Autonomous electric vehicle charging
Methods and systems for autonomous vehicle recharging or refueling are disclosed. Autonomous electric vehicles may be automatically recharged by routing the vehicles to available charging stations when not in operation, according to methods described herein. A charge level of the battery of an autonomous electric vehicle may be monitored until it reaches a recharging 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 recharge may be determined. In some embodiments, the vehicle may be controlled to automatically travel to a charging station, recharge the battery, and return to its starting location in order to recharge when not in use.
1. A computer-implemented method for automatically recharging an autonomous electric vehicle, the method comprising:
detecting, by one or more sensors disposed within the autonomous electric vehicle, a charge level of a battery of the autonomous electric vehicle below a maximum recharging threshold;
generating, by the one or more processors, a predicted use profile for the autonomous electric vehicle based upon prior vehicle use data;
determining, by the one or more processors, a next predicted use of the autonomous electric vehicle based upon the predicted use profile;
causing, by the one or more processors, the autonomous electric vehicle to charge at a location when a sufficient amount of time exists to charge the autonomous electric vehicle before the next predicted use;
determining a return location for the autonomous electric vehicle; and
causing the autonomous electric vehicle to return to the return location,
wherein the return location is determined based upon the predicted use profile or vehicle operator information, and is distinct from the location at which to charge the battery.
2. The computer-implemented method of claim 1 , wherein the detecting of the charge level of the battery corresponds to when the autonomous electric vehicle is not in use.
3. The computer-implemented method of claim 1 , wherein the detecting of the charge level of the battery corresponds to when the autonomous electric vehicle is in use, wherein the predicted use profile includes one or more predicted breaks in vehicle operation, each predicted break being associated with a break time and a break location, and wherein the location is based upon the one or more predicted breaks.
4. The computer-implemented method of claim 1 , wherein the location at which to charge the autonomous electric vehicle is associated with a charging station selected from a plurality of charging stations based at least in part upon availability of the selected charging station.
5. The computer-implemented method of claim 1 , further comprising:
identifying, using one or more geolocation components within the autonomous electric vehicle, a current location of the autonomous electric vehicle; and
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 charge the battery is selected from the location data associated with the one or more charging stations based at least in part upon distance from the current location.
6. The computer-implemented method of claim 5 , further comprising:
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 charge the battery,
wherein the causing the autonomous electric vehicle to charge at the location includes controlling the autonomous electric vehicle along the identified route.
7. The computer-implemented method of claim 1 , wherein the predicted use profile indicates a plurality of use periods and use locations over at least one day.
8. A computer system for automatically recharging an autonomous electric vehicle, the computer system comprising:
one or more processors disposed within the autonomous electric vehicle;
one or more sensors disposed within the autonomous electric vehicle and communicatively connected to the 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:
detect a charge level of a battery of the autonomous electric vehicle below a maximum recharging threshold;
generate a predicted use profile for the autonomous electric vehicle based upon prior vehicle use data;
determine a next predicted use of the autonomous electric vehicle based upon the predicted use profile;
cause the autonomous electric vehicle to charge at a location when a sufficient amount of time exists to charge the autonomous electric vehicle before the next predicted use;
determine a return location for the autonomous electric vehicle; and
cause the autonomous electric vehicle to return to the return location,
wherein the return location is determined based upon the predicted use profile or vehicle operator information, and is distinct from the location at which to charge the battery.
9. The computer system of claim 8 , wherein to detect the charge level of the battery, the executable instructions cause the computer system to detect the charge level of the battery when the autonomous electric vehicle is not in use.
10. The computer system of claim 8 , wherein to detect the charge level of the battery, the executable instructions cause the computer system to detect the charge level of the battery when the autonomous electric vehicle is in use, wherein the predicted use profile includes one or more predicted breaks in vehicle operation, each predicted break being associated with a break time and a break location, and wherein the location is based upon the one or more predicted breaks.
11. The computer system of claim 8 , wherein the location at which to charge the autonomous electric vehicle is associated with a charging station selected from a plurality of charging stations based at least in part upon availability of the selected charging station.
12. The computer system of claim 8 , wherein:
the executable instructions further cause the computer system to:
identify a current location of the autonomous electric vehicle using one or more geolocation components within the autonomous electric vehicle; and
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,
wherein the location at which to charge the battery is selected from the location data associated with the one or more charging stations based at least in part upon distance from the current location.
13. The computer system of claim 12 , wherein:
the executable instructions further cause the computer system to:
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
identify 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 charge the battery,
wherein to cause the autonomous electric vehicle to charge at the location, the executable instructions cause the computer system to control the autonomous electric vehicle along the identified route.
14. The computer system of claim 8 , wherein the predicted use profile indicates a plurality of use periods and use locations over at least one day.
15. A tangible, non-transitory computer-readable medium storing executable instructions for automatically recharging an autonomous electric vehicle that, when executed by at least one processor of a computer system, cause the computer system to:
detect a charge level of a battery of the autonomous electric vehicle below a maximum recharging threshold;
generate a predicted use profile for the autonomous electric vehicle based upon prior vehicle use data;
determine a location at which to charge the battery based upon the charge level and the predicted use profile;
determine a next predicted use of the autonomous electric vehicle based upon the predicted use profile;
control the autonomous electric vehicle to travel fully autonomously to the determined location when a sufficient amount of time exists to charge the autonomous electric vehicle before the next predicted use;
determine a return location for the autonomous electric vehicle; and
control the autonomous electric vehicle to return to the return location,
wherein the return location is determined based upon the predicted use profile or vehicle operator information, and is distinct from the location at which to charge the battery.
16. The tangible, non-transitory computer-readable medium of claim 15 , wherein the location at which to charge the battery is associated with a charging station selected from a plurality of charging stations based at least in part upon availability of the selected charging station.
17. The tangible, non-transitory computer-readable medium of claim 15 , further storing instructions that cause the computer system to:
identify a current location of the autonomous electric vehicle using one or more geolocation components within the autonomous electric vehicle; and
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,
wherein the location at which to charge the battery is selected from the location data associated with the one or more charging stations based at least in part upon distance from the current location.
18. The tangible, non-transitory computer-readable medium of claim 17 , further storing instructions that cause the computer system to:
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
identify 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 charge the battery,
wherein to cause the autonomous electric vehicle to charge at the location, the executable instructions cause the computer system to control the autonomous electric vehicle along the identified route.