DETAILED ACTION
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 .
Response to Amendment
This action is in response to amendments and remarks filed on 07/23/2026. Claim(s) 1-2, 6, and 8-9 have been amended. Claim(s) 3-4 have been cancelled. Claim(s) 10-11 have been added. Claim(s) 1-2 and 5-11 are pending examination. This action is made final.
Response to Arguments
Applicant presents the following argument(s) regarding the previous office action:
Applicant asserts that the 35 USC 103 rejection of the claims is improper. Applicant asserts that the limitations of independent claims 1, 8, and 9 are not taught by the prior art. Accordingly claim 1 and its dependents are allowable.
Applicant's arguments filed 07/23/2026 have been fully considered but they are not persuasive.
Regarding applicant’s argument A, the examiner respectfully disagrees. In response to applicant's argument, regarding claim 1, that the references fails to teach, “at least one other functional unit of the plurality of functional units configured to determine whether an abnormality is present in the system control unit by using information received from the system control unit,” the examiner does not find a difference between the determination of a deviation, as taught in the prior art, and an abnormality as claimed. The teachings of Irion would show that the system can determine that various functional units are detected to be deviating from a norm. This is akin to suffering from an abnormality. The functional units as claimed are part of a vehicle processor. When the processor determines that one is malfunctioning and acting abnormal this would be the same as in Irion, [0028]-[0029], [0046], [0049], ad [0069]. The system has detected a deviation from a path and in turn must mitigate that. This would be the same as solving the abnormalities of the current claims.
Regarding the second part of the claim 1 argument, that the prior art doesn’t teach, “the system control unit is configured to determine whether an abnormality is present in the at least one other functional unit by using information received from the at least one other functional unit,” the examiner disagrees. This is merely a broader version of claim 6. As taught by Irion in [0064], [0066], and [0069]-[0071]; the system is able to monitor the vehicle. This is done using information gathered from functional units. These units send data to the system control unit. When the data does not match up the vehicle system is able to determine that there is an error in at least one of the functional units of the vehicle system.
In light of the above the examiner would continue to reject claim 1 and its dependents at least as obvious under 35 USC 103.
Regarding the arguments to claim 8, the applicant asserts that Avery does not teach, “the moving object identifying unit is configured to determine a route planning abnormality in the route planning unit when a difference between the first estimated position along the first route planned by the route planning unit and the second estimated position along the second route planned by the route planning unit meets or exceeds a threshold.” Applicant asserts that the prior art does not compare an estimated location on a first route to an estimated location on a second route. However, the claim does not require a comparison of data between both route, rather the system determines differences between estimated and planned locations at two distinct time steps. Once both data points are collected the system can determine an abnormality. Avery in [0111], teaches that the system can perform the abnormality determination at any time it receives data, i.e. a first planned and second planned route. In light of this the examiner finds Avery to teach the claims. Also, as stated above each functional unit is part of a processor, if the processor system determines an error present, it would be clear that it has determined the error in itself. In light of the above the examiner would continue to reject claim 8 and its dependents at least as obvious under 35 USC 103.
Regarding applicant’s argument to claim 9, the applicant asserts that Avery does not teach, “the route planning unit is configured to determine a moving object identifying abnormality in the moving object identifying unit when a difference between the first measured position and the second measured position meets or exceeds a threshold.” Applicant asserts that Avery does not use data collected by the system to determine that it is an error, rather two elements (the vehicle and the base station), however by working in tandem these would be a system akin to the claimed system. A system can have any number of elements and a comparison of data between two parts of a system is still comparing data in a system. Also, as stated above each functional unit is part of a processor, if the processor system determines an error present, it would be clear that it has determined the error in itself. In light of the above the examiner would continue to reject claim 9 and its dependents at least as obvious under 35 USC 103.
Claim Rejections - 35 USC § 103
The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
Claim(s) 1 is/are rejected under 35 U.S.C. 103 as being unpatentable over Irion (US PG Pub 2017/0308095) in view of Sekine (US PG Pub 2019/0047586) .
Regarding claim 1, Irion teaches a remote control system that remotely controls a moving object to move automatically, the remote control system comprising:
a processor ([0049] teaches the system having a processor) including a plurality of functional units configured to send and receive information to and from each other, (Fig. 2 and [0049] teach a system with a processor, communication interface and monitoring system, i.e. functional units, that are in communication with each other. [0051] teaches this system as an offboard device to provide remote control of the vehicle) the plurality of functional units including
a system control unit configured to send control instructions and a([0049] teaches the processor has a communication unit that is configured to send control instructions to the vehicle/other units to control the vehicle) and
at least one other functional unit of the plurality of functional units configured to determine whether an abnormality is present in the system control unit by using information received from the system control unit, ([0028]-[0029], [0046], [0049], and [0069] teach the system determining that the vehicle has deviated from the path, i.e. an abnormality has been detected, these abnormalities are taught to be the result of sensors errors, algorithm errors, or actuator errors, which would be understood to be abnormalities within the functional units)
the system control unit is configured to determine whether an abnormality is present in the at least one other functional unit by using information received from the at least one other functional unit; ([0064], [0066], and [0069]-[0071] teaches the system monitoring the position of the vehicle and determining that an abnormality is present when the vehicle has deviated from the planned path. This is achieved by examining data collected by the system and comparing the data gathered to the expected data)
, and
each of the at least one other functional unit that has determined the abnormality is present in the system control unit generates a control instruction to reduce a moving speed of the moving object, to limit a steering angle of the moving object, or both. ([0037], [0073], and Claim 17; teach the system sending a stop signal to the vehicle in the event of a deviation detected from the route. Stopping would be analogous to reducing the speed of the moving object and the deviation is analogous to the abnormality detected)
Irion does not teach an authentication code for authenticating contents of the control instructions and wherein the at least one other functional unit determines that the abnormality is present in the system control unit when content of the control instruction received by the at least one other functional unit is different from content of the control instructions indicated by the authentication code.
However, Sekine teaches “an authentication code for authenticating contents of the control instructions” ([0055] teaches the vehicle ECU receiving an approval code to determine if an action is genuine) and “wherein the at least one other functional unit determines that the abnormality is present in the system control unit when content of the control instruction received by the at least one other functional unit is different from content of the control instructions indicated by the authentication code.” ([0055]-[0056] teaches the system determining whether or not a command is approved based on the received approval code. In the event the code is not legitimate the system will not allow for controls to occur, [0057].)
It would have been prima facie obvious to one of ordinary skill in the art, before the effective filing date, to incorporate the teachings of Irion with Sekine; and have a reasonable expectation of success. Both relate to vehicle control systems. While the elements of Sekine are embedded in a vehicle it would be obvious to incorporate them into a remote system. This would be seen as making separable as discussed in MPEP 2144.04(V)(C.) Applicant has removed features of an autonomous vehicle and implemented them into a remote control system. The combination of a remote control system with an autonomous vehicle would therefore be an obvious modification. Additionally, as Sekine teaches in [0006]-[0008] by using an authentication code a user can ensure that the vehicle is only operating as best it can. The authentication codes ensure that the vehicle does not try to perform an action that it should not, and only approved actions can be executed by the vehicle.
Claim(s) 2 and 6-7 is/are rejected under 35 U.S.C. 103 as being unpatentable over Irion (US PG Pub 2017/0308095) in view of Sekine (US PG Pub 2019/0047586), Thomas (US PG Pub 2023/0236022), and Avery (US PG Pub 2019/0258242).
Regarding claim 2, Irion teaches the remote control system according to claim 1, wherein the at least one other functional unit further includes ([0028]-[0029], [0046], [0049], and [0069] teach the system determining that the vehicle has deviated from the path, i.e. an abnormality has been detected, these abnormalities are taught to be the result of sensors errors, algorithm errors, or actuator errors, which would be understood to be abnormalities within the functional units)
a route planning unit configured to plan a route along which the moving object is to be moved and provide an estimated position of the moving object along the route; (Fig. 2, item 203; and [0049] teaches a processor that functionally determines the route a vehicle should move through an area, [0071] teaches the system monitoring the vehicle along the estimate path) and
a moving object identifying unit configured to acquire either or both of a measured position and a measured orientation of the moving object and provide either or both of the measured position and the measured orientation of the moving object, (Fig. 2, item 207; and [0049] teaches a monitoring system configured to monitor the vehicle’s travel and determine its location) wherein
the route planning unit acquires either or both of the measured position and the measured orientation of the moving object from the moving object identifying unit, ([0064], [0066], and [0070]-[0071] teaches the system monitoring the position of the vehicle)
the moving object identifying unit acquires the estimated position of the moving object along the route from the route planning unit, ([0064], [0066], and [0070]-[0071] teaches the system monitoring the position of the vehicle from the estimated route)
the moving object identifying unit determines that an abnormality is present in the route planning unit when the difference between the current estimated position of the moving object acquired from the route planning unit at the current time and a previous estimated position of the moving object acquired from the route planning unit at a previous time exceeds a threshold estimated position value. ([0064], [0066], and [0069]-[0071] teaches the system monitoring the position of the vehicle and determining that an abnormality is present when the vehicle has deviated from the planned path. The system has determined that an abnormality has occurred in the processor, which would encompass the functional units.)
Irion does not teach the route planning unit determines that an abnormality is present in the moving object identifying unit when a difference between a current measured position acquired from the moving object identifying unit at a current time and a respective previous measured position acquired at a previous time exceeds a threshold measured position value; or a difference between a current measured orientation acquired from the moving object identifying unit at a current time, and a previous measured orientation acquired at a previous time exceeds a threshold measured orientation value.
However, Thomas teaches “a difference between a current measured orientation acquired from the moving object identifying unit at a current time, and a previous measured orientation acquired at a previous time exceeds a threshold measured orientation value.” (0104] teaches the system monitoring a vehicle over a time period and determine that a deviation from a route has occurred when the vehicle current location/pose does not match an expected location/pose from a previous time period. In particular Thomas recites, “a second threshold provides that the rotational distance between poses shall not exceed the distance that is a function of a second predetermined value, such as the angular velocity with a calibration buffer according to a checker sample time.” The system is clearly determining that there is a change in pose over time. This allows for the system to determine that an abnormality has occurred.)
It would have been prima facie obvious to one of ordinary skill in the art, before the effective filing date, to incorporate the teachings of Irion and Sekine with Thomas; and have a reasonable expectation of success. All relate to the control of autonomous vehicles and monitoring the controls. While the elements of Thomas are embedded in a vehicle it would be obvious to incorporate them into a remote system. This would be seen as making separable as discussed in MPEP 2144.04(V)(C.) Applicant has removed features of an autonomous vehicle and implemented them into a remote control system. The combination of a remote control system with an autonomous vehicle would therefore be an obvious modification. Additionally, as Thomas teaches in [0019]-[0020] the validation of vehicle location from a monitoring system ensures that the vehicle is operating within acceptable bounds. If the vehicle deviates too much this can lead to collisions or other issues. Validating data from previous time periods and expiring time periods ensures that the data used is not too old or problematic. This allows for precise vehicle controls.
The combination of Irion, Sekine, and Thomas does not teach the route planning unit determines that an abnormality is present in the moving object identifying unit when a difference between a current measured position acquired from the moving object identifying unit at a current time and a respective previous measured position acquired at a previous time exceeds a threshold measured position value.
However, Avery teaches “the route planning unit determines that an abnormality is present in the moving object identifying unit when a difference between a current measured position acquired from the moving object identifying unit at a current time and a respective previous measured position acquired at a previous time exceeds a threshold measured position value.” (Fig. 5 and [0104]-[0111] teach the system determining that there is an abnormality in the system. This is achieved by the system monitoring the vehicle data gathered at a given time and comparing it to a previous time. This allows the system to determine that an abnormality is present in the event that the vehicle data does not match the expected data. The abnormality in the system is determined to be in a part of the processing system, which encompasses the functional units.)
It would have been prima facie obvious to one of ordinary skill in the art, before the effective filing date, to incorporate the teachings of Irion, Sekine, and Thomas with Avery; and have a reasonable expectation of success. All relate to the control of autonomous vehicles and monitoring the controls. As Avery teaches in [0037]-[0039] when anomalies are not properly detected by a system, the system will act irrationally. The data collected is tainted and will cause it to take adverse actions. By determining which system is not functioning properly the system can determine that the data is not to be trusted and can cause the vehicle to take a preventative action. This prevents crashes and/or other adverse events.
Regarding claim 6, Irion teaches remote control system according to claim 2, wherein the system control unit acquires ([0028]-[0029], [0046], [0049], and [0069] teach the system determining acquiring data from various elements)
either or both of a measured position and a measured orientation of the moving object from the moving object identifying unit; (Fig. 2, item 207; and [0049] teaches a monitoring system configured to monitor the vehicle’s travel and determine its location) and
the estimated position of the moving object along the route from the route planning unit, ([0064], [0066], and [0070]-[0071] teaches the system monitoring the position of the vehicle from the estimated route)
the system control unit determines an abnormality is present in the moving object identifying unit when ([0064], [0066], and [0069]-[0071] teaches the system monitoring the position of the vehicle and determining that an abnormality is present)
the system control unit determines an abnormality is present in the route planning unit when the difference between a current estimated position of the moving object acquired from the route planning unit at the current time and a previous estimated position of the moving object acquired from the route planning unit at the previous time exceeds a threshold estimated position value. ([0064], [0066], and [0069]-[0071] teaches the system monitoring the position of the vehicle and determining that an abnormality is present when the vehicle has deviated from the planned path)
Irion does not teach the difference between a current measured position acquired from the moving object identifying unit at the current time and a respective previous measured position acquired at the previous time exceeds a threshold measured position value; or the difference between a current measured orientation acquired from the moving object identifying unit at the current time, and a previous measured orientation acquired at the previous time exceeds a threshold measured orientation value.
However, Thomas teaches “the difference between a current measured orientation acquired from the moving object identifying unit at the current time, and a previous measured orientation acquired at the previous time exceeds a threshold measured orientation value.” (0104] teaches the system monitoring a vehicle over a time period and determine that a deviation from a route has occurred when the vehicle current location/pose does not match an expected location/pose from a previous time period)
It would have been prima facie obvious to one of ordinary skill in the art, before the effective filing date, to incorporate the teachings of Irion and Sekine with Thomas; and have a reasonable expectation of success. All relate to the control of autonomous vehicles and monitoring the controls. While the elements of Thomas are embedded in a vehicle it would be obvious to incorporate them into a remote system. This would be seen as making separable as discussed in MPEP 2144.04(V)(C.) Applicant has removed features of an autonomous vehicle and implemented them into a remote control system. The combination of a remote control system with an autonomous vehicle would therefore be an obvious modification. Additionally, as Thomas teaches in [0019]-[0020] the validation of vehicle location from a monitoring system ensures that the vehicle is operating within acceptable bounds. If the vehicle deviates too much this can lead to collisions or other issues. Validating data from previous time periods and expiring time periods ensures that the data used is not too old or problematic. This allows for precise vehicle controls.
The combination of Irion, Sekine, and Thomas does not teach the difference between a current measured position acquired from the moving object identifying unit at the current time and a respective previous measured position acquired at the previous time exceeds a threshold measured position value.
However, Avery teaches “the difference between a current measured position acquired from the moving object identifying unit at a current time and a respective previous measured position acquired at a previous time exceeds a threshold measured position value”(Fig. 5 and [0104]-[0111] teach the system determining that there is an abnormality in the system. This is achieved by the system monitoring the vehicle data gathered at a given time and comparing it to a previous time. This allows the system to determine that an abnormality is present in the event that the vehicle data does not match the expected data. The abnormality in the system is determined to be in a part of the processing system, which encompasses the functional units.)
It would have been prima facie obvious to one of ordinary skill in the art, before the effective filing date, to incorporate the teachings of Irion, Sekine, and Thomas with Avery; and have a reasonable expectation of success. All relate to the control of autonomous vehicles and monitoring the controls. As Avery teaches in [0037]-[0039] when anomalies are not properly detected by a system, the system will act irrationally. The data collected is tainted and will cause it to take adverse actions. By determining which system is not functioning properly the system can determine that the data is not to be trusted and can cause the vehicle to take a preventative action. This prevents crashes and/or other adverse events.
Regarding claim 7, Irion teaches the remote control system according to claim 2, wherein at least one of the system control unit, the route planning unit, or the moving object identifying unit generates a control instruction to stop the moving object. ([0037], [0073], and Claim 17; teach the system sending a stop signal to the vehicle in the event of a deviation detected from the route. Stopping would be analogous to reducing the speed of the moving object and the deviation is analogous to the abnormality detected)
Claim(s) 5 is/are rejected under 35 U.S.C. 103 as being unpatentable over Irion (US PG Pub 2017/0308095) in view of Sekine (US PG Pub 2019/0047586) and Thomas (US PG Pub 2023/0236022).
Regarding claim 5, the combination of Irion and Sekine teaches the remote control system according to claim 1.
The combination of Irion and Sekine does not teach wherein the at least one other functional unit of the plurality of functional units is further configured to determine that the abnormality is present in the system control unit when new information is not received from the system control unit for a predetermined time from a previous time when the information was received from the system control unit.
However, Thomas teaches “wherein the at least one other functional unit of the plurality of functional units is further configured to determine that the abnormality is present in the system control unit when new information is not received from the system control unit for a predetermined time from a previous time when the information was received from the system control unit.” ([0079] teaches the system determining an abnormal event in the case where a timer has expired before relevant data is received)
It would have been prima facie obvious to one of ordinary skill in the art, before the effective filing date, to incorporate the teachings of Irion and Sekine with Thomas; and have a reasonable expectation of success. All relate to the control of autonomous vehicles and monitoring the controls. While the elements of Thomas are embedded in a vehicle it would be obvious to incorporate them into a remote system. This would be seen as making separable as discussed in MPEP 2144.04(V)(C.) Applicant has removed features of an autonomous vehicle and implemented them into a remote control system. The combination of a remote control system with an autonomous vehicle would therefore be an obvious modification. Additionally, as Thomas teaches in [0019]-[0020] the validation of vehicle location from a monitoring system ensures that the vehicle is operating within acceptable bounds. If the vehicle deviates too much this can lead to collisions or other issues. Validating data from previous time periods and expiring time periods ensures that the data used is not too old or problematic. This allows for precise vehicle controls.
Claim(s) 8-11 is/are rejected under 35 U.S.C. 103 as being unpatentable over Irion (US PG Pub 2017/0308095) in view of Sekine (US PG Pub 2019/0047586), Thomas (US PG Pub 2023/0236022), and Avery (US PG Pub 2019/0258242).
Regarding claim 8, Irion teaches a remote control system that remotely controls a moving object to move automatically, the remote control system comprising: a processor ([0049] teaches the system having a processor) including a plurality of functional units configured to send and receive information to and from each other, (Fig. 2 and [0049] teach a system with a processor, communication interface and monitoring system, i.e. functional units, that are in communication with each other. [0051] teaches this system as an offboard device to provide remote control of the vehicle) the plurality of functional units including:
a moving object identifying unit configured to acquire a first measured position of the moving object; (Fig. 2, item 207; and [0049] teaches a monitoring system configured to monitor the vehicle’s travel and determine its location) and
a route planning unit configured to plan a first route along which the moving object is to be moved based on the first measured position (Fig. 2, item 203; and [0049] teaches a processor that functionally determines the route a vehicle should move through an area, [0071] teaches the system monitoring the vehicle along the estimate path) and provide a first estimated position of the moving object along the first route, ([0064], [0066], and [0070]-[0071] teaches the system monitoring the position of the vehicle from the estimated route) wherein:
the moving object identifying unit is configured to acquire a second measured position of the moving object; (Fig. 2, item 207; and [0049] teaches a monitoring system configured to monitor the vehicle’s travel and determine its location)
the route planning unit is configured to plan a second route along which the moving object is to be moved based on the second measured position of the moving object and provide a second estimated position of the moving object along the second route; (Fig. 2, item 203; and [0049] teaches a processor that functionally determines the route a vehicle should move through an area, [0071] teaches the system monitoring the vehicle along the estimate path)
upon determining the route planning abnormality, the processor is configured to generate a control instruction to reduce a moving speed of the moving object, to limit a steering angle of the moving object, or both. ([0037], [0073], and Claim 17; teach the system sending a stop signal to the vehicle in the event of a deviation detected from the route. Stopping would be analogous to reducing the speed of the moving object and the deviation is analogous to the abnormality detected)
Irion does not teach the moving object identifying unit is configured to determine a route planning abnormality in the route planning unit when a difference between the first estimated position along the first route planned by the route planning unit and the second estimated position along the second route planned by the route planning unit meets or exceeds a threshold.
However, Avery teaches “the moving object identifying unit is configured to determine a route planning abnormality in the route planning unit when a difference between the first estimated position along the first route planned by the route planning unit and the second estimated position along the second route planned by the route planning unit meets or exceeds a threshold” (Fig. 5 and [0104]-[0111] teach the system determining that there is an abnormality in the system. This is achieved by the system monitoring the vehicle data gathered at a given time and comparing it to a previous time. This allows the system to determine that an abnormality is present in the event that the vehicle data does not match the expected data. The abnormality in the system is determined to be in a part of the processing system, which encompasses the functional units. The system is configured to perform this test as many times as necessary and repeat it for any data point gathered.)
It would have been prima facie obvious to one of ordinary skill in the art, before the effective filing date, to incorporate the teachings of Irion with Avery; and have a reasonable expectation of success. Both relate to the control of autonomous vehicles and monitoring the controls. As Avery teaches in [0037]-[0039] when anomalies are not properly detected by a system, the system will act irrationally. The data collected is tainted and will cause it to take adverse actions. By determining which system is not functioning properly the system can determine that the data is not to be trusted and can cause the vehicle to take a preventative action. This prevents crashes and/or other adverse events.
Regarding claim 9, Irion teaches a remote control system that remotely controls a moving object to move automatically, the remote control system comprising: a processor ([0049] teaches the system having a processor) including a plurality of functional units configured to send and receive information to and from each other, (Fig. 2 and [0049] teach a system with a processor, communication interface and monitoring system, i.e. functional units, that are in communication with each other. [0051] teaches this system as an offboard device to provide remote control of the vehicle) the plurality of functional units including:
a moving object identifying unit configured to acquire a first measured position of the moving object; (Fig. 2, item 207; and [0049] teaches a monitoring system configured to monitor the vehicle’s travel and determine its location) and
a route planning unit configured to plan a first route along which the moving object is to be moved, the first route originating from the first measured position acquired form the moving object identifying unit, (Fig. 2, item 203; and [0049] teaches a processor that functionally determines the route a vehicle should move through an area, [0071] teaches the system monitoring the vehicle along the estimate path) and configured to provide a first estimated position of the moving object along the first route, ([0064], [0066], and [0070]-[0071] teaches the system monitoring the position of the vehicle from the estimated route) wherein:
the moving object identifying unit is configured to acquire a second measured position of the moving object; (Fig. 2, item 207; and [0049] teaches a monitoring system configured to monitor the vehicle’s travel and determine its location)
the route planning unit is configured to plan a second route along which the moving object is to be moved, the second route originating from the second measured position of the moving object acquired from the moving object identifying unit and configured to provide a second estimated position of the moving object along the second route; (Fig. 2, item 203; and [0049] teaches a processor that functionally determines the route a vehicle should move through an area, [0071] teaches the system monitoring the vehicle along the estimate path)
upon determining the moving unit identifying abnormality, the processor is configured to generate a control instruction to reduce a moving speed of the moving object, to limit a steering angle of the moving object, or both. ([0037], [0073], and Claim 17; teach the system sending a stop signal to the vehicle in the event of a deviation detected from the route. Stopping would be analogous to reducing the speed of the moving object and the deviation is analogous to the abnormality detected)
Irion does not teach the route planning unit is configured to determine a moving object identifying abnormality in the moving object identifying unit when a difference between the first measured position and the second measured position meets or exceeds a threshold.
However, Avery teaches “the route planning unit is configured to determine a moving object identifying abnormality in the moving object identifying unit when a difference between the first measured position and the second measured position meets or exceeds a threshold.” (Fig. 5 and [0104]-[0111] teach the system determining that there is an abnormality in the system. This is achieved by the system monitoring the vehicle data gathered at a given time and comparing it to a previous time. This allows the system to determine that an abnormality is present in the event that the vehicle data does not match the expected data. The abnormality in the system is determined to be in a part of the processing system, which encompasses the functional units.)
It would have been prima facie obvious to one of ordinary skill in the art, before the effective filing date, to incorporate the teachings of Irion with Avery; and have a reasonable expectation of success. Both relate to the control of autonomous vehicles and monitoring the controls. As Avery teaches in [0037]-[0039] when anomalies are not properly detected by a system, the system will act irrationally. The data collected is tainted and will cause it to take adverse actions. By determining which system is not functioning properly the system can determine that the data is not to be trusted and can cause the vehicle to take a preventative action. This prevents crashes and/or other adverse events.
Regarding claim 10, Irion teaches the remote control system according to claim 9, wherein:
upon determining the route planning abnormality, the processor is configured to generate the control instruction to reduce the moving speed of the moving object, to limit the steering angle of the moving object, or both. ([0037], [0073], and Claim 17; teach the system sending a stop signal to the vehicle in the event of a deviation detected from the route. Stopping would be analogous to reducing the speed of the moving object and the deviation is analogous to the abnormality detected)
Irion does not teach the moving object identifying unit is configured to determine a route planning abnormality in the route planning unit when a difference between the first estimated position along the first route planned by the route planning unit and the second estimated position along the second route planned by the route planning unit meets or exceeds a threshold.
However, Avery teaches “the moving object identifying unit is configured to determine a route planning abnormality in the route planning unit when a difference between the first estimated position along the first route planned by the route planning unit and the second estimated position along the second route planned by the route planning unit meets or exceeds a threshold.” (Fig. 5 and [0104]-[0111] teach the system determining that there is an abnormality in the system. This is achieved by the system monitoring the vehicle data gathered at a given time and comparing it to a previous time. This allows the system to determine that an abnormality is present in the event that the vehicle data does not match the expected data. The abnormality in the system is determined to be in a part of the processing system, which encompasses the functional units. The system is configured to perform this test as many times as necessary and repeat it for any data point gathered.)
It would have been prima facie obvious to one of ordinary skill in the art, before the effective filing date, to incorporate the teachings of Irion with Avery; and have a reasonable expectation of success. Both relate to the control of autonomous vehicles and monitoring the controls. As Avery teaches in [0037]-[0039] when anomalies are not properly detected by a system, the system will act irrationally. The data collected is tainted and will cause it to take adverse actions. By determining which system is not functioning properly the system can determine that the data is not to be trusted and can cause the vehicle to take a preventative action. This prevents crashes and/or other adverse events.
Regarding claim 11, Irion teaches the remote control system according to claim 8, wherein:
upon determining the moving object identifying abnormality, the processor is configured to generate the control instruction to reduce the moving speed of the moving object, to limit the steering angle of the moving object, or both. ([0037], [0073], and Claim 17; teach the system sending a stop signal to the vehicle in the event of a deviation detected from the route. Stopping would be analogous to reducing the speed of the moving object and the deviation is analogous to the abnormality detected)
Irion does not teach the route planning unit is configured to determine a moving object identifying abnormality in the moving object identifying unit when a difference between the first measured position and the second measured position meets or exceeds a threshold.
However, Avery teaches “the route planning unit is configured to determine a moving object identifying abnormality in the moving object identifying unit when a difference between the first measured position and the second measured position meets or exceeds a threshold.” (Fig. 5 and [0104]-[0111] teach the system determining that there is an abnormality in the system. This is achieved by the system monitoring the vehicle data gathered at a given time and comparing it to a previous time. This allows the system to determine that an abnormality is present in the event that the vehicle data does not match the expected data. The abnormality in the system is determined to be in a part of the processing system, which encompasses the functional units.)
It would have been prima facie obvious to one of ordinary skill in the art, before the effective filing date, to incorporate the teachings of Irion with Avery; and have a reasonable expectation of success. Both relate to the control of autonomous vehicles and monitoring the controls. As Avery teaches in [0037]-[0039] when anomalies are not properly detected by a system, the system will act irrationally. The data collected is tainted and will cause it to take adverse actions. By determining which system is not functioning properly the system can determine that the data is not to be trusted and can cause the vehicle to take a preventative action. This prevents crashes and/or other adverse events.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Piednoel (US PG Pub 2024/0430125) teaches a sensor data input chiplet obtains sensor data from a sensor system. A central chiplet executes a functional safety program to dynamically compare and verify output of workloads being executed by a set of workload processing chiplets, where the workloads are executed across the set of workload processing chiplets based on the sensor data.
Ma (US PG Pub 2024/0230866) teaches misalignment of camera and light detection and ranging (LIDAR) sensors can impact operations performed by an autonomous vehicle (AV) stack. Misalignment, or deviation from initial alignment over time, can occur in pitch, yaw, and roll dimensions. To address alignment issues, AV sensors may be calibrated before the AV drives on roadways. Additionally, AV sensors may be routinely calibrated at a maintenance facility to detect deviations from initial alignment of the sensors. Offline calibration of AV sensors in maintenance facilities can be inefficient and can significantly increase overhead. Therefore, online calibration of AV sensor misalignment may alleviate some of these concerns. Additionally, online calibration of AV sensors enables efficient monitoring and effective calibration of AV sensor alignment for a whole fleet of AVs while the fleet is on the road.
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/N.S./Examiner, Art Unit 3665 /CHRISTIAN CHACE/Supervisory Patent Examiner, Art Unit 3665
