Managing a fleet of vehicles

Patent metadata

Field	Value
Publication number	US-11168995-B2
Application number	US-201815921907-A
Country	US
Kind code	B2
Filing date	Mar 15, 2018
Priority date	Mar 15, 2018
Publication date	Nov 9, 2021
Grant date	Nov 9, 2021

Abstract

Aspects of the disclosure relate to determining a next vehicle task for a vehicle of a fleet. Vehicle data from the vehicle, charger data about at least one charger, and demand data may be received and used to determine the next vehicle task. The vehicle may be directed to the next vehicle task. Determining a next vehicle task may further be based on predictions made using the vehicle data, the charger data, and the demand data. Heuristics may also be used in determining a next vehicle task.

First claim

The invention claimed is:

1. A method of determining a next vehicle task for a vehicle of a fleet to perform, the method comprising:
receiving, by one or more processors of one or more server computing devices, from the vehicle, vehicle data including a vehicle charge status and a vehicle charge capacity;
receiving, by the one or more processors, from one or more computing devices of one or more chargers, charger data including one or more of charger location data, charger availability status, charger type or charger speed;
receiving, by the one or more processors, from one or more user computing devices, demand data about one or more of a current trip demand or a predicted future trip demand;
determining, by the one or more processors, the next vehicle task for the vehicle to perform based on the vehicle data, the charger data, the demand data and one or more fleet-wide heuristics that define a respective threshold number of vehicles recharging at a given time in respective zones established for the fleet, wherein the next vehicle task relates to recharging the vehicle;
determining, by the one or more processors, an extent to recharge the vehicle based on at least one of the vehicle data or the charger data; and
directing, by the one or more processors, the vehicle to perform the next vehicle task,
wherein the directing causes the vehicle to drive to a location of an available charger according to the charger data and using the available charger to recharge the vehicle up to the determined extent to recharge the vehicle, and
wherein the determined extent to recharge the vehicle is further based on whether the vehicle charge status exceeds a threshold maximum level.

2. The method according to claim 1 , further comprising:
determining an energy consumption rate of the vehicle; and
predicting a future vehicle charge status after a trip based on the energy consumption rate,
wherein directing the vehicle to perform the next vehicle task includes directing the vehicle to recharge after the trip when the predicted future vehicle charge status after the trip is below a threshold minimum level.

3. The method according to claim 2 , wherein the energy consumption rate for the trip is determined further based on weather conditions.

4. The method according to claim 1 , further comprising:
determining whether the vehicle charge status is below a threshold absolute minimum level,
wherein directing the vehicle to perform the next vehicle task includes directing the vehicle to recharge when the vehicle charge status is determined to be below the threshold absolute minimum level.

5. The method according to claim 1 , further comprising:
predicting a likelihood that an energy cost for recharging the vehicle at the given time will be lower than an energy cost for recharging the vehicle at a future time,
wherein determining the next vehicle task is further based on the likelihood that the energy cost for recharging the vehicle at the given time will be lower than the energy cost for recharging the vehicle at a future time.

6. The method according to claim 1 , further comprising:
determining one or more time windows with peak energy costs during which recharging of the vehicle is not performed.

7. The method according to claim 1 , further comprising:
selecting a suitable charger amongst the one or more chargers for recharging the vehicle,
wherein the vehicle recharges using the suitable charger.

8. The method according to claim 7 , wherein selecting the suitable charger is further based on needs of other vehicles in the fleet to recharge.

9. The method according to claim 7 , wherein selecting the suitable charger is further based on a distribution of where other vehicles in the fleet are recharging.

10. The method according to claim 7 , further comprising:
predicting a future charger availability based on availability, type, and speed of the suitable charger,
wherein selecting the suitable charger is based on the future charger availability.

11. The method according to claim 1 , further comprising:
determining, by the one or more processors, an extent to recharge the vehicle based on whether the vehicle charge status exceeds a threshold maximum level; and
adjusting, by the one or more processor, the threshold maximum level when the current trip demand is above a threshold peak demand,
wherein determining the extent to recharge the vehicle is further based on whether the vehicle charge status exceeds the adjusted threshold maximum level.

12. The method according to claim 1 , further comprising:
determining, by the one or more processors, an extent to recharge the vehicle based on whether the vehicle charge status falls below a threshold minimum level,
wherein the threshold minimum level is based on a cost of traveling involved to reach a charger for recharge.

13. The method according to claim 1 , further comprising:
determining, by the one or more processors, an extent to recharge the vehicle based on a comparison between a current energy cost and a predicted future energy cost.

14. The method according to claim 1 , further comprising:
determining a suitable next trip based on at least one of a vehicle type, a service type, or a number of passengers,
wherein the vehicle services the suitable next trip and recharges after the suitable next trip.

15. The method according to claim 14 , further comprising:
predicting a first vehicle location after a current vehicle task is performed;
predicting a second vehicle location after a next trip based on the demand data; and
predicting a likelihood that the vehicle will be closer to an available charger upon completing the current vehicle task than upon completing the next trip,
wherein determining the next vehicle task is further based on the likelihood that the vehicle will be closer to the available charger upon completing the current vehicle task than upon completing the next trip.

16. The method of claim 1 , wherein the respective threshold number is based on energy pricing for the respective zones at the given time.

17. The method according to claim 1 , wherein the demand data further specifies a vehicle type and a number of passengers requested for a trip by each of a plurality of users.

18. The method according to claim 17 , wherein the demand data further specifies a service type requested by each of the plurality of users.

19. The method according to claim 18 , wherein the service type is a taxi service.

20. The method according to claim 18 , wherein the service type is a carpool service.

21. A system for determining a next vehicle task for a vehicle of a fleet to perform, the system comprising:
the vehicle; and
one or more processors of one or more server computing devices, the one or more processors being configured to:
receive vehicle data about the vehicle in the fleet, the vehicle data including a vehicle charge status and a vehicle charge capacity;
receive, from one or more computing devices of one or more chargers, charger data including one or more of charger location data, charger availability status, charger type or charger speed;
receive, from one or more user computing devices, demand data about one or more of a current trip demand or a predicted future trip demand;
determine the next vehicle task for the vehicle to perform based on the vehicle data, the charger data, the demand data and one or more fleet-wide heuristics that define a respective threshold number of vehicles recharging at a given time i

Assignees

• Waymo Llc

Inventors

• Ludwick Christopher Kennedy
• Chatham Andrew Hughes
• Mcnaughton Matthew Paul
• Johnson Charles Bigelow

Classifications

• B60L53/66

  Data transfer between charging stations and vehicles · CPC title

• G08G1/20

  Monitoring the location of vehicles belonging to a group, e.g. fleet of vehicles, countable or determined number of vehicles · CPC title

• B60L53/68

  Off-site monitoring or control, e.g. remote control · CPC title

• B60L53/64

  Optimising energy costs, e.g. responding to electricity rates · CPC title

• Y04S30/14

  Details associated with the interoperability, e.g. vehicle recognition, authentication, identification or billing · CPC title