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 .
Priority
Receipt is acknowledged of certified copies of papers submitted under 35 U.S.C. 119(a)-(d), which papers have been placed of record in the file.
Information Disclosure Statement
The information disclosure statements (IDS) submitted on 10/10/2024 is being considered by the examiner.
Claim Objections
Claims 1 and 4 are objected to because of the following informalities:
In claim 1, line 23, the term “on the tentative complement point having been” should be changed to “on the tentative complementary point having been” in order to avoid typographical issue.
In claim 4, line 2, the term “recognition apparatus comprising” should be changed to “recognition apparatus comprising:” in order to avoid grammatical issue.
In claim 4, line 3, the term “a processor configured to” should be changed to “a processor configured to:” in order to avoid grammatical issue.
In claim 4, line 5, the term “in front of the vehicle,” should be changed “in front of the vehicle;” in order to avoid grammatical issue.
In claim 4, line 8, the term “with respect to the vehicle,” should be changed “with respect to the vehicle;” in order to avoid grammatical issue.
In claim 4, line 12, the term “behind the vehicle,” should be changed “behind the vehicle;” in order to avoid grammatical issue.
In claim 4, line 14, the term “information in each of the predetermined cycles,” should be changed “information in each of the predetermined cycles;” in order to avoid grammatical issue.
In claim 4, line 20, the term “on the tentative complement point having been” should be changed to “on the tentative complementary point having been” in order to avoid typographical issue.
In claim 4, line 21, the term “on the vehicle currently measured,” should be changed “on the vehicle currently measured;” in order to avoid grammatical issue.
In claim 4, line 23, the term “vehicle in each of the predetermined cycles,” should be changed “vehicle in each of the predetermined cycles;” in order to avoid grammatical issue.
Appropriate correction is required.
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.
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.
This application includes one or more claim limitations that use the word “means” or “step” but are nonetheless not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph because the claim limitation(s) recite(s) sufficient structure, materials, or acts to entirely perform the recited function.
Claim 2, recites limitations that use words like “means” (or “step”) or similar terms with functional language but do not invoke 35 U.S.C. 112(f):
Claim 2; recites the limitation, “yaw rate detector configured to……,” [Line 1-2].
Claim 2; recites the limitation, “vehicle speed detector……,” [Line 1-2].
Such claim limitation(s) is/are:
(i) “yaw rate detector” has a structure associated with it a yaw rate detector/sensor.
(ii) “vehicle speed detector” has a structure associated with it a vehicle speed detector/sensor.
Because this/these claim limitation(s) is/are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are not being interpreted to cover only the corresponding structure, material, or acts described in the specification as performing the claimed function, and equivalents thereof.
If applicant intends 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 remove the structure, materials, or acts that performs the claimed function; or (2) present a sufficient showing that the claim limitation(s) does/do not recite sufficient structure, materials, or acts to perform the claimed function.
Claims 1-3 recite limitations that use words like “means” (or “step”) or similar terms with functional language and do invoke 35 U.S.C. 112(f):
Claim 1; recites the limitation, “a lane-dividing line recognizer configured to…..” [Line 3].
Claim 1; recites the limitation, “a relative coordinate calculator configured to…..” [Line 6].
Claim 1; recites the limitation, “a first complementary point calculator configured to…...” [Line 9].
Claim 1; recites the limitation, “a first evaluation value acquirer configured to……,” [Line 14].
Claim 1; recites the limitation, “a second complementary point calculator configured to……,” [Line 17].
Claim 1; recites the limitation, “a second evaluation value acquirer configured to::……,” [Line 25].
Claim 1; recites the limitation, “a complementary point integrator configured to ……,” [Line 28].
Claim 2; recites the limitation, “the first evaluation value acquirer is configured to:……,” [Line 6].
Claim 3; recites the limitation, “the second evaluation value acquirer is configured to:……,” [Line 1-2].
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.
After a careful analysis, as disclosed above, and a careful review of the specification the following limitations in claims 1-3;
(i) “lane-dividing line recognizer” (Fig. 1, #13. Paragraph [0076 and 0111]- the image recognition ECU 13 may serve as a "lane-dividing line recognizer", a "relative coordinate calculator", a "first complementary point calculator", a "first evaluation value acquirer", a "second complementary point calculator", a "second evaluation value acquirer", and a "complementary point integrator". The image recognition ECU 13 illustrated in FIG. 1 is implementable by circuitry including at least one semiconductor integrated circuit such as at least one processor (e.g., a central processing unit (CPU)), at least one application specific integrated circuit (ASIC), and/or at least one field programmable gate array (FPGA). At least one processor is configurable, by reading instructions from at least one machine readable non-transitory tangible medium, to perform all or a part of functions of the image recognition ECU 13 illustrated in FIG. 1. Such a medium may take many forms, including, but not limited to, any type of magnetic medium such as a hard disk, any type of optical medium such as a CD and a DVD, any type of semiconductor memory (i.e., semiconductor circuit) such as a volatile memory and a non-volatile memory. The volatile memory may include a DRAM and a SRAM, and the nonvolatile memory may include a ROM and a NVRAM. The ASIC is an integrated circuit (IC) customized to perform, and the FPGA is an integrated circuit designed to be configured after manufacturing in order to perform, all or a part of the functions of the image recognition ECU 13 illustrated in FIG. 1. The lane-dividing line recognizer is illustrated in Fig. 1, as a black box #13, thus has sufficient structure or material wherein is a processor.).
(ii) “relative coordinate calculator” (Fig. 1, #13. Paragraph [0076 and 0111]- the image recognition ECU 13 may serve as a "lane-dividing line recognizer", a "relative coordinate calculator", a "first complementary point calculator", a "first evaluation value acquirer", a "second complementary point calculator", a "second evaluation value acquirer", and a "complementary point integrator". The image recognition ECU 13 illustrated in FIG. 1 is implementable by circuitry including at least one semiconductor integrated circuit such as at least one processor (e.g., a central processing unit (CPU)), at least one application specific integrated circuit (ASIC), and/or at least one field programmable gate array (FPGA). At least one processor is configurable, by reading instructions from at least one machine readable non-transitory tangible medium, to perform all or a part of functions of the image recognition ECU 13 illustrated in FIG. 1. Such a medium may take many forms, including, but not limited to, any type of magnetic medium such as a hard disk, any type of optical medium such as a CD and a DVD, any type of semiconductor memory (i.e., semiconductor circuit) such as a volatile memory and a non-volatile memory. The volatile memory may include a DRAM and a SRAM, and the nonvolatile memory may include a ROM and a NVRAM. The ASIC is an integrated circuit (IC) customized to perform, and the FPGA is an integrated circuit designed to be configured after manufacturing in order to perform, all or a part of the functions of the image recognition ECU 13 illustrated in FIG. 1. The relative coordinate calculator is illustrated in Fig. 1, as a black box #13, thus has sufficient structure or material wherein is a processor.).
(iii) “first complementary point calculator” (Fig. 1, #13. Paragraph [0076 and 0111]- the image recognition ECU 13 may serve as a "lane-dividing line recognizer", a "relative coordinate calculator", a "first complementary point calculator", a "first evaluation value acquirer", a "second complementary point calculator", a "second evaluation value acquirer", and a "complementary point integrator". The image recognition ECU 13 illustrated in FIG. 1 is implementable by circuitry including at least one semiconductor integrated circuit such as at least one processor (e.g., a central processing unit (CPU)), at least one application specific integrated circuit (ASIC), and/or at least one field programmable gate array (FPGA). At least one processor is configurable, by reading instructions from at least one machine readable non-transitory tangible medium, to perform all or a part of functions of the image recognition ECU 13 illustrated in FIG. 1. Such a medium may take many forms, including, but not limited to, any type of magnetic medium such as a hard disk, any type of optical medium such as a CD and a DVD, any type of semiconductor memory (i.e., semiconductor circuit) such as a volatile memory and a non-volatile memory. The volatile memory may include a DRAM and a SRAM, and the nonvolatile memory may include a ROM and a NVRAM. The ASIC is an integrated circuit (IC) customized to perform, and the FPGA is an integrated circuit designed to be configured after manufacturing in order to perform, all or a part of the functions of the image recognition ECU 13 illustrated in FIG. 1.The first complementary point calculator is illustrated in Fig. 1, as a black box #13, thus has sufficient structure or material wherein is a processor.).
(iv) “first evaluation value acquirer” (Fig. 1, #13. Paragraph [0076 and 0111]- the image recognition ECU 13 may serve as a "lane-dividing line recognizer", a "relative coordinate calculator", a "first complementary point calculator", a "first evaluation value acquirer", a "second complementary point calculator", a "second evaluation value acquirer", and a "complementary point integrator". The image recognition ECU 13 illustrated in FIG. 1 is implementable by circuitry including at least one semiconductor integrated circuit such as at least one processor (e.g., a central processing unit (CPU)), at least one application specific integrated circuit (ASIC), and/or at least one field programmable gate array (FPGA). At least one processor is configurable, by reading instructions from at least one machine readable non-transitory tangible medium, to perform all or a part of functions of the image recognition ECU 13 illustrated in FIG. 1. Such a medium may take many forms, including, but not limited to, any type of magnetic medium such as a hard disk, any type of optical medium such as a CD and a DVD, any type of semiconductor memory (i.e., semiconductor circuit) such as a volatile memory and a non-volatile memory. The volatile memory may include a DRAM and a SRAM, and the nonvolatile memory may include a ROM and a NVRAM. The ASIC is an integrated circuit (IC) customized to perform, and the FPGA is an integrated circuit designed to be configured after manufacturing in order to perform, all or a part of the functions of the image recognition ECU 13 illustrated in FIG. 1. The first evaluation value acquirer is illustrated in Fig. 1, as a black box #13, thus has sufficient structure or material wherein is a processor.).
(v) “second complementary point calculator” (Fig. 1, #13. Paragraph [0076 and 0111]- the image recognition ECU 13 may serve as a "lane-dividing line recognizer", a "relative coordinate calculator", a "first complementary point calculator", a "first evaluation value acquirer", a "second complementary point calculator", a "second evaluation value acquirer", and a "complementary point integrator". The image recognition ECU 13 illustrated in FIG. 1 is implementable by circuitry including at least one semiconductor integrated circuit such as at least one processor (e.g., a central processing unit (CPU)), at least one application specific integrated circuit (ASIC), and/or at least one field programmable gate array (FPGA). At least one processor is configurable, by reading instructions from at least one machine readable non-transitory tangible medium, to perform all or a part of functions of the image recognition ECU 13 illustrated in FIG. 1. Such a medium may take many forms, including, but not limited to, any type of magnetic medium such as a hard disk, any type of optical medium such as a CD and a DVD, any type of semiconductor memory (i.e., semiconductor circuit) such as a volatile memory and a non-volatile memory. The volatile memory may include a DRAM and a SRAM, and the nonvolatile memory may include a ROM and a NVRAM. The ASIC is an integrated circuit (IC) customized to perform, and the FPGA is an integrated circuit designed to be configured after manufacturing in order to perform, all or a part of the functions of the image recognition ECU 13 illustrated in FIG. 1. The second complementary point calculator is illustrated in Fig. 1, as a black box #13, thus has sufficient structure or material wherein is a processor.).
(vi) “second evaluation value acquirer” (Fig. 1, #13. Paragraph [0076 and 0111]- the image recognition ECU 13 may serve as a "lane-dividing line recognizer", a "relative coordinate calculator", a "first complementary point calculator", a "first evaluation value acquirer", a "second complementary point calculator", a "second evaluation value acquirer", and a "complementary point integrator". The image recognition ECU 13 illustrated in FIG. 1 is implementable by circuitry including at least one semiconductor integrated circuit such as at least one processor (e.g., a central processing unit (CPU)), at least one application specific integrated circuit (ASIC), and/or at least one field programmable gate array (FPGA). At least one processor is configurable, by reading instructions from at least one machine readable non-transitory tangible medium, to perform all or a part of functions of the image recognition ECU 13 illustrated in FIG. 1. Such a medium may take many forms, including, but not limited to, any type of magnetic medium such as a hard disk, any type of optical medium such as a CD and a DVD, any type of semiconductor memory (i.e., semiconductor circuit) such as a volatile memory and a non-volatile memory. The volatile memory may include a DRAM and a SRAM, and the nonvolatile memory may include a ROM and a NVRAM. The ASIC is an integrated circuit (IC) customized to perform, and the FPGA is an integrated circuit designed to be configured after manufacturing in order to perform, all or a part of the functions of the image recognition ECU 13 illustrated in FIG. 1. The second evaluation value acquirer is illustrated in Fig. 1, as a black box #13, thus has sufficient structure or material wherein is a processor.).
(vii) “complementary point integrator” (Fig. 1, #13. Paragraph [0076 and 0111]- the image recognition ECU 13 may serve as a "lane-dividing line recognizer", a "relative coordinate calculator", a "first complementary point calculator", a "first evaluation value acquirer", a "second complementary point calculator", a "second evaluation value acquirer", and a "complementary point integrator". The image recognition ECU 13 illustrated in FIG. 1 is implementable by circuitry including at least one semiconductor integrated circuit such as at least one processor (e.g., a central processing unit (CPU)), at least one application specific integrated circuit (ASIC), and/or at least one field programmable gate array (FPGA). At least one processor is configurable, by reading instructions from at least one machine readable non-transitory tangible medium, to perform all or a part of functions of the image recognition ECU 13 illustrated in FIG. 1. Such a medium may take many forms, including, but not limited to, any type of magnetic medium such as a hard disk, any type of optical medium such as a CD and a DVD, any type of semiconductor memory (i.e., semiconductor circuit) such as a volatile memory and a non-volatile memory. The volatile memory may include a DRAM and a SRAM, and the nonvolatile memory may include a ROM and a NVRAM. The ASIC is an integrated circuit (IC) customized to perform, and the FPGA is an integrated circuit designed to be configured after manufacturing in order to perform, all or a part of the functions of the image recognition ECU 13 illustrated in FIG. 1. The complementary point integrator is illustrated in Fig. 1, as a black box #13, thus has sufficient structure or material wherein is 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 § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1 and 4 are rejected under 35 U.S.C. 103 as being unpatentable over KAGIMOTO et al. (US 20240005673 A1), hereinafter referenced as KAGIMOTO, in view of KURODA (US 20170053533 A1), hereinafter referenced as KURODA, and further in view of HIROYUKI (US 20220178703 A1), hereinafter referenced as HIROYUKI.
Regarding claim 1, KAGIMOTO explicitly teaches a lane-dividing line recognition apparatus for a vehicle (Fig. 1. Paragraph [0027]-KAGIMOTO discloses FIG. 1 is a hardware configuration diagram illustrating an embodiment of a dividing line recognition device according to the present invention. A dividing line information integration device 100 of the present embodiment to which the dividing line recognition device according to the present invention is applied is mounted on a vehicle 10 and constitutes part of an advanced driver assistance system (ADAS) or an automated driving system (AD).), the lane-dividing line recognition apparatus comprising:
a lane-dividing line recognizer (Fig. 1, #100 called dividing line information integration device. Paragraph [0028]-KAGIMOTO discloses the dividing line information integration device 100 includes, for example, a central processing unit, a storage device such as a memory and a hard disk, a computer program stored in the storage device, and an input/output device. Specifically, the dividing line information integration device 100 is a computer system such as firmware or a microcontroller. Further, the dividing line information integration device 100 may be part of an electronic control unit (ECU) for an ADAS or an AD mounted on the vehicle 10 (wherein dividing line information integration device is a lane-dividing line recognizer).) configured to recognize data on a lane dividing line ahead of the vehicle in each of predetermined cycles (Fig. 5, illustrates detected dividing line ahead of the vehicle. Paragraph [0031]-KAGIMOTO discloses the dividing line information integration device 100 is constituted so as to repeatedly perform operation with a predetermined period. Further in paragraph [0032]-KAGIMOTO discloses the dividing line detection sensor 200 is a sensor that is mounted on the vehicle 10 and detects dividing lines around the vehicle 10. The dividing line detection sensor 200 is, for example, a stereo camera, an entire circumference overhead camera system, a light detection and ranging (LIDAR), a monocular camera, or a sensor capable of detecting other dividing lines (wherein detecting dividing lines is recognize data on a lane dividing line).), based on sensing data on a traveling environment in front of the vehicle (Fig. 1 and 2A-B. Paragraph [0032]-KAGIMOTO discloses the dividing line detection sensor 200 is a sensor that is mounted on the vehicle 10 and detects dividing lines around the vehicle 10. The dividing line detection sensor 200 is, for example, a stereo camera, an entire circumference overhead camera system, a light detection and ranging (LIDAR), a monocular camera, or a sensor capable of detecting other dividing lines (wherein detects dividing lines around the vehicle includes the environment in front of the vehicle). Further in paragraph [0033]-KAGIMOTO disclose the stereo camera generates a parallax image from images of two cameras and measures a relative position from the vehicle 10, relative speed, a line type of the dividing line, and the like, with respect to each pixel of an image of the dividing line (wherein pixels of an image are sensing data).);
a relative coordinate calculator (Fig. 1, #100 called dividing line information integration device. Paragraph [0028]-KAGIMOTO discloses the dividing line information integration device 100 includes, for example, a central processing unit, a storage device such as a memory and a hard disk, a computer program stored in the storage device, and an input/output device. Specifically, the dividing line information integration device 100 is a computer system such as firmware or a microcontroller. Further, the dividing line information integration device 100 may be part of an electronic control unit (ECU) for an ADAS or an AD mounted on the vehicle 10 (wherein dividing line information integration device is a relative coordinate calculator).) configured to extract a tentative complementary point from the data on the lane dividing line point (Fig. 5, illustrates a tentative complementary point #30A. Paragraph [0051]-KAGIMOTO discloses the recognized dividing line is generated by converting the dividing line recognized in the processing P2 into a likely shape using a least squares method, or the like. The processing in the processing P4 corresponds to a recognized dividing line generation unit (first dividing line generation unit) that generates the recognized dividing line (wherein converting is extracting and wherein the detected dividing line is a tentative complementary point). Further in paragraph [0057]-KAGIMOTO discloses FIG. 5 illustrates a detected dividing line 30A and a dividing line 30B redrawn as the recognized dividing line based on this detection result (wherein the detected dividing line a tentative complementary point).) in each of the predetermined cycles (Fig. 1. Paragraph [0031]-KAGIMOTO discloses the dividing line information integration device 100 is constituted so as to repeatedly perform operation with a predetermined period.), and
calculate relative coordinates of the tentative complementary point with respect to the vehicle (Fig. 5, #30B illustrates the relative coordinates of the tentative complementary point. Paragraph [0051]-KAGIMOTO discloses self-position/posture information (the position/posture of the own vehicle) necessary for accumulating the recognized dividing lines of the vehicle 10 and accumulating the traveling trajectory of the other vehicle 11 is estimated. In the processing P3, the self-position/posture information is estimated on the basis of the sensor information recognized in the processing P2. In processing P4, the dividing line is recognized from the information of the dividing line recognized in the processing P2, and the recognized dividing line is generated as the recognized dividing line. The recognized dividing line is generated by converting the dividing line recognized in the processing P2 into a likely shape using a least squares method, or the like. The processing in the processing P4 corresponds to a recognized dividing line generation unit (first dividing line generation unit) that generates the recognized dividing line (wherein the recognized dividing line is the tentative complementary point and wherein the coordinates are calculated as part of generating the recognized dividing line).);
a second complementary point calculator (Fig. 1, #100 called dividing line information integration device. Paragraph [0028]-KAGIMOTO discloses the dividing line information integration device 100 includes, for example, a central processing unit, a storage device such as a memory and a hard disk, a computer program stored in the storage device, and an input/output device. Specifically, the dividing line information integration device 100 is a computer system such as firmware or a microcontroller. Further, the dividing line information integration device 100 may be part of an electronic control unit (ECU) for an ADAS or an AD mounted on the vehicle 10 (wherein dividing line information integration device is a second complementary point calculator).) configured to calculate absolute position data on the tentative complementary point from the relative coordinates of the tentative complementary point (Fig. 10. Paragraph [0052]-KAGIMOTO discloses the dividing line is estimated on the basis of the positional relationship between the traveling trajectory of the other vehicle and the recognized dividing line generated in the processing P8, and the estimated dividing line is generated as the trajectory dividing line (wherein the trajectory dividing line is the absolute position data and wherein the tentative complementary point is the recognized dividing line).), based on absolute position data on the vehicle measured using signals from positioning satellites in each of the predetermined cycles (Fig. 1. Paragraph [0036]-KAGIMOTO discloses the positioning sensor 400 includes, for example, a velocity sensor, an acceleration sensor, an angular velocity sensor, a steering angle sensor, a gyro sensor, and a satellite positioning system such as a global navigation satellite system (GNSS) mounted on the vehicle 10 (wherein positioning data obtained from the GNSS is absolute position data of the vehicle). Further in paragraph [0031]-KAGIMOTO discloses the dividing line information integration device 100 is constituted so as to repeatedly perform operation with a predetermined period.), and
KAGIMOTO fails to explicitly teach a first complementary point calculator configured to update the relative coordinates of the tentative complementary point having been calculated, based on traveling information on the vehicle in each of the predetermined cycles, and calculate a first lane-dividing line complementary point usable for complementing the data on the lane dividing line by data on a lane dividing line behind the vehicle; calculate a second lane-dividing line complementary point usable for complementing the data on the lane dividing line by the data on the lane dividing line behind the vehicle, from the absolute position data on the tentative complement point having been extracted and the absolute position data on the vehicle currently measured.
However, KURODA explicitly teaches a first complementary point calculator (Fig. 1, #50 called vehicle travel controller. Paragraph [0036]-KURODA discloses as illustrated in the drawing, a vehicle travel controller 50 mainly includes an object recognition apparatus 20 which recognizes a position of an object existing behind an own vehicle, a steering angle sensor 21, a yaw rate sensor 22, a vehicle wheel speed sensor 23, a navigation system 24, and a control unit 25 which generates various control signals for controlling a travel state and the like of an own vehicle on the basis of a position of an object recognized by the object recognition apparatus 20.) configured to update the relative coordinates of the tentative complementary point having been calculated (Fig. 4-5. Paragraph [0054]-KURODA discloses in accordance with a series of conversion, coordinate information from the positions R1 to R3 of the right road dividing line detected at the time t(n) to positions Rm1 to Rm3 of the right road dividing line detected at the time t(n+m) is totally stored as the vehicle lane position information in the vehicle lane position information storage unit 10 at the time t(n+m) (see FIG. 5). Similarly, even in the left road dividing line, the position information of the road dividing line detected by the vehicle lane detection device 2 from the time t(n) to the time t(n+m) is stored as the vehicle lane position information in the vehicle lane position information storage unit 10. Further see paragraph [0050-0051].), based on traveling information on the vehicle in each of the predetermined cycles (Fig. 5. Paragraph [0051]-KURODA discloses the vehicle lane position estimation unit 4 converts the vehicle lane position detected in the past as the coordinate system using the center of the own vehicle as an original point in time on the basis of the information detected from the travel history calculation unit 11 and stores the conversion result in the vehicle lane position information storage unit 10 (wherein the information detected from the travel history calculation unit is traveling information on the vehicle).), and
calculate a first lane-dividing line complementary point (Fig. 6, illustrates that Ln1, Ln2, Rn1, and Rn2, are first lane-dividing line complementary points. Paragraph [0058]) usable for complementing the data on the lane dividing line by data on a lane dividing line behind the vehicle (Fig. 6, illustrates that Ln1, Ln2, Rn1, and Rn2, are first lane-dividing line complementary points. Paragraph [0057]-KURODA discloses the relative position calculation unit 5 is used to calculate a relative position of an object detected by the rear object detection device 1 at the position of the vehicle lane behind the own vehicle stored in the vehicle lane position information storage unit 10. Further in paragraph [0058]-KURODA discloses in the vehicle lane position information illustrated in FIG. 6 or 7, positions Rn1 and Rn2 of the right road dividing line are closest to each other in the Y-axis direction and positions Ln1 and Ln2 of the left road dividing line are closest to each other in the Y-axis direction. Then, the relative position calculation unit 5 obtains a line connecting two points Rn1 and Rn2 of the right road dividing line position, obtains an X-direction distance xr_np at a place corresponding to the position of the line in the Y-axis direction of the target vehicle VT, calculates a large/small relation between a value of the distance xr_np and a value P of the target vehicle VT in the X-axis direction, and transmits the calculation result to the determination unit 6 (wherein Ln1 is a first lane-dividing line complementary point which is able to be used to complement data on the lane dividing line behind the vehicle.);
calculate a second lane-dividing line complementary point (Fig. 6, illustrates that Ln1, Ln2, Rn1, and Rn2, are second lane-dividing line complementary points. Paragraph [0058]) usable for complementing the data on the lane dividing line by the data on the lane dividing line behind the vehicle (Fig. 6, illustrates that Ln1, Ln2, Rn1, and Rn2, are second lane-dividing line complementary points. Paragraph [0057]-KURODA discloses the relative position calculation unit 5 is used to calculate a relative position of an object detected by the rear object detection device 1 at the position of the vehicle lane behind the own vehicle stored in the vehicle lane position information storage unit 10. Further in paragraph [0058]-KURODA discloses in the vehicle lane position information illustrated in FIG. 6 or 7, positions Rn1 and Rn2 of the right road dividing line are closest to each other in the Y-axis direction and positions Ln1 and Ln2 of the left road dividing line are closest to each other in the Y-axis direction. Then, the relative position calculation unit 5 obtains a line connecting two points Rn1 and Rn2 of the right road dividing line position, obtains an X-direction distance xr_np at a place corresponding to the position of the line in the Y-axis direction of the target vehicle VT, calculates a large/small relation between a value of the distance xr_np and a value P of the target vehicle VT in the X-axis direction, and transmits the calculation result to the determination unit 6 (wherein Ln2 is a second lane-dividing line complementary point which is able to be used to complement data on the lane dividing line behind the vehicle).), from the absolute position data on the tentative complement point having been extracted (Fig. 3. Paragraph [0042]-KURODA discloses the vehicle lane detection unit 9 performs, for example, a binarization process or a feature point extraction process based on the image captured by the camera 8 to select a pixel (a road dividing line candidate point) which is considered as a road dividing line (including a white line, a yellow line, a broken line, or bott's-dots) on a road from the image, recognizes continuously arranged road dividing line candidate points as a road dividing line constituting the vehicle lane to obtain the position, and transmits information on the position to the vehicle lane position estimation unit 4 of the travel history calculation device 3 (wherein the candidate points are tentative complementary points and wherein the position of the vehicle late is absolute position data).) and the absolute position data on the vehicle currently measured (Fig. 3-4. Paragraph [0046]-KURODA discloses on the assumption that the coordinate system using the center of the own vehicle as an original point at the time t(n) is indicated by X(n)-Y(n), the coordinate system using the center of the own vehicle as an original point at the time t(n+1) is indicated by X(n+1)-Y(n+1), the speed of the own vehicle VS at the time t(n) is indicated by V.sub.n, and the traveling direction is indicated by θ.sub.n, a positional change amount (Δx, Δy) of the own vehicle VS for Δt=(t(n+1)−t(n)) (wherein the coordinate system using the center of the own vehicle/a positio9nal change amount is absolute position data on the vehicle currently measured).);
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of KAGIMOTO of a lane-dividing line recognition apparatus for a vehicle, the lane-dividing line recognition apparatus comprising: a lane-dividing line recognizer configured to recognize data on a lane dividing line ahead of the vehicle in each of predetermined cycles, based on sensing data on a traveling environment in front of the vehicle; a relative coordinate calculator configured to extract a tentative complementary point from the data on the lane dividing line in each of the predetermined cycles, and calculate relative coordinates of the tentative complementary point with respect to the vehicle with the teachings of KURODA of a first complementary point calculator configured to update the relative coordinates of the tentative complementary point having been calculated, based on traveling information on the vehicle in each of the predetermined cycles, and calculate a first lane-dividing line complementary point usable for complementing the data on the lane dividing line by data on a lane dividing line behind the vehicle; calculate a second lane-dividing line complementary point usable for complementing the data on the lane dividing line by the data on the lane dividing line behind the vehicle, from the absolute position data on the tentative complement point having been extracted and the absolute position data on the vehicle currently measured.
Wherein having KAGIMOTO’s lane dividing line recognition device having a first complementary point calculator configured to update the relative coordinates of the tentative complementary point having been calculated, based on traveling information on the vehicle in each of the predetermined cycles, and calculate a first lane-dividing line complementary point usable for complementing the data on the lane dividing line by data on a lane dividing line behind the vehicle; calculate a second lane-dividing line complementary point usable for complementing the data on the lane dividing line by the data on the lane dividing line behind the vehicle, from the absolute position data on the tentative complement point having been extracted and the absolute position data on the vehicle currently measured.
The motivation behind the modification would have been to obtain a lane diving line recognition device that enhances the ability to accurately detect the lane diving lines in order to provide driving assistance. Since both KAGIMOTO and KURODA involve detecting lane dividing lines, wherein KAGIMOTO it is possible to expand a range in which driving assistance or automatic driving functions, while KURODA it is possible to accurately recognize the position of the object existing at the rear side including the oblique rear side of the own vehicle. Please see KAGIMOTO et al. (US 20240005673 A1), Paragraph [0008], and KURODA (US 20170053533 A1), Paragraph [0012].
KAGIMOTO in view of KURODA fail to explicitly teach a first evaluation value acquirer configured to acquire a first evaluation value usable for evaluating accuracy in detecting the traveling information in each of the predetermined cycles; a second evaluation value acquirer configured to acquire a second evaluation value usable for evaluating accuracy in detecting the absolute position data on the vehicle in each of the predetermined cycles; and a complementary point integrator configured to integrate the first lane-dividing line complementary point and the second lane-dividing line complementary point corresponding to each other, using reliability calculated based on the first evaluation value and the second evaluation value.
However, HIROYUKI explicitly teaches a first evaluation value acquirer (Fig. 1, #100 called vehicle control device. Paragraph [0018]-HIROYUKI discloses the vehicle control device 100 is a device that controls operations of a vehicle, and is mounted in the vehicle. The vehicle control device 100 includes a calculation unit 110, a GNSS tuner 120, a gyro sensor 130, and a high-precision map 140. Further in paragraph [0053]-HIROYUKI discloses the above configurations, functions, and the like may be realized by software in which a processor interprets and executes a program that realizes each function.) configured to acquire a first evaluation value usable for evaluating accuracy in detecting the traveling information in each of the predetermined cycles (Fig. 5. Paragraph [0038]-HIROYUKI discloses the reliability calculation unit 1136 calculates the distance (perpendicular distance) between the estimated vehicle position and the center line of each lane. For a lane where the distance between the vehicle position and the center line is smaller, the reliability calculation unit 1136 sets the reliability to be higher (wherein the distance between the estimated vehicle position and the center line of each lane is the first evaluation value and wherein the traveling information is the distance).);
a second evaluation value acquirer (Fig. 1, #100 called vehicle control device. Paragraph [0018]-HIROYUKI discloses the vehicle control device 100 is a device that controls operations of a vehicle, and is mounted in the vehicle. The vehicle control device 100 includes a calculation unit 110, a GNSS tuner 120, a gyro sensor 130, and a high-precision map 140. Further in paragraph [0053]-HIROYUKI discloses the above configurations, functions, and the like may be realized by software in which a processor interprets and executes a program that realizes each function.) configured to acquire a second evaluation value usable for evaluating accuracy in detecting the absolute position data on the vehicle in each of the predetermined cycles (Fig. 2. Paragraph [0046]-HIROYUKI discloses the accuracy of the estimation of the vehicle position can be calculated based on, for example, the information on positioning error obtained from a GNSS tuner 120. When the accuracy of the estimation of the vehicle position is low, the reliability calculation unit 1136 may set the reliability of the estimation result by the third detector 1133 to be lower than those in other cases (wherein the positioning error obtained from a GNSS tuner is a second evaluation value and wherein the vehicle position determined from the GNSS is the absolute position data).); and
a complementary point integrator (Fig. 1, #100 called vehicle control device. Paragraph [0018]-HIROYUKI discloses the vehicle control device 100 is a device that controls operations of a vehicle, and is mounted in the vehicle. The vehicle control device 100 includes a calculation unit 110, a GNSS tuner 120, a gyro sensor 130, and a high-precision map 140. Further in paragraph [0053]-HIROYUKI discloses the above configurations, functions, and the like may be realized by software in which a processor interprets and executes a program that realizes each function.) configured to integrate the first lane-dividing line complementary point and the second lane-dividing line complementary point corresponding to each other (Fig. 2. Paragraph [0041]-HIROYUKI discloses the detection methods that the respective detectors use when estimating a traveling lane are different from each other for each detector, the detection methods including those to be used in: estimating a traveling lane using a position estimation result (the first detector 1131 to the third detector 1133); estimating a traveling lane using an image of the surroundings of the vehicle (the fourth detector 1134); estimating a traveling lane using a combination thereof (the second detector 1132); and the like. Therefore, the integrated reliability is calculated by integrating the results of estimating a traveling lane from a plurality of viewpoints (wherein the position of the traveling lane estimated using a position estimation result from the first detector and a position estimation result from the third detector are the first and second lane-dividing line complementary points and wherein the position estimation results integrated from a plurality of viewpoints all correspond to each other as they all correspond to the same detected lane).), using reliability calculated based on the first evaluation value (Fig. 5. Paragraph [0038]-HIROYUKI discloses the reliability calculation unit 1136 calculates the distance (perpendicular distance) between the estimated vehicle position and the center line of each lane. For a lane where the distance between the vehicle position and the center line is smaller, the reliability calculation unit 1136 sets the reliability to be higher (wherein the distance between the estimated vehicle position and the center line of each lane is the first evaluation value and wherein the traveling information is the distance).) and the second evaluation value (Fig. 2. Paragraph [0046]-HIROYUKI discloses the accuracy of the estimation of the vehicle position can be calculated based on, for example, the information on positioning error obtained from a GNSS tuner 120. When the accuracy of the estimation of the vehicle position is low, the reliability calculation unit 1136 may set the reliability of the estimation result by the third detector 1133 to be lower than those in other cases (wherein the positioning error obtained from a GNSS tuner is a second evaluation value and wherein the vehicle position determined from the GNSS is the absolute position data).).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of KAGIMOTO in view of KURODA of a lane-dividing line recognition apparatus for a vehicle, the lane-dividing line recognition apparatus comprising: a lane-dividing line recognizer configured to recognize data on a lane dividing line ahead of the vehicle in each of predetermined cycles, based on sensing data on a traveling environment in front of the vehicle; a relative coordinate calculator configured to extract a tentative complementary point from the data on the lane dividing line in each of the predetermined cycles, and calculate relative coordinates of the tentative complementary point with respect to the vehicle with the teachings of HIROYUKI of a first evaluation value acquirer configured to acquire a first evaluation value usable for evaluating accuracy in detecting the traveling information in each of the predetermined cycles; a second evaluation value acquirer configured to acquire a second evaluation value usable for evaluating accuracy in detecting the absolute position data on the vehicle in each of the predetermined cycles; and a complementary point integrator configured to integrate the first lane-dividing line complementary point and the second lane-dividing line complementary point corresponding to each other, using reliability calculated based on the first evaluation value and the second evaluation value.
Wherein having KAGIMOTO’s lane dividing line recognition device having a first evaluation value acquirer configured to acquire a first evaluation value usable for evaluating accuracy in detecting the traveling information in each of the predetermined cycles; a second evaluation value acquirer configured to acquire a second evaluation value usable for evaluating accuracy in detecting the absolute position data on the vehicle in each of the predetermined cycles; and a complementary point integrator configured to integrate the first lane-dividing line complementary point and the second lane-dividing line complementary point corresponding to each other, using reliability calculated based on the first evaluation value and the second evaluation value.
The motivation behind the modification would have been to obtain a lane diving line recognition device that enhances the ability to accurately detect the lane diving lines in order to provide driving assistance. Since both KAGIMOTO and HIROYUKI relate to vehicle control units and incorporate detecting lane dividing lines, wherein KAGIMOTO it is possible to expand a range in which driving assistance or automatic driving functions, while HIROYUKI the reliabilities of the respective estimation results by the respective detectors are integrated and compared with each other, so that a traveling lane can be accurately estimated even if the accuracy of the estimation result by any of the detectors is not sufficient. Please see KAGIMOTO et al. (US 20240005673 A1), Paragraph [0008], and HIROYUKI (US 20220178703 A1), Paragraph [0010].
Regarding claim 4, KAGIMOTO explicitly teaches a lane-dividing line recognition apparatus for a vehicle (Fig. 1. Paragraph [0027]-KAGIMOTO discloses FIG. 1 is a hardware configuration diagram illustrating an embodiment of a dividing line recognition device according to the present invention. A dividing line information integration device 100 of the present embodiment to which the dividing line recognition device according to the present invention is applied is mounted on a vehicle 10 and constitutes part of an advanced driver assistance system (ADAS) or an automated driving system (AD).), the lane-dividing line recognition apparatus comprising
a processor configured to (Fig. 1, #100 called dividing line information integration device. Paragraph [0028]-KAGIMOTO discloses the dividing line information integration device 100 includes, for example, a central processing unit, a storage device such as a memory and a hard disk, a computer program stored in the storage device, and an input/output device. Specifically, the dividing line information integration device 100 is a computer system such as firmware or a microcontroller. Further, the dividing line information integration device 100 may be part of an electronic control unit (ECU) for an ADAS or an AD mounted on the vehicle 10 (wherein dividing line information integration device is a lane-dividing line recognizer).)
recognize data on a lane dividing line ahead of the vehicle in each of predetermined cycles (Fig. 5, illustrates detected dividing lines ahead of the vehicle. Paragraph [0031]-KAGIMOTO discloses the dividing line information integration device 100 is constituted so as to repeatedly perform operation with a predetermined period. Further in paragraph [0032]-KAGIMOTO discloses the dividing line detection sensor 200 is a sensor that is mounted on the vehicle 10 and detects dividing lines around the vehicle 10. The dividing line detection sensor 200 is, for example, a stereo camera, an entire circumference overhead camera system, a light detection and ranging (LIDAR), a monocular camera, or a sensor capable of detecting other dividing lines (wherein detecting dividing lines is recognize data on a lane dividing line).), based on sensing data on a traveling environment in front of the vehicle (Fig. 1 and 2A-B. Paragraph [0032]-KAGIMOTO discloses the dividing line detection sensor 200 is a sensor that is mounted on the vehicle 10 and detects dividing lines around the vehicle 10. The dividing line detection sensor 200 is, for example, a stereo camera, an entire circumference overhead camera system, a light detection and ranging (LIDAR), a monocular camera, or a sensor capable of detecting other dividing lines (wherein detects dividing lines around the vehicle includes the environment in front of the vehicle). Further in paragraph [0033]-KAGIMOTO disclose the stereo camera generates a parallax image from images of two cameras and measures a relative position from the vehicle 10, relative speed, a line type of the dividing line, and the like, with respect to each pixel of an image of the dividing line (wherein pixels of an image are sensing data).),
extract a tentative complementary point from the data on the lane dividing line (Fig. 5, illustrates a tentative complementary point #30A. Paragraph [0051]-KAGIMOTO discloses the recognized dividing line is generated by converting the dividing line recognized in the processing P2 into a likely shape using a least squares method, or the like. The processing in the processing P4 corresponds to a recognized dividing line generation unit (first dividing line generation unit) that generates the recognized dividing line (wherein converting is extracting and wherein the detected dividing line is a tentative complementary point). Further in paragraph [0057]-KAGIMOTO discloses FIG. 5 illustrates a detected dividing line 30A and a dividing line 30B redrawn as the recognized dividing line based on this detection result (wherein the detected dividing line a tentative complementary point).) in each of the predetermined cycles (Fig. 1. Paragraph [0031]-KAGIMOTO discloses the dividing line information integration device 100 is constituted so as to repeatedly perform operation with a predetermined period.) in each of the predetermined cycles (Fig. 1. Paragraph [0031]-KAGIMOTO discloses the dividing line information integration device 100 is constituted so as to repeatedly perform operation with a predetermined period.), and
calculate relative coordinates of the tentative complementary point with respect to the vehicle (Fig. 5, #30B illustrates the relative coordinates of the tentative complementary point. Paragraph [0051]-KAGIMOTO discloses self-position/posture information (the position/posture of the own vehicle) necessary for accumulating the recognized dividing lines of the vehicle 10 and accumulating the traveling trajectory of the other vehicle 11 is estimated. In the processing P3, the self-position/posture information is estimated on the basis of the sensor information recognized in the processing P2. In processing P4, the dividing line is recognized from the information of the dividing line recognized in the processing P2, and the recognized dividing line is generated as the recognized dividing line. The recognized dividing line is generated by converting the dividing line recognized in the processing P2 into a likely shape using a least squares method, or the like. The processing in the processing P4 corresponds to a recognized dividing line generation unit (first dividing line generation unit) that generates the recognized dividing line (wherein the recognized dividing line is the tentative complementary point and wherein the coordinates are calculated as part of generating the recognized dividing line).),
calculate absolute position data on the tentative complementary point from the relative coordinates of the tentative complementary point (Fig. 10. Paragraph [0052]-KAGIMOTO discloses the dividing line is estimated on the basis of the positional relationship between the traveling trajectory of the other vehicle and the recognized dividing line generated in the processing P8, and the estimated dividing line is generated as the trajectory dividing line (wherein the trajectory dividing line is the absolute position data and wherein the tentative complementary point is the recognized dividing line).), based on absolute position data on the vehicle measured using signals from positioning satellites in each of the predetermined cycles (Fig. 1. Paragraph [0036]-KAGIMOTO discloses the positioning sensor 400 includes, for example, a velocity sensor, an acceleration sensor, an angular velocity sensor, a steering angle sensor, a gyro sensor, and a satellite positioning system such as a global navigation satellite system (GNSS) mounted on the vehicle 10 (wherein positioning data obtained from the GNSS is absolute position data of the vehicle). Further in paragraph [0031]-KAGIMOTO discloses the dividing line information integration device 100 is constituted so as to repeatedly perform operation with a predetermined period.), and
KAGIMOTO fails to explicitly teach update the relative coordinates of the tentative complementary point having been calculated, based on traveling information on the vehicle in each of the predetermined cycles, and calculate a first lane-dividing line complementary point usable for complementing the data on the lane dividing line by data on a lane dividing line behind the vehicle, calculate a second lane-dividing line complementary point usable for complementing the data on the lane dividing line by the data on the lane dividing line behind the vehicle, from the absolute position data on the tentative complement point having been extracted and the absolute position data on the vehicle currently measured.
However, KURODA explicitly teaches update the relative coordinates of the tentative complementary point having been calculated (Fig. 4-5. Paragraph [0054]-KURODA discloses in accordance with a series of conversion, coordinate information from the positions R1 to R3 of the right road dividing line detected at the time t(n) to positions Rm1 to Rm3 of the right road dividing line detected at the time t(n+m) is totally stored as the vehicle lane position information in the vehicle lane position information storage unit 10 at the time t(n+m) (see FIG. 5). Similarly, even in the left road dividing line, the position information of the road dividing line detected by the vehicle lane detection device 2 from the time t(n) to the time t(n+m) is stored as the vehicle lane position information in the vehicle lane position information storage unit 10. Further see paragraph [0050-0051].), based on traveling information on the vehicle in each of the predetermined cycles (Fig. 4-5. Paragraph [0054]-KURODA discloses in accordance with a series of conversion, coordinate information from the positions R1 to R3 of the right road dividing line detected at the time t(n) to positions Rm1 to Rm3 of the right road dividing line detected at the time t(n+m) is totally stored as the vehicle lane position information in the vehicle lane position information storage unit 10 at the time t(n+m) (see FIG. 5). Similarly, even in the left road dividing line, the position information of the road dividing line detected by the vehicle lane detection device 2 from the time t(n) to the time t(n+m) is stored as the vehicle lane position information in the vehicle lane position information storage unit 10. Further see paragraph [0050-0051].), based on traveling information on the vehicle in each of the predetermined cycles (Fig. 5. Paragraph [0051]-KURODA discloses the vehicle lane position estimation unit 4 converts the vehicle lane position detected in the past as the coordinate system using the center of the own vehicle as an original point in time on the basis of the information detected from the travel history calculation unit 11 and stores the conversion result in the vehicle lane position information storage unit 10 (wherein the information detected from the travel history calculation unit is traveling information on the vehicle).), and
calculate a first lane-dividing line complementary point (Fig. 6, illustrates that Ln1, Ln2, Rn1, and Rn2, are first lane-dividing line complementary points. Paragraph [0058]) usable for complementing the data on the lane dividing line by data on a lane dividing line behind the vehicle (Fig. 6, illustrates that Ln1, Ln2, Rn1, and Rn2, are first lane-dividing line complementary points. Paragraph [0057]-KURODA discloses the relative position calculation unit 5 is used to calculate a relative position of an object detected by the rear object detection device 1 at the position of the vehicle lane behind the own vehicle stored in the vehicle lane position information storage unit 10. Further in paragraph [0058]-KURODA discloses in the vehicle lane position information illustrated in FIG. 6 or 7, positions Rn1 and Rn2 of the right road dividing line are closest to each other in the Y-axis direction and positions Ln1 and Ln2 of the left road dividing line are closest to each other in the Y-axis direction. Then, the relative position calculation unit 5 obtains a line connecting two points Rn1 and Rn2 of the right road dividing line position, obtains an X-direction distance xr_np at a place corresponding to the position of the line in the Y-axis direction of the target vehicle VT, calculates a large/small relation between a value of the distance xr_np and a value P of the target vehicle VT in the X-axis direction, and transmits the calculation result to the determination unit 6 (wherein Ln1 is a first lane-dividing line complementary point which is able to be used to complement data on the lane dividing line behind the vehicle).),
calculate a second lane-dividing line complementary point (Fig. 6, illustrates that Ln1, Ln2, Rn1, and Rn2, are second lane-dividing line complementary points. Paragraph [0058]) usable for complementing the data on the lane dividing line by the data on the lane dividing line behind the vehicle (Fig. 6, illustrates that Ln1, Ln2, Rn1, and Rn2, are second lane-dividing line complementary points. Paragraph [0057]-KURODA discloses the relative position calculation unit 5 is used to calculate a relative position of an object detected by the rear object detection device 1 at the position of the vehicle lane behind the own vehicle stored in the vehicle lane position information storage unit 10. Further in paragraph [0058]-KURODA discloses in the vehicle lane position information illustrated in FIG. 6 or 7, positions Rn1 and Rn2 of the right road dividing line are closest to each other in the Y-axis direction and positions Ln1 and Ln2 of the left road dividing line are closest to each other in the Y-axis direction. Then, the relative position calculation unit 5 obtains a line connecting two points Rn1 and Rn2 of the right road dividing line position, obtains an X-direction distance xr_np at a place corresponding to the position of the line in the Y-axis direction of the target vehicle VT, calculates a large/small relation between a value of the distance xr_np and a value P of the target vehicle VT in the X-axis direction, and transmits the calculation result to the determination unit 6 (wherein Ln2 is a second lane-dividing line complementary point which is able to be used to complement data on the lane dividing line behind the vehicle).), from the absolute position data on the tentative complement point having been extracted (Fig. 3. Paragraph [0042]-KURODA discloses the vehicle lane detection unit 9 performs, for example, a binarization process or a feature point extraction process based on the image captured by the camera 8 to select a pixel (a road dividing line candidate point) which is considered as a road dividing line (including a white line, a yellow line, a broken line, or bott's-dots) on a road from the image, recognizes continuously arranged road dividing line candidate points as a road dividing line constituting the vehicle lane to obtain the position, and transmits information on the position to the vehicle lane position estimation unit 4 of the travel history calculation device 3 (wherein the candidate points are tentative complementary points and wherein the position of the vehicle late is absolute position data).) and the absolute position data on the vehicle currently measured (Fig. 3-4. Paragraph [0046]-KURODA discloses on the assumption that the coordinate system using the center of the own vehicle as an original point at the time t(n) is indicated by X(n)-Y(n), the coordinate system using the center of the own vehicle as an original point at the time t(n+1) is indicated by X(n+1)-Y(n+1), the speed of the own vehicle VS at the time t(n) is indicated by V.sub.n, and the traveling direction is indicated by θ.sub.n, a positional change amount (Δx, Δy) of the own vehicle VS for Δt=(t(n+1)−t(n)) (wherein the coordinate system using the center of the own vehicle/a positio9nal change amount is absolute position data on the vehicle currently measured).),
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of KAGIMOTO of a lane-dividing line recognition apparatus for a vehicle, the lane-dividing line recognition apparatus comprising a processor configured to recognize data on a lane dividing line ahead of the vehicle in each of predetermined cycles, based on sensing data on a traveling environment in front of the vehicle, extract a tentative complementary point from the data on the lane dividing line in each of the predetermined cycles, and calculate relative coordinates of the tentative complementary point with respect to the vehicle with the teachings of KURODA of update the relative coordinates of the tentative complementary point having been calculated, based on traveling information on the vehicle in each of the predetermined cycles, and calculate a first lane-dividing line complementary point usable for complementing the data on the lane dividing line by data on a lane dividing line behind the vehicle, calculate a second lane-dividing line complementary point usable for complementing the data on the lane dividing line by the data on the lane dividing line behind the vehicle, from the absolute position data on the tentative complement point having been extracted and the absolute position data on the vehicle currently measured.
Wherein having KAGIMOTO’s lane dividing line recognition device having update the relative coordinates of the tentative complementary point having been calculated, based on traveling information on the vehicle in each of the predetermined cycles, and calculate a first lane-dividing line complementary point usable for complementing the data on the lane dividing line by data on a lane dividing line behind the vehicle, calculate a second lane-dividing line complementary point usable for complementing the data on the lane dividing line by the data on the lane dividing line behind the vehicle, from the absolute position data on the tentative complement point having been extracted and the absolute position data on the vehicle currently measured.
The motivation behind the modification would have been to obtain a lane diving line recognition device that enhances the ability to accurately detect the lane diving lines in order to provide driving assistance. Since both KAGIMOTO and KURODA involve detecting lane dividing lines, wherein KAGIMOTO it is possible to expand a range in which driving assistance or automatic driving functions, while KURODA it is possible to accurately recognize the position of the object existing at the rear side including the oblique rear side of the own vehicle. Please see KAGIMOTO et al. (US 20240005673 A1), Paragraph [0008], and KURODA (US 20170053533 A1), Paragraph [0012].
KAGIMOTO in view of KURODA fail to explicitly teach acquire a first evaluation value usable for evaluating accuracy in detecting the traveling information in each of the predetermined cycles, acquire a second evaluation value usable for evaluating accuracy in detecting the absolute position data on the vehicle in each of the predetermined cycles, and integrate the first lane-dividing line complementary point and the second lane-dividing line complementary point corresponding to each other, using reliability calculated based on the first evaluation value and the second evaluation value.
However, HIROYUKI explicitly teaches acquire a first evaluation value usable for evaluating accuracy in detecting the traveling information in each of the predetermined cycles (Fig. 5. Paragraph [0038]-HIROYUKI discloses the reliability calculation unit 1136 calculates the distance (perpendicular distance) between the estimated vehicle position and the center line of each lane. For a lane where the distance between the vehicle position and the center line is smaller, the reliability calculation unit 1136 sets the reliability to be higher (wherein the distance between the estimated vehicle position and the center line of each lane is the first evaluation value).),
acquire a second evaluation value usable for evaluating accuracy in detecting the absolute position data on the vehicle in each of the predetermined cycles (Fig. 2. Paragraph [0046]-HIROYUKI discloses the accuracy of the estimation of the vehicle position can be calculated based on, for example, the information on positioning error obtained from a GNSS tuner 120. When the accuracy of the estimation of the vehicle position is low, the reliability calculation unit 1136 may set the reliability of the estimation result by the third detector 1133 to be lower than those in other cases (wherein the positioning error obtained from a GNSS tuner is a second evaluation value and wherein the vehicle position determined from the GNSS is the absolute position data).), and
integrate the first lane-dividing line complementary point and the second lane-dividing line complementary point corresponding to each other (Fig. 2. Paragraph [0041]-HIROYUKI discloses the detection methods that the respective detectors use when estimating a traveling lane are different from each other for each detector, the detection methods including those to be used in: estimating a traveling lane using a position estimation result (the first detector 1131 to the third detector 1133); estimating a traveling lane using an image of the surroundings of the vehicle (the fourth detector 1134); estimating a traveling lane using a combination thereof (the second detector 1132); and the like. Therefore, the integrated reliability is calculated by integrating the results of estimating a traveling lane from a plurality of viewpoints (wherein the position of the traveling lane estimated using a position estimation result from the first detector and a position estimation result from the third detector are the first and second lane-dividing line complementary points and wherein the position estimation results integrated from a plurality of viewpoints all correspond to each other as they all correspond to the same detected lane).), using reliability calculated based on the first evaluation value (Fig. 5. Paragraph [0038]-HIROYUKI discloses the reliability calculation unit 1136 calculates the distance (perpendicular distance) between the estimated vehicle position and the center line of each lane. For a lane where the distance between the vehicle position and the center line is smaller, the reliability calculation unit 1136 sets the reliability to be higher (wherein the distance between the estimated vehicle position and the center line of each lane is the first evaluation value and wherein the traveling information is the distance).) and the second evaluation value (Fig. 2. Paragraph [0046]-HIROYUKI discloses the accuracy of the estimation of the vehicle position can be calculated based on, for example, the information on positioning error obtained from a GNSS tuner 120. When the accuracy of the estimation of the vehicle position is low, the reliability calculation unit 1136 may set the reliability of the estimation result by the third detector 1133 to be lower than those in other cases (wherein the positioning error obtained from a GNSS tuner is a second evaluation value and wherein the vehicle position determined from the GNSS is the absolute position data).).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of KAGIMOTO in view of KURODA of a lane-dividing line recognition apparatus for a vehicle, the lane-dividing line recognition apparatus comprising a processor configured to recognize data on a lane dividing line ahead of the vehicle in each of predetermined cycles, based on sensing data on a traveling environment in front of the vehicle, extract a tentative complementary point from the data on the lane dividing line in each of the predetermined cycles, and calculate relative coordinates of the tentative complementary point with respect to the vehicle with the teachings of HIROYUKI of acquire a first evaluation value usable for evaluating accuracy in detecting the traveling information in each of the predetermined cycles, acquire a second evaluation value usable for evaluating accuracy in detecting the absolute position data on the vehicle in each of the predetermined cycles, and integrate the first lane-dividing line complementary point and the second lane-dividing line complementary point corresponding to each other, using reliability calculated based on the first evaluation value and the second evaluation value.
Wherein having KAGIMOTO’s lane dividing line recognition device having acquire a first evaluation value usable for evaluating accuracy in detecting the traveling information in each of the predetermined cycles, acquire a second evaluation value usable for evaluating accuracy in detecting the absolute position data on the vehicle in each of the predetermined cycles, and integrate the first lane-dividing line complementary point and the second lane-dividing line complementary point corresponding to each other, using reliability calculated based on the first evaluation value and the second evaluation value.
The motivation behind the modification would have been to obtain a lane diving line recognition device that enhances the ability to accurately detect the lane diving lines in order to provide driving assistance. Since both KAGIMOTO and HIROYUKI relate to vehicle control units and incorporate detecting lane dividing lines, wherein KAGIMOTO it is possible to expand a range in which driving assistance or automatic driving functions, while HIROYUKI the reliabilities of the respective estimation results by the respective detectors are integrated and compared with each other, so that a traveling lane can be accurately estimated even if the accuracy of the estimation result by any of the detectors is not sufficient.. Please see KAGIMOTO et al. (US 20240005673 A1), Paragraph [0008], and HIROYUKI (US 20220178703 A1), Paragraph [0010].
Claim 2 is rejected under 35 U.S.C. 103 as being unpatentable over KAGIMOTO et al. (US 20240005673 A1), hereinafter referenced as KAGIMOTO, in view of KURODA (US 20170053533 A1), hereinafter referenced as KURODA, and further in view of HIROYUKI (US 20220178703 A1), hereinafter referenced as HIROYUKI, and further in view of OKA et al. (US 20180188029 A1), hereinafter referenced as OKA.
Regarding claim 2, KAGIMOTO in view of KURODA and further in view of HIROYUKI explicitly teach the lane-dividing line recognition apparatus according to claim 1, further comprising:
KAGIMOTO further explicitly teaches a yaw rate detector (Fig. 1, #400 called positioning sensor. Paragraph [0036]) configured to detect, as the traveling information, a yaw rate acting on the vehicle (Fig. 1. Paragraph [0036]-KAGIMOTO discloses the positioning sensor 400 includes, for example, a velocity sensor, an acceleration sensor, an angular velocity sensor, a steering angle sensor, a gyro sensor, and a satellite positioning system such as a global navigation satellite system (GNSS) mounted on the vehicle 10 (wherein an angular velocity sensor is a yaw rate detector as yaw rate is a vehicle’s angular velocity).); and
a vehicle speed detector (Fig. 1, #400 called positioning sensor. Paragraph [0036]) configured to detect, as the traveling information, a vehicle speed of the vehicle (Fig. 1. Paragraph [0036]-KAGIMOTO discloses the positioning sensor 400 includes, for example, a velocity sensor, an acceleration sensor, an angular velocity sensor, a steering angle sensor, a gyro sensor, and a satellite positioning system such as a global navigation satellite system (GNSS) mounted on the vehicle 10 (wherein a velocity sensor is a vehicle speed detector).), wherein
KAGIMOTO in view of KURODA and further in view of HIROYUKI fail to explicitly teach the first evaluation value acquirer is configured to calculate the first evaluation value, based on one or both of detection accuracy of the yaw rate detector and detection accuracy of the vehicle speed detector that vary depending on the traveling environment.
However, OKA explicitly teaches the first evaluation value acquirer (Fig. 1, called CPU #11. Paragraph [0032]-OKA discloses the ECU 1 is made of a typical computer and includes the CPU 11, the RAM 12 that is a main storage device or memory, the flash memory 13 that is an auxiliary storage device, an I/O, and bus lines connecting them.) is configured to calculate the first evaluation value (Fig. 1. Paragraph [0038]-OKA discloses the zero-point correction, as referred to herein, is to correct a detected value of the sensor whose zero point has been deviated from a correct zero due to aging of the sensor, temperature characteristics of the sensor, or an initial shift of an output of the sensor to agree with a value where the zero point of the sensor agrees with the correct zero. Further in paragraph [0039]-OKA discloses a correction value used in the zero-point correction is used to remove an error component, as arising from a deviation of the zero point, from a detected value of the sensor. The correction value is determined to correspond to an amount by which the zero point is deviated from zero (which will also be referred to as a deviation) (wherein the calculated zero point correction amount/deviation is the first evaluation value).), based on one or both of detection accuracy of the yaw rate detector and detection accuracy of the vehicle speed detector that vary depending on the traveling environment (Fig. 4, illustrates how detection accuracy changes given the traveling environment. Paragraph [0056]-OKA discloses the correction value determination portion F6 calculates the correction value Q based on the zero-point equivalent value Yz determined by the zero-point determination portion F5. Further in paragraph [0057]-OKA discloses the correction value Q is, as described above, the zero-point equivalent value Yz of the yaw rate sensor 5, that is, a value equivalent to a deviation of the zero point thereof. The corrected detected value Yq, as derived by subtracting the correction value Q from the detected value Y, will, therefore, represents a value the yaw rate sensor 5 properly detects, in other words, a yaw rate actually acting on the system-mounted vehicle (wherein the detection accuracy of the yaw rate detector is the deviation from the zero point for the yaw rate detector and wherein the detection accuracy of the vehicle speed detector is the deviation from the zero point for the yaw rate detector as the yaw rate is a measure of the vehicle speed).).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of KAGIMOTO in view of KURODA and further in view of HIROYUKI of a lane-dividing line recognition apparatus for a vehicle, the lane-dividing line recognition apparatus comprising: a lane-dividing line recognizer configured to recognize data on a lane dividing line ahead of the vehicle in each of predetermined cycles, based on sensing data on a traveling environment in front of the vehicle; a relative coordinate calculator configured to extract a tentative complementary point from the data on the lane dividing line in each of the predetermined cycles, and calculate relative coordinates of the tentative complementary point with respect to the vehicle with the teachings of OKA of the first evaluation value acquirer is configured to calculate the first evaluation value, based on one or both of detection accuracy of the yaw rate detector and detection accuracy of the vehicle speed detector that vary depending on the traveling environment.
Wherein having KAGIMOTO’s lane dividing line recognition device having the first evaluation value acquirer is configured to calculate the first evaluation value, based on one or both of detection accuracy of the yaw rate detector and detection accuracy of the vehicle speed detector that vary depending on the traveling environment.
The motivation behind the modification would have been to obtain a lane diving line recognition device that enhances the ability to accurately detect the lane diving lines in order to provide driving assistance. Since both KAGIMOTO and OKA relate to vehicle control units and incorporate detecting lane dividing lines, wherein KAGIMOTO it is possible to expand a range in which driving assistance or automatic driving functions, while OKA it is possible to determine the correction value corresponding to a deviation of the current zero point while the vehicle is moving. This eliminates a risk that the correction value for use in the zero-point correction differs from an actual deviation of the zero point. Please see KAGIMOTO et al. (US 20240005673 A1), Paragraph [0008], and OKA et al. (US 20180188029 A1), Paragraph [0011].
Claim 3 is rejected under 35 U.S.C. 103 as being unpatentable over KAGIMOTO et al. (US 20240005673 A1), hereinafter referenced as KAGIMOTO, in view of KURODA (US 20170053533 A1), hereinafter referenced as KURODA, and further in view of HIROYUKI (US 20220178703 A1), hereinafter referenced as HIROYUKI, and further in view of KIYOHARA et al. (US 20230243657 A1), hereinafter referenced as KIYOHARA.
Regarding claim 3, KAGIMOTO in view of KURODA and further in view of HIROYUKI explicitly teach the lane-dividing line recognition apparatus according to claim 1,
KAGIMOTO in view of KURODA and further in view of HIROYUKI fail to explicitly teach wherein the second evaluation value acquirer is configured to calculate the second evaluation value, based on one or both of a number of the positioning satellites used in measuring the absolute position data and strength of the signals from the positioning satellites.
However, KIYOHARA explicitly teaches wherein the second evaluation value acquirer (Fig. 1, #100 called vehicle control device. Paragraph [0035]-KIYOHARA discloses the vehicle control device 100 is specifically an electronic control unit (ECU) including hardware such as an arithmetic device such as a central processing unit (CPU), a main storage device such as a semiconductor memory, an auxiliary storage device, and a communication device, and implements each function of the host vehicle position estimation unit 10 and the like by the arithmetic device executing a program loaded in the main storage device.) is configured to calculate the second evaluation value (Fig. 2. Paragraph [0050]-KIYOHARA discloses the satellite information indicates various parameters related to GNSS positioning, such as a positioning fix state obtained from the GNSS receiver, accuracy indexes such as position accuracy and speed accuracy, accuracy degradation indexes such as pDOP and vDOP, the number of satellites used for positioning, a reception signal strength of each positioning satellite, and a multipath flag (wherein the calculated satellite information is the second evaluation value).), based on one or both of a number of the positioning satellites used in measuring the absolute position data and strength of the signals from the positioning satellites (Fig. 2. Paragraph [0091]-KIYOHARA discloses in the satellite positioning, as described above, when the absolute position of the observation point is calculated from pseudo distances of a plurality of positioning satellites, a dilution of precision (DOP) such as a geometric dilution of precision (GDOP) and a position dilution of precision (PDOP) related to spatial coordinates can be calculated based on an observation vector. This is a numerical value calculated according to the positioning satellite arrangement in the sky. In addition, there are estimation accuracy indexes of the calculated absolute position, such as an index based on a value of a loss function at the time of calculating the absolute position by the least squares method described above and a positioning status such as 3D positioning or 2D positioning. Alternatively, an accuracy index (accuracy value) unique to a GNSS receiver manufacturer may be output, but the estimation accuracy indexes are used without being particularly distinguished in the present embodiment.).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of KAGIMOTO in view of KURODA and further in view of HIROYUKI of a lane-dividing line recognition apparatus for a vehicle, the lane-dividing line recognition apparatus comprising: a lane-dividing line recognizer configured to recognize data on a lane dividing line ahead of the vehicle in each of predetermined cycles, based on sensing data on a traveling environment in front of the vehicle; a relative coordinate calculator configured to extract a tentative complementary point from the data on the lane dividing line in each of the predetermined cycles, and calculate relative coordinates of the tentative complementary point with respect to the vehicle with the teachings of KIYOHARA of wherein the second evaluation value acquirer is configured to calculate the second evaluation value, based on one or both of a number of the positioning satellites used in measuring the absolute position data and strength of the signals from the positioning satellites.
Wherein having KAGIMOTO’s lane dividing line recognition device wherein the second evaluation value acquirer is configured to calculate the second evaluation value, based on one or both of a number of the positioning satellites used in measuring the absolute position data and strength of the signals from the positioning satellites.
The motivation behind the modification would have been to obtain a lane diving line recognition device that enhances the ability to accurately detect the lane diving lines in order to provide driving assistance. Since both KAGIMOTO and KIYOHARA relate to vehicle control units and incorporate detecting lane dividing lines, wherein KAGIMOTO it is possible to expand a range in which driving assistance or automatic driving functions, while KIYOHARA it is possible to frequently perform highly accurate estimation of a host vehicle position in a map even if the traveling environment and the traveling state change. Please see KAGIMOTO et al. (US 20240005673 A1), Paragraph [0008], and KIYOHARA et al. (US 20230243657 A1), Paragraph [0014].
Conclusion
Listed below are the prior arts made of record and not relied upon but are considered pertinent to applicant’s disclosure.
CHOI (US 20210323550 A1) – Provided is an apparatus for assisting driving of a vehicle, the apparatus comprising: a front camera mounted on a vehicle and having a field of view in front of the vehicle, the front camera configured to acquire front image data; a dynamics sensor mounted on the vehicle and configured to acquire dynamics data that is a motion state of the vehicle; and a controller including a processor configured to process the front image data and the dynamics data, wherein the controller is configured to generate a front virtual lane on the basis of the field of view in front of the vehicle based on the front image data, and generate a rear virtual lane on the basis of the field of view in rear of the vehicle based on the front virtual lane and the dynamics data…Abstract, Fig. 11.
WATANABE (US 20200104608 A1) – A lane-line recognizing apparatus includes an acquiring unit, an extractor, and an identifier including a storage and an estimator. The acquiring unit acquires a traveling environment information on a traveling environment in front of an own vehicle. The extractor extracts feature quantities of lane-line components of lane lines from each frame image on a basis of the traveling environment information acquired by the acquiring unit. The identifier identifies the lane lines on the basis of the feature quantities extracted by the extractor. The storage stores the feature quantities extracted by the extractor. When the feature quantities are extracted again after a transition from a condition where the lane lines are identifiable to a condition where the lane lines are unidentifiable, the estimator estimates, on the basis of the feature quantities stored in the storage, the lane lines after the transition to the condition where the lane lines are unidentifiable…Abstract, Fig. 3-5.
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/ETHAN N WOLFSON/ Examiner, Art Unit 2673
/CHINEYERE WILLS-BURNS/Supervisory Patent Examiner, Art Unit 2673
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