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 .
DETAILED ACTION
This is the initial office action based on the application filed on May 9th, 2024, which claims 1-20 are presented for examination.
Examiner Notes
Examiner cites particular columns and line numbers in the references as applied to the claims below for the convenience of the applicant. Although the specified citations are representative of the teachings in the art and are applied to the specific limitations within the individual claim, other passages and figures may apply as well. It is respectfully requested that, in preparing responses, the applicant fully consider the references in entirety as potentially teaching all or part of the claimed invention, as well as the context of the passage as taught by the prior art or disclosed by the examiner.
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.
Status of Claims
Claims 1-20 are pending in the application and have been examined below, of which, claims 1, 12, and 17 are presented in independent form.
Effective Date
Effective date that has been considered for this application is November 9th, 2022.
Internet E-mail
A written authorization by Applicant is required for the Examiner to respond via
internet e-mail to any Internet correspondence which contains information subject to the
confidentiality requirement as set forth in 35 U3.0. 122, such as proposed Examiner’s
Amendments or interview agenda items (MPEP 502.03; See Internet Usage Policy, 64
PR 33056 (June 21, 1999)). To authorize e-mail communications from the Examiner
(e.g. proposed Examiner’s Amendments), the Applicant must place a written
authorization in the record. Applicant may authorize electronic and email communication
by the Examiner via PTO Automated Interview Request web service. To schedule an
interview, applicant is encouraged to use the USPTO Automated Interview Request
(AER) at http://www.uspto.gov/interviewpractice.
Information Disclosure Statement
The information disclosure statement filed on May 9th, 2024 complies with the provisions of 37 CFR 1.97, 1.98. The complied IDS has been placed in the application file and the information referred to therein has been considered as to the merits.
Specification
Applicant is reminded of the proper content of an abstract of the disclosure. The abstract should be in narrative form and generally limited to a single paragraph within the range of 50 to 150 words in length. See MPEP § 608.01(b) for guidelines for the preparation of patent abstracts.
Drawings
The drawings are objected to as failing to comply with 37 CFR 1.84(p)(5) because they do not include the following reference sign(s) mentioned in the description: an interface 22 (See paragraph [0098] of the Publication).
Corrected drawing sheets in compliance with 37 CFR 1.121(d) are required in reply to the Office action to avoid abandonment of the application. Any amended replacement drawing sheet should include all of the figures appearing on the immediate prior version of the sheet, even if only one figure is being amended. Each drawing sheet submitted after the filing date of an application must be labeled in the top margin as either “Replacement Sheet” or “New Sheet” pursuant to 37 CFR 1.121(d). If the changes are not accepted by the examiner, the applicant will be notified and informed of any required corrective action in the next Office action. The objection to the drawings will not be held in abeyance.
Claim Objections
Claims 1-20 are objected to because of the following informalities:
Claims 1, 12, and 17 recite the limitation “wherein that at least one virtual vehicle” in lines 4, 8, and 5, respectively. The limitation should be -- wherein [[that]] the at least one virtual vehicle --.
Claims 1 and 12 recite the limitation “a drive assistance system” in lines 5 and 9, respectively. The limitation should be -- [[a]] the drive assistance system --.
Claims 1 and 17 recite the limitation “motion data of a real living being” in lines 6 and 7, respectively. The limitation should be -- motion data of [[a]] the real living being --.
Claim 1 recites the limitation “a pose of the at least one part of an anatomical structure” in lines 8-9. There is insufficient antecedent basis for this limitation in the claim. In the interest of compact prosecution, the examiner subsequently interprets this limitation as reading -- a pose of [[the]] at least one part of an anatomical structure --.
Claim 1 recites the limitation “a reaction of the driver” in lines 11-12. There is insufficient antecedent basis for this limitation in the claim. In the interest of compact prosecution, the examiner subsequently interprets this limitation as reading -- a reaction of [[the]] a drive --”.
Claim 4 recites the limitation “wherein creating the test event” in line 1. The limitation should be -- wherein [[creating]] generating the test event --.
Claims 7 and 20 recite the limitation “changing at least one part of the anatomical structure” in lines 2-3 and 3, respectively. The limitation should be -- changing the at least one part of the anatomical structure --.
Claim 11 recites the limitation “a first vehicle at the time the motion data is captured” in line 5. The limitation should be -- a first vehicle at [[the]] time the motion data is captured --.
Claim 12 recites the limitation “a pose of the at least one part of an anatomical structure” in lines 8-9. There is insufficient antecedent basis for this limitation in the claim. In the interest of compact prosecution, the examiner subsequently interprets this limitation as reading -- a pose of [[the]] at least one part of an anatomical structure --.
Claim 17 recites the limitation “a software module, stored in the memory” in line 9. There is insufficient antecedent basis for this limitation in the claim. In the interest of compact prosecution, the examiner subsequently interprets this limitation as reading -- “a software module, stored in [[the]] a memory --.
Claim 20 recites the limitation “storing the new motion in association with a subset of the virtual simulation data” in line 5. The limitation should be -- storing the new motion data in association with [[a]] the subset of the virtual simulation data --.
Claims 2-11, 13-16, and 18-20: are dependent on claims 1, 7, and 17, respectively, but not cure the deficiencies of those claims. Accordingly, they are objected for the same reasons.
Appropriate correction is required.
Claim Rejections - 35 USC § 112
The following is a quotation of the second paragraph of 35 U.S.C. 112:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claim 15 is rejected under 35 U.S.C. 112, second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which applicant regards as the invention.
Claim 15 recites the limitation “wherein the first vehicle is either a real vehicle or the virtual representation of the vehicle” in lines 1-2. It is unclear if the vehicle refers to the first vehicle or real vehicle. In the interest of compact prosecution, the examiner subsequently interprets this limitation as reading -- wherein the first vehicle is either a real vehicle or [[the]] a virtual representation of the first vehicle --.
Claim Rejections - 35 U.S.C § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1-20 are rejected under 35 U.S.C. § 103 as being unpatentable over Hartmann et al. (GB 256340 – hereinafter, Hartmann – IDS filed 05/09/2024) in view of Yang (Pub. No.: US 2017/0372131 – hereinafter, Yang).
Regarding claim 1:
Hartmann discloses a method for creating a test event for a driver assistance system, the method including:
generating a virtual test environment that includes at least one virtual living being and at least one virtual vehicle (“Virtual testing of interaction between vehicles and road users (Pedestrians) comprising virtual reality (VR) environment, based on a real world environment or new virtual environment, with vehicles and road users (pedestrians)” (See Abstract). Also, see page 9, 2nd paragraph), wherein the virtual living being is a virtual representation of a real living being (“in a third step the measurement of the actions of the test person in a motion capture system in a fourth step the processing for sending the information of gesture and actions to the visualization processing unit for visualization of the movement and to the vehicle” (See claim 1). Also, see page 9, 2nd paragraph) and wherein that at least one virtual vehicle is a virtual representation of a vehicle with a driver assistance system (“in a first step the computation of real world or new virtual environments with vehicles and road users (e.g. pedestrians)” (See claim 1));
capturing, with a motion capture system, motion data of a real living being interacting with a set of physical controls manipulatable to operate one or more parts of a first vehicle (“For Block D: Single testable object (e.g. vehicle in Autonomous Mode as simulation software (SIL), model- (MIL), vehicle-(VIL) or hardware- (HIL) in the loop) and Block E: Person with virtual (mixed-) reality devices with perception-, motion- and position- capture system devices and (mixed-) virtual reality glasses. The persons can be involved in real traffic situations or virtual reality cabs a stimuli of the perception (e.g. visualization of a scene of the virtual environment) is assumed” (See page 9, 3rd paragraph)), [[the motion data describing a time history of]] a pose of the at least one part of an anatomical structure of the real living being (“A visual pedestrian detection is described with extraction of a partial image and processing unit with prediction of human behavior” (See page 4, 3rd paragraph));
recording the captured motion data (“The movement, gestures and actions of the user may be captured by the MoCap system” (See Abstract)); and
generating a test event for the driver assistance system based on a reaction of the driver that is captured within the motion data (“testing the interaction process between pedestrians, virtual environments, and other road users and the vehicles.” (See claim 9)).
But Hartmann does not explicitly teach:
the motion data describing a time history of a pose of the at least one part of an anatomical structure of the real living being.
However, Yang discloses:
the motion data describing a time history of a pose of the at least one part of an anatomical structure of the real living being (FIG. 3 and associated text, such as, “The first collecting unit 110 may acquire the motion state of the eyes of a user, forming the eye motion data, and record the first acquisition time. The extracting unit 120 may extract position data of the user's eyeballs from the eye motion data. The second collecting unit 130 may capture the user behavior activity data using images, and record the second acquisition time. Further, the determining unit 140 may, based on the first acquisition time and the second acquisition time, determine a correspondence relationship between the position data of the user's eyeballs and the user behavior activity data. The correspondence relationship can be further used to determine the current user behavior activity based on the motion state of the user's eyes.” (See paras [0090] – [0091])).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Yang into the teachings of Hartmann because that would have using an eye tracking device to collect, over a long time period (e.g., a few hours), the eye position coordinates to obtain time discrete data of the user's gazing points, blinking, and sweeping motions; and encoding such eye motion data to better collect, evaluate, and analyze human behavior as suggested by Yang (See para [0123]).
Regarding claim 2:
The rejection of claim 1 is incorporated, Hartmann further discloses wherein the test event includes the motion data [[describing the time history of the pose]] and a first virtual stimulus of the virtual test environment (“In a fourth step, the information of measured gesture and actions of test persons reacting on the various traffic scenarios is transmitted to the visualization processing unit for visualization of the movement and to the vehicle.” (See page 9, 2nd paragraph)).
But Hartmann does not explicitly teach:
the motion data describing the time history of the pose.
However, Yang discloses:
the motion data describing the time history of the pose (FIG. 3 and associated text, such as, “The first collecting unit 110 may acquire the motion state of the eyes of a user, forming the eye motion data, and record the first acquisition time. The extracting unit 120 may extract position data of the user's eyeballs from the eye motion data. The second collecting unit 130 may capture the user behavior activity data using images, and record the second acquisition time. Further, the determining unit 140 may, based on the first acquisition time and the second acquisition time, determine a correspondence relationship between the position data of the user's eyeballs and the user behavior activity data. The correspondence relationship can be further used to determine the current user behavior activity based on the motion state of the user's eyes.” (See paras [0090] – [0091])).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Yang into the teachings of Hartmann because that would have using an eye tracking device to collect, over a long time period (e.g., a few hours), the eye position coordinates to obtain time discrete data of the user's gazing points, blinking, and sweeping motions; and encoding such eye motion data to better collect, evaluate, and analyze human behavior as suggested by Yang (See para [0123]).
Regarding claim 3:
The rejection of claim 1 is incorporated, Hartmann further discloses wherein the first vehicle is a real vehicle (“Virtual testing of interaction between vehicles and road users (Pedestrians) comprising virtual reality (VR) environment, based on a real world environment … with vehicles and road users (pedestrians)” (See Abstract)) [[or the virtual representation of the vehicle]].
Regarding claim 4:
The rejection of claim 2 is incorporated, Hartmann further discloses wherein creating the test event comprises: storing the motion data in association with first video data that includes the first virtual stimulus and aspects of the virtual test environment (“Information about the virtual reality environment is transmitted to the stimuli unit for the test person and the vehicle. With this information at the stimuli unit, the virtual environment is made accessible for test persons and their actions on the virtual environment and on traffic scenarios is measured using a motion capture system” (See page 9, 2nd paragraph)).
Regarding claim 5:
The rejection of claim 2 is incorporated, Hartmann further discloses wherein the motion data is collected while the real living being is interacting with the physical controls of the first vehicle and being stimulated by a second stimulus (“Information about the virtual reality environment is transmitted to the stimuli unit for the test person and the vehicle. With this information at the stimuli unit, the virtual environment is made accessible for test persons and their actions on the virtual environment and on traffic scenarios is measured using a motion capture system. In a fourth step, the information of measured gesture and actions of test persons reacting on the various traffic scenarios is transmitted to the visualization processing unit for visualization of the movement and to the vehicle.” (See page 9, 2nd paragraph)).
Regarding claim 6:
The rejection of claim 5 is incorporated, Hartmann further discloses wherein generating the test event further comprises: selecting the first virtual stimulus from multiple virtual stimuli of the virtual test environment, wherein the second stimulus is different from the first virtual stimulus (“Information about the virtual reality environment is transmitted to the stimuli unit for the test person and the vehicle. With this information at the stimuli unit, the virtual environment is made accessible for test persons and their actions on the virtual environment and on traffic scenarios is measured using a motion capture system. In a fourth step, the information of measured gesture and actions of test persons reacting on the various traffic scenarios is transmitted to the visualization processing unit for visualization of the movement and to the vehicle.” (See page 9, 2nd paragraph)).
Regarding claim 7:
The rejection of claim 5 is incorporated, Hartmann further discloses wherein the second stimulus is a virtual stimulus, and wherein the test event includes the second stimulus and new motion data (“In a fourth step, the information of measured gesture and actions of test persons reacting on the various traffic scenarios is transmitted to the visualization processing unit for visualization of the movement and to the vehicle.” (See page 9, 2nd paragraph)) [[that is generated by changing at least one part of the anatomical structure of the real living being that is included in the motion data]].
But Hartmann does not explicitly teach:
new motion data that is generated by changing at least one part of the anatomical structure of the real living being that is included in the motion data
However, Yang discloses:
new motion data that is generated by changing at least one part of the anatomical structure of the real living being that is included in the motion data (FIG. 3 and associated text, such as, “The first collecting unit 110 may acquire the motion state of the eyes of a user, forming the eye motion data, and record the first acquisition time. The extracting unit 120 may extract position data of the user's eyeballs from the eye motion data. The second collecting unit 130 may capture the user behavior activity data using images, and record the second acquisition time. Further, the determining unit 140 may, based on the first acquisition time and the second acquisition time, determine a correspondence relationship between the position data of the user's eyeballs and the user behavior activity data. The correspondence relationship can be further used to determine the current user behavior activity based on the motion state of the user's eyes.” (See paras [0090] – [0091])).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Yang into the teachings of Hartmann because that would have using an eye tracking device to collect, over a long time period (e.g., a few hours), the eye position coordinates to obtain time discrete data of the user's gazing points, blinking, and sweeping motions; and encoding such eye motion data to better collect, evaluate, and analyze human behavior as suggested by Yang (See para [0123]).
Regarding claim 8:
The rejection of claim 5 is incorporated, but Hartmann does not explicitly teach:
wherein changing the at least one part of the anatomical structure is performed based on an empirical quantile of the at least one part of the anatomical structure.
However, Yang discloses:
wherein changing the at least one part of the anatomical structure is performed based on an empirical quantile of the at least one part of the anatomical structure (FIG. 3 and associated text, such as, “The first collecting unit 110 may acquire the motion state of the eyes of a user, forming the eye motion data, and record the first acquisition time. The extracting unit 120 may extract position data of the user's eyeballs from the eye motion data. The second collecting unit 130 may capture the user behavior activity data using images, and record the second acquisition time. Further, the determining unit 140 may, based on the first acquisition time and the second acquisition time, determine a correspondence relationship between the position data of the user's eyeballs and the user behavior activity data. The correspondence relationship can be further used to determine the current user behavior activity based on the motion state of the user's eyes.” (See paras [0090] – [0091])).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Yang into the teachings of Hartmann because that would have using an eye tracking device to collect, over a long time period (e.g., a few hours), the eye position coordinates to obtain time discrete data of the user's gazing points, blinking, and sweeping motions; and encoding such eye motion data to better collect, evaluate, and analyze human behavior as suggested by Yang (See para [0123]).
Regarding claim 9:
The rejection of claim 1 is incorporated, Hartmann further including:
adding the test event to a training dataset (“The prediction of the test persons' movements and the predictive control actuator signals for the vehicle are calculated.” (See page 9, 2nd paragraph)); and
providing the test event as a test input to the driver assistance system (“testing the interaction process between pedestrians, virtual environments, and other road users and the vehicles.” (See claim 9)).
Regarding claim 10:
The rejection of claim 1 is incorporated, Hartmann further discloses wherein the motion data of the real living being is captured while the real living being is interacting with a sequence of virtual stimuli presented at a first speed and wherein the test event includes the sequence of virtual stimuli presented at a second speed that is faster or slower than the first speed (“a collision Avoidance system is introduced to bring the vehicle to a safe state with adequate and automated steering and acceleration. Modules with prediction of trajectories of moving objects, warning of the driver, estimation of the risk of collision and building of a Collision-State-map, trying of different acceleration/steering combinations to bring the vehicle to safe driving state and use of hypothetical trajectories” (See page 4, 3rd paragraph)).
Regarding claim 11:
The rejection of claim 1 is incorporated, but Hartmann does not explicitly teach:
wherein the motion data includes first captured motion data and second captured motion data, and wherein the method further comprises: determining transition data between first captured motion data and second captured motion data, the transition data describing a temporal and/or spatial transition from the first captured motion data to the second captured motion data, and wherein the test event includes the transition data reproduced at a time that is between the first captured motion data and the second captured motion data.
However, Yang discloses:
wherein the motion data includes first captured motion data and second captured motion data, and wherein the method further comprises: determining transition data between first captured motion data and second captured motion data, the transition data describing a temporal and/or spatial transition from the first captured motion data to the second captured motion data, and wherein the test event includes the transition data reproduced at a time that is between the first captured motion data and the second captured motion data (FIG. 3 and associated text, such as, “The first collecting unit 110 may acquire the motion state of the eyes of a user, forming the eye motion data, and record the first acquisition time. The extracting unit 120 may extract position data of the user's eyeballs from the eye motion data. The second collecting unit 130 may capture the user behavior activity data using images, and record the second acquisition time. Further, the determining unit 140 may, based on the first acquisition time and the second acquisition time, determine a correspondence relationship between the position data of the user's eyeballs and the user behavior activity data. The correspondence relationship can be further used to determine the current user behavior activity based on the motion state of the user's eyes.” (See paras [0090] – [0091])).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Yang into the teachings of Hartmann because that would have using an eye tracking device to collect, over a long time period (e.g., a few hours), the eye position coordinates to obtain time discrete data of the user's gazing points, blinking, and sweeping motions; and encoding such eye motion data to better collect, evaluate, and analyze human behavior as suggested by Yang (See para [0123]).
Regarding claim 12:
Hartmann discloses a method for testing a driver assistance system, the method including:
providing a test dataset that includes a test event (“testing the interaction process between pedestrians, virtual environments, and other road users and the vehicles.” (See claim 9)), the test event comprising:
motion data describing [[a time history]] of a pose of at least one part of an anatomical structure of a real living being (“A visual pedestrian detection is described with extraction of a partial image and processing unit with prediction of human behavior) (See page 4, 3rd paragraph)) that is interacting with physical controls of a first vehicle at the time the motion data is captured (“For Block D: Single testable object (e.g. vehicle in Autonomous Mode as simulation software (SIL), model- (MIL), vehicle-(VIL) or hardware- (HIL) in the loop) and Block E: Person with virtual (mixed-) reality devices with perception-, motion- and position- capture system devices and (mixed-) virtual reality glasses. The persons can be involved in real traffic situations or virtual reality cabs a stimuli of the perception (e.g. visualization of a scene of the virtual environment) is assumed” (See page 9, 3rd paragraph)); and
virtual simulation data that describes at least one virtual living being and at least one virtual vehicle, wherein the virtual living being is a virtual representation of the real living being and wherein that at least one virtual vehicle includes a driver assistance system (“Virtual testing of interaction between vehicles and road users (Pedestrians) comprising virtual reality (VR) environment, based on a real world environment or new virtual environment, with vehicles and road users (pedestrians)” (See Abstract)). “in a third step the measurement of the actions of the test person in a motion capture system in a fourth step the processing for sending the information of gesture and actions to the visualization processing unit for visualization of the movement and to the vehicle” (See claim 1). Also, see page 9, 2nd paragraph); and
providing the test dataset as input to the driver assistance system (“testing the interaction process between pedestrians, virtual environments, and other road users and the vehicles.” (See claim 9)).
But Hartmann does not explicitly teach:
motion data describing a time history of a pose of at least one part of an anatomical structure of a real living being.
However, Yang discloses:
motion data describing a time history of a pose of at least one part of an anatomical structure of a real living being (FIG. 3 and associated text, such as, “The first collecting unit 110 may acquire the motion state of the eyes of a user, forming the eye motion data, and record the first acquisition time. The extracting unit 120 may extract position data of the user's eyeballs from the eye motion data. The second collecting unit 130 may capture the user behavior activity data using images, and record the second acquisition time. Further, the determining unit 140 may, based on the first acquisition time and the second acquisition time, determine a correspondence relationship between the position data of the user's eyeballs and the user behavior activity data. The correspondence relationship can be further used to determine the current user behavior activity based on the motion state of the user's eyes.” (See paras [0090] – [0091])).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Yang into the teachings of Hartmann because that would have using an eye tracking device to collect, over a long time period (e.g., a few hours), the eye position coordinates to obtain time discrete data of the user's gazing points, blinking, and sweeping motions; and encoding such eye motion data to better collect, evaluate, and analyze human behavior as suggested by Yang (See para [0123]).
Regarding claim 13:
The rejection of claim 12 is incorporated, Hartmann further discloses wherein the driver assistance system includes a machine learning model and the method further includes: training the machine learning model, based on the test dataset, to identify and execute autonomous interventions for a vehicle that reduce likelihood of a vehicle accident (“In [42] a determination of a driving strategy is done with prediction of movements and evaluation of environment data and modelling the virtual driver with artificial intelligence In [43] the prediction of the region of movement, situation classification of normality of movement and selection of movement models for prediction In [44] a collision Avoidance system is introduced to bring the vehicle to a safe state with adequate and automated steering and acceleration. Modules with prediction of trajectories of moving objects, warning of the driver, estimation of the risk of collision and building of a Collision-State-map, trying of different acceleration/steering combinations to bring the vehicle to safe driving state and use of hypothetical trajectories In [45] an digital map of a parking area is used with a Car2X- communication network, so that the position data of mobile objects are detected. This information is used for navigation to a target position with collision avoidance. In [46] a process for collision avoidance and automated configuration of working area of a robot discussed. In [47] a classification of type of object (e.g. bicycle, pedestrian) and a classification and prediction of behavior is presented. Features are adaption and correction of characteristic values and motion planning depending on predictions. In [48] a probabilistic situation analysis is presented for the fusion of Situation Analysis to trigger safety systems. Application is for pre-crash system. In [49] a prediction procedure for trajectories for collision avoidance and the control of velocity is presented.” (See page 4, 3rd paragraph)).
Regarding claim 14:
The rejection of claim 12 is incorporated, Hartmann further discloses wherein the virtual simulation data of the test event includes a first virtual stimulus presented within a virtual test environment (“Virtual testing of interaction between vehicles and road users (Pedestrians) comprising virtual reality (VR) environment, based on a real world environment or new virtual environment, with vehicles and road users (pedestrians)” (See Abstract). Also, see page 9, 2nd paragraph).
Regarding claim 15:
The rejection of base claim 12 is incorporated. All the limitations of this claim have been noted in the rejection of claim 3, and is therefore rejected under similar rationale.
Regarding claim 16:
The rejection of base claim 12 is incorporated. All the limitations of this claim have been noted in the rejection of claims 5 and 6, and is therefore rejected under similar rationale.
Regarding claim 17:
Hartmann discloses a system comprising:
one or more storage devices (“Communication Device (wireless: 5G (successor of LTE) or wired bus system) can be wireless or a hardware based communication system to get data from” (See page 9, 2nd paragraph)) storing:
virtual simulation data that includes at least one virtual living being and at least one virtual vehicle (“Virtual testing of interaction between vehicles and road users (Pedestrians) comprising virtual reality (VR) environment, based on a real world environment or new virtual environment, with vehicles and road users (pedestrians)” (See Abstract). Also, see page 9, 2nd paragraph), wherein the virtual living being is a virtual representation of a real living being (“in a third step the measurement of the actions of the test person in a motion capture system in a fourth step the processing for sending the information of gesture and actions to the visualization processing unit for visualization of the movement and to the vehicle” (See claim 1). Also, see page 9, 2nd paragraph) and wherein that at least one virtual vehicle is a virtual representation of a vehicle with a driver assistance system (“in a first step the computation of real world or new virtual environments with vehicles and road users (e.g. pedestrians)” (See claim 1))
motion data of a real living being interacting with a set of physical control manipulatable to operate one or more parts of the vehicle (“For Block D: Single testable object (e.g. vehicle in Autonomous Mode as simulation software (SIL), model- (MIL), vehicle-(VIL) or hardware- (HIL) in the loop) and Block E: Person with virtual (mixed-) reality devices with perception-, motion- and position- capture system devices and (mixed-) virtual reality glasses. The persons can be involved in real traffic situations or virtual reality cabs a stimuli of the perception (e.g. visualization of a scene of the virtual environment) is assumed” (See page 9, 3rd paragraph)); and
a software module, stored in the memory, configured to:
generate a test event for the driver assistance system by combining a subset of the motion data with a subset of the virtual simulation data (“testing the interaction process between pedestrians, virtual environments, and other road users and the vehicles.” (See claim 9)), the subset of the motion data describing [[a time history of]] a pose of the at least one part of an anatomical structure of the real living being (“A visual pedestrian detection is described with extraction of a partial image and processing unit with prediction of human behavior) (See page 4, 3rd paragraph)); and
test the driver assistance system based on the test event (“testing the interaction process between pedestrians, virtual environments, and other road users and the vehicles.” (See claim 9)).
But Hartmann does not explicitly teach:
the subset of the motion data describing a time history of a pose of the at least one part of an anatomical structure of the real living being.
However, Yang discloses:
the subset of the motion data describing a time history of a pose of the at least one part of an anatomical structure of the real living being (FIG. 3 and associated text, such as, “The first collecting unit 110 may acquire the motion state of the eyes of a user, forming the eye motion data, and record the first acquisition time. The extracting unit 120 may extract position data of the user's eyeballs from the eye motion data. The second collecting unit 130 may capture the user behavior activity data using images, and record the second acquisition time. Further, the determining unit 140 may, based on the first acquisition time and the second acquisition time, determine a correspondence relationship between the position data of the user's eyeballs and the user behavior activity data. The correspondence relationship can be further used to determine the current user behavior activity based on the motion state of the user's eyes.” (See paras [0090] – [0091])).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Yang into the teachings of Hartmann because that would have using an eye tracking device to collect, over a long time period (e.g., a few hours), the eye position coordinates to obtain time discrete data of the user's gazing points, blinking, and sweeping motions; and encoding such eye motion data to better collect, evaluate, and analyze human behavior as suggested by Yang (See para [0123]).
Regarding claim 18:
The rejection of claim 17 is incorporated, Hartmann further discloses wherein the test event includes a first virtual stimulus described within the virtual simulation data (“Virtual testing of interaction between vehicles and road users (Pedestrians) comprising virtual reality (VR) environment, based on a real world environment or new virtual environment, with vehicles and road users (pedestrians)” (See Abstract). Also, see page 9, 2nd paragraph) and wherein the subset of the motion data is captured while the real living being is interacting with the physical controls of the vehicle and being stimulated by a second stimulus different from the first virtual stimulus (“A visual pedestrian detection is described with extraction of a partial image and processing unit with prediction of human behavior) (See page 4, 3rd paragraph)).
Regarding claim 19:
The rejection of base claim 17 is incorporated. All the limitations of this claim have been noted in the rejection of claim 10, and is therefore rejected under similar rationale.
Regarding claim 20:
The rejection of claim 17 is incorporated, Hartmann further discloses wherein the software module is further configured to generate the test event at least in part by:
generating new motion data (“In a fourth step, the information of measured gesture and actions of test persons reacting on the various traffic scenarios is transmitted to the visualization processing unit for visualization of the movement and to the vehicle.” (See page 9, 2nd paragraph)) [[by changing at least one part of the anatomical structure of the real living being]]
But Hartmann does not explicitly teach:
new motion data that is generated by changing at least one part of the anatomical structure of the real living being
However, Yang discloses:
new motion data that is generated by changing at least one part of the anatomical structure of the real living being (FIG. 3 and associated text, such as, “The first collecting unit 110 may acquire the motion state of the eyes of a user, forming the eye motion data, and record the first acquisition time. The extracting unit 120 may extract position data of the user's eyeballs from the eye motion data. The second collecting unit 130 may capture the user behavior activity data using images, and record the second acquisition time. Further, the determining unit 140 may, based on the first acquisition time and the second acquisition time, determine a correspondence relationship between the position data of the user's eyeballs and the user behavior activity data. The correspondence relationship can be further used to determine the current user behavior activity based on the motion state of the user's eyes.” (See paras [0090] – [0091])).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Yang into the teachings of Hartmann because that would have using an eye tracking device to collect, over a long time period (e.g., a few hours), the eye position coordinates to obtain time discrete data of the user's gazing points, blinking, and sweeping motions; and encoding such eye motion data to better collect, evaluate, and analyze human behavior as suggested by Yang (See para [0123]).
storing the new motion in association with a subset of the virtual simulation data (“Information about the virtual reality environment is transmitted to the stimuli unit for the test person and the vehicle. With this information at the stimuli unit, the virtual environment is made accessible for test persons and their actions on the virtual environment and on traffic scenarios is measured using a motion capture system” (See page 9, 2nd paragraph)).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to HANH THI MINH BUI whose telephone number is (571)270-1976. The examiner can normally be reached Monday - Friday: 7-3.
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, Hyung S. Sough can be reached at 571-272-6799. 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.
/HANH THI-MINH BUI/Primary Examiner, Art Unit 2192 June 2nd, 2026
Prosecution Insights