano fails to teach or reasonably suggest the features that the processing circuitry, mounted on the vehicle, is configured to execute generating a path plan that includes generating target data that is the recognition data with reduced accuracy and generating the path plan that can be generated using the target data in a case where the remaining capacity is equal to or less than a predetermined amount. Specifically, the combination of Levinson and Urano fails to teach or reasonably suggest the features of processing circuitry, mounted on the vehicle, that generates a path plan based on target data that is the recognition data with reduced accuracy.
Furthermore, the combination of Levinson and Urano fails to teach or reasonably suggest the features of processing circuitry, mounted on the vehicle, that generates a path plan based on target data that is the recognition data with reduced accuracy in a case where the remaining capacity is equal to or less than a predetermined amount. Rather, Urano teaches reducing the data amount when the data amount is equal to or larger than a data amount threshold value, which cannot be reasonably interpreted as the claimed acquired remaining capacity of the one or more storage devices. See Urano, Para. [0069]. In particular, Urano discloses that the data amount threshold value is based on the communication state with the remote instruction apparatus 1. See Id. at Para. [0084].
Examiner respectfully disagrees. Examiner asserts that the apparatus of Levinson, which is located at the autonomous vehicle [Paragraph 0011], may store sensor data, used to make driving operation decisions, in accordance with storage rules, which are based on the used capacity of the storage memory [Paragraphs 0019 & 0104]. Levinson, as noted above in Applicant arguments, may also implement a similar method with respect to remote computing devices, such as those of a teleoperations computing device. Turning now to the teaching(s) of Urano, while the teaching(s) of Urano recite wherein the data amount is reduced when transmitting the data to a remote operation system, rather than at a local computing device, Urano is relied upon to teach the limitation “generating the path plan that can be generated using the target data” [which has been reduced in accuracy due to the data storage device being filled to a threshold degree], referencing at least Paragraphs 0069 & 0076 – 0079 of Urano. In said referenced teachings, the data amount of the sensor information acquired is reduced, transmitted to a remote instruction apparatus, which then generates a remote instruction [via a remote commander] based on the reduced sensor data amount.
Examiner respectfully asserts that the combination of Levinson and Urano is therefore proper, and would have been obvious, in order to arrive at the present claimed invention. While Urano “teaches reducing the data amount when the data amount is equal to or larger than a data amount threshold value” which Applicant asserts cannot be “reasonably interpreted as the claimed acquired remaining capacity of the one or more storage devices,” Examiner respectfully asserts that as Levinson discloses reducing sensor data based on the storage capacity including for the transmission to remote/teleoperation computing devices, the rationale of reduction in Urano sufficiently correlates to that of Levinson. Further, while Levinson appears to be silent regarding the generation of a path plan based on the reduced data amount, Urano recites such limitations in at least Paragraphs 0069 & 0076 – 0079, which, while taking place remotely from the vehicle rather than onboard, takes place squarely as a function of reduced sensor data when said sensor data is desired to be reduced below a threshold value. As Levinson discloses an onboard planning component for planning the path of the vehicle in at least Paragraph 0060, Examiner respectfully asserts that in combining Levinson with Urano, the planning may also take place onboard the vehicle as disclosed by Levinson. Thus, Examiner respectfully asserts that the combination of Levinson and Urano renders obvious the present claimed invention.
Based on the foregoing, Applicant respectfully submits that independent claims 1 and 4, and all claims that depend thereon, can no longer be rejected as unpatentable over Levinson in view of Urano. Withdrawal of the rejections and a timely notice of allowance are respectfully requested.
Examiner respectfully maintains the rejection(s) under 35 USC 103 for at least the reasons set forth above, as well as those set forth below with respect to specific claim limitations for Claims 1, 3, & 4.
Applicant’s arguments with respect to claim 2 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.
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.
Claim(s) 1 - 4 is/are rejected under 35 U.S.C. 103 as being unpatentable over Levinson (US 2020/0192366 A1) in view of Urano (US 2021/0109515 A1).
Regarding Claim 1:
Levinson discloses: An autonomous driving system mounted on a vehicle, comprising (Levinson discloses in at least Paragraph 0011 wherein a computing device of an autonomous vehicle [i.e. an autonomous driving system mounted on a vehicle] may receive sensor data representing an environment and store portions of sensor data according to different storage rules)
one or more storage devices and processing circuitry, wherein the processing circuitry is configured to execute: (Levinson discloses in at least Paragraphs 0056 & 0088 wherein the vehicle computing device may include one or more processors and coupled memory [i.e. one or more storage devices and processing circuitry] configured to execute instructions to process data and perform disclosed operations [i.e. the processing circuitry is configured to execute the contents of the disclosure])
acquiring recognition data by recognizing a situation around the vehicle; (Levinson discloses in at least Paragraph 0092 wherein sensor data is generated [i.e. acquired] by one or more sensors and received at a memory. Sensor systems disclosed in at least Paragraphs 0084 & 0092 include lidar, radar, location, inertial measurement, environmental sensors, and the like, which are configured to measure vehicle and ambient conditions, as well as entities in the surroundings of the vehicle [i.e. recognition data for a situation around a vehicle])
generating a path plan for the vehicle based on the recognition data; (Levinson discloses in at least Paragraph 0060 wherein the planning component is configured to determine a path for the vehicle to follow to traverse an environment. At least Paragraph 0060 of Levinson further discloses wherein the determined route to traverse an environment may include a sequence of waypoints in travelling between two locations, waypoints including streets, intersections, coordinates, and the like, from which instructions may be generated to guide the vehicle along the determined route [i.e. generating a path plan for the vehicle]. At least Paragraph 0031 of Levinson discloses wherein the trajectory may be determined in view of other objects recognized on the roadway from the sensor data [i.e. the path plan is generated based on the recognition data])
performing autonomous driving control of the vehicle in accordance with the path plan; and (Levinson discloses in at least Paragraph 0062 wherein the vehicle computing device may include one or more system controllers configured to control vehicle operations, including steering, propulsion, braking, and the like. At least Paragraph 0067 of Levinson further discloses wherein the planned and selected trajectory is used to control the vehicle [i.e. perform autonomous driving control in accordance with the path plan])
storing a data log related to the autonomous driving control in the one or more storage devices, the data log including a log of data used for generating the path plan, and generating the path plan includes: (Levinson discloses in at least Paragraphs 0011 & 0112 wherein sensor data corresponding to an event [i.e. data used for generating a path plan] may be logged, including by flagging or otherwise tagging sensor data associated with an event, and storing it differently than other portions of sensor data also associated with the event. At least Paragraph 0011 of Levinson discloses wherein this may include storing a flagged portion of sensor data in the computing device [i.e. storing a data log related to the autonomous driving control in the one or more storage devices] for a longer duration or with a higher resolution than unflagged sensor data)
acquiring a remaining capacity of the one or more storage devices; and (Levinson discloses in at least Paragraphs 0019 & 0104 wherein the system is configured to determine whether the memory of the vehicle [i.e. the one or more storage devices] is at or above a threshold level, such as a specific percentage of the vehicle memory being filled with only a limited amount remaining available [i.e. a remaining capacity of the one or more storage devices]. At least Paragraphs 0019 & 0105 of Levinson further discloses wherein data storage rules may be set based on the vehicle memory storage level exceeding a specified storage level, with different data storage rules being defined for different sensor data)
generating target data that is the recognition data with reduced accuracy… in a case where the remaining capacity is equal to or less than a predetermined amount. (Levinson discloses in at least Paragraph 0011 wherein portions of sensor data that are not flagged may be stored in a data log on the computing device with a lower resolution [i.e. target data generated with a reduced accuracy] than other flagged portions of sensor data, according to a second storage rule different than a first storage rule. At least Paragraphs 0021 & 0041 further disclose wherein sensor data may be stored in memory according to different storage rules including introducing compression to the sensor data, lowering resolution, and the like [i.e. generating and storing target data with different levels of accuracy]. The utilization of different storage rules may be invoked under the condition of if, for example, the memory is full or above a specified storage level as disclosed in at least Paragraph 0019 of Levinson [i.e. reduced accuracy data is generated when the remaining capacity is equal to or less than a predetermined amount])
Levinson however appears to be silent regarding:
and generating the path plan that can be generated using the target data [with reduced accuracy]
However Urano teaches wherein a data amount reduction apparatus may be utilized to reduce a data amount of sensor information transmitted to a remote instruction apparatus used to determine operation instructions for the vehicle.
and generating the path plan that can be generated using the target data [that was generated with reduced accuracy] (However Urano teaches in at least Paragraph 0069 wherein a data amount reduction unit reduces the data amount of sensor information detected by a sensor when the amount of data generated by the sensor is equal to or larger than a data amount threshold. At least Paragraphs 0076 & 0078 of Urano further teach wherein the reduced data may be transmitted to the remote instruction apparatus for use in determining the remote instruction to be issued to control the autonomous vehicle in the given situation [i.e. a path plan is generated by the reduced accuracy target data]. Data reduction of sensor data may include, as taught in at least Paragraphs 0075, 0078, & 0079, limiting a field of view of sensor data, lowering a resolution of the image generated by the sensor(s), changing the storage format of the sensors, such as through compression, and the like)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the present claimed invention to have modified the disclosure of Levinson by incorporating the determination of vehicle path based on determined reduced sensor data as taught by Urano.
The motivation to do so is that, as acknowledged by Urano in at least Paragraphs 0006, 0009, & 0012, the remote instruction apparatus may issue an instruction appropriate to the sensor data received while reducing the amount of data required to be transmitted and analyzed, improving the transmission and storage of data by only utilizing data required to make such planning determinations, while still enabling appropriate planning operations to be conducted.
Regarding Claim 2:
The autonomous driving system according to claim 1, wherein generating the target data includes at least one of reducing a sampling rate of the recognition data, and changing representation of the recognition data.
Levinson discloses in at least Paragraph 0021 wherein the computing device may store sensor data according to different storage rules, which may include storing sensor data at different resolutions, however does not appear to specifically disclose wherein generating the target data includes at least one of reducing a sampling rate of the recognition data, and changing representation of the recognition data.
However Urano teaches in at least Paragraphs 0080 – 0082 wherein a data reduction of sensor data may take place by reducing a frame rate of the data, such that, in one example, only one out of each six captured images is extracted, rendering the sensor data acquired from a 6 fps camera equivalent to a 10 fps camera [i.e. generating the target data includes reducing a sampling rate of the recognition data].
It would have been obvious to one of ordinary skill in the art before the effective filing date of the present claimed invention to have modified the disclosure of Levinson by incorporating the data reduction based on a reduction in sensor data sampling rate as taught by Urano.
The motivation to do so is that, as acknowledged by Urano in at least Paragraphs 0080 – 0082, the amount of data may be reduced through the exclusion of data, allowing the situation of the vehicle to be recognized while lowering the amount of data required, improving the data reduction of the relevant sensor data.
Regarding Claim 3:
The autonomous driving system according to claim 1, wherein generating the path plan includes generating a travel trajectory for the autonomous driving control in a road in which the vehicle travels.
Levinson discloses in at least Paragraph 0060 wherein the planning component is configured to determine a path for the vehicle to follow to traverse an environment. At least Paragraph 0060 of Levinson further discloses wherein the determined route to traverse an environment may include a sequence of waypoints in travelling between two locations, waypoints including streets, intersections, coordinates, and the like, from which instructions may be generated to guide the vehicle along the determined route [i.e. a travel trajectory for the autonomous driving control in a road in which the vehicle travels].
Regarding Claim 4:
Levinson discloses: A control method for controlling autonomous driving of a vehicle, the control method comprising: (Levinson discloses in at least Paragraphs 0011 & 0125 a method for operating an autonomous vehicle during autonomous driving operations, including storing sensor data in logs according to storage rules, and operating the autonomous vehicle as disclosed in at least Paragraphs 0060 & 0067)
acquiring recognition data by recognizing a situation around the vehicle; (Levinson discloses in at least Paragraph 0092 wherein sensor data is generated [i.e. acquired] by one or more sensors and received at a memory. Sensor systems disclosed in at least Paragraphs 0084 & 0092 include lidar, radar, location, inertial measurement, environmental sensors, and the like, which are configured to measure vehicle and ambient conditions, as well as entities in the surroundings of the vehicle [i.e. recognition data for a situation around a vehicle])
generating a path plan for the vehicle based on the recognition data; (Levinson discloses in at least Paragraph 0060 wherein the planning component is configured to determine a path for the vehicle to follow to traverse an environment. At least Paragraph 0060 of Levinson further discloses wherein the determined route to traverse an environment may include a sequence of waypoints in travelling between two locations, waypoints including streets, intersections, coordinates, and the like, from which instructions may be generated to guide the vehicle along the determined route [i.e. generating a path plan for the vehicle]. At least Paragraph 0031 of Levinson discloses wherein the trajectory may be determined in view of other objects recognized on the roadway from the sensor data [i.e. the path plan is generated based on the recognition data])
performing autonomous driving control of the vehicle in accordance with the path plan; and (Levinson discloses in at least Paragraph 0062 wherein the vehicle computing device may include one or more system controllers configured to control vehicle operations, including steering, propulsion, braking, and the like. At least Paragraph 0067 of Levinson further discloses wherein the planned and selected trajectory is used to control the vehicle [i.e. perform autonomous driving control in accordance with the path plan])
storing a data log related to the autonomous driving control in a storage device, and the data log including a log of data used for generating the path plan, and generating the path plan includes: (Levinson discloses in at least Paragraphs 0011 & 0112 wherein sensor data corresponding to an event [i.e. data used for generating a path plan] may be logged, including by flagging or otherwise tagging sensor data associated with an event, and storing it differently than other portions of sensor data. At least Paragraph 0011 of Levinson discloses wherein this may include storing a flagged portion of sensor data in the computing device [i.e. storing a data log related to the autonomous driving control in the one or more storage devices] for a longer duration or with a higher resolution than unflagged sensor data)
acquiring a remaining capacity of the storage device; and (Levinson discloses in at least Paragraphs 0019 & 0104 wherein the system is configured to determine whether the memory of the vehicle [i.e. the one or more storage devices] is at or above a threshold level, such as a specific percentage of the vehicle memory being filled with only a limited amount remaining available [i.e. a remaining capacity of the one or more storage devices]. At least Paragraphs 0019 & 0105 of Levinson further discloses wherein data storage rules may be set based on the vehicle memory storage level exceeding a specified storage level, with different data storage rules being defined for different sensor data)
generating target data that is the recognition data with reduced accuracy… in a case where the remaining capacity is equal to or less than a predetermined amount. (Levinson discloses in at least Paragraph 0011 wherein portions of sensor data that are not flagged may be stored in a data log on the computing device with a lower resolution [i.e. target data generated with a reduced accuracy] than other flagged portions of sensor data, according to a second storage rule different than a first storage rule. At least Paragraphs 0021 & 0041 further disclose wherein sensor data may be stored in memory according to different storage rules including introducing compression to the sensor data, lowering resolution, and the like [i.e. generating and storing target data with different levels of accuracy]. The utilization of different storage rules may be invoked under the condition of if, for example, the memory is full or above a specified storage level as disclosed in at least Paragraph 0019 of Levinson [i.e. reduced accuracy data is generated when the remaining capacity is equal to or less than a predetermined amount])
Levinson however appears to be silent regarding:
and generating the path plan that can be generated using the target data [that was generated with reduced accuracy]
However Urano teaches wherein a data amount reduction apparatus may be utilized to reduce a data amount of sensor information transmitted to a remote instruction apparatus used to determine operation instructions for the vehicle.
and generating the path plan that can be generated using the target data [that was generated with reduced accuracy] (However Urano teaches in at least Paragraph 0069 wherein a data amount reduction unit reduces the data amount of sensor information detected by a sensor when the amount of data generated by the sensor is equal to or larger than a data amount threshold. At least Paragraphs 0076 & 0078 of Urano further teach wherein the reduced data may be transmitted to the remote instruction apparatus for use in determining the remote instruction to be issued to control the autonomous vehicle in the given situation [i.e. a path plan is generated by the reduced accuracy target data]. Data reduction of sensor data may include, as taught in at least Paragraphs 0075, 0078, & 0079, limiting a field of view of sensor data, lowering a resolution of the image generated by the sensor(s), changing the storage format of the sensors, such as through compression, and the like)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the present claimed invention to have modified the disclosure of Levinson by incorporating the determination of vehicle path based on determined reduced sensor data as taught by Urano.
The motivation to do so is that, as acknowledged by Urano in at least Paragraphs 0006, 0009, & 0012, the remote instruction apparatus may issue an instruction appropriate to the sensor data received while reducing the amount of data required to be transmitted and analyzed, improving the transmission and storage of data by only utilizing data required to make such planning determinations, while still enabling appropriate planning operations to be conducted.
Conclusion
The following prior art made of record but not relied upon is considered pertinent to the Applicant’s disclosure:
O’Grady (US 2023/0316816 A1): O’Grady recites a system for reducing a telematic load regarding vehicle information while preserving the ability to perform analytics on the reduced dataset at a cloud server. Datasets are evaluated to extract relevant data, and the relevant data is subsequently transmitted from the vehicle to a remote server.
Watts (US 2023/0271628 A1): Watts recites an electronic control unit configured to receive sensor information regarding a plurality of zones associated with the vehicle. Based on the driving mode, the sensor data may be evaluated and recognized to determine the relevant sensor data zones to the current situation, following which control of the vehicle may take place.
Han (US 12,328,528 B2): Han recites a system for recording and storing event-related video data, including data generated at a vehicle. Lower resolution cameras may be used for continuously recording data, in order to reduce the data resources used, while high resolution/bitrate data is used in the recording of event-related data.
THIS ACTION IS MADE FINAL. 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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to CHRISTOPHER RYAN CARDIMINO whose telephone number is (571)272-2759. The examiner can normally be reached M-Th 8:30-5:00.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Ramya Burgess can be reached at (571)272-6011. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/CHRISTOPHER R CARDIMINO/Examiner, Art Unit 3661
/RAMYA P BURGESS/Supervisory Patent Examiner, Art Unit 3661