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 .
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1 – 4, 6, 8 - 12 and 14 are rejected under 35 U.S.C. 103 as being unpatentable over Stein et al. (Pub. No.: US 2007/0221822 A1) and Sasaki (Pub. No.: US 2007/0047809 A1) in view of Sorstedt et al. (Pub. No.: US 2017/0307397 A1).
Regarding claim 1, Stein teaches a computer-implemented method for Adaptive High Beam Control (AHBC) for a vehicle, the method comprising:
obtaining information about an existence of streetlighting for an upcoming road segment ahead of the vehicle from a digital map layer (Detects bright spots in the image, e.g., streetlights, and tracks the spots over time collecting information about the spots regarding their shape, brightness, motion, spatial alignment and possibly color. When the algorithm has accumulated enough evidence that the spot is tagged as being in one of the relevant categories and the headlights are controlled appropriately ¶ 38),
controlling an illumination of a space in front of the vehicle based on the obtained
information about the existence of streetlighting for the upcoming road segment so to avoid
casting high beam illumination towards road areas associated with streetlights (Classify Spot 313, 23 control headlight deactivate high beams, FIG. 3).
Stein is silent to the digital map layer being based on a current position of the vehicle, wherein the digital map layer is formed from probe sourced data from a fleet of vehicles. However, in a similar field of endeavor, Sasaki teaches an environment recognition device which accumulates map information (¶ 106) and determines a vehicle location via GPS information (¶ 290) and where special probe vehicles are utilized to create a road traffic database which can be collected cheaply in high volume (¶ 357) and more specifically, include streetlight information (FIG. 5).
It would have been obvious to one with ordinary skill in the art before the effective filing date of the claimed invention to modify the digital map layer taught by Stein to be based on a current position of the vehicle, wherein the digital map layer is formed from probe sourced data from a fleet of vehicles as taught by Sasaki to enhance cost savings for the data storing system (¶ 357).
Stein and Sasaki is silent to wherein the digital map layer comprises a plurality of streetlight blocks, each streetlight block comprising a start and an end along a road, and each streetlight block defining a road segment having one or more streetlights. However, Sorstedt teaches a method for generating navigation data using a vehicle comprising a set of sensors and a step of traveling along a road and detecting at least one landmark and correlating and approving an associated section of a road for navigation (See Abstract). More specifically, sections of a roadway are depicted (See Figs. 2-4) where landmarks may be correlated to stored information where the landmarks may consist of streetlights (¶¶ 14, 34). The depicted sections of 5, 5’ (FIG. 2); 5’’ (FIG. 3) and 5’’’ (FIG. 4) are interpreted to be equivalent to the claimed “blocks” with “streetlights” where each section comprises a start and an end along a road (length of section 5, FIG. 2 and length of section 5’’, FIG. 3) where each section defines the road segment with at least the one streetlight.
It would have been obvious to modify the teachings of Stein and Sasaki to comprise a plurality of streetlight blocks, each streetlight block comprising a start and an end along a road, and each streetlight block defining a road segment having one or more streetlights as taught by Sorsedt to assist in enhance vehicle control features such as driver guidance or similar autonomous features (¶¶ 3-5).
Regarding claims 2 and 10, Stein discloses the method and system, wherein the one or more memory storage areas and the program code is configured to, with the one or more processors, cause the system to, comprising:
obtaining speed data of the vehicle (Vehicle speed ¶ 38); and
wherein the controlling the illumination of the space in front of the vehicle is further based on the obtained speed data (Adjust headlight based on vehicle speed and oncoming vehicles ¶ 38).
Regarding claims 3 and 11, Stein discloses the method and system, wherein the one or more memory storage areas and the program code is configured to, with the one or more processors, cause the system to, further comprising:
obtaining sensor data indicative of a presence of one or more streetlight poles in a
surrounding environment of the vehicle from one or more sensors configured to monitor the
surrounding environment of the vehicle (Streetlights 43, FIG. 4); and
wherein the controlling the illumination of the space in front of the vehicle is further based on the presence of one or more streetlight poles (23, FIG. 3).
Regarding claims 4 and 12, Stein discloses the method and system, wherein the one or more memory storage areas and the program code is configured to, with the one or more processors, cause the system to, further comprising:
obtaining sensor data comprising ambient lighting information of a surrounding
environment of the vehicle from one or more sensors configured to monitor the surrounding
environment of the vehicle (measures ambient light ¶ 45); and
wherein the controlling the illumination of the space in front of the vehicle is further based on the obtained ambient lighting information of the surrounding environment (23, FIG. 3).
Regarding claim 6, Sasaki teaches the method, further comprising obtaining the position of the vehicle (¶ 290).
It would have been obvious to modify Stein to further comprise obtaining the position of the vehicle as taught by Sasaki to enhance cost savings for the data storing system (¶ 357).
Regarding claim 8, Stein discloses a non-transitory computer-readable storage medium storing instructions which, when executed by a computing device of a vehicle, causes the computing device to carry out the method according to claim 1 (¶ 36).
Regarding claim 9, Stein teaches a system for Adaptive High Beam Control (AHBC) for a vehicle (23 Headlight control, FIG. 2), the system comprising one or more memory storage areas comprising program code, the one or more memory storage areas and the program code (algorithm for gathering image frames ¶ 36) being configured to, with one or more processors (24 Processor, FIG. 2), cause the system to at least:
obtain information about an existence of streetlighting for an upcoming road segment
ahead of the vehicle from a digital map layer based on a current position of the vehicle (Detects bright spots in the image, e.g., streetlights, and tracks the spots over time collecting information about the spots regarding their shape, brightness, motion, spatial alignment and possibly color. When the algorithm has accumulated enough evidence that the spot is tagged as being in one of the relevant categories and the headlights are controlled appropriately ¶ 38),
control an illumination of a space in front of the vehicle based on the obtained information about the existence of streetlighting for the upcoming road segment so to avoid casting high beam illumination towards road areas associated with streetlights (Classify Spot 313, 23 control headlight deactivate high beams, FIG. 3).
Stein is silent to the digital map layer being based on a current position of the vehicle, wherein the digital map layer is formed from probe sourced data from a fleet of vehicles. However, in a similar field of endeavor, Sasaki teaches an environment recognition device which accumulates map information (¶ 106) and determines a vehicle location via GPS information (¶ 290) and where special probe vehicles are utilized to create a road traffic database which can be collected cheaply in high volume (¶ 357) and more specifically, include streetlight information (FIG. 5).
It would have been obvious to one with ordinary skill in the art before the effective filing date of the claimed invention to modify the digital map layer taught by Stein to be based on a current position of the vehicle, wherein the digital map layer is formed from probe sourced data from a fleet of vehicles as taught by Sasaki to enhance cost savings for the data storing system (¶ 357).
Stein and Sasaki is silent to wherein the digital map layer comprises a plurality of streetlight blocks, each streetlight block comprising a start and an end along a road, and each streetlight block defining a road segment having one or more streetlights. However, Sorstedt teaches a method for generating navigation data using a vehicle comprising a set of sensors and a step of traveling along a road and detecting at least one landmark and correlating and approving an associated section of a road for navigation (See Abstract). More specifically, sections of a roadway are depicted (See Figs. 2-4) where landmarks may be correlated to stored information where the landmarks may consist of streetlights (¶¶ 14, 34). The depicted sections of 5, 5’ (FIG. 2); 5’’ (FIG. 3) and 5’’’ (FIG. 4) are interpreted to be equivalent to the claimed “blocks” with “streetlights” where each section comprises a start and an end along a road (length of section 5, FIG. 2 and length of section 5’’, FIG. 3) where each section defines the road segment with at least the one streetlight.
It would have been obvious to modify the teachings of Stain and Sasaki to comprise a plurality of streetlight blocks, each streetlight block comprising a start and an end along a road, and each streetlight block defining a road segment having one or more streetlights as taught by Sorsedt to assist in enhance vehicle control features such as driver guidance or similar autonomous features (¶¶ 3-5).
Regarding claim 14, Stein discloses a vehicle comprising a system according to claim 9 (18, FIG. 1).
Claim(s) 5 and 13 are rejected under 35 U.S.C. 103 as being unpatentable over Stein et al. (Pub. No.: US 2007/0221822 A1) and Sasaki (Pub. No.: US 2007/0047809 A1) in view of Sorstedt et al. (Pub. No.: US 2017/0307397 A1) as applied to claims 1 and 9 respectively above, and further in view of Epperlein et al. (Pub. No.: US 2020/005542 A1).
Regarding claims 5 and 13, Epperlein teaches Stein the method and system, wherein the one or more memory storage areas and the program code is configured to, with the one or more processors, cause the system to, further comprising: obtaining information about a speed limit for the upcoming road segment ahead of the vehicle from the digital map based on the current position of the vehicle and/or from one or more sensors configured to monitor a surrounding environment of the vehicle; and wherein controlling the illumination of the space in front of the vehicle is further based on the obtained information about the speed limit for the upcoming road segment (Determine illumination necessary along a vehicles planned trajectory based on speed limit ¶ 23).
It would have been obvious to modify the teachings of Stein and Sasaki in view of Sorstedt to obtain information about a speed limit for the upcoming road segment ahead of the vehicle from the digital map based on the current position of the vehicle and/or from one or more sensors configured to monitor a surrounding environment of the vehicle; and wherein controlling the illumination of the space in front of the vehicle is further based on the obtained information about the speed limit for the upcoming road segment as taught by Epperlein to enhance vehicle safety.
Allowable Subject Matter
Claim 7 is objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to TYLER J LEE whose telephone number is (571)272-9727. The examiner can normally be reached M-F 7:30-5:00.
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/TYLER J LEE/Primary Examiner, Art Unit 3663