DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 11/12/2025 has been entered.
Response to Arguments
Applicant’s amendments to the claims are acknowledged. The objections to the claims are hereby withdrawn.
Applicant's arguments with respect to the rejections of claims 1-3, 5-13, 15-21, and 23 under 35 U.S.C. §101 have been fully considered but they are not persuasive. The step of obtaining initial position information using a millimeter-wave radar sensor amounts to no more than mere data gathering necessary to perform the abstract idea. The millimeter-wave sensor is recited at a high level of generality and does not provide any meaningful limitations on practicing the abstract idea. In order for a particular machine to integrate an abstract idea into a practical application, the machine must “play a significant part in permitting the claimed method to be performed, rather than function solely as an obvious mechanism for permitting a solution to be achieved more quickly”. See MPEP 2105.06(b). The millimeter-wave radar is not integral to the functioning of the abstract idea, when viewed individually or when viewing the claim as a whole. Examiner further notes that the amended limitations in claims 1 and 11 are additionally directed to an abstract idea comprising mathematical concepts.
Applicant's arguments with respect to the rejections of claims 1-3, 5-13, and 15-20 under 35 U.S.C. §103 have been fully considered and are persuasive. However, upon further consideration, a new ground(s) of rejection is made in view of further limiting amendments made to the claims, changing the scope of the claimed invention.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
101 Analysis – Step 1
Independent Claims 1 and 11 are directed to a method and apparatus, respectively, for positioning a vehicle.. Therefore, the independent claims are within at least one of the four statutory categories.
101 Analysis – Step 2A, Prong I
Regarding Prong I of the Step 2A analysis in the 2019 PEG, the claims are to be analyzed to determine whether they recite subject matter that falls within one of the following groups of abstract ideas: a) mathematical concepts, b) certain methods of organizing human activity, and/or c) mental processes.
Independent Claim 1 includes limitations that recite an abstract idea (emphasized below) and will be used as a representative claim for the remainder of the 101 rejection. The analogous independent Claim 11 is rejected for the same reasons as the representative Claim 1 as discussed here. Claim 1 recites:
A vehicle positioning method performed by a positioning apparatus in a to-be-positioned vehicle, comprising:
obtaining a global positioning system (GPS) position covariance of the to-be-positioned vehicle;
based on the GPS position covariance being less than or equal to a preset position covariance threshold, obtaining initial position information of the to-be-positioned vehicle and vehicle information of a surrounding vehicle, wherein a distance of the surrounding vehicle from the to-be-positioned vehicle is less than a preset distance threshold, and the vehicle information comprises distance information and vehicle speed information;
determining a first position reckoning result of the surrounding vehicle based on the initial position information of the to-be-positioned vehicle, initial position information of the surrounding vehicle, including establishing a vehicle tracking table based on the vehicle information of the surrounding vehicle;
wherein the vehicle tracking table includes:
identification information of the surrounding vehicle,
an obtaining time of the vehicle information,
the initial position information,
the vehicle speed information,
orientation information,
information about a distance between the surrounding vehicle and the to-be- positioned vehicle, and the first position reckoning result;
wherein the vehicle information of the surrounding vehicle obtained by a millimeter-wave radar sensor of the to-be-positioned vehicle;
and determining a second position reckoning result of the to-be-positioned vehicle based on the first position reckoning result;
The examiner submits that the foregoing bolded limitation(s) recite an abstract idea directed to a “mental process” because under its broadest reasonable interpretation, the claim covers performance of the limitation in the human mind. For example, “determining …” the first and second position reckoning results and “establishing…” a vehicle tracking table in the context of this claim encompasses a person looking at data collected (received, detected, etc.) and forming a simple judgement (determination, analysis, comparison, etc.) either mentally or using a pen and paper. The limitations regarding the initial position reckoning algorithm are additionally directed to mathematical concepts. Accordingly, the claim recites at least one abstract idea. The Examiner notes that under MPEP 2106.04(a)(2)(III), the courts consider a mental process (thinking) that "can be performed in the human mind, or by a human using a pen and paper" to be an abstract idea. CyberSource Corp. v. Retail Decisions, Inc., 654 F.3d 1366, 1372, 99 USPQ2d 1690, 1695 (Fed. Cir. 2011). As the Federal Circuit explained, "methods which can be performed mentally, or which are the equivalent of human mental work, are unpatentable abstract ideas the ‘basic tools of scientific and technological work’ that are open to all.’" 654 F.3d at 1371, 99 USPQ2d at 1694 (citing Gottschalk v. Benson, 409 U.S. 63, 175 USPQ 673 (1972)). See also Mayo Collaborative Servs. v. Prometheus Labs. Inc., 566 U.S. 66, 71, 101 USPQ2d 1961, 1965 ("‘[M]ental processes[] and abstract intellectual concepts are not patentable, as they are the basic tools of scientific and technological work’" (quoting Benson, 409 U.S. at 67, 175 USPQ at 675)); Parker v. Flook, 437 U.S. 584, 589, 198 USPQ 193, 197 (1978) (same).
101 Analysis – Step 2A, Prong II
Regarding Prong II of the Step 2A analysis in the 2019 PEG, the claims are to be analyzed to determine whether the claim, as a whole, integrates the abstract into a practical application. As noted in the 2019 PEG, it must be determined whether any additional elements in the claim beyond the abstract idea integrate the exception into a practical application in a manner that imposes a meaningful limit on the judicial exception. The courts have indicated that additional elements merely using a computer to implement an abstract idea, adding insignificant extra solution activity, or generally linking use of a judicial exception to a particular technological environment or field of use do not integrate a judicial exception into a “practical application.”
In the present case, the additional limitations beyond the above-noted abstract idea are as follows (where the underlined portions are the “additional limitations” while the bolded portions continue to represent the “abstract idea”):
A vehicle positioning method performed by a positioning apparatus in a to-be-positioned vehicle, comprising:
obtaining a global positioning system (GPS) position covariance of the to-be-positioned vehicle;
based on the GPS position covariance being less than or equal to a preset position covariance threshold, obtaining initial position information of the to-be-positioned vehicle and vehicle information of a surrounding vehicle, wherein a distance of the surrounding vehicle from the to-be-positioned vehicle is less than a preset distance threshold, and the vehicle information comprises distance information and vehicle speed information;
determining a first position reckoning result of the surrounding vehicle based on the initial position information of the to-be-positioned vehicle, initial position information of the surrounding vehicle, including establishing a vehicle tracking table based on the vehicle information of the surrounding vehicle;
wherein the vehicle tracking table includes:
identification information of the surrounding vehicle,
an obtaining time of the vehicle information,
the initial position information,
the vehicle speed information,
orientation information,
information about a distance between the surrounding vehicle and the to-be- positioned vehicle, and the first position reckoning result;
wherein the vehicle information of the surrounding vehicle obtained by a millimeter-wave radar sensor of the to-be-positioned vehicle;
and determining a second position reckoning result of the to-be-positioned vehicle based on the first position reckoning result;
For the following reason(s), the examiner submits that the above identified additional limitations do not integrate the above-noted abstract idea into a practical application.
Regarding the additional limitations above, the examiner submits that these limitations are insignificant extra-solution activities that merely use a computer (apparatus) to perform the process. In particular, the steps of obtaining initial position information and vehicle information are recited at a high level of generality (i.e. as a general means of receiving information for use in the determining and other steps), and amounts to no more than mere data gathering, which is a form of insignificant extra-solution activity. Lastly, Claims 1 and 11 further recite an apparatus, millimeter-wave radar sensor, a memory, and a processor. These limitations merely describe how to generally “apply” the otherwise mental judgements in a generic or general purpose vehicle control environment. See Alice Corp. Pty. Ltd. v. CLS Bank Int'l, 573 U.S. at 223 (“[T]he mere recitation of a generic computer cannot transform a patent-ineligible abstract idea into a patent-eligible invention.”). The apparatus, memory, and processor are recited at a high level of generality and merely automates the steps.
Thus, taken alone, the additional elements do not integrate the abstract idea into a practical application. Further, looking at the additional limitation(s) as an ordered combination or as a whole, the limitation(s) add nothing that is not already present when looking at the elements taken individually. For instance, there is no indication that the additional elements, when considered as a whole, reflect an improvement in the functioning of a computer or an improvement to another technology or technical field, apply or use the above-noted judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition, implement/use the above-noted judicial exception with a particular machine or manufacture that is integral to the claim, effect a transformation or reduction of a particular article to a different state or thing, or apply or use the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is not more than a drafting effort designed to monopolize the exception (MPEP § 2106.05). Accordingly, the additional limitation(s) do/does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea.
101 Analysis – Step 2B
Regarding Step 2B of the 2019 PEG, representative independent claim 9 does not include additional elements (considered both individually and as an ordered combination) that are sufficient to amount to significantly more than the judicial exception for the same reasons to those discussed above with respect to determining that the claim does not integrate the abstract idea into a practical application. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of using an apparatus, sensor, memory, and processor to perform the steps amounts to nothing more than applying the exception using generic computer components. Generally applying an exception using generic computer components cannot provide an inventive concept. And as discussed above, the additional step of obtaining position and vehicle information is considered insignificant extra-solution activity.
The additional limitation of obtaining position and vehicle information is well-understood, routine and conventional because the specification does not provide any indication that the vehicle is anything other than a conventional vehicle with conventional vehicle sensors. MPEP 2106.05(d)(II), and the cases cited therein, including Intellectual Ventures I, LLC v. Symantec Corp., 838 F.3d 1307, 1321 (Fed. Cir. 2016), TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610 (Fed. Cir. 2016), and OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363 (Fed. Cir. 2015), indicate that mere collection or receipt of data over a network is a well‐understood, routine, and conventional function when it is claimed in a merely generic manner. Hence, the claim is not patent eligible.
Dependent Claims 2-3, 5-10, 12-13, 15-21, and 23 do not recite any further limitations that cause the claims to be patent eligible. Rather, the limitations of dependent claims are directed toward additional aspects of the judicial exception and/or additional elements that do not integrate the judicial exception into a practical application. Therefore, dependent Claims 2-10 and 12-20 are not patent eligible under the same rationale as provided for in the rejection of Claim 1.
Therefore, Claims 1-3, 5-13, 15-21, and 23 are ineligible under 35 USC §101.
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, 8, 11 and 18 are rejected under 35 U.S.C. 103 as being unpatentable over US 20200124422 A1, with an earliest priority date of 10/23/2018, hereinafter “Sorstedt”, in view of US 20090099773 A1, with an earliest priority date of 10/15/2007, hereinafter “Watanabe”, further in view of US 20210291856 A1, with an earliest priority date of 03/17/2020, hereinafter “Uenoyama”.
Regarding Claim 1, Sorstedt teaches A vehicle positioning method performed by a positioning apparatus in a to-be-positioned vehicle. See at least [0056] and figure 2, method 200. Additionally, see at least [0070] and figure 3, vehicle 1 with vehicle control system 10.
comprising: obtaining a global positioning system (GPS) position of the to-be-positioned vehicle. See at least [0005], [0046], [0057], and figure 2, steps 109-110, wherein a position of the ego-vehicle is determined using GNSS.
obtaining initial position information of the to-be-positioned vehicle and vehicle information of a surrounding vehicle, wherein a distance of the surrounding vehicle from the to-be-positioned vehicle is less than a preset distance threshold, and the vehicle information comprises distance information and vehicle speed information. See at least [0049]-[0050], [0060]-[0061], and figure 2, steps 102-104, wherein initial relative position information and velocity information is obtained from a surrounding vehicle. The surrounding vehicle is selected on the basis of being within a predefined threshold distance from the ego vehicle.
determining a first position reckoning result of the surrounding vehicle based on the initial position information of the to-be-positioned vehicle, initial position information of the surrounding vehicle. See at least [0054], [0064]-[0065], and figure 2, steps 106 and 112, wherein a second position of the surrounding vehicle is determined based on the velocity information of the surrounding vehicle and the first, initial position information of the surrounding vehicle determined from the relative position between the ego vehicle and surrounding vehicle.
including establishing a vehicle tracking table based on the vehicle information of the surrounding vehicle; wherein the vehicle tracking table includes: the vehicle speed information, the initial position information, information about a distance between the surrounding vehicle and the ego-vehicle, and the first position reckoning result. See at least [0029]-[0032], wherein a state vector is established based on the vehicle information of the surrounding vehicle to track surrounding vehicles. The state vector includes information regarding the orientation θ of the surrounding vehicle and the positioning result (initial position information) of the surrounding vehicle. See at least [0060]-[0061], wherein the state vector additionally includes the measured velocities of the surrounding vehicles. See at least [0060]-[0062], wherein (xNm, yNm) represent the measured relative position, or distance, in the horizontal x direction and vertical y direction of surrounding vehicle N at moment T relative to the ego-vehicle. See at least [0065]-[0068], wherein the state vector is updated to include a second map position (first position reckoning result) of the surrounding vehicle.
wherein the vehicle information of the surrounding vehicle obtained by a radar sensor of the to-be-positioned vehicle. See at least [0060], wherein the vehicle information is obtained by a radar sensor of the ego vehicle.
determining a second position reckoning result of the to-be-positioned vehicle based on the first position reckoning result. See at least [0054], [0068], and figure 2, steps 108 and 113, wherein a second position of the ego vehicle is determined based on the determined position of the surrounding vehicle.
Sorstedt remains silent on obtaining a GPS covariance, and performing the method steps based on the GPS position covariance being less than or equal to a preset position covariance threshold, and the vehicle tracking table including identification information of the surrounding vehicle, an obtaining time of the vehicle information, orientation information. Sorstedt does teach the tracking table containing orientation information, but the orientation information is for the ego-vehicle only. Sorstedt additionally remains silent on the radar being a millimeter-wave radar.
Watanabe teaches obtaining a covariance, and performing the method steps based on the covariance being less than or equal to a preset position covariance threshold. See at least [0089], wherein the KF positioning method is performed based on an error covariance P not exceeding a predetermined threshold value. In combination with Sorstedt’s teaching of obtaining a GPS measurement, this limitation is taught in its entirety.
One having ordinary skill in the art, before the effective filing date of the claimed invention, would have found it obvious to modify Sorstedt with Watanabe’s technique of obtaining a covariance and performing a positioning method when the covariance is less than or equal to a preset position covariance threshold. It would have been obvious to modify because doing so enables increased accuracy and reliability during positioning, as recognized by Watanabe (see at least [0008]-[0030]).
Uenoyama teaches the vehicle tracking table including identification information of the surrounding vehicle, an obtaining time of the vehicle information, orientation information. See at least [0092] and figure 9, wherein database 311 is configured as a table storing vehicle ID information, date and time information, and vehicle steering angle information. In combination with Sorstedt’s teaching, discussed above, of the vehicle tracking table storing orientation information, this limitation is taught in its entirety.
a millimeter-wave radar sensor. See at least [0110], wherein the radar sensor is a millimeter wave radar.
One having ordinary skill in the art, before the effective filing date of the claimed invention, would have found it obvious to modify Sorstedt with Uenoyama’s vehicle tracking table and millimeter-wave radar sensor. It would have been obvious to modify because doing so enables vehicles to avoid performing inappropriate driving operations based on a situation surrounding the vehicle.
Regarding Claim 8, Sorstedt, Watanabe, and Uenoyama in combination teach all of the limitations of Claim 1 as discussed above, and Sorstedt additionally teaches performing the determining a first position reckoning result of the surrounding vehicle based on the initial position information of the to-be-positioned vehicle and the vehicle information of the surrounding vehicle. See at least [0049]-[0050], [0060]-[0061], and figure 2, steps 102-104, wherein initial relative position information and velocity information is obtained from a surrounding vehicle. Additionally, see at least [0054], [0064]-[0065], and figure 2, steps 106 and 112, wherein a second position of the surrounding vehicle is determined based on the velocity information of the surrounding vehicle and the first, initial position information determined from the relative position between the ego vehicle and surrounding vehicle.
Sorstedt remains silent on determining whether the GPS position covariance is greater than the preset position covariance threshold, and when the GPS position covariance is greater than the preset position covariance threshold.
Watanabe teaches determining whether the GPS position covariance is greater than the preset position covariance threshold, and when the GPS position covariance is greater than the preset position covariance threshold. See at least [0089], wherein if the covariance P is determined to exceed the predetermined threshold value, the LS positioning method is performed. In combination with Sorstedt’s teaching of obtaining a GPS measurement, this limitation is taught in its entirety.
One having ordinary skill in the art, before the effective filing date of the claimed invention, would have found it obvious to modify Sorstedt with Watanabe’s technique of obtaining a covariance and performing a positioning method when the covariance is less than or equal to a preset position covariance threshold. It would have been obvious to modify because doing so enables increased accuracy and reliability during positioning, as recognized by Watanabe (see at least [0008]-[0030]).
Regarding Claim 11, Sorstedt teaches A vehicle positioning apparatus in a to-be-positioned vehicle, comprising: a memory storing executable instructions; and a processor configured to execute the executable instructions. See at least [0056] and figure 2, method 200. Additionally, see at least [0070]-[0073] and figure 3, vehicle 1 with vehicle control system 10, containing processor 14 and memory 16.
to: obtain a global positioning system (GPS) position of a to-be-positioned vehicle. See at least [0005], [0046], [0057], and figure 2, steps 109-110, wherein a position of the ego-vehicle is determined using GNSS.
obtain initial position information of the to-be-positioned vehicle and vehicle information of a surrounding vehicle, wherein a distance of the surrounding vehicle from the to-be-positioned vehicle is less than a preset distance threshold, and the vehicle information comprises distance information and vehicle speed information. See at least [0049]-[0050], [0060]-[0061], and figure 2, steps 102-104, wherein initial relative position information and velocity information is obtained from a surrounding vehicle. The surrounding vehicle is selected on the basis of being within a predefined threshold distance from the ego vehicle.
determine a first position reckoning result of the surrounding vehicle based on the initial position information of the to-be-positioned vehicle, initial position of the surrounding vehicle. See at least [0054], [0064]-[0065], and figure 2, steps 106 and 112, wherein a second position of the surrounding vehicle is determined based on the velocity information of the surrounding vehicle and the first, initial position information of the surrounding vehicle determined from the relative position between the ego vehicle and surrounding vehicle. Additionally, see at least [0060], wherein the vehicle information is obtained by a sensor of the ego vehicle.
including establishing a vehicle tracking table based on the vehicle information of the surrounding vehicle; wherein the vehicle tracking table includes: the vehicle speed information, the initial position information, information about a distance between the surrounding vehicle and the ego-vehicle, and the first position reckoning result. See at least [0029]-[0032], wherein a state vector is established based on the vehicle information of the surrounding vehicle to track surrounding vehicles. The state vector includes information regarding the orientation θ of the surrounding vehicle and the positioning result (initial position information) of the surrounding vehicle. See at least [0060]-[0061], wherein the state vector additionally includes the measured velocities of the surrounding vehicles. See at least [0060]-[0062], wherein (xNm, yNm) represent the measured relative position, or distance, in the horizontal x direction and vertical y direction of surrounding vehicle N at moment T relative to the ego-vehicle. See at least [0065]-[0068], wherein the state vector is updated to include a second map position (first position reckoning result) of the surrounding vehicle.
wherein the vehicle information of the surrounding vehicle obtained by a millimeter-wave radar sensor of the to-be-positioned vehicle. See at least [0060], wherein the vehicle information is obtained by a radar sensor of the ego vehicle.
determine a second position reckoning result of the to-be-positioned vehicle based on the first position reckoning result. See at least [0054], [0068], and figure 2, steps 108 and 113, wherein a second position of the ego vehicle is determined based on the determined position of the surrounding vehicle.
Sorstedt remains silent on obtaining a GPS covariance, and performing the method steps based on the GPS position covariance being less than or equal to a preset position covariance threshold, and the vehicle tracking table including identification information of the surrounding vehicle, an obtaining time of the vehicle information, orientation information. Sorstedt does teach the tracking table containing orientation information, but the orientation information is for the ego-vehicle only. Sorstedt additionally remains silent on the radar being a millimeter-wave radar.
Watanabe teaches obtaining a covariance, and performing the method steps based on the covariance being less than or equal to a preset position covariance threshold. See at least [0089], wherein the KF positioning method is performed based on an error covariance P not exceeding a predetermined threshold value. In combination with Sorstedt’s teaching of obtaining a GPS measurement, this limitation is taught in its entirety.
One having ordinary skill in the art, before the effective filing date of the claimed invention, would have found it obvious to modify Sorstedt with Watanabe’s technique of obtaining a covariance and performing a positioning method when the covariance is less than or equal to a preset position covariance threshold. It would have been obvious to modify because doing so enables increased accuracy and reliability during positioning, as recognized by Watanabe (see at least [0008]-[0030]).
Uenoyama teaches the vehicle tracking table including identification information of the surrounding vehicle, an obtaining time of the vehicle information, orientation information. See at least [0092] and figure 9, wherein database 311 is configured as a table storing vehicle ID information, date and time information, and vehicle steering angle information. In combination with Sorstedt’s teaching, discussed above, of the vehicle tracking table storing orientation information, this limitation is taught in its entirety.
a millimeter-wave radar sensor. See at least [0110], wherein the radar sensor is a millimeter wave radar.
One having ordinary skill in the art, before the effective filing date of the claimed invention, would have found it obvious to modify Sorstedt with Uenoyama’s vehicle tracking table and millimeter-wave radar sensor. It would have been obvious to modify because doing so enables vehicles to avoid performing inappropriate driving operations based on a situation surrounding the vehicle.
Regarding Claim 18, Sorstedt, Watanabe, and Uenoyama in combination teach all of the limitations of Claim 11 as discussed above, and Sorstedt additionally teaches the processor is configured to: perform the step of determining a first position reckoning result of the surrounding vehicle based on the initial position information of the to-be-positioned vehicle and the vehicle information of the surrounding vehicle. See at least [0049]-[0050], [0060]-[0061], and figure 2, steps 102-104, wherein initial relative position information and velocity information is obtained from a surrounding vehicle. Additionally, see at least [0054], [0064]-[0065], and figure 2, steps 106 and 112, wherein a second position of the surrounding vehicle is determined based on the velocity information of the surrounding vehicle and the first, initial position information determined from the relative position between the ego vehicle and surrounding vehicle.
Sorstedt remains silent on wherein prior to determining the first position reckoning result, determine whether the GPS position covariance is greater than the preset position covariance threshold, and if the GPS position covariance is greater than the preset position covariance threshold.
Watanabe teaches determining whether the GPS position covariance is greater than the preset position covariance threshold, and when the GPS position covariance is greater than the preset position covariance threshold. See at least [0089], wherein if the covariance P is determined to exceed the predetermined threshold value, the LS positioning method is performed. In combination with Sorstedt’s teaching of obtaining a GPS measurement, this limitation is taught in its entirety.
One having ordinary skill in the art, before the effective filing date of the claimed invention, would have found it obvious to modify Sorstedt with Watanabe’s technique of obtaining a covariance and performing a positioning method when the covariance is less than or equal to a preset position covariance threshold. It would have been obvious to modify because doing so enables increased accuracy and reliability during positioning, as recognized by Watanabe (see at least [0008]-[0030]).
Claims 2-3, 5, 12-13, and 15 are rejected under 35 U.S.C. 103 as being unpatentable Sorstedt, Watanabe, and Uenoyama in combination, further in view of US 20120290146 A1, filed 07/15/2011, hereinafter “Dedes”, further in view of “Road Slope Aided Vehicle Position Estimation System Based on Sensor Fusion of GPS and Automotive Onboard Sensors”, published 08/25/2015, hereinafter “Jo”, and further in view of US 20220179104 A1, with an earliest priority date of 07/08/2019, hereinafter “Hamada”.
Regarding Claim 2, Sorstedt, Watanabe, and Uenoyama in combination teach all of the limitations of Claim 1 as discussed above, and Sorstedt additionally teaches wherein the vehicle information of the surrounding vehicle further comprises the identification information of the surrounding vehicle. See at least [0017] and [0071], wherein the vehicle information of the surrounding vehicle includes an identification of the surrounding vehicle.
the distance information comprises information about a horizontal distance between the surrounding vehicle and the to-be-positioned vehicle, and information about a vertical distance between the surrounding vehicle and the to-be-positioned vehicle. See at least [0057]-[0060] and figure 3, wherein the position information of the surrounding vehicle comprises a relative position of the surrounding vehicle to the ego vehicle in the x and y directions, or horizontal and vertical directions. Relative position to the ego vehicle is equivalent to distance to the ego vehicle.
and the vehicle speed information comprises the vehicle speed information of the surrounding vehicle. See at least [0060], wherein the velocity information obtained comprises velocity information of the surrounding vehicle.
Sorstedt remains silent on the orientation information of the surrounding vehicle, and information about an angle difference between the surrounding vehicle and the to-be-positioned vehicle, and the orientation information comprises yaw angle information of the surrounding vehicle, pitch angle information of the surrounding vehicle, and roll angle information of the surrounding vehicle, and the vehicle speed information comprises yaw angular velocity information of the surrounding vehicle.
Dedes teaches the orientation information of the surrounding vehicle, and the orientation information comprises yaw angle information of the surrounding vehicle, pitch angle information of the surrounding vehicle, and roll angle information of the surrounding vehicle. See at least [0010], wherein orientation information includes pitch, yaw, and roll information, and orientation information is received from surrounding vehicles of the host vehicle.
One having ordinary skill in the art, before the effective filing date of the claimed invention, would have found it obvious to further modify Sorstedt with Dedes’ technique of obtaining orientation information comprising yaw, pitch, and roll information of the surrounding vehicle. It would have been obvious to modify because doing so enables vehicles to establish safety situational awareness by processing position and orientation measurements of the host vehicle and surrounding vehicles, as recognized by Dedes (see at least [0004]-[0006]).
Jo teaches and the vehicle speed information comprises yaw angular velocity information of the surrounding vehicle. See at least pg. 251, Section II.A, wherein a yaw angular velocity w_gyro is obtained.
One having ordinary skill in the art, before the effective filing date of the claimed invention, would have found it obvious to further modify Sorstedt with Jo’s technique of obtaining yaw angular velocity information. It would have been obvious to modify because doing so enables increased position estimation accuracy and reliability, as recognized by Jo (see at least pg. 251, Section I).
Hamada teaches information about an angle difference between the surrounding vehicle and the to-be-positioned vehicle. See at least [0084] and figures 9-10, wherein the relative angle between the surrounding vehicle 201 and the ego vehicle 200 is determined.
One having ordinary skill in the art, before the effective filing date of the claimed invention, would have found it obvious to further modify Sorstedt with Hamada’s technique of obtaining information about an angle difference between the surrounding vehicle and the to-be-positioned vehicle. It would have been obvious to modify because doing so enables highly accurate position estimation based on surrounding vehicles of the subject vehicle, as recognized by Hamada (see at least [0011]).
Regarding Claim 3, Sorstedt, Watanabe, Uenoyama, Dedes, Jo, and Hamada in combination teach all of the limitations of Claim 2 as discussed above, and Sorstedt additionally teaches wherein the step of determining the first position reckoning result comprises: obtaining the initial position information of the surrounding vehicle based on the vehicle tracking table and the initial position information of the to-be-positioned vehicle by using the initial position reckoning algorithm. See at least [0049] and [0060]-[0063], wherein the surrounding vehicle’s position is initialized and stored in the vector using an initial positioning method.
and obtaining the first position reckoning result based on the initial position information of the surrounding vehicle and the vehicle information of the surrounding vehicle by using a first position reckoning algorithm. See at least [0064]-[0065], wherein the second position (first position reckoning result) of the surrounding vehicle is obtained based on the first position (initial position) of the surrounding vehicle.
Regarding Claim 5, Sorstedt, Watanabe, Uenoyama, Dedes, Jo, and Hamada in combination teach all of the limitations of Claim 3 as discussed above, and Sorstedt additionally teaches wherein the first position reckoning result comprises first position reckoning coordinates (xi_t, yi_t), wherein xi_t and yi_t respectively represent coordinate information in the preset x-coordinate axis direction and coordinate information in the preset y-coordinate axis direction that are of the surrounding vehicle numbered i and that are at a moment t, xi_t-∆t and yi_t-∆t respectively represent coordinate information in the preset x-coordinate axis direction and coordinate information in the preset y-coordinate axis direction that are of the surrounding vehicle numbered i and that are at the moment t-∆t, See at least [0060]-[0062], wherein the vector x includes (XN,YN) of each surrounding vehicle N at a moment T.
Sorstedt remains silent on wherein the first position reckoning result comprises first position reckoning coordinates (zi_t, yawi_t, pitchi_t, rolli_t), and the first position reckoning algorithm comprises: yawi_t = yawi_t-∆t + yawratei_t * ∆t; pitchi_t = pitchi_t-∆t; rolli_t = rolli_t-∆t; xi_t = xi_t-∆t + vi_t * cos yawi_t * ∆t; yi_t = yi_t-∆t + vi_t * sin yawi_t * ∆t; and zi_t = zi_t-∆t, wherein zi_t, yawi_t, pitchi_t, and rolli_t respectively represent coordinate information in the preset x-coordinate axis direction, coordinate information in the preset y-coordinate axis direction, coordinate information in the preset z-coordinate axis direction, yaw angle information, pitch angle information, and roll angle information, zi_t-∆t, yawi_t-∆t, pitchi_t-∆t, and rolli_t-∆t respectively represent coordinate information in the preset x-coordinate axis direction, coordinate information in the preset y-coordinate axis direction, coordinate information in the preset z-coordinate axis direction, yaw angle information, pitch angle information, and roll angle information, yawratei_t represents yaw angular velocity information that is of the surrounding vehicle numbered i and that is at the moment t,∆t is a preset time interval, and vi_t represents vehicle speed information that is of the surrounding vehicle numbered i and that is at the moment t.
Dedes teaches rolli-_t, wherein rolli_t represents roll angle information, rolli_t-∆t represents roll angle information. See at least [0010], wherein orientation information includes pitch, yaw, and roll information, and orientation information is received from surrounding vehicles of the host vehicle.
One having ordinary skill in the art, before the effective filing date of the claimed invention, would have found it obvious to further modify Sorstedt with Dedes’ technique of obtaining orientation information comprising yaw, pitch, and roll information of the surrounding vehicle. It would have been obvious to modify because doing so enables vehicles to establish safety situational awareness by processing position and orientation measurements of the host vehicle and surrounding vehicles, as recognized by Dedes (see at least [0004]-[0006]).
Jo teaches wherein the first position reckoning result comprises first position reckoning coordinates (zi_t, yawi_t, pitchi_t). See at least pg. 254, Section III.A.1 and equations (10)-(11), wherein the first position reckoning results include Xk, Yk, Zk, ψk, and θk. θ represents the road slope, which is equivalent to pitch. Additionally, see at least pg. 251, Section II.A, wherein ψ represents vehicle heading, which is equivalent to yaw.
and the first position reckoning algorithm comprises:
yawi_t = yawi_t-∆t + yawratei_t * ∆t. See at least pg. 254, Section III.A.1 and equation (10), wherein ψk = ψk-1 + ∆t * wXY. Additionally, see at least pg. 251, Section II.A, wherein wXY represents yaw rate.
pitchi_t = pitchi_t-∆t. See at least pg. 254, Section III.A.1 and equation (10), wherein θk = θk-1 + ∆t * wvertical. wvertical represents the pitch rate. If the pitch does not change, then Jo’s equation is equivalent to the claimed equation.
rolli_t = rolli_t-∆t. See at least pg. 254, Section III.A.1 and equation (10), wherein aXYk = aXYk-1. In combination with Dedes’ teaching, discussed above, of roll angle information, this limitation is taught in its entirety. One of ordinary skill in the art would find it obvious to modify Jo’s equations to incorporate Dedes’ roll angle information.
xi_t = xi_t-∆t + vi_t * cos yawi_t * ∆t. See at least pg. 254, Section III.A.1 and equation (10), wherein Vxy represents vehicle speed.
yi_t = yi_t-∆t + vi_t * sin yawi_t * ∆t. See at least pg. 254, Section III.A.1 and equation (10), wherein Vxy represents vehicle speed.
and zi_t = zi_t-∆t. See at least pg. 254, Section III.A.1 and equation (11), wherein Vxy represents vehicle speed. If the pitch angle is 0 degrees, i.e. the road is flat, then Jo’s equation is equivalent to the claimed equation.
wherein zi_t, yawi_t, and pitchi_t respectively represent coordinate information in the preset z-coordinate axis direction, yaw angle information, and pitch angle information, zi_t-∆t, yawi_t-∆t, and pitchi_t-∆t respectively represent coordinate information in the preset z-coordinate axis direction, yaw angle information, pitch angle information, and roll angle information. See at least pg. 254, Section III.A.1, wherein Z represents height (z-coordinate axis direction) and θ represents the road slope, which is equivalent to pitch. Additionally, see at least pg. 251, Section II.A, wherein ψ represents vehicle heading, which is equivalent to yaw.
yawratei_t represents yaw angular velocity information that is of the surrounding vehicle numbered i and that is at the moment t. See at least pg. 251, Section II.A, wherein wXY represents yaw rate.
∆t is a preset time interval. See at least pg. 255, wherein k and k-1 represent different time update steps.
and vi_t represents vehicle speed information that is of the surrounding vehicle numbered i and that is at the moment t. See at least pg. 254, Section III.A.1 and equation (10), wherein Vxy represents vehicle speed.
One having ordinary skill in the art, before the effective filing date of the claimed invention, would have found it obvious to further modify Sorstedt with Jo’s first position reckoning algorithm incorporating the roll angle information of Dedes. It would have been obvious to modify because doing so enables increased position estimation accuracy and reliability, as recognized by Jo (see at least pg. 251, Section I).
Regarding Claim 12, Sorstedt, Watanabe, and Uenoyama in combination teach all of the limitations of Claim 11 as discussed above, and Sorstedt additionally teaches wherein the vehicle information of the surrounding vehicle further comprises the identification information of the surrounding vehicle. See at least [0017] and [0071], wherein the vehicle information of the surrounding vehicle includes an identification of the surrounding vehicle.
the distance information comprises information about a horizontal distance between the surrounding vehicle and the to-be-positioned vehicle, and information about a vertical distance between the surrounding vehicle and the to-be-positioned vehicle. See at least [0057]-[0060] and figure 3, wherein the position information of the surrounding vehicle comprises a relative position of the surrounding vehicle to the ego vehicle in the x and y directions, or horizontal and vertical directions. Relative position to the ego vehicle is equivalent to distance to the ego vehicle.
and the vehicle speed information comprises the vehicle speed information of the surrounding vehicle. See at least [0060], wherein the velocity information obtained comprises velocity information of the surrounding vehicle.
Sorstedt remains silent on the orientation information of the surrounding vehicle, and information about an angle difference between the surrounding vehicle and the to-be-positioned vehicle, and the orientation information comprises yaw angle information of the surrounding vehicle, pitch angle information of the surrounding vehicle, and roll angle information of the surrounding vehicle, and the vehicle speed information comprises yaw angular velocity information of the surrounding vehicle.
Dedes teaches the orientation information of the surrounding vehicle, and the orientation information comprises yaw angle information of the surrounding vehicle, pitch angle information of the surrounding vehicle, and roll angle information of the surrounding vehicle. See at least [0010], wherein orientation information includes pitch, yaw, and roll information, and orientation information is received from surrounding vehicles of the host vehicle.
One having ordinary skill in the art, before the effective filing date of the claimed invention, would have found it obvious to further modify Sorstedt with Dedes’ technique of obtaining orientation information comprising yaw, pitch, and roll information of the surrounding vehicle. It would have been obvious to modify because doing so enables vehicles to establish safety situational awareness by processing position and orientation measurements of the host vehicle and surrounding vehicles, as recognized by Dedes (see at least [0004]-[0006]).
Jo teaches and the vehicle speed information comprises yaw angular velocity information of the surrounding vehicle. See at least pg. 251, Section II.A, wherein a yaw angular velocity w_gyro is obtained.
One having ordinary skill in the art, before the effective filing date of the claimed invention, would have found it obvious to further modify Sorstedt with Jo’s technique of obtaining yaw angular velocity information. It would have been obvious to modify because doing so enables increased position estimation accuracy and reliability, as recognized by Jo (see at least pg. 251, Section I).
Hamada teaches information about an angle difference between the surrounding vehicle and the to-be-positioned vehicle. See at least [0084] and figures 9-10, wherein the relative angle between the surrounding vehicle 201 and the ego vehicle 200 is determined.
One having ordinary skill in the art, before the effective filing date of the claimed invention, would have found it obvious to further modify Sorstedt with Hamada’s technique of obtaining information about an angle difference between the surrounding vehicle and the to-be-positioned vehicle. It would have been obvious to modify because doing so enables highly accurate position estimation based on surrounding vehicles of the subject vehicle, as recognized by Hamada (see at least [0011]).
Regarding Claim 13, Sorstedt, Watanabe, Uenoyama, Dedes, Jo, and Hamada in combination teach all of the limitations of Claim 12 as discussed above, and Sorstedt additionally teaches wherein the processor is configured to determine the first position reckoning result by: obtaining the initial position information of the surrounding vehicle based on the vehicle tracking table and the initial position information of the to-be-positioned vehicle by using the initial position reckoning algorithm. See at least [0049] and [0060]-[0063], wherein the surrounding vehicle’s position is initialized and stored in the vector using an initial positioning method.
and obtaining the first position reckoning result based on the initial position information of the surrounding vehicle and the vehicle information of the surrounding vehicle by using a first position reckoning algorithm. See at least [0064]-[0065], wherein the second position (first position reckoning result) of the surrounding vehicle is obtained based on the first position (initial position) of the surrounding vehicle.
Regarding Claim 15, Sorstedt, Watanabe, Uenoyama, Dedes, Jo, and Hamada in combination teach all of the limitations of Claim 13 as discussed above, and Sorstedt additionally teaches wherein the first position reckoning result comprises first position reckoning coordinates (xi_t, yi_t), wherein xi_t and yi_t respectively represent coordinate information in the preset x-coordinate axis direction and coordinate information in the preset y-coordinate axis direction that are of the surrounding vehicle numbered i and that are at a moment t, xi_t-∆t and yi_t-∆t respectively represent coordinate information in the preset x-coordinate axis direction and coordinate information in the preset y-coordinate axis direction that are of the surrounding vehicle numbered i and that are at the moment t-∆t, See at least [0060]-[0062], wherein the vector x includes (XN,YN) of each surrounding vehicle N at a moment T.
Sorstedt remains silent on wherein the first position reckoning result comprises first position reckoning coordinates (zi_t, yawi_t, pitchi_t, rolli_t), and the first position reckoning algorithm comprises: yawi_t = yawi_t-∆t + yawratei_t * ∆t; pitchi_t = pitchi_t-∆t; rolli_t = rolli_t-∆t; xi_t = xi_t-∆t + vi_t * cos yawi_t * ∆t; yi_t = yi_t-∆t + vi_t * sin yawi_t * ∆t; and zi_t = zi_t-∆t, wherein zi_t, yawi_t, pitchi_t, and rolli_t respectively represent coordinate information in the preset x-coordinate axis direction, coordinate information in the preset y-coordinate axis direction, coordinate information in the preset z-coordinate axis direction, yaw angle information, pitch angle information, and roll angle information, zi_t-∆t, yawi_t-∆t, pitchi_t-∆t, and rolli_t-∆t respectively represent coordinate information in the preset x-coordinate axis direction, coordinate information in the preset y-coordinate axis direction, coordinate information in the preset z-coordinate axis direction, yaw angle information, pitch angle information, and roll angle information, yawratei_t represents yaw angular velocity information that is of the surrounding vehicle numbered i and that is at the moment t,∆t is a preset time interval, and vi_t represents vehicle speed information that is of the surrounding vehicle numbered i and that is at the moment t.
Dedes teaches rolli-_t, wherein rolli_t represents roll angle information, rolli_t-∆t represents roll angle information. See at least [0010], wherein orientation information includes pitch, yaw, and roll information, and orientation information is received from surrounding vehicles of the host vehicle.
One having ordinary skill in the art, before the effective filing date of the claimed invention, would have found it obvious to further modify Sorstedt with Dedes’ technique of obtaining orientation information comprising yaw, pitch, and roll information of the surrounding vehicle. It would have been obvious to modify because doing so enables vehicles to establish safety situational awareness by processing position and orientation measurements of the host vehicle and surrounding vehicles, as recognized by Dedes (see at least [0004]-[0006]).
Jo teaches wherein the first position reckoning result comprises first position reckoning coordinates (zi_t, yawi_t, pitchi_t). See at least pg. 254, Section III.A.1 and equations (10)-(11), wherein the first position reckoning results include Xk, Yk, Zk, ψk, and θk. θ represents the road slope, which is equivalent to pitch. Additionally, see at least pg. 251, Section II.A, wherein ψ represents vehicle heading, which is equivalent to yaw.
and the first position reckoning algorithm comprises:
yawi_t = yawi_t-∆t + yawratei_t * ∆t. See at least pg. 254, Section III.A.1 and equation (10), wherein ψk = ψk-1 + ∆t * wXY. Additionally, see at least pg. 251, Section II.A, wherein wXY represents yaw rate.
pitchi_t = pitchi_t-∆t. See at least pg. 254, Section III.A.1 and equation (10), wherein θk = θk-1 + ∆t * wvertical. wvertical represents the pitch rate. If the pitch does not change, then Jo’s equation is equivalent to the claimed equation.
rolli_t = rolli_t-∆t. See at least pg. 254, Section III.A.1 and equation (10), wherein aXYk = aXYk-1. In combination with Dedes’ teaching, discussed above, of roll angle information, this limitation is taught in its entirety. One of ordinary skill in the art would find it obvious to modify Jo’s equations to incorporate Dedes’ roll angle information.
xi_t = xi_t-∆t + vi_t * cos yawi_t * ∆t. See at least pg. 254, Section III.A.1 and equation (10), wherein Vxy represents vehicle speed.
yi_t = yi_t-∆t + vi_t * sin yawi_t * ∆t. See at least pg. 254, Section III.A.1 and equation (10), wherein Vxy represents vehicle speed.
and zi_t = zi_t-∆t. See at least pg. 254, Section III.A.1 and equation (11), wherein Vxy represents vehicle speed. If the pitch angle is 0 degrees, i.e. the road is flat, then Jo’s equation is equivalent to the claimed equation.
wherein zi_t, yawi_t, and pitchi_t respectively represent coordinate information in the preset z-coordinate axis direction, yaw angle information, and pitch angle information, zi_t-∆t, yawi_t-∆t, and pitchi_t-∆t respectively represent coordinate information in the preset z-coordinate axis direction, yaw angle information, pitch angle information, and roll angle information. See at least pg. 254, Section III.A.1, wherein Z represents height (z-coordinate axis direction) and θ represents the road slope, which is equivalent to pitch. Additionally, see at least pg. 251, Section II.A, wherein ψ represents vehicle heading, which is equivalent to yaw.
yawratei_t represents yaw angular velocity information that is of the surrounding vehicle numbered i and that is at the moment t. See at least pg. 251, Section II.A, wherein wXY represents yaw rate.
∆t is a preset time interval. See at least pg. 255, wherein k and k-1 represent different time update steps.
and vi_t represents vehicle speed information that is of the surrounding vehicle numbered i and that is at the moment t. See at least pg. 254, Section III.A.1 and equation (10), wherein Vxy represents vehicle speed.
One having ordinary skill in the art, before the effective filing date of the claimed invention, would have found it obvious to further modify Sorstedt with Jo’s first position reckoning algorithm incorporating the roll angle information of Dedes. It would have been obvious to modify because doing so enables increased position estimation accuracy and reliability, as recognized by Jo (see at least pg. 251, Section I).
Claims 6 and 16 are rejected under 35 U.S.C. 103 as being unpatentable over Sorstedt, Watanabe, Uenoyama, and Hamada.
Regarding Claim 6, Sorstedt, Watanabe, and Uenoyama in combination teach all of the limitations of Claim 1 as discussed above, and Sorstedt additionally teaches wherein determining the second position reckoning result comprises: obtaining the information about the horizontal distance between the surrounding vehicle and the to-be-positioned vehicle, and the information about the vertical distance between the surrounding vehicle and the to-be-positioned vehicle. See at least [0057]-[0060] and figure 3, wherein the position information of the surrounding vehicle comprises a relative position of the surrounding vehicle to the ego vehicle in the x and y directions, or horizontal and vertical directions. Relative position to the ego vehicle is equivalent to distance to the ego vehicle.
and obtaining the second position reckoning result with reference to the first position reckoning result by using a second position reckoning algorithm. See at least [0067]-[0068], wherein the second position of the surrounding vehicle (first position reckoning result) is used to determine a second position of the ego vehicle (second position reckoning result).
Sorstedt remains silent on the information about the angle difference between the surrounding vehicle and the to-be-positioned vehicle.
Hamada teaches the information about the angle difference between the surrounding vehicle and the to-be-positioned vehicle. See at least [0084] and figures 9-10, wherein the relative angle between the surrounding vehicle 201 and the ego vehicle 200 is determined.
One having ordinary skill in the art, before the effective filing date of the claimed invention, would have found it obvious to further modify Sorstedt with Hamada’s technique of obtaining information about an angle difference between the surrounding vehicle and the to-be-positioned vehicle. It would have been obvious to modify because doing so enables highly accurate position estimation based on surrounding vehicles of the subject vehicle, as recognized by Hamada (see at least [0011]).
Regarding Claim 16, Sorstedt, Watanabe, and Uenoyama in combination teach all of the limitations of Claim 11 as discussed above, and Sorstedt additionally teaches wherein the processor is configured to determine the second position reckoning result by: obtaining the information about the horizontal distance between the surrounding vehicle and the to-be-positioned vehicle, and the information about the vertical distance between the surrounding vehicle and the to-be-positioned vehicle. See at least [0057]-[0060] and figure 3, wherein the position information of the surrounding vehicle comprises a relative position of the surrounding vehicle to the ego vehicle in the x and y directions, or horizontal and vertical directions. Relative position to the ego vehicle is equivalent to distance to the ego vehicle.
and obtaining the second position reckoning result with reference to the first position reckoning result by using a second position reckoning algorithm. See at least [0067]-[0068], wherein the second position of the surrounding vehicle (first position reckoning result) is used to determine a second position of the ego vehicle (second position reckoning result).
Sorstedt remains silent on the information about the angle difference between the surrounding vehicle and the to-be-positioned vehicle.
Hamada teaches the information about the angle difference between the surrounding vehicle and the to-be-positioned vehicle. See at least [0084] and figures 9-10, wherein the relative angle between the surrounding vehicle 201 and the ego vehicle 200 is determined.
One having ordinary skill in the art, before the effective filing date of the claimed invention, would have found it obvious to further modify Sorstedt with Hamada’s technique of obtaining information about an angle difference between the surrounding vehicle and the to-be-positioned vehicle. It would have been obvious to modify because doing so enables highly accurate position estimation based on surrounding vehicles of the subject vehicle, as recognized by Hamada (see at least [0011]).
Claims 7, 17, and 23 are rejected under 35 U.S.C. 103 as being unpatentable over Sorstedt, Watanabe, Uenoyama, Dedes, Jo, and Hamada in combination as applied to claims above, and further in view of US 20130116921 A1, with an earliest priority date of 11/03/2011, hereinafter “Kasargod”.
Regarding Claim 7, Sorstedt, Watanabe, Uenoyama, and Hamada in combination teach all of the limitations of Claim 6 as discussed above, and Sorstedt additionally teaches wherein the second position reckoning result comprises second position reckoning coordinates (xt, yt), wherein xt and yt respectively represent coordinate information in a preset x-coordinate axis direction and coordinate information in a preset y-coordinate axis direction that are of a surrounding vehicle numbered i and that are at an initial moment t , xi_t and yi_t respectively represent coordinate information in the preset x-coordinate axis direction and coordinate information in the preset y-coordinate axis direction that are of the to-be-positioned vehicle at the initial moment t, See at least [0060]-[0062], wherein the vector x includes (XN,YN) of each surrounding vehicle N at a moment T, and (ξx, ξy) of the ego vehicle at moment T.
lxi_t and lyi_t respectively represent information about a horizontal distance and information about a vertical distance between the surrounding vehicle numbered i and the to-be-positioned vehicle at the initial moment t, See at least [0060]-[0062], wherein (xNm, yNm) represent the measured relative position, or distance, in the horizontal x direction and vertical y direction of vehicle N at moment T.
Sorstedt remains silent on first initial position coordinates (zt, yawt, pitcht, rollt), and the second position reckoning algorithm comprises: xt = xi_t - lxi_t; yt = yi_t - lyi_t; zt = zi_t; yawt = yawi_t - lyawi_t; pitcht = pitchi_t; and rollt = rolli_t, wherein zt, yawt, pitcht, and rollt respectively represent coordinate information in a preset z-coordinate axis direction, yaw angle information, pitch angle information, and roll angle information, zi_t, yawi_t, pitchi_t, and rolli_t respectively represent coordinate information in the preset z-coordinate axis direction, yaw angle information, pitch angle information, and roll angle information, and lyawi_t represents information about an angle difference between the surrounding vehicle numbered i and the to-be-positioned vehicle at the initial moment t.
Dedes teaches rollt, wherein rollt represents roll angle information, rolli_t represents roll angle information. See at least [0010], wherein orientation information includes pitch, yaw, and roll information, and orientation information is received from surrounding vehicles of the host vehicle.
One having ordinary skill in the art, before the effective filing date of the claimed invention, would have found it obvious to further modify Sorstedt with Dedes’ technique of obtaining orientation information comprising yaw, pitch, and roll information of the surrounding vehicle. It would have been obvious to modify because doing so enables vehicles to establish safety situational awareness by processing position and orientation measurements of the host vehicle and surrounding vehicles, as recognized by Dedes (see at least [0004]-[0006]).
Jo teaches first initial position coordinates (zt, yawt, pitcht, rollt). See at least pg. 254, Section III.A.1 and equations (10)-(11), wherein the first position reckoning results include Xk, Yk, Zk, ψk, and θk. θ represents the road slope, which is equivalent to pitch. Additionally, see at least pg. 251, Section II.A, wherein ψ represents vehicle heading, which is equivalent to yaw.
wherein zt, yawt, and pitcht respectively represent coordinate information in a preset z-coordinate axis direction, yaw angle information, and pitch angle information, zi_t, yawi_t, and pitchi_t respectively represent coordinate information in the preset z-coordinate axis direction, yaw angle information, and pitch angle information. See at least pg. 254, Section III.A.1, wherein Z represents height (z-coordinate axis direction) and θ represents the road slope, which is equivalent to pitch. Additionally, see at least pg. 251, Section II.A, wherein ψ represents vehicle heading, which is equivalent to yaw.
One having ordinary skill in the art, before the effective filing date of the claimed invention, would have found it obvious to further modify Sorstedt with Jo’s first position reckoning algorithm incorporating the roll angle information of Dedes. It would have been obvious to modify because doing so enables increased position estimation accuracy and reliability, as recognized by Jo (see at least pg. 251, Section I).
Hamada teaches and lyawi_t represents information about an angle difference between the surrounding vehicle numbered i and the to-be-positioned vehicle at the initial moment t. See at least [0084] and figures 9-10, wherein the relative angle θ between the surrounding vehicle 201 and the ego vehicle 200 is determined.
One having ordinary skill in the art, before the effective filing date of the claimed invention, would have found it obvious to further modify Sorstedt with Hamada’s technique of obtaining information about an angle difference between the surrounding vehicle and the to-be-positioned vehicle. It would have been obvious to modify because doing so enables highly accurate position estimation based on surrounding vehicles of the subject vehicle, as recognized by Hamada (see at least [0011]).
Kasargod teaches and the second position reckoning algorithm comprises: xt = xi_t - lxi_t; yt = yi_t - lyi_t; zt = zi_t,. See at least [0025]-[0026], wherein the initial position reckoning algorithm includes x, y, and z position coordinates in combination with user displacement in the x, y, and z direction. If the z displacement is zero, then Kasargod’s equation is equivalent to the claimed equation.
Kasargod is silent as to the specifics of yawt = yawi_t - lyawi_t; pitcht = pitchi_t; and rollt = rolli_t. Nevertheless, applying any mathematical formulae, including that of the claimed invention, would have been an obvious design choice for one of ordinary skill in the art because it facilitates known mathematical means for deriving a surrounding vehicle’s position based on the relative position of the surrounding vehicle and the ego vehicle. Since the invention failed to provide novel or unexpected results from the usage of said claimed formula, use of any mathematical means, including that of the claimed invention, would be an obvious matter of design choice within the skill of the art.
One of ordinary skill in the art, before the effective filing date of the claimed invention, would have found it obvious to further modify Sorstedt with Kasargod’s initial position reckoning algorithm. It would have been obvious to modify because doing so enables accurate positioning of vehicles in areas where GNSS signals are hindered, as recognized by Kasargod (see at least [0002]-[0007]).
Regarding Claim 17, Sorstedt, Watanabe, Uenoyama, and Hamada in combination teach all of the limitations of Claim 16 as discussed above, and Sorstedt additionally teaches wherein the second position reckoning result comprises second position reckoning coordinates (xt, yt), wherein xt and yt respectively represent coordinate information in a preset x-coordinate axis direction and coordinate information in a preset y-coordinate axis direction that are of a surrounding vehicle numbered i and that are at an initial moment t , xi_t and yi_t respectively represent coordinate information in the preset x-coordinate axis direction and coordinate information in the preset y-coordinate axis direction that are of the to-be-positioned vehicle at the initial moment t, See at least [0060]-[0062], wherein the vector x includes (XN,YN) of each surrounding vehicle N at a moment T, and (ξx, ξy) of the ego vehicle at moment T.
lxi_t and lyi_t respectively represent information about a horizontal distance and information about a vertical distance between the surrounding vehicle numbered i and the to-be-positioned vehicle at the initial moment t, See at least [0060]-[0062], wherein (xNm, yNm) represent the measured relative position, or distance, in the horizontal x direction and vertical y direction of vehicle N at moment T.
Sorstedt remains silent on first initial position coordinates (zt, yawt, pitcht, rollt), and the second position reckoning algorithm comprises: xt = xi_t - lxi_t; yt = yi_t - lyi_t; zt = zi_t; yawt = yawi_t - lyawi_t; pitcht = pitchi_t; and rollt = rolli_t, wherein zt, yawt, pitcht, and rollt respectively represent coordinate information in a preset z-coordinate axis direction, yaw angle information, pitch angle information, and roll angle information, zi_t, yawi_t, pitchi_t, and rolli_t respectively represent coordinate information in the preset z-coordinate axis direction, yaw angle information, pitch angle information, and roll angle information, and lyawi_t represents information about an angle difference between the surrounding vehicle numbered i and the to-be-positioned vehicle at the initial moment t.
Dedes teaches rollt, wherein rollt represents roll angle information, rolli_t represents roll angle information. See at least [0010], wherein orientation information includes pitch, yaw, and roll information, and orientation information is received from surrounding vehicles of the host vehicle.
One having ordinary skill in the art, before the effective filing date of the claimed invention, would have found it obvious to further modify Sorstedt with Dedes’ technique of obtaining orientation information comprising yaw, pitch, and roll information of the surrounding vehicle. It would have been obvious to modify because doing so enables vehicles to establish safety situational awareness by processing position and orientation measurements of the host vehicle and surrounding vehicles, as recognized by Dedes (see at least [0004]-[0006]).
Jo teaches first initial position coordinates (zt, yawt, pitcht, rollt). See at least pg. 254, Section III.A.1 and equations (10)-(11), wherein the first position reckoning results include Xk, Yk, Zk, ψk, and θk. θ represents the road slope, which is equivalent to pitch. Additionally, see at least pg. 251, Section II.A, wherein ψ represents vehicle heading, which is equivalent to yaw.
wherein zt, yawt, and pitcht respectively represent coordinate information in a preset z-coordinate axis direction, yaw angle information, and pitch angle information, zi_t, yawi_t, and pitchi_t respectively represent coordinate information in the preset z-coordinate axis direction, yaw angle information, and pitch angle information. See at least pg. 254, Section III.A.1, wherein Z represents height (z-coordinate axis direction) and θ represents the road slope, which is equivalent to pitch. Additionally, see at least pg. 251, Section II.A, wherein ψ represents vehicle heading, which is equivalent to yaw.
One having ordinary skill in the art, before the effective filing date of the claimed invention, would have found it obvious to further modify Sorstedt with Jo’s first position reckoning algorithm incorporating the roll angle information of Dedes. It would have been obvious to modify because doing so enables increased position estimation accuracy and reliability, as recognized by Jo (see at least pg. 251, Section I).
Hamada teaches and lyawi_t represents information about an angle difference between the surrounding vehicle numbered i and the to-be-positioned vehicle at the initial moment t. See at least [0084] and figures 9-10, wherein the relative angle θ between the surrounding vehicle 201 and the ego vehicle 200 is determined.
One having ordinary skill in the art, before the effective filing date of the claimed invention, would have found it obvious to further modify Sorstedt with Hamada’s technique of obtaining information about an angle difference between the surrounding vehicle and the to-be-positioned vehicle. It would have been obvious to modify because doing so enables highly accurate position estimation based on surrounding vehicles of the subject vehicle, as recognized by Hamada (see at least [0011]).
Kasargod teaches and the second position reckoning algorithm comprises: xt = xi_t - lxi_t; yt = yi_t - lyi_t; zt = zi_t,. See at least [0025]-[0026], wherein the initial position reckoning algorithm includes x, y, and z position coordinates in combination with user displacement in the x, y, and z direction. If the z displacement is zero, then Kasargod’s equation is equivalent to the claimed equation.
Kasargod is silent as to the specifics of yawt = yawi_t - lyawi_t; pitcht = pitchi_t; and rollt = rolli_t. Nevertheless, applying any mathematical formulae, including that of the claimed invention, would have been an obvious design choice for one of ordinary skill in the art because it facilitates known mathematical means for deriving a surrounding vehicle’s position based on the relative position of the surrounding vehicle and the ego vehicle. Since the invention failed to provide novel or unexpected results from the usage of said claimed formula, use of any mathematical means, including that of the claimed invention, would be an obvious matter of design choice within the skill of the art.
One of ordinary skill in the art, before the effective filing date of the claimed invention, would have found it obvious to further modify Sorstedt with Kasargod’s initial position reckoning algorithm. It would have been obvious to modify because doing so enables accurate positioning of vehicles in areas where GNSS signals are hindered, as recognized by Kasargod (see at least [0002]-[0007]).
Regarding claim 23, Sorstedt, Watanabe, and Uenoyama in combination teach all of the limitations of claim 1 as discussed above, and Sorstedt additionally teaches wherein the initial position information of the surrounding vehicle comprises first initial position coordinates (xi_t0, yi_t0), the initial position information of the to-be-positioned vehicle comprises second initial position coordinates (xt0, yt0), wherein xi_t0 and yi_t0 respectively represent coordinate information in a preset x-coordinate axis direction and coordinate information in a preset y-coordinate axis direction that are of a surrounding vehicle numbered i and that are at an initial moment t0 , xt0 and yt0 respectively represent coordinate information in the preset x-coordinate axis direction and coordinate information in the preset y-coordinate axis direction that are of the to-be-positioned vehicle at the initial moment t0, See at least [0060]-[0062], wherein the vector x includes (XN,YN) of each surrounding vehicle N at a moment T, and (ξx, ξy) of the ego vehicle at moment T.
lxi_t0 and lyi_t0 respectively represent information about a horizontal distance and information about a vertical distance between the surrounding vehicle numbered i and the to-be-positioned vehicle at the initial moment t0, See at least [0060]-[0062], wherein (xNm, yNm) represent the measured relative position, or distance, in the horizontal x direction and vertical y direction of vehicle N at moment T.
Sorstedt remains silent on first initial position coordinates (zi_t0, yawi_t0, pitchi_t0, rolli_t0), second initial position coordinates (zt0, yawt0, pitcht0, rollt0), and the initial position reckoning algorithm comprises: xi_t0 = xt0 + lxi_t0; yi_t0 = yt0+lyi_t0; zi_t0 = zt0; yawi_t0 = yawt0+lyawi_t0; pitchi_t0 = pitcht0; and rolli_t0 = rollt0, wherein zi_t0, yawi_t0, pitchi_t0, and rolli_t0 respectively represent coordinate information in a preset z-coordinate axis direction, yaw angle information, pitch angle information, and roll angle information that are of a surrounding vehicle numbered i and that are at an initial moment t0, zt0, yawt0, pitcht0, and rollt0 respectively represent coordinate information in the preset z-coordinate axis direction, yaw angle information, pitch angle information, and roll angle information that are of the to-be-positioned vehicle at the initial moment t0, and lyawi_t0 represents information about an angle difference between the surrounding vehicle numbered i and the to-be-positioned vehicle at the initial moment t0.
Dedes teaches rollt0, wherein rolli_t0 represents roll angle information, rollt0 represents roll angle information. See at least [0010], wherein orientation information includes pitch, yaw, and roll information, and orientation information is received from surrounding vehicles of the host vehicle.
One having ordinary skill in the art, before the effective filing date of the claimed invention, would have found it obvious to further modify Sorstedt with Dedes’ technique of obtaining orientation information comprising yaw, pitch, and roll information of the surrounding vehicle. It would have been obvious to modify because doing so enables vehicles to establish safety situational awareness by processing position and orientation measurements of the host vehicle and surrounding vehicles, as recognized by Dedes (see at least [0004]-[0006]).
Jo teaches first initial position coordinates (zi_t0, yawi_t0, pitchi_t0), second initial position coordinates (zt0, yawt0, pitcht0). See at least pg. 254, Section III.A.1 and equations (10)-(11), wherein the first position reckoning results include Xk, Yk, Zk, ψk, and θk. θ represents the road slope, which is equivalent to pitch. Additionally, see at least pg. 251, Section II.A, wherein ψ represents vehicle heading, which is equivalent to yaw.
wherein zi_t0, yawi_t0, and pitchi_t0 respectively represent coordinate information in a preset z-coordinate axis direction, yaw angle information, and pitch angle information, zt0, yawt0, and pitcht0 respectively represent coordinate information in the preset z-coordinate axis direction, yaw angle information, and pitch angle information. See at least pg. 254, Section III.A.1, wherein Z represents height (z-coordinate axis direction) and θ represents the road slope, which is equivalent to pitch. Additionally, see at least pg. 251, Section II.A, wherein ψ represents vehicle heading, which is equivalent to yaw.
One having ordinary skill in the art, before the effective filing date of the claimed invention, would have found it obvious to further modify Sorstedt with Jo’s first position reckoning algorithm incorporating the roll angle information of Dedes. It would have been obvious to modify because doing so enables increased position estimation accuracy and reliability, as recognized by Jo (see at least pg. 251, Section I).
Hamada teaches and lyawi_t0 represents information about an angle difference between the surrounding vehicle numbered i and the to-be-positioned vehicle at the initial moment t0. See at least [0084] and figures 9-10, wherein the relative angle θ between the surrounding vehicle 201 and the ego vehicle 200 is determined.
One having ordinary skill in the art, before the effective filing date of the claimed invention, would have found it obvious to further modify Sorstedt with Hamada’s technique of obtaining information about an angle difference between the surrounding vehicle and the to-be-positioned vehicle. It would have been obvious to modify because doing so enables highly accurate position estimation based on surrounding vehicles of the subject vehicle, as recognized by Hamada (see at least [0011]).
Kasargod teaches and the initial position reckoning algorithm comprises: xi_t0 = xt0 + lxi_t0; yi_t0 = yt0+lyi_t0; zi_t0 = zt0. See at least [0025]-[0026], wherein the initial position reckoning algorithm includes x, y, and z position coordinates in combination with user displacement in the x, y, and z direction. If the z displacement is zero, then Kasargod’s equation is equivalent to the claimed equation.
Kasargod is silent as to the specifics of yawi_t0 = yawt0+lyawi_t0; pitchi_t0 = pitcht0; and rolli_t0 = rollt0. Nevertheless, applying any mathematical formulae, including that of the claimed invention, would have been an obvious design choice for one of ordinary skill in the art because it facilitates known mathematical means for deriving a surrounding vehicle’s position based on the relative position of the surrounding vehicle and the ego vehicle. Since the invention failed to provide novel or unexpected results from the usage of said claimed formula, use of any mathematical means, including that of the claimed invention, would be an obvious matter of design choice within the skill of the art.
One of ordinary skill in the art, before the effective filing date of the claimed invention, would have found it obvious to further modify Sorstedt with Kasargod’s initial position reckoning algorithm. It would have been obvious to modify because doing so enables accurate positioning of vehicles in areas where GNSS signals are hindered, as recognized by Kasargod (see at least [0002]-[0007]).
Claims 9 and 19 rejected under 35 U.S.C. 103 as being unpatentable over Sorstedt, Watanabe, and Uenoyama as applied to claims above, and further in view of US 20160272196 A1, filed 03/20/2015, hereinafter “Hocking”.
Regarding Claim 9, Sorstedt, Watanabe, and Uenoyama in combination teach all of the limitations of Claim 1 as discussed above, and Sorstedt additionally teaches wherein a quantity N of surrounding vehicles is greater than 1, N vehicles of the surrounding vehicles correspond to N first position reckoning results. See at least [0060]-[0062] and figure 3, wherein N vehicles surround the ego vehicle, and N first position reckoning results are calculated for the N vehicles.
and using the positioning result value as a final second position reckoning result of the to-be-positioned vehicle. See at least [0053] and [0067]-[0068], wherein the N positioning results undergo a weighting process to result in a final position of the ego vehicle.
Sorstedt remains silent on and the step of determining a second position reckoning result of the to-be-positioned vehicle comprises: respectively determining, based on the N first position reckoning results, N second position reckoning results corresponding to the to-be-positioned vehicle, and calculating a positioning result average value of the N second position reckoning results.
Hocking teaches respectively determining, based on the N first position reckoning results, N second position reckoning results corresponding to the to-be-positioned vehicle, and calculating a positioning result average value of the N second position reckoning results. See at least [0066]-[0067], wherein multiple estimates for the position of the ego vehicle are determined, and the final location of the ego vehicle is determined as the average of the determined estimates.
One having ordinary skill in the art, before the effective filing date of the claimed invention, would have found it obvious to further modify Sorstedt with Hocking’s technique of determining multiple position results and calculating a position result average value. It would have been obvious to modify because doing so enables improved vehicle location accuracy in areas with poor signal conditions for GPS, as recognized by Hocking (see at least [0001]).
Regarding Claim 19, Sorstedt, Watanabe, and Uenoyama in combination teach all of the limitations of Claim 11 as discussed above, and Sorstedt additionally teaches wherein a quantity N of surrounding vehicles is greater than 1, N vehicles of the surrounding vehicles correspond to N first position reckoning results. See at least [0060]-[0062] and figure 3, wherein N vehicles surround the ego vehicle, and N first position reckoning results are calculated for the N vehicles.
and using the positioning result value as a final second position reckoning result of the to-be-positioned vehicle. See at least [0053] and [0067]-[0068], wherein the N positioning results undergo a weighting process to result in a final position of the ego vehicle.
Sorstedt remains silent on and the processor is configured to determine the second position reckoning result by: respectively determining, based on the N first position reckoning results, N second position reckoning results corresponding to the to-be-positioned vehicle, and calculating a positioning result average value of the N second position reckoning results.
Hocking teaches respectively determining, based on the N first position reckoning results, N second position reckoning results corresponding to the to-be-positioned vehicle, and calculating a positioning result average value of the N second position reckoning results. See at least [0066]-[0067], wherein multiple estimates for the position of the ego vehicle are determined, and the final location of the ego vehicle is determined as the average of the determined estimates.
One having ordinary skill in the art, before the effective filing date of the claimed invention, would have found it obvious to further modify Sorstedt with Hocking’s technique of determining multiple position results and calculating a position result average value. It would have been obvious to modify because doing so enables improved vehicle location accuracy in areas with poor signal conditions for GPS, as recognized by Hocking (see at least [0001]).
Claims 10 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Sorstedt, Watanabe, Uenoyama, and Jo.
Regarding Claim 10, Sorstedt, Watanabe, and Uenoyama in combination teach all of the limitations of Claim 1 as discussed above, and Sorstedt additionally teaches obtaining a GPS positioning result and an inertial measurement unit (IMU) reckoning result. See at least [0046]-[0048], wherein the initial position of the ego vehicle is obtained using a GNSS system and the vehicle’s IMU
and determining a final positioning result of the to-be-positioned vehicle based on the GPS positioning result and the IMU reckoning result and with reference to the second position reckoning result by using a filter. See at least [0057]-[0061] and [0068]-[0069], wherein the method 200 represents a positioning filter which utilizes the obtained initial pose of the vehicle and the determined second position reckoning result to update the state vector with the ego vehicle’s final position.
Sorstedt remains silent on an extended Kalman filter (EKF).
Jo teaches an extended Kalman filter(EKF). See at least pgs. 254-255, Section III.B “Road Slope Aided Position Estimation”, wherein an extended Kalman filter is used to estimate the final ego-vehicle position.
One having ordinary skill in the art, before the effective filing date of the claimed invention, would have found it obvious to further modify Sorstedt with Jo’s extended Kalman filter for position estimation. It would have been obvious to modify because doing so enables increased position estimation accuracy and reliability, as recognized by Jo (see at least pg. 251, Section I).
Regarding Claim 20, Sorstedt, Watanabe, and Uenoyama in combination teach all of the limitations of Claim 11 as discussed above, and Sorstedt additionally teaches wherein the processor is further configured to: obtain a GPS positioning result and an inertial measurement unit (IMU) reckoning result. See at least [0046]-[0048], wherein the initial position of the ego vehicle is obtained using a GNSS system and the vehicle’s IMU
and determine a final positioning result of the to-be-positioned vehicle based on the GPS positioning result and the IMU reckoning result and with reference to the second position reckoning result by using a filter. See at least [0057]-[0061] and [0068]-[0069], wherein the method 200 represents a positioning filter which utilizes the obtained initial pose of the vehicle and the determined second position reckoning result to update the state vector with the ego vehicle’s final position.
Sorstedt remains silent on an extended Kalman filter (EKF).
Jo teaches an extended Kalman filter (EKF). See at least pgs. 254-255, Section III.B “Road Slope Aided Position Estimation”, wherein an extended Kalman filter is used to estimate the final ego-vehicle position.
One having ordinary skill in the art, before the effective filing date of the claimed invention, would have found it obvious to further modify Sorstedt with Jo’s extended Kalman filter for position estimation. It would have been obvious to modify because doing so enables increased position estimation accuracy and reliability, as recognized by Jo (see at least pg. 251, Section I).
Claim 21 is rejected under 35 U.S.C. 103 as being unpatentable over Sorstedt, Watanabe, Uenoyama, Jo, and Hamada.
Regarding Claim 21 (previously Claim 20), Sorstedt, Watanabe, Uenoyama, and Jo in combination teach all of the limitations of Claim 10 as discussed above, and Sorstedt additionally teaches wherein after vehicle positioning information is initialized, the filter starts to perform iteration of positioning information prediction and positioning information observation, and further obtains the final positioning result of the to-be-positioned vehicle. See at least [0020] and [0066]-[0069], wherein the methods 100 and 120 repeatedly performs the steps of observing position information of surrounding vehicles, predicting position information of surrounding vehicles, and updating the position of the ego vehicle.
and wherein the positioning information observation is for performing correction on a result of the positioning information prediction, so as to provide an accurate positioning result. See at least [0066]-[0067] and equation 11, wherein the step 107 of observing position information of the surrounding vehicles is used to update, or correct, the predicted positions of the surrounding vehicles in step 113. This is performed using the process e(t). Additionally, see at least [0059] and equations 4-5, wherein e(t) represents a gaussian process which models errors in the sensor observations in the measurement model.
Sorstedt remains silent on an extended Kalman filter (EKF) and performing a weighted correction.
Jo teaches an extended Kalman filter (EKF). See at least pgs. 254-255, Section III.B “Road Slope Aided Position Estimation”, wherein an extended Kalman filter is used to estimate the final ego-vehicle position.
One having ordinary skill in the art, before the effective filing date of the claimed invention, would have found it obvious to further modify Sorstedt with Jo’s extended Kalman filter for position estimation. It would have been obvious to modify because doing so enables increased position estimation accuracy and reliability, as recognized by Jo (see at least pg. 251, Section I).
Hamada teaches performing a weighted correction. See at least [0097] and figure 13, wherein the position information obtained from observations A, A’, and A” is weighted when correcting the estimated position of the subject vehicle.
One having ordinary skill in the art, before the effective filing date of the claimed invention, would have found it obvious to further modify Sorstedt with Hamada’s technique of performing a weighted correction. It would have been obvious to modify because doing so enables highly accurate position estimation based on surrounding vehicles of the subject vehicle, as recognized by Hamada (see at least [0011]).
Conclusion
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/S.M.J./ Examiner, Art Unit 3667
/FARIS S ALMATRAHI/ Supervisory Patent Examiner, Art Unit 3667