Abstract: Methods and systems are disclosed for operating a fleet of vehicles having a central recharging location. In one example, the method comprises operating at least a first vehicle of the fleet and a second vehicle of the fleet in response to a completion rate being greater than a confidence threshold, where each of the first vehicle and the second vehicle only externally recharge at the central recharging location without external recharging on the respective route of each of the first vehicle and the second vehicle and in response to the completion rate being greater than a confidence threshold, selecting one of the first vehicle and the second vehicle to send on one route of the plurality of routes based on a highest completion rate and sending the unselected vehicle on another route of the plurality of routes based on a next highest completion rate.

Abstract: Methods and systems are disclosed for generating simulated vehicle performance data. In one example, a method includes building a vehicle model based on sensor data collected from one or more training vehicles, generating a simulation set of virtual vehicles based on the vehicle model, executing a simulation of each of the simulation set of vehicles a plurality of instances, each instance executed with different simulation vehicle operating parameters, obtaining simulation vehicle data from each of the simulation set of vehicles at each instance, training a machine learning model with the simulation vehicle data, and setting one or more parameters of one or more real vehicles based on output from the trained machine learning model.