Office Action Predictor
Last updated: April 15, 2026
Application No. 18/120,138

AUTOMATIC GENERATING OF BLOCKAGES IN MAP INFORMATION FOR USE BY A FLEET OF AUTONOMOUS VEHICLES

Non-Final OA §103
Filed
Mar 10, 2023
Examiner
JONES, JODI MARIE
Art Unit
3666
Tech Center
3600 — Transportation & Electronic Commerce
Assignee
Waymo LLC
OA Round
3 (Non-Final)
70%
Grant Probability
Favorable
3-4
OA Rounds
3y 1m
To Grant
73%
With Interview

Examiner Intelligence

Grants 70% — above average
70%
Career Allow Rate
48 granted / 69 resolved
+17.6% vs TC avg
Minimal +4% lift
Without
With
+3.7%
Interview Lift
resolved cases with interview
Typical timeline
3y 1m
Avg Prosecution
19 currently pending
Career history
88
Total Applications
across all art units

Statute-Specific Performance

§101
22.2%
-17.8% vs TC avg
§103
54.8%
+14.8% vs TC avg
§102
17.7%
-22.3% vs TC avg
§112
4.8%
-35.2% vs TC avg
Black line = Tech Center average estimate • Based on career data from 69 resolved cases

Office Action

§103
DETAILED ACTION The following is a Non-Final Office Action in response to communications filed on November 03, 2025. Claims 1-3, 5-11, 13-16 and 18-20 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 claim(s) 1-3, 5-11, 13-16 and 18-20 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument. 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) 1,2, 5-7 is/are rejected under 35 U.S.C. 103 as being unpatentable over Passa et al. "Passa" (US 2022/0063661) in view of Stenneth et al. "Stenneth" (US 2022/0063639). Regarding Claim 1, Passa teaches a method of generating blockages in map information for use by a fleet of autonomous vehicles, the method comprising: receiving, by one or more processors of a server computing system, information from an autonomous vehicle (Para. [0035]… Autonomous vehicle 402 additionally comprises an internal computing system 410 that is in communication with sensor systems 480 and systems 430, 432, 434, 436, and 438.) ; in response to the determination, generating, by the one or more processors, blockage data identifying a specific area of a blockage including the geographic area (Para. [0017]… If it is determined that blockage 108 represents an impediment to route 106, i.e., interacts with the best path for vehicle 102, an indication of blockage 108 may be stored, e.g., to a map database); and sending, by the one or more processors, the blockage data to autonomous vehicles of the fleet to enable autonomous control of the autonomous vehicles of the fleet such that the autonomous vehicles of the fleet avoid driving in the specific area of the blockage to prevent future disengagements of the autonomous driving mode or strandings in the geographic area (Para. [0015]... various blockages encountered by one or more AVs (e.g., in an AV fleet), can be indicated in a map database that is accessible by AV 102, as well as any number of AVs, for example, in an AV fleet.) Passa fails to teach receiving, by one or more processors of a server computing system, information from an autonomous vehicle indicating that an autonomous driving mode of the autonomous vehicle has been disengaged in a geographic area or that the autonomous vehicle has become stranded in the geographic area; and determining, by the one or more processors, that the geographic area has met a set of rules including a minimum number of disengagement or stranding instances associated with the fleet within the geographic area based on the received information indicating that the autonomous driving mode of the autonomous vehicle has been disengaged in the geographic area or that the autonomous vehicle has become stranded in the geographic area However, Stenneth teaches receiving, by one or more processors of a server computing system, information from an autonomous vehicle indicating that an autonomous driving mode of the autonomous vehicle has been disengaged in a geographic area or that the autonomous vehicle has become stranded in the geographic area (Para. [0056]…the apparatus 102 includes means, such as the processing circuitry 106, the memory 108, or the like, configured to access historical autonomous transition data associated with vehicles that transition from respective autonomous levels while traveling along one or more road segments associated with a first geographic area.; determining, by the one or more processors, that the geographic area has met a set of rules including a minimum number of disengagement or stranding instances associated with the fleet within the geographic area based on the received information indicating that the autonomous driving mode of the autonomous vehicle has been disengaged in the geographic area or that the autonomous vehicle has become stranded in the geographic area (Para. [0057….spatial reference point can be an autonomous transition region. For example, a spatial reference point can be a region of one or more road segments where an autonomous level for vehicles is likely to change… the apparatus 102, such as the processing circuitry 106, can be configured to designate a cluster as a spatial reference point in response to a determination that a minimum number of vehicles is within the spatial reference point or within a certain distance from the spatial reference point….Para. [0093]…the processing circuitry 106, can be configured to predict, using a machine learning model that receives the one or more features, whether the road segment comprises an autonomous transition area in which a particular number of vehicles are transitioned from respective autonomous levels. For example, in one or more embodiments, the machine learning model can be trained based on historical autonomous transition data associated with one or more second vehicles that are transitioned from respective autonomous levels while traveling along one or more road segments within a second geographic area, different than the first geographic area.) It would be obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the blockage routing method as taught by Passa with the method to predict autonomous transition regions using historical information as taught by Stenneth to improve navigation, route guidance, semi-autonomous and fully autonomous vehicle control (Stenneth, Para. [0004]). Regarding Claim 2, Passa in view of Stenneth teach the method of claim 1, wherein the received information indicates that the autonomous vehicle has disengaged from the autonomous driving mode in the geographic area (Stenneth, Para. [0092]…the apparatus 102, such as the processing circuitry 106, can be configured to generate and/or update transition pattern data ( e.g., disengagement pattern data and/or engagement pattern data) for a map layer associated with the second geographic area based on the predicted autonomous transition data for the second geographic area. ) Regarding Claim 5, Passa in view of Stenneth teach the method of claim 1, wherein determining that the geographic area has met the set of rules includes determining that the minimum number of disengagement or stranding incidents within the geographic area satisfies (Stenneth, Para. [0093]… the apparatus 102, such as the processing circuitry 106, can be configured to predict, using a machine learning model that receives the one or more features, whether the road segment comprises an autonomous transition area in which a particular number of vehicles are transitioned from respective autonomous levels. For example, in one or more embodiments, the machine learning model can be trained based on historical autonomous transition data associated with one or more second vehicles that are transitioned from respective autonomous levels while traveling along one or more road segments within a second geographic area, different than the first geographic area. ) Regarding Claim 6, Passa in view of Stenneth teach the method of claim 1, further comprising: receiving, by the one or more processors, updated information from a second autonomous vehicle (Passa, Para. [0017]; in response to the received updated information, determining, by the one or more processors, that the geographic area has met a second set of rules including a minimum number of autonomous vehicles (Stenneth, Para. [0093]); and based on the determination that the second set of rules has been met, sending a second instruction to the autonomous vehicles of the fleet to remove the blockage from map information stored locally at the autonomous vehicles of the fleet (Passa, Para. [0024-0025]. Regarding Claim 7, Passa in view of Stenneth teach the method of claim 6, wherein the second set of rules is associated with a timing constraint for the minimum number of autonomous vehicles providing the updated information being met (Stenneth, Para. [0066-0068]). Claim(s) 3 is/are rejected under 35 U.S.C. 103 as being unpatentable over Passa et al. "Passa" (US 2022/0063661) in view of Stenneth et al. "Stenneth" (US 2022/0063639) and in further view of Rusciano et al. "Rusciano" (US 2023/0368673). Regarding Claim 3, Passa in view of Stenneth teach the method of claim 1, but fails to teach wherein the received information indicated that the autonomous vehicles has become stranded in the geographic area. However, Rusciano teaches wherein the received information includes stranding information indicating a stranding instance associated with the autonomous vehicle (Para. [0027]...the autonomous vehicle 110 includes systems and methods for determining a risk profile of its situation if it becomes stranded and in need of recovery. In some examples, a stranded vehicle includes degraded sensors or other degraded components. In some examples, the autonomous vehicle 110 includes a risk determination component 106 that uses vehicle sensor data and location information to determine a vehicle risk profile and/or a vehicle severity level when a vehicle is in need of recovery). 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 of Passa in view of Stenneth with the method of autonomous fleet recovery as taught by Rusciano to improve quality and experience (Rusciano, Para. [0095)). Claim(s) 8-10 and 13-15 is/are rejected under 35 U.S.C. 103 as being unpatentable over Passa et al. "Passa" (US 2022/0063661) in view of Stenneth et al. "Stenneth" (US 2022/0063639) in further view of Beaurepaire et al. (US 2022/0063654). Regarding Claim 8, Passa in view of Stenneth teach the method of claim 1, further comprising: receiving, by the one or more processors, second information from a second autonomous vehicle (Passa, Para. [0017]… the encounter of AV 102 with blockage 108 may also be used to confirm/verify the persistence of blockage 108 which may have been previously identified by AV 102, or another fleet vehicle); determining, by the one or more processors, that the received information does not meet any of set of rules for generating blockages (Passa, Para. [0024]) ; determining, by the one or more processors, that a second blockage is needed based on the second information and an increase in a number of disengagement or stranding instances associated with the fleet (Beaurepaire, Para. [0122]); in response to determining that a second blockage is needed, generating, by the one or more processors, second blockage data identifying a second specific area of the second blockage (Passa, Para. [0026]… if the blockage is observed within the predetermined time period, then the blockage is added/output to a list or database of persisted blockage results, e.g., a map database); and sending, by the one or more processors, the second blockage data to the autonomous vehicles of the fleet in order to enable the autonomous vehicles of the fleet to avoid the second specific area of the second blockage (Passa, Para. [0036]…. the constraint may be a restriction upon navigation that is activated in accordance with protocols configured to avoid occupying the same space as other objects, abide by traffic laws, circumvent avoidance areas, etc.) It would be obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the blockage routing method as taught by Passa in view of Stenneth with the method to improve user experience for autonomous driving in transition regions as taught by Beaurepaire to potentially reduce accidents and operate autonomous vehicles in a more efficient and cost-effective manner (Beaurepaire, Para. [0099]). Regarding Claim 9, Passa in view of Stenneth and Beaurepaire teach the method of claim 8, further comprising using a probabilistic approach to determine the increase in the number of disengagement or stranding instances associated with the fleet (Stenneth, Para. [0079-0080]) Regarding Claim 10, Passa in view of Stenneth and Beaurepaire teach a method of generating blockages in map information for use by a fleet of autonomous vehicles, the method comprising: receiving, by one or more processors of a server computing system, information from an autonomous vehicle indicating that the autonomous vehicle is within a geographic area; (please refer to the rejection of claim 1 above); determining, by the one or more processors, that the geographic area has met at least one set of rules for generating blockages, including that the geographic area has been traversed by a minimum number of autonomous vehicles (Beaurepaire, Para. [0122-0124]); based on the determination that the received information meets at least one set of rules for generating blockages, generating, by the one or more processors, a blockage data identifying a specific area of a blockage including the geographic area indicating the autonomous vehicle is within the geographic area; (refer to the rejection of claim 1 above) ; and sending, by the one or more processors, the blockage data to autonomous vehicles of the fleet in order to enable the autonomous vehicles of the fleet to avoid the specific area of the blockage in order to reduce traffic congestion within the geographic area. (refer to the rejection of claim 1 above). Regarding Claim 13, Passa in view of Stenneth and Beaurepaire teach the method of claim 10, wherein determining that the geographic area has met the set of rules include determining that the number of autonomous vehicles that have traversed the geographic area satisfies a timing constraint (Beaurepaire, Para. [0122-0124]). Regarding Claim 14, Passa in view of Stenneth and Beaurepaire teach the method of claim 10, further comprising: receiving, by the one or more processors, updated information from a second autonomous vehicle of the fleet (Passa, Para. [0032]… The persistence duration for the blockage can be updated based on subsequent observations, either by the same AV, or by other AVs, for example, in an AV fleet); in response to receiving the updated information, determining, by the one or more processors, based on the updated information that a second set of rules for removing the blockage including a minimum number of autonomous vehicles (Passa, Para. [0032]); and based on the determination that the second set of rules has been met, sending a second instruction to the autonomous vehicles of the fleet to remove the blockage from map information stored locally at the autonomous vehicles of the fleet (Passa, Para. [0026]) . Regarding Claim 15, Passa in view of Stenneth and Beaurepaire teach the method of claim 14, wherein the second set of rules is associated with a timing constraint for the minimum number of autonomous vehicles providing the updated information (Stenneth, Para. [0067-0068]). Claim(s) 11 is/are rejected under 35 U.S.C. 103 as being unpatentable over Passa et al. ( US 2022/0063661) in view of Stenneth et al. (US 2022/0063639) in view of Beaurepaire et al. ( US 2022/0063654) in further view of Abrams (US 2020/0363223). Regarding Claim 11, Passa in view of Stenneth and Beaurepaire teach the method of claim 10, but fails to teach wherein the geographic area is a cul-de-sac . However, Abrams teaches wherein the geographic area is a cul-de-sac (Para. [0031]... These lane lines may designate roads or otherwise drivable areas such as lanes 220, 222, 224, 226 and cul-de-sac 230.) It would be obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Passa in view of Stenneth and Beaurepaire with the stranding analysis as taught by Abrams to improve the passenger or user experience (Abrams, Para. [0020]). Allowable Subject Matter Claims are 16, 18-20 pending and allowed. The following is a statement of reasons for the indication of allowable subject matter: In regards to independent claims 16, Passa et al. (US 2022/0063661) Stenneth et al. (2022/0063639) and Beaurepaire et al. (US 2022/0063654) alone, or as combined or modified, fail to show, teach or suggest the context of the remaining limitations of the claim(s):. Regarding Claim 16, a method of generating blockages in map information for use by a fleet of autonomous vehicles, the method comprising: receiving, by one or more processors of a server computing system, information from an autonomous vehicle indicating that the autonomous vehicle has reported entering a fallback state based on occurrence of an error situation within a geographic area; determining, by the one or more processors, that the geographic area has met at least one set of rules for generating blockages including a minimum number of autonomous vehicles of the fleet entering the fallback state based on occurrence of the error situation within the geographic area based on the received information indicating that the autonomous vehicle has reported entering the fallback state based on occurrence of the error situation within the geographic area; based on the determination that the received information meets at least one set of rules for generating blockages, generating, by the one or more processors, blockage data identifying a specific area of a blockage including the geographic area; and sending, by the one or more processors, the blockage data to autonomous vehicles of the fleet to enable autonomous control the autonomous vehicles of the fleet such that the autonomous vehicles of the fleet avoid driving the specific area of the blockage including the geographic area. Conclusion 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. 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, Anne Antonucci can be reached on (313) 446-6519. 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. /JODI JONES/Examiner, Art Unit 3666 /ANNE MARIE ANTONUCCI/Supervisory Patent Examiner, Art Unit 3666
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Prosecution Timeline

Mar 10, 2023
Application Filed
Mar 05, 2025
Non-Final Rejection — §103
Jun 05, 2025
Response Filed
Sep 03, 2025
Final Rejection — §103
Nov 03, 2025
Request for Continued Examination
Nov 09, 2025
Response after Non-Final Action
Dec 22, 2025
Non-Final Rejection — §103
Mar 17, 2026
Interview Requested
Mar 25, 2026
Applicant Interview (Telephonic)
Mar 26, 2026
Examiner Interview Summary
Mar 30, 2026
Response Filed

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Study what changed to get past this examiner. Based on 5 most recent grants.

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Prosecution Projections

3-4
Expected OA Rounds
70%
Grant Probability
73%
With Interview (+3.7%)
3y 1m
Median Time to Grant
High
PTA Risk
Based on 69 resolved cases by this examiner. Grant probability derived from career allow rate.

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