DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Status of Claims
This Office Action is in response to the application filed on 07 October 2025. Claims 1-20 are presently pending and are presented for examination.
Response to Amendments
In response to Applicant’s amendments dated 07 October 2025, Examiner withdraws the previous 35 U.S.C. 112(a) rejections; and maintains the previous prior art rejections.
Response to Arguments
Applicant's arguments, see Remarks, filed 07 October 2025, have been fully considered but they are not persuasive.
In response to applicant's argument, see Remarks, pg. 9, that the references fail to show certain features of the invention, it is noted that the features upon which applicant relies (i.e., “Yang’s system is focused on…and not updating sensor accuracy during charging while in motion”) are not recited in the rejected claim(s). Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir. 1993). For these reasons, examiner is unpersuaded and maintains the corresponding rejections.
In response to applicant's argument, see Remarks, pg. 10, that the references fail to show certain features of the invention, it is noted that the features upon which applicant relies (i.e., “…Steele’s disclosure focuses on…not on using the charging process to identify and update sensor localization accuracy.”) are not recited in the rejected claim(s). Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir. 1993). For these reasons, examiner is unpersuaded and maintains the corresponding rejections.
Applicant argues, see Remarks, pg. 11, that “Yang and Steele also fail to teach or suggest this claim element since Yang’s disclosure is limited to determining whether a vehicle is stopped in a predetermined region based on power transmission rates, but does not teach or suggest using charging rate information to compare with stored transmitter coil location data for localization purposes.” However, US-20220281343-A1 (“Yang”) does disclose using charging rate information and stored transmitter coil location data for localization purposes (see Yang, para. 0082). For these reasons, examiner is unpersuaded and maintains the corresponding rejections. For a more detailed discussion of how Yang teaches the amended limitations to the independent claims, see the Claim Rejections - 35 USC § 103 section, below.
The remaining arguments are essentially the same as those addressed above and/or below and are persuasive for at least the same reasons. Therefore, examiner is persuaded and withdraws the corresponding 35 U.S.C. 102 rejections of the relevant claims.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim(s) 1, 3, 5, 8, 10, 12, 15, 17, and 19 is/are rejected under 35 U.S.C. 103 as being unpatentable over US-20220281343-A1, hereinafter “Yang”, in view of US-20130154553-A1, hereinafter “Steele”.
Regarding claim 15 and analogous claims 1 and 8, Yang discloses a system (Yang, Fig. 2; para. 0057: “A system according to embodiments of the present disclosure may include the vehicle 100, a server 200, and a wireless charging system 300.”), comprising:
a connected automated electric vehicle (CAEV) (Yang, Fig. 2: vehicle 100; para. 0050: ”The vehicle 100 may be an electric vehicle.”; para. 0053: “…the condition that the vehicle 100 should be stopped at a location of the chargeable region having a wireless charging efficiency equal to or greater than the reference value is satisfied, charging may be automatically performed [i.e., automated].” (Note: One of ordinary skill in the art, at the time of the application, would find it obvious to apply the disclosed invention to a semi-autonomous or autonomous vehicle.); para. 0060: “The vehicle 100 may communicate with the server 200 and the wireless charging system 300 through a network 500 [i.e., connected]”); and
Regarding analogous claims 1 and 8: Yang also discloses a method (Yang, para. 0024: “According to another aspect of embodiments of the present disclosure, there is provided a method for providing wireless charging services for wirelessly charging a vehicle”) and a non-transitory computer readable medium [non-transitory CRM], storing instructions for execution by one or more hardware processors (Yang, para. 0007: “According to an aspect of embodiments of the present disclosure, there is provided a charging management device managing charging of a vehicle battery, including at least one processor, at least one memory that stores computer program instructions that, when executed, cause the at least one processor to perform operations…”)
a processor (Yang, para. 0020: “According to another aspect of embodiments of the present disclosure, there is provided a server for managing wireless charging of a vehicle on a road, including at least one processor, at least one memory that stores computer program instructions that, when executed, cause the at least one processor to perform operations…”), configured to:
receive, from a connected automated electric vehicle (CAEV), vehicle information related to operation of the CAEV (Yang, para. 64: “The server 200 may receive various information and signals from the vehicle 100 [i.e., the CAEV]. The server 200 may receive information on the traveling route or information on the current location and destination from the vehicle 100 [i.e., vehicle information related to operation of the CAEV].”);
determine one or more candidate routes to a destination of the CAEV based at least on the vehicle information (Yang, para. 0129: “In addition, the charging management device 101 may directly search for the traveling route, but may also search for the traveling route in the navigation application of the user terminal or the server 200.”; para. 0130: “The traveling route determined based on the plurality of traveling routes searched is transmitted to the server 200 (S104) [i.e., determine one or more candidate routes to a destination of the CAEV]. Of course, as described above, if the server 200 searches for the traveling route, the charging management device 101 may transmit, to the server 200, information on the current location and destination of the vehicle 100 [i.e., based at least on the vehicle information].”);
determine whether the CAEV is on a road segment of the one or more candidate routes to the destination having a dynamic charging system (Yang, Fig. 1; para. 0070: “The wireless charging station 320 is a device installed under the ground of a road and configured to wirelessly transmit power within a predetermined region [i.e., road segment]. The wireless charging station 320 may determine whether the vehicle 100 is stopped in a predetermined region.”; para. 0132: “The vehicle 100 may travel toward the destination along the traveling route [i.e., one or more candidate routes to the destination having a dynamic charging system], and traveling information collected in this process may be transmitted to the server 200 [i.e., determine] by the charging management device 101 (S108). The traveling information may include information such as the current location and the traveling speed of the vehicle 100.”); and
send, to the CAEV, a path planning trajectory (Yang, Fig. 1; para. 0048: “Referring to FIG. 1, a traveling route [i.e., path planning trajectory] for a vehicle 100 [i.e., the CAEV] to move to a destination is indicated by a thick arrow…Alternatively, the traveling route may be a result of searching by the server [i.e., processor, configured to: …send…] based on information related to the current location and destination provided from the vehicle 100 to a server such as a charging management server.”; Note: If the path planning trajectory is the result of actions completed by the processor and the CAEV is traveling on the planned trajectory, then the planned trajectory must have been sent from the server to the CAEV.)
while (Note: Processors are capable of executing two or more tasks/calculations concurrently.)
identifying a localization accuracy of one or more sensors of the CAEV to update the localization accuracy of the CAEV based on a battery of the CAEV being charged with the dynamic charging system along the one or more candidate routes (Yang, para. 0072: “The charge control device 310 is a device configured to control the charging operation of the wireless charging station 320. The charge control device 310 may be configured to control an operating state of the wireless charging station 320 based on vehicle information received from the server 200 and signal information of traffic lights. The vehicle information may include identification information for identifying the vehicle 100 and location information indicating the location of the vehicle 100 [i.e., Vehicle location based on vehicle sensors.].”; para. 0070: “The wireless charging station 320 is a device installed under the ground of a road and configured to wirelessly transmit power within a predetermined region. The wireless charging station 320 may determine whether the vehicle 100 is stopped in a predetermined region [i.e., identifying a localization accuracy of one or more sensors of the CAEV; Note: One or more sensors of the CAEV will have the same location as the CAEV.]. For example, the wireless charging station 320 may determine whether the vehicle 100 is stopped at a location in which a power transmission rate is equal to or greater than a reference value if power is wirelessly transmitted to the battery of the vehicle 100 [i.e., update the localization accuracy of the CAEV based on a battery of the CAEV being charged with the dynamic charging system…]. That is, determination may be made as to whether the wireless charging efficiency of the battery of the vehicle 100 by the wireless charging station 320 is equal to or greater than a reference value. If it is determined that the vehicle 100 is stopped in the predetermined region, the wireless charging station 320 may wirelessly transmit power to the battery of the vehicle 100.”; para. 0175: “The wireless charging station 320 may include a control unit 322, a communication unit 323, and a power transmission unit 324.”; para. 0176: “That is, the control unit 322 functions as a vehicle location determination device.”)…
…wherein the localization accuracy is updated by comparing charging rate information from the battery with stored transmitter coil location data to determine an actual position of the CAEV relative to known transmitter coil positions (Yang, para. 0082: “If the vehicle 100 is stopped to be completely covered by any one of the plurality of chargeable sub-regions 321 a to 321 d, the wireless charging efficiency will be higher than a reference value [i.e., localization accuracy is updated]. Accordingly, the battery of the vehicle 100 will be charged through a wireless power transmission unit provided in the wireless charging station 320. On the other hand, if the vehicle 100 is stopped over a part of any one of the plurality of chargeable sub-regions 321 a to 321 d, wireless charging efficiency [i.e., charging rate information from the battery] is determined according to information such as a relative location between the wireless charging unit provided in the vehicle 100 and the wireless power transmitting unit of the chargeable sub-region [i.e., comparing charging rate information from the battery with stored transmitter coil location data to determine an actual position of the CAEV relative to known transmitter coil positions]. Then, if the determined wireless charging efficiency is equal to or greater than a reference value, the battery of the vehicle 100 is charged.”).
Yang does not appear to explicitly disclose the following:
…while traveling at a non-zero velocity...
However, in the same field of endeavor, Steele teaches:
…while traveling at a non-zero velocity (Steele, para. 0085: “The approach is to install PTMs 14 that fully “energize” the normal lane lengths associated with cueing and acceleration through and surrounding intersection 52. This arrangement allows stationary electric vehicles 20 to receive maximum battery charging while waiting for an intersection light to change, and full charging energy plus acceleration energy transfer when vehicles 20 leave intersection 52 [i.e., while traveling at a non-zero velocity]. The energy demands of accelerating vehicles 20 represent a significantly disproportionate battery energy drain that can be nearly eliminated via a WAVES 10 energized intersection 52 [i.e., while traveling at a non-zero velocity]. Furthermore, electric vehicles 20 that are simply passing through intersection 52 on a green light also benefit by a relatively short period of full charge rate and full electromotive energization [i.e., while traveling at a non-zero velocity]. Since the cruising energy demands for EVs are modest at urban speeds, a network of such WAVES intersections 52 within a city environment can nearly fully provide the energy needs traffic without having to electrify gaps between intersections 52 such as would be the case in a full WAVES roadway 36 installation.”).
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention and with a reasonable likelihood of success to modify the invention disclosed by Yang, with the concept of an electric vehicle battery being charged by a dynamic charging system while in motion, taught by Steele, in order to maximize total inductive charging time and therefore attempt to maximize the state of charge of the electric vehicle’s battery (Steele, para. 0085: “The energy demands of accelerating vehicles 20 represent a significantly disproportionate battery energy drain that can be nearly eliminated via a WAVES 10 energized intersection 52. Furthermore, electric vehicles 20 that are simply passing through intersection 52 on a green light also benefit by a relatively short period of full charge rate and full electromotive energization. Since the cruising energy demands for EVs are modest at urban speeds, a network of such WAVES intersections 52 within a city environment can nearly fully provide the energy needs traffic without having to electrify gaps between intersections 52 such as would be the case in a full WAVES roadway 36 installation.”).
Regarding claim 17 and analogous claims 3 and 10, Yang and Steele teach the system of claim 15, and Yang further discloses the following:
the processor configured to: determine the destination of the CAEV based on the vehicle information, wherein the destination is indicated within the vehicle information (Yang, para. 0048: “Alternatively, the traveling route may be a result of searching by the server [i.e., the processor] based on information related to the current location and destination [i.e., configured to: determine the destination of the CAEV] provided from the vehicle 100 [i.e., the CAEV] to a server [i.e., based on the vehicle information, wherein the destination is indicated within the vehicle information] such as a charging management server.”).
Regarding claim 5, Yang and Steele teach the method of claim 1, and Yang further discloses the following:
wherein the determining the one or more candidate routes to the destination (see claim 1 analysis above),
determining one or more waypoints and one or more road segments for each of the one or more candidate routes to the destination (Yang, para. 0007: “According to an aspect of embodiments of the present disclosure, there is provided a charging management device managing charging of a vehicle battery…wherein the operations include searching for a vehicle traveling route at least based on a destination of a vehicle [i.e., the one or more candidate routes to the destination], identifying wireless charging stations available [i.e., determine one or more waypoints] to make charging while being stopped based on the traveling route, and receiving power from the wireless charging station when stopped in charging available positions at intersections [i.e., one or more road segments] in which the identified wireless charging stations are installed.”); and
determining the one or more road segments comprising a dynamic charging system (Yang, para. 0007: “According to an aspect of embodiments of the present disclosure, there is provided a charging management device managing charging of a vehicle battery…wherein the operations include searching for a vehicle traveling route at least based on a destination of a vehicle, identifying wireless charging stations available to make charging while being stopped based on the traveling route, and receiving power from the wireless charging station when stopped in charging available positions at intersections [i.e., determine one or more road segments] in which the identified wireless charging stations are installed [i.e., comprising a dynamic charging system].”),
wherein a number and a location of transmitter coils is detected for each of the one or more road segments comprising the dynamic charging system (Yang, para. 0007: “According to an aspect of embodiments of the present disclosure, there is provided a charging management device managing charging of a vehicle battery…wherein the operations include searching for a vehicle traveling route at least based on a destination of a vehicle, identifying wireless charging stations available to make charging while being stopped based on the traveling route [i.e., a number and a location of transmitter coils is detected], and receiving power from the wireless charging station when stopped in charging available positions at intersections [i.e., for each of the one or more road segments] in which the identified wireless charging stations are installed [i.e., comprising the dynamic charging system].”),
the transmitter coils being associated with a surface that the CAEV is traveling on (Yang, para. 0013: “According to another aspect of embodiments of the present disclosure, there is provided a wireless charging system including a wireless charging station [i.e., transmitter coils] installed under the ground of a road [i.e., associated with a surface that the CAEV is traveling on] and configured to wirelessly transmit power within a predetermined region…”).
Regarding claim 19 and analogous claim 12, Yang and Steele teach the system of claim 15, wherein the determining the one or more candidate routes to the destination (see claims 15 and 17 analyses above),
the processor configured to (Yang, para. 0007: “According to an aspect of embodiments of the present disclosure, there is provided a charging management device managing charging of a vehicle battery, including at least one processor, at least one memory that stores computer program instructions that, when executed, cause the at least one processor to perform operations…”):
determine one or more waypoints and one or more road segments for each of the one or more candidate routes to the destination (Yang, para. 0007: “According to an aspect of embodiments of the present disclosure, there is provided a charging management device managing charging of a vehicle battery…wherein the operations include searching for a vehicle traveling route at least based on a destination of a vehicle [i.e., the one or more candidate routes to the destination], identifying wireless charging stations available [i.e., determine one or more waypoints] to make charging while being stopped based on the traveling route, and receiving power from the wireless charging station when stopped in charging available positions at intersections [i.e., one or more road segments] in which the identified wireless charging stations are installed.”); and
determine the one or more road segments comprising a dynamic charging system (Yang, para. 0007: “According to an aspect of embodiments of the present disclosure, there is provided a charging management device managing charging of a vehicle battery…wherein the operations include searching for a vehicle traveling route at least based on a destination of a vehicle, identifying wireless charging stations available to make charging while being stopped based on the traveling route, and receiving power from the wireless charging station when stopped in charging available positions at intersections [i.e., determine one or more road segments] in which the identified wireless charging stations are installed [i.e., comprising a dynamic charging system].”),
wherein a number and a location of transmitter coils is detected for each of the one or more road segments comprising the dynamic charging system (Yang, para. 0007: “According to an aspect of embodiments of the present disclosure, there is provided a charging management device managing charging of a vehicle battery…wherein the operations include searching for a vehicle traveling route at least based on a destination of a vehicle, identifying wireless charging stations available to make charging while being stopped based on the traveling route [i.e., a number and a location of transmitter coils is detected], and receiving power from the wireless charging station when stopped in charging available positions at intersections [i.e., for each of the one or more road segments] in which the identified wireless charging stations are installed [i.e., comprising the dynamic charging system].”).
Claim(s) 2, 9, and 16 is/are rejected under 35 U.S.C. 103 as being unpatentable over Yang, in view of Steele, US-20210064041, hereinafter “Kim” and KR-20210056708-A, hereinafter “Yoon”.
Regarding claim 16 and analogous claims 2 and 9, Yang and Steele teach the system of claim 15, but do not appear to explicitly teach the following:
the processor configured to: determine, using the one or more sensors of the CAEV, a sensor field of view (FOV) of the CAEV based at least on the vehicle information; and determine an amount of computing resources of the CAEV based at least on the vehicle information.
However, in the same field of endeavor, Kim teaches:
(A system and a method (Kim, para. 0002: “The present disclosure relates to a path providing device [i.e., a system] providing a path (route) to a vehicle and a path providing method [i.e., a method] thereof.”), and a non-transitory CRM (para. 0622: “The present disclosure can be implemented as computer-readable codes (applications or software) in a program-recorded medium [i.e., a non-transitory CRM].”).)
the processor configured to: determine, using the one or more sensors of the CAEV, a sensor field of view (FOV) of the CAEV based at least on the vehicle information (Kim, Fig. 13, step S1350; para. 0428: “The processor 830 may generate autonomous driving visibility information [i.e., sensor field of view (FOV) of the CAEV] in which sensing information is fused with the optimal path to transmit it to at least one of electrical parts provided in a server [i.e., determine…based at least on the vehicle information] or a vehicle (S1350).”); and
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention and with a reasonable likelihood of success to modify the invention disclosed by Yang, as modified by Steele, with the concept of sending vehicle sensor and field-of-view data to a server, taught by Kim, in order to determine the location of a vehicle by using the available sensors and their field-of-view (Kim, para. 0027: “…generating autonomous driving visibility information and transmitting the generated autonomous driving visibility information to at least one of the server or an electric component disposed at the vehicle based on the sensing information and the determined optimal path, updating the optimal path based on dynamic information related to a movable object located in the optimal path and the autonomous driving visibility information, receiving different types of sensor data from a plurality of sensors disposed at the vehicle, and updating at least one of the autonomous driving visibility information or the optimal path based on information generated by combining at least two types of sensor data.”).
Yang, Steele, and Kim do not appear to explicitly teach the following:
determine an amount of computing resources of the CAEV based at least on the vehicle information.
However, in the same field of endeavor, Yoon teaches:
(A system, a method (translated copy of Yoon, para. 0001: “The present invention relates to a server workload distribution method [i.e., a method], a server workload support method of a vehicle [i.e., a method], and a server workload support vehicle [i.e., a system] that allow the workload of an edge server [i.e., a system] to be distributed and processed by the vehicle by utilizing the available computational resources of the vehicle will be.”), and a non-transitory CRM (para. 0208: “The embodiment according to the present invention described above may be implemented in the form of a computer program that can be executed through various components on a computer, and such a computer program may be recorded in a computer-readable medium [i.e., a non-transitory CRM].”).)
determine an amount of computing resources of the CAEV based at least on the vehicle information (translated copy of Yoon, para. 0004: “An object of the present disclosure is to enable distributed processing of the workload of the edge server to the vehicle by utilizing the available computational resources of the vehicle.”; Note: If an edge server is going to distribute a processing workload to the computational resources of a vehicle, it must first be apprised of the amount of and/or the amount of available computing resources of the vehicle, based on vehicle provided information.).
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention and with a reasonable likelihood of success to modify the invention disclosed by Yang, as modified by Steele and Kim, with the concept of distributed data processing and load balancing and the sharing of computing resource data of a vehicle, taught by Yoon, in order to accelerate the processing of the massive amounts of sensor data, generated by a network that includes autonomous vehicles (translated copy of Yoon, para. 0002: “When new technologies such as AI, IoT, and autonomous driving become popular in the future, the amount of data coming and going through the network will increase explosively. Since the computing server must be able to process this enormous amount of data without delay, a technology that complements cloud computing that processes all data centrally is needed. As a supplementary measure, edge computing technology is attracting attention recently.”; para. 0003: “Edge Computing is a computing method that supports data flow acceleration by processing data generated from various terminal devices in real time at the site or near the location where the data is generated without sending it to a centralized data center such as the cloud.”).
Claim(s) 4, 11, and 18 is/are rejected under 35 U.S.C. 103 as being unpatentable over Yang, in view of Steele and US-20160377449-A1, hereinafter “Gerlach”.
Regarding claim 18 and analogous claims 4 and 11, Yang and Steele teach the system of claim 15, and a processor, but do not appear to explicitly teach the following:
the processor configured to: predict the destination of the CAEV based on the vehicle information, wherein the destination is not indicated within the vehicle information, wherein the predicting the destination is based at least on one of a driver profile, a passenger profile, a vehicle profile, historic trip data, or a time of day.
However, in the same field of endeavor, Gerlach teaches:
the processor configured to (Gerlach, para. 0033: “Alternatively, the present method and system 100 may be embodied as a separate designated system that communicates with the vehicle navigation system and/or other vehicle systems.”; para. 0057: “The method 300 [i.e., a method] and system 100 [i.e., a system] of the invention, described above, may be implemented in a typical computer hardware configuration [i.e., processor]… Such a method may be implemented, for example, by operating a computer, as embodied by a digital data processing apparatus, to execute a sequence of machine-readable instructions [i.e., a non-transitory CRM, storing instructions for execution by one or more hardware processors].”):
predict the destination of the CAEV based on the vehicle information, wherein the destination is not indicated within the vehicle information (Gerlach, para. 0016: “…an exemplary feature of the present invention is to provide a system and method that more accurately predicts a vehicle destination [i.e., predict the destination] and/or route using complex sensor data fusion to consider more vehicle data in addition to the location and time [i.e., based on the vehicle information, wherein the destination is not indicated within the vehicle information].”),
wherein the predicting the destination is based at least on one of a driver profile, a passenger profile, a vehicle profile, historic trip data, or a time of day (Gerlach, para. 0016: “…an exemplary feature of the present invention is to provide a system and method that more accurately predicts a vehicle destination [i.e., predicting the destination] and/or route using complex sensor data fusion to consider more vehicle data in addition to the location and time [i.e., based at least on one of…time of day].”; para. 0017: “According to a first non-limiting, exemplary aspect of the invention, a method for predicting a destination of a vehicle includes receiving vehicle data from a plurality of sensors, the vehicle data including a current location of the vehicle, determining a plurality of usage scenarios based on the vehicle data [i.e., based at least on one of… a vehicle profile], accessing historical vehicle data [i.e., based at least on one of…historic trip data] and user data from a database [i.e., based at least on one of…a driver profile, a passenger profile], assigning, based on the vehicle data, a likelihood value to each of the plurality of usage scenarios, and predicting a set of destinations and routes for each of the plurality of usage scenarios.”).
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention and with a reasonable likelihood of success to modify the invention disclosed by Yang, as modified by Steele, with the capability of predicting a destination of a vehicle using driver or passenger profile data, vehicle profile data, historic trip data, and/or time of day, taught by Gerlach, in order to provide more accurate destination predictions in scenarios where drivers or users function in exceptional or spontaneous ways or there is an error in the destination data being communicated to the processor (Gerlach, para. 0027: “As detailed above, certain conventional techniques attempt to predict destinations by comparing time and location with recorded historic trips. There are several common situations, however, in which the most common trip pattern of a certain user is disrupted because of exceptional situations or spontaneous user decisions.”).
Claim(s) 6, 13, and 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Yang, in view of Steele and US-20160171521-A1, hereinafter “Ramirez”.
Regarding claim 20 and analogous claims 6 and 13, Yang and Steele teach the system of claim 19, and a processor, but do not appear to explicitly teach the following:
the processor configured to: determine a safety score for each of the one or more road segments for automated driving (AD); and identify a best route from the one or more candidate routes based at least on the safety score for the one or more road segments.
However, in the same field of endeavor, Ramirez teaches:
the processor configured to: determine a safety score for each of the one or more road segments for automated driving (AD) (Ramirez, Fig. 13: device 1301, processor 1303 [i.e., the processor configured to]; para. 0006: “Aspects of the disclosure relate to methods [i.e., a method], computer-readable media [i.e., a non-transitory CRM], systems and apparatuses [i.e., a system] for determining a road segment safety rating [i.e., safety score].”; para. 0115: “In certain embodiments, vehicle sensors, vehicle on-board diagnostic systems (OBDs) and other vehicle-based systems and/or vehicle communication systems, may collect and/or transmit data pertaining to autonomous driving of the vehicles [i.e., for automated driving (AD)].”); and
identify a best route from the one or more candidate routes based at least on the safety score for the one or more road segments (Ramirez, Fig. 6: safety rating system 600, recommendation module 614; para. 0096: “Road segment safety rating system 600 may further include a recommendation module 614. The recommendation module 614 may generate, or be configured to generate, one or more recommendations for alternate road segments that may have a safer rating [i.e., identify a best route from the one or more candidate routes] than, for instance, a road segment on which the vehicle is currently travelling or will be travelling [i.e., based at least on the safety score for the one or more road segments].”).
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention and with a reasonable likelihood of success to modify the invention disclosed by Yang, as modified by Steele, with the concept of determining a safety score of road segments and identifying a best route based on the safety score, taught by Ramirez, in order to mitigate the risk of travel on certain roads and/or road segments (Ramirez, para. 0004: “Therefore, there is a benefit in the art for an enhanced method and device for calculating a risk for a road segment and using it to, among other things, mitigate risk.”).
Claim(s) 7 and 14 is/are rejected under 35 U.S.C. 103 as being unpatentable over Yang, in view of Steele and "Intelligent wireless charging station for electric vehicles,” hereinafter “Sultanbek”.
Regarding claim 7 and analogous claim 14, Yang and Steele teach the method of claim 1, wherein in response to a determination that the road segment that the CAEV is on comprises the dynamic charging system and the ability to identify and update a localization accuracy of the CAEV (see claim 15 analysis above), but do not appear to explicitly teach the following:
verifying a localization accuracy of the CAEV or the one or more sensors of the CAEV based on a receiver coil of the CAEV interacting with a transmitter coil of the dynamic charging system, wherein a location of the transmitter coil of the dynamic charging system is known such that a location of the CAEV is determined based on the CAEV engaging with the dynamic charging system, wherein sensor calibration parameters or threshold values are updated to avoid localization error.
However, in the same field of endeavor, Sultanbek teaches:
(a method (Sultanbek, pg. 5, col. 2, last paragraph: “The flow chart of proposed algorithm is provided to describe the process of localization in detail (see Figure 9).”) and a non-transitory CRM (Sultanbek, pg. 6, col. 1, first full paragraph: “Simulation of algorithm was performed on C++ software to show the process of identifying coil position.”))
further comprises: verifying a localization accuracy of the CAEV or the one or more sensors of the CAEV based on a receiver coil of the CAEV interacting with a transmitter coil of the dynamic charging system (Sultanbek, pg. 5, col. 2, first full paragraph: “To perform localization [i.e., verifying a localization accuracy of the CAEV] and start charging, it is required to scan the entire searching area and identify precise location [i.e., localization accuracy] of the receiving coil. According to fingerprint method, map of data with current values should be produced. As discussed earlier, it was proposed to divide searching area into an imaginary mesh to produce a matrix. This matrix will return the current values measured over the receiver coil due to movement of transmitting coil under the ground [i.e., receiver coil of the CAEV interacting with a transmitter coil of the dynamic charging system].”),
wherein a location of the transmitter coil of the dynamic charging system is known such that a location of the CAEV is determined based on the CAEV engaging with the dynamic charging system (Sultanbek, pg. 5, col. 1, paragraph 6-7: “Receiving coil is embedded to the bottom of the vehicle, whereas, transmitting coil will be installed on the platform…Therefore, the whole installation will be driven along two axes in order to place coil on the appropriate position [i.e., location of the transmitter coil of the dynamic charging system is known].”; pg. 5, col. 2, first full paragraph: “To perform localization and start charging, it is required to scan the entire searching area and identify precise location of the receiving coil [i.e., a location of the CAEV is determined based on the CAEV engaging with the dynamic charging system; Note: Since the receiving coil is located on the vehicle, determining the location of the receiver coil will determine the location of the vehicle.]. According to fingerprint method, map of data with current values should be produced. As discussed earlier, it was proposed to divide searching area into an imaginary mesh to produce a matrix. This matrix will return the current values measured over the receiver coil due to movement of transmitting coil under the ground [i.e., based on the CAEV engaging with the dynamic charging system].”),
wherein sensor calibration parameters or threshold values are updated to avoid localization error (Note: One of ordinary skill in the art, at the time of the application would know that sensors in localization systems would need to be calibrated and updated in order to avoid system errors.).
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention and with a reasonable likelihood of success to modify the invention disclosed by Yang, as modified by Steele, with the capability of verifying a localization accuracy of a vehicle based on its receiver coil interacting with a transmitter coil, taught by Sultanbek, in order to charge the vehicle in the most efficient way possible, because location and positioning affects the efficiency of power transfer in inductive charging systems (Sultanbek, pg. 5, col. 2, first full paragraph: “Using this technique, developed matrix with current values at each square will allow identifying the most efficient charging position for the coils.”; pg. 5, col. 2, second full paragraph: “After finishing scanning of the whole area, matrix with current values is produced. Then, algorithm will process data of current values and will find the location, where two coils will have most efficient charging position.”).
Conclusion
THIS ACTION IS MADE FINAL. 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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/L.N.M./Examiner, Art Unit 3666
/HELAL A ALGAHAIM/SPE , Art Unit 3666
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