DETAILED ACTION
Response to Amendments
This office action regarding application number 18/330,577, filed June 7, 2023, is in response to the applicants arguments and amendments filed 2/26/2026. Claims 1, 13, and 22 have been amended. Claims 1-5, 9, 11-14, 18, and 20-24 are currently pending and are addressed below.
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 .
Response to Arguments
The applicants arguments and amendments to the application have not overcome some of the objections and rejections previously set forth in the Final action mailed November 26, 2025. Applicants amendments to claims 1 and 13 have not been deemed sufficient to overcome the previous 35 USC 103 rejections through the inclusion of “determine the current state of the vehicle as a flooded state based on a comparison between a first height from a ground surface of a road to the vehicle in a normal state and a second height form a water surface to the vehicle in a state of flooding wherein the first height is derived from a first contour of the vehicle generated in advance in the normal state and wherein the second height is derived from a second contour of the vehicle generated based on the image data,” the examiner finds that these newly amended limitations are taught by the Sharp reference as discussed below. Therefore the rejections are maintained with changes to reflect amendments. Additionally the applicants arguments have been fully considered but are not fully persuasive for the reasons seen below.
On pages 7-9 the applicant argues “In response to Applicants' last Amendment, the Examiner acknowledged that Gage and Pohl do not teach or suggest the claimed features. However, the Examiner is under the impression that Sharp discloses a technique for determining whether a vehicle is submerged by comparing a reference image with a current image to determine whether a specific body feature or exterior portion of the vehicle is located below a water surface. Sharp merely determines whether certain features of the vehicle exterior are positioned below the water surface by comparing a reference image and a current image. However, Sharp does not teach to calculate a height difference based on a normal state of the vehicle and a state of flooding. In other words, Sharp teaches a qualitative determination based on visibility or positional relationship of specific features, whereas claim 1 includes a quantitative determination in which a reference height and a height in a state of flooding are respectively determined from the overall exterior contour of the vehicle, and a flooded (submerged) state is determined based on the difference between these heights. Thus, the technical evaluation and the decision structure are fundamentally different.”, the examiner respectfully disagrees.
MPEP 2142-2144 discusses the requirements for a case of obviousness using 35 USC 103 and provides examples of such cases. MPEP 2111 discusses Broadest Reasonable Interpretation and the interpretation of claims.
As discussed in the rejections below Sharp teaches determine the current state of the vehicle as a flooded state (Paragraph [0006], “The present invention is directed to gathering more precise pieces of information about the instantaneous fording situation of a vehicle”); based on a comparison between a first height from a ground surface of a road to the vehicle in a normal state and a second height form a water surface to the vehicle in a state of flooding (Paragraph [0013], “In an example embodiment, the driver assistance system moreover includes at least one camera designed to detect at least one specific feature of the body of the vehicle,” here the camera is determining specific body feature to determine if the body feature is below the surface of the water by comparing a current image to a previous image) (Paragraph [0014], “respective assigned fording limits being stored in the memory unit for a multitude of specific positions on the vehicle. The processing unit is designed to determine for each of the specific positions whether the assigned fording limit is above or below the water surface plane,“ each of the known body features are associated with a normal height/fording limit) (Paragraph [0016], “the processing unit is preferably designed to determine the instantaneous distance of the assigned fording limit from the instantaneous water surface plane for each of the specific positions,” the system then determines the distance from the fording limit to the water surface plane, thereby comparing the first height/fording limit to a second height/water surface).
Therefore the combination of Gage, Pohl and Sharp teaches a quantitative determination in which a reference height and a height in a state of flooding are respectively determined from the overall exterior contour of the vehicle, and a flooded (submerged) state is determined based on the difference between these heights as disclosed by the claim. The rejection under 35 USC 103 is maintained.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are: “communication device” and “image acquisition device” in claims 1 and 2, and “output device” in claim 11 and 12.
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Regarding “communication device” in claims 1 and 2, the specification recites the structure of “According to an embodiment, the communication device 110 may use wireless communication, for example, at least one of wireless-fidelity (Wi-Fi), wireless broadcast (WiBro), long term evolution (LTE), long term evolution-advanced (LTE-A), a fifth generation (5G) wireless system, mm-wave or 60 GHz wireless communication, a wireless universal serial bus (USB), code division multiple access (CDMA), wideband CDMA (WCDMA), a universal mobile telecommunications system (UMTS), or a global system for mobile communication (GSM).” in at least paragraph [0044].
Regarding “image acquisition device” in claim 1, the specification recites the structure of “The image acquisition device 130 may be implemented with one or more cameras provided in the vehicle to obtain image data around the vehicle. According to an embodiment, the image acquisition device 130 may include at least one of a surround view camera, a digital side mirror camera, or a combination thereof. The surround view camera may include at least one of a front view camera, a left view camera, a right view camera, a rear view camera, or a combination thereof. The digital side mirror camera may obtain image data from the side and rear of the vehicle. A detailed description refers to FIG. 2.” in at least paragraph [0047].
Regarding “output device” in claim 11 and 12, the specification recites the structure of “The output device 150 may be implemented as a display device, a sound output device, or the like. Herein, the display device may include an output device for outputting the image data obtained by the image acquisition device 130, a display of the navigation 140, a head-up display (HUD), a cluster, or the like. The output device 150 may be implemented as at least one of a liquid crystal display (LCD), a thin film transistor-LCD (TFT-LCD), an organic light-emitting diode (OLED) display, a flexible display, a three-dimensional (3D) display, or an electronic-ink (e-ink) display,” in at least paragraph [0051].
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 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.
Claims 1-5, 11-14, 20, and 22-23 is/are rejected under 35 U.S.C. 103 as being unpatentable over Gage (US-20180063487) in view of Pohl (US-20200142419) and further in view of Sharp (US-20200039434).
Regarding claim 1, Gage teaches an apparatus for controlling a vehicle, the apparatus comprising (Paragraph [0039], “Based on the locally provided weather information, the computing device 18 may initiate a weather notification that can be sent to the vehicle user using, for example, the communications module 16.”)
a communication device (Paragraph [0016], "The communications module 16 may be provided, at least in part, for communication with the external weather information providing system, generally referred to as element 20, through a communications network 22, such as the internet or a dedicated network.")
a sensor (Paragraph [0028], "The second sensor 76 may be any device, for example, that can be used by the computing device 18 in verifying weather information. In some embodiments, the second sensor 76 may include RADAR, LiDAR, precipitation detectors, wind detectors, light detectors and/or the like. As described above, any sensor or combinations of sensors may be used to detect and monitor a weather event and used to verify weather information.")
an image acquisition device (Paragraph [0027], "A camera 72 may be coupled to the communication path 55 such that the communication line 38 communicatively couples the camera 72 to other modules of the vehicle 12. The camera 72 may be any device having an array of sensing devices capable of detecting radiation in an ultraviolet wavelength band, a visible light wavelength band, or an infrared wavelength band.")
and a controller configured to (Paragraph [0019], "The computing devices 18 can be any type of vehicle-installed (ECU), handheld, desktop, or other form of computing device, or can be composed of multiple computing devices. One or more processors 52 in the computing device 18 and elsewhere can be a single device, or multiple devices, capable of manipulating or processing information.")
determine a possibility of flooding of the vehicle based on weather data obtained from the communication device and precipitation data obtained from the sensor (Paragraph [0033], "At step 106, the remotely provided current weather information is provided to the computing device 18. The computing device 18 may include logic within machine readable instructions that determines an initial weather significance level at step 108. The initial weather significance level may be based on one or more factors and may depend on the type of weather event, such as snowfall rates/accumulation, rainfall rates/accumulation, wind speed, lightning frequency, weather watches and warnings (e.g., tornado, thunderstorm, flooding, etc.), hail presence, ice accumulation and the like.") (Paragraph [0028], “any sensor or combinations of sensors may be used to detect and monitor a weather event and used to verify weather information,” here the system can use a combination of the received current weather information and the sensor data in order to determine a weather significance level for a weather situation such as a possibility of flooding)
the weather data related to weather in an area of the vehicle (Paragraph [0032], "Once the communications module 16 is connected to the communications network 22, the external weather information providing system 20 may send weather information provided by the weather information server 26 to the communications module 16 at step 104 using any suitable weather information providing source available, for example, over the internet. The weather information may be in the form of weather forecast data, weather radar data and current weather information, as examples.")
in response to a determination that it is possible for the vehicle to be flooded determine a current state of the vehicle based on image data obtained from the image acquisition device (Paragraph [0033], "At step 110, the computing device 18 determines if the initial weather significance level is above a predetermined initial weather significance level threshold (e.g., at least about 1 inch of snowfall accumulation, at least about 30 mph wind speed, a tornado watch for the location, etc.). If the computing device 18 determines that the initial weather significance level is below the predetermined initial weather significance level threshold, the computing device continues to monitor the remotely provided current weather information. If the computing device 18 determines that the initial weather significance level is above the predetermined weather significance level threshold, the computing device 18 instructs the ECU 32 (FIG. 1) to initiate the vehicle video system 36 and camera 72 at step 112," here in response to a determination that a weather significance level/possibility of flooding exceeding a threshold the system will activate a camera system in order to determine a current state of the vehicle).
However, Gage does not explicitly teach after determining the current state of the vehicle, store a change in a state of flooding based on the weather data, the precipitation data, or the image data, and predict a future flooding situation based on the stored change in the state of flooding, in response to a determination that it is not possible for a user to move the vehicle within a predetermined time based on a user feedback, enter an emergency vehicle travel mode and control the vehicle to autonomously travel along a travel route of the vehicle to a safe place.
Pohl teaches a vehicle relocation system which determines a weather risk to a vehicle using a plurality of sensor including
after determining the current state of the vehicle, store a change in the state of flooding based on the weather data, the precipitation data, or the image data (Paragraph [0024], “According to various aspects, information (e.g., hazard identification information, obstacle condition information, etc.) may be handled (e.g., processed, analyzed, stored, etc.) in any suitable form, e.g., data may represent the information and may be handled via a computing system. The hazard condition may be used herein with the meaning of any detectable characteristic of the hazard itself and/or associated with the hazard,” here the system can handle/store data representing determined information such as the hazard condition/current state of the vehicle which was determined using sensor and image data)
and predict a future flooding situation based on the stored change in the state of flooding (Paragraph [0033], “The one or more processors 104 may be configured to utilize one or more algorithms, one or more artificial intelligences, and/or one or more databases, tables, or other information sources stored in one or more memories 106.”) (Paragraph [0047], “using one or more artificial intelligences to determine risk of one or more weather conditions and one or more identified hazards based on previous data of at least previous weather conditions, previous identified risks, and damages resulting therefrom; or otherwise.”)
and in response to a determination that it is not possible for a user to move the vehicle within a predetermined time based on a user feedback (Paragraph [0086], “Should this configuration be used, the user may be given a period of time in which to respond. In the event that the response is not received within the period of time, the one or more processors may be configured to select a preferred option and carry that option out autonomous. The user can decide what to do. If the user does not react within a certain time, an automatic option might be chosen,” here the system determined that the vehicle needs to be moved in response to a user not replying to a message within the predetermined time)
enter an emergency vehicle travel mode and control the vehicle to autonomously travel along a travel route of the vehicle to a safe place (Paragraph [0076], “In this scenario, the vehicle may be configured to wait a predetermined period of time before relocating. As a nonlimiting example, the vehicle may be configured to wait five minutes after informing the vehicle owner or regular driver of the intention to relocate before the vehicle proceeds with relocation,” here the system is configured to enter a travel mode and autonomously control the vehicle to travel to a safe place in a situation in which no feedback is received or approval is received from a driver) (Paragraph [0086], “Should this configuration be used, the user may be given a period of time in which to respond. In the event that the response is not received within the period of time, the one or more processors may be configured to select a preferred option and carry that option out autonomous. The user can decide what to do. If the user does not react within a certain time, an automatic option might be chosen.”).
Gage and Pohl are analogous art as they are both generally related to systems for determining a weather condition of a vehicle.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the instant application to include after determining the current state of the vehicle, store a change in a state of flooding based on the weather data, the precipitation data, or the image data, and predict a future flooding situation based on the stored change in the state of flooding, in response to a determination that it is not possible for a user to move the vehicle within a predetermined time based on a user feedback, enter an emergency vehicle travel mode and control the vehicle to autonomously travel along a travel route of the vehicle to a safe place of Pohl in the system for determining a local weather condition of Gage with a reasonable expectation of success in order to prevent damage to the vehicle by determining a future risk of damage and taking action to prevent that damage (Paragraph [0026], “In one or more aspects, a driving operation (such as, for example, any type of safety operation, e.g., relocation) may be implemented via one or more on-board components of a vehicle. The one or more on-board components of the vehicle may include, for example, a one or more cameras (e.g., at least a front camera), a computer system, etc., in order to detect hazards and to trigger an hazard avoidance function (e.g., relocation) to avoid damage to the vehicle. The one or more on-board components of the vehicle may include, for example, a one or more cameras, a computer system, etc., in order to detect a hazard and to relocate.”).
However the combination does not explicitly teach determine the current state of the vehicle as a flooded state based on a comparison between a first height from a ground surface of a road to the vehicle in a normal state and a second height form a water surface to the vehicle in a state of flooding wherein the first height is derived from a first contour of the vehicle generated in advance in the normal state and wherein the second height is derived from a second contour of the vehicle generated based on the image data.
Sharp teaches methods and systems for determining a wading situation for a vehicle using a plurality of sensors including
determine the current state of the vehicle as a flooded state (Paragraph [0006], “The present invention is directed to gathering more precise pieces of information about the instantaneous fording situation of a vehicle”)
based on a comparison between a first height from a ground surface of a road to the vehicle in a normal state and a second height form a water surface to the vehicle in a state of flooding (Paragraph [0013], “In an example embodiment, the driver assistance system moreover includes at least one camera designed to detect at least one specific feature of the body of the vehicle,” here the camera is determining specific body feature to determine if the body feature is below the surface of the water by comparing a current image to a previous image) (Paragraph [0014], “respective assigned fording limits being stored in the memory unit for a multitude of specific positions on the vehicle. The processing unit is designed to determine for each of the specific positions whether the assigned fording limit is above or below the water surface plane,“ each of the known body features are associated with a normal height/fording limit) (Paragraph [0016], “the processing unit is preferably designed to determine the instantaneous distance of the assigned fording limit from the instantaneous water surface plane for each of the specific positions,” the system then determines the distance from the fording limit to the water surface plane, thereby comparing the first height/fording limit to a second height/water surface)
wherein the first height is derived from a first contour of the vehicle generated in advance in the normal state and wherein the second height is derived from a second contour of the vehicle generated based on the image data (Paragraph [0029], “the driver assistance system can moreover include at least one camera, which is designed to detect at least one specific feature of the body of the vehicle, it being possible to identify by an evaluation of the detected feature whether a portion of the body including the feature is situated below the water surface. For this purpose, for example, it is possible to detect using methods of digital image processing and/or a comparison to reference images whether the feature is visible or whether, for example, it is visible in a distorted manner since it is already partially immersed in the water. Since the position of the feature thus detected on the vehicle is known, it is thus possible to establish whether this position of the vehicle is already situated in or under water, and the accuracy of the determination of the water surface plane relative to the vehicle can thereby be improved,” here the system can use image data to determine the current state of the vehicle by comparing a body feature/contour in a current/first image to a known reference/second image which is generated in advance).
Gage, Pohl, and Sharp are analogous art as they are both generally related to systems for determining a weather condition of a vehicle.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the instant application to include determine the current state of the vehicle as a flooded state based on a comparison between a first height from a ground surface of a road to the vehicle in a normal state and a second height form a water surface to the vehicle in a state of flooding wherein the first height is derived from a first contour of the vehicle generated in advance in the normal state and wherein the second height is derived from a second contour of the vehicle generated based on the image data of Sharp in the system for determining a local weather condition of Gage and Pohl with a reasonable expectation of success in order to improve the accuracy of the determination of the water depth (Paragraph [0029], “Since the position of the feature thus detected on the vehicle is known, it is thus possible to establish whether this position of the vehicle is already situated in or under water, and the accuracy of the determination of the water surface plane relative to the vehicle can thereby be improved.”).
Regarding claim 2, the combination of Gage, Pohl, and Sharp teaches the system as discussed above in claim 1, Gage further teaches wherein the communication device is configured to receive the weather data and the local image data in the area where the vehicle is located from a server (Paragraph [0016], “For connecting with the communications network 22, the communications module 16 includes a communications control unit 24 that can send and receive information to and from a weather information server 26 of the external weather information providing system 20.”) (Paragraph [0032], “The weather information may be in the form of weather forecast data, weather radar data and current weather information, as examples. Such weather information provided from a remote (i.e., not local) source to the communications module 16 may be referred to herein as “remotely provided weather information.”)
and receive user request data from a user terminal (Paragraph [0040], “As one illustrative example, the vehicle user may receive a weather notification from the vehicle 12 of snowfall at night. The vehicle user may select a vehicle action based on the weather notification to occur at some later time in the morning. For example, the vehicle user may select operation of the HVAC unit of the vehicle 12 to generate heat at a particular time to melt snow accumulating on the vehicle 12.”).
Regarding claim 3, the combination of Gage, Pohl, and Sharp teaches the system as discussed above in claim 1, however Gage does not explicitly teach wherein after the current state of the vehicle is determined, the controller is configured to measure a degree of flooding at time intervals based on the image data to determine a change in flooding and to predict the future flooding situation based on the change in flooding.
Pohl further teaches wherein after the current state of the vehicle is determined, the controller is configured to measure a degree of flooding at time intervals based on the image data to determine the change in the state of flooding and to predict the future flooding situation based on the change in the state of flooding (Paragraph [0054], “The system described herein may be configured to perform a risk calculation and/or evaluate the need for relocation at any frequency desired or upon any triggering event. Most or all of the evaluations performed by the vehicle are likely to be performed while the vehicle is parked and the ignition is not running. As such, the operations disclosed herein are likely to rely heavily or entirely upon battery reserves. Accordingly, it may be desirable to configure the vehicle (e.g. the one or more processors performing the principles and methods disclosed herein) to evaluate risk of damage from weather and/or possible spaces for relocation on a more frequent or less frequent basis, depending on the desired result and the available of reserve power. According to one aspect of the disclosure, the one or more processors may be configured to perform the risk evaluation and/or relocation evaluation at a predetermined interval (e.g. every five minutes, every ten minutes, every twenty minutes, every half-hour, etc.) without limitation.,” here the system can perform a risk evaluation by evaluating the severity of the weather a certain intervals of time using the image data of the vehicle) (Paragraph [0053], “FIG. 6 depicts a method of vehicle relocation including receiving first sensor data representing a current or predicted weather condition 602; receiving second sensor data representing at least a position or a vicinity of a vehicle 604; determining from at least the first sensor data and the second sensor data a risk of damage to the vehicle 606; and if the determined risk is outside of a target range, sending an instruction for the vehicle to travel to an alternate location 608,” here the system can perform the risk evaluation at intervals and use the risk evaluation to determine if the risk has exceeded the target range and the vehicle should be moved based on if the weather situation has changed or is predicted to change).
Gage and Pohl are analogous art as they are both generally related to systems for determining a weather condition of a vehicle.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the instant application to include wherein after the current state of the vehicle is determined, the controller is configured to measure a degree of flooding at intervals of a certain time based on the image data to determine a change in flooding and to predict the future flooding situation based on the change in flooding of Pohl in the system for determining a local weather condition of Gage with a reasonable expectation of success in order to prevent damage to the vehicle by determining a future risk of damage and taking action to prevent that damage (Paragraph [0026], “In one or more aspects, a driving operation (such as, for example, any type of safety operation, e.g., relocation) may be implemented via one or more on-board components of a vehicle. The one or more on-board components of the vehicle may include, for example, a one or more cameras (e.g., at least a front camera), a computer system, etc., in order to detect hazards and to trigger an hazard avoidance function (e.g., relocation) to avoid damage to the vehicle. The one or more on-board components of the vehicle may include, for example, a one or more cameras, a computer system, etc., in order to detect a hazard and to relocate.”).
Regarding claim 4, the combination of Gage, Pohl, and Sharp teaches the system as discussed above in claim 1, Gage further teaches wherein the sensor comprises a rain sensor (Paragraph [0028], “The second sensor 76 may be any device, for example, that can be used by the computing device 18 in verifying weather information. In some embodiments, the second sensor 76 may include RADAR, LiDAR, precipitation detectors, wind detectors, light detectors and/or the like. As described above, any sensor or combinations of sensors may be used to detect and monitor a weather event and used to verify weather information,” here the system includes a precipitation/rain sensor).
Regarding claim 5, the combination of Gage, Pohl, and Sharp teaches the system as discussed above in claim 1, however Gage does not explicitly teach wherein the controller is configured to utilize artificial intelligence based on previously obtained weather data, previously obtained precipitation data, or previously obtained image data and to determine the possibility of flooding of the vehicle based on a result of the artificial intelligence.
Pohl teaches wherein the controller is configured to utilize artificial intelligence based on previously obtained weather data, previously obtained precipitation data, or previously obtained image data and to determine the possibility of flooding of the vehicle based on a result of the artificial intelligence (Paragraph [0033], “The one or more processors 104 may be configured to utilize one or more algorithms, one or more artificial intelligences, and/or one or more databases, tables, or other information sources stored in one or more memories 106.”).
Gage and Pohl are analogous art as they are both generally related to systems for determining a weather condition of a vehicle.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the instant application to include wherein the controller is configured to utilize artificial intelligence based on previously obtained weather data, previously obtained precipitation data, or previously obtained image data and determine the possibility of flooding of the vehicle based on a result of the artificial intelligence of Pohl in the system for determining a local weather condition of Gage with a reasonable expectation of success in order to prevent damage to the vehicle by determining a future risk of damage and taking action to prevent that damage (Paragraph [0026], “In one or more aspects, a driving operation (such as, for example, any type of safety operation, e.g., relocation) may be implemented via one or more on-board components of a vehicle. The one or more on-board components of the vehicle may include, for example, a one or more cameras (e.g., at least a front camera), a computer system, etc., in order to detect hazards and to trigger an hazard avoidance function (e.g., relocation) to avoid damage to the vehicle. The one or more on-board components of the vehicle may include, for example, a one or more cameras, a computer system, etc., in order to detect a hazard and to relocate.”).
Regarding claim 11, the combination of Gage, Pohl, and Sharp teaches the system as discussed above in claim 1, Gage further teaches the controller is configured to control an output device to output a message providing a notification of the current state of the vehicle (Paragraph [0039], “Based on the locally provided weather information, the computing device 18 may initiate a weather notification that can be sent to the vehicle user using, for example, the communications module 16. The weather notification may be sent to the vehicle user at step 148 using any suitable process, such as a text message, email, cellular call, voicemail, as a notification through an application, etc. The weather notification can include information indicative of type of weather event, severity of weather event, recommended vehicle action steps, current vehicle status (e.g., windows down, engine ON, retractable top lowered, etc.). The vehicle user may then select a vehicle action based on the weather notification at step 150 using the user computing device 42 (FIG. 1),” here the system can send a notification to a user including a current state of the vehicle indicating a type and severity of the weather event such as flooding).
Pohl further teaches the controller is configured to control an output device to output a message providing a notification of the current state of the vehicle and the future flooding situation (Paragraph [0076], “According to another aspect of the disclosure, the vehicle may seek permission from the owner or regular driver for the relocation. That is, in the event that the vehicle determines a risk of damage to the vehicle outside of the range of acceptable risk, the vehicle may notify the owner or regular driver. According to one aspect of the disclosure, the vehicle may seek affirmative approval from the owner or regular driver to relocate.”) (Paragraph [0075], “By way of example, the user notification may be delivered via a cellular text message, and Internet-based text message, a notification on an application of a user device, a voice call, a voicemail message, or otherwise.”).
However the combination does not explicitly teach sending a notification regarding a current state of the vehicle while the vehicle is traveling.
Sharp teaches wherein, in case the vehicle is traveling the controller is configured to control an output device to output a message providing a notification of the current state of the vehicle (Paragraph [0017], “Furthermore, the display unit is preferably designed to display, in particular in real time, a perspective or three-dimensional representation of the vehicle, together with a perspective or three-dimensional representation of the instantaneous water surface plane. The warning can take place, for example, in that a representation of the vehicle is displayed on the display unit, and the affected specific position is highlighted in color and/or by another visual marking. As an alternative or in addition, an acoustic and/or a visual warning can be output, for example a voice message that names the affected specific position,” here the system can output a notification providing a current state of a vehicle in relation to a water level).
Gage, Pohl, and Sharp are analogous art as they are both generally related to systems for determining a weather condition of a vehicle.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the instant application to include wherein, in a state in which the vehicle is traveling the controller is configured to control an output device to output a message providing a notification of the current state of the vehicle of Sharp in the system for determining a local weather condition of Gage and Pohl with a reasonable expectation of success in order to improve the accuracy of the determination of the water depth and communicate that information to a user (Paragraph [0029], “Since the position of the feature thus detected on the vehicle is known, it is thus possible to establish whether this position of the vehicle is already situated in or under water, and the accuracy of the determination of the water surface plane relative to the vehicle can thereby be improved.”).
Regarding claim 12, the combination of Gage, Pohl, and Sharp teaches the system as discussed above in claim 1, Pohl further teaches wherein, in case the vehicle is traveling, the controller is configured to determine whether or not it is possible for the vehicle to travel to an original destination (Paragraph [0084], “According to another aspect of the disclosure, it may be anticipated that a particular location for parking may become quickly crowded, and an alternative may be sought. For example, in the event that many vehicles simultaneously or concurrently seek parking, a nearby parking garage may quickly become crowded and potentially unusable. Rather than wasting time (particularly in the inclement weather), the one or more vehicles may be configured to abandon an effort to reach the parking garage and simply seek shelter elsewhere,” here the system when it is determined that it is unable to reach shelter at the original destination will determine an alternative destination/route)
and in response to a determination that it is not possible for the vehicle to travel to the original destination, control an output device to output a distance where it is possible for the vehicle to travel from a current location of the vehicle (Paragraph [0050], “If a safer location is identified, the vehicle may optionally request clearance or approval for moving to the safer location 410. That is, depending on the ownership or the usage model of the vehicle, the owner or the user or the fleet manager may be required to approve (or otherwise not disapprove) a request to relocate.”) (Paragraph [0077], “According to another aspect of the disclosure, the vehicle may be configured with a maximum distance for relocation. That is, the vehicle may be configured to seek alternative locations only within a predetermined distance from the current location. As nonlimiting examples, the vehicle may be configured to seek alternative locations no more than 20 meters from the vehicle, no more than 50 meters from the vehicle, no more than 100 meters from the vehicle, etc.”) (Paragraph [0086], “According to another aspect, one or more user applications (apps) may be used to inform the user of a plurality of options for addressing a probable weather scenario. For each of the plurality of options, the one or more processors, via the app may be configured to provide the user with an estimated cost of each option. This may include, for example, the cost of fuel to arrive at the desired option, any parking fees associated with the desired option, the time required to utilize the desired option, expected damage to occur when reaching the desired option, etc,” here the system has determined that the vehicle needs to relocate in order to prevent damage and the vehicle is unable to reach shelter at a first location the vehicle can inform a user of a plurality of options within a distance of travel of the current location of the vehicle).
Gage and Pohl are analogous art as they are both generally related to systems for determining a weather condition of a vehicle.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the instant application to include wherein, in a state in which the vehicle is traveling, the controller is configured to determine whether or not it is possible for the vehicle to travel to an original destination and in response to a determination that it is not possible for the vehicle to travel to the destination, control an output device to output a distance where it is possible for the vehicle to travel from a current location of the vehicle of Pohl in the system for determining a local weather condition of Gage with a reasonable expectation of success in order to prevent damage to the vehicle by determining a future risk of damage and taking action to prevent that damage (Paragraph [0026], “In one or more aspects, a driving operation (such as, for example, any type of safety operation, e.g., relocation) may be implemented via one or more on-board components of a vehicle. The one or more on-board components of the vehicle may include, for example, a one or more cameras (e.g., at least a front camera), a computer system, etc., in order to detect hazards and to trigger an hazard avoidance function (e.g., relocation) to avoid damage to the vehicle. The one or more on-board components of the vehicle may include, for example, a one or more cameras, a computer system, etc., in order to detect a hazard and to relocate.”).
Regarding claim 13, Gage teaches a method for controlling a vehicle, the method comprising (Paragraph [0039], “Based on the locally provided weather information, the computing device 18 may initiate a weather notification that can be sent to the vehicle user using, for example, the communications module 16.”)
wirelessly receiving weather data related to an area where a vehicle is located (Paragraph [0016], "The communications module 16 may be provided, at least in part, for communication with the external weather information providing system, generally referred to as element 20, through a communications network 22, such as the internet or a dedicated network.")
sensing precipitation data using a sensor of the vehicle (Paragraph [0028], "The second sensor 76 may be any device, for example, that can be used by the computing device 18 in verifying weather information. In some embodiments, the second sensor 76 may include RADAR, LiDAR, precipitation detectors, wind detectors, light detectors and/or the like. As described above, any sensor or combinations of sensors may be used to detect and monitor a weather event and used to verify weather information.")
determining a possibility of flooding of the vehicle based on the received weather data and the sensed precipitation data (Paragraph [0033], "At step 106, the remotely provided current weather information is provided to the computing device 18. The computing device 18 may include logic within machine readable instructions that determines an initial weather significance level at step 108. The initial weather significance level may be based on one or more factors and may depend on the type of weather event, such as snowfall rates/accumulation, rainfall rates/accumulation, wind speed, lightning frequency, weather watches and warnings (e.g., tornado, thunderstorm, flooding, etc.), hail presence, ice accumulation and the like.") (Paragraph [0028], “any sensor or combinations of sensors may be used to detect and monitor a weather event and used to verify weather information,” here the system can use a combination of the received current weather information and the sensor data in order to determine a weather significance level for a weather situation such as a possibility of flooding)
in response to a determination that it is possible for the vehicle to be flooded, determining a current state of the vehicle based on image data around the vehicle, wherein the image data is obtained by an image acquisition device of the vehicle (Paragraph [0033], "At step 110, the computing device 18 determines if the initial weather significance level is above a predetermined initial weather significance level threshold (e.g., at least about 1 inch of snowfall accumulation, at least about 30 mph wind speed, a tornado watch for the location, etc.). If the computing device 18 determines that the initial weather significance level is below the predetermined initial weather significance level threshold, the computing device continues to monitor the remotely provided current weather information. If the computing device 18 determines that the initial weather significance level is above the predetermined weather significance level threshold, the computing device 18 instructs the ECU 32 (FIG. 1) to initiate the vehicle video system 36 and camera 72 at step 112," here in response to a determination that a weather significance level/possibility of flooding exceeding a threshold the system will activate a camera system in order to determine a current state of the vehicle).
However, Gage does not explicitly teach predict a future flooding situation based on the weather data, the precipitation data, or the image data.
Pohl teaches a vehicle relocation system which determines a weather risk to a vehicle using a plurality of sensor including
after determining the current state of the vehicle, measuring the state of flooding at time intervals based on the image data to determine a change in flooding (Paragraph [0054], “The system described herein may be configured to perform a risk calculation and/or evaluate the need for relocation at any frequency desired or upon any triggering event. Most or all of the evaluations performed by the vehicle are likely to be performed while the vehicle is parked and the ignition is not running. As such, the operations disclosed herein are likely to rely heavily or entirely upon battery reserves. Accordingly, it may be desirable to configure the vehicle (e.g. the one or more processors performing the principles and methods disclosed herein) to evaluate risk of damage from weather and/or possible spaces for relocation on a more frequent or less frequent basis, depending on the desired result and the available of reserve power. According to one aspect of the disclosure, the one or more processors may be configured to perform the risk evaluation and/or relocation evaluation at a predetermined interval (e.g. every five minutes, every ten minutes, every twenty minutes, every half-hour, etc.) without limitation.,” here the system can perform a risk evaluation by evaluating the severity of the weather a certain intervals of time using the image data of the vehicle) (Paragraph [0053], “FIG. 6 depicts a method of vehicle relocation including receiving first sensor data representing a current or predicted weather condition 602; receiving second sensor data representing at least a position or a vicinity of a vehicle 604; determining from at least the first sensor data and the second sensor data a risk of damage to the vehicle 606; and if the determined risk is outside of a target range, sending an instruction for the vehicle to travel to an alternate location 608,” here the system can perform the risk evaluation at intervals and use the risk evaluation to determine if the risk has exceeded the target range and the vehicle should be moved based on if the weather situation has changed or is predicted to change)
predicting a future flooding situation based on the weather data, the precipitation data, or the image data and the change in the state of flooding (Paragraph [0033], “The one or more additional sensors 108 may include one or more sensors that are capable of sensing current conditions associated with weather (temperature, air pressure, humidity, wind speed, etc.) and to deliver this detected information to the one or more processors, which may be configured to predict one or more weather conditions,” here the processor can use any of a plurality of data pieces in order to predict a weather condition which includes flooding)
and in response to a determination that it is not possible for a user to move the vehicle within a predetermined time based on a user feedback (Paragraph [0086], “Should this configuration be used, the user may be given a period of time in which to respond. In the event that the response is not received within the period of time, the one or more processors may be configured to select a preferred option and carry that option out autonomous. The user can decide what to do. If the user does not react within a certain time, an automatic option might be chosen,” here the system determined that the vehicle needs to be moved in response to a user not replying to a message within the predetermined time)
enter an emergency vehicle travel mode and control the vehicle to autonomously travel along a travel route of the vehicle to a safe place (Paragraph [0076], “In this scenario, the vehicle may be configured to wait a predetermined period of time before relocating. As a nonlimiting example, the vehicle may be configured to wait five minutes after informing the vehicle owner or regular driver of the intention to relocate before the vehicle proceeds with relocation,” here the system is configured to enter a travel mode and autonomously control the vehicle to travel to a safe place in a situation in which no feedback is received or approval is received from a driver) (Paragraph [0086], “Should this configuration be used, the user may be given a period of time in which to respond. In the event that the response is not received within the period of time, the one or more processors may be configured to select a preferred option and carry that option out autonomous. The user can decide what to do. If the user does not react within a certain time, an automatic option might be chosen.”).
Gage and Pohl are analogous art as they are both generally related to systems for determining a weather condition of a vehicle.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the instant application to include predict a future flooding situation based on the weather data, the precipitation data, or the image data and in response to a determination that it is not possible for a user to move the vehicle within a predetermined time based on a user feedback, enter an emergency vehicle travel mode and control the vehicle to autonomously travel along a travel route of the vehicle to a safe place of Pohl in the system for determining a local weather condition of Gage with a reasonable expectation of success in order to prevent damage to the vehicle by determining a future risk of damage and taking action to prevent that damage (Paragraph [0026], “In one or more aspects, a driving operation (such as, for example, any type of safety operation, e.g., relocation) may be implemented via one or more on-board components of a vehicle. The one or more on-board components of the vehicle may include, for example, a one or more cameras (e.g., at least a front camera), a computer system, etc., in order to detect hazards and to trigger an hazard avoidance function (e.g., relocation) to avoid damage to the vehicle. The one or more on-board components of the vehicle may include, for example, a one or more cameras, a computer system, etc., in order to detect a hazard and to relocate.”).
However the combination does not explicitly teach determining the current state of the vehicle as a flooded state based on a comparison between a first height from a ground surface of a road to the vehicle in a normal state and a second height form a water surface to the vehicle in a state of flooding, wherein the first height is derived from a first contour of the vehicle generated in advance in the normal state and wherein the second height is derived from a second contour of the vehicle generated based on the image data.
Sharp teaches methods and systems for determining a wading situation for a vehicle using a plurality of sensors including
determining the current state of the vehicle as a flooded state (Paragraph [0006], “The present invention is directed to gathering more precise pieces of information about the instantaneous fording situation of a vehicle”)
based on a comparison between a first height from a ground surface of a road to the vehicle in a normal state and a second height form a water surface to the vehicle in a state of flooding (Paragraph [0013], “In an example embodiment, the driver assistance system moreover includes at least one camera designed to detect at least one specific feature of the body of the vehicle,” here the camera is determining specific body feature to determine if the body feature is below the surface of the water by comparing a current image to a previous image) (Paragraph [0014], “respective assigned fording limits being stored in the memory unit for a multitude of specific positions on the vehicle. The processing unit is designed to determine for each of the specific positions whether the assigned fording limit is above or below the water surface plane,“ each of the known body features are associated with a normal height/fording limit) (Paragraph [0016], “the processing unit is preferably designed to determine the instantaneous distance of the assigned fording limit from the instantaneous water surface plane for each of the specific positions,” the system then determines the distance from the fording limit to the water surface plane, thereby comparing the first height/fording limit to a second height/water surface)
wherein the first height is derived from a first contour of the vehicle generated in advance in the normal state and wherein the second height is derived from a second contour of the vehicle generated based on the image data (Paragraph [0029], “the driver assistance system can moreover include at least one camera, which is designed to detect at least one specific feature of the body of the vehicle, it being possible to identify by an evaluation of the detected feature whether a portion of the body including the feature is situated below the water surface. For this purpose, for example, it is possible to detect using methods of digital image processing and/or a comparison to reference images whether the feature is visible or whether, for example, it is visible in a distorted manner since it is already partially immersed in the water. Since the position of the feature thus detected on the vehicle is known, it is thus possible to establish whether this position of the vehicle is already situated in or under water, and the accuracy of the determination of the water surface plane relative to the vehicle can thereby be improved,” here the system can use image data to determine the current state of the vehicle by comparing a body feature/contour in a current/first image to a known reference/second image which is generated in advance).
Gage, Pohl, and Sharp are analogous art as they are both generally related to systems for determining a weather condition of a vehicle.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the instant application to include determining the current state of the vehicle as a flooded state based on a comparison between a first height from a ground surface of a road to the vehicle in a normal state and a second height form a water surface to the vehicle in a state of flooding, wherein the first height is derived from a first contour of the vehicle generated in advance in the normal state and wherein the second height is derived from a second contour of the vehicle generated based on the image data of Sharp in the system for determining a local weather condition of Gage and Pohl with a reasonable expectation of success in order to improve the accuracy of the determination of the water depth (Paragraph [0029], “Since the position of the feature thus detected on the vehicle is known, it is thus possible to establish whether this position of the vehicle is already situated in or under water, and the accuracy of the determination of the water surface plane relative to the vehicle can thereby be improved.”).
Regarding claim 14, claim 14 is similar in scope to claim 5 and therefore is rejected under similar rationale.
Regarding claim 20, claim 20 is similar in scope to claim 12 and therefore is rejected under similar rationale.
Regarding claim 22, the combination of Gage, Pohl and Sharp teaches the method as discussed above in claim 13, however Gage does not explicitly teach receiving information about an elevated land from a user terminal or server generating a travel route for moving the vehicle to the elevated land and controlling the vehicle to perform autonomous driving along the travel route when entering the emergency vehicle travel mode.
Pohl further teaches receiving information about an elevated land from a user terminal or server (Paragraph [0058], “Similarly, map data indicating that the vehicle is in a valley or a point of depression may correspond with an increased risk of damage to the vehicle resulting from flooding. That is, certain aspects of map data may be correlated to weather hazards, and these correlations may assist the one or more processors in evaluating risk”) (Paragraph [0065], “Conversely, if flooding is expected and the vehicle is parked under a roof, but the parking spaces located in a area of low elevation (e.g. a depression), a high risk of damage to the vehicle may be ascertained.”) (Paragraph [0069], “For relocation, the vehicle may seek a relocation space that is associated with a lower risk of damage to the vehicle. The nature of the relocation space depends on the type or mechanism of damage to the vehicle that is anticipated. For example, in the case of hail, covered spaces may be preferred. However, in the case of high winds, covered spaces may potentially be disfavored,” here the map data received from the server includes elevation data and the system can use the data to determine an elevated risk associated with a low elevation area, the system can determine a relocation space that is associated with a lower risk which in the case of flooding would be a higher elevation)
generating the travel route for moving the vehicle to the elevated land and controlling the vehicle to perform autonomous driving along the travel route when entering the emergency vehicle travel mode (Paragraph [0076], “In this scenario, the vehicle may be configured to wait a predetermined period of time before relocating. As a nonlimiting example, the vehicle may be configured to wait five minutes after informing the vehicle owner or regular driver of the intention to relocate before the vehicle proceeds with relocation,” here the system is configured to enter a travel mode and autonomously control the vehicle to travel to a safe place in a situation in which no feedback is received or approval is received from a driver).
Gage and Pohl are analogous art as they are both generally related to systems for determining a weather condition of a vehicle.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the instant application to include receiving information about an elevated land from a user terminal or server generating a travel route for moving the vehicle to the elevated land and controlling the vehicle to perform autonomous driving along the travel route when entering the emergency vehicle travel mode of Pohl in the system for determining a local weather condition of Gage with a reasonable expectation of success in order to prevent damage to the vehicle by determining a future risk of damage and taking action to prevent that damage (Paragraph [0026], “In one or more aspects, a driving operation (such as, for example, any type of safety operation, e.g., relocation) may be implemented via one or more on-board components of a vehicle. The one or more on-board components of the vehicle may include, for example, a one or more cameras (e.g., at least a front camera), a computer system, etc., in order to detect hazards and to trigger an hazard avoidance function (e.g., relocation) to avoid damage to the vehicle. The one or more on-board components of the vehicle may include, for example, a one or more cameras, a computer system, etc., in order to detect a hazard and to relocate.”).
Regarding claim 23, claim 23 is similar in scope to claim 4 and therefore is rejected under similar rationale.
Claims 9 and 18 is/are rejected under 35 U.S.C. 103 as being unpatentable over Gage (US-20180063487) in view of Pohl (US-20200142419) further in view of Sharp (US-20200039434) and further in view of Sasaki (US-20210027627).
Regarding claim 9, the combination of Gage, Pohl, and Sharp teaches the system as discussed above in claim 1, Gage further teaches transmit a message for providing a notification of the current state of the vehicle the future flooding situation (Paragraph [0034], “Such weather information provided from a local source to the communications module 16 may be referred to herein as “locally provided weather information.” Based on the locally provided weather information, the communications module 16 may instruct one or more of the vehicle ECUs to initiate a vehicle function and/or some other function may be performed, such as provide a weather notification to the vehicle user.”) (Paragraph [0039], “Based on the locally provided weather information, the computing device 18 may initiate a weather notification that can be sent to the vehicle user using, for example, the communications module 16. The weather notification may be sent to the vehicle user at step 148 using any suitable process, such as a text message, email, cellular call, voicemail, as a notification through an application, etc. The weather notification can include information indicative of type of weather event, severity of weather event, recommended vehicle action steps, current vehicle status (e.g., windows down, engine ON, retractable top lowered, etc.). The vehicle user may then select a vehicle action based on the weather notification at step 150 using the user computing device 42 (FIG. 1),” here the system can send a notification to a user including a current state of the vehicle indicating a type and severity of the weather event such as flooding).
However Gage does not explicitly teach wherein, in a case the vehicle is parked, the controller is configured to transmit the image data to a user terminal in real time and a notification of vehicle travelable time to the user terminal
Pohl further teaches transmit a message for providing a notification of the current state of the vehicle and the future flooding situation (Paragraph [0076], “According to another aspect of the disclosure, the vehicle may seek permission from the owner or regular driver for the relocation. That is, in the event that the vehicle determines a risk of damage to the vehicle outside of the range of acceptable risk, the vehicle may notify the owner or regular driver. According to one aspect of the disclosure, the vehicle may seek affirmative approval from the owner or regular driver to relocate.”)
and a vehicle travelable time to the user terminal (Paragraph [0076], “As a nonlimiting example, the vehicle may be configured to wait five minutes after informing the vehicle owner or regular driver of the intention to relocate before the vehicle proceeds with relocation.”) (Paragraph [0086], “Should this configuration be used, the user may be given a period of time in which to respond. In the event that the response is not received within the period of time, the one or more processors may be configured to select a preferred option and carry that option out autonomous. The user can decide what to do. If the user does not react within a certain time, an automatic option might be chosen,” here the system is sending a notification to a user terminal with a period of time in which to respond before the vehicle autonomously takes action such as traveling to a new location).
Gage and Pohl are analogous art as they are both generally related to systems for determining a weather condition of a vehicle.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the instant application to include transmit a message for providing a notification of the current state of the vehicle the future flooding situation and a vehicle travelable time to the user terminal of Pohl in the system for determining a local weather condition of Gage with a reasonable expectation of success in order to prevent damage to the vehicle by determining a future risk of damage and taking action to prevent that damage (Paragraph [0026], “In one or more aspects, a driving operation (such as, for example, any type of safety operation, e.g., relocation) may be implemented via one or more on-board components of a vehicle. The one or more on-board components of the vehicle may include, for example, a one or more cameras (e.g., at least a front camera), a computer system, etc., in order to detect hazards and to trigger an hazard avoidance function (e.g., relocation) to avoid damage to the vehicle. The one or more on-board components of the vehicle may include, for example, a one or more cameras, a computer system, etc., in order to detect a hazard and to relocate.”).
However the combination does not explicitly teach wherein, in a case in which the vehicle is parked, the controller is configured to transmit the image data to a user terminal in real time.
Sasaki teaches a vehicle surveillance system for a parked vehicle using image data including
wherein, in a case the vehicle is parked, the controller is configured to transmit the image data to a user terminal in real time (Paragraph [0042], “The vehicle surveillance system 1 shown in FIG. 1 includes a vehicle 10, a user terminal 20, and a server 30. The vehicle surveillance system 1 is a system that shoots surroundings of the vehicle 10 or an inside of the vehicle 10 by using, for example, a camera and causes the user terminal 20 to display a shot image.”) (Paragraph [0082], “When the user makes an input to the effect that the user wants to view an image shot at the vehicle 10 into the user terminal 20, the user terminal 20 generates a viewing request (processing in S11). The viewing request may include information related to a time. Note that the user can also specify a past time. The viewing request is transmitted from the user terminal 20 to the server 30 (processing in S12). When the viewing request is received from the user terminal 20, the server 30 selects an image to be viewed by the user (processing in S13). The server 30 selects from the image information DB 313 an image associated with a vehicle 10 corresponding to a user ID and a time included in the viewing request. When selection of the image is completed, the image information is transmitted to the user terminal 20 (processing in S14), and at the user terminal 20, the image is output to the output section 25 (processing in S15).”).
Gage, Pohl, Sharp and Sasaki are analogous art as they are both generally related to systems for determining condition around a vehicle.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the instant application to include wherein, in a case in which the vehicle is parked, the controller is configured to transmit the image data to a user terminal in real time of Sasaki in the system for determining a local weather condition of Gage, Pohl, and Sharp with a reasonable expectation of success in order to improve the communication rate of a parked vehicle and allow a user to view the state of the vehicle in real time (Paragraph [0004], “In such a case, the image is transmitted from the vehicle through radio communication, but it may take some time to transmit the image, depending on a communication environment, so that it can be difficult to check the image in real time. Accordingly, an object of the disclosure is to further enhance a communication rate of a parked vehicle.”).
Regarding claim 18, claim 18 is similar in scope to claim 9 and therefore is rejected under similar rationale
Claims 21 and 24 is/are rejected under 35 U.S.C. 103 as being unpatentable over Gage (US-20180063487) in view of Pohl (US-20200142419) further in view of Sharp (US-20200039434) and further in view of Salter (US-20210213976).
Regarding claim 21, the combination of Gage, Pohl, and Sharp teaches the system as discussed above in claim 13, however Gage does not explicitly teach in response to a determination that the user is able to move the vehicle within the predetermined time based on the user feedback generating the travel route of the vehicle to the safe place, and providing a notification of the travel route to the user.
Pohl further teaches in response to a determination that the user is able to move the vehicle within the predetermined time based on the user feedback (Paragraph [0076], “According to another aspect of the disclosure, the vehicle may seek permission from the owner or regular driver for the relocation. That is, in the event that the vehicle determines a risk of damage to the vehicle outside of the range of acceptable risk, the vehicle may notify the owner or regular driver. According to one aspect of the disclosure, the vehicle may seek affirmative approval from the owner or regular driver to relocate. According to another aspect of the disclosure, the vehicle may simply inform the owner or regular driver of the intention to relocate, and assuming no express denial of permission to relocate is received by the vehicle from the owner or regular user, the vehicle may proceed with relocation. In this scenario, the vehicle may be configured to wait a predetermined period of time before relocating. As a nonlimiting example, the vehicle may be configured to wait five minutes after informing the vehicle owner or regular driver of the intention to relocate before the vehicle proceeds with relocation.”).
Gage and Pohl are analogous art as they are both generally related to systems for determining a weather condition of a vehicle.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the instant application to include in response to a determination that the user is able to move the vehicle within the predetermined time based on the user feedback of Pohl in the system for determining a local weather condition of Gage with a reasonable expectation of success in order to prevent damage to the vehicle by determining a future risk of damage and taking action to prevent that damage (Paragraph [0026], “In one or more aspects, a driving operation (such as, for example, any type of safety operation, e.g., relocation) may be implemented via one or more on-board components of a vehicle. The one or more on-board components of the vehicle may include, for example, a one or more cameras (e.g., at least a front camera), a computer system, etc., in order to detect hazards and to trigger an hazard avoidance function (e.g., relocation) to avoid damage to the vehicle. The one or more on-board components of the vehicle may include, for example, a one or more cameras, a computer system, etc., in order to detect a hazard and to relocate.”).
However the combination does not explicitly teach generating a travel route to a safe place for a user to relocate the vehicle.
Salter teaches systems and methods to determine water levels using a capacitive sensor system, and perform mitigating actions include
generating the travel route of the vehicle to the safe place, and providing a notification of the travel route to the user (Paragraph [0057], “In one example, the AV controller 1100 may send a message to the fleet control server 1170 via network 1160, and receive a response message from fleet control server 1170 via the network 1160. The message may indicate a route recommendation for moving vehicle 1103 to a location with an operable water depth”) (Paragraph [0062], “The interface device 1125 may allow a passenger and/or operator of the vehicle 1103 to receive information associated with any mitigating actions.”).
Gage, Pohl, Sharp and Salter are analogous art as they are both generally related to systems for determining a weather condition of a vehicle.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the instant application to include in response to a determination that the user is able to move the vehicle within the predetermined time based on the user feedback generating the travel route of the vehicle to the safe place, and providing a notification of the travel route to the user of Salter in the system for determining a local weather condition of Gage, Pohl and Sharp with a reasonable expectation of success in order to prevent a vehicle from becoming stranded and unable to move (Paragraph [0008], “As a result, the autonomous vehicle may attempt to travel through water that is too deep, causing the autonomous vehicle to become stranded amidst flood waters.”).
Regarding claim 24, claim 24 is similar in scope to claim 21 and therefore is rejected under similar rationale.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Zhang (US-20210188269) teaches the use of weather information and road condition information associated with a future vehicle location and suggesting controls to the vehicle to mitigate impacts. Urmson (US-9110196) teaches detecting weather based road conditions using laser data, precipitation sensors and camera information to determine the presence of water on the roadway. Ghannam (US-10255782) teaches control module also is to identify a flooding event when the humidity measurement exceeds the humidity level by a predetermined threshold and record the flooding event with a remote server via the communication module. Averbuch (US-11691646) teaches may identify an active flood event for the flood prone location based on the flood confidence and cause a flood event warning to be activated in an instance in which the active flood event is identified.
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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to CHRISTOPHER FEES whose telephone number is (303)297-4343. The examiner can normally be reached Monday-Thursday 7:30 - 5:30 MT.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Aniss Chad can be reached on (571) 270-3832. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/CHRISTOPHER GEORGE FEES/Primary Examiner, Art Unit 3662
Prosecution Insights