# US 12,183,197 B2 · Free lock detection of a micromobility transit vehicle systems and methods > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 12,183,197 B2 - Document ID: US12183197B2 - Status: Granted - Kind: B2 - Application number: 18/536,045 - Filed: 2023-12-11 - Published: 2024-04-11 - Granted: 2024-12-31 - Earliest claimed: 2020-03-31 - Assignees: Lyft, Inc. - Applicants: Lyft, Inc. - Inventors: Garrett Korda Drayna; Gary Shambat; Jacqueline Benesch Tandler; Griffin Samuel Valentine Thomson; Jens Paul Windau - Web page: https://patentgrep.com/patent/US12183197B2 ## CPC - G08G 1/123: indicating the position of vehicles, e.g. scheduled vehicles; {Managing passenger vehicles circulating according to a fixed timetable, e.g. buses, trains, trams}(transmission of navigation instructions to vehicles G08G1/0968) - G08G 1/205: {Indicating the location of the monitored vehicles as destination, e.g. accidents, stolen, rental} - G07C 5/008: {communicating information to a remotely located station (transmission systems for measured values G08C)} - G07C 5/085: {using electronic data carriers} - G08G: TRAFFIC CONTROL SYSTEMS (guiding railway traffic, ensuring the safety of railway traffic B61L; arrangement of road signs or traffic signals E01F9/00; radar or analogous systems, sonar systems, lidar systems specially adapted for traffic control G01S13/91, G01S15/88, G01S17/88; {radar or analogous systems, sonar systems, lidar systems specially adapted for anti-collision purposes G01S13/93, G01S15/93, G01S17/93}) - G07C: TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE ## Abstract Techniques are disclosed for systems and methods associated with free lock detection of a micromobility vehicle. Data from one or more sensors of the micromobility vehicle may be received and compared to a threshold stored or determined for the micromobility vehicle. Based on the comparing, an indication of free locking the micromobility vehicle may be determined and one or more notifications of the indication may be generated and sent for display on a mobile device. A parking condition of the micromobility vehicle may also be determined, such as utilizing image data of the micromobility vehicle. The image data may be analyzed to determine whether the micromobility vehicle is parked within a designated parking area distinguished through distinct coloring, patterns, signs, placards, markers, or images. ## Claims ### Claim 1 A method for identifying a parking location of a micromobility transit vehicle, comprising: detecting a completion of a ride reservation of a micromobility transit vehicle; and in response to detecting the completion of the ride reservation: receiving sensor data from one or more sensors associated with the micromobility transit vehicle; determining, based on the sensor data, whether a location of the micromobility transit vehicle corresponds to at least one of a plurality of detectable virtual stations; and identifying a parking location of the micromobility transit vehicle based on whether the location of the micromobility transit vehicle corresponds to the at least one of the plurality of detectable virtual stations. ### Claim 2 (depends on 1) The method of claim 1, wherein the plurality of detectable virtual stations comprises a first detectable virtual location, a second detectable virtual location, a third detectable virtual location, and a fourth detectable virtual location. ### Claim 3 (depends on 2) The method of claim 2, wherein: the first detectable virtual location comprises a parking location including a distinct color, a distinct texture, or a distinct pattern with respect to a surface on which the micromobility transit vehicle is parked; the second detectable virtual location comprises a parking location including an outline having a distinct color, a distinct texture, or a distinct pattern; the third detectable virtual location comprises a parking location including a predetermined placard; and the fourth detectable virtual location comprises a parking location including a sign having one or more predetermined indicia. ### Claim 4 (depends on 1) The method of claim 1, further comprising determining, based on the sensor data, whether the location of the micromobility transit vehicle corresponds to the at least one of the plurality of detectable virtual stations utilizing an object detection algorithm. ### Claim 5 (depends on 1) The method of claim 1, wherein determining whether the location of the micromobility transit vehicle corresponds to the at least one of the plurality of detectable virtual stations comprises determining, based on the sensor data, whether the location of the micromobility transit vehicle is: 1) completely within the at least one of the plurality of detectable virtual stations, 2) partially within the at least one of the plurality of detectable virtual stations, or 3) outside of the at least one of the plurality of detectable virtual stations. ### Claim 6 (depends on 1) The method of claim 1, further comprising: prior to receiving the sensor data from the one or more sensors associated with the micromobility transit vehicle, requesting an image of the micromobility transit vehicle or of an area proximate to the micromobility transit vehicle. ### Claim 7 (depends on 1) The method of claim 1, wherein identifying the location of the micromobility transit vehicle comprises identifying the location of the micromobility transit vehicle utilizing one or more classification models. ### Claim 8 A system for identifying a parking location of a micromobility transit vehicle, comprising: one or more non-transitory computer-readable storage media including instructions; and one or more processors communicatively coupled to the one or more sensors and the one or more non-transitory computer-readable storage media, the one or more processors configured to execute the instructions to: detect a completion of a ride reservation of a micromobility transit vehicle; and in response to detecting the completion of the ride reservation: receive sensor data from the one or more sensors associated with the micromobility transit vehicle; determine, based on the sensor data, whether a location of the micromobility transit vehicle corresponds to at least one of a plurality of detectable virtual stations; and identify a parking location of the micromobility transit vehicle based on whether the location of the micromobility transit vehicle corresponds to the at least one of the plurality of detectable virtual stations. ### Claim 9 (depends on 8) The system of claim 8, wherein the plurality of detectable virtual stations comprises a first detectable virtual location, a second detectable virtual location, a third detectable virtual location, and a fourth detectable virtual location. ### Claim 10 (depends on 9) The system of claim 9, wherein: the first detectable virtual location comprises a parking location including a distinct color, a distinct texture, or a distinct pattern with respect to a surface on which the micromobility transit vehicle is parked; the second detectable virtual location comprises a parking location including an outline having a distinct color, a distinct texture, or a distinct pattern; the third detectable virtual location comprises a parking location including a predetermined placard; and the fourth detectable virtual location comprises a parking location including a sign having one or more predetermined indicia. ### Claim 11 (depends on 8) The system of claim 8, wherein the instructions further comprise instructions to determine, based on the sensor data, whether the location of the micromobility transit vehicle corresponds to the at least one of the plurality of detectable virtual stations utilizing an object detection algorithm. ### Claim 12 (depends on 8) The system of claim 8, wherein the instructions to determine whether the location of the micromobility transit vehicle corresponds to the at least one of the plurality of detectable virtual stations further comprise instructions to determine, based on the sensor data, whether the location of the micromobility transit vehicle is: 1) completely within the at least one of the plurality of detectable virtual stations, 2) partially within the at least one of the plurality of detectable virtual stations, or 3) outside of the at least one of the plurality of detectable virtual stations. ### Claim 13 (depends on 8) The system of claim 8, wherein the instructions further comprise instructions to: prior to receiving the sensor data from the one or more sensors associated with the micromobility transit vehicle, request an image of the micromobility transit vehicle or of an area proximate to the micromobility transit vehicle. ### Claim 14 (depends on 8) The system of claim 8, wherein the instructions to identify the location of the micromobility transit vehicle further comprise instructions to identify the location of the micromobility transit vehicle utilizing one or more classification models. ### Claim 15 A non-transitory computer-readable medium comprising instructions that, when executed by one or more processors of a computing system, cause the computing system to: detect a completion of a ride reservation of a micromobility transit vehicle; and in response to detecting the completion of the ride reservation: receive sensor data from one or more sensors associated with the micromobility transit vehicle; determine, based on the sensor data, whether a location of the micromobility transit vehicle corresponds to at least one of a plurality of detectable virtual stations; and identify a parking location of the micromobility transit vehicle based on whether the location of the micromobility transit vehicle corresponds to the at least one of the plurality of detectable virtual stations. ### Claim 16 (depends on 15) The non-transitory computer-readable medium of claim 15, wherein the plurality of detectable virtual stations comprises a first detectable virtual location, a second detectable virtual location, a third detectable virtual location, and a fourth detectable virtual location. ### Claim 17 (depends on 16) The non-transitory computer-readable medium of claim 16, wherein: the first detectable virtual location comprises a parking location including a distinct color, a distinct texture, or a distinct pattern with respect to a surface on which the micromobility transit vehicle is parked; the second detectable virtual location comprises a parking location including an outline having a distinct color, a distinct texture, or a distinct pattern; the third detectable virtual location comprises a parking location including a predetermined placard; and the fourth detectable virtual location comprises a parking location including a sign having one or more predetermined indicia. ### Claim 18 (depends on 15) The non-transitory computer-readable medium of claim 15, wherein the instructions further comprise instructions to determine, based on the sensor data, whether the location of the micromobility transit vehicle corresponds to the at least one of the plurality of detectable virtual stations utilizing an object detection algorithm. ### Claim 19 (depends on 15) The non-transitory computer-readable medium of claim 15, wherein the instructions to determine whether the location of the micromobility transit vehicle corresponds to the at least one of the plurality of detectable virtual stations further comprise instructions to determine, based on the sensor data, whether the location of the micromobility transit vehicle is: 1) completely within the at least one of the plurality of detectable virtual stations, 2) partially within the at least one of the plurality of detectable virtual stations, or 3) outside of the at least one of the plurality of detectable virtual stations. ### Claim 20 (depends on 15) The non-transitory computer-readable medium of claim 15, wherein the instructions to identify the location of the micromobility transit vehicle further comprise instructions to identify the location of the micromobility transit vehicle utilizing one or more classification models.