DISTRIBUTING VEHICLES IN NEED OF CHARGE TO CHARGING STATIONS BASED ON PREDICTED FUTURE DEMAND

1 - 22 . (canceled)

23 . A system for directing an electric vehicle to a charging station, the system comprising:

memory for storing historical data associated with past demand for ridesharing vehicles in a geographical area and locations of a plurality of charging stations in the geographical area;

a communication interface for communicating with a fleet of ridesharing vehicles including a plurality of electric vehicles;

at least one processor programmed to access the memory and to:

receive, via the communications interface, current battery-charge data for the plurality of electric vehicles, wherein the current battery-charge data is reflective of a distance that each electric vehicle can operate before recharging;

identify, from the current battery-charge data, a specific electric vehicle traveling in the geographic area and in need of a charge;

receive current vehicle location data for the specific electric vehicle, wherein the current vehicle location data includes global positioning system (GPS) data generated by at least one GPS component associated with the specific electric vehicle;

determine, using the historical data, predicted demand for ridesharing requests in at least one area proximate to at least one of the plurality of charging stations;

based on an estimated charging completion time and the predicted demand, select a charging station for the specific electric vehicle, wherein the selected charging station is other than a charging station closest to a current location of the specific electric vehicle; and

direct the specific electric vehicle to the selected charging station.

24 . The system of claim 23 , wherein the at least one processor is further programmed to manage a schedule for charging at the selected charging station based on the predicted demand.

25 . The system of claim 23 , wherein the at least one processor is further programmed to determine a desired time for the specific vehicle to return to service based on the predicted demand and a location of the selected charging station, and to compare the desired time to the estimated charging completion time.

26 . The system of claim 25 , wherein the at least one processor is further programmed to reassign at least one user scheduled to be picked up by the specific electric vehicle to a different ridesharing vehicle when the estimated charging completion time is after the desired time to shorten the estimated charging completion time.

27 . The system of claim 25 , wherein the at least one processor is further programmed to change at least one drop-off location of at least one passenger currently riding the specific electric vehicle when the estimated charging completion time is after the desired time to shorten the estimated charging completion time.

28 . The system of claim 23 , wherein the at least one processor is further programmed to access a memory that stores information about charging capacities of each of the plurality of electric vehicles, and to determine the estimated charging completion time for the specific electric vehicle based on an expected battery usage when traveling to the selected charging station, the information about charging capacities of the specific electric vehicle, and a desired charging level prior to returning the specific vehicle to service.

29 . The system of claim 28 , wherein the at least one processor is further programmed to determine the expected battery usage when traveling to the selected charging station based on the current location of the specific electric vehicle, a location of the selected charging station, and characteristics of a driving route from the current location of the specific electric vehicle to the location of the selected charging station.

30 . The system of claim 28 , wherein the at least one processor is further programmed to determine the desired charging level prior to return of the specific vehicle to service based on the predicted demand and an availability of other vehicles in the fleet of ridesharing vehicles.

31 . The system of claim 23 , wherein the at least one processor is further programmed to determine the estimated charging completion time at the selected charging station further based on obtained current occupancy data for the selected charging station, wherein the obtained current occupancy data includes a current capacity utilization for each charging point in the selected charging station and current battery-charge data for each electric vehicle located at the selected charging station.

32 . The system of claim 23 , wherein the at least one processor is further programmed to direct the specific electric vehicle from a drop-off location of a last passenger to the selected charging station.

33 . The system of claim 32 , wherein directing the specific electric vehicle from the drop-off location includes transmitting to the specific electric vehicle a specific driving route to the selected charging station.

34 . The system of claim 23 , wherein the at least one processor is further programmed to identify at least two driving routes from the drop-off location of the last passenger to the selected charging station and to select a driving route that includes less elevation changes.

35 . The system of claim 23 , wherein the at least one processor is further programmed to make an intermediate stop at the specific charging station while at least one passenger remains in the specific electric vehicle, and to direct the at least one passenger to transfer to another ridesharing vehicle at the charging station.

36 . The system of claim 35 , wherein the at least one processor is further programmed to inform a driver of the another ridesharing vehicle about the at least one passenger before the specific electric vehicle arrives to the charging station.

37 . A system for directing an electric vehicle to a charging station, the system comprising:

memory for storing locations of a plurality of charging stations in the geographical area;

a communication interface for communicating with a fleet of ridesharing vehicles including a plurality of electric vehicles;

at least one processor programmed to access the memory and to:

receive, via the communications interface, current battery-charge data for the plurality of electric vehicles, wherein the current battery-charge data is reflective of a distance that each electric vehicle can operate before recharging;

identify, from the current battery-charge data, a specific electric vehicle traveling in the geographic area and in need of a charge;

receive current vehicle location data for the specific electric vehicle, wherein the current vehicle location data includes global positioning system (GPS) data generated by at least one GPS component associated with the specific electric vehicle;

receive, via the communications interface, current occupancy data for the plurality of charging stations, wherein the current occupancy data includes an estimated charging completion time for each charging station;

based on the estimated charging completion time, select a charging station for the specific electric vehicle, wherein the selected charging station is other than a charging station closest to a current location of the specific electric vehicle; and

direct the specific electric vehicle to the selected charging station.

38 . The system of claim 37 , wherein the at least one processor is further programmed to manage a schedule for charging at the selected charging station.

39 . The system of claim 37 , wherein the at least one processor is further programmed to access a memory that stores information about charging capacities of each of the plurality of electric vehicles, and to determine the estimated charging completion time for the specific electric vehicle based on an expected battery usage when traveling to the selected charging station, the information about charging capacities of the specific electric vehicle, and a desired charging level prior to returning the specific vehicle to service.

40 . The system of claim 37 , wherein the at least one processor is further programmed to determine the estimated charging completion time at the selected charging station further based on the received current occupancy data for the selected charging station, and wherein the obtained current occupancy data includes a current capacity utilization for each charging point in the selected charging station and current battery-charge data for each electric vehicle located at the selected charging station.

41 . The system of claim 37 , wherein the at least one processor is further programmed to direct the specific electric vehicle from a drop-off location of a last passenger to the selected charging station.

42 . The system of claim 41 , wherein directing the specific electric vehicle from the drop-off location includes transmitting to the specific electric vehicle a specific driving route to the selected charging station.

43 . A method for directing an electric vehicle to a charging station, the method comprising:

accessing a memory configured to store historical data associated with past demand for ridesharing vehicles in a geographical area and locations of a plurality of charging stations in the geographical area;

communicating with a fleet of ridesharing vehicles including a plurality of electric vehicles;

receiving current battery-charge data for the plurality of electric vehicles, wherein the current battery-charge data is reflective of a distance that each electric vehicle can operate before recharging;

identifying, from the current battery-charge data, a specific electric vehicle traveling in the geographic area and in need of a charge;

receiving current vehicle location data for the specific electric vehicle, wherein the current vehicle location data includes global positioning system (GPS) data generated by at least one GPS component associated with the specific electric vehicle;

determining, using the historical data, predicted demand for ridesharing requests in at least one area proximate at least one of the plurality of charging stations;

based on an estimated charging completion time and the predicted demand, selecting a charging station for the specific electric vehicle, wherein the selected charging station is other than a charging station closest to a current location of the specific electric vehicle; and

directing the specific electric vehicle to the selected charging station.

44 . The method of claim 43 , further comprising:

managing a schedule for charging at the selected charging station based on the predicted demand.

45 . The method of claim 43 , further comprising:

determining a desired time for the specific vehicle to return to service based on the predicted demand and a location of the selected charging station, and to compare the desired time to the estimated charging completion time.

46 . The method of claim 45 , further comprising:

reassigning at least one user scheduled to be picked up by the specific electric vehicle to a different ridesharing vehicle when the estimated charging completion time is after the desired time to shorten the estimated charging completion time.

47 . The method of claim 45 , further comprising:

changing at least one drop-off location of at least one passenger currently riding the specific electric vehicle when the estimated charging completion time is after the desired time to shorten the estimated charging completion time.

48 . A non-transitory computer-readable storage medium storing instructions that, when executed by at least one processor, cause the at least one processor to perform a method for directing an electric vehicle to a charging station, the method comprising:

accessing a memory configured to store historical data associated with past demand for ridesharing vehicles in a geographical area and locations of a plurality of charging stations in the geographical area;

communicating with a fleet of ridesharing vehicles including a plurality of electric vehicles;

receiving current battery-charge data for the plurality of electric vehicles, wherein the current battery-charge data is reflective of a distance that each electric vehicle can operate before recharging;

identifying, from the current battery-charge data, a specific electric vehicle traveling in the geographic area and in need of a charge;

receiving current vehicle location data for the specific electric vehicle, wherein the current vehicle location data includes global positioning system (GPS) data generated by at least one GPS component associated with the specific electric vehicle;

determining, using the historical data, predicted demand for ridesharing requests in at least one area proximate at least one of the plurality of charging stations;

based on an estimated charging completion time and the predicted demand, selecting a charging station for the specific electric vehicle, wherein the selected charging station is other than a charging station closest to a current location of the specific electric vehicle; and

directing the specific electric vehicle to the selected charging station.

49 - 127 . (canceled)