DETAILED ACTION
Claims 1-16 are considered in this office action. Claims 1-16 are pending examination.
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 .
Drawings
New corrected drawings in compliance with 37 CFR 1.121(d) are required in this application because figures 1-8 are missing details. Applicant is advised to employ the services of a competent patent draftsperson outside the Office, as the U.S. Patent and Trademark Office no longer prepares new drawings. The corrected drawings are required in reply to the Office action to avoid abandonment of the application. The requirement for corrected drawings will not be held in abeyance. The applicant is advised to include the details in the figures 1-8.
Claim Objections
Claim 1 is objected to because of the following informalities: AVP should be spelled out Automated Valet Parking in Line 1. Appropriate correction is required.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claim 14 is rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. The claim(s) does/do not fall within at least one of the four categories of patent eligible subject matter because the claim claims a computer program per se. A computer program, standing alone is intangible and constitutes information content rather than a physical manufacture or machine.
Claim Rejections - 35 USC § 102
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 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 1-2 and 12-16 are rejected under 35 U.S.C. 102(a)(1) based upon a public use or sale or other public availability of the invention Ahn (US11565691) and herein after will be referred as Ahn.
Regarding Claim 1, Ahn teaches a method for identifying an AVP motor vehicle for an AVP process (Col.5 Line 48-50: “FIG. 3 is a conceptual diagram illustrating an automated valet parking system and an automated valet parking method according to embodiments of the present disclosure.”), comprising the steps of:
infrastructure-side reception of driving behavior data which describe a first driving behavior of an AVP motor vehicle that is manually guided within a region of a parking area monitored by an infrastructure environment sensor system (Col.5 Line 52-56: “Referring to FIG. 3, in step (1), a driver drives a vehicle to a drop-off area in a parking lot. In step (2), the driver gets out of the vehicle at the drop-off area and a driving authority to control the vehicle is delegated to the infrastructure.”);
infrastructure-side reception of monitoring data based on the monitoring of the region by the infrastructure environment sensor system; infrastructure-side processing of the monitoring data in order to detect on the infrastructure side, based on the monitoring data, a motor vehicle located within the region monitored by the infrastructure environment sensor system; in the case of infrastructure-side detection of a motor vehicle located within the region based on the monitoring data, infrastructure-side determination, based on the monitoring data, of a second driving behavior of the motor vehicle detected on the infrastructure side; infrastructure-side comparison of the first driving behavior with the second driving behavior(Col.9 Line 60-Col.10 Line 7: “In step (3), vehicle information is transmitted from the vehicle to the infrastructure. The vehicle information includes state information and position information of the vehicle. The state information includes whether the vehicle is in a driving state, a parking stop state, or an emergency stop state. The vehicle information is transmitted periodically at a specific frequency (for example, 1 Hz which means once per second). The vehicle information is used as a parameter to determine whether a communication error has occurred between the vehicle and the infrastructure. For example, when the vehicle information does not reach the infrastructure at a specific time that is estimated on the basis of the communication frequency, the infrastructure determines that an error has occurred in communication between the vehicle and the infrastructure.”);
and infrastructure-side identification, based on the comparison, of the AVP motor vehicle as the motor vehicle detected on the infrastructure side (Col.11 Line 50-58: “In step (9), the infrastructure 100 transmits parking lot map information to the vehicle 200. The parking lot map information includes marking information. In step (10), the vehicle 200 estimates or calculates the position of the vehicle 200 on the basis of the transmitted marking information, and the vehicle 200 transmits the estimated position of the vehicle 200 to the infrastructure 100. In step (11), the infrastructure 100 determines a target position (for example, a parking spot).”).
Similarly Claims 11-16 are rejected on similar rational.
Regarding Claim 2, Ahn teaches the method of claim 1, wherein, in the case of infrastructure-side detection of a plurality of motor vehicles located within the region based on the monitoring data, a respective driving behavior of the plurality of motor vehicles detected on the infrastructure side is determined on the infrastructure side based on the monitoring data, wherein the respective driving behaviors are in each case compared on the infrastructure side with the first driving behavior, wherein, based on the respective comparisons, the AVP motor vehicle is identified on the infrastructure side as one of the plurality of motor vehicles detected on the infrastructure side (Col.11 Line50-60: “In step (9), the infrastructure 100 transmits parking lot map information to the vehicle 200. The parking lot map information includes marking information. In step (10), the vehicle 200 estimates or calculates the position of the vehicle 200 on the basis of the transmitted marking information, and the vehicle 200 transmits the estimated position of the vehicle 200 to the infrastructure 100. In step (11), the infrastructure 100 determines a target position (for example, a parking spot). In step (12), the infrastructure 100 transmits information on a permitted driving area to the vehicle 200. For example, the infrastructure 100 transmits boundary information of the permitted driving area to the vehicle 200.”).
Regarding Claim 12, Ahn teaches a device which performs the method of claim 1 (Figure 1).
Regarding Claim 13, Ahn teaches motor vehicle comprising the device of claim 12(Col.3 Line 15-16).
Regarding Claim 15, Ahn teaches non-transitory machine-readable storage medium on which the computer program claimed in claim 14 is stored (Col.15 Line 47-Col.16 Line 12).
Similarly Claim 14 is also rejected.
Regarding Claim 16, Ahn teaches a system for identifying an AVP motor vehicle for an AVP process, said system comprising a device as claimed in claim 12, which is configured to carry out all steps of the method as claimed in claim 1, and an infrastructure environment sensor system which is configured to monitor a region of a parking area and to output monitoring data based on the monitoring to the device (Fig.1).
Claims 11 is rejected under 35 U.S.C. 102(a)(1) based upon a public use or sale or other public availability of the invention Yoon et al. (US2021/0197802) and herein after will be referred as Yoon.
Regarding Claim 11, Yoon teaches a method for identifying an AVP motor vehicle for an AVP process (Para [0013]: “FIG. 3 is a conceptual diagram for explaining an automated valet parking system and method according to an exemplary embodiment of the present disclosure.”), comprising the steps of:
motor-vehicle-side determination of driving behavior data which describe a first driving behavior of the AVP motor vehicle that is manually guided within a region of a parking area monitored by an infrastructure environment sensor system (Para [0044]: “FIG. 3 is a conceptual diagram for explaining an automated valet parking system and method according to an exemplary embodiment of the present disclosure. Referring to FIG. 3, in (1), a driver drives a vehicle (e.g., the automated valet parking apparatus 200 illustrated in FIG. 1) to enter a parking lot and moves the vehicle to a drop-off area. In (2), the driver who has reached the drop-off area exits the vehicle and the driving authority is transferred from the driver to the infrastructure (e.g., the infrastructure 100 illustrated in FIG. 1).”);
motor-vehicle-side reception of monitoring data based on the monitoring of the region by the infrastructure environment sensor system (Para [0083]: “FIG. 8 is a flowchart illustrating a position measurement operation of the vehicle which supports the automated valet parking according to the present disclosure. Further, FIGS. 9 to 13 are diagrams for explaining an operation of measuring the position of the vehicle based on an environmental sensor according to the present disclosure. The operations described below may indicate various exemplary embodiments of (4) of FIG. 4A. Referring to FIG. 8, in operation S810, the vehicle (e.g., the automated valet parking apparatus 100 illustrated in FIG. 1) may predict the position of the vehicle based on a particle filter. The prediction based on the particle filter may include an operation of setting an initial position and an operation of predicting a position of the vehicle.”);
motor-vehicle-side processing of the monitoring data in order to detect on the motor vehicle side, based on the monitoring data, a motor vehicle located within the region monitored by the infrastructure environment sensor system (Para [0062]: “In (4), a position may be measured. The target of the position measurement may be a vehicle which performs parking, an obstacle which exists within the parking lot, or a vehicle which has already been parked. The infrastructure may measure the position of the vehicle or the obstacle and store the position of the vehicle in a database. The infrastructure may identify and detect vehicles or obstacles and monitor the safety of each of a plurality of vehicles which perform parking. Further, the infrastructure may monitor the operation of the vehicle which reaches the target position to perform parking, and transfer a command. The vehicle may measure its own position.”);
in the case of motor-vehicle-side detection of a motor vehicle located within the region based on the monitoring data, motor-vehicle-side determination, based on the monitoring data, of a second driving behavior of the motor vehicle detected on the motor vehicle side (Para [0085]: “Additionally, to perform an operation of predicting a position of the vehicle, the vehicle may predict the position and direction of the particle based on the movement of the vehicle. For example, the movement of the vehicle may be determined based on a behavior sensor (e.g., an acceleration sensor, a wheel speed sensor, a yaw rate sensor, or the like), and predict the position of the particle which is moved by the moving amount based on the moving amount of the vehicle. Further, the vehicle may predict the direction of the particle by applying a rotational value, which is proportional to the amount of rotation of the vehicle, to the particle. Additionally, the vehicle may predict the direction of the vehicle based on a shift state of the vehicle (e.g., forward shift or reverse shift), and may also predict the direction of the particle based on the shift state of the vehicle.”);
motor-vehicle-side comparison of the first driving behavior with the second driving behavior; and motor-vehicle-side identification, based on the comparison, of the AVP motor vehicle as the motor vehicle detected on the motor vehicle side (Para [0093]: “In operation S840, the vehicle may correct the position of the vehicle based on the matching. According to an exemplary embodiment, the vehicle may correct the position of the vehicle, predicted based on the particle filter, based on the matching. The vehicle may improve the position measurement performance of the vehicle by fusing the environmental information collected through the first environmental sensor and the environmental information collected using the second environmental sensor. For example, in the case of measuring a position using only the first environmental sensor, a positioning error may be generated in a section without a parking slot, and in the case of measuring a position using only the second environmental sensor, a positioning error may be generated in a section without a fixed obstacle, but the vehicle according to the present disclosure may reduce the positioning error by fusing the first environmental sensor and the second environmental sensor, thereby more accurately measuring the position of the vehicle even in an indoor parking lot where GLANS-based positioning is not possible.”).
Allowable Subject Matter
Claim 3-10 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Nicodemus et al. (US2018/0072345A1) discloses a method for controlling an automated parking operation in which a motor vehicle is controlled autonomously on a route between a drop zone and a parking space includes steps of detecting that a person is on board the motor vehicle during an autonomous driving process, determining that permission does not exist for transporting the person on the trip, and carrying out one or more actions.
Nerayoff et al. (US20140036077A1) teaches a method of tracking the use of at least one destination location, the method including identifying a vehicle by use of identification images captured by an identification camera, such as by processing of images of license plates, determining characteristics of the vehicle visible in the identification images, and determining usage of a destination location, such as a parking spot, based on a camera monitoring the destination location capturing images of the vehicle having characteristics corresponding to those determined for the identification images.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ABDHESH K JHA whose telephone number is (571)272-6218. The examiner can normally be reached M-F:0800-1700.
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/ABDHESH K JHA/Primary Examiner, Art Unit 3668