Office Action Predictor
Last updated: April 15, 2026
Application No. 18/177,984

SYSTEMS AND METHODS FOR CONTROLLING VEHICLE MOVEMENT IN A PARKING LOT

Non-Final OA §103
Filed
Mar 03, 2023
Examiner
FUREMAN, JARED
Art Unit
2859
Tech Center
2800 — Semiconductors & Electrical Systems
Assignee
Ford Global Technologies, LLC
OA Round
1 (Non-Final)
36%
Grant Probability
At Risk
1-2
OA Rounds
3y 2m
To Grant
45%
With Interview

Examiner Intelligence

Grants only 36% of cases
36%
Career Allow Rate
34 granted / 94 resolved
-31.8% vs TC avg
Moderate +8% lift
Without
With
+8.5%
Interview Lift
resolved cases with interview
Typical timeline
3y 2m
Avg Prosecution
27 currently pending
Career history
121
Total Applications
across all art units

Statute-Specific Performance

§101
0.3%
-39.7% vs TC avg
§103
52.1%
+12.1% vs TC avg
§102
29.9%
-10.1% vs TC avg
§112
14.7%
-25.3% vs TC avg
Black line = Tech Center average estimate • Based on career data from 94 resolved cases

Office Action

§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 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. Claim(s) 1-6, 10-14 and 16-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Starns (US 2019/0205842 A1) in view of Gupta et al (US 2012/0112929 A1). Regarding claim 1, Starns teaches: A method for managing a plurality of vehicles (autonomous vehicles 140) of a parking lot (200), wherein the parking lot includes, an exit lane (the area proximate exits 106), an entry lane (the area proximate entry 104), and one or more charging lanes (the areas between entry 104 and exit 106, where vehicles 140 are parked, as shown in Fig. 2), the method comprising: obtaining parking lot data associated with the parking lot (see step 510, Fig. 5 and para. 0049), wherein the parking lot data indicates an availability of a plurality of parking spaces of the parking lot (available charging stations and, thus, associated parking spaces, see para. 0020, 0034 & 0036); obtaining vehicle data associated with the plurality of vehicles (see step 520, Fig. 5 and para. 0050), wherein the vehicle data includes one or more electrical charging characteristics of each of the plurality of vehicles (for example, battery size, para. 0020), or a combination thereof; and controlling a movement of the plurality of vehicles via the exit lane, the entry lane, and the one or more charging lanes based on the vehicle data (see para. 0020 & 0021). Starns teaches that the vehicles include different makes, models and types (see para. 0016). However, Starns does not specifically teach: wherein the vehicle data includes one or more physical characteristics of each of the plurality of vehicles; dynamically defining one or more parking characteristics of the parking lot based on the vehicle data and the parking lot data; controlling a movement of the plurality of vehicles via the one or more parking characteristics of the parking lot. Gupta et al teaches a method for managing a plurality of vehicles (24, Fig. 2) of a parking lot (10), comprising: obtaining vehicle data associated with the plurality of vehicles (see step 42, Fig. 4), wherein the vehicle data includes one or more physical characteristics of each of the plurality of vehicles (dimensional information, also see car length and car breadth in Fig. 5); dynamically defining one or more parking characteristics of the parking lot based on the vehicle data and the parking lot data (the parking space is drawn when cars are parking, see Fig. 2 and para. 0034); controlling a movement of the plurality of vehicles via the one or more parking characteristics of the parking lot (the vehicle can be guided to the parking space, see para. 0043; step 45, Fig. 4 and para. 0049). In view of Gupta et al’s teachings, it would have been obvious to one of ordinary skill in the art prior to the effective filing date, to include with the system and method of Starns, wherein the vehicle data includes one or more physical characteristics of each of the plurality of vehicles; dynamically defining one or more parking characteristics of the parking lot based on the vehicle data and the parking lot data; controlling a movement of the plurality of vehicles via the one or more parking characteristics of the parking lot, since this would allow for maximizing the use of available space based on vehicle sizes (see the abstract and para. 0012, of Gupta et al). Regarding claims 12 and 18, Starns teaches: A system and method for managing a plurality of vehicles (autonomous vehicles 140) of a parking lot (200), wherein the parking lot includes, an exit lane(the area proximate exits 106), an entry lane (the area proximate entry 104), and one or more charging lanes (the areas between entry 104 and exit 106, where vehicles 140 are parked, as shown in Fig. 2), the system comprising: one or more processors (see abstract and 702, Fig. 7 and para. 0067-0069); and one or more nontransitory computer-readable mediums (see abstract, 704 & 706, Fig. 7 and para. 0067-0069) comprising instructions that are executable by the one or more processors, wherein the instructions comprise: obtaining parking lot data associated with the parking lot (see step 510, Fig. 5 and para. 0049), wherein the parking lot data indicates an availability of a plurality of parking spaces of the parking lot (available charging stations and, thus, associated parking spaces, see para. 0020, 0034 & 0036); obtaining vehicle data associated with the plurality of vehicles (see step 520, Fig. 5 and para. 0050), wherein the vehicle data includes one or more electrical charging characteristics of each of the plurality of vehicles (for example, battery size, para. 0020), and the one or more electrical charging characteristics of each of the plurality of vehicles comprises an amount of electrical energy of each of the plurality of vehicles (for example, battery size, para. 0020), a charging time of each of the plurality of vehicles (charge time, see para. 0019 & 0021), or a combination thereof; and controlling a movement of the plurality of vehicles via the exit lane, the entry lane, and the one or more charging lanes based on the vehicle (see para. 0020 & 0021). Starns teaches that the vehicles include different makes, models and types (see para. 0016). However, Starns does not specifically teach: wherein the vehicle data includes one or more physical characteristics of each of the plurality of vehicles, wherein: the one or more physical characteristics of each of the plurality of vehicles comprises a vehicle type of each of the plurality of vehicles, a vehicle width of each of the plurality of vehicles, a vehicle length of each of the plurality of vehicles, or a combination thereof; dynamically defining one or more parking characteristics of the parking lot based on the vehicle data and the parking lot data, wherein the one or more parking characteristics of the parking lot comprises one or more parking space widths of the plurality of parking spaces, one or more parking space lengths of the plurality of parking spaces, a number of the plurality of parking spaces, an arrangement of the plurality of parking spaces, or a combination thereof; controlling a movement of the plurality of vehicles via the one or more parking characteristics of the parking lot. Gupta et al teaches a method for managing a plurality of vehicles (24, Fig. 2) of a parking lot (10), comprising: obtaining vehicle data associated with the plurality of vehicles (see step 42, Fig. 4), wherein the vehicle data includes one or more physical characteristics of each of the plurality of vehicles (dimensional information, also see car length and car breadth in Fig. 5), wherein: the one or more physical characteristics of each of the plurality of vehicles comprises a vehicle type of each of the plurality of vehicles (for example, very large cars, large cars, medium cars, see Figs. 2 & 5), a vehicle width of each of the plurality of vehicles (see car breadth, Fig. 5), a vehicle length of each of the plurality of vehicles (see car length, Fig. 5), or a combination thereof (dimensional information, see step 42 in Fig. 4, also see car length and car breadth in Fig. 5); dynamically defining one or more parking characteristics of the parking lot based on the vehicle data and the parking lot data (the parking space is drawn when cars are parking, see Fig. 2 and para. 0034), wherein the one or more parking characteristics of the parking lot comprises one or more parking space (22) widths of the plurality of parking spaces, one or more parking space lengths of the plurality of parking spaces, a number of the plurality of parking spaces, an arrangement of the plurality of parking spaces, or a combination thereof (see the widths, lengths and number of parking spaces 22 in Fig. 2); controlling a movement of the plurality of vehicles via the one or more parking characteristics of the parking lot (the vehicle can be guided to the parking space, see para. 0043; step 45, Fig. 4 and para. 0049). In view of Gupta et al’s teachings, it would have been obvious to one of ordinary skill in the art prior to the effective filing date, to include with the system and method of Starns, wherein the vehicle data includes one or more physical characteristics of each of the plurality of vehicles, wherein: the one or more physical characteristics of each of the plurality of vehicles comprises a vehicle type of each of the plurality of vehicles, a vehicle width of each of the plurality of vehicles, a vehicle length of each of the plurality of vehicles, or a combination thereof; dynamically defining one or more parking characteristics of the parking lot based on the vehicle data and the parking lot data, wherein the one or more parking characteristics of the parking lot comprises one or more parking space widths of the plurality of parking spaces, one or more parking space lengths of the plurality of parking spaces, a number of the plurality of parking spaces, an arrangement of the plurality of parking spaces, or a combination thereof; controlling a movement of the plurality of vehicles via the one or more parking characteristics of the parking lot, since this would allow for maximizing the use of available space based on vehicle sizes (see the abstract and para. 0012, of Gupta et al). Regarding claim 2, Starns as modified by Gupta et al teaches: The method of Claim 1, wherein the one or more physical characteristics of each of the plurality of vehicles comprises a vehicle type of each of the plurality of vehicles (for example, very large cars, large cars, medium cars, see Figs. 2 & 5 of Gupta et al), a vehicle width of each of the plurality of vehicles (see car breadth, Fig. 5), a vehicle length of each of the plurality of vehicles (see car length, Fig. 5), or a combination thereof. Regarding claim 3, Starns as modified by Gupta et al teaches: The method of Claim 1, wherein the one or more electrical charging characteristics of each of the plurality of vehicles comprises an amount of electrical energy of each of the plurality of vehicles (see battery size and charge level, paras. 0020-0021 of Starns), a charging time of each of the plurality of vehicles (charge time, see para. 0019 & 0021), or a combination thereof. Regarding claim 4, Starns as modified by Gupta et al teaches: The method of Claim 1, wherein the one or more parking characteristics of the parking lot comprises one or more parking space (22) widths of the plurality of parking spaces, one or more parking space lengths of the plurality of parking spaces, a number of the plurality of parking spaces, an arrangement of the plurality of parking spaces, or a combination thereof (see the widths, lengths and number of parking spaces 22 in Fig. 2 of Gupta et al). Regarding claims 5, 13 and 19, Starns as modified by Gupta et al teaches: The method and system of Claims 1, 12 and 18 further comprising: obtaining charging station data (availability) associated with a plurality of charging stations (202) disposed proximate to the one or more charging lanes (see Fig. 2A); determining, based on the one or more electrical charging characteristics of the vehicle data, whether a given vehicle from among the plurality of vehicles has a given amount of electrical energy that is less than a threshold amount of electrical energy (for example, a threshold used to determine if a vehicle 140 requires charging, see paras. 0027 & 0042); and in response to determining that the given amount of electrical energy is less than the threshold amount of electrical energy: identifying a given charging station (202) from among the plurality of charging stations based on the charging station data; and controlling a movement of the given vehicle to travel to the given charging station along a given path defined by the exit lane and the one or more charging lanes (see paras. 0017-0019, 0027 & 0042 of Starns). Regarding claims 6 and 14, Starns as modified by Gupta et al teaches: The method and system of Claims 5 and 14 further comprising, in response to determining that the given amount of electrical energy is less than the threshold amount of electrical energy: identifying one or more impeding vehicles (140) from among the plurality of vehicles based on a set of parking spaces (parking spaces adjacent chargers 202) from among the plurality of parking spaces, wherein the set of parking spaces are associated with the given vehicle; and controlling a movement of the one or more impeding vehicles along a taxi path defined by one of the exit lane and the entry lane (see paras. 0017-0019, 0021, 0043 and claim 5 of Starns). Regarding claims 10, 16 and 20, Starns as modified by Gupta et al teaches: The method and method of Claim 1, 12 and 18 further comprising: determining whether a given parking space from among the plurality of parking spaces is available based on the parking lot data (the parking space adjacent a particular charger 202); and controlling, in response to determining the given parking space is available, a movement of a given vehicle (140) from among the plurality of vehicles to travel to the given parking space along a given path defined by the entry lane, the one or more charging lanes, or a combination thereof (see paras. 0017-0019, 0027 & 0042 of Starns). Regarding claims 11 and 17, Starns as modified by Gupta et al teaches: The method of Claim 10 further comprising: identifying one or more impeding vehicles (a first and/or second vehicle 140) from among the plurality of vehicles based on a set of parking spaces from among the plurality of parking spaces (the parking space adjacent a particular charger 202), wherein the set of parking spaces are associated with the given vehicle; and controlling a movement of the one or more impeding vehicles and the given vehicle along a parking operation path defined by the exit lane, the entry lane, or a combination thereof (see paras. 0017-0019, 0021, 0043 and claim 5 of Starns). Claim(s) 7-9 and 15 is/are rejected under 35 U.S.C. 103 as being unpatentable over Starns (US 2019/0205842 A1) as modified by Gupta et al (US 2012/0112929 A1) as applied to claims 5 and 13 above, and further in view of Zhao et al (US 2014/0354229 A1). Regarding claims 7 and 15, the teachings of Starns as modified by Gupta et al as applied to the method and system of Claims 5 and 13 have been discussed above. Starns as modified by Gupta et al does not specifically teach: (regarding claims 7 and 15) in response to determining that the given amount of electrical energy is less than the threshold amount of electrical energy: obtaining robot data associated with a plurality of robots, wherein the robot data indicates a positional characteristic of each of the plurality of robots of each of the plurality of robots; identifying a given robot from among the plurality of robots based on the robot data; and controlling a movement of the given robot to travel along the one or more charging lanes to the given charging station; (regarding claim 8) wherein the one or more charging lanes include a gantry, and wherein controlling the movement of the given robot further comprises broadcasting a command to the given robot to travel along the gantry proximate to the given charging station; and (regarding claim 9) wherein the given robot is a mobile robot, and wherein controlling the movement of the mobile robot further comprises broadcasting a command to the mobile robot to autonomously travel along the one or more charging lanes proximate to the given charging station. Zhao et al teaches a system and method for managing a plurality of vehicles (12) of a parking lot (see parking spaces 14, of charging station 10, in Figs. 1 & 2), including: (regarding claims 7 and 15) in response to determining that the given amount of electrical energy is less than the threshold amount of electrical energy (for example, a vehicle 12 requires charging): obtaining robot data associated with a plurality of robots (charging apparatus 28 & 30, Figs. 1-4, 16 & 17), wherein the robot data indicates a positional characteristic of each of the plurality of robots of each of the plurality of robots (see para. 0036, 0043-0046 & 0065); identifying a given robot from among the plurality of robots based on the robot data; and controlling a movement of the given robot to travel along the one or more charging lanes to the given charging station (see paras. 0035, 0044-0046 & 0065); (regarding claim 8) wherein the one or more charging lanes include a gantry (overhead track 26, see para. 0029-0031 & 0065 and Figs. 2, 4 & 17), and wherein controlling the movement of the given robot (30) further comprises broadcasting a command to the given robot to travel along the gantry proximate to the given charging station (see para. 0029-0031, 0034, 0036 and 0065); and (regarding claim 9) wherein the given robot (28 and/or 30) is a mobile robot, and wherein controlling the movement of the mobile robot further comprises broadcasting a command to the mobile robot to autonomously travel along the one or more charging lanes proximate to the given charging station (see paras. 0035, 0044-0046 & 0065). In view of Zhao et al’s teachings, it would have been to one of ordinary skill in the art prior to the effective filing date, to include with the system and method of Starns as modified by Gupta et al, (regarding claims 7 and 15) in response to determining that the given amount of electrical energy is less than the threshold amount of electrical energy: obtaining robot data associated with a plurality of robots, wherein the robot data indicates a positional characteristic of each of the plurality of robots of each of the plurality of robots; identifying a given robot from among the plurality of robots based on the robot data; and controlling a movement of the given robot to travel along the one or more charging lanes to the given charging station; (regarding claim 8) wherein the one or more charging lanes include a gantry, and wherein controlling the movement of the given robot further comprises broadcasting a command to the given robot to travel along the gantry proximate to the given charging station; and (regarding claim 9) wherein the given robot is a mobile robot, and wherein controlling the movement of the mobile robot further comprises broadcasting a command to the mobile robot to autonomously travel along the one or more charging lanes proximate to the given charging station, since this would provide additional automation with minimal interaction from a user (see para. 0035 of Zhao et al), which would be desirable for use with the automated vehicles of Starns. Conclusion The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Please see the additional references cited on the attached PTO-892, which are directed to systems and method for managing parking and/or charging of vehicles. Any inquiry concerning this communication or earlier communications from the examiner should be directed to Jared Fureman whose telephone number is (571)272-2391. The examiner can normally be reached M-F 8:30 am - 5:00 pm. 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, Drew Dunn can be reached at 571-272-2312. 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. /JARED FUREMAN/Primary Examiner, Art Unit 2859
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Prosecution Timeline

Mar 03, 2023
Application Filed
Jan 24, 2026
Non-Final Rejection — §103
Mar 05, 2026
Interview Requested
Mar 12, 2026
Examiner Interview Summary
Apr 03, 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

1-2
Expected OA Rounds
36%
Grant Probability
45%
With Interview (+8.5%)
3y 2m
Median Time to Grant
Low
PTA Risk
Based on 94 resolved cases by this examiner. Grant probability derived from career allow rate.

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