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 action is in reply to the response filed on May 18, 2026.
Claims 1-20 are currently pending and have been examined.
This action is made FINAL.
The examiner would like to note that this application is being handled by examiner Christine Huynh.
Response to Arguments
Applicant's arguments filed May 18, 2026 have been fully considered but they are not persuasive. With respect to the 35 U.S.C. 101 rejection, applicants argue in pages 7-8 that the amendments have overcome the 101. The applicant argues that because the instant limitations include receiving “external information”, then there is practical application of the limitations because the external infrastructure can include power and airport/seaport facilities. However, the examiner disagrees, as the limitation “receiving, by the processor, external information related to an electromagnetic interference area from an external system…” is insignificant extra-solution activities that merely use a computer (processor) to perform the process. In particular, the receiving steps from the external source are recited at a high level of generality (i.e. as a general means of gathering the infrastructure data for use in the determining step), and amounts to mere data gathering, which is a form of insignificant extra-solution activity. The physical infrastructure facilities are merely being used to relay information. Therefore, the claims as amended are still directed to an abstract idea. Accordingly, the 35 U.S.C. 101 rejection is maintained. See detailed rejection below.
Applicant’s arguments with respect to claim(s) 1 and similar independent claim 11 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument. Upon further search and consideration, claims 1 and 11 are rejected under 35 U.S.C. 103 as being unpatentable over Chan et al. (US 11237555 B1) in view of Ali et al. (US 20230282121 A1). See detailed rejection below.
Dependent claims are rejected for the same reasons above due to dependency. See detailed rejection below.
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.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
101 Analysis – Step 1
Claims 1-10 are directed to a method of controlling an autonomous vehicle and claims 11-20 are directed to an autonomous vehicle which are/is one of the statutory categories of invention.
101 Analysis – Step 2A, Prong I
Regarding Prong I of the Step 2A analysis in the 2019 PEG, the claims are to be analyzed to determine whether they recite subject matter that falls within one of the follow groups of abstract ideas: a) mathematical concepts, b) certain methods of organizing human activity, and/or c) mental processes.
Independent claim 1 includes limitations that recite an abstract idea (emphasized below) and will be used as a representative claim for the remainder of the 101 rejection. Claim 1 recites:
A method of controlling an autonomous vehicle including a processor, the method comprising:
receiving, by the processor, external information related to an electromagnetic interference area from an external system, wherein the external information includes at least one of information related to locations of electric power transmitting stations or substations, information related to airports or seaports, and information related to predicted thunderstroke areas;
generating an avoidance area on a navigation map by applying the external information to the navigation map;
determining whether the autonomous vehicle enters the avoidance area based on the navigation map; and
generating a warning signal related to an occurrence of an error in the autonomous vehicle based on a result of the determining.
The examiner submits that the foregoing bolded limitation(s) constitute a “mental process” because under its broadest reasonable interpretation, the claim covers performance of the limitation in the human mind. For example, “determining whether the autonomous vehicle enters the avoidance area based on the navigation map” in the context of this claim encompasses a person (driver) looking at data collected on a map and forming a simple judgement based on the given data. Accordingly, the claim recites at least one abstract idea.
101 Analysis – Step 2A, Prong II
Regarding Prong II of the Step 2A analysis in the 2019 PEG, the claims are to be analyzed to determine whether the claim, as a whole, integrates the abstract into a practical application. As noted in the 2019 PEG, it must be determined whether any additional elements in the claim beyond the abstract idea integrate the exception into a practical application in a manner that imposes a meaningful limit on the judicial exception. The courts have indicated that additional elements merely using a computer to implement an abstract idea, adding insignificant extra solution activity, or generally linking use of a judicial exception to a particular technological environment or field of use do not integrate a judicial exception into a “practical application.”
In the present case, the additional limitations beyond the above-noted abstract idea are as follows (where the underlined portions are the “additional limitations” while the bolded portions continue to represent the “abstract idea”):
A method of controlling an autonomous vehicle including a processor, the method comprising:
receiving, by the processor, external information related to an electromagnetic interference area from an external system, wherein the external information includes at least one of information related to locations of electric power transmitting stations or substations, information related to airports or seaports, and information related to predicted thunderstroke areas;
generating an avoidance area on a navigation map by applying the external information to the navigation map;
determining whether the autonomous vehicle enters the avoidance area based on the navigation map; and
generating a warning signal related to an occurrence of an error in the autonomous vehicle based on a result of the determining.
For the following reason(s), the examiner submits that the above identified additional limitations do not integrate the above-noted abstract idea into a practical application.
Regarding the additional limitations of “receiving, by the processor, external information related to an electromagnetic interference area from an external system…”, “generating an avoidance area on a navigation map by applying the external information to the navigation map”, and “generating a warning signal related to an occurrence of an error in the autonomous vehicle based on a result of the determining”, the examiner submits that these limitations are insignificant extra-solution activities that merely use a computer (processor) to perform the process. In particular, the receiving steps from the external source are recited at a high level of generality (i.e. as a general means of gathering infrastructure data for use in the determining step), and amounts to mere data gathering, which is a form of insignificant extra-solution activity. The generating an avoidance area on a map is merely populating an existing map with the received information. The displaying results step on the driver display console is also recited at a high level of generality (i.e. as a general means of displaying the avoidance result from the determining step), and amounts to mere post solution displaying, which is a form of insignificant extra-solution activity. Lastly, the “vehicle controller” is recited at a high-level of generality (i.e., as a generic processor performing a generic computer function of ranking information based on a determined amount of use) such that it amounts no more than mere instructions to apply the exception using a generic computer component.
Thus, taken alone, the additional elements do not integrate the abstract idea into a practical application. Further, looking at the additional limitation(s) as an ordered combination or as a whole, the limitation(s) add nothing that is not already present when looking at the elements taken individually. For instance, there is no indication that the additional elements, when considered as a whole, reflect an improvement in the functioning of a computer or an improvement to another technology or technical field, apply or use the above-noted judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition, implement/use the above-noted judicial exception with a particular machine or manufacture that is integral to the claim, effect a transformation or reduction of a particular article to a different state or thing, or apply or use the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is not more than a drafting effort designed to monopolize the exception (MPEP § 2106.05). Accordingly, the additional limitation(s) do/does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea.
101 Analysis – Step 2B
Regarding Step 2B of the Revised Guidance, representative independent claim 1 does not include additional elements (considered both individually and as an ordered combination) that are sufficient to amount to significantly more than the judicial exception for the same reasons to those discussed above with respect to determining that the claim does not integrate the abstract idea into a practical application. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of using a vehicle controller to perform the evaluating… amounts to nothing more than mere instructions to apply the exception using a generic computer component. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. And as discussed above, the additional limitations of “receiving by the processor, external information from an external source, and updating navigation map information based on the received external information” and “generating a warning signal related to an occurrence of an error in the autonomous vehicle based on a result of the determining”, the examiner submits that these limitations are insignificant extra-solution activities. Hence, the claim is not patent eligible.
Dependent claim(s) 2-10 and 12-20 do not recite any further limitations that cause the claims to be directed towards statutory subject matter. The claims merely recite: [repeat the judicial exception]. Each of the further limitations expound upon the [repeat judicial exception] and do not recite additional elements integrating the [repeat judicial exception] into a practical application or additional elements that are not well-understood, routine or conventional. Therefore, dependent claims 2-10 and 12-20 are similarly rejected as being directed towards non-statutory subject matter.
Therefore, claim(s) 1-20 is/are ineligible under 35 USC §101.
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.
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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claim(s) 1-3, 6, 9-13, 16, and 19-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Chan et al. (US 11237555 B1) in view of Jian (US 20180239359 A1) and Ali et al. (US 20230282121 A1).
Regarding claims 1-3, 6, 9-13, 16, and 19-20:
With respect to claims 1 and 11, Chan teaches:
determining whether the autonomous vehicle enters the avoidance area based on the navigation map; (“In some embodiments, threat assessment may include determining current EMI activity or an EMI level for a particular geographic area (e.g., a current geographic region of vehicle 100). In some embodiments, threat assessment may include comparing a detected EMI level with one or more of a baseline EMI level and historical EMI data. If, for example, the detected EMI level is above the baseline EMI level (e.g., a pre-determined threshold), or if the detected EMI level is above historical EMI levels (e.g., in the top 20.sup.th percentile based upon the historical EMI levels), then the backup control computing device 102 may initiate the determined set of mitigating actions based upon the detected EMI level.” (col 16, lines 15-23), “FIG. 6 illustrates an exemplary computer-implemented method of EMI risk mitigation 600. The computer-implemented method 600 may include, via one or more processors, sensors, transceivers, and/or servers: (1) detecting electromagnetic interference (EMI), and/or determining current EMI activity or level(s) for a specific area, such as a city 602; (2) comparing the current EMI activity or level(s) with baseline EMI data or historical EMI data to determine or identify vehicle systems (such as autonomous or semi-autonomous vehicle systems, or other systems discussed elsewhere herein) with likely or potential performance degradation at the current EMI activity or level(s) 604” (col 21, line 64 – col 22, line 8), where it can be determined when a vehicle enters an avoidance area by determining detected EMI levels.
generating a warning signal related to an occurrence of an error in the autonomous vehicle based on a result of the determining; (“The method 600 may also include adjusting an insurance discount for vehicles equipped with, or capable of implementing, the EMI risk mitigation functionality 610. In some embodiments, adjusting may include adjusting an insurance discount for drivers having vehicles that are configured to initiate the one or more risk mitigation actions. In some embodiments, risk mitigation actions may include, generating warnings to vehicles or vehicle operators, generating a visual alert to an operator of the vehicle…” (col 22, lines 23-31)), where a warning signal can be generated based on EMI affecting vehicle functionality.
a processor; (“The processor is programmed to detect an anomalous event. The anomalous event may include one of a geomagnetic interference event and a cyber-attack event.” (col 2, lines 31-33).
Chan does not teach, but Ali teaches:
receiving, by the processor, external information related to an electromagnetic interference area from an external system, wherein the external information includes at least one of information related to locations of electric power transmitting stations or substations, information related to airports or seaports, and information related to predicted thunderstroke areas; (“FIG. 1 sets forth a diagram of a system 100 configured of displaying electromagnetic spectrum information for UAV navigation according to embodiments of the present disclosure. The system 100 of FIG. 1 includes an unmanned aerial vehicle (UAV) 102, a user device 120, a server 140, a distributed computing network 151, an air traffic data server 160, a weather data server 170, a regulatory data server 180, and a topographic data server 190.” [0025], “In some examples, the radar map data 801 includes information related to radar sources and their locations and ranges. The radar sources may be stationary radar sources (e.g., an airport radar system) or moveable radar sources (e.g., radar systems of ships, planes, or portable ground-based radar). In some examples, the radar map data 801 for a radar system includes at least the location of the radar system.” [0095], “The method of FIG. 13 also includes obtaining 1302, from a map server 1301, the electromagnetic spectrum map data 507. In some examples, obtaining 1302, from a map server 1301, the electromagnetic spectrum map data 507 may be carried out by the ES awareness controller 501 requesting the electromagnetic spectrum map data 507 for a particular geographic area from the map server 1301 (e.g., the map server 440 of FIG. 4). For example, the geographic area may correspond to the present location of the UAV 503, a flight path of the UAV, or some other geographic location associated with a UAV mission. In one example, the map server 1301 may aggregate electromagnetic spectrum information such as one or more of cellular communications information, satellite communications information, radar activity information, laser activity information, spectrum activity information, interference activity information, and so on as described above.” [0109]), where external information from servers including air traffic data servers, which can be an airport, and weather data servers can be received relating to electromagnetic interference information related to airports locations, other radar source locations, and weather information that can affect electromagnetic waves.
generating an avoidance area on a navigation map by applying the external information to the navigation map; (“generating, based on interference map data, an interference map layer; and generating, based on UAV information, a UAV sensor range map layer. In an embodiment, the ES awareness controller 139 further includes computer program instructions that when executed by the processor 122 cause the processor 122 to carry out the operations of obtaining, from a map server, the electromagnetic spectrum map data” [0039], “In the method of FIG. 8, generating 502, by the control device 500 associated with the UAV 503, the first map layer 505 based on the electromagnetic spectrum map data 507 includes generating 802, based on radar map data 801, a radar activity map layer 803. In some examples, the radar map data 801 includes information related to radar sources and their locations and ranges. The radar sources may be stationary radar sources (e.g., an airport radar system) or moveable radar sources (e.g., radar systems of ships, planes, or portable ground-based radar). In some examples, the radar map data 801 for a radar system includes at least the location of the radar system.” [0095], “In further examples, the interference map data 1101 includes information about spectrum activity associated with a particular location. For example, the interference map data 497 can be based other electromagnetic spectrum map data discussed above. In such cases, the interference map data 1101 can include spectrum activity information as it relates to particular communications devices or sensors of the UAV. In still further examples, the interference map data 1101 can identify areas where some or all frequencies are jammed are intentionally jammed.” [0104]), where a map is generated using the external information, including areas to avoid due to the electromagnetic interference.
It would have been obvious to one of ordinary skill in the art before the effective filling date of the instant application to have combined Chan’s preventing a malfunction caused by electromagnetic interference with Ali’s map information because (“there are many types of ambient and environmental electromagnetic signals that a UAV may encounter during flight. In some cases, such as with control device and data communications signals, it is important that the UAV does not navigate outside of the range of such communication. In other cases, electromagnetic activity could interfere with the UAV's communication and sensor systems. Thus, it is advantageous to provide a UAV user or operator with a visualization of non-visible portions of the electromagnetic spectrum, which can assist the user or operator in safe navigation of the UAV.” See Ali [0004]), in order to improve autonomous vehicle navigation based on electromagnetic interference.
With respect to claims 2 and 12, Chan in combination with Ali, as shown in the rejection above, discloses the limitations of claims 1 and 11. The combination of Chan and Ali teaches preventing a malfunction caused by electromagnetic interference which may occur during autonomous driving of claims 1 and 11. Chan further teaches:
at least one of an internal operation error predicted to occur in vehicle electronic units mounted on the autonomous vehicle and an autonomous driving operation error of the autonomous vehicle predicted to occur during autonomous driving of the autonomous vehicle; (“Since certain automation systems are performing safety-critical application (e.g., piloting functions) autonomously or semi-autonomously, miscalculations or other system errors introduced by such events may create problems for those involved. As such, it would be beneficial to have a backup control system to protect against dangers imposed by electromagnetic interference or cyber-attacks.” (col 6, line 63 – col 7, line 2), “In the exemplary embodiments, a backup control system analyzes and detects “anomalous events” associated with EMI or cybersecurity that may impact operation of automation systems for autonomous or semi-autonomous vehicles and associated infrastructure. The backup control system includes a backup control computing device (e.g., installed onboard the vehicle(s)) and a backup control server wirelessly connected to the backup control computing device. The backup control computing device may be configured to control various automation systems that provide aspects of autonomous operation for the vehicle and, more specifically, to perform mitigating actions on those automation systems of the vehicle when anomalous events are detected.” (col 7, lines 3-15)), where anomalous operation errors are predicted to occur during autonomous driving of the vehicle.
With respect to claims 3 and 13, Chan in combination with Ali, as shown in the rejection above, discloses the limitations of claims 2 and 12. The combination of Chan and Ali teaches preventing a malfunction caused by electromagnetic interference which may occur during autonomous driving of claims 2 and 12. Chan further teaches:
in response to an entry of the autonomous vehicle into the avoidance area, inducing, by the processor, a transfer of a control authority over the autonomous vehicle to a driver; (“The method 600 may also include adjusting an insurance discount for vehicles equipped with, or capable of implementing, the EMI risk mitigation functionality 610. In some embodiments, adjusting may include… transferring vehicle control back over to a human passenger...” (col 22, lines 23-37)), which shows that upon the detection of EMI, control authority can be transferred to the driver. Thus, it would have been obvious to a person of ordinary skill in the art where the control authority is transferred upon entering an avoidance area as an area where EMI is detected can be an avoidance area in an attempt to provide an improved system or method, as a person with ordinary skill has good reason to pursue the known options within his or her technical grasp. In turn, because the product as claimed has the properties predicted by the prior art, it would have been obvious to make the system or product where the control authority is transferred upon entering an avoidance area.
With respect to claims 6 and 16, Chan in combination with Ali, as shown in the rejection above, discloses the limitations of claims 2 and 12. The combination of Chan and Ali teaches preventing a malfunction caused by electromagnetic interference which may occur during autonomous driving of claims 2 and 12. Chan further teaches:
outputting, by the processor, the generated warning signal to a display unit mounted on the autonomous vehicle and operatively connected to the processor; (“The method 600 may also include adjusting an insurance discount for vehicles equipped with, or capable of implementing, the EMI risk mitigation functionality 610. In some embodiments, adjusting may include adjusting an insurance discount for drivers having vehicles that are configured to initiate the one or more risk mitigation actions. In some embodiments, risk mitigation actions may include, generating warnings to vehicles or vehicle operators, generating a visual alert to an operator of the vehicle…” (col 22, lines 23-31)), where a warning signal can be generated and outputted on a display based on EMI affecting vehicle functionality.
With respect to claims 9 and 19, Chan in combination with Ali, as shown in the rejection above, discloses the limitations of claims 1 and 11. The combination of Chan and Ali teaches preventing a malfunction caused by electromagnetic interference which may occur during autonomous driving of claims 1 and 11. Chan does not teach, but Ali teaches:
wherein the external system includes at least one system operated by electric power utilities airports or seaports, or meteorological agencies; (“FIG. 1 sets forth a diagram of a system 100 configured of displaying electromagnetic spectrum information for UAV navigation according to embodiments of the present disclosure. The system 100 of FIG. 1 includes an unmanned aerial vehicle (UAV) 102, a user device 120, a server 140, a distributed computing network 151, an air traffic data server 160, a weather data server 170, a regulatory data server 180, and a topographic data server 190.” [0025], “Air traffic data servers may be, for example, radar stations, airport air traffic control systems, the FAA, UAV control systems, and so on.” [0060], “Weather data servers may be, for example, the National Weather Service (NWS), the National Oceanic and Atmospheric Administration (NOAA), local meteorologists, radar stations, other aircraft, and so on.” [0061], “In some examples, the radar map data 801 includes information related to radar sources and their locations and ranges. The radar sources may be stationary radar sources (e.g., an airport radar system) or moveable radar sources (e.g., radar systems of ships, planes, or portable ground-based radar). In some examples, the radar map data 801 for a radar system includes at least the location of the radar system.” [0095]), where the external system includes airports or meteorological agencies.
It would have been obvious to one of ordinary skill in the art before the effective filling date of the instant application to have combined Chan’s preventing a malfunction caused by electromagnetic interference with Ali’s map information because (“there are many types of ambient and environmental electromagnetic signals that a UAV may encounter during flight. In some cases, such as with control device and data communications signals, it is important that the UAV does not navigate outside of the range of such communication. In other cases, electromagnetic activity could interfere with the UAV's communication and sensor systems. Thus, it is advantageous to provide a UAV user or operator with a visualization of non-visible portions of the electromagnetic spectrum, which can assist the user or operator in safe navigation of the UAV.” See Ali [0004]), in order to improve autonomous vehicle navigation based on electromagnetic interference.
With respect to claim 10, Chan in combination with Ali, as shown in the rejection above, discloses the limitations of claim 1. The combination of Chan and Ali teaches preventing a malfunction caused by electromagnetic interference which may occur during autonomous driving of claim 1. Chan further teaches:
A non-transitory computer-readable recording medium storing a program for executing autonomous driving of the autonomous vehicle of claim 1; (“a non-transitory computer-readable medium storing instructions may be provided. When executed by a processor of a computing device, the instructions cause the processor of a backup control computing device to perform operations including receiving an indication of an anomalous event… The automation system may be configured to control an aspect of autonomous operation of the vehicle.” (col 2, lines 4-16)).
With respect to claim 20, Chan in combination with Ali, as shown in the rejection above, discloses the limitations of claim 11. The combination of Chan and Ali teaches preventing a malfunction caused by electromagnetic interference which may occur during autonomous driving of claim 11. Chan further teaches:
wherein the avoidance area includes a plurality of ranges in which an electromagnetic interference intensity decreases as a distance from a center point of the avoidance area increases, (“In some embodiments, threat assessment may include determining current EMI activity or an EMI level for a particular geographic area (e.g., a current geographic region of vehicle 100). In some embodiments, threat assessment may include comparing a detected EMI level with one or more of a baseline EMI level and historical EMI data. If, for example, the detected EMI level is above the baseline EMI level (e.g., a pre-determined threshold), or if the detected EMI level is above historical EMI levels (e.g., in the top 20th percentile based upon the historical EMI levels), then the backup control computing device 102 may initiate the determined set of mitigating actions based upon the detected EMI level.” (column 16, lines 14-23), which shows that the severity of the EMI levels can be determined. Thus, it would have been obvious to a person of ordinary skill in the art that an electromagnetic interference intensity decreases as a distance from a center point of the avoidance area increases in an attempt to provide an improved system or method, as Chan teaches determining the severity of electromagnetic interference intensity, as a person with ordinary skill has good reason to pursue the known options within his or her technical grasp. In turn, because the product as claimed has the properties predicted by the prior art, it would have been obvious to make the system or product where the electromagnetic interference intensity decreases as a distance from a center point of the avoidance area increases.
wherein, in response to the autonomous vehicle entering the avoidance area, the processor is configured to generate warning signals having different intensities or different messages corresponding to the plurality of ranges; (“In some embodiments, threat assessment may include determining current EMI activity or an EMI level for a particular geographic area (e.g., a current geographic region of vehicle 100). In some embodiments, threat assessment may include comparing a detected EMI level with one or more of a baseline EMI level and historical EMI data. If, for example, the detected EMI level is above the baseline EMI level (e.g., a pre-determined threshold), or if the detected EMI level is above historical EMI levels (e.g., in the top 20th percentile based upon the historical EMI levels), then the backup control computing device 102 may initiate the determined set of mitigating actions based upon the detected EMI level.” (column 16, lines 14-23), “Determining a severity of the detected anomalous event may include generating an event score based upon various factors. Factors may include, for example, a likelihood of the anomalous event impacting vehicle 100 or a particular automation system 116 (shown in FIG. 1), an amount of use of the particular automation system 116 (shown in FIG. 1) likely to be impacted (e.g., how frequently automation system 116, shown in FIG. 1, is used by the driver or by vehicle 100 during normal operation), and a level of criticality of the particular automation system 116 (shown in FIG. 1) most likely to be impacted (e.g., higher value for systems that directly control steering functionality, lower value for systems that only provide warnings)” (column 16, lines 40-52), where different warning signals can be used corresponding to the plurality of ranges of the plurality of ranges of electromagnetic interference.
Claim(s) 4-5 and 14-15 is/are rejected under 35 U.S.C. 103 as being unpatentable over Chan et al. (US 11237555 B1) in view of Ali et al. (US 20230282121 A1) and Jian (US 20180239359 A1).
Regarding claims 4-5 and 14-15:
With respect to claims 4 and 14, Chan in combination with Ali, as shown in the rejection above, discloses the limitations of claims 3 and 13. The combination of Chan and Ali teaches preventing a malfunction caused by electromagnetic interference which may occur during autonomous driving of claims 3 and 13. Chan and Ali do not teach, but Jian teaches:
activating, by the processor, a search mode of searching for an avoidance path that detours around the avoidance area; (“At 110, a vehicle may determine a route to travel from a current location of the vehicle to a destination indicated (e.g., via a user interface of a navigation system, a button or switch, voice command, etc.) by a user. The vehicle may determine a route based on input from a GPS receiver and/or using a GPS navigation map. In some examples, the vehicle may identify several possible routes to arrive at the indicated destination, and may compare one or more routes according to various criteria.” [0017], “In some examples, a vehicle's starting point can automatically be obtained based on data from one or more location sensors, such as GPS, or based on data from an HD map. In response, the vehicle can retrieve and display the danger map 202 that includes various routes from location A to location B, and displays a danger level associated with each location along the routes.” [0022], “In some examples, the danger value threshold can correspond to one or more thresholds for changing driving style (e.g., including speed, acceleration, following distance, and other characteristics described above) and/or one or more thresholds for avoiding an area with that danger value altogether.” [0038]), which shows a search mode of searching for an avoidance path, or the path with a low danger level, to avoid areas with high danger.
It would have been obvious to one of ordinary skill in the art before the effective filling date of the instant application to have combined Chan’s preventing a malfunction caused by electromagnetic interference with Jian’s map search because (“it can be advantageous to store location-based perception data indicative of dangerous situations so that an autonomous vehicle can predict which areas along one or more routes will be dangerous and adjust its driving behavior and selected route accordingly.” See Jian [0020]).
With respect to claims 5 and 15, Chan in combination with Ali and Jian, as shown in the rejection above, discloses the limitations of claims 4 and 14. The combination of Chan, Ali, and Jian teaches preventing a malfunction caused by electromagnetic interference which may occur during autonomous driving of claims 4 and 14. Chan and Ali do not teach, but Jian teaches:
displaying, by the processor, the avoidance path; (“The vehicle may present any identified routes on a vehicle display to allow a user to change one or more criteria (e.g., time, distance, energy efficiency, etc.) for selecting a route or to allow a user to manually select between various possible routes. In some examples, the vehicle may display to the user only a few suggested routes of several possible routes identified by the vehicle.” [0017], “The routes may be displayed in an order specified by relevant criteria or user preferences, such as the safety, energy efficiency, distance, or duration of each route. For example, a user may specify a maximum danger value for any location included in a suggested route, and in response the vehicle may display routes without any location associated with a danger value exceeding the specified maximum danger value.” [0030]), which shows displaying the route selections and the selected route that is chosen based on the danger value.
It would have been obvious to one of ordinary skill in the art before the effective filling date of the instant application to have combined Chan’s preventing a malfunction caused by electromagnetic interference with Jian’s map display because (“it can be advantageous to store location-based perception data indicative of dangerous situations so that an autonomous vehicle can predict which areas along one or more routes will be dangerous and adjust its driving behavior and selected route accordingly.” See Jian [0020]).
Claim(s) 7-8 and 17-18 is/are rejected under 35 U.S.C. 103 as being unpatentable over Chan et al. (US 11237555 B1) in view of Ali et al. (US 20230282121 A1) and Zhang et al. (CN 114132513 A).
Regarding claims 7-8 and 17-18:
With respect to claims 7 and 17, Chan in combination with Ali, as shown in the rejection above, discloses the limitations of claims 6 and 16. The combination of Chan and Ali teaches preventing a malfunction caused by electromagnetic interference which may occur during autonomous driving of claims 6 and 16. Chan does not teach, but Zhang teaches:
storing, by the processor, a first operating state of the vehicle electronic units operating before the autonomous vehicle enters the avoidance area; (“In one embodiment, when a magnetic field disturbance event is detected, determining the current first working state of the first magnetic field sensing device includes: When the magnetic field interference signal is detected, obtain the first distance from the first magnetic field induction device to the magnetic field interference signal source; If the first distance matches a first preset distance interval, the current first working state of the first magnetic field sensing device is determined. In one of the embodiments, after the if the first working state is a non-working state, the current second working state of the second magnetic field sensing device is controlled to be an working state” (8-11)), where the first working state of the first sensor is operated to detect an interference before entering the interference affected area.
analyzing, by the processor, a second operating state of the vehicle electronic units operating after the autonomous vehicle exits the avoidance area, in comparison to the first operating state; (“the current second working state of the second magnetic field sensing device is controlled to be a working state, so as to use the second magnetic field sensing device to detect no The magnetic field induction signal of the man-machine realizes that when the first magnetic field induction device is detected to be disturbed by the magnetic field, the second magnetic field induction device of the drone is controlled to perform magnetic field induction, so that the first magnetic field induction device of the drone cannot work. , it can quickly switch to the second magnetic field induction device for magnetic field induction, and the magnetic field induction device can be alternated in time, which effectively guarantees the normal use of the drone.” (32)), where the second operating state is similar to when the second sensor is in a working state and the first sensor is in a non-working state, compared to when the first sensor is in a working state before entering an avoidance area. Thus, it would have been obvious to a person of ordinary skill in the art to analyze that the second sensor is in a working state and the first sensor is in a non-working state when the vehicle exits an avoidance area, as it is determining the affect of the interference, in an attempt to provide an improved system or method, as a person with ordinary skill has good reason to pursue the known options within his or her technical grasp. In turn, because the product as claimed has the properties predicted by the prior art, it would have been obvious to make the system or product to analyze that the second sensor is in a working state and the first sensor is in a non-working state when the vehicle exits an avoidance area.
It would have been obvious to one of ordinary skill in the art before the effective filling date of the instant application to have combined Chan’s preventing a malfunction caused by electromagnetic interference with Zhang’s operating state analysis because (“so as to ensure that the drone can detect the normal magnetic field sensing signal in real time, Improve the user's drone experience.” See Zhang (51)), which, while Zhang is regarding a drone, shows detecting interference for an autonomous vehicle.
With respect to claims 8 and 18, Chan in combination with Ali and Zhang, as shown in the rejection above, discloses the limitations of claims 7 and 17. The combination of Chan, Ali, and Zhang teaches preventing a malfunction caused by electromagnetic interference which may occur during autonomous driving of claims 7 and 17. Chan does not teach, but Zhang teaches:
restoring, by the processor, the vehicle electronic units into the stored first operating state in response that a difference between the first operating state and the second operating state is greater than or equal to a predetermined range; (“by acquiring the second distance from the second magnetic field sensing device to the magnetic field interference signal source, if the second distance matches the second preset distance interval, the current second working state of the second magnetic field sensing device is controlled to be working state” (72), “In practical applications, when the magnetic field interference signal is detected, the signal strength (ie, the first signal strength) of the magnetic field interference signal to the first magnetic field sensing device can be collected. For example, if the signal strength of the magnetic field interference signal is collected, it can indicate the first A high-voltage DC line where the magnetic field sensing device is located in a high-altitude area has a distance range affected by electromagnetic interference; if the signal strength of the magnetic field interference signal is not collected, it can indicate that the high-voltage DC line where the first magnetic field sensing device is not located in a high-altitude area has electromagnetic interference The affected distance range can then be controlled to maintain the normal working state of the first magnetic field induction device.” (75)), where when there is detected interference then the second sensor is in a working state and the first sensor is in a non-working state. If there is no interference, then the first sensor is in a working state. Thus, it would have been obvious to a person of ordinary skill in the art to restore the electronic unit back to a first operating state in an attempt to provide an improved system or method, as a person with ordinary skill has good reason to pursue the known options within his or her technical grasp. In turn, because the product as claimed has the properties predicted by the prior art, it would have been obvious to make the system or product to restore the electronic unit back to a first operating state, because the first operating state is comparable to when the first sensor is in a working state as no interference is detected.
maintaining, by the processor, the second operating state in response that the difference is smaller than the predetermined error range; (“In this embodiment, by acquiring the second distance from the second magnetic field sensing device to the magnetic field interference signal source, if the second distance matches the second preset distance interval, the current second working state of the second magnetic field sensing device is controlled to be working state, if the second distance does not match the second preset distance interval, control the drone to move the preset distance in the opposite direction to the magnetic field interference signal source until the adjusted second distance matches the second preset distance interval. Match and control the current second working state of the second magnetic field sensing device to be the working state, which can be alternated in time based on the magnetic field sensing device, effectively ensuring that the drone detects a normal magnetic field sensing signal.” (72)), where when there is detected interference then the second sensor is in a working state and the first sensor is in a non-working state. Thus, it would have been obvious to a person of ordinary skill in the art to maintain the electronic unit to be in a second operating state in an attempt to provide an improved system or method, as a person with ordinary skill has good reason to pursue the known options within his or her technical grasp. In turn, because the product as claimed has the properties predicted by the prior art, it would have been obvious to make the system or product to maintain the electronic unit to be in a second operating state because the second operating state is comparable to when the second sensor is in a working state and will continue to be in a working state when interference is detected.
It would have been obvious to one of ordinary skill in the art before the effective filling date of the instant application to have combined Chan’s preventing a malfunction caused by electromagnetic interference with Zhang’s operating state analysis because (“so as to ensure that the drone can detect the normal magnetic field sensing signal in real time, Improve the user's drone experience.” See Zhang (51)), which, while Zhang is regarding a drone, shows detecting interference for an autonomous vehicle.
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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Christine N Huynh whose telephone number is (571)272-9980. The examiner can normally be reached Monday - Friday 8 am - 4 pm.
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/CHRISTINE NGUYEN HUYNH/Examiner, Art Unit 3662
/ANISS CHAD/Supervisory Patent Examiner, Art Unit 3662
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