DETAILED ACTION
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claims 1-20 are pending in Instant Application.
Priority
Examiner acknowledges Applicant’s claim to priority benefits of JP2023-148035 filed 09/13/2023.
Information Disclosure Statement
The information disclosure statement(s) (IDS) submitted on 09/11/2024, 01/30/2025, and 02/24/2026 are in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement(s) is/are being considered if signed and initialed by the Examiner.
Claim Objections
Claim 17 is objected to because of the following informalities: The claim provides a double comma on line 10. Examiner believes this is a typographical. Appropriate correction is required.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1-16 and 18-20 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Okamura et al. (USPGPub 2021/0122362). As per claim 1, Okamura discloses an inspection system of remotely or autonomously inspecting a mobile body that is movable through unattended operation, the inspection system comprising: a processor (see at least Figure 1; item 15), wherein the processor is configured to: generate and output a control instruction that causes the mobile body to operate (see at least paragraph 0099; wherein the vehicle instruction unit 15 gives various instructions to the autonomous driving vehicle 2 that performs automatic valet parking. When the autonomous driving vehicle 2 starts the automatic valet parking, the vehicle instruction unit 15 instructs the target route to reach the target parking space of the autonomous driving vehicle 2); and execute an abnormality process determined in advance in a case where a difference obtained by comparing at least two of physical quantities for the mobile body as a target is more than a criterion value determined in advance, the physical quantities including (see at least paragraph 0080; wherein the failure type determination unit 13 may determine that there is an abnormality in the internal sensor 23 when a predetermined time elapses in a state in which each parameter (vehicle speed, accelerations, yaw rate, and the like) of the recognition result of the traveling state in the vehicle information exceeds the abnormality determination threshold value) a first physical quantity related to operation of the mobile body achieved according to the control instruction, the first physical quantity being calculated using the control instruction (see at least paragraph 0081; wherein the failure type determination unit 13 may determine the presence or absence and the failure type caused by the vehicle based on the vehicle information and the detection result of the parking lot sensor 4. When the difference between the position information of the autonomous driving vehicles 2 included in the vehicle information and the position of the autonomous driving vehicles 2 recognized from the detection result of the parking lot sensor 4 (for example, the captured image of the monitoring camera) is equal to or greater than the error threshold value, the failure type determination unit 13 may determine that an abnormality in position recognition has occurred in the autonomous driving vehicles 2 as a vehicle-induced failure), a second physical quantity related to the operation, calculated using a result of a detection by an internal sensor mounted on the mobile body (see at least paragraph 0080; wherein the failure type determination unit 13 may determine that there is an abnormality in the internal sensor 23 when a predetermined time elapses in a state in which each parameter (vehicle speed, accelerations, yaw rate, and the like) of the recognition result of the traveling state in the vehicle information exceeds the abnormality determination threshold value), and a third physical quantity related to the operation, calculated using a result of a detection by an external sensor positioned outside the mobile body (see at least paragraph 0082; wherein the failure type determination unit 13 may determine that the external sensor 22 is abnormal when the actual environment detected by the parking lot sensor 4 is different from the external environment recognized by the autonomous driving vehicle 2, based on the recognition result of the external environment of the autonomous driving vehicle 2 included in the vehicle information and the environment around the autonomous driving vehicle 2 recognized from the detection result of the parking lot sensor 4). As per claim 2, Okamura discloses further comprising a server device including the processor and configured to transmit the control instruction to the mobile body from outside of the mobile body (see at least Figure 1; item 1), wherein the abnormality process includes at least one of: a process of determining that there is an abnormality with at least one of the server device, a surrounding environment of the mobile body that performs the operation, the mobile body as the target, and the external sensor (see at least paragraph 0080; wherein the failure type determination unit 13 may determine that there is an abnormality in the internal sensor 23 when a predetermined time elapses in a state in which each parameter (vehicle speed, accelerations, yaw rate, and the like) of the recognition result of the traveling state in the vehicle information exceeds the abnormality determination threshold value); a process of indicating occurrence of the abnormality; a process of transmitting the control instruction of braking the mobile body as the target from the server device to the mobile body as the target; a process of stopping the server device; and a process of stopping the external sensor. As per claim 3, Okamura discloses wherein the processor is configured to execute, as the abnormality process, a process of determining that there is an abnormality with at least one of the server device, the surrounding environment, and the mobile body as the target, in a case where a first difference is more than a first criterion value determined in advance, the first difference being a difference between the first physical quantity and the second physical quantity compared with each other for the mobile body as the target (see at least paragraph 0080; wherein the failure type determination unit 13 may determine the presence or absence and type of a failure caused by the vehicle from vehicle information other than the failure information. The failure type determination unit 13 may determine that there is an abnormality in the internal sensor 23 when a predetermined time elapses in a state in which each parameter (vehicle speed, accelerations, yaw rate, and the like) of the recognition result of the traveling state in the vehicle information exceeds the abnormality determination threshold value). As per claim 4, Okamura discloses wherein the processor is configured to determine that there is an abnormality with at least one of the surrounding environment and the mobile body as the target in a case where a first condition determined in advance related to normality of the server device is met and the first difference is more than the first criterion value (see at least paragraph 0080; wherein the failure type determination unit 13 may determine the presence or absence and type of a failure caused by the vehicle from vehicle information other than the failure information. The failure type determination unit 13 may determine that there is an abnormality in the internal sensor 23 when a predetermined time elapses in a state in which each parameter (vehicle speed, accelerations, yaw rate, and the like) of the recognition result of the traveling state in the vehicle information exceeds the abnormality determination threshold value). As per claim 5, Okamura discloses wherein the first condition includes a condition that in a predetermined period a first number of times, when the first difference for a plurality of mobile bodies that are different from the mobile body as the target is more than the first criterion value, is equal to or less than a predetermined number of times (see at least paragraphs 0080-0083; wherein the failure type determination unit 13 may determine the presence or absence and type of a failure caused by the vehicle from vehicle information other than the failure information. The failure type determination unit 13 may determine that there is an abnormality in the internal sensor 23 when a predetermined time elapses in a state in which each parameter (vehicle speed, accelerations, yaw rate, and the like) of the recognition result of the traveling state in the vehicle information exceeds the abnormality determination threshold value). As per claim 6, Okamura discloses wherein the first condition includes a condition that a first operation determined in advance, which excludes the server device from targets for an abnormality determination, is executed on a reception unit configured to receive an operation from a user (see at least paragraphs 0059-0060; wherein the user frontend 3 has a function of issuing an entry request and an exit request to the parking lot management server 1. By operating the user frontend 3, the user can make an automatic valet parking entry and exit request. For example, after the user stops and gets off the autonomous driving vehicle 2 in the drop-off space 62 of the drop-off area 52 of the parking lot 50, the user operates the user frontend 3 to complete the entrance request, thereby giving the parking lot management server 1 the authority to instruct the autonomous driving vehicle 2. The user makes the autonomous driving vehicle 2 parked in the parking space 61 travel to the pick-up space 63 of the pick-up area 53 via the parking lot management server 1 by issuing an exit request. The autonomous driving vehicle 2 waits for the user in the pick-up space 63. For example, when the autonomous driving vehicle 2 arrives at the pick-up space 63 and stops, the parking lot management server 1 terminates the authority to instruct the autonomous driving vehicle 2. The instruction authority may be terminated when the user issues an instruction to open or start the autonomous driving vehicle 2. Autonomous driving vehicle 2 may terminate the instruction authority. It is to be noted that the operation of the autonomous driving vehicle 2 in response to the entrance request and the exit request is not limited to the above-described mode. The same applies to the parking lot management server 1). As per claim 7, Okamura discloses wherein the processor is configured to determine that there is an abnormality with at least one of the server device and the mobile body as the target in a case where a second condition determined in advance related to normality of the surrounding environment is met and the first difference is more than the first criterion value, and the second condition includes: a condition that a second operation determined in advance, which excludes the surrounding environment from targets for an abnormality determination, is executed on a reception unit configured to receive an operation from a user, and a condition that the processor made determination that there is no abnormality with the surrounding environment by using a sensor that detects the surrounding environment (see at least paragraphs 0107-0108; wherein as shown in FIG. 7A, the autonomous driving ECU 20 of the autonomous driving vehicle 2 determines whether or not a vehicle-induced failure has occurred in the autonomous driving vehicle 2. Whether or not a vehicle-induced failure has occurred is determined, for example, on the basis of the diagnosis result of the diagnosis function in each device of the autonomous driving vehicle 2. If the autonomous driving ECU 20 determines that a vehicle-induced failure has occurred (YES in S10), the autonomous driving ECU 20 proceeds to S12. If the autonomous driving ECU 20 does not determine that a vehicle-induced failure has occurred (NO in S10), the process ends. Thereafter, the autonomous driving ECU 20 repeats the process of S10 again after a certain period of time. In S12, the autonomous driving ECU 20 transmits the vehicle information including the failure information to the parking lot management server 1 by the vehicular information providing unit 34. After that, the autonomous driving ECU 20 ends the current process and repeats the process from S10 again after a certain period of time). As per claim 8, Okamura discloses wherein the processor is configured to determine that there is an abnormality with at least one of the server device and the surrounding environment in a case where a third condition determined in advance related to normality of the mobile body as the target is met and the first difference is more than the first criterion value, and the third condition includes a condition that a third operation determined in advance, which excludes the mobile body as the target from targets for an abnormality determination, is executed on a reception unit configured to receive an operation from a user (see at least paragraph 0080; wherein the failure type determination unit 13 may determine that there is an abnormality in the internal sensor 23 when a predetermined time elapses in a state in which each parameter (vehicle speed, accelerations, yaw rate, and the like) of the recognition result of the traveling state in the vehicle information exceeds the abnormality determination threshold value). As per claim 9, Okamura discloses wherein the processor is configured to execute, as the abnormality process, a process of determining that there is an abnormality with at least one of the internal sensor mounted on the mobile body as the target and the external sensor in a case where a second difference is more than a second criterion value determined in advance, the second difference being a difference between the second physical quantity and the third physical quantity compared with each other (see at least paragraph 0080; wherein the failure type determination unit 13 may determine that there is an abnormality in the internal sensor 23 when a predetermined time elapses in a state in which each parameter (vehicle speed, accelerations, yaw rate, and the like) of the recognition result of the traveling state in the vehicle information exceeds the abnormality determination threshold value). As per claim 10, Okamura discloses wherein the processor is configured to determine that there is an abnormality with the external sensor in a case where a fourth condition determined in advance related to normality of the internal sensor mounted on the mobile body as the target is met and the second difference is more than the second criterion value, and the fourth condition includes a condition that a fourth operation determined in advance, which excludes the internal sensor from targets for an abnormality determination, is executed on a reception unit configured to receive an operation from a user (see at least paragraph 0077; wherein the plurality of failure type candidates include at least one of an abnormality in the autonomous driving ECU 20, an abnormality in the external sensor 22, an abnormality in the internal sensor 23, an abnormality in the actuator 24, and an abnormality in the power supply. The actuator abnormality includes at least one of a brake actuator abnormality, an engine actuator abnormality, and a steering actuator abnormality. The actuator malfunction may include a parking brake control actuator malfunction or a shift control actuator malfunction). As per claim 11, Okamura discloses wherein the processor determines that there is an abnormality with the internal sensor in a case where a fifth condition determined in advance related to normality of the external sensor is met and the second difference is more than the second criterion value, and the fifth condition includes a condition that a fifth determined in advance, which excludes the external sensor from targets for an abnormality determination, is executed on a reception unit configured to receive an operation from a user (see at least paragraph 0077; wherein the plurality of failure type candidates include at least one of an abnormality in the autonomous driving ECU 20, an abnormality in the external sensor 22, an abnormality in the internal sensor 23, an abnormality in the actuator 24, and an abnormality in the power supply. The actuator abnormality includes at least one of a brake actuator abnormality, an engine actuator abnormality, and a steering actuator abnormality. The actuator malfunction may include a parking brake control actuator malfunction or a shift control actuator malfunction). As per claim 12, Okamura discloses wherein the processor is configured to execute, as the abnormality process, a process of determining that there is an abnormality with at least one of the server device, the surrounding environment, the mobile body as the target, and the external sensor in a case where a third difference is more than a third criterion value determined in advance, the third difference being a difference between the first physical quantity and the third physical quantity compared with each other (see at least paragraph 0077; wherein the plurality of failure type candidates include at least one of an abnormality in the autonomous driving ECU 20, an abnormality in the external sensor 22, an abnormality in the internal sensor 23, an abnormality in the actuator 24, and an abnormality in the power supply. The actuator abnormality includes at least one of a brake actuator abnormality, an engine actuator abnormality, and a steering actuator abnormality. The actuator malfunction may include a parking brake control actuator malfunction or a shift control actuator malfunction). As per claim 13, Okamura discloses wherein the processor is configured to determine that there is an abnormality with at least one of the surrounding environment, the external sensor, and the mobile body as the target in a case where a first condition determined in advance related to normality of the server device is met and the third difference is more than the third criterion value, and the first condition includes a condition that a first operation determined in advance, which excludes the server device from targets for an abnormality determination, is executed on a reception unit configured to receive an operation from a user (see at least paragraph 0077; wherein the plurality of failure type candidates include at least one of an abnormality in the autonomous driving ECU 20, an abnormality in the external sensor 22, an abnormality in the internal sensor 23, an abnormality in the actuator 24, and an abnormality in the power supply. The actuator abnormality includes at least one of a brake actuator abnormality, an engine actuator abnormality, and a steering actuator abnormality. The actuator malfunction may include a parking brake control actuator malfunction or a shift control actuator malfunction). As per claim 14, Okamura discloses wherein the processor is configured to determine that there is an abnormality with at least one of the server device, the mobile body as the target, and the external sensor in a case where a second condition determined in advance related to normality of the surrounding environment is met and the third difference is more than the third criterion value, and the second condition includes: a condition that a second operation determined in advance, which excludes the surrounding environment from targets for an abnormality determination, is executed on a reception unit configured to receive an operation from a user, and a condition that the processor made determination that there is no abnormality with the surrounding environment by using a sensor that detects the surrounding environment (see at least paragraph 0077; wherein the plurality of failure type candidates include at least one of an abnormality in the autonomous driving ECU 20, an abnormality in the external sensor 22, an abnormality in the internal sensor 23, an abnormality in the actuator 24, and an abnormality in the power supply. The actuator abnormality includes at least one of a brake actuator abnormality, an engine actuator abnormality, and a steering actuator abnormality. The actuator malfunction may include a parking brake control actuator malfunction or a shift control actuator malfunction). As per claim 15, Okamura discloses wherein the processor is configured to determine that there is an abnormality with at least one of the server device, the surrounding environment, and the external sensor in a case where a third condition determined in advance related to normality of the mobile body as the target is met and the third difference is more than the third criterion value, and the third condition includes a condition that a third operation determined in advance, which excludes the mobile body as the target from targets for an abnormality determination, is executed on a reception unit configured to receive an operation from a user (see at least paragraph 0077; wherein the plurality of failure type candidates include at least one of an abnormality in the autonomous driving ECU 20, an abnormality in the external sensor 22, an abnormality in the internal sensor 23, an abnormality in the actuator 24, and an abnormality in the power supply. The actuator abnormality includes at least one of a brake actuator abnormality, an engine actuator abnormality, and a steering actuator abnormality. The actuator malfunction may include a parking brake control actuator malfunction or a shift control actuator malfunction). As per claim 16, Okamura discloses wherein the processor is configured to determine that there is an abnormality with at least one of the server device, the surrounding environment, and the mobile body as the target in a case where a fifth condition determined in advance related to normality of the external sensor is met and the third difference is more than the third criterion value, and the fifth condition includes a condition that a fifth operation determined in advance, which excludes the external sensor from targets for an abnormality determination, is executed on a reception unit configured to receive an operation from a user (see at least paragraph 0077; wherein the plurality of failure type candidates include at least one of an abnormality in the autonomous driving ECU 20, an abnormality in the external sensor 22, an abnormality in the internal sensor 23, an abnormality in the actuator 24, and an abnormality in the power supply. The actuator abnormality includes at least one of a brake actuator abnormality, an engine actuator abnormality, and a steering actuator abnormality. The actuator malfunction may include a parking brake control actuator malfunction or a shift control actuator malfunction). As per claim 18, Okamura discloses wherein the external sensor is an unattended operation sensor that is used to move the mobile body through the unattended operation (see at least paragraph 0037; wherein the external sensor 22 may also include a sonar sensor that detects sounds outside the autonomous driving vehicle 2). As per claim 19, Okamura discloses a server device of remotely or autonomously inspecting a mobile body that is movable through unattended operation, the server device comprising: a processor (see at least Figure 1; item 15), wherein the processor is configured to: generate a control instruction that causes the mobile body to operate, and transmit the control instruction to the mobile body from outside of the mobile body (see at least paragraph 0099; wherein the vehicle instruction unit 15 gives various instructions to the autonomous driving vehicle 2 that performs automatic valet parking. When the autonomous driving vehicle 2 starts the automatic valet parking, the vehicle instruction unit 15 instructs the target route to reach the target parking space of the autonomous driving vehicle 2); and execute an abnormality process determined in advance in a case where a difference obtained by comparing at least two of physical quantities for the mobile body as a target is more than a criterion value determined in advance, the physical quantities including (see at least paragraph 0080; wherein the failure type determination unit 13 may determine that there is an abnormality in the internal sensor 23 when a predetermined time elapses in a state in which each parameter (vehicle speed, accelerations, yaw rate, and the like) of the recognition result of the traveling state in the vehicle information exceeds the abnormality determination threshold value) a first physical quantity related to operation of the mobile body achieved according to the control instruction, the first physical quantity being calculated using the control instruction (see at least paragraph 0081; wherein the failure type determination unit 13 may determine the presence or absence and the failure type caused by the vehicle based on the vehicle information and the detection result of the parking lot sensor 4. When the difference between the position information of the autonomous driving vehicles 2 included in the vehicle information and the position of the autonomous driving vehicles 2 recognized from the detection result of the parking lot sensor 4 (for example, the captured image of the monitoring camera) is equal to or greater than the error threshold value, the failure type determination unit 13 may determine that an abnormality in position recognition has occurred in the autonomous driving vehicles 2 as a vehicle-induced failure), a second physical quantity related to the operation, calculated using a result of a detection by an internal sensor mounted on the mobile body to detect a state of the mobile body (see at least paragraph 0080; wherein the failure type determination unit 13 may determine that there is an abnormality in the internal sensor 23 when a predetermined time elapses in a state in which each parameter (vehicle speed, accelerations, yaw rate, and the like) of the recognition result of the traveling state in the vehicle information exceeds the abnormality determination threshold value), and a third physical quantity related to the operation, calculated using a result of a detection by an external sensor positioned outside the mobile body (see at least paragraph 0082; wherein the failure type determination unit 13 may determine that the external sensor 22 is abnormal when the actual environment detected by the parking lot sensor 4 is different from the external environment recognized by the autonomous driving vehicle 2, based on the recognition result of the external environment of the autonomous driving vehicle 2 included in the vehicle information and the environment around the autonomous driving vehicle 2 recognized from the detection result of the parking lot sensor 4). As per claim 20, Okamura discloses an inspection method of remotely or autonomously inspecting a mobile body that is movable through unattended operation, the inspection method comprising: generating and outputting a control instruction that causes the mobile body as a target to operate (see at least paragraph 0099; wherein the vehicle instruction unit 15 gives various instructions to the autonomous driving vehicle 2 that performs automatic valet parking. When the autonomous driving vehicle 2 starts the automatic valet parking, the vehicle instruction unit 15 instructs the target route to reach the target parking space of the autonomous driving vehicle 2); and executing an abnormality process determined in advance in a case where a difference obtained by comparing at least two of physical quantities for the mobile body as the target is more than a criterion value determined in advance, the physical quantities including (see at least paragraph 0080; wherein the failure type determination unit 13 may determine that there is an abnormality in the internal sensor 23 when a predetermined time elapses in a state in which each parameter (vehicle speed, accelerations, yaw rate, and the like) of the recognition result of the traveling state in the vehicle information exceeds the abnormality determination threshold value) a first physical quantity related to operation of the mobile body executed according to the control instruction, the first physical quantity being calculated using the control instruction (see at least paragraph 0081; wherein the failure type determination unit 13 may determine the presence or absence and the failure type caused by the vehicle based on the vehicle information and the detection result of the parking lot sensor 4. When the difference between the position information of the autonomous driving vehicles 2 included in the vehicle information and the position of the autonomous driving vehicles 2 recognized from the detection result of the parking lot sensor 4 (for example, the captured image of the monitoring camera) is equal to or greater than the error threshold value, the failure type determination unit 13 may determine that an abnormality in position recognition has occurred in the autonomous driving vehicles 2 as a vehicle-induced failure), a second physical quantity related to the operation, calculated using a result of a detection by an internal sensor mounted on the mobile body to detect a state of the mobile body from inside of the mobile body (see at least paragraph 0080; wherein the failure type determination unit 13 may determine that there is an abnormality in the internal sensor 23 when a predetermined time elapses in a state in which each parameter (vehicle speed, accelerations, yaw rate, and the like) of the recognition result of the traveling state in the vehicle information exceeds the abnormality determination threshold value), and a third physical quantity related to the operation, calculated using a result of a detection by an external sensor positioned outside the mobile body (see at least paragraph 0082; wherein the failure type determination unit 13 may determine that the external sensor 22 is abnormal when the actual environment detected by the parking lot sensor 4 is different from the external environment recognized by the autonomous driving vehicle 2, based on the recognition result of the external environment of the autonomous driving vehicle 2 included in the vehicle information and the environment around the autonomous driving vehicle 2 recognized from the detection result of the parking lot sensor 4).
Allowable Subject Matter
Claim(s) 17 is objected to as being dependent upon a rejected base claim, but would be allowable if rewritten to include all of the limitations of the base claim and any intervening claims. The prior art fails to explicitly teach wherein the processor is configured to: execute, as the abnormality process, a process of determining that there is an abnormality with the mobile body as the target in a case where a first difference is more than a first criterion value determined in advance, a second difference is more than a second criterion value determined in advance, and a third difference is equal to or less than a third criterion value determined in advance, the first difference being a difference between the first physical quantity and the second physical quantity compared with each other, the second difference being a difference between the second physical quantity and the third physical quantity compared with each other, , and the third difference being a difference between the first physical quantity and the third physical quantity compared with each other; execute, as the abnormality process, a process of determining that there is an abnormality with the server device in a case where the first difference is more than the first criterion value, the second difference is equal to or less than the second criterion value, and the third difference is more than the third criterion value; and execute, as the abnormality process, a process of determining that there is an abnormality with the external sensor in a case where the first difference is equal to or less than the first criterion value, the second difference is more than the second criterion value, and the third difference is more than the third criterion value.
Relevant Art
The prior art made of record and not relied upon are considered pertinent to applicant’s disclosure: USPGPub 2024/0323657 – Provide vehicle-to-everything (V2X) and Intelligent Transport System (ITS) communications technologies, and in particular, to misbehavior detection and misbehavior reporting services for Collective Perception Messages (CPMs). The misbehavior detection mechanisms include one or more data consistency checks, including a multi-step systematic data consistency check within individual CPMs, across multiple CPMs from the same transmitter, and across multiple CPMs from different transmitters. Potential misbehaviors are reported to a misbehavior authority in one or more misbehavior reports. USPGPub 2023/0252383 – Provide information technology methods and systems for management of value chain network entities, including supply chain and demand management entities. The present disclosure also relates to the field of enterprise management platforms, more particularly involving an edge-distributed database and query language for storing and retrieving value chain data.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MAHMOUD S ISMAIL whose telephone number is (571)272-1326. The examiner can normally be reached M - F: 8:00AM- 4:00PM.
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/MAHMOUD S ISMAIL/Primary Examiner, Art Unit 3662
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