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 .
Response to Arguments
Claim Rejections - 35 USC § 103:
Applicant’s arguments with respect to independent claims 1 and 17 have been considered but are moot. Amendment to independent claims 1 and 17 necessitates new grounds of rejection.
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 11/03/3035 has been entered.
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 1-2 and 17-18 are rejected under 35 U.S.C. 103 as being unpatentable over Ben Shalom et al. (US 20160318490 A1; hereinafter Ben Shalom) in view of (Hempel et al. US 20230373488 A1; hereinafter Hempel) in further view of Nishimura et al. (US 20220398923 A1; hereinafter Nishimura).
Regarding claim 1, Ben Shalom teaches a data processing apparatus to be applied to a vehicle (see at least, [0008] a traffic light detection system for a vehicle), the data processing apparatus comprising: one or more processors; and one or more memories storing instructions for causing the one or more processors (see at least, [0051] Each memory 140, 150 may include software instructions that when executed by a processor (e.g., applications processor 180 and/or image processor 190), may control operation of various aspects of system ) to: receive, from an onboard stereo camera of the vehicle, stereo images (see at least, Fig 2A, [0106] image capture devices 122 and 124 may provide images for stereo analysis by system); generate a distance image based on the received stereo images (see at least, [0087] each image capture device 122, 124…such that each device acquires images of objects at a desired distance range relative to vehicle); detect a traffic light based on the generated distance image (see at least, [0152] traffic light detection module….performs image analysis of one or more
images acquired by at least one of image capture devices 122, 124….analyze the one or more images
to detect a shape of the traffic light, a color of the traffic light); calculate a first distance which is a distance from the vehicle to the traffic light based on the generated distance image (see at least, [0256] The distance of the vehicle to the traffic light fixture may be determined based on analysis of at least two of the plurality of images including the traffic light fixture); determine vehicle position by using a locator that calculates the vehicle position, the locator including at least one of an acceleration sensor, a speed sensor, a gyroscope sensor and a Global Positioning Signal (GPS) receiver (see at least, [0061] processing unit 110 may be included on vehicle 200…may also be equipped with a position sensor 130, such as a GPS receiver); acquire, from a map database, map data based on the determined vehicle position data (see at least, [0061] processing unit 110 may be included on vehicle 200…may also include a map database 160); detect a digitized traffic light within an area in the map data (see at least, [0197] detections and determinations may also be made at least in part on map data, system 100
may recognize a traffic light associated with the lane), the digitized traffic light corresponding to the traffic light detected based on the stereo images received from the onboard stereo camera.
Ben Shalom does not explicitly teach the area having a predetermined distance from a digitized position of the traffic light in the map data; in response to detecting the digitized traffic light within the area in the map data, calculate a stop line corresponding to the traffic light by using a second distance, the second distance being a distance from the digitized traffic light to a digitized stop line corresponding to the digitized traffic light in the map data; and execute a traveling control of the vehicle based on the estimated position data of the stop line. However, Hempel teaches these limitation.
Hempel teaches the area having a predetermined distance from a digitized position of the traffic light in the map data (see at least, [0209] the map data relating to the road or street network used by the vehicle 100 may comprise distance data relating to the distance between the position of the stop
line of a signaling unit 200, 210 and the position of the signaling unit 200, 210…may indicate, for example, that the stop line of the particular signaling unit 200, 210 is arranged x meters in front of the signaling unit 200, 210); in response to detecting the digitized traffic light within the area in the map data, calculate a stop line corresponding to the traffic light by using a second distance, the second distance being a distance from the digitized traffic light to a digitized stop line corresponding to the digitized traffic light in the map data (see at least, [0209] The distance data may be provided…in the map data as a respective attribute for the individual signaling units 200, 210 recorded in the
map data…may indicate, for example, that the stop line of the particular signaling unit 200, 210 is arranged x meters in front of the signaling unit 200, 210…the maximum, the greatest possible and/or the average distance between the stop line and the signaling unit 200, 210 may possibly be indicated); execute a traveling control of the vehicle based on the estimated position data of the stop line (see at least, [0021] the vehicle can be guided in an automated manner up to or in front of the stop line of the signaling unit. During the automated deceleration process, the vehicle guidance system can control one or more wheel brakes…in an automated manner in order to brake the vehicle).
Ben Shalom further does not explicitly teach wherein the one or more processors are configured to decrease the predetermined distance as the first distance decreases. However, Nishimura teaches this limitation.
Nishimura teaches wherein the one or more processors are configured to decrease the predetermined distance as the first distance decreases (see at least, (see at least, Fig 3, [0011] (traffic signal recognition device according to the present embodiment, when setting the number threshold based on the first distance, the second threshold may be set as the number threshold in a case where the first distance is smaller than the distance threshold, and a deceleration acceleration when the vehicle
stops before the stop line is equal to or less than a predetermined deceleration acceleration).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have further modified Ben Shalom to include decrease the predetermined distance threshold as the first distance from the vehicle to the traffic light decreases as taught by Nishimura in order to recognize the traffic signal while suppressing an increase in the free running distance of the vehicle (Nishimura, [0006]).
Regarding claim 2, the combination of Ben Shalom, Hempel and Nishimura teaches the data processing apparatus according to claim 1. Hempel further teaches wherein the second distance having been calculated in past (see at least, [0040] The map data may also comprise the distance data for a signaling unit as a map attribute of the signaling unit…may have been determined, in particular learnt, in advance (for example by using collected environmental data from a multiplicity of different vehicles during journeys at the respective signaling unit)).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have further modified Ben Shalom to include the second distance having been calculated in past as taught by Hempel in order to effect automated deceleration of the vehicle at the first signaling unit on the basis of the position data and the distance data (Hempel, [0041]).
Regarding claim 17, Ben Shalom teaches a data processing apparatus to be applied to a vehicle (see at least, [0008] a traffic light detection system for a vehicle), the data processing apparatus comprising: circuitry configured to (see at least, [0051] Each memory 140, 150 may include software instructions that when executed by a processor (e.g., applications processor 180 and/or image processor 190), may control operation of various aspects of system ) to: receive, from an onboard stereo camera of the vehicle, stereo images (see at least, Fig 2A, [0106] image capture devices 122 and 124 may provide images for stereo analysis by system); generate a distance image based on the received stereo images (see at least, [0087] each image capture device 122, 124…such that each device acquires images of objects at a desired distance range relative to vehicle); detect a traffic light based on the generated distance image (see at least, [0152] traffic light detection module….performs image analysis of one or more images acquired by at least one of image capture devices 122, 124….analyze the one or more images to detect a shape of the traffic light, a color of the traffic light); calculate a first distance which is a distance from the vehicle to the traffic light based on the generated distance image (see at least, [0256] The distance of the vehicle to the traffic light fixture may be determined based on analysis of at least two of the plurality of images including the traffic light fixture); determine vehicle position by using a locator that calculates the vehicle position, the locator including at least one of an acceleration sensor, a speed sensor, a gyroscope sensor and a Global Positioning Signal (GPS) receiver (see at least, [0061] processing unit 110 may be included on vehicle 200…may also be equipped with a position sensor 130, such as a GPS receiver); acquire, from a map database, map data based on the determined vehicle position data (see at least, [0061] processing unit 110 may be included on vehicle 200…may also include a map database 160); detect a digitized traffic light within an area in the map data (see at least, [0197] detections and determinations may also be made at least in part on map data, system 100 may recognize a traffic light associated with the lane), the digitized traffic light corresponding to the traffic light detected based on the stereo images received from the onboard stereo camera.
Ben Shalom does not explicitly teach the area having a predetermined distance from a digitized position of the traffic light in the map data; in response to detecting the digitized traffic light within the area in the map data, calculate a stop line corresponding to the traffic light by using a second distance, the second distance being a distance from the digitized traffic light to a digitized stop line corresponding to the digitized traffic light in the map data; and execute a traveling control of the vehicle based on the estimated position data of the stop line. However, Hempel teaches these limitation.
Hempel teaches the area having a predetermined distance from a digitized position of the traffic light in the map data (see at least, [0209] the map data relating to the road or street network used by the vehicle 100 may comprise distance data relating to the distance between the position of the stop
line of a signaling unit 200, 210 and the position of the signaling unit 200, 210…may indicate, for example, that the stop line of the particular signaling unit 200, 210 is arranged x meters in front of the signaling unit 200, 210); in response to detecting the digitized traffic light within the area in the map data, calculate a stop line corresponding to the traffic light by using a second distance, the second distance being a distance from the digitized traffic light to a digitized stop line corresponding to the digitized traffic light in the map data (see at least, [0209] The distance data may be provided…in the map data as a respective attribute for the individual signaling units 200, 210 recorded in the
map data…may indicate, for example, that the stop line of the particular signaling unit 200, 210 is arranged x meters in front of the signaling unit 200, 210…the maximum, the greatest possible and/or the average distance between the stop line and the signaling unit 200, 210 may possibly be indicated); execute a traveling control of the vehicle based on the estimated position data of the stop line (see at least, [0021] the vehicle can be guided in an automated manner up to or in front of the stop line of the signaling unit. During the automated deceleration process, the vehicle guidance system can control one or more wheel brakes…in an automated manner in order to brake the vehicle).
Ben Shalom further does not explicitly teach wherein the one or more processors are configured to decrease the predetermined distance as the first distance decreases. However, Nishimura teaches this limitation.
Nishimura teaches wherein the one or more processors are configured to decrease the predetermined distance as the first distance decreases (see at least, (see at least, Fig 3, [0011] (traffic signal recognition device according to the present embodiment, when setting the number threshold based on the first distance, the second threshold may be set as the number threshold in a case where the first distance is smaller than the distance threshold, and a deceleration acceleration when the vehicle
stops before the stop line is equal to or less than a predetermined deceleration acceleration).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have further modified Ben Shalom to include decrease the predetermined distance threshold as the first distance from the vehicle to the traffic light decreases as taught by Nishimura in order to recognize the traffic signal while suppressing an increase in the free running distance of the vehicle (Nishimura, [0006]).
Regarding claim 18, the combination of Ben Shalom, Hempel and Nishimura teaches the data processing apparatus according to claim 17. Hempel further teaches wherein the second distance having been calculated in past (see at least, [0040] The map data may also comprise the distance data for a signaling unit as a map attribute of the signaling unit…may have been determined, in particular learnt, in advance (for example by using collected environmental data from a multiplicity of different vehicles during journeys at the respective signaling unit)).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have further modified Ben Shalom to include the second distance having been calculated in past as taught by Hempel in order to effect automated deceleration of the vehicle at the first signaling unit on the basis of the position data and the distance data (Hempel, [0041]).
Claims 5-6 and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Ben Shalom et al. (US 20160318490 A1; hereinafter Ben Shalom) in view of (Hempel et al. US 20230373488 A1; hereinafter Hempel) in further view of Nishimura et al. (US 20220398923 A1; hereinafter Nishimura) and Hayat et al. (US 20230280183 A1; hereinafter Hayat)
Regarding claim 5, the combination of Ben Shalom, Hempel and Nishimura teaches the data processing apparatus according to claim 1. The combination does not explicitly teach wherein the traffic light comprises a target that is relatively easy for a stereo camera to image, and the stop line comprises a target that is relatively difficult for the stereo camera to image. However, Hayat teaches this limitation.
Hayat teaches wherein the first target traffic light comprises a target that is relatively easy for a stereo camera to image (Fig 2D, [0136] The fields of view of image capture devices 122, 124, and 126 may include any desired area relative to an environment of vehicle 200…one or more of image capture devices 122, 124, and 126 may be configured to acquire image data from an environment in front of vehicle; Examiner interprets environment in front of the vehicle to include traffic lights, e.g. ([0189] processing unit…may execute stereo image analysis module…to detect candidate objects…traffic lights), and the second target stop line comprises a target that is relatively difficult for the stereo camera to image ([0129], FIG. 2A, the two image capture devices 122 and 124 are at different heights; Examiner interprets the relative difficulty for the stereo camera to image as the detection range of the cameras 122 and 124 may capture the ground surface for the stop line ).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have further modified the combination of Ben Shalom, Hempel and Nishimura to include traffic light comprises a target that is relatively easy for a stereo camera to image, and the stop line comprises a target that is relatively difficult for the stereo camera to image in order to provide sufficient accuracy for navigation over a local scale (Hayat, [0273]).
Regarding claim 6, the combination of Ben Shalom, Hempel and Nishimura teaches the data processing apparatus according to claim 2. The combination does not explicitly teach wherein the traffic light comprises a target that is relatively easy for a stereo camera to image, and the stop line comprises a target that is relatively difficult for the stereo camera to image. However, Hayat teaches this limitation.
Hayat teaches wherein the first target traffic light comprises a target that is relatively easy for a stereo camera to image (Fig 2D, [0136] The fields of view of image capture devices 122, 124, and 126 may include any desired area relative to an environment of vehicle 200…one or more of image capture devices 122, 124, and 126 may be configured to acquire image data from an environment in front of vehicle; Examiner interprets environment in front of the vehicle to include traffic lights, e.g. ([0189] processing unit…may execute stereo image analysis module…to detect candidate objects…traffic lights), and the second target stop line comprises a target that is relatively difficult for the stereo camera to image ([0129], FIG. 2A, the two image capture devices 122 and 124 are at different heights; Examiner interprets the relative difficulty for the stereo camera to image as the detection range of the cameras 122 and 124 may capture the ground surface for the stop line ).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have further modified the combination of Ben Shalom, Hempel and Nishimura to include traffic light comprises a target that is relatively easy for a stereo camera to image, and the stop line comprises a target that is relatively difficult for the stereo camera to image in order to provide sufficient accuracy for navigation over a local scale (Hayat, [0273]).
Regarding claim 19, the combination of Ben Shalom, Hempel and Nishimura teaches the data processing apparatus according to claim 17. The combination does not explicitly teach wherein the traffic light comprises a target that is relatively easy for a stereo camera to image, and the stop line comprises a target that is relatively difficult for the stereo camera to image. However, Hayat teaches this limitation.
Hayat teaches wherein the first target traffic light comprises a target that is relatively easy for a stereo camera to image (Fig 2D, [0136] The fields of view of image capture devices 122, 124, and 126 may include any desired area relative to an environment of vehicle 200…one or more of image capture devices 122, 124, and 126 may be configured to acquire image data from an environment in front of vehicle; Examiner interprets environment in front of the vehicle to include traffic lights, e.g. ([0189] processing unit…may execute stereo image analysis module…to detect candidate objects…traffic lights), and the second target stop line comprises a target that is relatively difficult for the stereo camera to image ([0129], FIG. 2A, the two image capture devices 122 and 124 are at different heights; Examiner interprets the relative difficulty for the stereo camera to image as the detection range of the cameras 122 and 124 may capture the ground surface for the stop line ).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have further modified the combination of Ben Shalom, Hempel and Nishimura to include traffic light comprises a target that is relatively easy for a stereo camera to image, and the stop line comprises a target that is relatively difficult for the stereo camera to image in order to provide sufficient accuracy for navigation over a local scale (Hayat, [0273]).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Stein et al. (US 20150210312 A1) discloses an estimator configured to estimate position data of the second target based on the first distance data detected by the detector and the second distance data calculated by the processor (e.g. [0266] processing unit...may compare the relative distance between recognized traffic light fixtures in the junction to the 3D model to determine the distance to the junction's stop line, even when the stop line is not visible from the current location of vehicle).
Any inquiry concerning this communication or earlier communications from the examiner should be directed to TOYA PETTIEGREW whose telephone number is (313)446-6636. The examiner can normally be reached 8:30pm - 5:00pm M-F.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Jelani Smith can be reached at 571-270-3969. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/TOYA PETTIEGREW/Primary Examiner, Art Unit 3662