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 communication is responsive to the correspondence filled on 08/29/2025.
Claims 1-20 are presented for examination.
IDS Considerations
The information disclosure statement (IDS) submitted on 09/30/2025 and 08/29/2025 is/are being considered by the examiner as the submission is in compliance with the provisions of 37 CFR 1.97.
Claim Objections
Claims 9 objected to because of the dependency on cancelled claim 8. Appropriate correction is required.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the claims at issue are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); and In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on a nonstatutory double patenting ground provided the reference application or patent either is shown to be commonly owned with this application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The USPTO internet Web site contains terminal disclaimer forms which may be used. The filing date of the application will determine what form should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission.
Claims 1 and 16 are rejected on the ground of nonstatutory obviousness-type double patenting as being unpatentable over claims 1 of US Pat. 12257953 B2.
Even though instant application does not claim “a CMS controller including a memory and a processor; the CMS controller being connected to a plurality of cameras disposed about a vehicle and configured to receive a video feed from each of the cameras in the plurality of cameras, the CMS controller including at least one side camera configured to define a rear side view and identifying a current location (t0) of a set of prediction points of the trailer along an inside edge of the trailer and store the current location (t0) of the set of prediction points in a prediction set; identifying a first predicted future position of each prediction point at a time t1 based on a set of parameters including at least a trailer angle of the vehicle, a steering angle of the vehicle and the current location (t0) of the corresponding prediction point and storing the first future prediction point (t1) in the prediction set; identifying at least one additional predicted future position of each prediction point at a time (tn) based on a second set of parameters including at least the trailer angle of the vehicle, the steering angle of the vehicle, and the location at a previous time (tn−1) of the corresponding prediction point; and ”, however not claiming this does not provide instant application a patentable distinction. Because lack of limitation makes the claim broad obvious variation of US Pat. 12257953 B2.
Even though US Pat. 12257953 B2 does not claim wherein the lane detection module includes an algorithm configured to identify a lane marking in a roadway, the at least one captured image including the lane marking and the trailer boundary is based upon a trailer feature detected by the object detection algorithm. However, this is well known in the art as an example given in prior art Lee (U.S. Pub. No. 20170247054 A1) [0024], [0035-0037] teach this.
It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to combine US Pat. 12257953 B2 and Lee (U.S. Pub. No. 20170247054 A1) with predictable results to identify a lane marking in a roadway, because these are analogous art and ordinary skill knows these features are combinable.
Also, US Pat. 12257953 B2 does not claim and the trailer boundary is based upon a trailer feature detected by the object detection algorithm. However, this is well known in the art as an example given in prior art Sperrle (U.S. Pub. No. 20230406410 A1) [0018].
It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to combine US Pat. 12257953 B2, Lee (U.S. Pub. No. 20170247054 A1) and Sperrle (U.S. Pub. No. 20230406410 A1) with predictable results to identify a lane marking in a roadway, because these are analogous art and will accommodate efficiency.
Instant Application 19/315,002
US Pat. 12257953 B2
1. A camera monitor system (CMS) for a vehicle, comprising:
at least one rear-facing camera configured to provide at least one captured image of at least one field of view,
the at least one field of view captures at least a portion of a trailer;
a display in communication with the camera and configured to depict a displayed image comprising at least a portion of the captured image;
and a controller in communication with the camera and the display, the controller comprising: a lane detection module configured to determine a lane boundary [geometry] for the vehicle, wherein the striking area prediction module defines the striking area geometry by:
wherein the lane detection module includes an algorithm configured to identify a lane marking in a roadway, the at least one captured image including the lane marking,
a trailer detection module configured to determine a trailer boundary, wherein the trailer detection module includes an object detection algorithm configured to detect the trailer in the at least one captured image.
and the trailer boundary is based upon a trailer feature detected by the object detection algorithm,
and a collision alert module configured to determine an imminent intersection between the trailer boundary and the lane boundary and provide an alert in response thereto.
1. A camera monitoring system (CMS) for a vehicle, comprising:
a CMS controller including a memory and a processor; the CMS controller being connected to a plurality of cameras disposed about a vehicle and configured to receive a video feed from each of the cameras in the plurality of cameras, the CMS controller including at least one side camera configured to define a rear side view
and at least one rear camera configured to generate a rear facing view;
the memory storing a trailer end detection module configured to identify a trailer end of a trailer within at least one image generated by the plurality of cameras;
identifying a current location (t0) of a set of prediction points of the trailer along an inside edge of the trailer and store the current location (t0) of the set of prediction points in a prediction set;
identifying a first predicted future position of each prediction point at a time t1 based on a set of parameters including at least a trailer angle of the vehicle, a steering angle of the vehicle and the current location (t0) of the corresponding prediction point and storing the first future prediction point (t1) in the prediction set; identifying at least one additional predicted future position of each prediction point at a time (tn) based on a second set of parameters including at least the trailer angle of the vehicle, the steering angle of the vehicle, and the location at a previous time (tn−1) of the corresponding prediction point; and
converting each location in the prediction set from a three dimensional real world position to a two dimensional position within a rear view display image,
generate a geometry including each two dimensional position, and causing the CMS to display the geometry over an image on the rear view display image as an overlay.
the memory storing a trailer end detection module configured to identify a trailer end of a trailer within at least one image generated by the plurality of cameras;
and the memory further storing a trailer striking area prediction module configured to define a striking area geometry using a set of predicted future positions of prediction points in a prediction set, the prediction points being defined along an edge of the trailer,
9. Limitations of remaining claims of instant application are obvious over US Pat. 12257953 B2 in view of prior art discussed under Claim Rejections – 35 USC § 103 of this office action. Same motivation described under Claim Rejections – 35 USC § 103 of this office action is applicable for combining US Pat. 12257953 B2 and stated prior arts. Please note 35 U.S.C. 101 allows only one patent from one patent application or invention. Remaining dependent claim limitations points to same invention as per applicant disclosure. As such, all dependent claims of instant application are obvious variation of independent claim 1 and also the specification points to same invention.
CLAIM INTERPRETATION
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.
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: in claim 1.
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.
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.
Examiner is invoking 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, for examining claim(s) 1 because these claim(s) are drawn to a functionality comprising module which use a generic placeholder, “module” coupled with functional language “a lane detection module configured to determine a lane boundary for the vehicle, wherein the lane detection module includes an algorithm configured to identify a lane marking in a roadway” in claim 1 without reciting sufficient structure to achieve the function.
However, a review of the specification PGPUB paragraph [0058] shows corresponding structure.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1, 7 and 16 is/are rejected under 35 U.S.C. 103 as being unpatentable over Lee (U.S. Pub. No. 20170247054 A1), in view of Sperrle (U.S. Pub. No. 20230406410 A1).
Regarding to claim 1 and 16:
1. Lee teach a camera monitor system (CMS) for a vehicle, comprising: a display in communication with the camera and configured to depict a displayed image comprising at least a portion of the captured image; and a controller in communication with the camera and the display, the controller comprising: (Lee [0019] FIG. 1 The travel path 22 can be displayed on the display 30. [0021] if the controller 28 determines that the predicted path of the vehicle 14 will cause the trailer 16 to cross out of the lane 12, then the controller 28 will provide a suitable warning, such as an icon on the display 30, haptic seat, haptic steering wheel, warning chimes, etc., prior to the vehicle 14 reaching the curve 20, such as about 5 seconds before. The display 30 may illustrate the predicted path of the vehicle 14 and the trailer 16. In another embodiment, the controller 28 may not only warn the vehicle driver that the trailer 16 may cross out of the lane 12, but also may show a path on the display 30 that the vehicle 14 should follow so that the trailer 16 does not cross out of the lane 12 when traveling through the curve 20 so as to provide a desired steering path for the driver.)
a lane detection module configured to determine a lane boundary for the vehicle, (Lee [0021] where the vehicle 14 is being autonomously driven, the system will cause the vehicle 14 to be steered along a corrected lane following path or lane keeping path to prevent the trailer 16 from crossing out of the lane 12 in the curve 20.) wherein the lane detection module includes an algorithm configured to identify a lane marking in a roadway, the at least one captured image including the lane marking, (Lee [0024] In order to determine whether the trailer 16 will cross out of the travel lane 12 when in the curve 20, the radius of curvature of the curve 20 and the width of the trailer 16 need to be known. The radius of curvature of the curve 20 can be obtained from cameras, the map database 26, information from the GPS unit 32, or otherwise, and the turn radius R.sub.f is obtained by equation (1). Using these two radius values, the width of the trailer 16, the width of the lane 12 and equation (4), the controller 28 can determine whether part of the trailer 16 will cross out of the lane 12 in the curve 20 within some predetermined tolerance, such as +/−20 cm. For example, if the width of the lane 12 is 3.5 m, the curve 20 has a 200 m radius of curvature, l is 2.9464 m, a.sub.1 is 1.105 m, b.sub.1 is 0.55 m, b.sub.2 is 14.63 m, and the trailer width is 2.5908 m, the controller 28 can determine using equation (4) that the turn radius R.sub.t at a center of the trailer's end is 199.443 m, which is less than the radius of curvature of the curve 20. By knowing the width of the trailer 16 and the width of the lane 12, the controller 28 can then determine that the end of the trailer 16 will cross out of the travel lane 12, where the controller 28 can then provide a warning to the vehicle driver in advance. [0035] Using the roadway lateral offset y.sub.r, the heading angle φ.sub.r and the roadway curvature ρ, the path generation processor 102 generates a smooth desired path by solving a fifth order polynomial equation provided as:
y.sub.d(t)=a.sub.5x.sub.d.sup.5(t)+a.sub.4x.sub.d.sup.4(t)+a.sub.3x.sub.d.sup.3(t)+a.sub.2x.sub.d.sup.2(t)+a.sub.1x.sub.d.sup.1(t)+a.sub.0. (12) [0036] The fifth order polynomial path generation captures the roadway parameters y.sub.r, ρ and φ.sub.r at the beginning and the end of the path and guarantees the smoothness of the path up to the second order path derivatives. In addition, the path can be obtained by a few simple algebraic computations using the road geometry measurement, thus it does not require heavy computing power. [0037] This path information including state variable x.sub.d, lateral position y.sub.d, and heading angle φ.sub.d is provided to a comparator 104 that receives a signal identifying a predicted vehicle path from a path prediction processor 106, discussed below, and provides an error signal between the desired path and the predicted path. The lateral speed v.sub.y, the yaw angle φ and the lateral position y.sub.r of the vehicle 14 are predicted or estimated over the turn change completion time. After the roadway model of equation (8) is obtained, the roadway lateral position y.sub.r and the yaw angle φ.sub.r can be predicted at the path prediction processor 106 using a vehicle dynamic model)
and a collision alert module configured to determine an imminent intersection between the trailer boundary and the lane boundary and provide an alert in response thereto. (Lee [0021] The present invention proposes identifying the predicted path of the vehicle 14 through the curve 20, whether the vehicle 14 is being autonomously driven, semi-autonomously driven and/or mechanically driven, before the vehicle 14 enters the curve 20 to determine whether the trailer 16 will cross out of the lane 12, and if so, provide one or more remedial actions. In one embodiment, if the controller 28 determines that the predicted path of the vehicle 14 will cause the trailer 16 to cross out of the lane 12, then the controller 28 will provide a suitable warning, such as an icon on the display 30, haptic seat, haptic steering wheel, warning chimes, etc., prior to the vehicle 14 reaching the curve 20, such as about 5 seconds before. )
Lee do not explicitly teach at least one rear-facing camera configured to provide at least one captured image of at least one field of view, the at least one field of view captures at least a portion of a trailer; a trailer detection module configured to determine a trailer boundary, wherein the trailer detection module includes an object detection algorithm configured to detect the trailer in the at least one captured image and the trailer boundary is based upon a trailer feature detected by the object detection algorithm.
However Sperrle teach at least one rear-facing camera configured to provide at least one captured image of at least one field of view, (Sperrle Fig, 1A and 1B shows rear facing FOV camera. [0027] FIG. 1A In order to be able to represent these partial surrounding areas that are not recorded at the present point in time in the environment model, items of image information of vehicle cameras 121, 122, 123, 124 and of trailer camera 125 in a close range around vehicle 100 are stored while the vehicle is traveling. The computing device 130 of the vehicle, which is advantageously connected to vehicle cameras 121, 122, 123, 124 and to the trailer camera 125 [], is designed to generate or compute an environment model, based on the current camera images of vehicle cameras 121, 122, 123, 124 and on the current camera image of trailer camera 125)
the at least one field of view captures at least a portion of a trailer; (Sperrle [0027] FIG. 1A The partial surrounding area 199 on the right side 113 of trailer 110 and the partial surrounding area 198 on the left side 112 of trailer 110, however, are not visible for any camera or are not recorded by any camera, since the trailer 110 blocks [least a portion of a trailer] these partial surrounding areas 198, 199)
a trailer detection module configured to determine a trailer boundary, wherein the trailer detection module includes an object detection algorithm (Sperrle [0012] In a further development of the present invention, a detection of a static or dynamic object is provided as a function of the detected vehicle camera images and/or of the detected trailer camera image and/or of another distance detection device) configured to detect the trailer in the at least one captured image (Sperrle [0018] In a particularly preferred embodiment of the present invention, the display of the environment model comprises at least an insertion of a schematic border of the trailer, which represents the dimensions of the trailer, the schematic border representing the trailer being automatically ascertained on the basis of the at least three vehicle camera images. For this purpose, the trailer is preferably displayed in at least semi-transparent fashion, and particularly preferably the trailer is displayed in transparent fashion. The schematic border may be represented two-dimensionally or three-dimensionally. This embodiment makes it particularly easy for the driver to comprehend the display and increases the clarity considerably.)
and the trailer boundary is based upon a trailer feature detected by the object detection algorithm. (Sperrle [0029] FIG. 2 in step 290, the detected object is highlighted in the displayed environment model and/or a collision warning is displayed 290 in the environment model for a user of the vehicle if the detected object is located in the ascertained predicted movement trajectory of the trailer and/or if the detected dynamic object is moving into the ascertained predicted movement trajectory of the trailer. Alternatively or additionally, information is inserted in the display 290 of the environment model about the distance between the detected object and the trailer 110 and/or between the detected object and one of the wheels of the trailer 110 as trailer 110 moves along the ascertained predicted movement trajectory. The inserted distance information represents in particular a distance perpendicular to the ascertained predicted movement trajectory of trailer 110. In an optional step 285 prior to displaying the environment model, an input of a user regarding a parking space for the trailer 110 is detected and/or an (automatic) detection of the parking space for trailer 110 is performed on the basis of the detected vehicle camera images and/or the detected trailer camera image.)
It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to modify Lee, further incorporating Sperrle in video/camera technology. One would be motivated to do so, to incorporate a trailer detection module configured to determine a trailer boundary, wherein the trailer detection module includes an object detection algorithm configured to detect the trailer in the at least one captured image and the trailer boundary is based upon a trailer feature detected by the object detection algorithm. This functionality will improve efficiency with predictable results.
Regarding to claim 7:
7. Lee teach the CMS of claim 1, Lee do not explicitly teach wherein one of the at least one rear-facing camera is mounted to a tractor, and the at least one field of view from the one of the at least one rear-facing camera captures portion of the trailer.
However Sperrle teach wherein one of the at least one rear-facing camera is mounted to a tractor, (Sperrle Fig, 1A and 1B shows rear facing FOV camera. [0027] FIG. 1A In order to be able to represent these partial surrounding areas that are not recorded at the present point in time in the environment model, items of image information of vehicle cameras 121, 122, 123, 124 and of trailer camera 125 in a close range around vehicle 100 are stored while the vehicle is traveling. The computing device 130 of the vehicle, which is advantageously connected to vehicle cameras 121, 122, 123, 124 and to the trailer camera 125 [], is designed to generate or compute an environment model, based on the current camera images of vehicle cameras 121, 122, 123, 124 and on the current camera image of trailer camera 125. Trailer 110 additionally comprises a trailer camera 125 on the rear side 114 of trailer 110, which records a trailer camera image of a rearward surrounding area 195 of vehicle 100 or of trailer 110) and the at least one field of view from the one of the at least one rear-facing camera captures portion of the trailer. (Sperrle [0027] FIG. 1A The partial surrounding area 199 on the right side 113 of trailer 110 and the partial surrounding area 198 on the left side 112 of trailer 110, however, are not visible for any camera or are not recorded by any camera, since the trailer 110 blocks [least a portion of a trailer] these partial surrounding areas 198, 199)
Claims 2 is/are rejected under 35 U.S.C. 103 as being unpatentable over Lee (U.S. Pub. No. 20170247054 A1), in view of Sperrle (U.S. Pub. No. 20230406410 A1), further in view of Lu (U.S. Pub. No. 20220135127 A1).
Regarding to claim 2:
2. Lee teach the CMS of claim 1, Lee do not explicitly teach wherein the alert is provided by an overlay depicted on the display.
However Lu teach wherein the alert is provided by an overlay depicted on the display. (Lu [0086] Referring now to FIGS. 11A and 11B, the system 12 does not restrict the user from setting the DTA 212 (e.g., via the user input 200) to an angle within the jackknife and/or collision zones 730. The system may instead alert the user when the desired trailer angle or DTA 212 is selected to be within a jackknife and/or collision zone 730. For example, the system 12 may provide an intermittent audio tone (e.g., a beeping) and/or provide a warning on the display 24. Alternatively, or additionally, the driver can be visually alerted when the desired trailer angle or DTA 212 is selected to be within a jackknife and/or collision zone 730. For example, an electronically generated graphic overlay can be displayed superimposed over the real-time video images of the rearward scene being displayed on the screen of the video monitor that is viewable by the driver of the vehicle when trailering.)
The motivation for combining Lee and Sperrle as set forth in claim 1 is equally applicable to claim 2. It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to modify Lee, further incorporating Sperrle and Lu in video/camera technology. One would be motivated to do so, to incorporate the alert is provided by an overlay depicted on the display. This functionality will improve user experience with predictable results.
8. (CANCELLED)
13. (CANCELLED)
Claims 14-15 and 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Lee (U.S. Pub. No. 20170247054 A1), in view of Sperrle (U.S. Pub. No. 20230406410 A1), further in view of Jales (U.S. Pub. No. 20200164803 A1).
Regarding to claim 14:
14. Lee teach the CMS of claim 1, Lee do not explicitly teach wherein the trailer feature is at least one trailer wheel.
However Jales teach wherein the trailer feature is at least one trailer wheel. (Jales [0045] As further discussed in reference to FIGS. 3-6, the invention disclosure provides a solution for the detection of the trailer angle γ based on deep learning and convolutional networks. In this way, the system 8 may reliably estimate the trailer angle γ based on an end-to-end approach for angle estimation utilizing only the existing backup camera (e.g. imaging device 14 of the vehicle 12). [0048] As shown in FIG. 3, the trailer angle γ is shown in relation to a number of parameters of the vehicle 12 and the trailer 10. In operation, the kinematic model depicted in FIG. 3 may be utilized as the basis for the system 8 to control the navigation of the vehicle 12 to direct the trailer 10 along a calculated path. During such operations, the system 8 may monitor the trailer angle γ to ensure that the trailer 10 is accurately guided by the vehicle 12. The parameter that may be utilized for the model include, but are not limited to, the following: [0049] δ: steering angle at steered wheels 40 of the vehicle 12)
The motivation for combining Lee and Sperrle as set forth in claim 1 is equally applicable to claim 14. It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to modify Lee, further incorporating Sperrle and Jales in video/camera technology. One would be motivated to do so, to incorporate the trailer feature is at least one trailer wheel. This functionality will improve accuracy with predictable results.
Regarding to claim 15:
15. Lee teach the CMS of claim 1, Lee do not explicitly teach wherein the trailer feature is at least one trailer edge line.
However Jales teach wherein the trailer feature is at least one trailer edge line. (Jales [0043] In particular, the disclosure provides for the detection of the trailer angle γ based on the image data captured by an imaging device 14. Based on the image data captured by the imaging device 14, the system 8 may identify various characteristics of the trailer 10 based on a variety of image processing techniques (e.g. edge detection, background subtraction, template matching etc.). However, due to variations related in the trailer 10 and the local environment (e.g. shadows, textured surfaces, noise, etc.), conventional image processing techniques may not be sufficiently robust to reliably and accurately monitor the trailer angle γ without the aid of additional sensors.)
Regarding to claim 20:
20. Lee teach the method of claim 16, Lee do not explicitly teach wherein the step includes trailer feature includes at least one of at least one trailer wheel and at least one trailer edge line.
However Jales teach wherein the step includes trailer feature includes at least one of at least one trailer wheel (Jales [0045] As further discussed in reference to FIGS. 3-6, the invention disclosure provides a solution for the detection of the trailer angle γ based on deep learning and convolutional networks. In this way, the system 8 may reliably estimate the trailer angle γ based on an end-to-end approach for angle estimation utilizing only the existing backup camera (e.g. imaging device 14 of the vehicle 12). [0048] As shown in FIG. 3, the trailer angle γ is shown in relation to a number of parameters of the vehicle 12 and the trailer 10. In operation, the kinematic model depicted in FIG. 3 may be utilized as the basis for the system 8 to control the navigation of the vehicle 12 to direct the trailer 10 along a calculated path. During such operations, the system 8 may monitor the trailer angle γ to ensure that the trailer 10 is accurately guided by the vehicle 12. The parameter that may be utilized for the model include, but are not limited to, the following: [0049] δ: steering angle at steered wheels 40 of the vehicle 12) and at least one trailer edge line. (Jales [0043] In particular, the disclosure provides for the detection of the trailer angle γ based on the image data captured by an imaging device 14. Based on the image data captured by the imaging device 14, the system 8 may identify various characteristics of the trailer 10 based on a variety of image processing techniques (e.g. edge detection, background subtraction, template matching etc.). However, due to variations related in the trailer 10 and the local environment (e.g. shadows, textured surfaces, noise, etc.), conventional image processing techniques may not be sufficiently robust to reliably and accurately monitor the trailer angle γ without the aid of additional sensors.)
Claims 18 is/are rejected under 35 U.S.C. 103 as being unpatentable over Lee (U.S. Pub. No. 20170247054 A1), in view of Sperrle (U.S. Pub. No. 20230406410 A1), further in view of Efrat (U.S. Pub. No. 20210276574 A1).
Regarding to claim 18:
18. Lee teach the method of claim 16, Lee do not explicitly teach wherein the captured image including the lane marking, wherein the identifying is performed by at least one of filtering a color of the lane marking and deep learning from a surrounding portion of the captured image.
However Efrat teach wherein the captured image including the lane marking, wherein the identifying is performed by at least one of filtering a color of the lane marking and deep learning from a surrounding portion of the captured image. (Efrat [0052] The FOV image 820 also illustrates the clusters 811, 812, 813, and 814 projected onto the lanes 821, 822, 823, and 824, respectively. A clustering algorithm may be applied to the embeddings, wherein clustering is a machine learning technique that involves grouping of data points. Given a set of data points, a clustering algorithm classifies each data point into a specific group. Clustering, i.e., concatenation requires that the grid sections be proximal, but not necessarily adjacent to one other. The feature vectors can thus be derived by developing corresponding clusters 811, 812, 813, and 814, respectively, from the lanes 821, 822, 823, and 824, respectively)
The motivation for combining Lee and Sperrle as set forth in claim 1 is equally applicable to claim 18. It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to modify Lee, further incorporating Sperrle and Efrat in video/camera technology. One would be motivated to do so, to incorporate the captured image including the lane marking, wherein the identifying is performed by at least one of filtering a color of the lane marking and deep learning from a surrounding portion of the captured image. This functionality will improve quality with predictable results.
Allowable subject matter
Regarding to claim 3-6, 9-12, 17 and 19:
Claims 3-6, 9-12, 17 and 19 is/are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims because the limitations of these dependent claims are not obvious from the prior art search when all the limitations of independent and intervening claims are taken into account.
Regarding to claim 17:
17. Lee teach the method of claim 16, wherein the alert is provided by an overlay depicted on a display, wherein the overlay is configured to increase in intensity based upon a severity level, and wherein the severity level is based upon at least one of a time until the imminent intersection and a time until a collision with a vehicle in an adjoining lane of the vehicle. (Lu [0086] Referring now to FIGS. 11A and 11B, the system 12 does not restrict the user from setting the DTA 212 (e.g., via the user input 200) to an angle within the jackknife and/or collision zones 730. The system may instead alert the user when the desired trailer angle or DTA 212 is selected to be within a jackknife and/or collision zone 730. For example, the system 12 may provide an intermittent audio tone (e.g., a beeping) and/or provide a warning on the display 24. Alternatively, or additionally, the driver can be visually alerted when the desired trailer angle or DTA 212 is selected to be within a jackknife and/or collision zone 730. For example, an electronically generated graphic overlay can be displayed superimposed over the real-time video images of the rearward scene being displayed on the screen of the video monitor that is viewable by the driver of the vehicle when trailering. Claim 17 is allowed for the same reason as claim 3)
Regarding to claim 19:
19. Lee teach the method of claim 16, wherein the trailer boundary detecting step includes using a kinematics model with a first bicycle model indicative of a tractor predicted path, a second bicycle model is connected to the first bicycle model by a hitch point, the first bicycle model includes Ackerman steering, and the second bicycle model indicative of the trailer predicted path, and the kinematics model is configured to receive a steering angle and a vehicle speed, and the trailer predicted path is based upon the steering angle and the vehicle speed. (Sperrle [0011] In one example embodiment of the present invention, the steering angle of the vehicle is additionally acquired. Subsequently, a predicted movement trajectory of the trailer is ascertained at least as a function of the ascertained trailer angle and as a function of the acquired steering angle. Optionally, the predicted movement trajectory may be ascertained as a function of further variables, for example as a function of the acquired yaw angle of the vehicle and/or as a function of the speed of the vehicle and/or as a function of data of the trailer, for example the distance from the coupling point at the drawbar to the wheel axle of the trailer, in particular along the longitudinal axis of the trailer. In this embodiment, the ascertained predicted movement trajectory of the trailer is additionally shown in the displayed environment model. Claim 19 is allowed for the same reason as claim 10)
Closely related prior art
Examiner notes teaching of U.S. Pub. No. 20170320518 A1 is/are pertinent to the independent claim(s), because it teach trailer trajectory.
Conclusion
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, William F Kraig can be reached on (571) 272-8660. The fax phone number for the organization where this application or proceeding is assigned is (571) 273-8300.
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/NASIM N NIRJHAR/Primary Examiner, Art Unit 2896
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