Autonomous vehicle refueling
Methods and systems for autonomous vehicle recharging or refueling are disclosed. Autonomous vehicles may be automatically refueled by routing the vehicles to available fueling stations when not in operation, according to methods described herein. A fuel level within a tank of an autonomous vehicle may be monitored until it reaches a refueling threshold, at which point an on-board computer may generate a predicted use profile for the vehicle. Based upon the predicted use profile, a time and location for the vehicle to refuel the vehicle may be determined. In some embodiments, the vehicle may be controlled to automatically travel to a fueling station, refill a fuel tank, and return to its starting location in order to refuel when not in use.
1. A computer-implemented method for automatically refueling or recharging an autonomous vehicle, comprising:
determining, by one or more processors, an indication of predicted use of the autonomous vehicle based upon prior vehicle use data or schedule data relating to one or more vehicle operators associated with the autonomous vehicle;
determining, by the one or more processors, a time and a location at which to refuel or recharge the autonomous vehicle based upon (i) a fuel level or charge level of the autonomous vehicle and (ii) the indication of predicted use of the autonomous vehicle;
determining, by the one or more processors, a return location for the autonomous vehicle based upon the indication of predicted use of the autonomous vehicle;
causing, by the one or more processors, the autonomous vehicle to travel fully autonomously to the determined location at the determined time;
causing, by the one or more processors, one or more of a fuel tank or a battery of the autonomous vehicle to be fully or partially filled or charged at the location; and
causing, by the one or more processors, the autonomous vehicle to travel fully autonomously to the return location.
2. The computer-implemented method of claim 1 , wherein the determined time is a time when the autonomous vehicle is not predicted to be in use based upon the indication of predicted use.
3. The computer-implemented method of claim 1 , the method further comprising:
determining, using one or more sensors disposed within the autonomous vehicle, the fuel level or the charge level of the autonomous vehicle.
4. The computer-implemented method of claim 3 , wherein determining the fuel level or the charge level further comprises determining the fuel level or the charge level as an estimate of a maximum remaining use based upon a measurement of an amount of fuel remaining in the fuel tank or a measurement of a charge level remaining in the battery of the autonomous vehicle.
5. The computer-implemented method of claim 1 , further comprising:
identifying, using one or more geolocation components within the autonomous vehicle, a current location of the autonomous vehicle;
accessing, by the one or more processors, map data containing map information regarding a plurality of road segments, the map information including location data associated with each road segment and an indication of suitability for autonomous operation feature use associated with each road segment; and
identifying, by the one or more processors, a route consisting of one or more road segments from the plurality of road segments between the current location and the location at which to refuel or recharge the autonomous vehicle,
wherein causing the autonomous vehicle to travel fully autonomously to the determined location includes causing the autonomous vehicle to travel along the identified route.
6. The computer-implemented method of claim 5 , further comprising:
identifying, by the one or more processors, one or more charging stations in an area surrounding the current location from a database including location data for a plurality of charging stations,
wherein the location at which to refuel or recharge the autonomous vehicle is selected as a location at which to recharge the battery of the autonomous vehicle from the location data associated with the one or more charging stations based at least in part upon distance from the current location.
7. The computer-implemented method of claim 6 , wherein the location at which to charge the battery is associated with the charging station selected from the one or more charging stations based at least in part upon availability of the charging station.
8. The computer-implemented method of claim 1 , wherein the indication of predicted use includes a predicted use profile indicating a plurality of use periods and use locations over at least one day.
9. The computer-implemented method of claim 1 , wherein the return location is distinct from a prior location from which the autonomous vehicle travels to the location at which to refuel or recharge the autonomous vehicle.
10. The computer-implemented method of claim 1 , wherein causing the autonomous vehicle to travel fully autonomously to the determined location at the determined time and causing the autonomous vehicle to travel fully autonomously to the return location includes (i) generating, at a server remote from the autonomous vehicle, data indicating fully autonomous routes for the autonomous vehicle to travel and (ii) communicating, from the server to an on-board computer of the autonomous vehicle, the data indicating the fully autonomous routes.
11. A computer system for automatically refueling or recharging an autonomous vehicle, comprising:
one or more processors; and
a program memory coupled to the one or more processors and storing executable instructions that, when executed by the one or more processors, cause the computer system to:
determine an indication of predicted use of the autonomous vehicle based upon prior vehicle use data or schedule data relating to one or more vehicle operators associated with the autonomous vehicle;
determine a time and a location at which to refuel or recharge the autonomous vehicle based upon (i) a fuel level or charge level of the autonomous vehicle and (ii) the indication of predicted use of the autonomous vehicle;
determine a return location for the autonomous vehicle based upon the indication of predicted use of the autonomous vehicle;
cause the autonomous vehicle to travel fully autonomously to the determined location at the determined time;
cause one or more of a fuel tank or a battery of the autonomous vehicle to be fully or partially filled or charged at the location; and
cause the autonomous vehicle to travel fully autonomously to the return location.
12. The computer system of claim 11 , wherein the determined time is a time when the autonomous vehicle is not predicted to be in use based upon the indication of predicted use.
13. The computer system of claim 11 , wherein:
the executable instructions further cause the computer system to:
identify, using one or more geolocation components within the autonomous vehicle, a current location of the autonomous vehicle;
access map data containing map information regarding a plurality of road segments, the map information including location data associated with each road segment and an indication of suitability for autonomous operation feature use associated with each road segment; and
determine a route consisting of one or more road segments from the plurality of road segments between the current location and the location at which to refuel or recharge the autonomous vehicle; and
the executable instructions that cause the computer system to cause the autonomous vehicle to travel fully autonomously to the determined location cause the computer system to cause the autonomous vehicle to travel along the identified route.
14. The computer system of claim 13 , wherein:
the executable instructions further cause the computer system to identify one or more charging stations in an area surrounding the current location from a database including location data for a plurality of charging stations; and
the location at which to refuel or recharge the autonomous vehicle is selected as a location at which to recharge the battery of the autonomous vehicle from the location data associated with the one or more charging stations based at least in part upon distance from the current location and based at least in part upon availability of the charging station.
15. The computer system of claim 11 , wherein the computer system comprises a server remote from the autonomous vehicle, the remote server comprising the one or more processors and the program memory.
16. A tangible, non-transitory computer-readable medium storing executable instructions for automatically refueling or recharging an autonomous vehicle that, when executed by at least one processor of a computer system, cause the computer system to:
determine an indication of predicted use of the autonomous vehicle based upon prior vehicle use data or schedule data relating to one or more vehicle operators associated with the autonomous vehicle;
determine a time and a location at which to refuel or recharge the autonomous vehicle based upon (i) a fuel level or charge level of the autonomous vehicle and (ii) the indication of predicted use of the autonomous vehicle;
determine a return location for the autonomous vehicle based upon the indication of predicted use of the autonomous vehicle;
cause the autonomous vehicle to travel fully autonomously to the determined location at the determined time;
cause one or more of a fuel tank or a battery of the autonomous vehicle to be fully or partially filled or charged at the location; and
cause the autonomous vehicle to travel fully autonomously to the return location.
17. The tangible, non-transitory computer-readable medium of claim 16 , wherein the determined time is a time when the autonomous vehicle is not predicted to be in use based upon the indication of predicted use.
18. The tangible, non-transitory computer-readable medium of claim 16 , wherein:
the executable instructions further cause the computer system to:
identify, using one or more geolocation components within the autonomous vehicle, a current location of the autonomous vehicle;
access map data containing map information regarding a plurality of road segments, the map information including location data associated with each road segment and an indication of suitability for autonomous operation feature use associated with each road segment; and
determine a route consisting of one or more road segments from the plurality of road segments between the current location and the location at which to refuel or recharge the autonomous vehicle; and
the executable instructions that cause the computer system to cause the autonomous vehicle to travel fully autonomously to the determined location cause the computer system to cause the autonomous vehicle to travel along the identified route.
19. The tangible, non-transitory computer-readable medium of claim 18 , wherein:
the executable instructions further cause the computer system to identify one or more charging stations in an area surrounding the current location from a database including location data for a plurality of charging stations; and
the location at which to refuel or recharge the autonomous vehicle is selected as a location at which to recharge the battery of the autonomous vehicle from the location data associated with the one or more charging stations based at least in part upon distance from the current location and based at least in part upon availability of the charging station.
20. The tangible, non-transitory computer-readable medium of claim 16 , wherein the executable instructions that cause the autonomous vehicle to travel fully autonomously to the determined location at the determined time and to cause the autonomous vehicle to travel fully autonomously to the return location include executable instructions that cause the computer system to (i) generate, at a server remote from the autonomous vehicle, data indicating fully autonomous routes for the autonomous vehicle to travel and (ii) communicate, from the server to an on-board computer of the autonomous vehicle, the data indicating the fully autonomous routes.