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 .
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.
Claims 3 – 5, 12 - 14, 20 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 applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 3 recites “further including determining, via the trajectory control architecture, at least one of a large tracking error and a large trajectory error based on a maneuver phase.” The limitations “large tracking error” and “large trajectory error” are subjective because it is unclear how the “tracking error” and the “trajectory error” are determined as “large”.
Claim 4 – 5 are dependent on claim 3 but do not cure the deficiencies thereof, thus being rejected for the same basis as claim 3 above.
Claim 12 recites the system with substantially same scope as claim 3, thus being rejected for the same basis as claim 3 above.
Claims 13 – 14 are dependent on claim 12 but do not cure the deficiencies thereof, thus being rejected for the same basis as claim 12 above.
Claim 20 recites “determining, via the trajectory control architecture, at least one of a large tracking error and a large trajectory error based on a maneuver phase.” The limitations “large tracking error” and “large trajectory error” are subjective because it is unclear how the “tracking error” and the “trajectory error” are determined as “large”.
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 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) 1 – 2, 6 – 11, 15 – 18 are rejected under 35 U.S.C. 103 as being unpatentable over Gyllenhammar et al. (Publication No. US 20210394794 A1; hereinafter Gyllen) in view of Shiue et al. (Publication No. US 20210183171 A1; hereinafter Shiue) and in further view of Olson et al. (Publication No. US 20210046923 A1; hereinafter Olson).
Regarding to claim 1, Gyllen teaches
A computer-implemented method when executed by data processing hardware causes the data processing hardware to perform operations comprising:
monitoring, via a trajectory control architecture of a controller, at least one active safety feature and a trajectory of a vehicle; ([Par. 0021], “The trajectory monitoring system 1 is adapted for assessment of a vehicle control system 211 of an advanced driver-assistance system, ADAS, or autonomous driving, AD, system 21 of the vehicle 2. The trajectory monitoring system 1 may optionally be comprised in the ADAS or AD system 21, and/or be provided in association and/or connection therewith 21.”; [Par. 0020], “according to embodiments herein which relate to assessment of a vehicle control system of an ADAS or AD system of a vehicle, there will be disclosed an approach according to which vehicle control actuations of the ADAS or AD system may be monitored for performance, safety and/or validation while the ADAS or AD system is operating.”; [Par. 0024], “The trajectory monitoring system 1 is—e.g. by means of a planned trajectory determining unit 101—adapted and/or configured for determining in view of a reference system 3 a planned vehicle trajectory 4 adapted to be executed by the vehicle control system 211 during a predeterminable time period T. Thereby, there is mapped an upcoming intended vehicle trajectory 4 to a reference system 3 —such as a coordinate system and/or digital map—applicable for the vehicle 2 and/or said intended vehicle trajectory 4.”)
tracking, via the trajectory control architecture, an error of the trajectory; ([Par. 0061], “In Action 1003, the trajectory monitoring system 1 determines—e.g. with support from the deviation determining unit 103—an accuracy deviation measure 7 indicating deviation between the actual vehicle trajectory 5 and the planned vehicle trajectory 4.”)
Gyllen teaches determine the error of the trajectory based on the deviation between the planned trajectory and the actual trajectory as described above, but does not explicitly disclose comparing the tracked error with a trajectory history stored on the controller;
However, Shiue teaches comparing the tracked error with a trajectory history stored on the controller. ([Par. 0034], “In Step S418, the abnormality estimating unit 21 for snaking retrieves the present position information of the vehicle-parameter information and compares the present position information with a given historical steering angle and a given historical trajectory. When the steering angle of the vehicle-parameter information is larger than the given historical steering angle and a difference between the vehicle trajectory and the given historical trajectory is larger than a historical trajectory error, the abnormality estimating unit 21 for snaking generates the abnormality warning signal and transmits it to the far-end server 30, such that the far-end server 30 displays the abnormality warning signal.”
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claim invention to modify Gyllen to incorporate the teaching of Shiue. The modification would have been obvious because comparing a tracked trajectory error with a historical trajectory enables more accurate estimation of deviation in the vehicle’s current trajectory, thereby allowing the system to reliably detect abnormal driving behavior and trigger an appropriate warning or corrective action.
The combination of Gyllen and Shiue teaches to monitor the trajectory error of the vehicle as described above, but does not explicitly disclose adapting, based on the comparison of the tracked error and the trajectory history, performance elements of the vehicle via the trajectory control architecture; and monitoring, based on the adapted performance elements, the trajectory of the vehicle.
However, Olsen teaches adapting, based on the comparison of the tracked error and the trajectory history, performance elements of the vehicle via the trajectory control architecture; ([Par. 0153 – 0154], “a potential state of the device to follow a potential trajectory may be obtained, for example, by TMP 222 in the case the device is an autonomous vehicle, and/or system monitor 220. In some cases, operation 1304 may include determining the potential state based on the current state, such as a location proximate to a location associated with the current state. [0154] At operation 1306, the current state may be compared with the potential state, and at operation1308, it may be determined if the potential trajectory passes one or more consistency checks. The one or more consistency checks may include one or more of the consistency checks described above. Operations 1306 and 1308 may include generating a difference between the current state and the potential state, and comparing the difference to a set of deviation values, such as described above.”; [Par. 0159], “The system monitor 220 may update the feasibility limits according to various inputs received by the system monitor 220, including system data and status updates from the primary compute unit202 and/or drive manager 402, and/or other data, such as sensor data. In some aspects, the system monitor 220 may maintain and update various status information on various subsystems of the vehicle, including, for example a current state of a number of subsystems, which may affect one or more feasibility limits. In one example, operational states or statuses for various subsystem of an autonomous vehicle 1400 may include tire pressure information, motor operation as a percentage, various components of the vehicle electrical system, and various other subsystems as may be found in a vehicle or autonomous vehicle, or other device capable of movement.” and
monitoring, based on the adapted performance elements, the trajectory of the vehicle. ([Par. 0162], “a collection of feasibility limits, and/or adjustments thereto may be specific to one or more trajectory types, such as primary trajectory, a contingent trajectory, and so on. In this example, the system monitor 220 may set different capability limits for different types of trajectories. For example, a maximum velocity of a contingent trajectory may be set lower than for a primary trajectory.”; [Par. 0163], “Upon updating the feasibility limits, the system monitor 220 may send the updated limits, e.g., in the form of one or more values TMP 222 and primary compute unit 202. The TMP 222 may use the feasibility limits in the process of validating potential trajectories and the primary compute unit 202and/or trajectory planner AI 212 may use the feasibility limits in generating new trajectories. Upon selecting a potential trajectory, the TMP 222 may then send the one or more trajectories to the primary compute unit 202, system monitor 220, and drive manager 402 to provide further feedback for future trajectory determination.”
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claim invention to modify the combination of Gyllen and Shiue to incorporate the teaching of Olson. The modification would have been obvious because adapting the vehicle’s performance elements based on the determined trajectory error enables adjustment of vehicle operation to reduce deviation and cause the vehicle to follow a more accurate trajectory.
Regarding to claim 2, the combination of Gyllen, Shiue, and Olson teaches the method of claim 1.
Gyllen further teaches wherein the error includes at least one of a tracking error and a trajectory error. ([Par. 0061], “In Action 1003, the trajectory monitoring system 1 determines—e.g. with support from the deviation determining unit 103—an accuracy deviation measure 7 indicating deviation between the actual vehicle trajectory 5 and the planned vehicle trajectory 4.”)
Regarding to claim 6, the combination of Gyllen, Shiue, and Olson teaches the method of claim 1.
Olson further teaches further including projecting, based on a time step and the trajectory history, a new trajectory at future time steps. ([Par. 0153 – 0154], “a potential state of the device to follow a potential trajectory may be obtained, for example, by TMP 222 in the case the device is an autonomous vehicle, and/or system monitor 220. In some cases, operation 1304 may include determining the potential state based on the current state, such as a location proximate to a location associated with the current state. [0154] At operation 1306, the current state may be compared with the potential state, and at operation1308, it may be determined if the potential trajectory passes one or more consistency checks. The one or more consistency checks may include one or more of the consistency checks described above. Operations 1306 and 1308 may include generating a difference between the current state and the potential state, and comparing the difference to a set of deviation values, such as described above.”)
Regarding to claim 7, the combination of Gyllen, Shiue, and Olson teaches the method of claim 6.
Shiue further teaches wherein tracking the error includes identifying a tracking error based on the trajectory history and a current position. ([Par. 0010], “retrieving the position information of the vehicle and comparing the position information with a given historical steering angle and a given historical trajectory, and the abnormality analyzing module generating the abnormality warning signal when the steering angle of the vehicle-parameter information is larger than the given historical steering angle and a difference between the vehicle trajectory and the given historical trajectory is larger than ahistorical trajectory error.”)
Regarding to claim 8, the combination of Gyllen, Shiue, and Olson teaches the method of claim 6.
Olson further teaches wherein projecting the new trajectory includes comparing a historical trajectory window with a future trajectory point. ([Par. 0144], “In order to determine whether potential trajectory is consistent with a current trajectory or state of a vehicle, the current location may first be obtained or determined. In some cases, the current location could be an estimated location at a future time, for example, corresponding to a location when the vehicle would start the potential trajectory 1204 or at the end of trajectory 1214. The vehicle maybe projected onto the potential trajectory 1204 into a potential state, such as state 1208. In some cases, state 1208 may be selected to be the closest location to the current state 1216 of the vehicle on trajectory 1204. The potential state 1208 may be determined relative to the current state 1216, to, for example minimize the distance between the two points. This may include a geometric evaluation (such as determining a shortest Euclidian distance between the trajectory 1204 and state 1216 or via other means).”; [Par. 0145], “In some cases, a current trajectory, represented by a state of the vehicle at location 1216, maybe compared to state 1208 on potential trajectory 1204. Each state 1216 and 1208 of the vehicle maybe represented by a number of parameters, such as position, orientation, yaw, and/or velocity. These values may be compared to determine one or more deviation values, such as a distance between the two states, a command steering position difference between the vehicle at the first state 1216 and vehicle at the second state 1208, a yaw deviation between the two states, and/or a velocity deviation between the two states. For example, a distance to trajectory threshold may indicate when a vehicle is too far from a potential trajectory to be consistent. Another example includes a command steering position, which may be how far a vehicle would have to change its steering angle to reach the potential trajectory. The deviation values may then be compared to one or more thresholds to determine if the potential trajectory 12104 is consist with a current trajectory of the vehicle.”)
Regarding to claim 9, the combination of Gyllen, Shiue, and Olson teaches the method of claim 8.
Olson further teaches further including determining, based on the comparison between the historical trajectory window and the future trajectory point, a trajectory error. ([Par. 0144], “In order to determine whether potential trajectory is consistent with a current trajectory or state of a vehicle, the current location may first be obtained or determined. In some cases, the current location could be an estimated location at a future time, for example, corresponding to a location when the vehicle would start the potential trajectory 1204 or at the end of trajectory 1214. The vehicle maybe projected onto the potential trajectory 1204 into a potential state, such as state 1208. In some cases, state 1208 may be selected to be the closest location to the current state 1216 of the vehicle on trajectory 1204. The potential state 1208 may be determined relative to the current state 1216, to, for example minimize the distance between the two points. This may include a geometric evaluation (such as determining a shortest Euclidian distance between the trajectory 1204 and state 1216 or via other means).”; [Par. 0145], “In some cases, a current trajectory, represented by a state of the vehicle at location 1216, maybe compared to state 1208 on potential trajectory 1204. Each state 1216 and 1208 of the vehicle maybe represented by a number of parameters, such as position, orientation, yaw, and/or velocity. These values may be compared to determine one or more deviation values, such as a distance between the two states, a command steering position difference between the vehicle at the first state 1216 and vehicle at the second state 1208, a yaw deviation between the two states, and/or a velocity deviation between the two states. For example, a distance to trajectory threshold may indicate when a vehicle is too far from a potential trajectory to be consistent. Another example includes a command steering position, which may be how far a vehicle would have to change its steering angle to reach the potential trajectory. The deviation values may then be compared to one or more thresholds to determine if the potential trajectory 12104 is consist with a current trajectory of the vehicle.”)
Claim 10 recites the system with substantially similar scope as claim 1, thus being rejected for the same basis as claim 1 above.
Gyllen further teaches A system comprising: data processing hardware; and
memory hardware in communication with the data processing hardware, the memory hardware storing instructions that when executed on the data processing hardware cause the data processing hardware to perform operations
([Par. 0010], “the disclosed subject-matter relates to a computer program product comprising a computer program containing computer program code means arranged to cause a computer or a processor to execute the steps of a trajectory monitoring system described herein, stored on a computer-readable medium or a carrier wave.”)
Claims 11, 15 – 18 recites the system with substantially similar scope as claims 2, 6 – 9 respectively, thus being rejected for same basis as claims 2, 6 – 9 respectively above.
Claim(s) 3 – 5, 12 – 14 are rejected under 35 U.S.C. 103 as being unpatentable over the combination of Gyllen, Shiue and Olson in view of Hruschka et al. (English Translation of DE102019212666A1; hereinafter Hruschka).
Regarding to claim 3, the combination of Gyllen, Shiue, and Olson teaches the method of claim 1.
The combination of Gyllen, Shiue and Olson teaches to monitor the trajectory error as described in claim 1 above, but does not explicitly disclose further including determining, via the trajectory control architecture, at least one of a large tracking error and a large trajectory error based on a maneuver phase.
However, Hruschka teaches further including determining, via the trajectory control architecture, at least one of a large tracking error and a large trajectory error based on a maneuver phase. ([Par. 0025], “As a first step, at least one trajectory to be driven by the vehicle is planned. The trajectory can be... B. represent an evasive maneuver to avoid a collision. In addition, expected control errors are determined for at least one trajectory to be driven. This involves including at least one vehicle model and an empirically determined model error.”)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claim invention to modify the combination of Gyllen, Shiue and Olson to incorporate the teaching of Hruschka. The modification would have been obvious because determining trajectory error as a function of the maneuver phase allows the system to more accurately assess when trajectory deviations become safety-critical, and to trigger appropriate corrective actions (e.g., limit the maneuver, re-plan, or stabilize) to reduce the likelihood of a collision or loss of control.
Regarding to claim 4, the combination of Gyllen, Shiue, Olson, and Hruschka teaches the method of claim 3.
Hruschka further teaches wherein determining the large tracking error and large trajectory error includes comparing the maneuver phase with an error threshold of the trajectory control architecture. ([Par. 0040], “the error is evaluated for the actual lateral position y<sub>ref</sub>of the vehicle and the actual yaw angle φ<sub>ref</sub>of the vehicle with respect to the values set for the trajectories and compared with the respective predicted standard deviations σ. Both errors are evaluated separately, effectively doubling the number of available samples.”)
Regarding to claim 5, the combination of Gyllen, Shiue, Olson, and Hruschka teaches the method of claim 4.
Shiue further teaches wherein the maneuver phase includes one or more of an initiation phase, a countersteer phase, and a stability phase. ([Par. 0026], “A planning module 22 is used to plan at least one trajectory to be driven and to adjust the planning taking into account expected control errors for the at least one trajectory to be driven. The trajectory can be... B. represent an evasive maneuver to avoid a collision. The planning can be done, for example, by... B. can be adjusted by extending a safety distance to other road users by a confidence interval of a probability distribution resulting from the control errors.” Wherein this is mapped to any of initiation phase or countersteer phase.)
Claims 12 - 14 recites the system with substantially similar scope as claims 3 - 5 respectively, thus being rejected for same basis as claims 3 - 5 respectively above.
Claim(s) 19 is rejected under 35 U.S.C. 103 as being unpatentable over Gyllen in view of Olson.
Regarding to claim 19, Gyllen teaches A computer-implemented method when executed by data processing hardware causes the data processing hardware to perform operations ([Par. 0010], “the disclosed subject-matter relates to a computer program product comprising a computer program containing computer program code means arranged to cause a computer or a processor to execute the steps of a trajectory monitoring system described herein, stored on a computer-readable medium or a carrier wave.”) comprising:
monitoring, via a trajectory control architecture of a controller, at least one active safety feature and a trajectory of a vehicle; ([Par. 0021], “The trajectory monitoring system 1 is adapted for assessment of a vehicle control system 211 of an advanced driver-assistance system, ADAS, or autonomous driving, AD, system 21 of the vehicle 2. The trajectory monitoring system 1 may optionally be comprised in the ADAS or AD system 21, and/or be provided in association and/or connection therewith 21.”; [Par. 0020], “according to embodiments herein which relate to assessment of a vehicle control system of an ADAS or AD system of a vehicle, there will be disclosed an approach according to which vehicle control actuations of the ADAS or AD system may be monitored for performance, safety and/or validation while the ADAS or AD system is operating.”; [Par. 0024], “The trajectory monitoring system 1 is—e.g. by means of a planned trajectory determining unit 101—adapted and/or configured for determining in view of a reference system 3 a planned vehicle trajectory 4 adapted to be executed by the vehicle control system 211 during a predeterminable time period T. Thereby, there is mapped an upcoming intended vehicle trajectory 4 to a reference system 3 —such as a coordinate system and/or digital map—applicable for the vehicle 2 and/or said intended vehicle trajectory 4.”)
tracking, via the trajectory control architecture, one of a trajectory error and a tracking error of the trajectory; ([Par. 0061], “In Action 1003, the trajectory monitoring system 1 determines—e.g. with support from the deviation determining unit 103—an accuracy deviation measure 7 indicating deviation between the actual vehicle trajectory 5 and the planned vehicle trajectory 4.”)
Gyllen teaches monitor the error of the trajectory of the vehicle as described above, but does not explicitly disclose projecting, based on a time step and a trajectory history, a new trajectory at future time steps; comparing the tracked error and a historical trajectory window with a future trajectory point; adapting, via the trajectory control architecture, performance elements of the vehicle based on the projected new trajectory and the comparison of the tracked error and the trajectory history with the future trajectory point; and monitoring, based on the adapted performance elements, the trajectory of the vehicle.
However, Olson teaches projecting, based on a time step and a trajectory history, a new trajectory at future time steps; ([Par. 0144], “In order to determine whether potential trajectory is consistent with a current trajectory or state of a vehicle, the current location may first be obtained or determined. In some cases, the current location could be an estimated location at a future time, for example, corresponding to a location when the vehicle would start the potential trajectory 1204 or at the end of trajectory 1214. The vehicle maybe projected onto the potential trajectory 1204 into a potential state, such as state 1208. In some cases, state 1208 may be selected to be the closest location to the current state 1216 of the vehicle on trajectory 1204. The potential state 1208 may be determined relative to the current state 1216, to, for example minimize the distance between the two points. This may include a geometric evaluation (such as determining a shortest Euclidian distance between the trajectory 1204 and state 1216 or via other means).”; [Par. 0153], “a potential state of the device to follow a potential trajectory may be obtained, for example, by TMP 222 in the case the device is an autonomous vehicle, and/or system monitor 220. In some cases, operation 1304 may include determining the potential state based on the current state, such as a location proximate to a location associated with the current state. Wherein the “potential trajectory” corresponds to the “new trajectory” at the future time steps.)
comparing the tracked error and a historical trajectory window with a future trajectory point; ([Par. 0144], “In order to determine whether potential trajectory is consistent with a current trajectory or state of a vehicle, the current location may first be obtained or determined. In some cases, the current location could be an estimated location at a future time, for example, corresponding to a location when the vehicle would start the potential trajectory 1204 or at the end of trajectory 1214. The vehicle maybe projected onto the potential trajectory 1204 into a potential state, such as state 1208. In some cases, state 1208 may be selected to be the closest location to the current state 1216 of the vehicle on trajectory 1204. The potential state 1208 may be determined relative to the current state 1216, to, for example minimize the distance between the two points. This may include a geometric evaluation (such as determining a shortest Euclidian distance between the trajectory 1204 and state 1216 or via other means).”; [Par. 0145], “In some cases, a current trajectory, represented by a state of the vehicle at location 1216, maybe compared to state 1208 on potential trajectory 1204. Each state 1216 and 1208 of the vehicle maybe represented by a number of parameters, such as position, orientation, yaw, and/or velocity. These values may be compared to determine one or more deviation values, such as a distance between the two states, a command steering position difference between the vehicle at the first state 1216 and vehicle at the second state 1208, a yaw deviation between the two states, and/or a velocity deviation between the two states. For example, a distance to trajectory threshold may indicate when a vehicle is too far from a potential trajectory to be consistent. Another example includes a command steering position, which may be how far a vehicle would have to change its steering angle to reach the potential trajectory. The deviation values may then be compared to one or more thresholds to determine if the potential trajectory 12104 is consist with a current trajectory of the vehicle.”; [Par. 0154] At operation 1306, the current state may be compared with the potential state, and at operation1308, it may be determined if the potential trajectory passes one or more consistency checks. The one or more consistency checks may include one or more of the consistency checks described above. Operations 1306 and 1308 may include generating a difference between the current state and the potential state, and comparing the difference to a set of deviation values, such as described above.”)
adapting, via the trajectory control architecture, performance elements of the vehicle based on the projected new trajectory and the comparison of the tracked error and the trajectory history with the future trajectory point; ([Par. 0153 – 0154], “a potential state of the device to follow a potential trajectory may be obtained, for example, by TMP 222 in the case the device is an autonomous vehicle, and/or system monitor 220. In some cases, operation 1304 may include determining the potential state based on the current state, such as a location proximate to a location associated with the current state. [0154] At operation 1306, the current state may be compared with the potential state, and at operation1308, it may be determined if the potential trajectory passes one or more consistency checks. The one or more consistency checks may include one or more of the consistency checks described above. Operations 1306 and 1308 may include generating a difference between the current state and the potential state, and comparing the difference to a set of deviation values, such as described above.”; [Par. 0159], “The system monitor 220 may update the feasibility limits according to various inputs received by the system monitor 220, including system data and status updates from the primary compute unit202 and/or drive manager 402, and/or other data, such as sensor data. In some aspects, the system monitor 220 may maintain and update various status information on various subsystems of the vehicle, including, for example a current state of a number of subsystems, which may affect one or more feasibility limits. In one example, operational states or statuses for various subsystem of an autonomous vehicle 1400 may include tire pressure information, motor operation as a percentage, various components of the vehicle electrical system, and various other subsystems as may be found in a vehicle or autonomous vehicle, or other device capable of movement.”) and
monitoring, based on the adapted performance elements, the trajectory of the vehicle. ([Par. 0162], “a collection of feasibility limits, and/or adjustments thereto may be specific to one or more trajectory types, such as primary trajectory, a contingent trajectory, and so on. In this example, the system monitor 220 may set different capability limits for different types of trajectories. For example, a maximum velocity of a contingent trajectory may be set lower than for a primary trajectory.”; [Par. 0163], “Upon updating the feasibility limits, the system monitor 220 may send the updated limits, e.g., in the form of one or more values TMP 222 and primary compute unit 202. The TMP 222 may use the feasibility limits in the process of validating potential trajectories and the primary compute unit 202and/or trajectory planner AI 212 may use the feasibility limits in generating new trajectories. Upon selecting a potential trajectory, the TMP 222 may then send the one or more trajectories to the primary compute unit 202, system monitor 220, and drive manager 402 to provide further feedback for future trajectory determination.”
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claim invention to modify the combination of Gyllen to incorporate the teaching of Olson. The modification would have been obvious because evaluating the error between the vehicle’s current trajectory and a potential trajectory at future time steps enables the system to detect trajectory deviations in advance and adjust vehicle operation accordingly, thereby reducing collision risk and ensuring that the vehicle follows an appropriate potential trajectory.
Claim(s) 20 is rejected under 35 U.S.C. 103 as being unpatentable over the combination of Gyllen and Olson in view of Hruschka.
Regarding to claim 20, the combination of Gyllen Olson teaches the method of claim 1.
The combination of Gyllen and Olson teaches to monitor the trajectory error as described in claim 1 above, but does not explicitly disclose further including determining, via the trajectory control architecture, at least one of a large tracking error and a large trajectory error based on a maneuver phase.
However, Hruschka teaches further including determining, via the trajectory control architecture, at least one of a large tracking error and a large trajectory error based on a maneuver phase. ([Par. 0025], “As a first step, at least one trajectory to be driven by the vehicle is planned. The trajectory can be... B. represent an evasive maneuver to avoid a collision. In addition, expected control errors are determined for at least one trajectory to be driven. This involves including at least one vehicle model and an empirically determined model error.”)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claim invention to modify the combination of Gyllen and Olson to incorporate the teaching of Hruschka. The modification would have been obvious because determining trajectory error as a function of the maneuver phase allows the system to more accurately assess when trajectory deviations become safety-critical, and to trigger appropriate corrective actions (e.g., limit the maneuver, re-plan, or stabilize) to reduce the likelihood of a collision or loss of control.
Conclusion
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