Prosecution Insights
Last updated: April 19, 2026
Application No. 18/886,955

SHARED MOBILITY SIMULATION AND PREDICTION SYSTEM

Non-Final OA §101§103§112
Filed
Sep 16, 2024
Examiner
WEBER, TAMARA L
Art Unit
3667
Tech Center
3600 — Transportation & Electronic Commerce
Assignee
Allstate Insurance Company
OA Round
1 (Non-Final)
87%
Grant Probability
Favorable
1-2
OA Rounds
2y 3m
To Grant
99%
With Interview

Examiner Intelligence

Grants 87% — above average
87%
Career Allow Rate
531 granted / 609 resolved
+35.2% vs TC avg
Moderate +12% lift
Without
With
+12.0%
Interview Lift
resolved cases with interview
Typical timeline
2y 3m
Avg Prosecution
17 currently pending
Career history
626
Total Applications
across all art units

Statute-Specific Performance

§101
15.7%
-24.3% vs TC avg
§103
34.6%
-5.4% vs TC avg
§102
23.1%
-16.9% vs TC avg
§112
18.2%
-21.8% vs TC avg
Black line = Tech Center average estimate • Based on career data from 609 resolved cases

Office Action

§101 §103 §112
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 . 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. Claim Status This action is in response to applicant’s filing on 9/16/2024 and 11/30/2024. Claims 1-20 are pending and considered below. Claim Objections Claims 7 and 14 are objected to because of the following informalities: “risk of bodily” should be “risk of bodily injury”. Appropriate correction is required. Claim Rejections - 35 USC § 112 The following is a quotation of 35 U.S.C. 112(b): (b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention. The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph: The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention. Claims 7 and 14 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention. Regarding claims 7 and 14, the phrase “causing the device to present information indicative of the weighted average to the device” is vague and indefinite. Claim Rejections - 35 USC § 101 35 U.S.C. 101 reads as follows: Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title. Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without integrating the judicial exception into a practical application and without an additional element which amounts to significantly more than the judicial exception. Regarding claims 1-7, step 1 analysis, the subject matter of claims 1-7 is included in the four patent-eligible subject matter categories (e.g., process, machine, manufacture, or composition of matter). Claims 1-7 are directed to a device (one or more processors and one or more storage devices). Claims 1-7 are directed to a judicial exception. The claim limitations recite a revised step 2A, prong one, abstract idea (a mental process involving observation and evaluation which could be performed in the human mind). Claims 1-7 are directed to a device for determining risk information for each of one or more drivers; and determining aggregate risk information associated with an updated selection of one or more drivers. This limitation is a simple process that, under the broadest reasonable interpretation, covers performance of the limitation in the mind. For example, the claims encompass a ride-share manager determining that a driver with multiple collisions represents an unacceptable risk; deciding to fire the driver; and determining that the removal of the driver improves the fleet risk score. Thus, the claims recite a mental process. Claims 1-7 include the revised step 2A, prong two, additional elements of receiving driver information; presenting aggregate risk information associated with a first selection of one or more drivers; receiving an indication to add or remove one or more drivers from the first selection of one or more drivers; and presenting aggregate risk information associated with an updated selection of one or more drivers. Receiving driver information; and receiving an indication to add or remove one or more drivers from the first selection of one or more drivers is data gathering, which is a form of insignificant extra-solution activity. Presenting aggregate risk information associated with a first selection of one or more drivers; and presenting aggregate risk information associated with an updated selection of one or more drivers is insignificant extra-solution activity. Claims 1-7 do not recite revised step 2A, prong two, additional elements that integrate the abstract idea into a practical application. Claims 1-7 generally link the use of the abstract idea to a particular technological environment or field of use (ride-share vehicle systems). Claims 1-7 include the step 2B additional elements of one or more processors, and one or more storage devices. Applicant’s specification does not provide any indication that the processors and storage devices are anything other than conventional processors and storage devices. Receiving input information and presenting output information are well-understood, routine, and conventional functions when claimed using generic processors and storage devices. Processors and storage devices are widely prevalent and in common use in ride-share vehicle systems. Processors and storage devices are not significantly more than the judicial exception since they are well-understood, routine, and conventional features previously known to the ride-share vehicle industry. Therefore, claims 1-7 are rejected under 35 U.S.C. 101. Regarding claims 8-14, step 1 analysis, the subject matter of claims 8-14 is included in the four patent-eligible subject matter categories. Claims 8-14 are directed to a device (a non-transitory computer readable medium, and at least one processor). Claims 8-14 are directed to a judicial exception. The claim limitations recite a revised step 2A, prong one, abstract idea (a mental process involving observation and evaluation which could be performed in the human mind). Claims 8-14 are directed to a device for determining risk information for each of one or more drivers; and determining aggregate risk information associated with an updated selection of one or more drivers. This limitation is a simple process that, under the broadest reasonable interpretation, covers performance of the limitation in the mind. For example, the claims encompass a ride-share manager determining that a driver with multiple collisions represents an unacceptable risk; deciding to fire the driver; and determining that the removal of the driver improves the fleet risk score. Thus, the claims recite a mental process. Claims 8-14 include the revised step 2A, prong two, additional elements of receiving driver information; presenting aggregate risk information associated with a first selection of one or more drivers; receiving an indication to add or remove one or more drivers from the first selection of one or more drivers; and presenting aggregate risk information associated with an updated selection of one or more drivers. Receiving driver information; and receiving an indication to add or remove one or more drivers from the first selection of one or more drivers is data gathering, which is a form of insignificant extra-solution activity. Presenting aggregate risk information associated with a first selection of one or more drivers; and presenting aggregate risk information associated with an updated selection of one or more drivers is insignificant extra-solution activity. Claims 8-14 do not recite revised step 2A, prong two, additional elements that integrate the abstract idea into a practical application. Claims 8-14 generally link the use of the abstract idea to a particular technological environment or field of use (ride-share vehicle systems). Claims 8-14 include the step 2B additional elements of a non-transitory computer readable medium, and at least one processor. Applicant’s specification does not provide any indication that the medium and processors are anything other than conventional media and processors. Receiving input information and presenting output information are well-understood, routine, and conventional functions when claimed using generic media and processors. Media and processors are widely prevalent and in common use in ride-share vehicle systems. Media and processors are not significantly more than the judicial exception since they are well-understood, routine, and conventional features previously known to the ride-share vehicle industry. Therefore, claims 8-14 are rejected under 35 U.S.C. 101. Regarding claims 15-20, step 1 analysis, the subject matter of claims 15-20 is included in the four patent-eligible subject matter categories. Claims 15-20 are directed to a method. Claims 15-20 are directed to a judicial exception. The claim limitations recite a revised step 2A, prong one, abstract idea (a mental process involving observation and evaluation which could be performed in the human mind). Claims 15-20 are directed to a method for determining risk information for each of one or more drivers; and determining aggregate risk information associated with an updated selection of one or more drivers. This limitation is a simple process that, under the broadest reasonable interpretation, covers performance of the limitation in the mind. For example, the claims encompass a ride-share manager determining that a driver with multiple collisions represents an unacceptable risk; deciding to fire the driver; and determining that the removal of the driver improves the fleet risk score. Thus, the claims recite a mental process. Claims 15-20 include the revised step 2A, prong two, additional elements of receiving driver information; presenting aggregate risk information associated with a first selection of one or more drivers; receiving an indication to add or remove one or more drivers from the first selection of one or more drivers; and presenting aggregate risk information associated with an updated selection of one or more drivers. Receiving driver information; and receiving an indication to add or remove one or more drivers from the first selection of one or more drivers is data gathering, which is a form of insignificant extra-solution activity. Presenting aggregate risk information associated with a first selection of one or more drivers; and presenting aggregate risk information associated with an updated selection of one or more drivers is insignificant extra-solution activity. Claims 15-20 do not recite revised step 2A, prong two, additional elements that integrate the abstract idea into a practical application. Claims 15-20 generally link the use of the abstract idea to a particular technological environment or field of use (ride-share vehicle systems). Claims 15-20 do not include any step 2B additional elements. Therefore, claims 15-20 are rejected under 35 U.S.C. 101. See, the 2019 Revised Patent Subject Matter Eligibility Guidance, which is available on the USPTO Website. 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 1-5, 8-12 and 15-19 are rejected under 35 U.S.C. 103 as being unpatentable over Pinkus (US-2013/0066688-A1, hereinafter Pinkus). Regarding claim 1, Pinkus discloses: one or more processors (paragraphs [0066-0068]); one or more storage devices that store instruction code executable by the one or more processors to cause the computing platform to perform operations comprising: (paragraphs [0066-0068] and FIG. 3, regulatory agency computer system-200, CPU-210, and data store-213); receiving, from one or more data sources, driver information associated with one or more drivers that are associated with a driving fleet (paragraph [0074] and FIG. 5, Receive driver input events-501); determining, based on the driver information, risk information for each of the one or more drivers (paragraph [0074] and FIG. 5, Determine severity of driver input events-502, Past events with severity? - 503, Retrieve past events-505, and Determine aggregate severity-506); causing a device to present aggregate risk information associated with a first selection of one or more drivers (paragraphs [0078-0081] and FIG. 7, event definition user interface-700, venue name field-701, address field-702, warning level-703, no engagement level-704, drop down list-705, point value text field-706, Add button-707, event type list-708, and Delete button-709); after receiving an indication to add or remove one or more drivers from the first selection of one or more drivers (paragraphs [0075-0076] and FIG. 5, Remedial action required? - 504, and Take action-508); and causing the device to present aggregate risk information associated with an updated selection of one or more drivers (paragraphs [0096-0100] and FIG. 9, event manager-102, agency model driver input data-810, agency model comfort rating data-811, agency schema-812, fleet owner driver input data-920, fleet owner comfort rating data-921, and fleet owner schema-922). Regarding claims 2, 9 and 16, Pinkus further discloses: receiving driver information from one or more shared mobility servers and one or more driver/vehicle information servers (paragraphs [0030] and [0101]). Regarding claims 3, 10 and 17, Pinkus further discloses: receiving driver information that specifies, for each of the one or more drivers, a driver ID associated with the driver, a date the driver was added to the driving fleet, and information indicative of driver risk (paragraphs [0065] and [0073]; and FIG. 2C, sensor manager-101, event manager-102, for-hire vehicle (FHV) meter-105, and status indicator-112). Regarding claims 4, 11 and 18, Pinkus further discloses: wherein the driver information indicative of driver risk comprises one or more: a number of accidents a driver has had, a number of tickets a driver has had, and an indication of whether the driver has had a license suspended or canceled (paragraphs [0023-0029] and [0081]). Regarding claims 5, 12 and 19, Pinkus further discloses: causing the device to present information indicative of an aggregated risk of: bodily injury, collision, comprehensive damage, and property damage associated with the first selection of one or more drivers (paragraphs [0023-0029] and [0081]). Regarding claim 8, Pinkus further discloses: A non-transitory computer readable medium having stored thereon instruction code that, when executed by at least one processor of a computing platform, causes the computing platform to perform operations comprising: (paragraphs [0066-0068] and FIG. 3, regulatory agency computer system-200, CPU-210, and data store-213); receiving, from one or more data sources, driver information associated with one or more drivers that are associated with a driving fleet (paragraph [0074] and FIG. 5, Receive driver input events-501); determining, based on the driver information, risk information for each of the one or more drivers (paragraph [0074] and FIG. 5, Determine severity of driver input events-502, Past events with severity? - 503, Retrieve past events-505, and Determine aggregate severity-506); causing a device to present aggregate risk information associated with a first selection of one or more drivers (paragraphs [0078-0081] and FIG. 7, event definition user interface-700, venue name field-701, address field-702, warning level-703, no engagement level-704, drop down list-705, point value text field-706, Add button-707, event type list-708, and Delete button-709); after receiving an indication to add or remove one or more drivers from the first selection of one or more drivers (paragraphs [0075-0076] and FIG. 5, Remedial action required? - 504, and Take action-508); and causing the device to present aggregate risk information associated with an updated selection of one or more drivers (paragraphs [0096-0100] and FIG. 9, event manager-102, agency model driver input data-810, agency model comfort rating data-811, agency schema-812, fleet owner driver input data-920, fleet owner comfort rating data-921, and fleet owner schema-922). Regarding claim 15, Pinkus further discloses: receiving, from one or more data sources, driver information associated with one or more drivers that are associated with a driving fleet (paragraph [0074] and FIG. 5, Receive driver input events-501); determining, based on the driver information, risk information for each of the one or more drivers (paragraph [0074] and FIG. 5, Determine severity of driver input events-502, Past events with severity? - 503, Retrieve past events-505, and Determine aggregate severity-506); causing a device to present aggregate risk information associated with a first selection of one or more drivers (paragraphs [0078-0081] and FIG. 7, event definition user interface-700, venue name field-701, address field-702, warning level-703, no engagement level-704, drop down list-705, point value text field-706, Add button-707, event type list-708, and Delete button-709); after receiving an indication to add or remove one or more drivers from the first selection of one or more drivers (paragraphs [0075-0076] and FIG. 5, Remedial action required? - 504, and Take action-508); and causing the device to present aggregate risk information associated with an updated selection of one or more drivers (paragraphs [0096-0100] and FIG. 9, event manager-102, agency model driver input data-810, agency model comfort rating data-811, agency schema-812, fleet owner driver input data-920, fleet owner comfort rating data-921, and fleet owner schema-922). Claims 6-7, 13-14 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Pinkus, as applied to claims 1, 8 and 15 above, and further in view of Carver et al. (U.S. Patent Number 10,049,408, hereinafter Carver). Regarding claims 6, 13 and 20, Pinkus does not disclose a machine learning model. However, Carver discloses a system for assessing asynchronous authenticated data sources for use in driver risk management, including the following features: inputting driver information associated with a particular driver into a plurality of trained machine learning models respectively trained to output respective indications of a risk of bodily injury, a risk of collision, a risk of comprehensive damage, and a risk of property damage associated with the driver (col. 5, lines 5-36; col. 16, line 3 - col. 18, line 25; and FIG. 1, results database VIN & driver verification-101, scoring database-107, driver safety index (DSI) - 108, vehicle risk index (VRI) & mileage- 109, collision level index (CLI) - 110, and risk manager-150). Carver teaches dynamically mining variables to compute driver safety, vehicle risk, and collision level using a machine learning algorithm to detect changes in driver behavior (col. 5, lines 24-32). It would have been obvious for a person of ordinary skill in the art at the time of the effective filing date of the claimed invention to incorporate the machine learning algorithm of Carver into the system for computing the safety and comfort ratings of drivers and for-hire vehicles (FHVs) of Pinkus. A person of ordinary skill would have been motivated to do so, with a reasonable expectation of success, for the purpose of efficiently determining driver risk. A person of ordinary skill would be familiar with the use of machine learning models to analyze large data inputs. Regarding claims 7 and 14, Pinkus does not disclose a weighted average of risk factors. However, Carver further discloses: determining a weighted average of the respective indications of the risk of bodily, the risk of collision, the risk of comprehensive damage, and the risk of property damage associated with the driver (col. 9, line 56 - col. 10, line 23); and causing the device to present information indicative of the weighted average to the device (col. 7, lines 25-47; col. 8, lines 13-51; FIG. 7, device-700, communication connection(s) - 712, and output device(s) - 716; and FIG. 8, system-800, client device-810, server-830, display-850, and computer system-860). Carver teaches driver safety, vehicle risk, and collision level indices should be summed for a common group of trips, or period of time using a time weighted average to produce a fleet level score stored, along with individual scores, by VIN number in a results database in order to bias the results to the most recent events, or time series data because it has been shown that recent events are much more predictive of risk factors than historical patterns when the pattern sequence is changing (col. 9, line 56 - col. 10, line 23). It would have been obvious for a person of ordinary skill in the art at the time of the effective filing date of the claimed invention to incorporate the time weighted average of Carver into the system for computing the safety and comfort ratings of drivers and for-hire vehicles (FHVs) of Pinkus. A person of ordinary skill would have been motivated to do so, with a reasonable expectation of success, for the purpose of efficiently determining driver risk. A person of ordinary skill would be familiar with the use of weighted averages to analyze risk factors based on changing pattern sequences. Conclusion The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Brinkmann et al. (U.S. Patent Number 9,081,650) discloses a driving analysis server which calculates a driver score for a first vehicle based on a comparison of driving behavior in the first vehicle to corresponding driving behaviors in other vehicles (Abstract). Fish et al. (US-2017/0186324-A1) discloses a system that provides a safety rating for a driver or a vehicle to a rider of the vehicle (Abstract). A GUI displays a picture of the driver, name of the driver, and a driver safety rating (paragraph [0065]). Volos et al. (US-2019/0100216-A1) discloses a risk assessment module which calculates a risk assessment score for a driver based on an anomaly score, where the risk assessment score is indicative of a risk level of a first driver relative to other drivers (Abstract). Campos et al. (US-2022/0253021-A1) discloses systems for detecting a driving action that mitigates risk (Abstract). Any inquiry concerning this communication or earlier communications from the examiner should be directed to TAMARA L WEBER whose telephone number is (303)297-4249. The examiner can normally be reached 8:30-5:00 MTN. 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, Faris Almatrahi can be reached at 3134464821. 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. /TAMARA L WEBER/ Examiner, Art Unit 3667
Read full office action

Prosecution Timeline

Sep 16, 2024
Application Filed
Feb 26, 2026
Non-Final Rejection — §101, §103, §112 (current)

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

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Prosecution Projections

1-2
Expected OA Rounds
87%
Grant Probability
99%
With Interview (+12.0%)
2y 3m
Median Time to Grant
Low
PTA Risk
Based on 609 resolved cases by this examiner. Grant probability derived from career allow rate.

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