Systems and methods for dynamically generating optimal routes for management of multiple vehicles
AssigneeState Farm Mutual Automobile Insurance Company
InventorsAaron Williams, Ryan Michael Gross, Joseph Robert Brannan
Life of this patent
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Abstract
A vehicle routing system includes a vehicle routing and analytics (VRA) computing device, one or more databases, and one or more vehicles communicatively coupled to the VRA computing device. The VRA computing device is configured to generate an optimal route for a vehicle to travel that maximizes potential revenue for operation of the vehicle, the optimal route including a schedule of a plurality of tasks, and generate analytics associated with operation of the vehicle. The VRA computing device is further configured to provide a management hub software application accessible by vehicle users associated with vehicles, tasks sources, and other users.
Claims20
A vehicle routing and analytics (VRA) computing device comprising at least one processor in communication with a memory, the VRA computing device communicatively coupled to a fleet of vehicles, wherein the at least one processor is programmed to:
- control each vehicle of the fleet of vehicles to travel along a respective optimal route, the optimal route including a scheduled list of tasks for the vehicle to perform;
- detect one vehicle of the fleet of vehicles has deviated from the respective optimal route;
- execute at least one at least one of artificial intelligence and deep learning functionality to assign any remaining tasks assigned to the one vehicle to one or more other vehicles of the fleet of vehicle;
- automatically update each respective optimal route of the one or more other vehicles to generate an updated optimal route including an updated scheduled list of tasks including at least one task previously assigned to the one vehicle;
- and
- control the one or more vehicles of the fleet of vehicles to travel along the respective updated optimal route according to the updated scheduled list of tasks.
A computer-implemented method for generating a route for each vehicle of a fleet of vehicles, the method implemented using a vehicle routing analytics (VRA) computing device communicatively coupled to the fleet of vehicles, wherein the VRA computing device includes at least one processor in communication with a memory, wherein the method comprises:
- controlling each vehicle of the fleet of vehicles to travel along a respective optimal route, the optimal route including a scheduled list of tasks for the vehicle to perform;
- detecting one vehicle of the fleet of vehicles has deviated from the respective optimal route;
- executing at least one at least one of artificial intelligence and deep learning functionality to assign any remaining tasks assigned to the one vehicle to one or more other vehicles of the fleet of vehicle;
- automatically updating each respective optimal route of the one or more other vehicles to generate an updated optimal route including an updated scheduled list of tasks including at least one task previously assigned to the one vehicle;
- and
- controlling the one or more vehicles of the fleet of vehicles to travel along the respective updated optimal route according to the updated scheduled list of tasks.
At least one non-transitory computer-readable storage medium having stored thereon computer-executable instructions that, when executed by at least one processor of a vehicle routing and analytics (VRA) computing device communicatively coupled to a fleet of vehicles, the computer-executable instructions cause the at least one processor to:
- control each vehicle of the fleet of vehicles to travel along a respective optimal route, the optimal route including a scheduled list of tasks for the vehicle to perform;
- detect one vehicle of the fleet of vehicles has deviated from the respective optimal route;
- execute at least one at least one of artificial intelligence and deep learning functionality to assign any remaining tasks assigned to the one vehicle to one or more other vehicles of the fleet of vehicle;
- automatically update each respective optimal route of the one or more other vehicles to generate an updated optimal route including an updated scheduled list of tasks including at least one task previously assigned to the one vehicle;
- and
- control the one or more vehicles of the fleet of vehicles to travel along the respective updated optimal route according to the updated scheduled list of tasks.
Dependencies are inferred from the claim text.