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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 06/27/2025 has been entered.
Response to Arguments
Applicant’s arguments, see pages 7-8, filed 06/27/2025, with respect to the rejection(s) of Claims 1-2, and 4-20 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 Therefore, the rejection has been withdrawn.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 Shwartz (US 20220269277 A1).
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 4-20 are rejected under § 103 as being unpatentable over Wheeler (US 20180188045 A1) in view of Shalev-Shwartz (US 20220269277 A1).
Regarding Claim 1, Wheeler discloses a computer implemented method comprising:
transmitting, by one or more computing devices of an autonomous vehicle (AV), an identifier for the AV to a cloud computing service; [0030] “the online HD map system 110 is implemented as a distributed computing system, for example, a cloud-based service that allows clients such as vehicle computing systems 120 to make requests for information and services” [0053] “Upon detecting a map discrepancy, the vehicle 150 sends an update message to the online HD map system 110 comprising information regarding the map discrepancy. The map discrepancy module 290 may construct the update message, which may comprise a vehicle identifier (ID), one or more timestamps, a route traveled, lane element IDs of lane elements traversed, a type of discrepancy, a magnitude of discrepancy, a discrepancy fingerprint to help identify duplicate discrepancy alert messages” The vehicle ID is used to identify the vehicle within the system.
receiving, by the one or more computing devices and from the cloud computing service, a map update document for a map zone linked to the identifier, wherein the map update document contains attributes of the map zone; [0033] “The online HD map system 110 uses the data received from the vehicles 150 to create and update HD maps describing the regions in which the vehicles 150 are driving.” [0034] “The online HD map system 110 sends 125 HD maps to individual vehicles 150 as required by the vehicles 150. For example, if an autonomous vehicle needs to drive along a route, the vehicle computing system 120 of the autonomous vehicle provides information describing the route being traveled to the online HD map system 110.” The HD map system sends route-specific map data, effectively delivering the map zone and its attributes to the vehicle.
generating, by the one or more computing devices and based on information provided by sensors of the AV, a local map update document including data indicating road conditions of the map zone [0006] “The autonomous vehicles detect map discrepancies based on differences in the surroundings observed using sensor data compared to the high-definition map and send messages describing these map discrepancies to the online system.” [0030] “The online HD map system 110 receives sensor data captured by sensors of the vehicles, and combines the data received from the vehicles 150 to generate and maintain HD maps.” Wheeler discloses that vehicles detect discrepancies using their own sensors, which means they generate a local map update document before sending data to the cloud. The messages describing discrepancies sent to the system constitute a local map update document containing road condition data. [0118] “the vehicle 150 compares the remaining portion of the 3D representation to the existing occupancy map to determine whether to add new representations and/or whether to remove existing representations. For example, if the remaining portion of the 3D representation includes an object (or a road) that is not represented in the existing occupancy map, the vehicle 150 updates the existing occupancy map to include a representation of this object (or this road). As another example, if the existing occupancy map includes a representation of an object (or a road) that is not represented in the remaining portion of the 3D representation, the vehicle 150 updates the existing occupancy map to remove the representation of this object (or this road).” Wheeler describes comparing sensor data with an existing HD map and determining differences. When a vehicle identifies a change in road conditions (e.g., missing lane markings, new construction barriers), it generates a more restrictive version of the map data by either removing outdated data or adding new obstacles. This shows a “more restrictive” data attribute, as it restricts the AV's possible routes or modifies navigation constraints.
and transmitting, by the one or more computing devices, the updated map to one or more downstream modules of the AV configured to use the updated map to operate the AV. [0034] “The online HD map system 110 sends (i.e., transmits) 125 HD maps to individual vehicles 150 as required by the vehicles 150 [0106] “The HD map system 110 determines 1016 a set of changes to the HD map 510, if the confidence value is above the threshold value. The HD map system 110 determines whether changes should be made to the landmark map 520. For example, the HD map system 110 determines whether one or more attributes (e.g., a location, a geometric shape, a semantic information) of an existing landmark object needs to be changed, whether an existing landmark object should be removed, and whether a new landmark object should be added and associated attributes. The HD map system 110 creates a change record for a particular landmark object that should be modified, added, or removed.”
Wheeler does not appear to fully teach the claim limitation regarding “determining, by using the one or more computing devices to compare the attributes of the map zone and the data, a more restrictive data or attribute between the attributes of the map zone and the data” and “generating, by the one or more computing devices, an updated map by applying the more restrictive data or attribute to a base map of the AV”
However, Shwartz teaches equivalent teachings wherein determining, by using the one or more computing devices to compare the attributes of the map zone and the data, a more restrictive data or attribute between the attributes of the map zone and the data [0280] “Supplementation or augmentation of navigational constraints may be performed on a per set basis (e.g., by adding new navigational constraints to a predetermined set of constraints) or may be performed on a per constraint basis (e.g., modifying a particular constraint such that the modified constraint is more restrictive than the original, or adding a new constraint that corresponds to a predetermined constraint, wherein the new constraint is more restrictive than the corresponding constraint in at least one aspect).” [0285] “Where the presence of a navigational constraint augmentation factor is identified (e.g., at step 1507), a second navigational constraint may be determined or developed in response to detection of the constraint augmentation factor. This second navigational constraint may be different from the first navigational constraint and may include at least one characteristic augmented with respect to the first navigational constraint. The second navigational constraint may be more restrictive than the first navigational constraint, because detection of a constraint augmentation factor in the environment of the host vehicle or associated with the host vehicle may suggest that the host vehicle may have at least one navigational capability reduced with respect to normal operating conditions.”
generating, by the one or more computing devices, an updated map by applying the more restrictive data or attribute to a base map of the AV [0083] “wireless transceiver 172 may and/or receive data over one or more networks (e.g., cellular networks, the Internet, etc.). For example, wireless transceiver 172 may upload data collected by system 100 to one or more servers, and download data from the one or more servers. Via wireless transceiver 172, system 100 may receive, for example, periodic or on demand updates to data stored in map database 160, memory 140, and/or memory 150. Similarly, wireless transceiver 172 may upload any data (e.g., images captured by image acquisition unit 120, data received by position sensor 130 or other sensors, vehicle control systems, etc.) from system 100 and/or any data processed by processing unit 110 to the one or more servers.” [0359] “Map database 1911 may include any type of database for storing map data useful to system 1900. In some embodiments, map database 1911 may include data relating to the position, in a reference coordinate system, of various items, including roads, water features, geographic features, businesses, points of interest, restaurants, gas stations, etc. Map database 1911 may store not only the locations of such items, but also descriptors relating to those items, including, for example, names associated with any of the stored features. In some cases, map database 1911 may store a sparse data model including polynomial representations of certain road features (e.g., lane markings) or target trajectories for the host vehicle. Map database 1911 may also include stored representations of various recognized landmarks that may be used to determine or update a known position of the host vehicle with respect to a target trajectory.”
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Wheeler to include the features of Shwartz to make the system wherein determining, by using the one or more computing devices to compare the attributes of the map zone and the data, a more restrictive data or attribute between the attributes of the map zone and the data and generating, by the one or more computing devices, an updated map by applying the more restrictive data or attribute to a base map of the AV.
A person that is skilled in the art would have been motivated to combine Wheeler and Shwartz teachings to improve operational safety and accuracy of the system [Shwartz 0003] “the goal of a fully autonomous vehicle that is capable of navigating on roadways is on the horizon. Autonomous vehicles may need to take into account a variety of factors and make appropriate decisions based on those factors to safely and accurately reach an intended destination. For example, an autonomous vehicle may need to process and interpret visual information (e.g., information captured from a camera), information from radar or lidar, and may also use information obtained from other sources (e.g., from a GPS device, a speed sensor, an accelerometer, a suspension sensor, etc.)”
Regarding Claim 2, Wheeler in combination with Shwartz discloses the method of claim 1, Wheeler further teaches wherein the attributes include at least: some map zone identifiers, a map zone type, coordinates defining the map zone on the base map, and data specific to the map zone. [0069] “the online HD map system 110 represents a geographic region (i.e., map zone) using an object or a data record that comprises various attributes including, a unique identifier for the geographical region, a unique name for the geographical region, description of the boundary of the geographical region, for example, using a bounding box of latitude and longitude coordinates, and a collection of landmark features and occupancy grid data.”
Wheeler does not appear to fully teach the claim limitation regarding “a map zone identifier”
However, Shwartz teaches equivalent teachings a map zone identifier [0359] “Map database 1911 may also include stored representations of various recognized landmarks that may be used to determine or update a known position of the host vehicle with respect to a target trajectory. The landmark representations may include data fields such as landmark type, landmark location, among other potential identifiers. Accordingly, sensory information (such as images. RADAR signal, depth information from LIDAR or stereo processing of two or more images) of the environment may be processed together with position information, such as a GPS coordinate, vehicle's ego motion, etc., to determine a current location of the vehicle relative to the known landmarks, and refine the vehicle location. Certain aspects of this technology are included in a localization technology known as REM™, which is being marketed by the assignee of the present application.”
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Wheeler to include the features of Shwartz to make the system wherein the attributes include at least: map zone identifier, a map zone type, coordinates defining the map zone on the base map, and data specific to the map zone.
A person that is skilled in the art would have been motivated to combine Wheeler and Shwartz teachings to improve operational safety and accuracy of the system [0003] “the goal of a fully autonomous vehicle that is capable of navigating on roadways is on the horizon. Autonomous vehicles may need to take into account a variety of factors and make appropriate decisions based on those factors to safely and accurately reach an intended destination. For example, an autonomous vehicle may need to process and interpret visual information (e.g., information captured from a camera), information from radar or lidar, and may also use information obtained from other sources (e.g., from a GPS device, a speed sensor, an accelerometer, a suspension sensor, etc.)”
Regarding Claim 4, Wheeler discloses the method of claim 1, wherein the transmitting of the updated map to the one or more downstream modules is done based on a subscription model in which the one or more downstream modules subscribe to map client libraries that are configured to push the up-dated map to the one or more downstream modules when the updated map is generated. [0030] “The online HD map system 110 sends HD map data to the vehicles for use in driving the vehicles. In an embodiment, the online HD map system 110 is implemented as a distributed computing system, for example, a cloud-based service that allows clients such as vehicle computing systems 120 to make requests for information and services. For example, a vehicle computing system 120 may make a request for HD map data for driving along a route and the online HD map system 110 provides the requested HD map data.” Downstream modules subscribe to map libraries for automatic updates that is connected to this system. The cloud service is acting like a subscription-based model where the vehicle requests map data as needed.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Wheeler to include the features of Shwartz to make the system wherein the transmitting of the updated map to the one or more downstream modules is done based on a subscription model in which the one or more downstream modules subscribe to map client libraries that are configured to push the up-dated map to the one or more downstream modules when the updated map is generated.
Regarding Claim 5, Wheeler discloses the method of claim 4, further comprising transmitting the updated map to the one or more downstream modules in real-time after the updated map is generated. [0124] “The vehicle 150 periodically receives 1140 real-time sensor data. The vehicle 150 fetches 1142 occupancy map data based on the current location from the occupancy map database 1168. The vehicle 150 processes 1144 the sensor data to obtain images of surroundings of the vehicle 150 as well as LIDAR scanner points. The vehicle 150 registers 1146 the images in the 3D coordinate system of the occupancy map to thereby create a 3D representation of the surroundings. The vehicle 150 may perform 1148 live 3D obstacle detection concurrently with registering the images. The vehicle 150 detects 1150 any moving obstacles, and can remove 1152 certain moving obstacles from the 3D representation of the surroundings. The vehicle 150 may remove moving obstacles to boost localization success rate. Steps 1148, 1150, and 1152 may occur in real-time, while the remaining steps may occur offline.”
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Wheeler to include the features of Shwartz to make the system wherein further comprising transmitting the updated map to the one or more downstream modules in real-time after the updated map is generated.
Regarding Claim 6, Wheeler discloses the method of claim 4, further comprising transmitting the updated map to the one or more downstream modules based on a scheduled time interval. [0055] “the vehicle sends update messages only upon reaching or docking at high bandwidth access points, at which time it will send either a collated update message or a set of update messages, comprising update messages constructed since the last high bandwidth access point was reached or docked at. In an embodiment, upon receiving a confirmation message that the collated update message or one or more update messages were received by the online HD map system 110, the vehicle 150 marks the data for deletion to schedule a local delete process and/or deletes the data. Alternatively, the vehicle may report to the server periodically based on time, such as every hour.”
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Wheeler to include the features of Shwartz to make the system wherein further comprising transmitting the updated map to the one or more downstream modules based on a scheduled time interval.
Regarding Claim 7, Wheeler discloses the method of claim 1, further comprising setting, by the one or more computing devices, a minimum time interval at which to receive the map update document from the cloud computing service. [0055] “upon receiving a confirmation message that the collated update message or one or more update messages were received by the online HD map system 110, the vehicle 150 marks the data for deletion to schedule a local delete process and/or deletes the data. Alternatively, the vehicle may report to the server periodically based on time, such as every hour (i.e., minimum time intervals).”
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Wheeler to include the features of Shwartz to make the system wherein further comprising setting, by the one or more computing devices, a minimum time interval at which to receive the map update document from the cloud computing service.
Regarding Claim 8, Wheeler discloses a non-transitory computer readable medium [0165] “machine able to read instructions from a machine-readable medium and execute them in a processor (or controller).” The claim also recites the parallel limitations in claim 1, respectively for the reasons discussed above. Therefore, claim 8 is rejected using the same rational reasoning.
Regarding Claim 9, The claim recites the parallel limitations in claim 2, respectively for the reasons discussed above. Therefore, claim 9 is rejected using the same rational reasoning.
Regarding Claim 10, The claim recites the parallel limitations in claim 3, respectively for the reasons discussed above. Therefore, claim 10 is rejected using the same rational reasoning.
Regarding Claim 11, The claim recites the parallel limitations in claim 4, respectively for the reasons discussed above. Therefore, claim 11 is rejected using the same rational reasoning.
Regarding Claim 12, The claim recites the parallel limitations in claim 5, respectively for the reasons discussed above. Therefore, claim 12 is rejected using the same rational reasoning.
Regarding Claim 13, The claim recites the parallel limitations in claim 6, respectively for the reasons discussed above. Therefore, claim 13 is rejected using the same rational reasoning.
Regarding Claim 14, The claim recites the parallel limitations in claim 7, respectively for the reasons discussed above. Therefore, claim 14 is rejected using the same rational reasoning.
Regarding Claim 15, Wheeler discloses a computing system comprising: a memory storing instructions; and one or more processors of an autonomous vehicle (AV), coupled to the memory, configured to process the stored instructions. [0165] “machine able to read instructions from a machine-readable medium and execute them in a processor (or controller).” The claim also recites the parallel limitations in claim 1, respectively for the reasons discussed above. Therefore, claim 15 is rejected using the same rational reasoning.
Regarding Claim 16, The claim recites a system of the parallel limitations in claim 2, respectively for the reasons discussed above. Therefore, claim 16 is rejected using the same rational reasoning.
Regarding Claim 17, The claim recites a system of the parallel limitations in claim 4, respectively for the reasons discussed above. Therefore, claim 17 is rejected using the same rational reasoning.
Regarding Claim 18, The claim recites a system of the parallel limitations in claim 5, respectively for the reasons discussed above. Therefore, claim 18 is rejected using the same rational reasoning.
Regarding Claim 19, The claim recites a system of the parallel limitations in claim 6, respectively for the reasons discussed above. Therefore, claim 19 is rejected using the same rational reasoning.
Regarding Claim 20, The claim recites a system of the parallel limitations in claim 7, respectively for the reasons discussed above. Therefore, claim 20 is rejected using the same rational reasoning.
Claim 3 is rejected under § 103 as being unpatentable over Wheeler (US 20180188045 A1), in view of Shalev-Shwartz (US 20220269277 A1), and further in view of Scattolin (US 20190187877 A1).
Regarding Claim 3, The method of claim 1, Wheeler and Shwartz do not appear to teach wherein the map update document is implemented as a JavaScript Object Notation (JSON) file or a Protocol Buffers document. However, Scattolin teaches equivalent teachings wherein the map update document is implemented as a JavaScript Object Notation (JSON) file or a Protocol Buffers document [0021] “the map rendering engine 120 can include a JavaScript library downloaded (i.e., updated) from the server system 100 or other host over a communication network 135 to render the GUI of the map interface 130 based on web documents such as HTML content.”
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the inventions of Wheeler and Shwartz to include the features of Scattolin to have the system include the map update document which is implemented as a JavaScript.
A person that is skilled in the art would have been motivated to combine Wheeler, Shwartz, and Scattolin teachings to improve operational effectiveness and efficiency of the system [Scattolin 0015] “Highlighting such resource icons relative to the resource icons representing other cloud resources that do not satisfy the received search criteria improves the ability of the map to be efficiently searched”
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to HUSSAM ALZATEEMEH whose telephone number is (703)756-1013. The examiner can normally be reached 8:00-5:00 M-F.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Aniss Chad can be reached on (571) 270-3832. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/HUSSAM ALDEEN ALZATEEMEH/Examiner, Art Unit 3662
/ANISS CHAD/Supervisory Patent Examiner, Art Unit 3662