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 .
This is a Non-Final rejection on the merits of this application. Claims 26, 28-37, and 39-47 are pending and addressed below.
Continued Examination Under 37 CFR 1.114
1. 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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 10/31/2025 has been entered.
Response to Arguments
2. Regarding the rejection made under 35 USC 102/103, the Applicant’s arguments have been fully considered but are not persuasive.
Applicant argues on page 9 of the remarks that Nariyambut Murali fails to disclose determining a reason for the change of the position of the vehicle based on the auxiliary data. Applicant further argues on page 10 that the last sentence of paragraph [0043] of Nariyambut Murali only states some reasons why the vehicle may be permitted to leave the current lane, but nothing in this sentence disclose that the vehicle determines a reason for the change of the position of the vehicle and it does not do this based on the auxiliary data. The Examiner respectfully disagrees. Applicant’s specification [0092-0093] states that “the presence of lane markings in image or data received may be indicative that the vehicle 300 is beginning to stray outside the lane 116…may also be indicative that the position of the vehicle 300 in the lane has changed for some other reason, e.g. in preparation for making a turn, or to avoid an obstacle.” Thus, the reason refers to the determination that the vehicle is straying outside the lane or making a turn or avoiding an obstacle. Nariyambut Murali states reasons why the vehicle may be permitted to leave the current lane such as lane changes or obstacle avoidance which is a reason. Nariyambut Murali states “for example, if the distance is trending away from a center of a lane or toward a lane marking, the lane component 104 may determine a change in a driving path to move the vehicle toward a center of the lane. As another example, if the distance is trending away from the center of the lane a warning may be provided to a human driver to recommend moving back toward a center of the lane.” (see at least [0034]). Nariyambut Murali further states “the driving maneuver component 508 may determine one or more driving maneuvers to be performed by the vehicle and/or to be suggested to a vehicle controller or human driver. In one embodiment, the driving maneuver component 508 determines a driving maneuver that places or maintains the vehicle centered between the lane markings…For example, in one embodiment, the driving maneuver component 508 may determine a driving path that places the vehicle near a left or right side of the lane to avoid debris, increase a distance between the parent vehicle and a neighboring vehicle, and/or perform other positioning maneuvers within a lane...Obviously, in case of imminent collisions, lane changes, or the like, the driving maneuver component 508 may allow the vehicle to leave the current lane.” (see at least [0043]). Additionally, Nariyambut Murali teaches using auxiliary data to assist with determining the reason for leaving the lane. Nariyambut Murali states “the vehicle control system 100 may also include one or more sensor systems/devices for detecting a presence of nearby objects, lane markers, and/or or determining a location of a parent vehicle (e.g., a vehicle that includes the vehicle control system 100). For example, the vehicle control system 100 may include radar systems 106, one or more LIDAR systems 108, one or more camera systems 110, a global positioning system (GPS) 112, and/or ultra sound systems 114” (see at least [0019]). Thus, Nariyambut Murali teaches determining a reason for the change of the position of the vehicle based on the auxiliary data.
Applicant further argues on page 10 of the remarks that Nariyambut Murali fails to disclose distinguishing between whether a change of the position of the vehicle in the lane in preparation for making a turn or avoiding an obstacle and a change of the position of the vehicle indicative that the vehicle is at risk of straying outside the lane as recited in claim 26. The Examiner respectfully disagrees. Nariyambut Murali states “for example, if the distance is trending away from a center of a lane or toward a lane marking, the lane component 104 may determine a change in a driving path to move the vehicle toward a center of the lane.” (see at least [0034]). Nariyambut Murali further states “the driving maneuver component 508 may determine one or more driving maneuvers to be performed by the vehicle and/or to be suggested to a vehicle controller or human driver. In one embodiment, the driving maneuver component 508 determines a driving maneuver that places or maintains the vehicle centered between the lane markings…For example, in one embodiment, the driving maneuver component 508 may determine a driving path that places the vehicle near a left or right side of the lane to avoid debris, increase a distance between the parent vehicle and a neighboring vehicle, and/or perform other positioning maneuvers within a lane...Obviously, in case of imminent collisions, lane changes, or the like, the driving maneuver component 508 may allow the vehicle to leave the current lane.” (see at least [0043]). Thus, Nariyambut Murali teaches distinguishing between different scenarios such as the vehicle trending away from a center of a lane and allowing the vehicle to leave the current lane in a case of imminent collisions and/or lane changes (making a turn or avoiding obstacles).
Therefore, the prior art meets the claim limitations, and the Applicant’s arguments are not persuasive.
Claim Objections
3. Claim 40 is objected to because of the following informalities:
In claim 40, the phrase “according to any claim 37” should be replaced with “according to claim 37” to remove the term any since there is only one claim 37.
Appropriate correction is required.
Claim Interpretation
4. The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
5. The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
6. This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are:
“image processing subsystem is configured to” in claims 31, 34, and 42.
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
A review of the specification (citation to US pub. No. 20230286500) shows the following appears to be the corresponding structure described in the specification for the 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph limitations:
“image processing subsystem” in claims 31, 34, and 42 corresponds to image processing subsystems (e.g. processing hardware and/or software and/or firmware) (see at least [0077]). Examiner is interpreting “image processing subsystem” as a software module running on a processor.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Claim Rejections - 35 USC § 102 and/or 103
7. In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
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.
8. Claims 26, 28-31, 37, 39-43, and 45-47 is/are rejected under 35 U.S.C. 102(a)(2)/(a)(1) as anticipated by or, in the alternative, under 35 U.S.C. 103 as obvious over Nariyambut Murali et al. (US 20170267177, hereinafter Nariyambut Murali).
Regarding claim 26, Nariyambut Murali teaches a system for monitoring a position of a vehicle in a lane of a road (see at least Fig. 6 and [0012]: “Applicants have developed systems, methods, and devices for detecting lane markings and/or determining a position of a vehicle with respect to lane markings.”), the system comprising:
a processor (see at least Fig. 1 and [0065]: “Example 17 is computer readable storage media storing instructions that, when executed by one or more processors, cause the processors to receive data from both a first camera and a second camera, wherein the first camera is positioned on a first side of a vehicle and the second camera is positioned on a second side of the vehicle opposite the first side.”);
a first camera configured to output first image data relating to a surface of the road on a first side of the vehicle (see at least Figs. 1, 2 and [0024]: “The camera systems 110 may include cameras positioned on opposite sides of the vehicle so that lane markings on each side of the vehicle can be detected.”; [0026]: “The vehicle 202 may include a plurality of laterally positioned cameras that are oriented to obtain images of ground regions near the vehicle 202. For example, a camera (not shown) positioned on a left side of the vehicle 202 may obtain images of the ground in the left side region 208 (indicated by dashed lines) and a camera (not shown) positioned on a right side of the vehicle 202 may obtain images of the ground in the right side region 210 (indicated by dashed lines).”);
a second camera configured to output second image data relating to a surface of the road on a second side of the vehicle (see at least Figs. 1, 2 and [0024]: “The camera systems 110 may include cameras positioned on opposite sides of the vehicle so that lane markings on each side of the vehicle can be detected.”; [0026]: “The vehicle 202 may include a plurality of laterally positioned cameras that are oriented to obtain images of ground regions near the vehicle 202. For example, a camera (not shown) positioned on a left side of the vehicle 202 may obtain images of the ground in the left side region 208 (indicated by dashed lines) and a camera (not shown) positioned on a right side of the vehicle 202 may obtain images of the ground in the right side region 210 (indicated by dashed lines).”),
wherein the processor is configured to:
receive auxiliary data indicating whether or not the vehicle is approaching a turn or obstacle in the road (see at least [0019]: “The vehicle control system 100 may also include one or more sensor systems/devices for detecting a presence of nearby objects, lane markers, and/or or determining a location of a parent vehicle (e.g., a vehicle that includes the vehicle control system 100). For example, the vehicle control system 100 may include radar systems 106, one or more LIDAR systems 108, one or more camera systems 110, a global positioning system (GPS) 112, and/or ultra sound systems 114. The vehicle control system 100 may include a data store 116 for storing relevant or useful data for navigation and safety such as map data, driving history, or other data. The vehicle control system 100 may also include a transceiver 118 for wireless communication with a mobile or wireless network, other vehicles, infrastructure, or any other communication system.”);
infer, estimate or determine the position of the vehicle relative to a lane marking detected in the image data from one or more of the cameras (see at least [0026]: “The side cameras may periodically obtain images of the ground regions 208 and 210 near the vehicle and the vehicle 202 (such as the lane component 104 of the vehicle 202) may use this information to determine a position of the vehicle 202 within a lane of the roadway 200. The positions or distances determined by the lane component 104 may include distances between lane markings 204 and 206 and a side panel of the vehicle 202 or distances between lane markings 204 and 206 and an axis 212 (e.g., the long axis) of the vehicle 202.”);
detect a change of the position of the vehicle relative to the lane marking (see at least [0034]: “The lane component 104 (or an automated driving/assistance system 100) determines at 408 a driving maneuver or a warning based on the filtered and tracked distance at 406. For example, if the distance is trending away from a center of a lane or toward a lane marking, the lane component 104 may determine a change in a driving path to move the vehicle toward a center of the lane. As another example, if the distance is trending away from the center of the lane a warning may be provided to a human driver to recommend moving back toward a center of the lane.”); and
determine, a reason for the change of the position of the vehicle in the lane based on the auxiliary data, wherein the processor is configured to distinguish between a change of the position of the vehicle in the lane in preparation for making a turn or avoiding an obstacle and a change of the position of the vehicle indicative that the vehicle is at risk of straying outside the lane (see at least [0028]: “Based on the accurate positioning, a driving path 214 may be calculated to place the vehicle 202 within the center of a lane or to maintain the vehicle 202 at or near a center of the lane. The driving path 214 may be computed to keep the vehicle within the lane and thus minimize risk of accidents with other vehicles in other lanes or risk of driving off of the roadway 200. Driving maneuvers may be determined based on the current position in the lane as well as any other available information, such as perception information from a forward and/or rear facing camera, LIDAR system 108, radar system 106, map data, driving history, or any other data. For example, a current position of the vehicle 202 within the lane as well as a curvature of the lane or roadway 200 may be used to determine a future driving path for the vehicle 202.”; [0043]: “The driving maneuver component 508 may determine one or more driving maneuvers to be performed by the vehicle and/or to be suggested to a vehicle controller or human driver. In one embodiment, the driving maneuver component 508 determines a driving maneuver that places or maintains the vehicle centered between the lane markings…For example, in one embodiment, the driving maneuver component 508 may determine a driving path that places the vehicle near a left or right side of the lane to avoid debris, increase a distance between the parent vehicle and a neighboring vehicle, and/or perform other positioning maneuvers within a lane...Obviously, in case of imminent collisions, lane changes, or the like, the driving maneuver component 508 may allow the vehicle to leave the current lane.”).
wherein responsive to a determination that the change of the position of the vehicle in the lane is indicative that the vehicle is at risk of straying outside the lane, the processor performs a first operation (see at least Fig. 1 and [0018]: “Referring now to the figures, FIG. 1 illustrates an example vehicle control system 100 that may be used to detect lanes, including lane markings or boundaries. The vehicle control system 100 may include an automated driving/assistance system 102. The automated driving/assistance system 102 may be used to automate or control operation of a vehicle or to provide assistance to a human driver…The automated driving/assistance system 102 may include a lane component 104 that uses a neural network, or other model or algorithm, to detect a lane marking or boundary and/or to determine a position of the vehicle in relation to the lane.”); [0028]: “Based on the accurate positioning, a driving path 214 may be calculated to place the vehicle 202 within the center of a lane or to maintain the vehicle 202 at or near a center of the lane. The driving path 214 may be computed to keep the vehicle within the lane and thus minimize risk of accidents with other vehicles in other lanes or risk of driving off of the roadway 200. Driving maneuvers may be determined based on the current position in the lane as well as any other available information, such as perception information from a forward and/or rear facing camera, LIDAR system 108, radar system 106, map data, driving history, or any other data. For example, a current position of the vehicle 202 within the lane as well as a curvature of the lane or roadway 200 may be used to determine a future driving path for the vehicle 202.”; [0034]: “In one embodiment, the lane component 104 filters at 406 the output using a state-space estimation technique and tracks the changes to provide information useful for balancing a vehicle in a lane, and/or for various active safety applications. The lane component 104 (or an automated driving/assistance system 100) determines at 408 a driving maneuver or a warning based on the filtered and tracked distance at 406. For example, if the distance is trending away from a center of a lane or toward a lane marking, the lane component 104 may determine a change in a driving path to move the vehicle toward a center of the lane. As another example, if the distance is trending away from the center of the lane a warning may be provided to a human driver to recommend moving back toward a center of the lane.”); and
wherein responsive to a determination that the change of the position of the vehicle in the lane is in preparation for making the turn or avoiding the obstacle, the processor does not perform the first operation (see at least [0043]: “The driving maneuver component 508 may determine one or more driving maneuvers to be performed by the vehicle and/or to be suggested to a vehicle controller or human driver...Obviously, in case of imminent collisions, lane changes, or the like, the driving maneuver component 508 may allow the vehicle to leave the current lane.” Nariyambut Murali teaches allowing the vehicle to leave the current lane which is suppressing the lane centering action (does not perform the first operation) when in a case of imminent collisions and/or lane changes (making a turn or avoiding obstacles).).
Nariyambut Murali (P. [0034]) teaches “for example, if the distance is trending away from a center of a lane or toward a lane marking, the lane component 104 may determine a change in a driving path to move the vehicle toward a center of the lane. As another example, if the distance is trending away from the center of the lane a warning may be provided to a human driver to recommend moving back toward a center of the lane.” Nariyambut Murali (P. [0043]) further teaches that “the driving maneuver component 508 may determine one or more driving maneuvers to be performed by the vehicle and/or to be suggested to a vehicle controller or human driver. In one embodiment, the driving maneuver component 508 determines a driving maneuver that places or maintains the vehicle centered between the lane markings…For example, in one embodiment, the driving maneuver component 508 may determine a driving path that places the vehicle near a left or right side of the lane to avoid debris, increase a distance between the parent vehicle and a neighboring vehicle, and/or perform other positioning maneuvers within a lane...Obviously, in case of imminent collisions, lane changes, or the like, the driving maneuver component 508 may allow the vehicle to leave the current lane.” Hence, Nariyambut Murali teaches determining the reason and logic for the change of the position of the vehicle in the lane and provide a warning and/or control the vehicle.
Alternatively, even it is it not implicitly taught by Nariyambut Murali, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to determine a reason for the change of the position of the vehicle in the lane in order to suppress the lane centering action to avoid a collision with an obstacle.
Regarding claim 28, Nariyambut Murali teaches the limitations of claim 26. Nariyambut Murali further teaches wherein the auxiliary data is received from a forward-facing camera provided on the vehicle or from a mapping, location or route planning system (see at least Fig. 1 and [0028]: “Driving maneuvers may be determined based on the current position in the lane as well as any other available information, such as perception information from a forward and/or rear facing camera, LIDAR system 108, radar system 106, map data, driving history, or any other data. For example, a current position of the vehicle 202 within the lane as well as a curvature of the lane or roadway 200 may be used to determine a future driving path for the vehicle 202.”; [0032]: “In one embodiment, a neural network may be used to determine the distance at 404 between the vehicle and lane markings. In one embodiment, the lane component 104 may determine a position in a lane based on distances from markings on either side of the vehicle.”).
Regarding claim 29, Nariyambut Murali teaches the limitations of claim 26. Nariyambut Murali further teaches wherein the first operation comprises: outputting a control signal to one or more of: a driver warning system; a brake control subsystem; a throttle control subsystem; and a steering control subsystem (see at least Fig. 1 and [0018]: “Referring now to the figures, FIG. 1 illustrates an example vehicle control system 100 that may be used to detect lanes, including lane markings or boundaries. The vehicle control system 100 may include an automated driving/assistance system 102. The automated driving/assistance system 102 may be used to automate or control operation of a vehicle or to provide assistance to a human driver. For example, the automated driving/assistance system 102 may control one or more of braking, steering, acceleration, lights, alerts, driver notifications, radio, or any other auxiliary systems of the vehicle. In another example, the automated driving/assistance system 102 may not be able to provide any control of the driving (e.g., steering, acceleration, or braking), but may provide notifications and alerts to assist a human driver in driving safely. The automated driving/assistance system 102 may include a lane component 104 that uses a neural network, or other model or algorithm, to detect a lane marking or boundary and/or to determine a position of the vehicle in relation to the lane. In one embodiment, the automated driving/assistance system 102 may determine a driving maneuver or driving path to maintain or place the vehicle at or near a center of the lane.”).
Regarding claim 30, Nariyambut Murali teaches the limitations of claim 26. Nariyambut Murali further teaches wherein the processor is configured to determine a value representative of a distance and/or between the vehicle and a lane marking that delimits a boundary of the lane based on the first or second image data (see at least [0029]: “FIG. 3 depicts an example image 300 captured by a side view camera. The image 300 shows a surface 302 of a roadway with a lane marking 304. The image 300 has a pixel height of N and a pixel width of M. In one embodiment, the lane component 104 may receive the image 300 and determine a distance 306 from a bottom of the image 300 to the lane marking 304. The distance 306 may be determined as a pixel value (e.g., a pixel height) or may be determined based on a distance measurement unit such as feet or meters. In one embodiment, a distance 306 in pixels may be converted to distance using a preconfigured function or calculation. For example, a linear or parabolic function based on the location and orientation of the camera may be used to convert a pixel length or height into feet or meters. In one embodiment, the lane component 104 may use a neural network to determine the distance 306. In one embodiment, if a lane marking 304 is not present, the lane component 104 may return a null value to indicate that there is no lane marking in the image.”).
Regarding claim 31, Nariyambut Murali teaches the limitations of claim 26. Nariyambut Murali further teaches wherein:
the first and second cameras are each provided or associated with an image processing subsystem (see at least Fig. 1 and [0023] “In one embodiment, the camera systems 110 may include a plurality of cameras. For example, the camera systems 110 may include cameras facing in different directions to provide different views and different fields of view for areas near or around the vehicle.”);
the image processing subsystem is configured to detect the presence and/or position of a lane marking in the image data provided by the respective camera and to transmit data indicative of the presence and/or position of the lane marking to the processor (see at least Figs. 1, 2, and [0023]: “In one embodiment, the camera systems 110 may include a plurality of cameras. For example, the camera systems 110 may include cameras facing in different directions to provide different views and different fields of view for areas near or around the vehicle.”; [0024]: “The camera systems 110 may include cameras positioned on opposite sides of the vehicle so that lane markings on each side of the vehicle can be detected. In one embodiment, the side cameras may be angled downward to provide information about a region on the ground immediately next to the vehicle. For example, the camera may be oriented to face in a direction perpendicular, or substantially perpendicular, to an axis of the vehicle and with a downward angle to provide a view of the ground horizontally neighboring a wheel or side panel of the vehicle. Thus, if a lane marking is right next to the side of the vehicle, the marking may be shown within an image captured by a side camera.”; [0029]: “In one embodiment, the lane component 104 may receive the image 300 and determine a distance 306 from a bottom of the image 300 to the lane marking 304.”); and
the processor is configured to determine a value representative of a distance and/or an angle between the vehicle and the lane marking based on the data indicative of the presence and/or position of the lane marking (see at least Fig. 4 and [0029]: “In one embodiment, the lane component 104 may receive the image 300 and determine a distance 306 from a bottom of the image 300 to the lane marking 304. The distance 306 may be determined as a pixel value (e.g., a pixel height) or may be determined based on a distance measurement unit such as feet or meters. In one embodiment, a distance 306 in pixels may be converted to distance using a preconfigured function or calculation. For example, a linear or parabolic function based on the location and orientation of the camera may be used to convert a pixel length or height into feet or meters. In one embodiment, the lane component 104 may use a neural network to determine the distance 306. In one embodiment, if a lane marking 304 is not present, the lane component 104 may return a null value to indicate that there is no lane marking in the image.”).
Regarding claim 37, Nariyambut Murali teaches a vehicle comprising a system for monitoring a position of the vehicle in a lane of a road (see at least Figs. 1 and 6), wherein the system comprises:
a processor (see at least Fig. 1 and [0065]: “Example 17 is computer readable storage media storing instructions that, when executed by one or more processors, cause the processors to receive data from both a first camera and a second camera, wherein the first camera is positioned on a first side of a vehicle and the second camera is positioned on a second side of the vehicle opposite the first side.”);
a first camera positioned on a first side of the vehicle in a downward-facing orientation to provide first image data relating to a surface of the road on the first side of the vehicle (see at least Figs. 1, 2 and [0024]: “The camera systems 110 may include cameras positioned on opposite sides of the vehicle so that lane markings on each side of the vehicle can be detected. In one embodiment, the side cameras may be angled downward to provide information about a region on the ground immediately next to the vehicle. For example, the camera may be oriented to face in a direction perpendicular, or substantially perpendicular, to an axis of the vehicle and with a downward angle to provide a view of the ground horizontally neighboring a wheel or side panel of the vehicle.”; [0026]: “The vehicle 202 may include a plurality of laterally positioned cameras that are oriented to obtain images of ground regions near the vehicle 202. For example, a camera (not shown) positioned on a left side of the vehicle 202 may obtain images of the ground in the left side region 208 (indicated by dashed lines) and a camera (not shown) positioned on a right side of the vehicle 202 may obtain images of the ground in the right side region 210 (indicated by dashed lines).”);
a second camera positioned on a second side of the vehicle in a downward-facing orientation to provide second image data relating to a surface of the road on a second side of the vehicle (see at least Figs. 1, 2 and [0024]: “The camera systems 110 may include cameras positioned on opposite sides of the vehicle so that lane markings on each side of the vehicle can be detected. In one embodiment, the side cameras may be angled downward to provide information about a region on the ground immediately next to the vehicle. For example, the camera may be oriented to face in a direction perpendicular, or substantially perpendicular, to an axis of the vehicle and with a downward angle to provide a view of the ground horizontally neighboring a wheel or side panel of the vehicle.”; [0026]: “The vehicle 202 may include a plurality of laterally positioned cameras that are oriented to obtain images of ground regions near the vehicle 202. For example, a camera (not shown) positioned on a left side of the vehicle 202 may obtain images of the ground in the left side region 208 (indicated by dashed lines) and a camera (not shown) positioned on a right side of the vehicle 202 may obtain images of the ground in the right side region 210 (indicated by dashed lines).”),
wherein the processor is configured to:
receive auxiliary data (see at least [0019]: “The vehicle control system 100 may also include one or more sensor systems/devices for detecting a presence of nearby objects, lane markers, and/or or determining a location of a parent vehicle (e.g., a vehicle that includes the vehicle control system 100). For example, the vehicle control system 100 may include radar systems 106, one or more LIDAR systems 108, one or more camera systems 110, a global positioning system (GPS) 112, and/or ultra sound systems 114. The vehicle control system 100 may include a data store 116 for storing relevant or useful data for navigation and safety such as map data, driving history, or other data. The vehicle control system 100 may also include a transceiver 118 for wireless communication with a mobile or wireless network, other vehicles, infrastructure, or any other communication system.”);
infer, estimate or determine the position of the vehicle relative to a lane marking detected in the image data from one or more of the cameras (see at least [0026]: “The side cameras may periodically obtain images of the ground regions 208 and 210 near the vehicle and the vehicle 202 (such as the lane component 104 of the vehicle 202) may use this information to determine a position of the vehicle 202 within a lane of the roadway 200. The positions or distances determined by the lane component 104 may include distances between lane markings 204 and 206 and a side panel of the vehicle 202 or distances between lane markings 204 and 206 and an axis 212 (e.g., the long axis) of the vehicle 202.”);
detect a change of the position of the vehicle relative to the lane marking (see at least [0034]: “The lane component 104 (or an automated driving/assistance system 100) determines at 408 a driving maneuver or a warning based on the filtered and tracked distance at 406. For example, if the distance is trending away from a center of a lane or toward a lane marking, the lane component 104 may determine a change in a driving path to move the vehicle toward a center of the lane. As another example, if the distance is trending away from the center of the lane a warning may be provided to a human driver to recommend moving back toward a center of the lane.”); and
determine, a reason for the change of the position of the vehicle in the lane based on the auxiliary data, wherein the processor is configured to distinguish between a change of the position of the vehicle in the lane in preparation for making a turn or avoiding an obstacle and a change of the position of the vehicle indicative that the vehicle is at risk of straying outside the lane (see at least [0028]: “Based on the accurate positioning, a driving path 214 may be calculated to place the vehicle 202 within the center of a lane or to maintain the vehicle 202 at or near a center of the lane. The driving path 214 may be computed to keep the vehicle within the lane and thus minimize risk of accidents with other vehicles in other lanes or risk of driving off of the roadway 200. Driving maneuvers may be determined based on the current position in the lane as well as any other available information, such as perception information from a forward and/or rear facing camera, LIDAR system 108, radar system 106, map data, driving history, or any other data. For example, a current position of the vehicle 202 within the lane as well as a curvature of the lane or roadway 200 may be used to determine a future driving path for the vehicle 202.”; [0043]: “The driving maneuver component 508 may determine one or more driving maneuvers to be performed by the vehicle and/or to be suggested to a vehicle controller or human driver. In one embodiment, the driving maneuver component 508 determines a driving maneuver that places or maintains the vehicle centered between the lane markings…For example, in one embodiment, the driving maneuver component 508 may determine a driving path that places the vehicle near a left or right side of the lane to avoid debris, increase a distance between the parent vehicle and a neighboring vehicle, and/or perform other positioning maneuvers within a lane...Obviously, in case of imminent collisions, lane changes, or the like, the driving maneuver component 508 may allow the vehicle to leave the current lane.”),
wherein responsive to a determination that the change of the position of the vehicle in the lane is indicative that the vehicle is at risk of straying outside the lane, the processor performs a first operation (see at least Fig. 1 and [0018]: “Referring now to the figures, FIG. 1 illustrates an example vehicle control system 100 that may be used to detect lanes, including lane markings or boundaries. The vehicle control system 100 may include an automated driving/assistance system 102. The automated driving/assistance system 102 may be used to automate or control operation of a vehicle or to provide assistance to a human driver…The automated driving/assistance system 102 may include a lane component 104 that uses a neural network, or other model or algorithm, to detect a lane marking or boundary and/or to determine a position of the vehicle in relation to the lane.”); [0028]: “Based on the accurate positioning, a driving path 214 may be calculated to place the vehicle 202 within the center of a lane or to maintain the vehicle 202 at or near a center of the lane. The driving path 214 may be computed to keep the vehicle within the lane and thus minimize risk of accidents with other vehicles in other lanes or risk of driving off of the roadway 200. Driving maneuvers may be determined based on the current position in the lane as well as any other available information, such as perception information from a forward and/or rear facing camera, LIDAR system 108, radar system 106, map data, driving history, or any other data. For example, a current position of the vehicle 202 within the lane as well as a curvature of the lane or roadway 200 may be used to determine a future driving path for the vehicle 202.”; [0034]: “In one embodiment, the lane component 104 filters at 406 the output using a state-space estimation technique and tracks the changes to provide information useful for balancing a vehicle in a lane, and/or for various active safety applications. The lane component 104 (or an automated driving/assistance system 100) determines at 408 a driving maneuver or a warning based on the filtered and tracked distance at 406. For example, if the distance is trending away from a center of a lane or toward a lane marking, the lane component 104 may determine a change in a driving path to move the vehicle toward a center of the lane. As another example, if the distance is trending away from the center of the lane a warning may be provided to a human driver to recommend moving back toward a center of the lane.”); and
wherein responsive to a determination that the change of the position of the vehicle in the lane is in preparation for making the turn or avoiding the obstacle, the processor does not perform the first operation (see at least [0043]: “The driving maneuver component 508 may determine one or more driving maneuvers to be performed by the vehicle and/or to be suggested to a vehicle controller or human driver...Obviously, in case of imminent collisions, lane changes, or the like, the driving maneuver component 508 may allow the vehicle to leave the current lane.” Nariyambut Murali teaches allowing the vehicle to leave the current lane which is suppressing the lane centering action (does not perform the first operation) when in a case of imminent collisions and/or lane changes (making a turn or avoiding obstacles).).
Nariyambut Murali (P. [0034]) teaches “for example, if the distance is trending away from a center of a lane or toward a lane marking, the lane component 104 may determine a change in a driving path to move the vehicle toward a center of the lane. As another example, if the distance is trending away from the center of the lane a warning may be provided to a human driver to recommend moving back toward a center of the lane.” Nariyambut Murali (P. [0043]) further teaches that “the driving maneuver component 508 may determine one or more driving maneuvers to be performed by the vehicle and/or to be suggested to a vehicle controller or human driver. In one embodiment, the driving maneuver component 508 determines a driving maneuver that places or maintains the vehicle centered between the lane markings…For example, in one embodiment, the driving maneuver component 508 may determine a driving path that places the vehicle near a left or right side of the lane to avoid debris, increase a distance between the parent vehicle and a neighboring vehicle, and/or perform other positioning maneuvers within a lane...Obviously, in case of imminent collisions, lane changes, or the like, the driving maneuver component 508 may allow the vehicle to leave the current lane.” Hence, Nariyambut Murali teaches determining the reason and logic for the change of the position of the vehicle in the lane and provide a warning and/or control the vehicle.
Alternatively, even it is it not implicitly taught by Nariyambut Murali, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to determine a reason for the change of the position of the vehicle in the lane in order to suppress the lane centering action to avoid a collision with an obstacle.
Regarding claim 39, Nariyambut Murali teaches the limitations of claim 37. Nariyambut Murali further teaches wherein the vehicle further comprises a forward-facing camera or a mapping, location or route planning system for providing the auxiliary data to the processor for providing the auxiliary data to the processor (see at least Fig. 1 and [0028]: “Driving maneuvers may be determined based on the current position in the lane as well as any other available information, such as perception information from a forward and/or rear facing camera, LIDAR system 108, radar system 106, map data, driving history, or any other data. For example, a current position of the vehicle 202 within the lane as well as a curvature of the lane or roadway 200 may be used to determine a future driving path for the vehicle 202.”; [0032]: “In one embodiment, a neural network may be used to determine the distance at 404 between the vehicle and lane markings. In one embodiment, the lane component 104 may determine a position in a lane based on distances from markings on either side of the vehicle.”).
Regarding claim 40, Nariyambut Murali teaches the limitations of claim 37. Nariyambut Murali further teaches wherein the vehicle further comprises one or more of:
a driver warning system; a brake control subsystem; a throttle control subsystem; and
a steering control subsystem, and wherein the processor is configured to output a control signal to one or more of the driver warning system, the brake control subsystem, the throttle control subsystem, and the steering control subsystem if it is determined that the vehicle is at risk of straying outside the lane (see at least Fig. 1 and [0018]: “Referring now to the figures, FIG. 1 illustrates an example vehicle control system 100 that may be used to detect lanes, including lane markings or boundaries. The vehicle control system 100 may include an automated driving/assistance system 102. The automated driving/assistance system 102 may be used to automate or control operation of a vehicle or to provide assistance to a human driver. For example, the automated driving/assistance system 102 may control one or more of braking, steering, acceleration, lights, alerts, driver notifications, radio, or any other auxiliary systems of the vehicle. In another example, the automated driving/assistance system 102 may not be able to provide any control of the driving (e.g., steering, acceleration, or braking), but may provide notifications and alerts to assist a human driver in driving safely. The automated driving/assistance system 102 may include a lane component 104 that uses a neural network, or other model or algorithm, to detect a lane marking or boundary and/or to determine a position of the vehicle in relation to the lane. In one embodiment, the automated driving/assistance system 102 may determine a driving maneuver or driving path to maintain or place the vehicle at or near a center of the lane.”).
Regarding claim 41, Nariyambut Murali teaches the limitations of claim 37. Nariyambut Murali further teaches wherein the processor is configured to determine a value representative of a distance and/or an angle between the vehicle and a lane marking that delimits a boundary of the lane based on the first or second image data (see at least [0029]: “FIG. 3 depicts an example image 300 captured by a side view camera. The image 300 shows a surface 302 of a roadway with a lane marking 304. The image 300 has a pixel height of N and a pixel width of M. In one embodiment, the lane component 104 may receive the image 300 and determine a distance 306 from a bottom of the image 300 to the lane marking 304. The distance 306 may be determined as a pixel value (e.g., a pixel height) or may be determined based on a distance measurement unit such as feet or meters. In one embodiment, a distance 306 in pixels may be converted to distance using a preconfigured function or calculation. For example, a linear or parabolic function based on the location and orientation of the camera may be used to convert a pixel length or height into feet or meters. In one embodiment, the lane component 104 may use a neural network to determine the distance 306. In one embodiment, if a lane marking 304 is not present, the lane component 104 may return a null value to indicate that there is no lane marking in the image.”).
Regarding claim 42, Nariyambut Murali teaches the limitations of claim 37. Nariyambut Murali further teaches wherein:
the first and second cameras are each provided or associated with an image processing subsystem (see at least Fig. 1 and [0023] “In one embodiment, the camera systems 110 may include a plurality of cameras. For example, the camera systems 110 may include cameras facing in different directions to provide different views and different fields of view for areas near or around the vehicle.”);
the image processing subsystem is configured to detect the presence and/or position of a lane marking in the image data output by the respective camera and to transmit data indicative of the presence and/or position of the lane marking to the processor (see at least Figs. 1, 2, and [0023]: “In one embodiment, the camera systems 110 may include a plurality of cameras. For example, the camera systems 110 may include cameras facing in different directions to provide different views and different fields of view for areas near or around the vehicle.”; [0024]: “The camera systems 110 may include cameras positioned on opposite sides of the vehicle so that lane markings on each side of the vehicle can be detected. In one embodiment, the side cameras may be angled downward to provide information about a region on the ground immediately next to the vehicle. For example, the camera may be oriented to face in a direction perpendicular, or substantially perpendicular, to an axis of the vehicle and with a downward angle to provide a view of the ground horizontally neighboring a wheel or side panel of the vehicle. Thus, if a lane marking is right next to the side of the vehicle, the marking may be shown within an image captured by a side camera.”; [0029]: “In one embodiment, the lane component 104 may receive the image 300 and determine a distance 306 from a bottom of the image 300 to the lane marking 304.”); and
the processor is configured to determine a value representative of a distance between the vehicle and the lane marking based on the data indicative of the presence and/or position of the lane marking (see at least Fig. 4 and [0029]: “In one embodiment, the lane component 104 may receive the image 300 and determine a distance 306 from a bottom of the image 300 to the lane marking 304. The distance 306 may be determined as a pixel value (e.g., a pixel height) or may be determined based on a distance measurement unit such as feet or meters. In one embodiment, a distance 306 in pixels may be converted to distance using a preconfigured function or calculation. For example, a linear or parabolic function based on the location and orientation of the camera may be used to convert a pixel length or height into feet or meters. In one embodiment, the lane component 104 may use a neural network to determine the distance 306. In one embodiment, if a lane marking 304 is not present, the lane component 104 may return a null value to indicate that there is no lane marking in the image.”).
Regarding claim 43, Nariyambut Murali teaches the limitations of claim 42. Nariyambut Murali further teaches wherein the vehicle further comprises one or more of:
a driver warning system, a brake control subsystem; a throttle control subsystem; and
a steering control subsystem, and wherein the processor is configured to output a control signal to one or more of the driver warning system, the brake control subsystem, the throttle control subsystem, and the steering control subsystem if it is determined that the vehicle is at risk of straying outside the lane (see at least Fig. 1 and [0018]: “Referring now to the figures, FIG. 1 illustrates an example vehicle control system 100 that may be used to detect lanes, including lane markings or boundaries. The vehicle control system 100 may include an automated driving/assistance system 102. The automated driving/assistance system 102 may be used to automate or control operation of a vehicle or to provide assistance to a human driver. For example, the automated driving/assistance system 102 may control one or more of braking, steering, acceleration, lights, alerts, driver notifications, radio, or any other auxiliary systems of the vehicle. In another example, the automated driving/assistance system 102 may not be able to provide any control of the driving (e.g., steering, acceleration, or braking), but may provide notifications and alerts to assist a human driver in driving safely. The automated driving/assistance system 102 may include a lane component 104 that uses a neural network, or other model or algorithm, to detect a lane marking or boundary and/or to determine a position of the vehicle in relation to the lane. In one embodiment, the automated driving/assistance system 102 may determine a driving maneuver or driving path to maintain or place the vehicle at or near a center of the lane.”).
Regarding claim 45, Nariyambut Murali teaches the limitations of claim 37. Nariyambut Murali further teaches wherein the vehicle comprises a bus, a minibus, a car, a van, a lorry, a truck or a taxi (see at least Fig. 2).
Regarding claim 46, Nariyambut Murali teaches the limitations of claim 26. Nariyambut Murali further teaches wherein the processor is configured to:
determine that the change of the position of the vehicle in the lane is indicative that the vehicle is at risk of straying outside the lane if the auxiliary data is not indicative that the vehicle is approaching a turn or obstacle (see at least Fig. 1 and [0028]: “Based on the accurate positioning, a driving path 214 may be calculated to place the vehicle 202 within the center of a lane or to maintain the vehicle 202 at or near a center of the lane. The driving path 214 may be computed to keep the vehicle within the lane and thus minimize risk of accidents with other vehicles in other lanes or risk of driving off of the roadway 200. Driving maneuvers may be determined based on the current position in the lane as well as any other available information, such as perception information from a forward and/or rear facing camera, LIDAR system 108, radar system 106, map data, driving history, or any other data. For example, a current position of the vehicle 202 within the lane as well as a curvature of the lane or roadway 200 may be used to determine a future driving path for the vehicle 202.”; [0032]: “In one embodiment, a neural network may be used to determine the distance at 404 between the vehicle and lane markings. In one embodiment, the lane component 104 may determine a position in a lane based on distances from markings on either side of the vehicle.”; [0043]: “The driving maneuver component 508 may determine one or more driving maneuvers to be performed by the vehicle and/or to be suggested to a vehicle controller or human driver. In one embodiment, the driving maneuver component 508 determines a driving maneuver that places or maintains the vehicle centered between the lane markings…Thus, the lane component 104 may allow a vehicle to be at different positions within a lane while accounting for current driving situations. Obviously, in case of imminent collisions, lane changes, or the like, the driving maneuver component 508 may allow the vehicle to leave the current lane.” Nariyambut Murali teaches utilizing additional data to detect obstacles and maintain the vehicle at or near the center of the lane when there is not obstacle on the road.); and
determine that the change of the position of the vehicle in the lane is in preparation for making the turn or avoiding the obstacle if the auxiliary data is indicative that the vehicle is approaching a turn or obstacle (see at least Fig. 1 and [0028]: “Driving maneuvers may be determined based on the current position in the lane as well as any other available information, such as perception information from a forward and/or rear facing camera, LIDAR system 108, radar system 106, map data, driving history, or any other data. For example, a current position of the vehicle 202 within the lane as well as a curvature of the lane or roadway 200 may be used to determine a future driving path for the vehicle 202.”; [0032]: “In one embodiment, a neural network may be used to determine the distance at 404 between the vehicle and lane markings. In one embodiment, the lane component 104 may determine a position in a lane based on distances from markings on either side of the vehicle.”; [0043]: “The driving maneuver component 508 may determine one or more driving maneuvers to be performed by the vehicle and/or to be suggested to a vehicle controller or human driver. In one embodiment, the driving maneuver component 508 determines a driving maneuver that places or maintains the vehicle centered between the lane markings…Thus, the lane component 104 may allow a vehicle to be at different positions within a lane while accounting for current driving situations. Obviously, in case of imminent collisions, lane changes, or the like, the driving maneuver component 508 may allow the vehicle to leave the current lane.” Nariyambut Murali teaches utilizing additional data to detect obstacles and suppress the lane centering action in a case of imminent collision.).
Regarding claim 47, Nariyambut Murali teaches the limitations of claim 37. Nariyambut Murali further teaches wherein the processor is configured to:
determine that the change of the position of the vehicle in the lane is indicative that the vehicle is at risk of straying outside the lane if the auxiliary data is not indicative that the vehicle is approaching a turn or obstacle (see at least Fig. 1 and [0028]: “Based on the accurate positioning, a driving path 214 may be calculated to place the vehicle 202 within the center of a lane or to maintain the vehicle 202 at or near a center of the lane. The driving path 214 may be computed to keep the vehicle within the lane and thus minimize risk of accidents with other vehicles in other lanes or risk of driving off of the roadway 200. Driving maneuvers may be determined based on the current position in the lane as well as any other available information, such as perception information from a forward and/or rear facing camera, LIDAR system 108, radar system 106, map data, driving history, or any other data. For example, a current position of the vehicle 202 within the lane as well as a curvature of the lane or roadway 200 may be used to determine a future driving path for the vehicle 202.”; [0032]: “In one embodiment, a neural network may be used to determine the distance at 404 between the vehicle and lane markings. In one embodiment, the lane component 104 may determine a position in a lane based on distances from markings on either side of the vehicle.”; [0043]: “The driving maneuver component 508 may determine one or more driving maneuvers to be performed by the vehicle and/or to be suggested to a vehicle controller or human driver. In one embodiment, the driving maneuver component 508 determines a driving maneuver that places or maintains the vehicle centered between the lane markings…Thus, the lane component 104 may allow a vehicle to be at different positions within a lane while accounting for current driving situations. Obviously, in case of imminent collisions, lane changes, or the like, the driving maneuver component 508 may allow the vehicle to leave the current lane.” Nariyambut Murali teaches utilizing additional data to detect obstacles and maintain the vehicle at or near the center of the lane when there is not obstacle on the road.); and
determine that the change of the position of the vehicle in the lane is in preparation for making the turn or avoiding the obstacle if the auxiliary data is indicative that the vehicle is approaching a turn or obstacle (see at least Fig. 1 and [0028]: “Driving maneuvers may be determined based on the current position in the lane as well as any other available information, such as perception information from a forward and/or rear facing camera, LIDAR system 108, radar system 106, map data, driving history, or any other data. For example, a current position of the vehicle 202 within the lane as well as a curvature of the lane or roadway 200 may be used to determine a future driving path for the vehicle 202.”; [0032]: “In one embodiment, a neural network may be used to determine the distance at 404 between the vehicle and lane markings. In one embodiment, the lane component 104 may determine a position in a lane based on distances from markings on either side of the vehicle.”; [0043]: “The driving maneuver component 508 may determine one or more driving maneuvers to be performed by the vehicle and/or to be suggested to a vehicle controller or human driver. In one embodiment, the driving maneuver component 508 determines a driving maneuver that places or maintains the vehicle centered between the lane markings…Thus, the lane component 104 may allow a vehicle to be at different positions within a lane while accounting for current driving situations. Obviously, in case of imminent collisions, lane changes, or the like, the driving maneuver component 508 may allow the vehicle to leave the current lane.” Nariyambut Murali teaches utilizing additional data to detect obstacles and suppress the lane centering action in a case of imminent collision.).
Claim Rejections - 35 USC § 103
9. Claims 32-34 is/are rejected under 35 U.S.C. 103 as being unpatentable over Nariyambut Murali et al. (US 20170267177, hereinafter Nariyambut Murali) in view of Fusconi et al. (US 20220032994, hereinafter Fusconi).
Regarding claim 32, Nariyambut Murali teaches the limitations of claim 31. Nariyambut Murali further teaches wherein the first operation comprises: outputting a control signal to one or more of:
a driver warning system; a brake control subsystem; a throttle control subsystem; and
a steering control subsystem (see at least Fig. 1 and [0018]: “Referring now to the figures, FIG. 1 illustrates an example vehicle control system 100 that may be used to detect lanes, including lane markings or boundaries. The vehicle control system 100 may include an automated driving/assistance system 102. The automated driving/assistance system 102 may be used to automate or control operation of a vehicle or to provide assistance to a human driver. For example, the automated driving/assistance system 102 may control one or more of braking, steering, acceleration, lights, alerts, driver notifications, radio, or any other auxiliary systems of the vehicle. In another example, the automated driving/assistance system 102 may not be able to provide any control of the driving (e.g., steering, acceleration, or braking), but may provide notifications and alerts to assist a human driver in driving safely. The automated driving/assistance system 102 may include a lane component 104 that uses a neural network, or other model or algorithm, to detect a lane marking or boundary and/or to determine a position of the vehicle in relation to the lane. In one embodiment, the automated driving/assistance system 102 may determine a driving maneuver or driving path to maintain or place the vehicle at or near a center of the lane.”), and
wherein the first operation further comprises: comparing the value representative of the distance to a threshold (see at least Fig. 3 and [0029]: “FIG. 3 depicts an example image 300 captured by a side view camera. The image 300 shows a surface 302 of a roadway with a lane marking 304. The image 300 has a pixel height of N and a pixel width of M. In one embodiment, the lane component 104 may receive the image 300 and determine a distance 306 from a bottom of the image 300 to the lane marking 304. The distance 306 may be determined as a pixel value (e.g., a pixel height) or may be determined based on a distance measurement unit such as feet or meters. In one embodiment, a distance 306 in pixels may be converted to distance using a preconfigured function or calculation.”; [0038]: “The lane mark component 504 is configured to determine a distance between the vehicle and one or more lane markings near the vehicle. For example, the lane mark component 504 may determine a distance between the vehicle and a lane marking on the left side and also determine a distance between the vehicle and a lane marking on the right side. Based on the distances to the lane markings on the left and/or right side, the lane mark component 504 may be able to determine whether the vehicle is centered within a current lane or if the vehicle is moving toward or away from a center of the lane. The distance may be a distance between a center or side panel of the vehicle and the lane marking.”).
Nariyambut Murali fails to explicitly teach comparing the value representative of the distance to a threshold and deferring outputting the control signal if the value is greater than the threshold, or outputting the control signal if the value is equal to or less than the threshold.
However, Fusconi teaches a system and method for steering assist in a vehicle that compares a value representative of the distance to a threshold and deferring outputting a control signal if the value is greater than the threshold, or outputting the control signal if the value is equal to or less than the threshold (see at least [0075]: “If the second width WL2 is greater than or equal to the second threshold WT2, the control system 1 is configured to suppress the output of the road edge traversal signal SRE. The road edge assist steering torque STQ-RE is suppressed and the haptic signal is not generated at the steering wheel 5 if the host vehicle 2 approaches or crosses the first or second road edge RE-1, RE-2. In the second scenario illustrated in FIG. 3A, the control system 1 enables the output of the road edge traversal signal SRE when the second width WL2 of the second road section R-B is less than the second threshold WT2. However, the control system 1 suppresses the output of the road edge traversal signal SRE when the second width WL2 of the second road section R-B is greater than or equal to the second threshold WT2.”). Fusconi teaches comparing a second width WL2 (value representative of distance) to a second threshold WT2 and suppressing (deferring) steering torque (control signal) if the second width WL2 is greater than the second threshold WT2.
Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Nariyambut Murali to incorporate the teachings of Fusconi and provide a means to compares a value representative of the distance to a threshold and deferring outputting a control signal if the value is greater than the threshold, or outputting the control signal if the value is equal to or less than the threshold, with a reasonable expectation of success, in order to verify and recognize that a road marking is valid within a range before controlling the vehicle.
Regarding claim 33, Nariyambut Murali teaches the limitations of claim 26. Nariyambut Murali fails further teaches wherein the processor is configured to detect the presence of a lane marking in the first or second image data (see at least [0019]: “The vehicle control system 100 may also include one or more sensor systems/devices for detecting a presence of nearby objects, lane markers, and/or or determining a location of a parent vehicle (e.g., a vehicle that includes the vehicle control system 100).”).
Nariyambut Murali fails to explicitly teach detecting the presence of a lane marking in the first or second image data based on a difference in colour or a difference in contrast between the lane marking and the surface of the road.
However, Fusconi teaches a system and method for steering assist in a vehicle that detects a presence of a lane marking in a first or second image data based on a difference in colour or a difference in contrast between the lane marking and a surface of a road (see at least [0068]: “The lane departure warning system 9 is operable to monitor the image data captured by the sensor unit 10 at least substantially in real time. The image processing module 11 analyses the image data to identify the first road edge RE-1 and/or the second road edge RE-2. The image processing module 11 may, for example, identify changes in the contrast and/or colour of the image data which may be indicative of the first and/or second road edge RE-1, RE-2… The image processing module 11 may, for example, utilise image processing techniques to identify continuous or interrupted lines extending in a forward direction (i.e. parallel to the centre line CL of the host vehicle 2).”).
Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Nariyambut Murali to incorporate the teachings of Fusconi and provide a means to detect a presence of a lane marking in a first or second image data based on a difference in colour or a difference in contrast between the lane marking and a surface of a road, with a reasonable expectation of success, in order to provide an alternative means to recognize the lane marking from the road surface.
Regarding claim 34, Nariyambut Murali teaches the limitations of claim 26. Nariyambut Murali further teaches wherein the image processing subsystem is configured to detect the presence of a lane marking (see at least [0019]: “The vehicle control system 100 may also include one or more sensor systems/devices for detecting a presence of nearby objects, lane markers, and/or or determining a location of a parent vehicle (e.g., a vehicle that includes the vehicle control system 100).”).
Nariyambut Murali fails to explicitly teach wherein the image processing subsystem is configured to detect the presence of a lane marking based on a difference in colour or a difference in contrast between the lane marking and the surface of the road.
However, Fusconi teaches a system and method for steering assist in a vehicle that detects a presence of a lane marking in a first or second image data based on a difference in colour or a difference in contrast between the lane marking and a surface of a road (see at least [0068]: “The lane departure warning system 9 is operable to monitor the image data captured by the sensor unit 10 at least substantially in real time. The image processing module 11 analyses the image data to identify the first road edge RE-1 and/or the second road edge RE-2. The image processing module 11 may, for example, identify changes in the contrast and/or colour of the image data which may be indicative of the first and/or second road edge RE-1, RE-2… The image processing module 11 may, for example, utilise image processing techniques to identify continuous or interrupted lines extending in a forward direction (i.e. parallel to the centre line CL of the host vehicle 2).”).
Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Nariyambut Murali to incorporate the teachings of Fusconi and provide a means to detect a presence of a lane marking in a first or second image data based on a difference in colour or a difference in contrast between the lane marking and a surface of a road, with a reasonable expectation of success, in order to provide an alternative means to recognize the lane marking from the road surface.
Claim Rejections - 35 USC § 103
10. Claim 35 is/are rejected under 35 U.S.C. 103 as being unpatentable over Nariyambut Murali et al. (US 20170267177, hereinafter Nariyambut Murali) in view of Nemeth et al. (US 20210314497, hereinafter Nemeth).
Regarding claim 35, Nariyambut Murali teaches the limitations of claim 26.
Nariyambut Murali fails to explicitly teach a third camera configured to output third image data relating to the surface of the road on the first side of the vehicle and a fourth camera configured to output fourth image data relating to the surface of the road on the second side of the vehicle.
However, Nemeth teaches a system and method for monitoring areas on sides of a commercial vehicle that comprises a third camera configured to output third image data relating to a surface of a road on a first side of a vehicle (see at least Fig. 7B and [0015]: “The camera monitoring system optionally comprises a third camera unit, which is designed to acquire image data from a further lateral area on a driver side of the utility vehicle. The third camera unit provides the image data to the first image processing unit for processing…It is obvious that the third camera unit can also provide the image data to the second image processing unit and the fourth camera unit can also provide the image data to the first image processing unit.”); and
a fourth camera configured to output fourth image data relating to the surface of the road on a second side of the vehicle (see at least Fig. 7B and [0015]: “The camera monitoring system optionally comprises a fourth camera unit, which is designed to acquire image data from the further lateral area on the driver side of the utility vehicle. The fourth camera unit provides the image data to the second image processing unit for processing. It is obvious that the third camera unit can also provide the image data to the second image processing unit and the fourth camera unit can also provide the image data to the first image processing unit.”).
Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Nariyambut Murali to incorporate the teachings of Nemeth and provide a third camera configured to output third image data relating to a surface of a road on a first side of a vehicle and a fourth camera configured to output fourth image data relating to the surface of the road on a second side of the vehicle, with a reasonable expectation of success, in order to provide additional cameras for redundancy in case either the first and/or second camera fails.
Claim Rejections - 35 USC § 103
11. Claims 36 and 44 is/are rejected under 35 U.S.C. 103 as being unpatentable over Nariyambut Murali et al. (US 20170267177, hereinafter Nariyambut Murali) in view of LaPonse (US 20220198200, hereinafter LaPonse).
Regarding claim 36, Nariyambut Murali teaches the limitations of claim 26.
Nariyambut Murali fails to explicitly teaches wherein each camera is provided with a source of illumination such as an infra-red lamp.
However, LaPonse teaches a system and method for detecting road lane conditions and provide vehicle lane assistance wherein each camera is provided with a source of illumination such as an infra-red lamp (see at least [0014]: “In the embodiment, the infrared (IR) detecting device 14 comprises an infrared camera or a thermal imaging camera. The infrared camera typically uses short wavelength infrared light to illuminate an area of interest. Some of the infrared energy is reflected back to the infrared camera and interpreted to generate an image data.”).
Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Nariyambut Murali to incorporate the teachings of LaPonse and provide each camera with a source of illumination such as an infra-red lamp, with a reasonable expectation of success, in order to illuminate an area of interest so the camera can pick up infrared energy reflected back from road markings in low light conditions such as nighttime.
Regarding claim 44, Nariyambut Murali teaches the limitations of claim 37.
Nariyambut Murali fails to explicitly teaches wherein each camera is provided with a source of illumination comprising an infra-red lamp.
However, LaPonse teaches a system and method for detecting road lane conditions and provide vehicle lane assistance wherein each camera is provided with a source of illumination such as an infra-red lamp (see at least [0014]: “In the embodiment, the infrared (IR) detecting device 14 comprises an infrared camera or a thermal imaging camera. The infrared camera typically uses short wavelength infrared light to illuminate an area of interest. Some of the infrared energy is reflected back to the infrared camera and interpreted to generate an image data.”).
Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Nariyambut Murali to incorporate the teachings of LaPonse and provide each camera with a source of illumination such as an infra-red lamp, with a reasonable expectation of success, in order to illuminate an area of interest so the camera can pick up infrared energy reflected back from road markings in low light conditions such as nighttime.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Rothermel (US 20150235140) teaches a method and system for determining a lane change that is intended or not intended by the driver when driving a vehicle.
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/T.M.L./Examiner, Art Unit 3656
/KHOI H TRAN/Supervisory Patent Examiner, Art Unit 3656