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 Request for Continued Examination filed on November 21, 2025. Claims 1-20 are pending. Claims 1, 6, 11 and 16 are independent.
Response to Arguments
Applicants’ arguments have been fully considered and persuasive because they are directed toward the newly added claim limitations. Thus, the rejection has been withdrawn in light of the newly added claim limitations.
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 1-20 are rejected under 35 U.S.C. 103 as being unpatentable over U.S. Patent Publication No. 2014/0032049 to Moshchuk et al. (hereinafter “Moshchuk”) in view of U.S. Patent Publication No. 2017/0083021 to Balaghiasefi et al. (hereinafter “Balaghiasefi”) and U.S. Patent No. 8,788,176 to Yopp.
With respect to independent claims 1, 6, 11 and 17, Moshchuk discloses
a) a plurality of sensors, each sensor of the plurality configured to acquire sensor data related to a second vehicle proximate to a subject vehicle (see paragraph [0025]: One or more sensor(s) may be attached to or associated with the vehicle 10. A computer vision sensor (e.g., a camera) 18, LIDAR sensor 20 (e.g., laser radar (LADAR) sensor), radar sensor 22, or other remote sensing device may obtain data allowing system 12 to determine or measure the relative location of the vehicle with respect to road features, for example, other vehicles, lane markers(s), road shoulder(s), median barrier(s), edge of the road and other objects or features.); and
b) one or more processors in the subject vehicle (see paragraphs [0027] and [0028]: The collision avoidance control system 12 may be or may include a computing device mounted on the dashboard of the vehicle, in passenger compartment or in a trunk. A collision avoidance control system according to an embodiment of the present invention. Collision avoidance control system 12 may include one or more processor(s) or controller(s) 40, memory 42, long term storage 44, input device(s) 46, and output device(s) 48.);
c) wherein the one or more processors is/are programmed to:
i) determine, by analyzing the sensor data faster than a human driver of ordinary skill, whether a collision between the subject vehicle and the second vehicle is imminent (see paragraphs [0033], [0038] – [0040]: If vehicle is within a predefined distance to the object 60 that poses a collision threat, within a predefined velocity range, and within a predefined acceleration range, system 12 or other systems associated with vehicle 10 may provide pre-collision preparation and/or warnings to the driver of vehicle 10. The warnings to driver of vehicle 10 may be a signal, for example, an audible warning, a warning light or other form of warning. If the driver does not mitigate the collision threat, collision avoidance control system 12 may control the vehicle through collision imminent braking, automated steering control, or other controls or maneuvers in order to avoid object 60 or mitigate the impact between vehicle 10 and object 60. Automated braking may include common or typical braking (e.g., applying both front brakes, both rear brakes, or all brakes simultaneously), differential braking (e.g., applying brakes on each wheel independent of other wheel brakes), and/or another braking system or method. A current time-to-collision estimate (TTC) is compared to the first threshold Th1. If the current TTC estimate is greater than the first threshold Th1, then routine proceeds to step 87 where the routine exits. If the current TTC estimate is less than the first threshold Th1, then routine proceeds to step 77. In step 77, a collision warning is initiated. The collision warning may be an alert or other collision mitigation device that is enabled. In step 78, a current time-to-collision (TTC) estimate is compared to the second threshold Th2. If the current TTC estimate is greater than the second threshold Th2, then routine proceeds to step 87 where the routine exits. If the current TTC estimate is less than the second threshold Th2,);
ii) upon determining that the collision is imminent, calculate, faster than a human driver of ordinary skill, one or more actions, each action comprising acceleration or braking or steering, or a sequence of these, of the subject vehicle (see paragraph [0033]: If the driver does not mitigate the collision threat, collision avoidance control system 12 may control the vehicle through collision imminent braking, automated steering control, or other controls or maneuvers in order to avoid object 60 or mitigate the impact between vehicle 10 and object 60. Automated braking may include common or typical braking (e.g., applying both front brakes, both rear brakes, or all brakes simultaneously), differential braking (e.g., applying brakes on each wheel independent of other wheel brakes), and/or another braking system or method.);
iii) select, faster than a human driver of ordinary skill, a particular action or sequence of actions configured to avoid the collision when the collision is avoidable, or to minimize or reduce harm of the collision when the collision is unavoidable (see paragraphs [0033] and [0035]: If vehicle is within a predefined distance to the object 60 that poses a collision threat, within a predefined velocity range, and within a predefined acceleration range, system 12 or other systems associated with vehicle 10 may provide pre-collision preparation and/or warnings to the driver of vehicle 10. The warnings to driver of vehicle 10 may be a signal, for example, an audible warning, a warning light or other form of warning. If the driver does not mitigate the collision threat, collision avoidance control system 12 may control the vehicle through collision imminent braking, automated steering control, or other controls or maneuvers in order to avoid object 60 or mitigate the impact between vehicle 10 and object 60. Automated braking may include common or typical braking (e.g., applying both front brakes, both rear brakes, or all brakes simultaneously), differential braking (e.g., applying brakes on each wheel independent of other wheel brakes), and/or another braking system or method.);
iv) implement the particular action or sequence of actions, faster and more precisely than a human driver of ordinary skill, by sending control signals to means for accelerating or decelerating or steering the subject vehicle (see paragraph [0033]: FIG. 3 is a schematic diagram of the collision avoidance control system using steering control. Collision avoidance control system 12 may be passive or operate in the background during normal vehicle operation. System 12 may become active when, for example, vehicle sensor data indicates likelihood of imminent collision, or a collision threat. The warnings to driver of vehicle 10 may be a signal, for example, an audible warning, a warning light or other form of warning. If the driver does not mitigate the collision threat, collision avoidance control system 12 may control the vehicle through collision imminent braking, automated steering control, or other controls or maneuvers in order to avoid object 60 or mitigate the impact between vehicle 10 and object 60.); and
v) while implementing the particular action or sequence of actions, continue calculating further actions or sequences of actions configured to avoid the collision or to further reduce the harm of the collision (see paragraph [0034]: During a potential collision threat, a time-to-collision (TTC) is recursively updated. Utilizing the selected technique, the optimal collision avoidance path is recursively updated for determining whether the optimal collision avoidance path should be modified based on vehicle speeds, lateral accelerations, changes in direction by the driver, and changes in position and velocity of the forward driven vehicle. Moreover, various conditions are constantly monitored for either maintaining the steering assist adjustments in the enabled state or for disabling the steering assist adjustments. Various conditions include, but are not limited to, whether the collision avoidance path is feasible, whether the target lane is clear of other objects, whether the driver is overriding the steering assist adjustments, or whether the lateral acceleration is greater than a predetermined threshold.).
Moshchuk does not explicitly disclose that the actions or sequence or actions are configured by adjusting the particular action or sequence of actions according to a motion of the second vehicle and vi) wherein each listed action is performed faster than a human driver of ordinary skill when the action is performed in less than a particular time interval while simultaneously driving the subject vehicle, and each action is performed more precisely than a human driver of ordinary skill when the action is performed with an error less than a particular uncertainty value.
Balaghiasefi discloses an occupancy map generator 16 calculates an occupancy map from the environmental model 11 that represents the obstacles in the surroundings of the vehicle. The occupancy map is continuously updated. Finally, the generator 17 derives the common state space from the state space and the occupancy map. The monitoring algorithm 18 assesses or monitors the target trajectory of the vehicle in each case for the updated common state space at each time operation within the defined maneuver duration. (See paragraphs [0049] and [0050])
It would have been obvious to one of ordinary skilled in the art, before the effective filing date of the invention to combine the system for mitigating a collision using avoidance logic of Moshchuk with the PID controller of Balaghiasefi in order to provide a system that maintains an optimum path based on continuous feedback and control that precise path tracking than a human manually steering with no knowledge of the optimal curvature and TTC calculations.
Moshchuk discloses the collision avoidance path is recursively updated and steering adjustments are made to the steering assist adjustment torque for maintaining the vehicle along an updated collision avoidance path. The optimum collision avoidance path is re-calculated at every time step after a driver initiates a steering maneuver. (See paragraphs [0003] and [0046]). The collision system of Moshchuk reacts based on TTC thresholds, path feasibility, and stability constraints, with continuous updates on every control cycle.
Yopp discloses an intrusion zone that may be defined in terms of a time-to-impact threshold established as an amount of time reflecting a driver or control system reaction time and other representative performance factors. A time-to-impact threshold 21 having a value of 2 seconds creates a smaller intrusion zone than a time-to-impact threshold 22 with a value of 3 seconds. The actual size of an intrusion zone depends on the relative approaching speed of the target object on a collision course. In conventional driver assistance systems, however, values for the time-to-impact threshold have been based on a fixed set of driving conditions such as vehicle loading and vehicle-road interactions even though these conditions do not remain static. Vehicle apparatus for dynamically updating a time-to-impact threshold.
It would have been obvious to one of ordinary skilled in the art, before the effective filing date of the invention to combine the system for mitigating a collision using avoidance logic of Moshchuk with the establishing industry standard for time-to-impact thresholds of Yopp for a system that calculates, select and implement faster and more precisely than a human driver manually estimating TTC and steering/braking while driving. Particular time intervals and uncertainty values are routine engineering choices.
With respect to dependent claims 2, 12 and 20, Moshchuk discloses wherein the particular time interval is 1 second and the particular uncertainty value is 5% (see paragraphs [0037], [0040] and [0041]: in response to the steering assist mode not being enabled, a first threshold Th1, a second threshold Th2, a third threshold Th3, and steering assist threshold ThSAA are determined. The first threshold Th1 is reached where 90% of drivers will initiate some evasive maneuver including braking and/or steering to avoid colliding with the target vehicle. The second threshold Th2 is reached where 95% of the drivers will initiate hard braking or steering to avoid a collision with the target vehicle. In step 78, a current time-to-collision (TTC) estimate is compared to the second threshold Th2. If the current TTC estimate is greater than the second threshold Th2, then routine proceeds to step 87 where the routine exits. If the current TTC estimate is less than the second threshold Th2, then routine proceeds to step 79. In step 79, autonomous collision warning braking is initiated.).
Yopp discloses the time-to-impact threshold includes a nominal or default value that is adjusted according to several different measures of vehicle and driving conditions. Respective offsets determined by a load monitor, a braking monitor, and a steering monitor are added to the threshold in response to measured vehicle performance parameters being different from expected values. (See abstract).
It would have been obvious to one of ordinary skilled in the art, before the effective filing date of the invention to combine the system for mitigating a collision using avoidance logic of Moshchuk with the time-to-impact thresholds of Yopp in order to meet safety and performance objectives. Such uncertainty value is an obvious engineering choice within the ordinary design space of such systems.
With respect to dependent claim 3, Moshchuk discloses wherein the analyzing the sensor data comprises deriving a position or velocity or acceleration of the second vehicle based on data from at least two sensors of different technologies (see paragraph [0034]: Utilizing the selected technique, the optimal collision avoidance path is recursively updated for determining whether the optimal collision avoidance path should be modified based on vehicle speeds, lateral accelerations, changes in direction by the driver, and changes in position and velocity of the forward driven vehicle.).
With respect to dependent claims 4, 8 and 19, Moshchuk discloses wherein the analyzing the sensor data is sufficiently complex that a human driver of ordinary skill could not perform the analyzing in time to avoid or minimize the collision (see paragraphs [0033] and [0035]: If vehicle is within a predefined distance to the object 60 that poses a collision threat, within a predefined velocity range, and within a predefined acceleration range, system 12 or other systems associated with vehicle 10 may provide pre-collision preparation and/or warnings to the driver of vehicle 10. The warnings to driver of vehicle 10 may be a signal, for example, an audible warning, a warning light or other form of warning. If the driver does not mitigate the collision threat, collision avoidance control system 12 may control the vehicle through collision imminent braking, automated steering control, or other controls or maneuvers in order to avoid object 60 or mitigate the impact between vehicle 10 and object 60. Automated braking may include common or typical braking (e.g., applying both front brakes, both rear brakes, or all brakes simultaneously), differential braking (e.g., applying brakes on each wheel independent of other wheel brakes), and/or another braking system or method.).
With respect to dependent claims 5 and 10, Moshchuk discloses wherein the step of determining that the collision is imminent is performed, by the one or more processors, faster than a human driver of ordinary skill while driving the subject vehicle (see paragraph [0033]: Collision avoidance control system 12 may be passive or operate in the background during normal vehicle operation. System 12 may become active when, for example, vehicle sensor data indicates likelihood of imminent collision, or a collision threat.).
With respect to dependent claims 7 and 17, Moshchuk discloses a computer vision sensor (e.g., a camera) 18, LIDAR sensor 20 (e.g., laser radar (LADAR) sensor), radar sensor 22, or other remote sensing device may obtain data allowing system 12 to determine or measure the relative location of the vehicle with respect to road features.
Moshchuk does not explicitly discloses the step of analyzing the sensor data comprises comparing measurement data from sensors of different technologies.
Balaghiasefi discloses a monitoring process 18 is represented, which comprises a grid map generator 13, a trajectory generator 14, a state space generator 15, an occupancy map generator 16 and a generator 17 for the common state space. All the map generators 13-15 only operate once at the start (if the vehicle is at the starting point of the target trajectory thereof) to generate the grid map, all drivable trajectories and the state space, the generators 16 and 17 operate for each change of inputs that could alter the occupancy map or the common state space. The monitoring algorithm 18 assesses or monitors the target trajectory of the vehicle in each case for the updated common state space at each time operation within the defined maneuver duration (the time period in which the vehicle is moving along the target trajectory thereof). If using the calculation of the degree of freedom the monitoring process or the monitoring algorithm 18 detects that the target trajectory of the vehicle has to be adjusted or completely newly determined, this is notified to the maneuver plan 12. (See paragraphs [0048] and [0049]).
It would have been obvious to one of ordinary skilled in the art, before the effective filing date of the invention to combine the system for mitigating a collision using avoidance logic of Moshchuk with the map generator comparison based on a monitoring process of Balaghiasefi in order to improve reliability and accuracy for meeting safety and performance objectives.
With respect to dependent claims 9 and 19, Moshchuk discloses wherein the step of selecting the particular sequence is performed fast enough to avoid or minimize the harm of the imminent collision (see paragraphs [0033] and [0035]: If vehicle is within a predefined distance to the object 60 that poses a collision threat, within a predefined velocity range, and within a predefined acceleration range, system 12 or other systems associated with vehicle 10 may provide pre-collision preparation and/or warnings to the driver of vehicle 10. The warnings to driver of vehicle 10 may be a signal, for example, an audible warning, a warning light or other form of warning. If the driver does not mitigate the collision threat, collision avoidance control system 12 may control the vehicle through collision imminent braking, automated steering control, or other controls or maneuvers in order to avoid object 60 or mitigate the impact between vehicle 10 and object 60. Automated braking may include common or typical braking (e.g., applying both front brakes, both rear brakes, or all brakes simultaneously), differential braking (e.g., applying brakes on each wheel independent of other wheel brakes), and/or another braking system or method.).
With respect to dependent claim 13, Moshchuk discloses one or more sensor(s) may be attached to or associated with the vehicle 10. A computer vision sensor (e.g., a camera) 18, LIDAR sensor 20 (e.g., laser radar (LADAR) sensor), radar sensor 22, or other remote sensing device may obtain data allowing system 12 to determine or measure the relative location of the vehicle with respect to road features, for example, other vehicles, lane markers(s), road shoulder(s), median barrier(s), edge of the road and other objects or features.
Moshchuk does not explicitly disclose wherein the sensors include multiple different technologies, and wherein the analyzing the sensor data includes merging data from at least two different technology types.
Balaghiasefi discloses that besides a controller 4, a device 20 comprises a LIDAR sensor 2, a camera 3 and a communications device 5. Using the sensor 2 and the camera 3, the surroundings of the ego-vehicle 10 are recorded. Information about plans (for example, planned target trajectories) of further vehicles that can influence the planning and the checking of the target trajectory of the ego-vehicle 10 can also be received by the ego-vehicle 10 by means of the communications device 5 (see paragraph [0076]).
It would have been obvious to one of ordinary skilled in the art, before the effective filing date of the invention to combine the system for mitigating a collision using avoidance logic of Moshchuk with the merged sensor data of Balaghiasefi in order to effectively derive collision free trajectories and target trajectory, prevent erroneous data for improved accuracy and safety.
With respect to dependent claim 14, Moshchuk discloses wherein the analyzing the sensor data is performed, by the processor, faster than a human driver of ordinary skill (see abstract: A processor recursively calculates a time-to-collision with the obstacle and an optimal collision avoidance path for avoiding the collision.).
With respect to dependent claim 15, Moshchuk discloses the step of implementing the particular action is performed, by the processor, more precisely than a human driver of ordinary skill.
Balaghiasefi discloses inputs relating to the path planning is applied to the MPC 92 for determining a desired road wheel angle 94 of the host vehicle for maintaining the vehicle on the optimum collision avoidance path. The determined difference between the desired road wheel angle and the actual road wheel angle from the summation block 95 is applied to a PID controller 98. It should be understood that any other controller that converts a road wheel angle request into corresponding steering torque request can be used here. In addition, a maximum allowable lateral acceleration 100 that is tolerable by the host vehicle for generating the optimum collision avoidance maneuver is provided to the PID controller in block 98. The PID controller 98 outputs a torque command 102 that is applied by a steering mechanism for adjusting the steering angle for maintaining the vehicle along the most updated optimum collision avoidance path. (See paragraph [0048]).
It would have been obvious to one of ordinary skilled in the art, before the effective filing date of the invention to combine the system for mitigating a collision using avoidance logic of Moshchuk with the PID controller of Balaghiasefi in order to provide a system that maintains an optimum path based on continuous feedback and control that precise path tracking than a human manually steering with no knowledge of the optimal curvature and TTC calculations.
With respect to dependent claim 18, Moshchuk discloses wherein the step of implementing the calculated strategy is performed faster and more precisely than a human driver of ordinary skill while driving the subject vehicle (see paragraph [0033]: FIG. 3 is a schematic diagram of the collision avoidance control system using steering control. Collision avoidance control system 12 may be passive or operate in the background during normal vehicle operation. System 12 may become active when, for example, vehicle sensor data indicates likelihood of imminent collision, or a collision threat. The warnings to driver of vehicle 10 may be a signal, for example, an audible warning, a warning light or other form of warning. If the driver does not mitigate the collision threat, collision avoidance control system 12 may control the vehicle through collision imminent braking, automated steering control, or other controls or maneuvers in order to avoid object 60 or mitigate the impact between vehicle 10 and object 60.).
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