DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Status of Claims
This Office Action is in response to the reply filed on May 29, 2026. Claims 1-20 are pending. Claims 1, 14 and 20 are independent.
Response to Arguments
Applicants’ arguments have been fully considered. Therefore, the rejection has been withdrawn. However, upon further consideration, a new ground of rejection is made.
Claim Rejections - 35 USC § 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, 3, 7, 9, 10, 12-15 and 18-20 are rejected under 35 U.S.C. 103 as being unpatentable over U.S. Patent Publication No. 2020/0174481 to Van Heukelom et al. (hereinafter “Van Heukelom”) in view of U.S. Patent Publication No. 2014/0346823 to Stebbins et al. (hereinafter “Stebbins”).
With respect to independent claims 1, 14 and 20, Van Heukelom discloses obtaining, from one or more sensors, data representing a sensed position of the first vehicle and a sensed feature in a proximity of the first vehicle (see paragraph [0026]: the sensor data can include data captured by one or more of a lidar sensor, a radar sensor, an image sensor, a time-of-flight sensor, a sonar sensor);
defining a first probability density function (PDF) based on the obtained data, the first PDF representing likelihood of a future position of the first vehicle (see paragraph [0022]: individual trajectory probabilities of the multiple trajectories can be compared to evaluate the trajectories. In some cases, a trajectory having the lowest probability can represent a lowest risk associated with a trajectory (where a probability corresponds to a likelihood that an object and the vehicle will occupy a same location at a same time).);
defining a second PDF based on the obtained data, the second PDF representing likelihood related to a proxemic risk presented by the sensed feature (see paragraph [0023]: representing predictions associated with a plurality of objects in a single discretized probability distribution or heat map can represent a simplified representation of the environment for the purposes of evaluating risk associated with a trajectory.);
computing a risk metric representing a likelihood of the proxemic risk to the first vehicle based on an overlap between the first PDF and the second PDF; and in response to the risk metric exceeding a defined risk threshold, control at least one haptic output unit, embedded in the first vehicle, to provide haptic output indicative of the proxemic risk.
Stebbins teaches during operation and as also discussed in greater detail below, the control module 130 receives input signals from the collision avoidance modules 110 and communications module 120 that indicate the possibility of a collision condition. The control module 130 evaluates the input signals, and as appropriate, operates the haptic alert assembly 140 and/or alert devices 150, 152, 154 to alert the driver of the collision condition. (See paragraph [0023]). Stebbins also teaches the control module 130 evaluates the input signals, and as appropriate, operates the haptic alert assembly 140 and/or alert devices 150, 152, 154 to alert the driver of the collision condition. (See paragraph [0023]).
It would have been obvious to one skilled in the art before the effective filing date of the invention to combine the input signals from the collision modules by evaluating the input signals and operates the haptic alert of Stebbins with overlap-based region probability metric of Van Heukelom to provide a more accurate probability grounded trigger and risk metric for the known haptic alert action.
With respect to dependent claim 3, Van Heukelom discloses wherein the sensed feature is a sensed location of another vehicle in the proximity of the first vehicle, and the second PDF represents likelihood of a future position of the other vehicle (see paragraphs [0042] and [0043]: An environment 202 includes a vehicle 204 and an object 206. Location prediction probabilities 212 represent a Gaussian distribution of probabilities associated with possible locations of the object 206 in the predicted environment 210 at T2.);
wherein the second PDF is a 1D Gaussian distribution having a mean defined by the sensed location of the other vehicle and a standard deviation defined by a variation in relative distance between the first vehicle and the other vehicle (see paragraphs [0013], [0034] and [0044]: the discretized probability distribution represents aggregated prediction probabilities associated with a probability that an object. The location prediction probabilities 212 can represent a one-dimensional Gaussian distribution. A covariance matrix associated with an uncertainty of an object at an initial state or time. The covariance matrix can include a variance with respect to a longitudinal and/or lateral position in the environment.); and
wherein the risk metric is computed based on an area of the overlap between the first PDF and the second PDF (see paragraph [0020]: a region probability can be determined by summing, integrating, or otherwise aggregating the individual probabilities of the discretized probability distribution corresponding to the region of the vehicle (also referred to as an overlapping region or an overlap).).
With respect to dependent claim 7, Van Heukelom discloses wherein the one or more sensors include at least one of: a camera unit, a radar unit, a global navigation satellite system (GNSS) unit, a LIDAR unit or an ultrasound unit (see paragraph [0026]: the sensor data can include data captured by one or more of a lidar sensor, a radar sensor, an image sensor, a time-of-flight sensor, a sonar sensor).
With respect to dependent claims 9 and 18, Van Heukelom does not explicitly teach wherein a direction of the likely proxemic risk is determined based on the sensed feature, and wherein the at least one haptic unit is controlled to provide haptic output indicative of the direction of the likely proxemic risk.
Stebbins teaches the sensors 192 monitor the adjacent lane for approaching traffic from behind in the next lane over, typically one or more vehicles approaching in the adjacent lane at a speed such that the approaching vehicle poses a collision risk. Additionally, the sensors 194 monitor the adjacent lane for an immediately adjacent vehicle that is within the side blind spot of the driver. Based on the input from sensors 192, 194, the evaluation unit 136 determines if the collision condition exists. Signals associated with the lane change and side blind spot warning modules 112, 114 may actuate left and/or right actuators of the haptic alert assembly 140 positioned within the left and/or right seat back bolsters. The alert pattern may include directional commands, such as the operation the right and/or left actuator to provide additional information about the nature of the collision condition (e.g., operation of only the right actuator(s) would indicate collision threat is on the right). (See paragraphs [0031] - [0033]).
It would have been obvious to one skilled in the art before the effective filing date of the invention to combine the evaluation unit that determines a collision condition of Stebbins with the overlap-region location data of Van Heukelom to provide directional alert related to a risk source.
With respect to dependent claims 10 and 19, Van Heukelom does not explicitly teach wherein there is a plurality of haptic units embedded in a respective plurality of locations in the first vehicle, and at least one selected haptic unit is selected from the plurality of haptic units to provide the haptic output, the at least one selected haptic unit being embedded in a respective location in the first vehicle corresponding to the direction of the likely proxemic risk.
Stebbins teaches the haptic alert assembly 140 includes a first actuator 322 installed in the first lower bolster 320 and a second actuator 332 installed in the second lower bolster 330. The haptic alert assembly 140 may further include a third actuator 382 installed in the first back bolster 380 and a fourth actuator 392 installed in the second back bolster 390. The haptic controller 350 commands actuators 322, 332, 382, 392 based on a haptic pattern. For example, when an object is detected approaching from the right side of the vehicle when the vehicle is beginning to merge into an adjacent right lane, the actuator 392 positioned near the driver's back on the right side is selected for actuation, and vice versa. (See paragraphs [0041] and [0047]).
It would have been obvious to one skilled in the art before the effective filing date of the invention to combine the haptic controller based on a haptic pattern of Stebbins with the highest risk overlap determination of Van Heukelom to obtain an accurate directional trigger for an existing actuation selection scheme.
With respect to dependent claim 12, Van Heukelom does not explicitly teach wherein the direction of the likely proxemic risk is from a side of the first vehicle, and the at least one selected haptic unit is embedded in a side of a driver's seat of the first vehicle.
Stebbins teaches the side blind spot warning module 114, in cooperation with the other components of the system 100, functions to alert the driver, prior to a lane change, during a lane change, or upon anticipating that the driver is changing lanes, that another vehicle is within the intended lane, e.g., is within the “side blind spot” of the driver. The lower bolsters 320, 330 are generally considered the left outermost and right outermost side of the lower seat member 210. The haptic alert assembly 140 includes a first actuator 322 installed in the first lower bolster 320 and a second actuator 332 installed in the second lower bolster 330. (See paragraph [0025], [0039] and [0041]).
It would have been obvious to one skilled in the art before the effective filing date of the invention to combine the blind spot warning module and lower-bolster actuators of Stebbins with the overlap metric of Van Heukelom to provide a more precise substitute risk-input for the blind spot sensor logic to account for uncertainty and relative motion.
With respect to dependent claim 13, Van Heukelom does not explicitly teach wherein the direction of the likely proxemic risk is from a rear of the first vehicle, and the at least one selected haptic unit is embedded in a back of a driver's seat of the first vehicle.
Stebbins teaches the lane change warning module 112 may include one or more sensors 192 on the rear of the vehicle that function to monitor a range 193 of approximately 25-70 meters, as shown. Within this range 193, the sensors 192 may recognize an approaching vehicle. The haptic alert assembly 140 may further include a third actuator 382 installed in the first back bolster 380 and a fourth actuator 392 installed in the second back bolster 390. A clear signal regarding the nature of the alert and direction the alert is referring to, e.g., rapid pulsing of the left back actuator 382 signals to the driver indicate a vehicle is approaching in the left adjacent lane. (See paragraph [0026], [0041] and [0046]).
It would have been obvious to one skilled in the art before the effective filing date of the invention to combine the rear-facing lane change warning module and back-bolster actuators of Stebbins with the overlap metric of Van Heukelom to provide a risk computation method of alert system zones that is simple and consistent.
With respect to dependent claim 15, Van Heukelom discloses wherein the first PDF is a 1D Gaussian distribution having a mean defined by an estimated stopping distance of the first vehicle relative to the sensed position and a standard deviation defined by a variation in sensed speed of the first vehicle (see paragraphs [0013], [0034] and [0044]: the discretized probability distribution represents aggregated prediction probabilities associated with a probability that an object. The location prediction probabilities 212 can represent a one-dimensional Gaussian distribution. A covariance matrix associated with an uncertainty of an object at an initial state or time. The covariance matrix can include a variance with respect to a longitudinal and/or lateral position in the environment.);
wherein the sensed feature is a sensed location of another vehicle in the proximity of the first vehicle, and the second PDF represents likelihood of a future position of the other vehicle (see paragraphs [0042] and [0043]: An environment 202 includes a vehicle 204 and an object 206. Location prediction probabilities 212 represent a Gaussian distribution of probabilities associated with possible locations of the object 206 in the predicted environment 210 at T2.);
wherein the second PDF is a 1D Gaussian distribution having a mean defined by the sensed location of the other vehicle and a standard deviation defined by a variation in relative distance between the first vehicle and the other vehicle; and wherein the risk metric is computed based on an area of the overlap between the first PDF and the second PDF (see paragraphs [0013], [0034] and [0044]: the discretized probability distribution represents aggregated prediction probabilities associated with a probability that an object. The location prediction probabilities 212 can represent a one-dimensional Gaussian distribution. A covariance matrix associated with an uncertainty of an object at an initial state or time. The covariance matrix can include a variance with respect to a longitudinal and/or lateral position in the environment.).
Claims 11 is rejected under 35 U.S.C. 103 as being unpatentable over Van Heukelom and Stebbins as applied to claim 1 above, and further in view of U.S. Patent Publication 2007/0299580 to Lin et al. (hereinafter “Lin”).
With respect to dependent claim 11, Van Heukelom and Stebbins do not explicitly teach wherein the direction of the likely proxemic risk is from a front of the first vehicle, and the at least one selected haptic unit is embedded in a steering wheel of the first vehicle.
Lin teaches a vehicle 10 including a vehicle active stability controller 12. The vehicle 10 also includes a hand-wheel angle sensor 14 that provides a signal to the controller 12 of the position of a vehicle hand-wheel 16. A path error can be determined from any of several devices, such as, lane-watching cameras, map information as compared with the vehicle position provided by the GPS receiver 24, etc. The DAAFSD signal is added to the steering signal from the controller 64 by an adder 76 that causes the hand-wheel 16 to vibrate when the AFS controller 62 is providing the steering angle signal for stability control. (See paragraphs [0022], [0024] and [0029]).
It would have been obvious to one skilled in the art before the effective filing date of the invention to combine the generic steering wheel haptic actuation mechanism of Lin with the risk computation engine that converts sensor data into probability distributions of Van Heukelom to provide a more accurate collision proxemic risk alert system with an threshold signal.
Allowable Subject Matter
Claims 2, 4-6, 8 and 16-17 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
Any inquiry concerning this communication or earlier communications from the examiner should be directed to DEMETRA R SMITH-STEWART whose telephone number is (571)270-3965. The examiner can normally be reached 10am - 6pm.
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/DEMETRA R SMITH-STEWART/Examiner, Art Unit 3661
/PETER D NOLAN/Supervisory Patent Examiner, Art Unit 3661
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