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 .
This Office Action is in response to Applicant Amendment and Arguments filed on 4/28/2026.
Claim(s) 1-6 are pending for examination.
This Action is made NON-FINAL.
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 4/28/2026 has been entered.
Response to Arguments
With regards to claim(s) 1 - 6 previously rejected under 35 U.S.C. 103 have been considered but are deemed moot in view of the new grounds of rejection necessitated by Applicant's Amendment.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis 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) 1-3 are rejected under 35 U.S.C. 103 as being unpatentable over Oba (US 20240034362 A1) in view of Ishioka et al. (US 20200207355 A1, hereinafter known as Ishioka).
Regarding claim 1, Oba teaches A method for providing a fallback for a failure situation occurring in autonomous driving performed by an autonomous driving system, the method comprising:
{abstract “information processing is disclosed. In one example, an information processing device includes automated driving control notifies a vehicle driver of a condition enabling automated driving of the vehicle based on an operation design domain that is set for the vehicle. In another example, an information processing method notifies a vehicle driver of a condition enabling automated driving of the vehicle based on the set operation design domain for the vehicle. In another example, an information processing program is configured to cause a computer to execute an automated driving control step of making a notification to a driver of a vehicle regarding a condition enabling automated driving of the vehicle based on an operation design domain that is set for the vehicle.”
}
predicting whether a vehicle will deviate from a geographical boundary of an operational design domain (ODD) while the vehicle drives autonomously along a route, and determining a deviation point and a deviation time point by comparing a current speed and the route of the vehicle with the ODD; and
performing a minimal risk maneuver (MRM) process of controlling the vehicle to provide the fallback for the failure situation occurring in the autonomous driving based on the deviation point,
{Para [0122] “he situation recognition unit 10153 performs recognition processing on a situation related to the own vehicle based on data or signals from each unit of the vehicle control system 10100, such as the self-position estimation unit 10132, the vehicle exterior information detection unit 10141, the vehicle interior information detection unit 10142, the vehicle state detection unit 10143, and the map analysis unit 10151. For example, the situation recognition unit 10153 performs recognition processing on situations such as own vehicle situations, own vehicle surrounding situations, and own vehicle driver situations. In addition, the situation recognition unit 10153 generates a local map (hereinafter, it is referred to as a situation recognition map) used to recognize the situation around the own vehicle as necessary. The situation recognition map is an occupancy grid map, for example.”
Para [0123] “Examples of the own vehicle situations to be recognized include the position, attitude, and movement (for example, speed, acceleration, and moving direction) of the own vehicle, and the presence or absence of abnormality as well as details of the abnormality if any. Examples of the own vehicle surrounding situations to be recognized include a type and a position of a surrounding stationary object, a type, a position, and a movement (for example, speed, acceleration, moving direction, and the like) of a surrounding moving object, a configuration of a surrounding road and a state of a road surface, as well as conditions such as surrounding weather, temperature, humidity, and brightness. Examples of the driver situations to be recognized include a driver's physical condition, a wakefulness level, a concentration level, a fatigue level, movement of a line of sight, and driving operation.”
Para [0182] “For example, it is assumed that a specific expressway permits automated driving travel at driving automation level 4, and the automated driving performance of on-board devices of the vehicle permits automated driving travel corresponds to driving automation level 4. In this case, the driver can travel through the section using the driving automation level of the vehicle as level 4. When the vehicle approaches a situation where the vehicle deviates from the ODD section where the vehicle can travel at the driving automation level 4, the automated driving system prompts the driver to perform recovery to manual-controlled driving (FIG. 5, step S10). When the response is delayed, the automated driving system simply issues a warning (FIG. 5, step S11). When the automated driving system does not perform recovery to the manual-controlled driving at an appropriate timing even though the warning is issued in step S11, the automated driving system is supposed to shift to emergency forced evacuation steering, the control referred to as MRM within the ODD section where the vehicle can travel with the automated driving at the driving automation level 4 (FIG. 5, step S14), thereby preventing the vehicle from entering the section where the automated driving cannot be handled by the system.”
Para [0189] “In the next step S22, the automated driving system manages a step of handover to manual-controlled driving by the driver. For example, the automated driving system performs monitoring of the state of the driver, and determines, in step S22, the margin from the current time point (current geographical point) to the handover start point, whether to extend the grace time until the handover start, and the like based on the monitoring result, the state of the vehicle at that time point, and the like. The automated driving system performs control such as further notification and transition to MRM according to the determination result.”
Para [0190] “The “margin” herein is a time that can be ensured longer than the time required to reach the handover completion limit point when the vehicle travels at a cruising speed estimated from the flow of surrounding vehicles on the road on which the vehicle is traveling, as compared with the time estimated to be required by the driver to achieve recovery by the driver status analysis detected through continuous passive monitoring. In addition, the “extension of the grace time until the handover start” described above refers to extending the time before reaching the handover completion limit point by, for example, reducing the traveling speed of the vehicle or moving to a road shoulder, temporary evacuation area, or a low-speed traveling lane without disturbing the flow of surrounding cruise traveling vehicles.”
}
wherein the MRM process comprises, when the deviation from the geographical boundary of the ODD is predicted:
{Para [0344] “On the other hand, on an ordinary road having a traffic of many ordinary passenger cars, it is necessary to perform automated handling along the flow of the corresponding road section without disturbing the flow. At this time, at a stage where automated handling is predicted to be difficult, the system needs to select whether to perform handover to manual-controlled driving, to enable completion of smooth handover to the driver at a cruising speed that is safe in automated driving. When estimation of successful operation is low, the system needs to perform selection such as whether to take evacuation travel to a road shoulder, a service area, an evacuation parking pool space, or a general road permitting stop or low speed travel while evacuation selection is left as selection candidate.”
}
Oba does not teach, sequentially searching for a full-shoulder stop zone as a safe zone in a first section of the route from the deviation time point, the full-shoulder stop zone having a shoulder width sufficient for the vehicle to fully stop on a shoulder; and
when the full-shoulder stop zone is unavailable in the first section, searching for a half-shoulder stop zone as the safe zone in a second section of the route subsequent to the first section and before the deviation time point, the half-shoulder stop zone having a shoulder width less than the full-shoulder stop zone.
However, Ishioka teaches sequentially searching for a full-shoulder stop zone as a safe zone in a first section of the route from the deviation time point, the full-shoulder stop zone having a shoulder width sufficient for the vehicle to fully stop on a shoulder; and
{Fig. 3 para [0166] “The vehicle control device (10) according to the present invention performs the lane change assist control from the merging lane (302) into the main line (320), the vehicle control device (10) comprising the external environment recognition unit (200) that detects the surrounding situation in front of the host vehicle (12) and in a direction of the main line while traveling in the merging lane (302), the merging assist capability determination unit (220) which determines, on the basis of the detected surrounding situation, whether or not the lane change assist control from the merging lane (302) into the main line (320) is possible, and the vehicle stop control unit (228) which causes the host vehicle (12) to stop at an appropriate vehicle stop position in the case that merging into the main line is impossible, wherein, in the case that the vehicle stop position (312) exists outside of a road more ahead of the vanishing point (310) of the merging lane (302), the vehicle stop control unit (228) causes the host vehicle to stop outside of the road, and in the case that the vehicle stop position (312) does not exist outside of the road, the vehicle stop control unit (228) causes the host vehicle to stop within the merging lane (302).”
Label 312 can be considered as a full shoulder.
}
when the full-shoulder stop zone is unavailable in the first section, searching for a half-shoulder stop zone as the safe zone in a second section of the route subsequent to the first section and before the deviation time point, the half-shoulder stop zone having a shoulder width less than the full-shoulder stop zone.
{para [0166] “The vehicle control device (10) according to the present invention performs the lane change assist control from the merging lane (302) into the main line (320), the vehicle control device (10) comprising the external environment recognition unit (200) that detects the surrounding situation in front of the host vehicle (12) and in a direction of the main line while traveling in the merging lane (302), the merging assist capability determination unit (220) which determines, on the basis of the detected surrounding situation, whether or not the lane change assist control from the merging lane (302) into the main line (320) is possible, and the vehicle stop control unit (228) which causes the host vehicle (12) to stop at an appropriate vehicle stop position in the case that merging into the main line is impossible, wherein, in the case that the vehicle stop position (312) exists outside of a road more ahead of the vanishing point (310) of the merging lane (302), the vehicle stop control unit (228) causes the host vehicle to stop outside of the road, and in the case that the vehicle stop position (312) does not exist outside of the road, the vehicle stop control unit (228) causes the host vehicle to stop within the merging lane (302).”
Para [0178] “Further still, in the vehicle control device (10), when causing the host vehicle to stop within the merging lane (302) in the case that the vehicle stop position (312) does not exist outside of the road, the vehicle stop control unit (228) may cause the host vehicle to stop in the vicinity of the vanishing point (310) of the merging lane (302).”
Fig. 3 label 310, Where the vanishing point can be considered as a half shoulder
}
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Oba to incorporate the teachings of Ishioka to try to first stop in a full shoulder before attempting to stop in a half shoulder because it prevents the blocking of traffic if possible para [0171] “In accordance with this feature, obstruction of the flow of traffic within the merging lane (302) can be minimized.”
Regarding claim 2, Oba in view of Ishioka teaches The method of claim 1.
Oba teaches wherein the MRM process includes making a request for a vehicle driver to intervene in the autonomous driving at a time point when the deviation is predicted or in advance from the time point, and
changing a driving mode to a manual driving mode when a vehicle control is given over to the driver by the driver intervention (or override).
{Para [0182] “For example, it is assumed that a specific expressway permits automated driving travel at driving automation level 4, and the automated driving performance of on-board devices of the vehicle permits automated driving travel corresponds to driving automation level 4. In this case, the driver can travel through the section using the driving automation level of the vehicle as level 4. When the vehicle approaches a situation where the vehicle deviates from the ODD section where the vehicle can travel at the driving automation level 4, the automated driving system prompts the driver to perform recovery to manual-controlled driving (FIG. 5, step S10). When the response is delayed, the automated driving system simply issues a warning (FIG. 5, step S11). When the automated driving system does not perform recovery to the manual-controlled driving at an appropriate timing even though the warning is issued in step S11, the automated driving system is supposed to shift to emergency forced evacuation steering, the control referred to as MRM within the ODD section where the vehicle can travel with the automated driving at the driving automation level 4 (FIG. 5, step S14), thereby preventing the vehicle from entering the section where the automated driving cannot be handled by the system.”
}
Regarding claim 3, Oba in view of Ishioka and Kim teaches The method of claim 2.
Oba teaches wherein the MRM process includes instructing an emergency stop of the vehicle when the driver intervention is impossible.
{Para [0182] “For example, it is assumed that a specific expressway permits automated driving travel at driving automation level 4, and the automated driving performance of on-board devices of the vehicle permits automated driving travel corresponds to driving automation level 4. In this case, the driver can travel through the section using the driving automation level of the vehicle as level 4. When the vehicle approaches a situation where the vehicle deviates from the ODD section where the vehicle can travel at the driving automation level 4, the automated driving system prompts the driver to perform recovery to manual-controlled driving (FIG. 5, step S10). When the response is delayed, the automated driving system simply issues a warning (FIG. 5, step S11). When the automated driving system does not perform recovery to the manual-controlled driving at an appropriate timing even though the warning is issued in step S11, the automated driving system is supposed to shift to emergency forced evacuation steering, the control referred to as MRM within the ODD section where the vehicle can travel with the automated driving at the driving automation level 4 (FIG. 5, step S14), thereby preventing the vehicle from entering the section where the automated driving cannot be handled by the system.”
Para [0344] “On the other hand, on an ordinary road having a traffic of many ordinary passenger cars, it is necessary to perform automated handling along the flow of the corresponding road section without disturbing the flow. At this time, at a stage where automated handling is predicted to be difficult, the system needs to select whether to perform handover to manual-controlled driving, to enable completion of smooth handover to the driver at a cruising speed that is safe in automated driving. When estimation of successful operation is low, the system needs to perform selection such as whether to take evacuation travel to a road shoulder, a service area, an evacuation parking pool space, or a general road permitting stop or low speed travel while evacuation selection is left as selection candidate.”
}
Claim(s) 4-5 are rejected under 35 U.S.C. 103 as being unpatentable over Oba (US 20240034362 A1) in view of Ishioka et al. (US 20200207355 A1, hereinafter known as Ishioka) and Park et al. (US 20230382371 A1, hereinafter known as Park).
Regarding Claim 4, Oba in view of Ishioka teaches The method of claim 3.
Oba in view of Ishioka does not teach wherein the MRM process is classified into necessary control operations based on a MRM type that determines a stop type by a diagnosis result of a failure cause of the vehicle.
Park teaches wherein the MRM process is classified into necessary control operations based on a MRM type that determines a stop type by a diagnosis result of a failure cause of the vehicle.
{Para [0073-0077] “When there is a request for the minimal risk maneuver, the vehicle 100 can determine a failure state (S120). According to the embodiments, the vehicle 100 may monitor the state of each of the components of the vehicle 100 and identify the failed components. The vehicle 100 may monitor the state of each of the components of the vehicle 100 in real time. The vehicle 100 may determine which sensor is currently available (or operable) among the sensors 110.
Also, the vehicle 100 can determine a failure state and a cause (or situation) of the failure state. For example, the vehicle 100 can additionally determine what causes the determined failure state.
The vehicle 100 may select a type of the minimal risk maneuver (S130). According to the embodiments, the vehicle 100 may select the type of the minimal risk maneuver suitable for a current failure state based on the determination result of the failure state.
The type of the minimal risk maneuver may include stopping the vehicle, controlling the steering of the vehicle, maintaining a lane, providing visual, audible and tactile notifications, decelerating the vehicle, accelerating the vehicle, and initiating/ending the autonomous driving, turning off the vehicle, transmitting an emergency signal, controlling a hazard warning light, speed reduction warning, controlling a brake light, transferring control authority to another passenger, and remote control.
The vehicle 100 can initiate the minimal risk maneuver by using the selected type of the minimal risk maneuver (S140). According to the embodiments, the vehicle 100 can control the vehicle 100 according to the selected type of the minimum risk maneuver. For example, the processor 130 of the vehicle 100 may transmit a control command corresponding to the selected type of the minimum risk maneuver to the controller 120, and the controller 120 may control the vehicle 100 in accordance with the control command.”
}
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Oba in view of Ishioka to incorporate the teachings of Park’s MRM process because it improves safety and driving stability para [0007] “According to the present disclosure, even if a vehicle is in risk due to an event occurring during autonomous driving, the minimal risk maneuver capable of eliminating the risk can be performed. Accordingly, the vehicle can escape from the risk and the condition of the vehicle can be converted into a minimal risk condition, so that the driving stability of the vehicle can be further increased.”
Regarding Claim 5, Oba in view of Ishioka and Park teaches The method of claim 4. Park further teaches wherein the MRM process requests safe zone information required based on the MRM type, and generates a route for the vehicle to stop on a received safe zone.
{Para [0148-0154] “As described above, the MRM type may include first to fifth five types.
The level 1 MRM type is the straight stop in which only the longitudinal deceleration control is performed, and the lateral control is not performed. According to the level 1 MRM type, the lateral control is impossible. For example, the level 1 MRM type may be selected in the case of a lane detection failure, control failure of a lateral actuator (steering), etc. When the MRM is performed according to the level 1 MRM type, the vehicle may deviate from the boundary of a lane or may deviate to the outside of the road. Therefore, the level 1 MRM type may not allow control to accelerate the vehicle.
The level 2 MRM type is the in-lane stop in which both longitudinal deceleration control and lateral control can be performed. The level 2 MRM type can determine a front target vehicle and route by using surrounding information such as sensors, map data, and communication information. The level 2 MRM type may be selected when it is possible to control the lane change but is not possible to drive a distance larger than a predetermined distance.
The level 3 MRM type is the lane change plus stop in traffic lane, in which longitudinal deceleration control and longitudinal acceleration control can be performed and lateral control can also be performed. The level 3 MRM type can determine a front target vehicle and route by using surrounding information such as sensors, map data, and communication information. The level 3 MRM type may be selected when it is not possible to move to a potential stopping area that is out of the flow of traffic. For example, the level 3 MRM type may be selected when the ADS system is operating normally and the potential stopping area cannot be detected or when it is impossible to drive to the potential stopping area by the ADS system due to time and/or system limit. The acceleration control can also be performed for stable lane change. Whether to change lanes or the number of lanes to be changed may be determined according to circumstances.
The level 4 MRM type is the shoulder stop in which longitudinal acceleration control and longitudinal deceleration control can be performed and lateral control can also be performed. The level 4 MRM type can determine a front target vehicle and route by using surrounding information such as sensors, map data, and communication information. The level 4 MRM type may be selected when it is possible to drive to the shoulder of a highway and when there is no obstacle on the shoulder. The acceleration control can also be performed when it is determined that the acceleration control is necessary in light of the flow of traffic to the shoulder.
The level 5 MRM type is the parking lane stop in which longitudinal acceleration control and longitudinal deceleration control can be performed and lateral control can also be performed. The level 5 MRM type can determine a front target vehicle and route by using surrounding information such as sensors, map data, and communication information. The level 5 MRM type may be selected when it is possible to drive to a parking space and when there is no obstacle in the parking space. The acceleration control can also be performed when it is determined that the acceleration control is necessary in light of the flow of traffic to the parking space.
Each of the MRM types described above may be performed within a predetermined execution time. Such execution time may include a minimum execution time and/or a maximum execution time. If the MRM cannot be performed within a predetermined execution time, the MRM type may be transitioned to a low-level type which can be performed immediately.”
}
Claim(s) 6 is rejected under 35 U.S.C. 103 as being unpatentable over Oba (US 20240034362 A1) in view of Ishioka et al. (US 20200207355 A1, hereinafter known as Ishioka), Park et al. (US 20230382371 A1, hereinafter known as Park), and Pendleton et al. (US 20230091987 A1, hereinafter known as Pendleton).
Regarding Claim 6, Oba in view of Ishioka and Park teaches The method of claim 5
Oba in view of Ishioka and Park does not teach, further comprising receiving a remote request to perform the MRM process from a control server when the deviation from the ODD or occurrence of the failure situation is determined as a monitoring result while the vehicle drives, wherein the control server provides the safe zone information when making the request to perform the MRM process.
However, Pendleton teaches further comprising receiving a remote request to perform the MRM process from a control server when the deviation from the ODD or occurrence of the failure situation is determined as a monitoring result while the vehicle drives,
{Para [0115-0116] “OED framework 600 further includes arbitrator system 625. Arbitrator system 625 is configured to receive perception map(s) 607 and the minimum perception zone data 611. In an embodiment, arbitrator system 625 is further configured to receive trajectory data 609 directly from planning system 404. Arbitrator system 625 then compares perception map(s) 607 and minimum perception zone data 611 (and, in an embodiment, trajectory data 609) to identify whether the AV is operating within its ODD. Specifically, arbitrator system 625 is configured to assign a first level of risk to an output of perception system 402. In some embodiments, arbitrator system 625 is configured to assign a first level of risk of non-compliance with a functional requirement related to the trajectory based on sensor data 606.
Arbitrator system 625 further assigns a second level of risk of non-compliance with the functional requirement to the output (e.g., minimum perception zone data 611) of assessment system 620. Arbitrator system 625 calculates a total level of risk based on the assigned first and second levels of risk. Based on the total level of risk, arbitrator system 625 identifies whether the AV is in a safe state. An example of a safe state is when the AV is able to perform the assigned trajectory/maneuver or navigate the assigned trajectory/maneuver within the ODD of the AV. An example of an unsafe state is when the requirements of the trajectory/maneuver exceed the functional capabilities of the AV. If arbitrator system 625 identifies that the AV is in an unsafe state, it outputs unsafe indicator data 616 to an intervention request system 630, which generates and sends/transmits an intervention request to, e.g., remote AV system 114 for RVA intervention or to planning system 404 and/or AV control system 408 for an MRM intervention.”
The arbitrator system and intervention request system can be remote as discussed in para [0109] “Referring to FIG. 6, FIG. 6 is an example OED framework. In some embodiments, one or more of the elements described with respect to OED framework 600 are performed (e.g., completely, partially, and/or the like) by one or more vehicles 102 (e.g., one or more devices of vehicles 102). Additionally, or alternatively, one or more elements described with respect to OED framework 600 can be performed (e.g., completely, partially, and/or the like) by another device or group of devices separate from, or including, vehicles 102 such as one or more of the other devices of any of FIGS. 1, 2, 3, and 4.”
}
wherein the control server provides the safe zone information when making the request to perform the MRM process.
{Para [0119] “In one embodiment, intervention request 612 is, for example, a request to an RVA operator or teleoperator for data associated with control of the vehicle. For example, intervention request 612 can include a request for data upon which control system 408 can act to cause the AV to take one or more actions. In another embodiment, intervention request 612 is a MRM which can be a pre-identified maneuver such as the AV slowing, stopping, pulling over, etc., to place the AV back into a safe state. In another embodiment, intervention request 612 can include a request for a degraded mode operation (DMO) task such as reduced speed operation.”
para [0160] “The process 1100 further includes identifying, at 1120 based on the PVM, a trajectory that is to be traversed by the at least one vehicle. Element 1120 can be performed by, for example, planning system 404, or by intervention request system 630. In an embodiment, the trajectory is similar to trajectory 520, described above. In another embodiment, the trajectory relates to a maneuver such as a MRM, an RVA request, a DMO, etc., as described above.”
As discussed in para [0109] the intervention request system can be a remote system. If intervention request system is providing the trajectory to stop or pull over it can be considered as providing the safe zone information when making the request to perform the MRM process
}
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Oba in view of Ishioka and Park to incorporate the teachings of Pendleton to classify the MRM process because it improves safety para [0056-0058] “Some of the advantages of the techniques described above include provision of a OED framework that efficiently addresses complexities involved in operation of an AV in an environment across various driving scenarios. In a specific example herein, the complexities relate to different driving scenarios where multiple factors (e.g., lighting, weather conditions, other objects that are in or near the road, characteristics of the road, etc.) influence the ODD of the autonomous system. The OED framework allows a minimum risk maneuver (MRM) or other maneuver or intervention is triggered based on a holistic analysis of a driving scenario. Another advantage is that embodiments herein provide a framework to model sensor perception capability and performance under different conditions. Such conditions include environmental conditions (e.g., fog, rain, sun glare, etc.), sensor-visibility conditions (e.g., blockage of the sensor by a foreign object such as mud), occlusion-related conditions (e.g., the detection of an object by the sensor), or sensor-structural conditions (e.g., the type or placement of the sensor). By identifying this OED framework, the model of the sensor perception capability is usable by the autonomous system to ascertain operational capabilities of the autonomous system in different scenarios so that the autonomous system may be operated within those capabilities. Another advantage is that embodiments herein provide a quantitative measure of non-compliance risk with respect to safety, regulatory and comfort rules under different well-defined driving scenarios, while still allowing for direct intervention assignment in response to ill-defined situations (e.g., anomalous events) or prolonged immobility (e.g., “stuck” detection). Multiple situations or scenarios are evaluated concurrently (e.g., lane change while navigating an intersection). Internal state agnostic metrics are generalized for both compliance check of current state and of predicted future states. Applicability of the situation assessment is independent of underlying decision making algorithm(s). The situation assessment can be used to assess multiple concurrent trajectory proposals.”
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure: Horigome (US 20210403037 A1) teaches in para [0061] “The first safe area setting unit 112 sets a first safe area SA1 (see FIG. 4) with respect to the vehicle external environment (e.g., a 3D map) estimated by the vehicle external environment estimation unit 111. The first safe area SA1 is set using a model constructed through deep learning as an area which the subject vehicle can pass. The model is constructed, for example, through reconstruction of a model previously constructed for each type of the motor vehicle 1 based on, e.g., the past driving history of the driver. The first safe area SA1 is what is called free space. For example, the free space is an area on the road without any dynamic obstacle such as other vehicles or pedestrians, and any static obstacle such as a median strip or traffic poles. The first safe area SA1 may include a space of the road shoulder 8 where the vehicle can stop in case of emergency.”
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ALEXANDER MATTA whose telephone number is (571)272-4296. The examiner can normally be reached Mon - Fri 10:00-6:00.
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/A.G.M./Examiner, Art Unit 3668
/ABDHESH K JHA/Primary Examiner, Art Unit 3668
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