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 .
DETAILED ACTION
This is in response to applicant’s amendment/response filed on 11/24/2025, which has
been entered and made of record. Claim 1, 8, 14 are amended. Claims 1-20 are pending in the application.
Response to Arguments
Applicant arguments regarding claim rejections under 103 are considered, but are moot in view of new ground of rejections.
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 (i.e., changing from AIA to pre-AIA ) 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) 1-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Minster et al. (US 2017/0267233 A1) in view of Park (US 10847032) and in view of Bostick et al (US 2018/0246509 A1) and further in view of Sisbot (US 2017/0278305 A1).
Regarding claim 1, Minster teaches:
A computer system for using augmented reality (AR) to enhance parking of autonomous vehicles (Abstract: “Systems and methods for autonomous vehicle parking” [0075] for AR teachings. FIG. 5.) comprising:
one or more processing devices; (FIG. 5, the devices in FIG. 5 all have computers. Computers have memories.)
an autonomous vehicles parking manager communicatively and operably coupled to the one or more processing devices; (FIG. 5, 540.)
one or more sensors communicatively and operably coupled to the autonomous vehicles parking manager; ([0016], “Based on the parking space data provided by the facilitator 540 and the plurality of AVs 550, as well as parking space information obtained from the sensors associated with the autonomous vehicle 510”)
a display device communicatively and operably coupled to the autonomous vehicles parking manager; ([0030], “The system 500 may optionally include a user interface 560 (not shown) that enables an autonomous vehicle user (e.g., a passenger, or a ridesharing platform user who may not be a passenger) to interact with and provide information to an autonomous vehicle 510. The user interface 560 is preferably a web interface or a native application interface accessible through a mobile electronic device (e.g., a smartphone, a laptop computer, etc.) but may additionally or alternatively be any interface through which a user may communicate with an autonomous vehicle 510, the parking facilitator 540, or a system that affects control of an autonomous vehicle 510 (e.g., the autonomous vehicle routing coordinator 520). For example, a user interface 560 may be a touchscreen in an autonomous vehicle 510. The user interface 560 is preferably any interface capable of receiving user input as described in the section on the method 100. Additionally or alternatively, the user interface 560 may be any interface capable of influencing autonomous vehicle parking; for instance, the user interface 560 maybe the user interface of a ridesharing platform that affects ridesharing vehicle demand.”) and
one or more augmented reality (AR) devices communicatively and operably coupled to the autonomous vehicles parking manager, ([0076], “S130 functions to provide augmented reality capabilities to a user device (e.g., a mobile computing device or the like) that allows an intended passenger to livestream their environment with a computer-generated overlay that is superimposed or superposed over a display of the livestreamed environment.”) the autonomous vehicles parking manager configured to:
capture, through the one or more sensors, at least a portion of physical characteristics of a parking facility; ([0058], “S130 may additionally include collecting parking space data S131. S131 functions to enable autonomous vehicles to collect data (e.g., image data or other sensor data) that can be processed and/or analyzed to determine parking space characteristics and/or status.” [0052], “S130 includes receiving parking space data. S130 functions to enable the autonomous vehicle to receive data (either from an internal source, such as an autonomous vehicle sensor suite, or from an external source, such as another autonomous vehicle or parking agent) that describes parking spaces, availability of one or more parking spaces, or other information related to a parking environment for an autonomous vehicle. Parking space data preferably can be used to ascertain availability and/or accessibility information of parking spaces and actual (e.g., physical) characteristics of parking spaces and/or the surrounding environment of an autonomous vehicle, as opposed to parking parameters—which preferably described desired or required characteristics for parking spaces.”)
identify, through the one or more sensors, at least a portion of physical characteristics of at least a portion of first vehicles within at least a portion of the parking facility; ([0064], “S132 preferably performs image analysis using model-based feature detection (e.g., comparing image data to examples of features known to correspond to parking space characteristics and/or status), but may additionally or alternatively include performing feature detection in any manner (e.g., via machine learning algorithms). Features detected by S132 that may correspond to parking space characteristics and/or status may include, for example, the presence of a parked vehicle, the type of parked vehicle, the status of a parked vehicle (e.g., whether the hazard lights are on, whether doors/trunk are open), the presence of parking meters, the presence of painted parking space demarcations on the street, the presence of signs (e.g., parking signs), the presence of parking tickets on parked vehicles, and the presence of parking enforcement.” [0061], “S130 may additionally include processing parking space data S132. S132 preferably includes analyzing and/or processing parking space data to produce parking space characteristics (e.g., size, shape, location, cost, times of availability, etc.) and/or status (e.g., whether the space is occupied, current cost to park in the space).”)
generate, subject to the capturing and identifying, an AR representation of the at least a portion of the parking facility, on a real time basis, using a parking facility computing system, (the method here are implemented by the computing system presented on FIG. 5. The process of S130 as shown in FIG. 2 is implemented by computing system in real time, to process livestream information as shown in [0075]-[0076] below. ) and the at least a portion of first vehicles; (FIG. 3, [0075]-[0076], “In a variation of a preferred embodiment, S130 includes receiving parking space data from a passenger and/or another human (e.g., a remote expert). For example, a passenger or remote expert may be asked to select a parking space using an interface on an electronic device (e.g., the passenger's smartphone, a touchscreen inside the vehicle), as shown in FIG. 3. As another example, a passenger may be asked to take a picture (or simply point a camera at) a location they would like to park. In this example, the passenger may do so with an augmented reality (AR) interface that highlights acceptable parking spaces (e.g., parking spaces of a certain size), as shown in FIG. 4. In one example embodiment, S130 functions to provide augmented reality capabilities to a user device (e.g., a mobile computing device or the like) that allows an intended passenger to livestream their environment with a computer-generated overlay that is superimposed or superposed over a display of the livestreamed environment. The overlay, in some embodiments, may provide display and/or provide information from the autonomous vehicle's perspective. That is, the overlay would demonstrate a manner in which the autonomous vehicle would interpret the livestreamed environment surrounding the intended passenger including the identifiable objects and traffic elements (e.g., lanes, traffic lights, curbs, bus lanes) in the environment, the location, and the like. For instance, if in the livestream environment, an available open parking space is a best position for the autonomous vehicle to stop and park temporarily to pick up the intended passenger, the overlay may show this position as green area together with an indication of optimal parking location. Alternatively, any location in the livestream which includes a bus lane, an obstruction (e.g., another vehicle, an object, etc.) that cannot be used to park, the augmented reality overlay would illustrate those positions as red indicating suboptimal or unavailable locations for parking.”)
present, through the display device, the AR representation of the at least a portion of the parking facility and the at least a portion of first vehicles; ([0076] and [0078], “Additionally, or alternatively, the livestream and augmented reality overlay of the intended passenger's mobile computing device may be communicated or shared with the autonomous vehicle.” FIG. 3.)
receive, subject to the presenting, one or more potential parking locations at least partially based on presently vacant parking locations indicated within the AR representation of the at least a portion of the parking facility and the at least a portion of the vehicles; ([0078], “Additionally, or alternatively, the livestream and augmented reality overlay of the intended passenger's mobile computing device may be communicated or shared with the autonomous vehicle. The autonomous vehicle may be able to compare the augmented reality (AR) and livestream mapping of the mobile computing device of the intended passenger to its own mapping (e.g., three-dimensional map) to determine a parking location. Thus, based on finding overlaps between the AR livestream mapping and the mapping and parking space data of the autonomous vehicle, the autonomous vehicle may better localize a suitable and convenient parking location when traveling to satisfy a ride or pickup request.” FIG. 3 and [0075])
recommend, subject to the receiving the one or more potential parking locations, a selection of one or more selected parking locations of the vacant parking locations for one or more autonomous vehicles based on user perferences; ([0074]-[0075], “S130 may additionally or alternatively include generating predicted parking space availability (or cost, or any other parking space status) based on historical data captured by autonomous vehicles and/or other sources, or any other suitable data. For example, S130 may include generating a parking space heatmap that could be used (e.g., in absence of more accurate data) to aid an autonomous vehicle in estimating a good location to park. Predicted parking space status may be generated based on any suitable criteria (e.g., historical space availability, traffic, time of day, etc.). As another example, predicted parking space availability maybe determined by using sensor data to determine that a vehicle is leaving a parking spot, or that a number of vehicles are leaving a parking lot or garage. As a third example, predicted parking space availability may be provided by another party, such as a parking garage that tracks its usage. In a variation of a preferred embodiment, S130 includes receiving parking space data from a passenger and/or another human (e.g., a remote expert). For example, a passenger or remote expert may be asked to select a parking space using an interface on an electronic device (e.g., the passenger's smartphone, a touchscreen inside the vehicle), as shown in FIG. 3. As another example, a passenger may be asked to take a picture (or simply point a camera at) a location they would like to park. In this example, the passenger may do so with an augmented reality (AR) interface that highlights acceptable parking spaces (e.g., parking spaces of a certain size), as shown in FIG. 4.”) and
park, subject to the receiving, one or more autonomous vehicles within one or more selected parking locations of the one or more potential parking locations. ([0081]-[0082], “After selecting a parking space, S140 may include generating autonomous vehicle controls or control parameters based on the selected parking space and the parking space data associated with the selected parking space. For instance, whether the parking space involves or does not involve a curb may influence the controls relating to the angles at which the autonomous vehicle may turn to achieve a successful parking maneuver within the selected parking space. Other factors, such as the size and shape of the parking space, as well as whether there are other vehicles next or near the parking space may also influence the controls generation process. This additional information, of course, may be obtained from the sensors available to the autonomous vehicle. Once the autonomous vehicle controls for parking the autonomous vehicle are generated, S140 may include executing the controls and performing any action necessary (or desired) to enable the autonomous vehicle to park legally within the selected parking space.”)
receive one or more pick up locations for the one or more autonomous vehicles based on the user preferences; ([0034], “In the instance that the vehicle coordinator receives a pickup or ride request, the pickup or ride request may include pickup related data including rider preferences, pickup location, vehicle type requested, date and time of the requested pickup, and the like.”) and
However, Minster does not explicitly teach, but Park teaches:
one or more memory devices communicatively and operably coupled to the one or more processing devices;(para 108: “Further, the vehicle storage unit 1900 can be electrically connected to the vehicle control unit 1200 and store basic data for each part of the parking position notification apparatus, control data for controlling operations of each part of the parking position notification apparatus, and input and output data.” Para 118: “In addition, the terminal storage unit 2400 can be electrically connected to the terminal control unit 2200 and store basic data for each part of the parking position notification apparatus, control data for controlling the operation of each part of the parking position notification apparatus, and input and output data.”)
Minster teaches an autonomous vehicles parking system, which have one or more processing devices that communicate with each other to perform the intended functions. However, Minster does not explicitly teach one or more memory devices communicate and operably coupled to the one or more processing devices. On the other hand, Park teaches this feature that uses storage unit to store some basic data related to parking.
It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to have combined the teachings of Minster with the specific teachings of Park to use storage unit to save some basic data that can be used to in the process of determining autonomous vehicles parking. The benefit would be to improve system efficiency.
However, Minster in view of Park does not, but Bostick teaches:
guide the one or more autonomous vehicles along one or more paths of travel from the one or more selected parking locations to the one or more pick up locations (Abstract: “One or more processor(s) receive an input defining a delineated area of a vehicular area on a display. The delineated area is specific for particular parking spots in a parking lot. Use of the parking lot is restricted to autonomous self-driving vehicles (SDVs). The processor(s) retrieve a calendar entry from an electronic calendar describing a quantity of persons who require SDVs to transport them during a particular time period to a specific destination. The processor(s) determine a quantity of SDVs required to transport the persons. The processor(s) transmit instructions to SDV controllers on-board the SDVs to autonomously drive from the particular parking spots to an intermediate staging area and then to a pick-up location to pick up the persons for delivery to the specific destination during the particular time period.”)
Minster in view of Park teaches parking an autonomous driving car in a parking lot and receiving request to pick up a customer. Bostick teaches once receiving the request to pick up a customer, the autonomous car can be guided to the pickup location to pick up the customer.
It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to have combined the teachings of Minster and Park with the specific teachings of Bostick to provide uses better services.
However, Minster in view of Park and Bostick does not, but Sisbot teaches:
based on rules and regulations of the parking facility;([0153], “The first parking space also includes a first parking sign 405. The visual context application 199 may perform one or more of the following operations: identify the first parking space in an image captured by the exterior camera 104; identify the first parking sign 405 associated with the first parking space in the image captured by the exterior camera 104; determine the rule indicated by the first parking sign 405 based on one or more object priors; determine that it is legal to park in the first parking space based on the present time of day and the rule indicated by the first parking sign; determine that the first parking space is relevant to the driver 125 since it is legal to park there;”)
display the one or more selected parking locations on the one or more AR devices in order for a user to choose one or more of the one or more selected parking locations;([0153], “determine that the first parking space is relevant to the driver 125 since it is legal to park there; select a voice command for engaging an automatic parking system of the vehicle 103 to cause the vehicle 103 to automatically park in the first parking space; select a 3D overlay indicating that the driver 125 may provide a voice command to cause the vehicle 103 to automatically park in the first parking space; paint the fourth 3D overlay 400 on the 3D HUD 231;”)
Minster in view of Park and Bostick teaches an autonomous vehicles navigation system. Sisbot teaches deciding the available parking space based on regulations of the facility.
It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to have combined the teachings of Minster in view of Park and Bostick with the specific teachings of Sisbot to accurately identify parking spaces for vehicle.
Regarding claim 2, Minster in view of Park and Bostick and Sisbot teaches:
The system of claim 1, wherein the autonomous vehicles parking manager is further configured to:
capture of the at least a portion of physical characteristics of the parking facility, (Minster [0058], “S130 may additionally include collecting parking space data S131. S131 functions to enable autonomous vehicles to collect data (e.g., image data or other sensor data) that can be processed and/or analyzed to determine parking space characteristics and/or status.” [0052], “S130 includes receiving parking space data. S130 functions to enable the autonomous vehicle to receive data (either from an internal source, such as an autonomous vehicle sensor suite, or from an external source, such as another autonomous vehicle or parking agent) that describes parking spaces, availability of one or more parking spaces, or other information related to a parking environment for an autonomous vehicle. Parking space data preferably can be used to ascertain availability and/or accessibility information of parking spaces and actual (e.g., physical) characteristics of parking spaces and/or the surrounding environment of an autonomous vehicle, as opposed to parking parameters—which preferably described desired or required characteristics for parking spaces.”)
and identifying the at least a portion of physical characteristics of the at least a portion of first vehicles within the at least a portion of the parking facility, at a first time; (Minster [0064], “S132 preferably performs image analysis using model-based feature detection (e.g., comparing image data to examples of features known to correspond to parking space characteristics and/or status), but may additionally or alternatively include performing feature detection in any manner (e.g., via machine learning algorithms). Features detected by S132 that may correspond to parking space characteristics and/or status may include, for example, the presence of a parked vehicle, the type of parked vehicle, the status of a parked vehicle (e.g., whether the hazard lights are on, whether doors/trunk are open), the presence of parking meters, the presence of painted parking space demarcations on the street, the presence of signs (e.g., parking signs), the presence of parking tickets on parked vehicles, and the presence of parking enforcement.” [0061], “S130 may additionally include processing parking space data S132. S132 preferably includes analyzing and/or processing parking space data to produce parking space characteristics (e.g., size, shape, location, cost, times of availability, etc.) and/or status (e.g., whether the space is occupied, current cost to park in the space).”) and
generate a first AR representation, at the first time, of the at least a portion of the parking facility, on a real time basis, using a parking facility computing system , and the at least a portion of first vehicles; (Minster FIG. 3, [0075]-[0076], “In a variation of a preferred embodiment, S130 includes receiving parking space data from a passenger and/or another human (e.g., a remote expert). For example, a passenger or remote expert may be asked to select a parking space using an interface on an electronic device (e.g., the passenger's smartphone, a touchscreen inside the vehicle), as shown in FIG. 3. As another example, a passenger may be asked to take a picture (or simply point a camera at) a location they would like to park. In this example, the passenger may do so with an augmented reality (AR) interface that highlights acceptable parking spaces (e.g., parking spaces of a certain size), as shown in FIG. 4. In one example embodiment, S130 functions to provide augmented reality capabilities to a user device (e.g., a mobile computing device or the like) that allows an intended passenger to livestream their environment with a computer-generated overlay that is superimposed or superposed over a display of the livestreamed environment. The overlay, in some embodiments, may provide display and/or provide information from the autonomous vehicle's perspective. That is, the overlay would demonstrate a manner in which the autonomous vehicle would interpret the livestreamed environment surrounding the intended passenger including the identifiable objects and traffic elements (e.g., lanes, traffic lights, curbs, bus lanes) in the environment, the location, and the like. For instance, if in the livestream environment, an available open parking space is a best position for the autonomous vehicle to stop and park temporarily to pick up the intended passenger, the overlay may show this position as green area together with an indication of optimal parking location. Alternatively, any location in the livestream which includes a bus lane, an obstruction (e.g., another vehicle, an object, etc.) that cannot be used to park, the augmented reality overlay would illustrate those positions as red indicating suboptimal or unavailable locations for parking.”)
capture, through the one or more sensors, at a second time, the at least a portion of the physical characteristics of the parking facility; (Minster [0058], “S130 may additionally include collecting parking space data S131. S131 functions to enable autonomous vehicles to collect data (e.g., image data or other sensor data) that can be processed and/or analyzed to determine parking space characteristics and/or status.” [0052], “S130 includes receiving parking space data. S130 functions to enable the autonomous vehicle to receive data (either from an internal source, such as an autonomous vehicle sensor suite, or from an external source, such as another autonomous vehicle or parking agent) that describes parking spaces, availability of one or more parking spaces, or other information related to a parking environment for an autonomous vehicle. Parking space data preferably can be used to ascertain availability and/or accessibility information of parking spaces and actual (e.g., physical) characteristics of parking spaces and/or the surrounding environment of an autonomous vehicle, as opposed to parking parameters—which preferably described desired or required characteristics for parking spaces.”)
identify, through the one or more sensors, at the second time, at least a portion of physical characteristics of at least a portion of the first vehicles within the at least a portion of the parking facility; (Minster [0064], “S132 preferably performs image analysis using model-based feature detection (e.g., comparing image data to examples of features known to correspond to parking space characteristics and/or status), but may additionally or alternatively include performing feature detection in any manner (e.g., via machine learning algorithms). Features detected by S132 that may correspond to parking space characteristics and/or status may include, for example, the presence of a parked vehicle, the type of parked vehicle, the status of a parked vehicle (e.g., whether the hazard lights are on, whether doors/trunk are open), the presence of parking meters, the presence of painted parking space demarcations on the street, the presence of signs (e.g., parking signs), the presence of parking tickets on parked vehicles, and the presence of parking enforcement.” [0061], “S130 may additionally include processing parking space data S132. S132 preferably includes analyzing and/or processing parking space data to produce parking space characteristics (e.g., size, shape, location, cost, times of availability, etc.) and/or status (e.g., whether the space is occupied, current cost to park in the space).”) and generate, subject to the capturing and identifying, at the second time, a second augmented reality (AR) representation of the at least a portion of the parking facility, on a real time basis, using a parking facility computing system, and the at least a portion of first vehicles. (Minster FIG. 3, [0075]-[0076], “In a variation of a preferred embodiment, S130 includes receiving parking space data from a passenger and/or another human (e.g., a remote expert). For example, a passenger or remote expert may be asked to select a parking space using an interface on an electronic device (e.g., the passenger's smartphone, a touchscreen inside the vehicle), as shown in FIG. 3. As another example, a passenger may be asked to take a picture (or simply point a camera at) a location they would like to park. In this example, the passenger may do so with an augmented reality (AR) interface that highlights acceptable parking spaces (e.g., parking spaces of a certain size), as shown in FIG. 4. In one example embodiment, S130 functions to provide augmented reality capabilities to a user device (e.g., a mobile computing device or the like) that allows an intended passenger to livestream their environment with a computer-generated overlay that is superimposed or superposed over a display of the livestreamed environment. The overlay, in some embodiments, may provide display and/or provide information from the autonomous vehicle's perspective. That is, the overlay would demonstrate a manner in which the autonomous vehicle would interpret the livestreamed environment surrounding the intended passenger including the identifiable objects and traffic elements (e.g., lanes, traffic lights, curbs, bus lanes) in the environment, the location, and the like. For instance, if in the livestream environment, an available open parking space is a best position for the autonomous vehicle to stop and park temporarily to pick up the intended passenger, the overlay may show this position as green area together with an indication of optimal parking location. Alternatively, any location in the livestream which includes a bus lane, an obstruction (e.g., another vehicle, an object, etc.) that cannot be used to park, the augmented reality overlay would illustrate those positions as red indicating suboptimal or unavailable locations for parking.”)
Minster teaches the processing of parking an autonomous vehicle by performing the capturing, identifying and generating steps listed above. Since most time these steps have to repeat several times in order for the vehicle to find a perfect parking spot. So It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to have repeatedly performed the steps listed above in order to find a proper parking spot for a vehicle.
Regarding claim 3, Minster in view of Park and Bostick and Sisbot teaches:
The system of claim 1, wherein the autonomous vehicles parking manager is further configured to: analyze historical data indicating movement patterns of second vehicles within the parking facility; and present a recommendation whether the one or more autonomous vehicles should be parked in the selected parking location.( Minster [0060], “As previously mentioned, S131 may include collecting data at autonomous vehicles even if those vehicles are not searching for parking; such data may be used to provide parking space information to other vehicles or for the collecting vehicles at a later time (e.g., as historical parking space data). The collection of parking space information by the other autonomous vehicles may be triggered by requests from subject autonomous vehicle requiring a parking space or a ridesharing platform or autonomous vehicle coordinator. Additionally, or alternatively, the other autonomous vehicles may continuously or periodically perform parking spaces searches for the purposes of generating parking space heat maps and for learning parking patterns for one or more geographic areas. For instance, based on the continuous and/or periodic collection of parking space information, a heat map or similar reference data may be generated or determine that illustrates when and where parking spaces are likely to be available or not available in the future.” [0074] “S130 may additionally or alternatively include generating predicted parking space availability (or cost, or any other parking space status) based on historical data captured by autonomous vehicles and/or other sources, or any other suitable data. For example, S130 may include generating a parking space heatmap that could be used (e.g., in absence of more accurate data) to aid an autonomous vehicle in estimating a good location to park. Predicted parking space status may be generated based on any suitable criteria (e.g., historical space availability, traffic, time of day, etc.). As another example, predicted parking space availability maybe determined by using sensor data to determine that a vehicle is leaving a parking spot, or that a number of vehicles are leaving a parking lot or garage.”)
Regarding claim 4, Minster in view of Park and Bostick and Sisbot teaches:
The system of claim 3, wherein the autonomous vehicles collaboration manager is further configured to: capture, through the one or more sensors, real time movement of at least a portion of one or more third vehicles through the parking facility. (Minster [0074], “As another example, predicted parking space availability maybe determined by using sensor data to determine that a vehicle is leaving a parking spot, or that a number of vehicles are leaving a parking lot or garage.”)
Regarding claim 5, Minster in view of Park and Bostick and Sisbot teaches:
The system of claim 1, wherein the autonomous vehicles parking manager is further configured to: capture, through the one or more sensors, a real time approach of the one or more autonomous vehicles toward the parking facility.( Minster [0076], “In one example embodiment, S130 functions to provide augmented reality capabilities to a user device (e.g., a mobile computing device or the like) that allows an intended passenger to livestream their environment with a computer-generated overlay that is superimposed or superposed over a display of the livestreamed environment.”)
Regarding claim 6, Minster in view of Park and Bostick and Sisbot teaches:
The system of claim 1, wherein the autonomous vehicles parking manager is further configured to: navigate, at least partially through the AR representation of the at least a portion of the parking facility and the at least a portion of first vehicles, the one or more autonomous vehicles through the parking facility. (Minster, [0079], “S140 includes parking the autonomous vehicle into a selected parking space. S140 functions to select a parking space for the autonomous vehicle to park in, generate controls for maneuvering the autonomous vehicle into the parking space, and navigate the vehicle into the parking space based on the controls.” FIG. 3)
Regarding claim 7, Minster in view of Park and Bostick and Sisbot teaches:
The system of claim 6, wherein the autonomous vehicles parking manager is further configured to: navigate one of autonomously and semi-autonomously. (Minster, [0079], “S140 includes parking the autonomous vehicle into a selected parking space. S140 functions to select a parking space for the autonomous vehicle to park in, generate controls for maneuvering the autonomous vehicle into the parking space, and navigate the vehicle into the parking space based on the controls.” FIG. 3)
Regarding claim 8, Minster in view of Park and Bostick and Sisbot teaches:
A computer program product to enhance parking of autonomous vehicles comprising: one or more computer readable storage media; and program instructions collectively stored on the one or more computer storage media, (Minster [0084], “The method of the preferred embodiment and variations thereof can be embodied and/or implemented at least in part as a machine configured to receive a computer-readable medium storing computer-readable instructions. The instructions are preferably executed by computer-executable components preferably integrated with an autonomous vehicle platform. The computer-readable medium can be stored on any suitable computer-readable media such as RAMs, ROMs, flash memory, EEPROMs, optical devices (CD or DVD), hard drives, floppy drives, or any suitable device. The computer-executable component is preferably a general or application specific processor, but any suitable dedicated hardware or hardware/firmware combination device can alternatively or additionally execute the instructions.”) the program instructions comprising: the rest of claim 8 recites similar limitations of claim 1, thus are rejected accordingly.
Claims 9-13 recite similar limitations of claim 2-6 respectively, thus are rejected using the same rejection rationale respectively.
Claims 14-20 recite similar limitations of claim 1-7 respectively, thus are rejected using the same rejection rationale respectively.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/YANNA WU/Primary Examiner, Art Unit 2615
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