Abstract: Systems and methods are disclosed for managing task assignments for a plurality of work machines at a site. An assignment engine may: receive first state data for a work machine including historical data, operating condition, and location data, and second state data for the site including characteristic data for materials and a plurality of available tasks; predict performance data and energy consumption data of the work machine for a task; select a task for the work machine by inputting first state data and second state data into a trained reinforcement-learning model, wherein: the model has been trained to learn an assignment policy that optimizes a reward function such that the learned policy selects a task for at least one work machine from the plurality of tasks available at the site; and cause the at least one work machine to be operated according to the at least one task assignment.

Abstract: Systems and methods are disclosed for managing task assignments for a plurality of work machines at a site. An assignment engine may: receive first state data for a work machine including historical data, operating condition, and location data, and second state data for the site including characteristic data for materials and a plurality of available tasks; predict performance data and energy consumption data of the work machine for a task; select a task for the work machine by inputting first state data and second state data into a trained reinforcement-learning model, wherein: the model has been trained to learn an assignment policy that optimizes a reward function such that the learned policy selects a task for at least one work machine from the plurality of tasks available at the site; and cause the at least one work machine to be operated according to the at least one task assignment.

Abstract: A fleet and trolley system, a first method of charging a work machine, and a second method of charging a fleet of work machines are disclosed. The fleet and trolley system includes a trolley network, at least one zero-emission work machine, and a controller. The controller manages a scheduled usage of the trolley network, a power draw, and a distribution of the power draw by the work machine. The first method includes monitoring states of the work machine, scheduling a usage of the trolley network, and supplying electric power to the work machine. The second method includes monitoring states of a fleet, monitoring states of the trolley network, scheduling usages of the trolley network, and supplying electric power to one or more machines of the fleet. Advantageously, the disclosed system and methods may improve an efficiency, productivity, and longevity of a fleet of zero-emission work machines.

Abstract: A method of operating a machine at a worksite includes determining data associated with at least one of a machine operation at the worksite and a worksite condition, and determining, based on the data, that one of machine propulsion and machine retarding will be required for greater than a corresponding threshold. The method also includes determining, in response to determining that machine propulsion will be required, a desired propulsion gear, and recommending the propulsion gear to an operator of the machine. The method further includes determining, in response to determining that machine retarding will be required, a desired retarding gear, and recommending the retarding gear to the operator. In such a method, the retarding gear is determined based on a maximum temperature associated with the machine.

Abstract: A method and system for managing cruise control in a machine provide for maintaining a speed of the machine at a target speed in the absence of an acceleration or deceleration command from an operator of the machine. When a deceleration command is received from the operator of the machine the machine is slowed below the target speed while the deceleration command is received and is returned to the target speed when the deceleration command is no longer received.

Abstract: A method of operating a machine at a worksite includes determining data associated with at least one of a machine operation at the worksite and a worksite condition, and determining, based on the data, that one of machine propulsion and machine retarding will be required for greater than a corresponding threshold. The method also includes determining, in response to determining that machine propulsion will be required, a desired propulsion gear, and recommending the propulsion gear to an operator of the machine. The method further includes determining, in response to determining that machine retarding will be required, a desired retarding gear, and recommending the retarding gear to the operator. In such a method, the retarding gear is determined based on a maximum temperature associated with the machine.