| CPC G06Q 50/40 (2024.01) [G01C 21/3484 (2013.01); G06F 3/0482 (2013.01); G06F 3/04842 (2013.01); G06F 3/0485 (2013.01); G06N 20/00 (2019.01); G06Q 30/0284 (2013.01); G06Q 30/06 (2013.01); G06Q 30/0621 (2013.01); H04L 67/52 (2022.05); H04L 67/60 (2022.05)] | 20 Claims |

|
1. A method comprising:
receiving a target location from a computing device, the target location comprising primary map coordinates on a geographical map;
analyzing historical user data associated with the target location using a machine learning model trained to perform operations comprising:
determining a first access point associated with the target location the first access point comprising first refined map coordinates, the first refined map coordinates being different from the primary map coordinates, and
determining a second access point associated with the target location, the second access point comprising second refined map coordinates, the second refined map coordinates being different from the primary map coordinates and the first refined map coordinates;
determining that a size of a set of transportation data associated with the second access point is below a threshold size;
in response to the determination, causing presentation of the first access point as a first selectable user interface element on a graphical user interface of the computing device;
receiving a first selection of the first selectable user interface element from the computing device; and
in response to receiving the first selection, initiating a trip request to the first access point.
|