Prosecution Insights
Last updated: April 19, 2026
Application No. 18/949,078

SYSTEMS AND METHODS FOR PROACTIVE ELECTRONIC VEHICLE CHARGING

Non-Final OA §102§103
Filed
Nov 15, 2024
Examiner
GORDON, MATHEW FRANKLIN
Art Unit
3665
Tech Center
3600 — Transportation & Electronic Commerce
Assignee
Allstate Insurance Company
OA Round
1 (Non-Final)
72%
Grant Probability
Favorable
1-2
OA Rounds
2y 3m
To Grant
85%
With Interview

Examiner Intelligence

Grants 72% — above average
72%
Career Allow Rate
199 granted / 278 resolved
+19.6% vs TC avg
Moderate +13% lift
Without
With
+13.3%
Interview Lift
resolved cases with interview
Typical timeline
2y 3m
Avg Prosecution
14 currently pending
Career history
292
Total Applications
across all art units

Statute-Specific Performance

§101
3.2%
-36.8% vs TC avg
§103
57.1%
+17.1% vs TC avg
§102
25.0%
-15.0% vs TC avg
§112
14.1%
-25.9% vs TC avg
Black line = Tech Center average estimate • Based on career data from 278 resolved cases

Office Action

§102 §103
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 Status This action is in response to the application filed on 11/15/2024. Claims 1-20 are pending and examined below. Claim Rejections - 35 USC § 102 The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action: A person shall be entitled to a patent unless – (a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale or otherwise available to the public before the effective filing date of the claimed invention. Claims 1-5, 7-12, and 14-19 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by US 20190205842 A1 (“Starns”). Regarding claim 1, Starns teaches receiving, at one or more processors, trip data of an EV, the trip data including ;predicting, at the one or more processors, that the EV will have a power level below a threshold power level in a location an area along a route of the EV based on the trip data (see at least [0027]); identifying, at the one or more processors, a mobile EV charging station of a plurality of mobile EV charging stations based on one or more factors (see at least [0031]) generating, at the one or more processors, one or more driving instructions for the mobile EV charging station; and transmitting, via a communication network, the one or more driving instructions to at least one of a mobile computing device or the mobile EV charging station to cause deployment of the mobile EV charging station to the location (see at least [0048]). Regarding claim 2, Starns teaches the trip data includes at least one of a remaining range of the EV or the route (see at least [0031]). Regarding claim 3, Starns teaches the one or more factors include at least one of EV charging station data, a distance between each of the plurality of mobile EV charging stations and the location, how much charge remains in each of the plurality of mobile EV charging stations, or one or more environmental factors (see at least [0031]) Regarding claim 4, Starns teaches the one or more environmental factors include traffic between each of the plurality of mobile EV charging stations and the location (see at least[0048]). Regarding claim 5, Starns teaches the one or more driving instructions include at least one of a GPS navigation instruction or an automated driving instruction (see at least [0031]). Regarding claim 7, Starns teaches determining the location using at least one of a distance between each of the plurality of mobile EV charging stations and the location, how much charge remains in each of the plurality of mobile EV charging stations, or traffic between each of the plurality of mobile EV charging stations and the location (see at least [0048]). Regarding claim 8, Starns teaches at least one processor; and a memory storing instructions, which when executed by the at least one processor, cause the system to: receive trip data of an EV ;predict that the EV will have a power level below a threshold power level in a location along a route of the EV based on the trip data (see at least [0027]); identify a mobile EV charging station of a plurality of mobile EV charging stations based on one or more factors; generate one or more driving instructions for the mobile EV charging station (see at least [0031]); and transmit the one or more driving instructions to at least one of a mobile computing device or the mobile EV charging station to cause the mobile EV charging station to move to the location (see at least [0045]). Regarding claim 9, Starns teaches the trip data includes at least one of a range of the EV or the route (see at least [0031]). Regarding claim 10, Starns teaches the one or more factors include at least one of EV charging station data, a distance between each of the plurality of mobile EV charging stations and the location, how much charge remains in each of the plurality of mobile EV charging stations, or one or more environmental factors (see at least [0031]). Regarding claim 11, Starns teaches the one or more environmental factors include traffic between each of the plurality of mobile EV charging stations and the location (see at least [0048]). Regarding claim 12, Starns teaches the one or more driving instructions include at least one of a GPS navigation instruction or an automated driving instruction (see at least [0031]). Regarding claim 14, Starns teaches determine the location using at least one of a distance between each of the plurality of mobile EV charging stations and the location, how much charge remains in each of the plurality of mobile EV charging stations, or traffic between each of the plurality of mobile EV charging stations and the location (see at least [0048]) Regarding claim 15, Starns teaches the computer process comprising: receiving trip data of an Depredating that the EV will have a power level below a threshold power level in a location along a route of the EV based on the trip data (see at least [0027]); identifying a mobile EV charging station of a plurality of mobile EV charging stations based on one or more factors (see at least [0031]); and generating one or more driving instructions for the mobile EV charging station to direct the mobile EV charging station to move to the location (see at least [0048]). Regarding claim 16, Starns teaches the trip data includes at least one of a range of the EV or the route (see at least [0031]) Regarding claim 17, Starns teaches the one or more factors include at least one of EV charging station data, a distance between each of the plurality of mobile EV charging stations and the location, how much charge remains in each of the plurality of mobile EV charging stations, or one or more environmental factors (see at least[0031]) Regarding claim 18, Starns teaches the one or more environmental factors include traffic between each of the plurality of mobile EV charging stations and the location (see at least [0048]). Regarding claim 19, Starns teaches at least one of the plurality of mobile EV charging stations is an autonomous vehicle (see at least 0031]). 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 6, 13, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over US 20190205842 A1 (“Starns”) in view of US 20240017628 A1 (“Woods”). Regarding claims 6, 13, and 20 Starns is not explicit on at least one of the plurality of mobile EV charging stations is an autonomous vehicle, however, Woods discloses at least one of the plurality of mobile EV charging stations is an autonomous vehicle (see at least [0044]). One of ordinary skill in the art would have been motivated to combine the system disclosed by Starns with the system disclosed by Woods because there are not as many charging stations (e.g., quick-charge or fast-charge charging stations) currently available as desired, and a range such a vehicle can travel (which sometimes may not be sufficient to go from one location to another) may drop even further when, e.g., a trailer is attached to the vehicle resulting in a heavier load (Woods, [0003]) Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to MATHEW FRANKLIN GORDON whose telephone number is (408)918-7612. The examiner can normally be reached Monday - Friday, 7:00 - 5:00 PST. 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, Hunter Lonsberry can be reached at (571) 272 - 7298. 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. /MATHEW FRANKLIN GORDON/Primary Examiner, Art Unit 3665
Read full office action

Prosecution Timeline

Nov 15, 2024
Application Filed
Jan 24, 2026
Non-Final Rejection — §102, §103 (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
72%
Grant Probability
85%
With Interview (+13.3%)
2y 3m
Median Time to Grant
Low
PTA Risk
Based on 278 resolved cases by this examiner. Grant probability derived from career allow rate.

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