DETAILED ACTION
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim status
Claims 1-20 are currently pending for examination.
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.
Claims 1 and 11 are rejected under 35 U.S.C. 103 as being unpatentable over Lee et al. (Lee; US 2023/0386227) in view of Ishiguro (US 2024/0400053).
For claim 1, Lee discloses a method performed by an apparatus of a vehicle [E.g. 0032-0035, 0005], the method comprising:
obtaining, via a camera of the vehicle, image data representing one or more photographic images of a driver of the vehicle [E.g. 0011: the plurality of sensors comprising an imaging sensor and the sensor data comprising images or 3D point representations of a vehicle occupant. The plurality of sensors may include a physiological sensor. The plurality of sensors may include the imaging sensor and/or the physiological sensor. The data processing system can extract a plurality of time-series features of the vehicle occupant from the images or 3D point representations, 0046: sensors 106 can include an imaging sensor 106A (e.g., IR or visual spectrum camera, millimeter wave radar, LiDAR, etc.) configured to generate 3D point representation data indicative of various features of a vehicle occupant, such as facial features (e.g., facial droop), body posture, and the like. The sensor may generate a point cloud having a discrete set of data points in space that represent a 3D portion or aspect of the vehicle occupant. In an alternative embodiment, an imaging sensor may generate a 2D image from which features of a vehicle occupant may be extracted. In the example embodiments, 3D point representation data is used to extract features of the vehicle occupant, but it is intended that images may be used instead of or in addition to the 3D point representation data. The one or more imaging sensors 106A can be communicatively coupled to the processing/aggregation circuit 110, to convey the data thereto. The one or more imaging sensors 106A can be positioned to capture 3D point representation data associated with one or more vehicle occupants or portions thereof. For example, a first imaging sensor 106A can be configured to capture 3D point representation data comprising facial landscaping points (e.g., a tip of a nose, chin, eye, and so forth). In some embodiments, the one or more imaging sensors 106A can include various positions or lensing (e.g., fisheye lenses) configured to generate 3D point representation data of a body position. For example, a user may slouch in their seat, be slumped over a steering wheel, holding a steering wheel, or may have limp arms (e.g., as in the case of an unresponsive occupant), 0044];
determining, based on performing a facial expression analysis on the image data, an emotion classification of the driver [E.g. 0007: Vehicle occupants can experience anomalies such as altered mental or physical statuses responsive to an acute or chronic medical issue. The various mental statuses can be associated with one or more conditions. For example, a condition such as eye closure can correspond to migraine headaches, or a stroke of various severities. According to the systems and methods of the present disclosure, the various conditions may be associated with different actions. For example, an action can include presenting an indication from a user interface indicating that to a user should remain alert, an indication that the user should halt the vehicle, or an activation of an autonomy system of the vehicle to halt the vehicle. Various sensors can detect features of a user such as a facial or body landscape, physiological parameters of a vehicle occupant, or vehicle parameters relating to vehicle control of the vehicle occupant. Based on the features such as the features of a facial landscape, the physiological parameters, or the vehicle parameters, the systems and methods herein can determine a condition of a vehicle occupant, and take an action response to the condition, 0030: a data processing system can detect an altered mental or physical status of a vehicle occupant corresponding to a medical anomaly such as a medical emergency, and a gradation thereof, such as a low, medium, or high classification. An altered mental status may depend upon or correlate to a physical status. For example, an altered mental status indicating unconsciousness can correlate to a heart attack; an altered mental status of aphasia or neglect syndrome can correlate to a stroke. The data processing system can monitor data points disposed over a facial landscape of a vehicle occupant…, 0046; Figs. 5-6];
determining a value associated with a heart rate of the driver, wherein the value associated with the heart rate corresponds to the image data [E.g. 0011: data processing system can receive sensor data from a plurality of sensors associated with a vehicle, the plurality of sensors comprising an imaging sensor and the sensor data comprising images or 3D point representations of a vehicle occupant. The plurality of sensors may include a physiological sensor. The plurality of sensors may include the imaging sensor and/or the physiological sensor. The data processing system can extract a plurality of time-series features of the vehicle occupant from the images or 3D point representations. The data processing system can execute a machine learning model using the plurality of time-series features of the vehicle occupant to determine at least one condition of the vehicle occupant inferred from the plurality of time-series features, 0044: the sensors 106 may include sensors configured to collect data regarding physiological characteristics of the vehicle occupant. In an example embodiment, the sensors 106 may include both an imaging sensor to detect features of the body of the vehicle occupant and sensors to detect physiological characteristics. It is intended, however, that some configurations may include only one type of sensor, 0047: physiological sensor 106B can include millimeter wave radar detectors configured to transmit and receive a signal reflected from an occupant, the signal being indicative of a heart rate, breath rate, chest movement, heart rate variability, other vital signs, or the like. The physiological sensor 106B can include thermal imaging sensors or other IR sensors 106, such as sensors 106 configured to measure skin temperature.)];
determining based on the emotion classification, and based on the heart rate, presence of an emergency situation [E.g. 0005-0007, 0030-0031, 0037];
outputting, via a user interface of the vehicle and based on the presence of the emergency situation, a first request for a user response from the driver [E.g. 0007: the various conditions may be associated with different actions. For example, an action can include presenting an indication from a user interface indicating that to a user should remain alert, an indication that the user should halt the vehicle, or an activation of an autonomy system of the vehicle to halt the vehicle, Figs. 10-11 and 0031] ; and
transmitting, to an emergency dispatch service provider and based on receiving no user response from the driver within a predetermined time period after the first request is output, an emergency rescue request [E.g. 0033: the system 100 can communicate over the network 150. For example, the vehicle 102 can communicate with one or more server systems 152 and one or more remote providers 154 over the network 150, 0036: system 100 can include or interface with one or more remote providers 154. A remote provider 154 may refer to or include an emergency service provider, a primary medical care provider for the user, an emergency contact associated with a vehicle 102 or user, a data provider associated with a health condition of a user, or the like. The remote provider can include a person who is a non-occupant of the vehicle 102 or a computing device associated therewith; Fig. 10 and 0039].
Lee fails to expressly disclose determining, based on the image data having one or more pre-determined image characteristics, that the driver satisfies an age threshold and determining, based on the driver satisfying the age threshold presence of an emergency situation.
However, as shown by Ishiguro, it was well known in the art of vehicles to include determining, based on image data having one or more pre-determined image characteristics, that the driver satisfies an age threshold and determining, based on the driver satisfying the age threshold presence of an emergency situation [E.g. 0028, 0057, 0061-0064, 0008, 0013].
It would have been obvious to one of ordinary skill in the art of vehicles before the
effective filling date of the claimed invention modify Lee with the teaching of Ishiguro so that the age of the driver is taking into consideration when determining an emergency situation because elderly driver are more vulnerable and thereby enhance the overall safety on the road, also it is merely combing prior art elements according to known methods to yield predicable results.
For claim 11, is interrupted and rejected as discussed with respect to claim 1.
Claims 2-4, 6, 12-14 and 16 are rejected under 35 U.S.C. 103 as being unpatentable over Lee in view of Ishiguro and further in view of Official Notice.
For claim 2, Lee discloses outputting, via the user interface of the vehicle and based on presence of a second emergency situation [E.g. 0005, 0007, 0030], a second request for a user response from the driver [Figs.10-11, 0007, 0030-0031].
Lee fails to expressly disclose outputting, via the user interface and based on receiving a user response to the second request, a third request for an indication of consent by the driver to transferring a right of control of the vehicle; and transferring, based on receiving the indication of consent, the right of control of the vehicle to an entity different from the driver.
However, examiner takes official notice that outputting, via the user interface and based on receiving a user response to second request, a third request for an indication of consent by the driver to transferring a right of control of the vehicle; and transferring, based on receiving the indication of consent, the right of control of the vehicle to an entity different from the driver is well known in the art of autonomous vehicle and would have been obvious to one of ordinary skill in the art in order to ensure that the driver authorized the transfer of the vehicle from manual driving to autonomous driving and thereby enhance the overall driver experiences.
For claim 3, Lee discloses wherein the entity comprises a remote server that is configured to control the vehicle remotely [E.g. 0032-0033, 0036].
For claim 4, Lee discloses wherein the entity comprises a computing device located in the vehicle and configured to control the vehicle to perform autonomous driving [E.g. 0007, 0052, 0058].
For claim 6, Lee in view of Ishiguro fails to expressly disclose wherein the one or more pre-determined image characteristics are associated with at least one of hair of the driver or a wrinkle of the driver, and wherein the determining that the driver satisfies the age threshold comprises: estimating an age of the driver based on the image data by using a first model trained to identify presence of gray hair and presence of wrinkles.
However, examiner takes official notice that one or more pre-determined image characteristics are associated with at least one of hair of the driver or a wrinkle of the driver, and wherein the determining that the driver satisfies the age threshold comprises: estimating an age of the driver based on the image data by using a first model trained to identify presence of gray hair and presence of wrinkles is well known in the art of a user age determination and would have been obvious to one of ordinary skill in the art in order to ensure an accurate age determination process and thereby improve the overall age determination system.
For claim 12, is interpreted and rejected as discussed with respect to claim 2.
For claim 13, is interpreted and rejected as discussed with respect to claim 3.
For claim 14, is interpreted and rejected as discussed with respect to claim 4.
For claim 16, is interpreted and rejected as discussed with respect to claim 6.
Allowable Subject Matter
Claims 5, 7-10, 15 and 17-20 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Conclusion
8. The prior art made of record and not relied upon is considered pertinent to Applicant's disclosure: see PTO-892 Notice of Reference Cited.
9. Any inquiry concerning this communication or earlier communications from the examiner should be directed to MOHAMED BARAKAT whose telephone number is (571)270-3696. The examiner can normally be reached on 9:00am-5:00PM.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Davetta Goins can be reached on (571) 272-2957. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/MOHAMED BARAKAT/
Primary Examiner, Art Unit 2689
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