DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Status of Claims
Claims 1-7, 9-15, and 17-19 filed on 05/21/2026 are presently examined. Claims 8, 16, and 20 are cancelled. Claims 1, 9, and 17 are amended.
Response to Arguments
Regarding 112(f) interpretation, the interpretation is still invoked regardless of whether “means for” is included in the claim. There exists placeholder terms, functional language, and no structure to define the placeholder terms or how they carry out the function. The interpretation is necessary, unless Applicant amends the claims to clarify the structure. Examiner kindly reminds Applicant that 112(f) interpretation is not a rejection of the claims.
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.
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: a gaze tracking module to dynamically track gaze directions of a vehicle operator, an unmonitored region(s) detection module to identify operator monitored regions and operator unmonitored regions in claim 17, an ADAS resource allocation module to allocate an increased portion of ADAS perception resources in claim 17, an external environment perception module to track external road agents in claim 17. Each module does not have a recited structure and they are performing a function with functional language. Therefore, 112(f) is required to be invoked on the above limitations. See the Claim Interpretation section below for more information. Accordingly, the previous 35 SUC 112(f) claim interpretation is maintained.
Regarding 35 USC 103 rejections, Applicant’s arguments with respect to claims 1, 9, and 17 have been considered but are moot because the amendment required a new ground of rejection which does not rely on the reference Yamaoka applied in the prior rejection of record for the teachings or matter specifically challenged in the argument. Yamaoka has been replaced by reference Lee (US 20210122364 A1).
Moncomble fails to disclose predicting, based on an input from the vehicle operator and based on tracking the external road agents in the forward, operator unmonitored regions, whether the input is predicted to cause a collision with one of the external road agents in a forward, operator unmonitored region of the scene visible to the vehicle operator; overriding the input from the vehicle operator responsive to predicting that the input is predicted to cause the collision with one of the external road agents in a forward, operator unmonitored region of the scene visible to the vehicle operator; and controlling the ego vehicle to avoid the collision with the external road agent detected in the forward, operator unmonitored region of the scene visible to the vehicle operator.
However, Lee teaches predicting, based on an input from the vehicle operator and based on tracking the external road agents in the forward, operator unmonitored regions, whether the input is predicted to cause a collision with one of the external road agents in a forward, operator unmonitored region of the scene visible to the vehicle operator; overriding the input from the vehicle operator responsive to predicting that the input is predicted to cause the collision with one of the external road agents in a forward, operator unmonitored region of the scene visible to the vehicle operator; and controlling the ego vehicle to avoid the collision with the external road agent detected in the forward, operator unmonitored region of the scene visible to the vehicle operator ([[0035] “When the front object exists within the limited trajectory or is predicted to exist within the limited trajectory within a preset time, the collision risk determination unit 312 determines that there is a collision risk between the vehicle and the front object. When the forward gaze determination unit 306 determines that the driver is not gazing forward, the collision risk determination unit 312 determines whether a collision between the vehicle and the front object is expected within the driving trajectory. When the front object exists within the driving trajectory or is predicted to exist within the driving trajectory within a preset time, the collision risk determination unit 312 determines that there is a collision risk between the vehicle and the front object.”[0036] “The braking intervention determination unit 314 determines whether to intervene in braking for a brake system of a vehicle based on a result determined by the collision risk determination unit 312. When the collision risk determination unit 312 determines that there is a collision risk between a vehicle and a front object, the braking intervention determination unit 314 may determine to intervene in braking for the brake system.”). The driver input in Lee’s case is the current chosen trajectory and vehicle state (velocity, acceleration, etc.). Overriding the input involved automatic braking that the driver would not have done.
It would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify Moncomble with Lee’s teaching of tracking gaze directions of a driver and determine whether the driver is paying attention to a visible front object ahead of the vehicle that has the potential to collide with the vehicle, and automatically braking the vehicle when it is determined that the driver is not paying attention to the object in front of the vehicle. One would be motivated, with a reasonable expectation of success, to detect when a vehicle operator is not paying attention to a visible road object intersecting into their lane ahead of their vehicle, in order to prevent collision with the front object by autonomously braking the vehicle (Lee [0004] “the FCA technology is a technology for preventing a collision between a vehicle driving on a road and a front object.”). This would improve safety for all road agents on the road.
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:
a gaze tracking module to dynamically track gaze directions of a vehicle operator in claims 17-19. It is described in the specification [0056] as “The gaze tracking module 312 receives a data stream from the first sensor 306 and/or the second sensor 304. The data stream may include a 2D RGB image from the first sensor 306 and LIDAR data points from the second sensor 304. The data stream may include multiple frames, such as image frames of traffic data. These sensors may also include a driver facing camera to monitor the operator of the car 350.” Fig. 3: a vehicle ADAS controller (310); [0043]: The modules may be software modules running in the processor 320…hardware modules coupled to the processor 320, or some combination thereof.
an unmonitored region(s) detection module to identify operator monitored regions and operator unmonitored regions in claim 17. It is described in the specification [0007] as “unmonitored region(s) detection module to identify operator monitored regions and operator unmonitored regions in the scene based on dynamically tracking the gaze directions of the vehicle operator.” And [0056] “the first sensor 306 and/or the second sensor 304. The data stream may include a 2D RGB image from the first sensor 306 and LIDAR data points from the second sensor 304. The data stream may include multiple frames, such as image frames of traffic data. These sensors may also include a driver facing camera to monitor the operator of the car 350.” Fig. 3: a vehicle ADAS controller (310) ); [0043]: The modules may be software modules running in the processor 320…hardware modules coupled to the processor 320, or some combination thereof.
an ADAS resource allocation module to allocate an increased portion of ADAS perception resources in claim 17. It is described in the specification [0023] “Devoting fewer resources to tracking autonomous dynamic objects (ADOs) to which the driver is paying attention could mean using simpler models, drawing fewer samples from a sampling predictor (e.g., trajectory samples), and the like.” And [0024] “ADAS directs a greater share of computational resources (e.g., model complexity, number of samples, etc.) to perceptual tasks pertaining to region(s) of a scene to which a driver is not paying attention.” Fig. 3: a vehicle ADAS controller (310) ); [0043]: The modules may be software modules running in the processor 320…hardware modules coupled to the processor 320, or some combination thereof.
an external environment perception module to track external road agents in claim 17. It is described in the specification [0038] “The second sensor 304 may be a ranging sensor, such as a light detection and ranging (LIDAR) sensor or a radio detection and ranging (RADAR) sensor for capturing an external vehicle environment.” Fig. 3: a vehicle ADAS controller (310) ); [0043]: The modules may be software modules running in the processor 320…hardware modules coupled to the processor 320, or some combination thereof.
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.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1, 3-7, 9, 11-15, 17, and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Moncomble et al. (US 20230406204 A1), in view of Lee (US 20210122364 A1), hereinafter referred to as Moncomble and Lee, respectively.
Regarding claims 1, 9, and 17 Moncomble discloses A method for resource allocation of an advanced driver assistance system (ADAS), the method comprising: dynamically tracking, using a driver facing camera, gaze directions based on eyes of a vehicle operator regarding a scene surrounding an ego vehicle ([0065] “In one embodiment, the data from the sensor amongst the sensors 91, 92, 93 which are used to determine the direction of the gaze of the driver C” [also see FIG. 1]);
identifying operator monitored regions and forward, operator unmonitored regions in the scene relative to the ego vehicle based on dynamically tracking the gaze directions based on the eyes of the vehicle operator captured using the driver facing camera, wherein the forward, operator unmonitored regions comprise regions within a field of view of the vehicle operator that are classified as unmonitored based on the dynamically tracked gaze directions ([0106] “step S1 for determining a monitoring area Z that the driver C is monitoring. The method continues with a step S2 for obtaining an area Z′ not monitored by the driver C” [also see FIG. 1 and FIG. 3] Z is driver monitored region and Z’ is driver non-monitored region. [0061] “At a given moment in time, it allows a monitored area Z to be determined during the step S1.” The monitored and unmonitored regions ahead of the vehicle are all within the field of view of the operator. [0018] “the observation that the driver is focusing his/her gaze at one location will remove this location from the unmonitored area for a given period of time. This location will return to the unmonitored area at the expiration of this period of time if the driver has not returned his/her gaze to this location.”);
allocating an increased portion of ADAS perception resources to the forward, operator unmonitored regions of the scene ([0014] “activating sensors of the vehicle relating to the unmonitored area” [0015] “A step for analyzing data captured by the sensors relating to said unmonitored area in order to detect an event to come” [0020] “Activating sensors relating to an unmonitored area offers several advantages. Firstly, this activation allows it to be guaranteed that alerts fed back by the activated sensors occur in an area not being monitored by the driver. In this way, the driver will not be inconvenienced by unnecessary alerts. Another advantage is the economy of resources and of energy consumption. The sensors are only activated in order to compensate a non-monitoring by the driver” [0084] “The activation of the sensors 91, 92, 93 relating to the unmonitored area Z′ allows it to be guaranteed that a potential alert comes from an unmonitored area and will not therefore erroneously draw the attention of the driver C and also allows the power consumption of the sensors 91, 92, 93 to be minimized.”);
tracking external road agents detected in the forward operator unmonitored regions of the scene using the increased portion of ADAS perception resources ([0022] “the method will rely on predefined scenarios of road traffic events in order to determine whether events detected by the sensors in the unmonitored area effectively warrant information representative of an alert being rendered, or more simply an alert being triggered or not depending on the imminence of a categorized event. For example, an object may arrive at a road junction toward the automobile vehicle in the area not being monitored by the driver and, depending on the nature of the object and the nature of the junction, an alert could be triggered.” [see FIG. 3] sensors detect vehicles in the environment. [0090] “The existence of predefined scenarios allows the events detected during the data analysis step S3 to be categorized by verifying whether these events correspond to such scenarios. For example, the detection of a third-party vehicle approaching the vehicle V…”);
Moncomble fails to disclose predicting, based on an input from the vehicle operator and based on tracking the external road agents in the forward, operator unmonitored regions, whether the input is predicted to cause a collision with one of the external road agents in a forward, operator unmonitored region of the scene visible to the vehicle operator; overriding the input from the vehicle operator responsive to predicting that the input is predicted to cause the collision with one of the external road agents in a forward, operator unmonitored region of the scene visible to the vehicle operator; and controlling the ego vehicle to avoid the collision with the external road agent detected in the forward, operator unmonitored region of the scene visible to the vehicle operator.
However, Lee teaches predicting, based on an input from the vehicle operator and based on tracking the external road agents in the forward, operator unmonitored regions, whether the input is predicted to cause a collision with one of the external road agents in a forward, operator unmonitored region of the scene visible to the vehicle operator; overriding the input from the vehicle operator responsive to predicting that the input is predicted to cause the collision with one of the external road agents in a forward, operator unmonitored region of the scene visible to the vehicle operator; and controlling the ego vehicle to avoid the collision with the external road agent detected in the forward, operator unmonitored region of the scene visible to the vehicle operator ([[0035] “When the front object exists within the limited trajectory or is predicted to exist within the limited trajectory within a preset time, the collision risk determination unit 312 determines that there is a collision risk between the vehicle and the front object. When the forward gaze determination unit 306 determines that the driver is not gazing forward, the collision risk determination unit 312 determines whether a collision between the vehicle and the front object is expected within the driving trajectory. When the front object exists within the driving trajectory or is predicted to exist within the driving trajectory within a preset time, the collision risk determination unit 312 determines that there is a collision risk between the vehicle and the front object.”[0036] “The braking intervention determination unit 314 determines whether to intervene in braking for a brake system of a vehicle based on a result determined by the collision risk determination unit 312. When the collision risk determination unit 312 determines that there is a collision risk between a vehicle and a front object, the braking intervention determination unit 314 may determine to intervene in braking for the brake system.”).
It would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify Moncomble with Lee’s teaching of tracking gaze directions of a driver and determine whether the driver is paying attention to a visible front object ahead of the vehicle that has the potential to collide with the vehicle, and automatically braking the vehicle when it is determined that the driver is not paying attention to the object in front of the vehicle. One would be motivated, with a reasonable expectation of success, to detect when a vehicle operator is not paying attention to a visible road object intersecting into their lane ahead of their vehicle, in order to prevent collision with the front object by autonomously braking the vehicle (Lee [0004] “the FCA technology is a technology for preventing a collision between a vehicle driving on a road and a front object.”). This would improve safety for all road agents on the road.
Regarding claims 3, 11, and 19, Moncomble discloses The method of claim 1, in which dynamically tracking comprises dynamically determining the gaze direction of the vehicle operator based on sensor data captured by the driver facing camera to monitor the vehicle operator ([see FIG. 1] [0061] “sensors 91, 92, 93 oriented toward the driver C will feed back to the module 101 data relating to the face of the driver C … At a given moment in time, it allows a monitored area Z to be determined during the step S1.” [0066] “module 101 to implement the step S1 for determining a monitoring area that the driver C is monitoring, which are in general images of the face of the driver C”).
Regarding claims 4 and 12, Moncomble discloses The method of claim 1, further comprising allocating a reduced portion of the ADAS perception resources to the operator monitored regions of the scene ([0014] “activating sensors of the vehicle relating to the unmonitored area” [0015] “A step for analyzing data captured by the sensors relating to said unmonitored area in order to detect an event to come” [0020] “Activating sensors relating to an unmonitored area offers several advantages. Firstly, this activation allows it to be guaranteed that alerts fed back by the activated sensors occur in an area not being monitored by the driver. In this way, the driver will not be inconvenienced by unnecessary alerts. Another advantage is the economy of resources and of energy consumption. The sensors are only activated in order to compensate a non-monitoring by the driver” [0084] “The activation of the sensors 91, 92, 93 relating to the unmonitored area Z′ allows it to be guaranteed that a potential alert comes from an unmonitored area and will not therefore erroneously draw the attention of the driver C and also allows the power consumption of the sensors 91, 92, 93 to be minimized.” Moncomble only activates sensors in unmonitored regions.).
Regarding claims 5 and 13, Moncomble discloses The method of claim 1, in which allocating the increased portion of ADAS perception resources comprises assigning increased external-road-agent predictor resources to track external road agents in the unmonitored regions of the scene ([0022] “the method will rely on predefined scenarios of road traffic events in order to determine whether events detected by the sensors in the unmonitored area effectively warrant information representative of an alert being rendered, or more simply an alert being triggered or not depending on the imminence of a categorized event. For example, an object may arrive at a road junction toward the automobile vehicle in the area not being monitored by the driver and, depending on the nature of the object and the nature of the junction, an alert could be triggered.” [see FIG. 3] sensors detect vehicles in the environment. [0090] “The existence of predefined scenarios allows the events detected during the data analysis step S3 to be categorized by verifying whether these events correspond to such scenarios. For example, the detection of a third-party vehicle approaching the vehicle V…”).
Regarding claims 6 and 14, Moncomble fails to explicitly disclose The method of claim 5, in which the increased external-road-agent predictor resources comprises an increased model complexity and/or a number of samples ([0014] “activating sensors of the vehicle relating to the unmonitored area” [0015] “A step for analyzing data captured by the sensors relating to said unmonitored area in order to detect an event to come” [0020] “Activating sensors relating to an unmonitored area offers several advantages. Firstly, this activation allows it to be guaranteed that alerts fed back by the activated sensors occur in an area not being monitored by the driver. In this way, the driver will not be inconvenienced by unnecessary alerts. Another advantage is the economy of resources and of energy consumption. The sensors are only activated in order to compensate a non-monitoring by the driver” [0084] “The activation of the sensors 91, 92, 93 relating to the unmonitored area Z′ allows it to be guaranteed that a potential alert comes from an unmonitored area and will not therefore erroneously draw the attention of the driver C and also allows the power consumption of the sensors 91, 92, 93 to be minimized.”).
However, Lee teaches the increased external-road-agent predictor resources comprises an increased model complexity and/or a number of samples. ([0261] “in response to a determination that a potentially threatening object is present in the point cloud map, the vehicle collision avoidance apparatus may set an area corresponding to the spatial coordinates of the potentially threatening object in the image as the region of interest. In this case, the vehicle collision avoidance apparatus may increase a frame rate by a set multiple when the camera photographs the region of interest so as to increase the number of times of identifying the type of the potentially threatening object in the received image of the region of interest”).
It would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify Moncomble with Lee’s teaching of automatic braking for external road agents. One would be motivated, with a reasonable expectation of success, to provide the increasing of the rate of data capture (frame rate) when detecting a potential threat taught by Lee in addition to the activating of sensors only for unmonitored regions taught by Moncomble in order to increase the accuracy of recognition of the object ([0261] “increasing the accuracy of recognizing the type of potentially threatening object above a set reliability.”).
Regarding claims 7 and 15, Moncomble discloses The method of claim 1, in which tracking external road agents comprises tracking autonomous dynamic objects (ADOs) identified in the operator unmonitored regions of the scene using the increased portion of ADAS perception resources ([see FIG. 3] vehicle V detects vehicle D in the crossroads, which may be an autonomous vehicle, by activating sensors in the unmonitored region where vehicle D is present. [0116] “the step S1 has determined a monitoring area Z that the driver C of the vehicle V is monitoring. The step S2 has subsequently obtained an area Z′ not monitored by the driver C of the vehicle, and, consequently, sensors 91, 92, 93, not shown in FIG. 3, relating to the unmonitored area Z′ have been activated … The step S3 for analyzing data captured by the sensors 91, 92, 93 relating to the unmonitored area Z′ will thus allow an event to come to be detected, namely the arrival at the junction of the vehicle D shown in FIG. 3, the arrow indicating its direction of travel.” [0117] “in the situation in FIG. 3, the vehicle D could be connected to the communications network N, and could receive information transmitted by the method from the vehicle V′ which would indicate a loss of attention on the part of the driver of the vehicle V′. This transmitted information could then have a direct action on the driving, for example a decrease in the speed, if the vehicle D has capacities for autonomous driving”).
Claims 2, 10, and 18 are rejected under 35 U.S.C. 103 as being unpatentable over Moncomble in view of Lee, further in view of Arar et al. (US 20220121867 A1), hereafter referred to as Arar.
Regarding claims 2, 10, and 18 Moncomble fails to explicitly disclose The method of claim 1, in which dynamically tracking further comprises visualizing gaze-direction behavior of the vehicle operator using an operator attention heatmap, indicating where and how often the vehicle operator is focusing their gaze.
However, Arar teaches dynamically tracking further comprises visualizing gaze-direction behavior of the vehicle operator using an operator attention heatmap, indicating where and how often the vehicle operator is focusing their gaze ([0028] “as illustrated in FIG. 2E, the gaze information of the occupant may be tracked over some period of time and used to generate a heat map 210 (e.g., with darker regions corresponding to more frequent gaze locations or directions than regions that are lighter or have less dense patterns of points) corresponding to gaze locations and directions of the occupant over time (e.g., over a thirty second period, one minute, three minutes, five minutes, etc.)”).
It would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify Moncomble with Arar’s teaching of a heat map. One would be motivated, with a reasonable expectation of success, to include the driver attention heat map from Arar in order to improve determining of whether the driver has attention toward a vehicle or object on the road or not ([0048] “For example, where a driver sees a vehicle (e.g., is determined to have seen based on a comparison of the estimated field of view of the driver and the location of the vehicle) some distance in front of the ego-vehicle 500, but is determined to have a high cognitive load and/or low attentiveness (e.g., based on the heat map, fixations, etc.), the state may include aware (e.g., of the vehicle) but inattentive (e.g., potentially has not processed the presence of the vehicle)”).
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MARK R HEIM whose telephone number is (571)270-0120. The examiner can normally be reached M-F 9-6 EST.
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/M.R.H./Examiner, Art Unit 3668
/Fadey S. Jabr/Supervisory Patent Examiner, Art Unit 3668
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