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 .
Examiner's Note
Examiner has cited particular paragraphs / columns and line numbers or figures 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 from the applicant, in preparing the responses, to 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. Applicant is reminded that the Examiner is entitled to give the broadest reasonable interpretation to the language of the claims. Furthermore, the Examiner is not limited to Applicants’ definition which is not specifically set forth in the claims.
The instant application contains numerous claims which use “and/or” language. Claims using this construction will be interpreted as if writing using the preferred method of "at least one of A and B" consistent with Ex Parte Gross (13858627 (P.T.A.B. Feb. 27, 2017)). In some claims, the scope of the list of possible alternatives is unclear and further 112(b) rejections have been applied in the appropriate sections.
At least claims 1 and 8 contain contingent limitation modifying a method. The Patent Trial and Appeal Board has previously held that “giving the claim its broadest reasonable interpretation, ‘[i]f the condition for performing a contingent step is not satisfied, the performance recited by the step need not be carried out in order for the claimed method to be performed’". (MPEP § 2111.04(II) quoting Ex parte Schulhauser, Appeal 2013-007847 (PTAB April 28, 2016) at 10 (quotation omitted)). Consequently, the contingent limitations of method claims 1-17 may not have been given patentable weight.
Drawings
The drawings are objected to under 37 CFR 1.83(a) because they are unlabeled. Unlabeled rectangular box(es) shown in the drawings should be provided with descriptive text labels" per MPEP § 608.02(b) paragraph 6.22. Any structural detail that is essential for a proper understanding of the disclosed invention should be shown in the drawing. MPEP § 608.02(d). Applicant is particular directed to Figures 1-2.
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.
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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claim 1-2, 6, and 18-19 are rejected under 35 U.S.C. 103 as being unpatentable over Kleinehagenbrick (DE 102014226462 A1) in view of Kim et al. (US 20240140413 A1) (the combination of which will be referred to as 'combination Kleinehagenbrick' hereinafter).
Regarding claim 1, Kleinehagenbrick discloses a method for:
controlling an at least partially autonomous ego motor vehicle, (Kleinehagenbrick: ¶ 038; engine and optionally a brake 19 so that the vehicle) wherein the ego motor vehicle has a control device with a computing device, and a sensor device or communication device, the method comprises at least the following steps of: (Kleinehagenbrick: ¶ 038; data obtained from these sensors are sent to a main control unit) a. detecting, by means of the sensor device or the communication device, a relevant road user; (Kleinehagenbrick: ¶ 039; unit 20 receives the output of the various sensors and acquires various pieces of information on preceding vehicles) b. determining, by the computing device, a probability value in respect of the relevant road user leaving an anticipated travel route of the ego motor vehicle; c. comparing, by the computing device, the probability value with a defined limit value; if the probability value exceeds the limit value, the method furthermore comprises the following steps for controlling a speed of the ego motor vehicle: (Kleinehagenbrick: ¶ 040; predicts the future behavior of the preceding vehicles . . . to provide the probability of lane change based on various factors, and predicts lane change when the probability has exceeded a predetermined threshold) d. determining, by the computing device, a current shortest distance between the ego motor vehicle and the relevant road user; (Kleinehagenbrick: ¶ 003; the distances, the relative speed, and the relative angular positions and the relative lateral speeds between the preceding vehicles and the own vehicle are calculated from data obtained from the output of the sensor) e. determining, by the computing device, a safety measure which contains at . . . (Kleinehagenbrick: ¶ 006; When the vehicle approaches a preceding vehicle that travels slower than the own vehicle, the speed of the own vehicle is adjusted to the speed of the preceding vehicle while maintaining a predetermined distance between the two vehicles or the gap at a predetermined value.) f. determining, by the computing device, an ideal speed of the ego motor vehicle at which a predefined safety measure is attainable; (Kleinehagenbrick: ¶ 045; [When ego vehicle] loses the preceding vehicle, the previously set target speed (set speed) is restored, and this speed is normally higher than the target speed required to follow the preceding vehicle with constant gap. Therefore, by closing the gap when the preceding vehicle is expected to change lanes, the own vehicle is allowed to accelerate at a timing earlier than it is otherwise possible, so that decelerated acceleration can be avoided) g. determining, by the computing device, a speed-based adjustment value for acceleration and/or deceleration of the ego motor vehicle on a basis of the ideal speed determined in the step f; (Kleinehagenbrick: ¶ 060; vehicle P 1 has changed lanes, the preceding vehicle P 1 is no longer the target vehicle, so that the own vehicle E accelerates the determined initially set speed.) h. determining, by the computing device, a distance-based adjustment value for acceleration and/or deceleration of the ego motor vehicle on a basis of a hazard factor kept available by a storage unit; (Kleinehagenbrick: ¶ 013; a target gap calculating unit for selecting a preceding vehicle on the same lane as the own vehicle as a target vehicle under a predetermined condition, and determining a target gap between the own vehicle and the target vehicle) (Kleinehagenbrick: ¶ 056; a prediction is made about the behavior of the preceding vehicle when the preceding vehicle has already begun. . . the cut-out prediction unit 21 causes the evaluation unit 24 to instruct the target gap calculation unit 24 to redefine the gap, and the target speed unit 23 to calculate the target speed which will cause a decrease in the gap) i. selecting, by the computing device, between the speed-based adjustment value (Kleinehagenbrick: ¶ 045; [When ego vehicle] loses the preceding vehicle, the previously set target speed (set speed) is restored, and this speed is normally higher than the target speed required to follow the preceding vehicle with constant gap. Therefore, by closing the gap when the preceding vehicle is expected to change lanes, the own vehicle is allowed to accelerate at a timing earlier than it is otherwise possible, so that decelerated acceleration can be avoided) and the distance-based adjustment value; and (Kleinehagenbrick: ¶ 045; When the own vehicle follows the preceding vehicle while keeping a certain distance from the preceding vehicle (constant gap) and a cut-out (lane change to the right adjacent lane) by the preceding vehicle is not predicted by the cut-out prediction unit 21, the evaluation unit 24 instructs the target gap calculation unit 22 to keep the standard gap) j. controlling, by the control device, deceleration or acceleration of the ego motor vehicle on a basis of the speed-based adjustment value or the distance-based adjustment value selected in the step i. (Kleinehagenbrick: ¶ 049; target speed setting unit 17 thus receives a command for the target speed . . . and sends a corresponding command to, for example, the throttle valve 18 of the engine)
To the extent Kleinehagenbrick is silent about or does not explicitly teach: least one collision probability; Kim does teach:
which contains at least one collision probability; (Kim: ¶ 029; the collision prediction function 114 can determine a probability of collision for each target object and compare each probability to a threshold in order to determine if a collision with that target object is probable or likely to occur.)
Before the effective filling date of the claimed invention, it would have been obvious to one of ordinary skill in the art to combine the teachings of Kim with the teachings of Kleinehagenbrick because doing so would result in the predicable benefit of reducing the risk outcome resulting from path predictions associated with multiple candidate polynomial-paths . A person of ordinary skill in the art would obviously be taught or suggested that this would increase the likelihood of responding to dangerous situations with appropriate intensity while reducing the chance of vehicle over-response to low risk situations resulting in improved control performance, comfort, and safety. (Kim: ¶ 020-021).
Regarding claim 2, as detailed above, combination Kleinehagenbrick teaches the invention as detailed with respect to claim 1. Kleinehagenbrick further teaches:
wherein the probability value determined in the step b is a probability value in respect of turning off and/or a lane change of the relevant road user. (Kleinehagenbrick: ¶ 040; prediction unit 21 is configured to provide the probability of lane change based on various factors, and predicts lane change when the probability has exceeded a predetermined threshold.)
Regarding claim 6, as detailed above, combination Kleinehagenbrick teaches the invention as detailed with respect to claim 1. Kleinehagenbrick is silent about or does not explicitly teach:
wherein the at least one collision probability is determined on a basis of the following sub-steps: e.1.1 determining a turning off point of the relevant road user; e.1.2 determining at least one potential travel progression of the relevant road user; e.1.3 determining at least one potential travel progression of the ego motor vehicle; and e.1.4 determining a potential temporal progression of the shortest distance based on the turning off point determined in the step e.1.1, the potential travel progression of the relevant road user determined in the step e.1.2 and the potential travel progression of the ego motor vehicle determined in the step e.1.3; Kim does teach:
wherein the at least one collision probability is determined on a basis of the following sub-steps: e.1.1 determining a turning off point of the relevant road user; (Kim: ¶ 029; the collision prediction function 114 can determine a probability of collision for each target object and compare each probability to a threshold in order to determine if a collision with that target object is probable or likely to occur.) e.1.2 determining at least one potential travel progression of the relevant road user; (Kim: ¶ 027; target path prediction function 110 can also perform this process for each of multiple target objects, such as to generate polynomials for multiple target objects around or near the vehicle 100.) e.1.3 determining at least one potential travel progression of the ego motor vehicle; and (Kim: ¶ 028; predicted path of the vehicle 100 may be used by the target path prediction function) e.1.4 determining a potential temporal progression of the shortest distance based on the turning off point determined in the step e.1.1, the potential travel progression of the relevant road user determined in the step e.1.2 and the potential travel progression of the ego motor vehicle determined in the step e.1.3. (Kim: ¶ 028; path prediction function 112 can repeat this process over time as operation of the vehicle 100 continues, such as when the speed, acceleration/deceleration, or steering direction of the vehicle 100 changes).
Regarding claim 18, as detailed above, combination Kleinehagenbrick discloses the invention as detailed with respect to claim 1. Kleinehagenbrick further discloses:
control device comprising: a computing device; a storage unit; a sensor device and/or a communication device; and (Kleinehagenbrick: ¶ 038; data obtained from these sensors are sent to a main control unit) wherein the control device is configured for carrying out the method according to claim 1. (Kleinehagenbrick: ¶ 051; operation of the own vehicle is controlled/regulated by the travel control system)
Regarding claim 19, as detailed above, combination Kleinehagenbrick discloses the invention as detailed with respect to claim 1. Kleinehagenbrick further discloses:
motor vehicle comprising: a drive unit for providing a drive torque; a braking device for providing a braking torque; at least one propulsion wheel being torque-transmittingly coupled to said drive unit and said braking device, and by means of said drive unit and said braking device a propulsion of the motor vehicle is providable on a basis of the drive torque and respectively the braking torque; and (Kleinehagenbrick: ¶ 038; engine and optionally a brake 19 so that the vehicle) a controller, containing: a computing device; a storage unit; a sensor device and/or a communication device; and (Kleinehagenbrick: ¶ 038; data obtained from these sensors are sent to a main control unit) said controller is configured at least for controlling said drive unit in accordance with the method according to claim 1. (Kleinehagenbrick: ¶ 051; operation of the own vehicle is controlled/regulated by the travel control system)
Claims 3-5 and 14-15 are rejected under 35 U.S.C. 103 as being unpatentable over combination Kleinehagenbrick in view of Eagelberg et al. (US 20180120859 A1). As regards the individual claims:
Regarding claim 3, as detailed above, combination Kleinehagenbrick teaches the invention as detailed with respect to claim 1. Kleinehagenbrick further teaches:
wherein the step b comprises at least the following sub-steps: b.1 determining, by the computing device, a maneuvering intention of the relevant road user for carrying out a steering maneuver; (Kleinehagenbrick: ¶ 040; predicts the future behavior of the preceding vehicles . . . to provide the probability of lane change based on various factors, and predicts lane change when the probability has exceeded a predetermined threshold) . . . b.3 determining, by the computing device, the probability value on a basis of the maneuvering intention determined in the step b.1 and the following intention determined in the step b.2. (Kleinehagenbrick: ¶ 055; indicators determined by the context-based prediction unit can also be converted into probabilities.) (Kleinehagenbrick: ¶ 058; context-based prediction unit (CBP) 27 indicates a high possibility that the preceding vehicle P 1 is cutting out.)
To the extent Kleinehagenbrick is silent about or does not explicitly teach: b.2 determining, by the computing device, a following intention of the ego motor vehicle for following the steering maneuver of the relevant road user; and Eagelberg does teach:
b.2 determining, by the computing device, a following intention of the ego motor vehicle for following the steering maneuver of the relevant road user; and (Eagelberg: ¶ 222; if the predicted trajectory indicates that target vehicle 802 will remain on road 1202, host vehicle 200 may decelerate to maintain a safe distance between host vehicle 200 and target vehicle 802.).
Before the effective filling date of the claimed invention, it would have been obvious to one of ordinary skill in the art to combine the teachings of Eagelberg with the teachings of Kleinehagenbrick because applying confidence intervals to objects outside of the vehicle would predictably help identify unexpected data inconsistencies which can be used to trigger transferring control to the driver resulting in improved driver safety (Eagelberg: ¶ 138).
Regarding claim 4, as detailed above, combination Kleinehagenbrick in view of Eagelberg teaches the invention as detailed with respect to claim 3. Kleinehagenbrick further teaches:
wherein the maneuvering intention is determined as a maneuvering probability (Kleinehagenbrick: ¶ 040; predicts the future behavior of the preceding vehicles . . . to provide the probability of lane change based on various factors, and predicts lane change when the probability has exceeded a predetermined threshold)
While Eagelberg does not explicitly teach: and the following intention is determined as a following probability.; Eagelberg does teach:
A method in which a vehicle uses data about the ego vehicle and a target vehicle to determine if the vehicle ahead is exiting a lane or roadway or not based on observed external data and applies differing ego-vehicle control depending on the assessment. (Eagelberg: ¶ 222; if the predicted trajectory indicates that target vehicle 802 will exit road 1202, host vehicle 200 may accelerate to close a headway distance between host vehicle 200 and target vehicle 800 and/or may pass target vehicle 802 on the left. As another example, if the predicted trajectory indicates that target vehicle 802 will remain on road 1202, host vehicle 200 may decelerate to maintain a safe distance between host vehicle 200 and target vehicle 802.)
Before the effective filling date of the claimed invention, a person of ordinary skill in the art would be taught: and the following intention is determined as a following probability by Eagelberg’s teachings because a person of ordinary skill in the art would recognize that Eagelberg’s selecting between the differing vehicle control would require an assessment of which one is more likely or a threshold test based on probability. For Eagelberg to choose to decelerate or not, based on a determination if the leading vehicle is exiting or not, requires determining if the leading vehicle is exiting which, in turns, requiring the probability that the leading vehicle is exiting is above a threshold test.
Regarding claim 5, as detailed above, combination Kleinehagenbrick in view of Eagelberg teaches the invention as detailed with respect to claim 3. Kleinehagenbrick further teaches:
wherein the probability value is determined in the step b on a basis of at least one of the following factors: (Kleinehagenbrick: ¶ 055; indicators determined by the context-based prediction unit can also be converted into probabilities.) a turning off signal of the relevant road user and/or of the ego motor vehicle; (Kleinehagenbrick: ¶ 039; may include activation of turn signals)
And Eagelberg further teaches:
a transverse acceleration of the relevant road user and/or of the ego motor vehicle; (Eagelberg: ¶ 192; determined characteristic(s) of the target vehicle include a detected lateral motion of the target vehicle) a longitudinal acceleration of the relevant road user and/or of the ego motor vehicle; (Eagelberg: ¶ 192; determined characteristic(s) of the target vehicle includes a velocity of the target vehicle relative to the host vehicle,) navigation data of the relevant road user and/or of the ego motor vehicle; (Eagelberg: ¶ 144; expected curvature may be extracted from map data)
a communication message of the relevant road user; and (Kleinehagenbrick: ¶ 037; C2X device 15 that communicates with other vehicles) detecting a turning off possibility or a lane change possibility. (Eagelberg: ¶ 158; vehicle ahead of the autonomous vehicle may change lanes or exit a road and no longer be positioned ahead of the autonomous vehicle in the lane. The autonomous vehicle may therefore maintain or increase its rate of acceleration in anticipation of the departure of the other vehicle from the lane. However, if the vehicle is predicted to stay in the same lane as the autonomous vehicle past the split lane, the autonomous vehicle may maintain or decrease its rate of acceleration.)
Regarding claim 14, as detailed above, combination Kleinehagenbrick in view of Eagelberg teaches the invention as detailed with respect to claim 3. Eagelberg further teaches:
wherein the steering maneuver is turning off maneuver and/or a lane change maneuver. (Eagelberg: ¶ 158; vehicle ahead of the autonomous vehicle may change lanes or exit a road and no longer be positioned ahead of the autonomous vehicle in the lane. The autonomous vehicle may therefore maintain or increase its rate of acceleration in anticipation of the departure of the other vehicle from the lane. However, if the vehicle is predicted to stay in the same lane as the autonomous vehicle past the split lane, the autonomous vehicle may maintain or decrease its rate of acceleration.)
Regarding claim 15, as detailed above, combination Kleinehagenbrick in view of Eagelberg teaches the invention as detailed with respect to claim 5. Kleinehagenbrick further teaches:
wherein: the turning off signal is a light signal or a hand signal; and (Kleinehagenbrick: ¶ 039; data obtained from the vision sensor 11 may include activation of turn signals)
And Eagelberg further teaches:
detecting the turning off possibility or a lane change possibility on a basis of a traffic sign, a map and/or a camera recording. (Eagelberg: ¶ 112; wide FOV camera and process the images to detect vehicles . . .analyze images to identify objects moving in the image, such as vehicles changing lanes,)
Claims 7-11, 13, and 17 are rejected under 35 U.S.C. 103 as being unpatentable over combination Kleinehagenbrick as applied to claim 1 above, and further in view of Pazhayampallil et al. (US 20210261159 A1).
Regarding claim 7, as detailed above, combination Kleinehagenbrick teaches the invention as detailed with respect to claim 1. To the extent Kleinehagenbrick is silent about or does not explicitly teach:
wherein: in a step e.2 an action margin of the ego motor vehicle for a worst-case scenario is determined; and in the step e. the safety measure is determined on a basis of the action margin and the at least one collision probability. Pazhayampallil does teach:
wherein: in a step e.2 an action margin of the ego motor vehicle for a worst-case scenario is determined; and (Pazhayampallil: ¶ 046; autonomous vehicle can implement worst-case assumptions for the current speed of the object and future accelerations of the object to calculate a future state boundary that represents a ground area that is accessible to the object from the current time to the critical time in a worst-case scenario) (Pazhayampallil: ¶ 053; autonomous vehicle can multiply this calculated velocity of the object—relative to the autonomous vehicle—by an error margin, such as “1.5.”) in the step e. the safety measure is determined on a basis of the action margin and the at least one collision probability. (Pazhayampallil: ¶ 048; vehicle can: verify a very high confidence that the autonomous vehicle will avoid collision with the object—even given a most-adversarial action by the object) (Pazhayampallil: ¶ 038; vehicle can also add a safety margin to these stopping distance and/or stopping duration values, such as by: adding three meters to the stopping distance)
Before the effective filling date of the claimed invention, it would have been obvious to one of ordinary skill in the art to combine the teachings of Pazhayampallil with the teachings of Kleinehagenbrick because doing so would result in the predicable benefit of allowing the vehicle to minimize dynamic overcompensation by the ego vehicle resulting from path predictions utilizing high frequency sensor scans that can over magnify anticipated target-vehicle predictions (Pazhayampallil: ¶ 053).
Regarding claim 8, as detailed above, combination Kleinehagenbrick in view of Pazhayampallil teaches the invention as detailed with respect to claim 7. Pazhayampallil teaches:
wherein the action margin in the step e.2 includes a remaining distance (Pazhayampallil: ¶ 038; vehicle can also add a safety margin to these stopping distance and/or stopping duration values, such as by: adding three meters to the stopping distance) if the ego motor vehicle and the relevant road user come completely to a standstill (Pazhayampallil: ¶ 035; estimating a stopping duration, for the autonomous vehicle to reach a full stop, based on a speed of the autonomous vehicle at the first time) in the worst-case scenario. (Pazhayampallil: ¶ 048; autonomous vehicle can: implement worst-case assumptions for the current speed and future acceleration of the object in order to predict a worst-case ground area that may be accessible to the object from the current time)
Regarding claim 9, as detailed above, combination Kleinehagenbrick in view of Pazhayampallil teaches the invention as detailed with respect to claim 8. Pazhayampallil teaches:
wherein the action margin is determined for straight ahead travel of the relevant road user (Pazhayampallil: ¶ 035; estimating a stopping duration, for the autonomous vehicle to reach a full stop, based on a speed of the autonomous vehicle at the first time; and storing a critical time offset from the first time by the stopping duration.)
And Kleinehagenbrick teaches: and the remaining distance is a longitudinal distance. (Kleinehagenbrick: ¶ 003; the distances . . . between the preceding vehicles and the own vehicle are calculated from data obtained from the output of the sensor)
Regarding claim 10, as detailed above, combination Kleinehagenbrick in view of Pazhayampallil teaches the invention as detailed with respect to claim 7.Pazhayampallil teaches:
wherein the action margin is determined on a basis of at least one of the following parameters for the relevant road user and/or the ego motor vehicle: a driver type; (Pazhayampallil: ¶ 035; estimating a stopping duration, for the autonomous vehicle to reach a full stop, based on a speed of the autonomous vehicle at the first time; and storing a critical time offset from the first time by the stopping duration.) . . . (Pazhayampallil: ¶ 035; calculate an angular velocity (or “yaw”) of the object about its center) (Pazhayampallil: ¶ 089; angular motion in a yaw direction)
And Kleinehagenbrick teaches: . . . a type of vehicle; (Kleinehagenbrick: ¶ 039; the type of vehicle detected, such as passenger vehicles, buses, and trucks.) further road users; (Kleinehagenbrick: ¶ 039; information on preceding vehicles) road conditions; (Kleinehagenbrick: ¶ 036; vehicle estimates road surface qualities) weather conditions; and (Kleinehagenbrick: ¶ 043; prediction made . . . the environment of the own vehicle, and the weather conditions) current kinematic data including distance, speed, acceleration, (Kleinehagenbrick: ¶ 003; the distances, the relative speed, and the relative angular positions and the relative lateral speeds between the preceding vehicles and the own vehicle) yaw angle, and yaw rate of the ego vehicle and of the relevant vehicle. . . .
Regarding claim 11, as detailed above, combination Kleinehagenbrick in view of Pazhayampallil teaches the invention as detailed with respect to claim 7. Pazhayampallil teaches:
wherein the action margin includes a safety factor so that the action margin is definable by means of the safety factor between a minimum distance for which a crash is actually preventable in the worst-case scenario and a maximum distance. (Pazhayampallil: ¶ 038; vehicle can also add a safety margin . . . by multiplying these values by a safety margin (e.g., “1.2”).)
Regarding claim 13, as detailed above, combination Kleinehagenbrick in view of Pazhayampallil teaches the invention as detailed with respect to claim 7. Pazhayampallil teaches:
wherein the hazard factor is determined in accordance with the step h based on the collision probability or a critical proximity and the action margin (Pazhayampallil: ¶ 032; autonomous vehicle can also store [Examiner note: specific] object avoidance rules, such as a minimum temporal or spatial margin between the autonomous vehicle and a future state boundary of any object)
Regarding claim 17, as detailed above, combination Kleinehagenbrick in view of Pazhayampallil teaches the invention as detailed with respect to claim 7. Kim teaches
wherein the hazard factor is determined in accordance with the step h based on the at least one collision probability or a critical proximity and the action margin by means of a set of characteristic curves. (Kim: ¶¶ 028-029; predicted path of the vehicle 100 may be used by the target path prediction function 110 when generating at least some of the polynomials for one or more target objects . . . the generated polynomials for each target object and the vehicle 100 are provided to a collision prediction function 114, which generally operates to estimate whether a collision between the vehicle 100 and any target object).
Claims 12 and 16 are rejected under 35 U.S.C. 103 as being unpatentable over combination Kleinehagenbrick in view of Pazhayampallil as applied to claim 7 above, and further in view of Eagelberg et al. (US 20180120859 A1).
Regarding claim 12, as detailed above, combination Kleinehagenbrick in view of Pazhayampallil teaches the invention as detailed with respect to claim 1. Pazhayampallil teaches:
wherein in the step e the safety measure (Pazhayampallil: ¶ 072; vehicle can then calculate a navigational action that, when executed by the autonomous vehicle, maintains the autonomous vehicle within the access zone, such as: slowing the autonomous vehicle to reduce a rate of approach to an edge of the access zone if the autonomous vehicle is within the temporal or spatial margin of this edge)
To the extent Kleinehagenbrick is silent about or does not explicitly teach: is determined on a basis of map data and/or swarm data. Eagelberg does teach:
is determined on a basis of map data and/or swarm data. (Eagelberg: ¶ 135; unit 110 may consider additional sources of information to further develop a safety model for vehicle 200 . . . the detected road edges and barriers, and/or general road shape descriptions extracted from map data).
Before the effective filling date of the claimed invention, it would have been obvious to one of ordinary skill in the art to combine the teachings of Eagelberg with the teachings of Kleinehagenbrick because applying confidence intervals to objects outside of the vehicle would predictably help identify unexpected data inconsistencies which can be used to trigger transferring control to the driver resulting in improved driver safety (Eagelberg: ¶ 138).
Regarding claim 16, as detailed above, combination Kleinehagenbrick in view of Pazhayampallil in view of Eagelberg teaches the invention as detailed with respect to claim 12. Eagelberg teaches:
wherein the safety measure is the action margin (Eagelberg: ¶ 192; if the determined characteristic(s) of the target vehicle include a position of the target vehicle on the road forward of the host vehicle, the navigational action for the host vehicle may be determined to avoid a collision with the target vehicle, e.g., through acceleration or deceleration of the host vehicle.) and/or the at least one collision probability and is determined on the basis of the map data and/or the swarm data (Eagelberg: ¶ 144; expected curvature may be extracted from map data (e.g., data from map database 160), from road polynomials, from other vehicles' snail trails, from prior knowledge about the road, and the like. If the difference in curvature of the snail trail and the expected curvature of the road segment exceeds a predetermined threshold, processing unit 110 may determine that the leading vehicle is likely changing lanes.) by means of an artificial intelligence. (Eagelberg: ¶ 241; machine learning, the neural network may use labeled image 1406 and/or 1506 to improve lane mark labeling.)
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure Valverde et al. (US 20240367650 A1) which discloses methods for determining distance bounds for adaptive cruise control wherein an autonomous vehicle system can identify a second vehicle on the roadway that is traveling in front of the autonomous vehicle.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to CHARLES PALL whose telephone number is (571)272-5280. The examiner can normally be reached on M-F 9:30 - 18:30.
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/C.P./ Examiner, Art Unit 3663
/ANGELA Y ORTIZ/Supervisory Patent Examiner, Art Unit 3663