Patent ID: 11972378
Assignee: FORD GLOBAL TECHNOLOGIES, LLC
Field: Control (Instruments)
Classification: CPC G | IPC G

Claim 0:
1. A system for use of machine learning for dispatch of mobile aid and service, comprising:
a dispatch database maintaining, for a plurality of vehicles available for dispatch, vehicle data and constraints data; and
a processor programmed to execute a dispatch server to perform operations including to:
receive a dispatch request requesting a vehicle to arrive at a request location,
utilize a machine-learning model to identify a subset of the plurality of vehicles to respond to the dispatch request, the subset including vehicles indicated, by the machine-learning model, as being most probable choices to handle the dispatch request, the machine-learning model utilizing the vehicle data and the constraints data as inputs to determine the subset of the plurality of vehicles,
inform the subset of the plurality of vehicles of the dispatch request,
receive a result indicative of which one of the subset of the plurality of vehicles actually performed the dispatch request, and
update training of the machine-learning model using the vehicle data, the constraints data, and the result to improve the machine-learning model in learning to identify the subset one or more of the plurality of vehicles that are the most probable choices to handle the dispatch request, including to
receive historical constraints data and historical vehicle data from the plurality of vehicles;
receive historical dispatch requests during a period of time for which the historical vehicle data and the historical constraints data is available; and
train the machine-learning model in dispatch of the plurality of vehicles using the historical vehicle data, the historical constraints data, and the historical dispatch requests provided as the inputs to the machine-learning model, and an indication of which of the plurality of vehicles was dispatched for the historical dispatch requests as ground truth for intended output of the machine-learning model,
set aside a portion of the historical vehicle data and the historical constraints data from the training,
use the portion to validate the machine-learning model,
perform additional training of the machine-learning model using the historical vehicle data and the historical constraints data responsive to the machine-learning model not meeting with the ground truth for at least a minimum threshold, and
apply the machine-learning model for use by the dispatch server in handling additional dispatch requests responsive to the machine-learning model meeting with the ground truth for at least the minimum threshold.