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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on July 29, 2025 has been entered.
Response to Amendment
Applicant submitted amendments and remarks on July 29, 2025. Therein, Applicant submitted substantive arguments. Claims 1 and 10 have been amended. No claims were added or cancelled.
The submitted claims are considered below.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
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.
Claims 1-3, 6-11, and 15-22 are rejected under 35 U.S.C. 103 as being unpatentable over Chen, et al. (U.S. Patent No. 10850739) in view of Rumler, et al. (U.S. Patent Application Publication No. 20220371585) and further in view of Foster, et al. (U.S. Patent Application Publication No. 20220348227).
Regarding claim 1, Chen, et al. teaches: A method, comprising: determining a current position of a vehicle in a lane of travel; (Fig. 5, Step (310), Step (510), Col. 8, lines 4-7: "…center reference line is generated by detecting the center of the current lane, which is detected from camera image data [determining current position of vehicle in travel lane].")
determining a lane biasing preference applicable to at least one of the vehicle or a driver of the vehicle; (Fig. 6, Fig. 5, Step (610), Col. 8, lines 30-38: "…the behavior of previous drivers that position their vehicle towards a lane edge before completing a lane change is detected and used to determine the bias [preference applicable to driver of vehicle]")
based on current weather at the vehicle's location; (Step (305), Col. 5, line 63 to Col. 6, lines 1-2: "FIG. 3 is a method for implementing a lane change using a bias offset by an autonomous vehicle. The autonomous vehicle is initialized at step (305). Initializing the autonomous vehicle may include [setting up lane biasing preference], […] calibrating the vehicle to the current ambient temperature and weather [based on current weather at the vehicle's location]")
calculating a distance offset relative to the current position of the vehicle resulting in a lane biasing position commensurate with the lane biasing preference; (Fig. 6, Fig. 5, Step (610), Col. 8, lines 30-32: "…determine a minimum and maximum biased distance [distance offset with respect to lane biasing preference] at step (610)." ; Col. 8, lines 38-44: "…minimum bias distance is a minimal change in vehicle position towards the lane boundary while the maximum bias distance is the maximum distance a vehicle may move within the current lane without crossing into the adjacent lane [offset distance calculation determination method].")
and autonomously or semi-autonomously controlling the vehicle to move the vehicle from the current position of the vehicle in the lane of travel to the lane biasing position (Chen, et al. Fig. 8, Step (840), Col. 9, lines 49-58: "…the autonomous vehicle will wait a short period of time, such as at least three seconds, before moving from the bias reference line to the adjacent lane center reference line [autonomously controlling vehicle to move from current position to lane biasing position].").
Chen, et al. does not teach wherein the lane biasing preference identifies a preferred position of the vehicle toward one side and off a center-line of the lane of travel; at one side and off the center-line of the lane of travel based on the calculated distance offset.
In a similar field of endeavor (customizable lane biasing for autonomous vehicles), Rumler, et al. teaches: wherein the lane biasing preference identifies a preferred position of the vehicle toward one side and off a center-line of the lane of travel; (Block (412), Fig. 3, Fig. 4, Paragraph [0046]: "…uses the lane-keeping system (152) [lane biasing system] to automatically position the vehicle at the offset position (218) along the offset path (216) when the vehicle (102) [preferred position to one side of vehicle] […] centerline (140) of the vehicle (102) is usually spaced apart from the center (198) of the lane (110) [off a center-line of lane of travel].")
at one side and off the center-line of the lane of travel based on the calculated distance offset (Block (412), Fig. 3, Fig. 4, Paragraph [0046]: "…uses the lane-keeping system (152) [lane biasing system] to automatically position the vehicle at the offset position (218) along the offset path (216) when the vehicle (102) [preferred position to one side of vehicle] […] centerline (140) of the vehicle (102) is usually spaced apart from the center (198) of the lane (110) [off a center-line of lane of travel]." ; Paragraph [0035]: "…position data (180) corresponding to an offset (202) of from thirty centimeters (30 cm) to one meter (1 m) away from the center (198) of the lane (110) [calculated distance offset].").
Therefore, it would have been obvious to one of the ordinary skill of the art before the effective filing date of the claimed invention to modify Chen, et al. to include the teaching of Rumler, et al. based on a reasonable expectation of success and motivation to improve the process of lane biasing for an autonomous vehicle based on operator preferences (Rumler, et al. Paragraphs [0001] and [0006]-[0007]).
The combination of Chen, et al. and Rumler, et al. does not teach and wherein the lane biasing preference is determined, at least in part, based on how current weather affects interactions between the vehicle and an object in the lane of travel.
In a similar field of endeavor (safe driving for autonomous vehicles), Foster, et al. teaches: and wherein the lane biasing preference is determined, at least in part, based on how current weather affects interactions between the vehicle and an object in the lane of travel (Paragraph [0080]: "…alter the positioning of the autonomous vehicle within its lane, that is to say adjust lane biasing, in light of surrounding vehicles or objects, as will be described in greater detail below [lane biasing preference based on interactions with objects in lane of travel]." ; Paragraph [0107]: "Autonomous vehicle may consider […] the prevailing weather condition [current weather]").
Therefore, it would have been obvious to one of the ordinary skill of the art before the effective filing date of the claimed invention to modify the combination of Chen, et al. and Rumler, et al. to include the teaching of Foster, et al. based on a reasonable expectation of success and motivation to improve the process of safe navigation for autonomous vehicles in varied road conditions (Foster, et al. Paragraphs [0069] – [0070]).
Regarding claim 2, Chen, et al., Rumler, et al., and Foster, et al. remain as applied to claim 1, and in a further embodiment, teach: The method of claim 1, wherein determining the lane biasing preference comprises obtaining the lane biasing preference from at least one of a vehicle profile, a passenger profile, or a driver profile (Chen, et al. Fig. 6, Step (640), Col. 8, lines 48-51: "…user preference at step (640) [driver profile - user preference].").
Regarding claim 3, Chen, et al., Rumler, et al., and Foster, et al. remain as applied to claim 2, and in a further embodiment, teach: The method of claim 2, wherein the vehicle profile comprises information reflecting at least one of physical vehicle characteristics or vehicle operating characteristics (Chen, et al. Fig. 3, Step (305), Col. 5, line 63 to Col. 6, lines 1-2: "…starting the autonomous vehicle, performing an initial system check, calibrating the vehicle to the current ambient temperature and weather, and calibrating any systems as needed at startup [vehicle operating characteristics].").
Regarding claim 6, Chen, et al., Rumler, et al., and Foster, et al. remain as applied to claim 1, and in a further embodiment, teach: The method of claim 1, wherein determining the lane biasing preference further comprises perceiving at least one of current driver conditions, current passenger conditions, current vehicle operating conditions, current environmental conditions, and current road conditions (Chen, et al. Step (310), Col. 6, lines 3-11: "…generate an object list and lane detection data at step (310). Perception data may include image data from one or more cameras, data received from one or more radars and lidar, and other data [perceiving environmental conditions from lidar sensors]." ; Chen, et al. Step (315), Col. 6, lines 14-17: "…receiving the object lesson lane detection data, the data processing system may plan a change from a center reference line of a current lane to a bias reference line of the current lane using a lane bias [lane detection data used to determine lane biasing]").
Regarding claim 7, Chen, et al., Rumler, et al., and Foster, et al. remain as applied to claim 6, and in a further embodiment, teach: The method of claim 6, wherein determining the lane biasing preference further comprises adjusting the lane biasing preference in accordance with the at least one of the current driver conditions, current passenger conditions, current vehicle operating conditions, current environmental conditions, and current road conditions (Chen, et al. Step (650), Col. 8, lines 52-58: "…bias point may be adjusted per speed of the present vehicle at step (650) [processor instructions adjusted according to current vehicle operating conditions].").
Regarding claim 8, Chen, et al., Rumler, et al., and Foster, et al. remain as applied to claim 6, and in a further embodiment, teach: The method of claim 6, wherein calculating the distance offset further comprises adjusting the distance offset in accordance with the at least one of the current driver conditions, current passenger conditions, current vehicle operating conditions, current environmental conditions, and current road conditions, (Chen, et al. Step (650), Col. 8, lines 52-58: "…bias point may be adjusted per speed of the present vehicle at step (650) [processor instructions adjusted according to current vehicle operating conditions].")
such that the adjusted distance offset still results in a lane biasing position commensurate with the lane biasing preference (Chen, et al. Step (640), Col. 8, lines 48-51: "…bias may be adjusted for a user preference at step (640) [adjustment due to preference set by user].").
Regarding claim 9, Chen, et al., Rumler, et al., and Foster, et al. remain as applied to claim 1, and in a further embodiment, teach: The method of claim 1, wherein the lane biasing preference reflects a preference based on historical lane biasing positions learned by the vehicle while being operated in one of a manual mode, a semi-autonomous mode, or a fully autonomous mode (Chen, et al. Fig. 14, Col. 10, lines 38-44: "…data processing system may generate a sampling of trajectories (1410) from the bias reference line to the center reference line of the adjacent lane [lane bias preference]. The data processing system may select the best trajectory (1420) along which the autonomous vehicle will navigate into the adjacent lane [processor executes lane biasing preference - operated in autonomous mode].").
Regarding claim 10, Chen, et al. teaches: A system, comprising: (Col. 4, lines 24-27: "…data processing system (125) [system]")
a processor; (Col. 5, lines 1-4: " processors [processor]")
and a memory unit including instructions that when executed cause the processor to: (Col. 5, lines 1-4: "…[processor], memory, and instructions stored in memory and executable by the one or more processors [memory unit executed by processor]")
learn, based on analyzing at least one of current and historical driver or passenger behaviors, a lane biasing preference; (Col. 8, lines 30-38: "…behavior of previous drivers that position their vehicle towards a lane edge before completing a lane change is detected and used to determine the bias at which the autonomous vehicle should navigate to before completing the lane change [historical driver behaviors - lane biasing preference].")
and current weather at the vehicle's location; (Col. 5, line 63 to Col. 6, lines 1-2: "FIG. 3 is a method for implementing a lane change using a bias offset by an autonomous vehicle. The autonomous vehicle is initialized at step (305). Initializing the autonomous vehicle may include [setting up lane biasing preference] […] calibrating the vehicle to the current ambient temperature and weather [based on current weather at the vehicle's location]")
calculate a distance offset relative to a current position of the vehicle resulting in a lane biasing position commensurate with the lane biasing preference; (Col. 8, lines 30-32: "…determine a minimum and maximum biased distance [distance offset with respect to lane biasing preference] at step (610)."; Col. 8, lines 38-44: "…minimum bias distance is a minimal change in vehicle position towards the lane boundary while the maximum bias distance is the maximum distance a vehicle may move within the current lane without crossing into the adjacent lane [offset distance calculation determination method].")
and autonomously or semi-autonomously control the vehicle to move from the current position of the vehicle in a lane of travel to the lane biasing position (Col. 9, lines 49-58: "…the autonomous vehicle will wait a short period of time, such as at least three seconds, before moving from the bias reference line to the adjacent lane center reference line [autonomously controlling vehicle to move from current position to lane biasing position].").
Chen, et al. does not teach wherein the lane biasing preference identifies a preferred position of a vehicle toward one side and off a center-line of a lane of travel based on the at least one of the current and historical driver or passenger behaviors; on one side and off the center-line of the lane of travel based on the calculated distance offset.
In a similar field of endeavor (customizable lane biasing for autonomous vehicles), Rumler, et al. teaches: wherein the lane biasing preference identifies a preferred position of a vehicle toward one side and off a center-line of a lane of travel based on the at least one of the current and historical driver or passenger behaviors, (Paragraph [0046]: "…the lane-keeping system (152) [lane biasing system] to automatically position the vehicle at the offset position (218) along the offset path (216) when the vehicle (102) [preferred position to one side of vehicle] […] centerline (140) of the vehicle (102) is usually spaced apart from the center (198) of the lane (110) [off a center-line of lane of travel]." ; Paragraph [0042]: "For example, in an embodiment as described herein, the server (104) generates trend data (250) by processing the lane-offset data (212) received from a plurality of the vehicles (102) [based on historical driver behavior data].")
on one side and off the center-line of the lane of travel based on the calculated distance offset (Paragraph [0046]: "…uses the lane-keeping system (152) [lane biasing system] to automatically position the vehicle at the offset position (218) along the offset path (216) when the vehicle (102) [preferred position to one side of vehicle] […] centerline (140) of the vehicle (102) is usually spaced apart from the center (198) of the lane (110) [off a center-line of lane of travel]." ; Paragraph [0035]: "…position data (180) corresponding to an offset (202) of from thirty centimeters (30 cm) to one meter (1 m) away from the center (198) of the lane (110) [calculated distance offset].").
Therefore, it would have been obvious to one of the ordinary skill of the art before the effective filing date of the claimed invention to modify Chen, et al. to include the teaching of Rumler, et al. based on a reasonable expectation of success and motivation to improve the process of lane biasing for an autonomous vehicle based on operator preferences (Rumler, et al. Paragraphs [0001] and [0006]-[0007]).
The combination of Chen, et al. and Rumler, et al. does not teach wherein the lane biasing preference is further determined, at least in part, based on how current weather affects interactions between the vehicle and an object in the lane of travel.
In a similar field of endeavor (safe driving for autonomous vehicles), Foster, et al. teaches: wherein the lane biasing preference is further determined, at least in part, based on how current weather affects interactions between the vehicle and an object in the lane of travel (Paragraph [0080]: "…alter the positioning of the autonomous vehicle within its lane, that is to say adjust lane biasing, in light of surrounding vehicles or objects, as will be described in greater detail below [lane biasing preference based on interactions with objects in lane of travel]." ; Paragraph [0107]: "Autonomous vehicle may consider […] the prevailing weather condition [current weather] ").
Therefore, it would have been obvious to one of the ordinary skill of the art before the effective filing date of the claimed invention to modify the combination of Chen, et al. and Rumler, et al. to include the teaching of Foster, et al. based on a reasonable expectation of success and motivation to improve the process of safe navigation for autonomous vehicles in varied road conditions (Foster, et al. Paragraphs [0069] – [0070]).
Regarding claim 11, Chen, et al., Rumler, et al., and Foster, et al. remain as applied to claim 10, and in a further embodiment, teach: The system of claim 10, wherein the instructions, when executed, further cause the processor to store the at least one of the current and historical driver or passenger behaviors in the memory unit as a profile (Chen, et al. Col. 5, lines 1-9: "…processors, memory, and instructions stored in memory and executable by the one or more processors [stored in memory unit and executed by processors] […] perception component plan actions such as lane changes, and generate commands to execute lane changes [current driver behaviors - taken from sensors].").
Regarding claim 15, Chen, et al., Rumler, et al., and Foster, et al. remain as applied to claim 10, and in a further embodiment, teach: The system of claim 10, wherein the instructions that when executed cause the processor to calculate the distance offset further causes the processor through at least one monitoring device, to perceive at least one of current driver conditions, current passenger conditions, current vehicle operating conditions, current environmental conditions, and current road conditions (Chen et al. Col. 6, lines 3-11: "…generate an object list and lane detection data at step (310). Perception data may include image data from one or more cameras, data received from one or more radars and lidar, and other data [monitoring device - environmental conditions from lidar sensors]." ; Chen, et al. Col. 6, lines 14-17: "….receiving the object lesson lane detection data, the data processing system may plan a change from a center reference line of a current lane to a bias reference line of the current lane using a lane bias [lane detection data used to determine lane biasing]").
Regarding claim 16, Chen, et al., Rumler, et al., and Foster, et al. remain as applied to claim 15, and in a further embodiment, teach: The system of claim 15, wherein determining the lane biasing preference further comprises adjusting the lane biasing preference in accordance with the at least one of the current driver conditions, current passenger conditions, current vehicle operating conditions, current environmental conditions, and current road conditions (Chen, et al. Col. 8, lines 52-58: "…bias point may be adjusted per speed of the present vehicle at step (650) [processor instructions adjusted according to current vehicle operating conditions].").
Regarding claim 17, Chen, et al., Rumler, et al., and Foster, et al. remain as applied to claim 16, and in a further embodiment, teach: The system of claim 16, wherein the instructions that when executed cause the processor to calculate the distance offset further causes the processor to adjust the distance offset in accordance with the at least one of the current driver conditions, current passenger conditions, current vehicle operating conditions, current environmental conditions, and current road conditions, (Chen, et al. Col. 8, lines 52-58: "…bias point may be adjusted per speed of the present vehicle at step (650) [processor instructions adjusted according to current vehicle operating conditions].")
such that the adjusted distance offset still results in a lane biasing position commensurate with the lane biasing preference (Chen, et al. Col. 8, lines 48-51: "…bias may be adjusted for a user preference at step (640) [adjustment due to preference set by user].").
Regarding claim 18, Chen, et al., Rumler, et al., and Foster, et al. remain as applied to claim 10, and in a further embodiment, teach: The system of claim 10, wherein the instructions that when executed cause the processor to learn the lane biasing preference, are executed while the vehicle is being operated in one of a manual mode, a semi-autonomous mode, or a fully autonomous mode (Chen, et al. Fig. 14, Col. 10, lines 38-44: "…data processing system may generate a sampling of trajectories (1410) from the bias reference line to the center reference line of the adjacent lane [lane bias preference]. The data processing system may select the best trajectory (1420) along which the autonomous vehicle will navigate into the adjacent lane [processor executes lane biasing preference - operated in autonomous mode].").
Regarding claim 19, Chen, et al., Rumler, et al., and Foster, et al. remain as applied to claim 1, and in a further embodiment, teach: The method of claim 1, wherein controlling the vehicle to move is controlled from the current position of the vehicle in the lane of travel to the lane biasing position in a subsequent lane of travel (Chen, et al. Col. 5, lines 41-42: "...autonomous vehicle. The actions may include navigating from the center of the lane to an adjacent lane using a bias distance [controlling vehicle to move from current vehicle in travel lane to biased position in subsequent lane]").
Regarding claim 20, Chen, et al., Rumler, et al., and Foster, et al. remain as applied to claim 1, and in a further embodiment, teach: The method of claim 1, wherein the lane biasing position is maintained for a determined period of time upon controlling the vehicle to move from the current position of the vehicle in the lane of travel to the lane biasing position (Chen, et al. Step (840), Fig. 8, Col. 9, lines 52-57: "…minimum period of time [minimum period of time] […] bias change in position at step (840) [vehicle controlled to move from current position in travel lane to lane biasing position].").
Regarding claim 21, Chen, et al., Rumler, et al., and Foster, et al. remain as applied to claim 10, and in a further embodiment, teach: The system of claim 10, wherein controlling the vehicle to move is controlled from the current position of the vehicle in the lane of travel to the lane biasing position in a subsequent lane of travel (Chen, et al. Col. 5, lines 41-42: "...plan actions for the autonomous vehicle. The actions may include navigating from the center of the lane to an adjacent lane using a bias distance [controlling vehicle to move from current vehicle in travel lane to biased position in subsequent lane]").
Regarding claim 22, Chen, et al., Rumler, et al., and Foster, et al. remain as applied to claim 10, and in a further embodiment, teach: The system of claim 10, wherein the lane biasing position is maintained for a determined period of time upon controlling the vehicle to move from the current position of the vehicle in the lane of travel to the lane biasing position (Chen, et al. Col. 12, lines 49-54: "…waiting for a minimum period of time [maintained for determined period of time] […] navigate the vehicle from the first reference line in the current lane to the biased reference line in current lane [controlling vehicle to move from current position in travel lane to lane biasing position]").
Claim 4 is rejected under 35 U.S.C. 103 as being unpatentable over Chen, et al. (U.S. Patent No. 10850739), Rumler, et al. (U.S. Patent Application Publication No. 20220371585), and Foster, et al. (U.S. Patent Application Publication No. 20220348227) in view of Dolgov, et al. (U.S. Patent No. 9090259).
Regarding claim 4, the combination of Chen, et al., Rumler, et al., and Foster, et al. teaches: The method of claim 2, wherein the driver profile comprises information reflecting physical driver characteristics (Chen, et al. Fig. 6, Step (610), Col. 8, lines 30-38: "…behavior of previous drivers that position their vehicle towards a lane edge before completing a lane change is detected and used to determine the bias at which the autonomous vehicle should navigate to before completing the lane change [physical driver characteristics].").
The combination of Chen, et al., Rumler, et al., and Foster, et al. does not teach and wherein the passenger profile comprises information reflecting physical passenger characteristics.
In a similar field of endeavor (controlling vehicle lateral lane positioning), Dolgov, et al. teaches: and wherein the passenger profile comprises information reflecting physical passenger characteristics (Col. 17, line 61 to Col. 18, lines 1-3: "…computing device may be configured to determine an optimized trajectory [profile based on data] […] constraints may include a smoothness constraint to prevent the vehicle from making sudden or jerky movements that may be noticeable by a passenger [physical passenger characteristics].").
Therefore, it would have been obvious to one of the ordinary skill of the art before the effective filing date of the claimed invention to modify the combination of Chen, et al. and Rumler, et al. to include the teaching of Dolgov, et al. based on a reasonable expectation of success and motivation to improve the process of controlling lateral lane positioning for a vehicle (Dolgov, et al. Col. 1, lines 32-50).
Claims 5 and 12-14 are rejected under 35 U.S.C. 103 as being unpatentable over Chen, et al. (U.S. Patent No. 10850739), Rumler, et al. (U.S. Patent Application Publication No. 20220371585), and Foster, et al. (U.S. Patent Application Publication No. 20220348227) in view of Oh (U.S. Patent Application Publication No. 20220234623).
Regarding claim 5, the combination of Chen, et al., Rumler, et al., and Foster, et al. does not teach the method of claim 1, wherein determining the lane biasing preference comprises executing a machine learning model to predict the lane biasing preference.
In a similar field of endeavor (biased driving systems), Oh teaches: The method of claim 1, wherein determining the lane biasing preference comprises executing a machine learning model to predict the lane biasing preference (Method (1100), Paragraph [0100]: "…steps (1120 to 1140) of learning and storing driving style for each driver [conducting machine learning] […] and steps (1150 to 1180) of performing biased driving based on results of execution in the steps (1120 to 1140) of learning and storing driving style for each driver and map shape information upon determining that the host vehicle is driving in the autonomous driving mode (Yes of 1110) [using model to predict lane biasing preference for each driver].").
Therefore, it would have been obvious to one of the ordinary skill of the art before the effective filing date of the claimed invention to modify the combination of Chen, et al., Rumler, et al., and Foster, et al. to include the teaching of Oh based on a reasonable expectation of success and motivation to improve a biased driving process in a vehicle can be controlled based on host vehicle recognition accuracy, nearby vehicle risk, driving style, road curvature, and road shape (Oh Paragraphs [0007] – [0010]).
Regarding claim 12, the combination of Chen, et al., Rumler, et al., and Foster, et al. does not teach the system of claim 10, wherein the instructions, when executed, further cause the processor to determine a currently-applicable lane biasing preference by executing a machine learning model for predicting the lane biasing preference in accordance with the at least one of the current and historical driver or passenger behaviors.
In a similar field of endeavor (biased driving systems), Oh teaches: The system of claim 10, wherein the instructions, when executed, further cause the processor to determine a currently-applicable lane biasing preference by executing a machine learning model for predicting the lane biasing preference in accordance with the at least one of the current and historical driver or passenger behaviors (Paragraph [0103]: "…biased driving system (200) [system with instructions] […] capable of outputting a final biased value as a learning result so as to be used for biasing using a nearby road shape and object information as input when a previously learned model is present in the autonomous driving mode [learned historical driver behavior].").
Therefore, it would have been obvious to one of the ordinary skill of the art before the effective filing date of the claimed invention to modify the combination of Chen, et al., Rumler, et al., and Foster, et al. to include the teaching of Oh based on a reasonable expectation of success and motivation to improve a biased driving process in a vehicle can be controlled based on host vehicle recognition accuracy, nearby vehicle risk, driving style, road curvature, and road shape (Oh Paragraphs [0007] – [0010]).
Regarding claim 13, Chen, et al., Rumler, et al., Foster, et al., and Oh remain as applied to claim 12, and in a further embodiment, teach: The system of claim 12, wherein the instructions, when executed, further cause the processor to determine, via at least one monitoring device, physical driver characteristics or physical passenger characteristics (Chen, et al. Col. 8, lines 30-38: "…behavior of previous drivers that position their vehicle towards a lane edge before completing a lane change is detected and used to determine the bias at which the autonomous vehicle should navigate to before completing the lane change [physical driver characteristics].").
Regarding claim 14, Chen, et al., Rumler, et al., Foster, et al., and Oh remain as applied to claim 13, and in a further embodiment, teach: The system of claim 13, wherein the instructions, when executed, further cause the processor to determine the currently-applicable lane biasing preference by executing the machine learning model for predicting the lane biasing preference in accordance with the at least one of the current and historical driver or passenger behaviors, (Oh Paragraph [0096]: "…extraction module (262) [processor] may reflect driving style of the host vehicle driver when creating an imaginary line of an object, and learns road phenomenon and object information, driver information, and a final biased value [learning model - lane biasing preference - historical driver behaviors]")
and adjusted to account for at least one of the physical driver characteristics the physical passenger characteristics, or physical vehicle characteristics (Oh Paragraph [0096]: "…variation of the lane width to derive the learned final biased value in a situation similar to the learned situation may be set as a basic offset [adjustment value - based on previously discussed driver characteristics]").
Response to Arguments
Applicant’s arguments with respect to claims 1 and 10 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Applicant asserted that amended claims 1 and 10 were patentable over Chen, et al. (U.S. Patent No. 10850739) in view of Rumler, et al. (U.S. Patent Application Publication No. 20220371585) because the references did not meet the claim limitation “and wherein the lane biasing preference is determined, at least in part, based on how current weather affects interactions between the vehicle and an object in the lane of travel”. Please note that Foster, et al. (U.S. Patent Application Publication No. 20220348227) was cited in order to teach this feature. In Foster, et al., an autonomous vehicle control system has the ability to “…alter the positioning of the autonomous vehicle within its lane, that is to say adjust lane biasing, in light of surrounding vehicles or objects” (Paragraph [0080]) through the process of “…consider […] the prevailing weather condition” in the travel region (Paragraph [0107]). Subsequently, it would have been obvious to combine Foster, et al. with Chen, et al. and Rumler, et al. because Chen, et al. teaches the process of determining a lane biasing preference relative to the driver of a vehicle (Figs. 5-6, Step (610), Col. 8, lines 30-36) and Rumler, et al. teaches a lane biasing procedure in which the vehicle travels toward one side and off a center-line of the lane of travel (Block (412), Fig. 3, Fig. 4, Paragraph [0035] and [0046]).
Therefore, it can be concluded that since the combination of Chen, et al., Rumler, et al., and Foster, et al. reads on the claim limitation “and wherein the lane biasing preference is determined, at least in part, based on how current weather affects interactions between the vehicle and an object in the lane of travel”, as stated in amended claims 1 and 20, the arguments presented by the Applicant are not persuasive, and the rejection is maintained.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Mujumdar, et al. (U.S. Patent No. 11753027) describes a vehicle lateral-control system with adjustable parameters. The system includes a controller circuit which receives data from a driver-monitoring sensor and vehicle sensors and uses the data to determine lateral-steering parameters of the vehicle based on the vehicle lateral-response data.
Applicant is considered to have implicit knowledge of the entire disclosure once a reference has been cited. Therefore, any previously cited figures, columns and lines should not be considered to limit the references in any way. The entire reference must be taken as a whole; accordingly, the Examiner contends that the art supports the rejection of the claims and the rejection is maintained.
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/TORRENCE S MARUNDA II/Examiner, Art Unit 3663
/ANGELA Y ORTIZ/Supervisory Patent Examiner, Art Unit 3663