Patent Issued for Systems and methods for dynamically generating optimal routes for management of multiple vehicles (USPTO 11466998): State Farm Mutual Automobile Insurance Company
2022 OCT 31 (NewsRx) -- By a
The patent’s inventors are Brannan,
This patent was filed on
From the background information supplied by the inventors, news correspondents obtained the following quote: “It is well known to use vehicles for delivery of cargo, including persons and items. Newer methods of transporting such cargo are being implemented, such as ride-sharing and businesses contracting with third parties for package delivery. However, current systems require users to pick and choose discrete jobs. For example, a driver for a ride-share service seeks individual persons (or groups thereof) to provide rides to. Likewise, third-party delivery contractors accept individual delivery jobs. Current systems do not provide users with any strategies for maximizing revenue. Accordingly, it is left up to users to attempt to maximize their revenue, time, and/or other resources as they choose individual jobs or tasks. Moreover, many known systems may limit or place restrictions on concurrent jobs, such that users accept consecutive jobs and may be deprived of the advantages (in time and revenue) of concurrent jobs.”
Supplementing the background information on this patent, NewsRx reporters also obtained the inventors’ summary information for this patent: “The present embodiments may relate to, inter alia, systems and methods for optimizing delivery routing for a plurality of vehicles. Vehicle users (e.g., owners, lessors, fleet managers, etc.) may register with a vehicle routing system to receive vehicle routing services therefrom. The vehicle users may submit “definitions” of their vehicle that describe how they want their vehicle to be used (e.g., the times and locations that the vehicle is available to make deliveries). The vehicle routing system may receive a plurality of tasks (e.g., delivering cargo including person(s) and/or object(s)) to be completed, and may analyze the vehicle definitions and the plurality of tasks to generate an optimal route for each vehicle that maximizes the vehicle’s profit generation. In the exemplary embodiment, the vehicle routing system may include artificial intelligence and/or deep learning functionality to generate the optimal routes.
“In addition, the vehicle routing system may collect and process sensor data from the plurality of vehicles, as the vehicle operate according the optimal routes (e.g., performing delivery tasks). The sensor data may characterize use/performance of the vehicle, an ambient environment around the vehicle (e.g., weather, traffic), local infrastructure, and more. The vehicle routing system may process the sensor data (e.g., using the artificial intelligence and/or deep learning functionality) to generate vehicle analytics for each vehicle, identify trends, update optimal routes, and/or make recommendations.
“In the exemplary embodiment, the vehicle routing system maintains a management hub software application (“app”) that enables users to view vehicle analytics and recommendations made by the vehicle routing system. The management hub may additionally enable users to update their user preferences or vehicle definitions of registered vehicles. Additionally or alternatively, the management hub app provides users access to a plurality of other services provided by the vehicle routing system, including maintenance/repair services, financial services, marketing services, and the like.
“In one aspect, a vehicle routing and analytics (VRA) computing device for generating an optimal route for a vehicle that maximizes potential revenue for operation of the vehicle may be provided. The VRA computing device may include at least one processor in communication with a memory, wherein the at least one processor may be programmed to retrieve a vehicle definition for the vehicle, the vehicle definition including availability parameters and delivery preferences associated with the vehicle. The at least one processor may also be programmed to retrieve, based in part on the vehicle definition, a plurality of task definitions defining a respective plurality of tasks, each task including a respective cargo to be delivered, pick-up time, delivery time, pick-up location, delivery location, and task value. The at least one processor may be further programmed to generate, by executing at least one of artificial intelligence and deep learning functionality using the vehicle definition and the plurality of task definitions, an optimal route for the vehicle that includes a scheduled list of a subset of the plurality of tasks for the vehicle to perform, wherein the optimal route maximizes the potential revenue for operation of the vehicle within a period of time associated with the optimal route, and to transmit the optimal route to the vehicle for operation of the vehicle according to the optimal route. The VRA computing device may include additional, less, and/or alternative functionality, including that described herein.
“In another aspect, a computer-implemented method for generating an optimal route for a vehicle to travel that maximizes potential revenue for operation of the vehicle may be provided. The method may be implemented by a vehicle routing and analytics (VRA) computing device including at least one processor. The method may include retrieving a vehicle definition for the vehicle, the vehicle definition including availability parameters and delivery preferences associated with the vehicle. The method may also include retrieving, based in part on the vehicle definition, a plurality of task definitions defining a respective plurality of tasks, each task including a respective cargo to be delivered, pick-up time, delivery time, pick-up location, delivery location, and task value. The method may further include generating, by executing at least one of artificial intelligence and deep learning functionality using the vehicle definition and the plurality of task definitions, an optimal route for the vehicle that includes a scheduled list of a subset of the plurality of tasks for the vehicle to perform, wherein the optimal route maximizes the potential revenue for operation of the vehicle within a period of time associated with the optimal route, and transmitting the optimal route to the vehicle for operation of the vehicle according to the optimal route. The method may include additional, fewer, and/or alternative steps, including those described herein.”
The claims supplied by the inventors are:
“1. A vehicle routing and analytics (VRA) computing device for generating an optimal route for a first vehicle to travel that maximizes potential revenue for operation of the first vehicle, the VRA computing device communicatively coupled to a plurality of vehicles including the first vehicle, each vehicle having a plurality of sensors disposed thereon and configured to collect sensor data during operation of the respective vehicle, wherein the VRA computing device comprises at least one processor in communication with a memory, wherein the at least one processor is programmed to: retrieve a vehicle definition for the first vehicle of the plurality of vehicles, the vehicle definition including availability parameters and delivery preferences associated with the first vehicle; retrieve, based in part on the vehicle definition, a plurality of task definitions defining a respective plurality of tasks, each task including a respective cargo to be delivered, pick-up time, delivery time, pick-up location, delivery location, and task value; generate, by executing at least one of artificial intelligence and deep learning functionality using the vehicle definition and the plurality of task definitions, the optimal route for the first vehicle that includes a scheduled list of a subset of the plurality of tasks for the first vehicle to perform, wherein the optimal route maximizes the potential revenue for operation of the first vehicle within a period of time associated with the optimal route; control the first vehicle to traverse the optimal route by transmitting control instructions associated with the optimal route to the first vehicle; and receive, from the first vehicle, sensor data during operation of the first vehicle according to the optimal route.
“2. The VRA computing device of claim 1, wherein the at least one processor is further programmed to determine, based upon the received sensor data from the first vehicle, a first risk level associated with operation of the first vehicle according to the optimal route.
“3. The VRA computing device of claim 2, wherein the at least one processor is further programmed to: retrieve an insurance policy associated with the first vehicle; determine whether the first risk level exceeds a threshold defined in the insurance policy; and when the first risk level exceeds the threshold, transmit a notification to a vehicle user associated with the first vehicle that the first risk level exceeds the threshold.
“4. The VRA computing device of claim 3, wherein the at least one processor is further programmed to generate the notification including a recommendation of a one-time supplemental insurance policy associated with the optimal route.
“5. The VRA computing device of claim 2, wherein the at least one processor is further programmed to: retrieve an insurance policy associated with the first vehicle; determine whether the first risk level exceeds a threshold defined in the insurance policy; and when the first risk level exceeds the threshold, modify the optimal route to include one or more alternative paths such that the modified optimal route has a second risk level below the threshold.
“6. The VRA computing device of claim 1, wherein a first task of the subset of tasks is associated with a high-value cargo, wherein the at least one processor is further programmed to: generate a recommendation message including a recommendation for a one-time supplemental insurance policy associated with the first task; and transmit the recommendation message to a vehicle user associated with the first vehicle.
“7. The VRA computing device of claim 1, wherein the at least one processor is further programmed to generate, based upon the sensor data received from the first vehicle, a risk profile associated with the first vehicle.
“8. The VRA computing device of claim 1, wherein the at least one processor is further programmed to: detect, based upon the sensor data received from the first vehicle, that the first vehicle requires one or more services; generate a service schedule for the first vehicle, the service schedule including the required one or more services, a respective service time associated with each service, and a respective service vendor associated with each service; and transmit the service schedule to the first vehicle for operation of the first vehicle according to the service schedule.
“9. The VRA computing device of claim 1, wherein the plurality of sensors disposed on the first vehicle include at least one sensor configured to identify check-in and check-out of cargo to and from the first vehicle, and wherein the at least one processor is further programmed to monitor the sensor data received from the first vehicle for adherence to the optimal route.
“10. The VRA computing device of claim 9, wherein the at least one processor is further programmed to: identify, based upon the monitoring, a deviation from the optimal route; and transmit a control signal to the first vehicle, the control signal operative to cause the first vehicle to at least one of: (i) generate an alarm, or (ii) record at least one of audio and video at the first vehicle to capture additional sensor data associated with the deviation.
“11. The VRA computing device of claim 9, wherein the at least one processor is further programmed to: identify, based upon the monitoring, a deviation from the optimal route; and transmit an alert to a first responder computing device to report the deviation.
“12. The VRA computing device of claim 9, wherein the at least one processor is further programmed to generate an electronic ledger of the identified check-in and check-out of the cargo to and from the first vehicle.
“13. The VRA computing device of claim 9, wherein the at least one processor is further programmed to: identify, based upon the monitoring, a deviation from the optimal route including an unauthorized check-in of cargo to the first vehicle; and transmit a notification signal to the first vehicle directing suspension of further operation of the first vehicle.
“14. The VRA computing device of claim 1, wherein the at least one processor is further programmed to receive sensor data from the plurality of vehicles.
“15. The VRA computing device of claim 14, wherein the at least one processor is further programmed to: identify, based upon sensor data received from a subset of the plurality of vehicles having a same make and model, a need for a similar service common to the subset of vehicles; and generate a service report indicating the need for the similar service common to the subset of vehicles for notification of a manufacturer of the subset of vehicles.
“16. The VRA computing device of claim 14, wherein the at least one processor is further programmed to: process the sensor data received from the plurality of vehicles to identify an infrastructure risk; and generate a risk report identifying the infrastructure risk for notification of an entity capable of responding to the infrastructure risk.
“17. The VRA computing device of claim 14, wherein the at least one processor is further programmed to: process the sensor data received from the plurality of vehicles to identify an ongoing infrastructure project; generate, from the sensor data over a period of time, a time lapse of progress of the ongoing infrastructure project; and generate a progress report including the time lapse of progress of the ongoing infrastructure project for notification of an entity associated with the ongoing infrastructure project.
“18. The VRA computing device of claim 14, wherein the at least one processor is further programmed to: process the sensor data received from the plurality of vehicles to identify a real-time emergency incident; and transmit a notification to a first responder computing device, the notification including an indication of the real-time emergency incident and a location thereof.
“19. A computer-implemented method for generating an optimal route for a first vehicle to travel that maximizes potential revenue for operation of the first vehicle, the method implemented by a vehicle routing and analytics (VRA) computing device including at least one processor and a memory, the VRA computing device communicatively coupled to a plurality of vehicles including the first vehicle, each vehicle having a plurality of sensors disposed thereon and configured to collect sensor data during operation of the respective vehicle, wherein the method comprises: retrieving a vehicle definition for the first vehicle of the plurality of vehicles, the vehicle definition including availability parameters and delivery preferences associated with the first vehicle; retrieving, based in part on the vehicle definition, a plurality of task definitions defining a respective plurality of tasks, each task including a respective cargo to be delivered, pick-up time, delivery time, pick-up location, delivery location, and task value; generating, by executing at least one of artificial intelligence and deep learning functionality using the vehicle definition and the plurality of task definitions, the optimal route for the first vehicle that includes a scheduled list of a subset of the plurality of tasks for the first vehicle to perform, wherein the optimal route maximizes the potential revenue for operation of the first vehicle within a period of time associated with the optimal route; controlling the first vehicle to traverse the optimal route by transmitting the optimal route to the first vehicle for operation of the first vehicle according to the optimal route; and receiving, from the first vehicle, sensor data during operation of the first vehicle according to the optimal route.
“20. The method of claim 19, wherein the method further comprises determining, based upon the received sensor data from the first vehicle, a first risk level associated with operation of the first vehicle according to the optimal route.”
For the URL and additional information on this patent, see: Brannan,
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