DETAILED ACTION
The following is a Final Office Action in response to applicant’s amendments filed on April 13th 2026. Claims 1-7 and 9-10 are pending.
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 .
Response to Arguments/Amendments
Applicant’s arguments, with respect to the rejection of claim 1-7 under 35 USC 101 have been fully considered and are persuasive. The rejection has been withdrawn.
Applicant’s arguments, with respect to the rejection(s) of claim(s) 1-7 under 35 USC 102 have been fully considered and are persuasive. Therefore, the rejection has been withdrawn. However, upon further consideration, a new ground(s) of rejection is made in view of Oyama (US 2016/0259335) .
Applicant’s arguments, with respect to the rejection(s) of claim(s) 5 under 35 USC 103 have been fully considered and are persuasive. Therefore, the rejection has been withdrawn. However, upon further consideration, a new ground(s) of rejection is made in view of Oyama (US 2016/0259335) .
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.
Claim(s) 1-4 and 6-7 is/are rejected under 35 U.S.C. 103 as being unpatentable over Tanaka (US 2023/0027195) in view of Urano et al. (US 2017/0122749) in view of Oyama (US 2016/0259335).
Regarding claim 1, Tanaka teaches a map generation apparatus comprising:
an in-vehicle detector configured to detect an external situation around a subject
vehicle (Para. [0025]… The camera 11, which is an example of an image capturing unit for capturing the surroundings of the vehicle 2, includes a two-dimensional detector constructed from an array of optoelectronic transducers, such as CCD or C-MOS, having sensitivity to visible light and a focusing optical system that forms an image of a target region on the two-dimensional detector); and a microprocessor and a memory coupled to the microprocessor, wherein the microprocessor is configured to perform:
recognizing an exterior environment situation around a subject vehicle by using
a detection data of the in-vehicle detector (Para. [0033-0035]… the processor 23 inputs an image received from the camera 11 into a classifier that has been trained to detect a detection target feature, thereby detecting the feature represented in the inputted image…);
generating a map including position information indicating a position of a predetermined feature based on recognition information acquired in the recognizing (Para. [0036]… The processor 23 includes, in feature data, the latitude and longitude indicating the position of the feature represented in the feature data as information indicating the position of the feature represented in the feature data. Additionally, the processor 23 refers to the road map to identify a link that is a road section including the position of the feature represented in the feature data or a road section closest to this position); and the microprocessor is further configured to perform:
calculating a reliability of the map generated in the generating, for each piece of
position information (Para. [0052]… for each feature represented in the map and located in the collection target region including the position of the feature represented in the
feature data, the update unit 43 calculates the distance from the position where the reliability of the feature represented in the map is highest…);
storing the map and reliability information indicating the reliability as map information (Para. [0043]…the storage device 32 stores a map to be generated or updated, the reliability distributions of the positions of features represented in the map, and the identifying information of each vehicle);
Tanaka fails to teach an actuator for traveling, wherein generating a travel trajectory for the subject vehicle based on the recognized position of the subject vehicle and, and controlling the actuator so that the subject vehicle travels automatically along the target path, and
updating, when at least a part of a new map newly generated in the generating is included in the existing map stored in the memory unit as the map information, data of a corresponding section of the existing map corresponding to a generation section of the new map based on a comparison between the reliability of the new map in the generation section and data and the reliability of the existing map in the corresponding section.
However, Urano teaches an actuator for traveling (Urano, Fig. 1, actuator 6), generating a travel path for the subject vehicle based on the recognized information and the map; (Urano, Para. [0091]…the traveling plan generation unit 14 generates the traveling plan of the vehicle M based on the target route R set by the navigation system 5 and the map information of the map database 4) , and controlling the actuator so that the subject vehicle travels automatically along the target path (Urano, Para. [0101]…the traveling control unit 15 carries out the automatic driving control for the vehicle M by controlling an output of the actuator 6 ( such as the driving force, the braking force, and the steering torque) with the command control value.)
It would be obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the method for collecting feature date as taught by Tanaka with the map update determination system as taught by Urano to improve an update method for a case where the map information becomes outdated due to topographic changes (in, for example, lane width and road curvature) attributable to construction works or the like (Urano, Para. [0006]).
Further, Oyama teaches updating, when at least a part of a new map newly generated in the generating is included in the existing map stored in the memory unit as the map information, data of a corresponding section of the existing map corresponding to a generation section of the new map based on a comparison between the reliability of the new map in the generation section and data and the reliability of the existing map in the corresponding section (Oyama, Para. [0036]…the steering controller 20 calculates a basic motor current Ipsb in accordance with driver input, calculates a reliability of the frontward environment information in a predetermined manner, and calculates a reliability of the map information in a predetermined manner while updating the map information. In S102, the steering controller 20 compares the reliability of the frontward environment information with update information relating to the map information, and selects either one of the frontward environment information and the map information as information to be used during automatic driving control.
It would be obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Tanaka in view of Urano with the travel control apparatus as taught by Oyama to implement a precise and stable automatic driving continuously without appropriately varying the form of the automatic driving (Oyama, Para. [0006]).
Regarding claim 2, Tanaka in view of Urano and Oyama teach the map generation apparatus according to claim 1, wherein the microprocessor is configured to perform the calculating including setting at least one of a position coordinate of the subject vehicle in the map information (Tanaka, Para. [0037]…the processor 23 may include, in the feature data, the position and the travel direction of the vehicle 2 at the time of generation of the feature data, which are used for estimating the position of the feature, as well as the intensity of received GPS signals used for determining the position of the vehicle ), a number of samples of the recognition information (Tanaka, Para. [0032]… the processor 23 executes the process related to generation of feature data at predetermined intervals ( e.g., 0.1 to 10 seconds) during travel of the vehicle) and the position information of travel lanes recognized in the recognizing as a parameter (Tanaka, Para. [0034]…for each type of detection target feature (e.g., a lane-dividing line, a pedestrian crossing, and a stop line), the classifier calculates a confidence score indicating how likely the feature is represented in a region in the input image), and calculating an estimated value distribution of the position information of the feature as the reliability information based on the parameter (Tanaka, Para. [0050]…the update unit 43 updates the reliability distribution of the position of each feature in the collection target region, based on the position of the feature indicated by each of one or more pieces of received feature data. The update unit 43 may execute an update process described below whenever receiving feature data or two or more predetermined number of pieces of feature data.)
Regarding claim 3, Tanaka in view of Urano and Oyama teach the vehicle control apparatus according to claim 2, wherein the microprocessor is configured to perform the calculating including calculating the estimated value distribution in the generation section when the new map is generated (Tanaka, Para. [0054]… The update unit 43 then approximates the reliability of each division with a normal distribution to calculate an updated reliability distribution of the position of the feature), and calculating the estimated value distribution in the corresponding section when the existing map is updated (Tanaka, Para. [0054]); and the updating including updating the position information of the existing map by fusing the existing map in the corresponding section and the new map in the generation section, wherein the fusing prioritizes date of a map having smaller variance based on a comparison between the estimated value distribution calculated in the corresponding section of the existing map and the estimated value distribution calculated in the generation section of the new map (Tanaka, Para. [0059]… the positional reliability distribution is defined by an average position and a variance covariance matrix when the positional reliability distribution is expressed as a normal distribution. The higher the reliability at the average position or the smaller the values of the elements of the variance-covariance matrix, the smaller the extent of the reliability distribution. Additionally, the smaller the extent of the reliability distribution, the more accurately the position of the feature is determined.)
Regarding claim 4, Tanaka in view of Urano and Oyama teach the vehicle control apparatus according to claim 3, wherein the microprocessor is configured to perform the calculating including setting weights for data of the existing map and data of the new map based on at least one of the position information of the travel lanes (Tanaka, Para. [0070]… when updating the reliability distribution by maximum likelihood estimation, the update unit 43 uses weighted positions obtained by multiplying the positions of a feature indicated by individual feature data by a weighting factor for the maximum likelihood estimation), the recognition result in the recognizing (Tanaka, Para. [0034-0035]), a frequency of update of the existing map (Tanaka, Para. [0047]… the collection instruction unit 41 may set a region where a predetermined period has elapsed since the last update as a collection target region), a presence or absence of a past travel history, and a travel frequency (Tanaka, Para. [0034]).
Regarding claim 6, Tanaka in view of Urano and Oyama teach the vehicle control apparatus according to claim 1, wherein the microprocessor is configured to perform the recognizing including recognizing the exterior environment situation at a predetermined frame rate (Tanaka, Para. [0025]…the camera 11 captures a region in front of the vehicle 2 every predetermined capturing period), and generates images of this region), and the calculating including, when calculating the reliability of the new map, calculating the reliability of the new map for each piece of position information of the same feature recognized in each of a plurality of frames with close acquisition times (Tanaka, Para. [0035]… the processor 23 associates object regions representing the same feature in two images obtained at different timings with each other, using optical flow. The processor 23 can estimate the position of the feature by triangulation, based on the positions and the travel directions of the vehicle 2 at the times of acquisition of the two images, the parameters of the camera 11, and the positions of the object regions in the respective images), and when calculating the reliability of the existing map, calculating the reliability of the existing map for each piece of position information of the same feature included in the existing map which has been updated (Tanaka, Para. [0052]) .
Regarding claim 7, Tanaka in view of Urano and Oyama teaches the vehicle control apparatus according to claim 1, Urano teaches further comprising a sensor configured to detect presence or absence of an intervention in the driving operation, wherein the microprocessor is configured to perform the updating including, when at least a part of the new map is included in the existing map, determining whether there has been intervention in the driving operation in the generation section of the new map based on the detection data of the sensor, and when there has not been intervention in the driving operation, not updating the data of the corresponding section of the existing map corresponding to the generation section (Urano, Para. [0201]… the map update determination system 200 calculates the evaluation value of the traveling plan based on the number of the driver's intervention operations or the frequency of the driver's intervention operation as well as the result of the comparison between the control target value and the control result detection value. Accordingly, the map update determination system 200 may determine that the map information needs to be updated even in cases such as those illustrated in FIGS. 12A, 12B, 13A, and 13B, and thus, a more appropriate map information update determination may be performed.)
It would be obvious to one of ordinary skill in the art before the effective date of the claimed invention to modify the method for collecting feature date as taught by Tanaka with the map update determination system as taught by Urano to improve an update method for a case where the map information becomes outdated due to topographic changes (in, for example, lane width and road curvature) attributable to construction works or the like (Urano, Para. [0006]).
Claim(s) 5 is/are rejected under 35 U.S.C. 103 as being unpatentable over Tanaka (US 2023/0027195) in view of Urano et al. (US 2017/0122739 in view of Oyama (US 2016/0259335) in further view of Keidel et al. (US 2022/0101637)..
Regarding claim 5, Tanaka teaches the map generation apparatus according to claim 3, Keidel teaches further wherein the microprocessor is configured to perform the updating including, in a case where first position information of the feature in the generation section of the new map does not correspond to second position information of the feature in the corresponding section of the existing map, updating the position information of the existing map by fusing the existing map of the corresponding section and the new map of the generation section based on a map shape estimated from a polynomial approximation using the data of the new map in the generation section and the data of the existing map in the corresponding section (Keidel, Para. [0017]… first surrounding-area measurement data may be recorded by at least one camera and second surrounding-area measurement data may be provided by a map. On the basis of the surrounding-area measurement data recorded by the camera or ascertained from the map, it is possible in each case to ascertain a polynomial or a polynomial spline which respectively describes in approximation the course of a roadway in the surrounding area of the vehicle. The state function may in this case be adapted to the first surrounding-area measurement data and in addition to the second surrounding area measurement data.)
It would be obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the method for collecting feature date as taught by Tanaka in view of Urano and Oyama with the method for multi-sensor data fusion for autonomous vehicle as taught by Keidel to provide a method for estimating the course of a roadway that ensures the highly available and precise determination of the course of a roadway (Keidel, Para. [0007])
Claim(s) 9-10 is/are rejected under 35 U.S.C. 103 as being unpatentable over Tanaka (US 2023/0027195) in view of Urano et al. (US 2017/0122749) in view of Oyama (US 2016/0259335) in further view of Fujiwara et al. (US 2023/0014570).
Regarding claim 9, Tanaka in view of Urano and Oyama teach the vehicle control apparatus according to claim 1, Fujiwara teaches further wherein the microprocessor is configured to perform: the updating including fusing the existing map and the new map by weighted least squares using weights set based on the reliability (Fujiwara, Para. 52…. the corrected map route point sequence is weighted with respect to the autonomous route point sequence by an optimization technique, such as a weighted non-linear least-squares method, in accordance with the reliability of the map route point sequence based on the information accuracy of the own vehicle information, the information accuracy of the map data, and the like and then an n-th order curve connecting the integrated route point sequence, which includes the autonomous route point sequence and a part of the compensated corrected map route point sequence, is estimated to generate the integrated route curve.
It would be obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the method for collecting feature date as taught by Tanaka in view of Urano and Oyama with the route generation device as taught by Fujiwara to provide a route generation device that is more reliable and allows for appropriately controlling a vehicle (Fujiwara, Para. [0015-0016])
Regarding claim 10, Tanaka in view of Urano, Oyama and Fujiwara teach the vehicle control apparatus according to claim 9, wherein the weighted least squares minimizes a cost function representing a sum of squared errors using weights based on the reliability of the existing map and the reliability of the new map, and calculates position information of a feature in the existing map, and updates the position information of the existing map based on the calculated position information (Fujiwara, Para. [0052]).
It would be obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the method for collecting feature date as taught by Tanaka in view of Urano and Oyama with the route generation device as taught by Fujiwara to provide a route generation device that is more reliable and allows for appropriately controlling a vehicle (Fujiwara, Para. [0015-0016])
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JODI M JONES whose telephone number is (571)272-0107. The examiner can normally be reached M-F 8:30am-5:00pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Anne Antonucci can be reached at (313) 446-6519. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/JODI JONES/Examiner, Art Unit 3666
/ANNE MARIE ANTONUCCI/Supervisory Patent Examiner, Art Unit 3666
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