Dynamic vertiport configuration
A vertiport system dynamically updates configuration of a vertiport based on predicted usage of the vertiport during a given time frame. The vertiport system predicts vertiport usage using flight data and estimated passenger demands and determines a desired number of parking pads and a desired number of final approach and takeoff (FATO) pads for the vertiport during the time frame. Based on the desired number of parking pads and the desired number of FATO pads for the vertiport, the vertiport system determines an updated configuration of the vertiport. According to the updated configuration, the vertiport system updates the configuration of the vertiport for at least a portion of the time frame.
1. A method comprising:
predicting vertiport usage for a vertiport for a time frame using vehicle routing data and user demand data, wherein the vertiport is associated with a current configuration indicative of a current number of parking pads and a current number of final approach and takeoff (FATO) pads for the vertiport, wherein at least one FATO pad of the current number of FATO pads is associated with a first lighting pattern and at least one parking pad of the current number of parking pads is associated with a second lighting pattern that is different than the first lighting pattern;
determining a desired number of parking pads and a desired number of FATO pads for the vertiport during the time frame based on the predicted vertiport usage;
determining an updated configuration of the vertiport based on the desired number of parking pads and the desired number of FATO pads, wherein the desired number of parking pads is different than the current number of parking pads or the desired number of FATO pads is different than the current number of FATO pads; and
updating the vertiport from the current configuration to the updated configuration for at least a portion of the time frame, wherein updating the vertiport comprises changing at least one of: the first lighting pattern associated with the at least one FATO pad or the second lighting pattern associated with the at least one parking pad.
2. The method of claim 1 , wherein the predicted vertiport usage is based at least in part on current vertiport usage.
3. The method of claim 1 , further comprising receiving the current configuration of the vertiport, wherein the current configuration further comprises a current location for each of the current number of parking pads and a current location for each of the current number of FATO pads, wherein the updated configuration of the vertiport is further based on the current configuration of the vertiport.
4. The method of claim 3 , wherein determining the updated configuration of the vertiport based on the desired number of parking pads, and the desired number of FATO pads further comprises:
assigning each of a plurality of inbound vehicles and a plurality of outbound vehicles to a parking pad or a FATO pad.
5. The method of claim 1 , wherein the vehicle routing data includes:
a number of inbound vehicles expected to land at the vertiport within the time frame; and
a number of outbound vehicles expected to takeoff from the vertiport within the time frame.
6. The method of claim 5 , wherein the vehicle routing data further includes an amount of charge to be added to an incoming vehicle, and wherein the updated configuration includes a parking area having a charging system for the incoming vehicle.
7. The method of claim 6 , further comprising, responsive to adding the amount of charge to an outbound vehicle parked at a parking pad associated with the second lighting pattern, converting the parking pad into a FATO pad associated with the first lighting pattern.
8. The method of claim 6 , further comprising, responsive to adding the amount of charge to an outbound vehicle parked at a parking pad, providing instructions to the outbound vehicle to navigate to a FATO pad via a taxiway.
9. The method of claim 1 , wherein determining an updated configuration of the vertiport further comprises:
applying a machine-learned model to the predicted vertiport usage, the machine-learned model outputting the updated configuration, wherein the machine-learned model was trained using a cost function representing one or more goals, the one or more goals including increasing passenger throughput.
10. The method of claim 9 , wherein the one or more goals further includes reducing energy usage of the vertiport.
11. The method of claim 1 , further comprising comparing the updated configuration to a set of rules provided by aviation regulation, wherein the current configuration of the vertiport is updated responsive to the updated configuration being in compliance with the set of rules.
12. The method of claim 1 , wherein changing at least one of: the first lighting pattern associated with the at least one FATO pad or the second lighting pattern associated with the at least one parking pad comprises:
changing an illumination of one or more lights to change the at least one FATO pad or the at least one parking pad as represented on a ground surface.
13. The method of claim 1 , wherein changing at least one of: the first lighting pattern associated with the at least one FATO pad or the second lighting pattern associated with the at least one parking pad comprises:
changing a color associated with the at least one FATO pad or the at least one parking pad.
14. A non-transitory computer-readable medium comprising computer program instructions that when executed by a computer processor cause the computer processor to perform steps comprising:
predicting vertiport usage for a vertiport for a time frame using vehicle routing data, wherein the vertiport is associated with a current configuration indicative of a current number of parking pads and a current number of final approach and takeoff (FATO) pads for the vertiport, wherein at least one FATO pad of the current number of FATO pads is associated with a first lighting pattern and at least one parking pad of the current number of parking pads is associated with a second lighting pattern that is different than the first lighting pattern;
determining a desired number of parking pads and a desired number of FATO pads for the vertiport during the time frame based on the predicted vertiport usage;
determining an updated configuration of the vertiport based on the desired number of parking pads, and the desired number of FATO pads, wherein the desired number of parking pads is different than the current number of parking pads or the desired number of FATO pads is different than the current number of FATO pads; and
updating the vertiport from the current configuration to the updated configuration for at least a portion of the time frame, wherein updating the vertiport comprises changing at least one of: the first lighting pattern associated with the at least one FATO pad or the second lighting pattern associated with the at least one parking pad.
15. The non-transitory computer-readable medium of claim 14 , wherein determining the updated configuration of the vertiport based on the desired number of parking pads, and the desired number of FATO pads further comprises:
assigning each of a plurality of inbound vehicles and a plurality of outbound vehicles to a parking pad or a FATO pad.
16. The non-transitory computer-readable medium of claim 14 , wherein the non-transitory computer-readable medium further comprises instructions that when executed by a computer processor cause the computer processor to receive the current configuration of the vertiport, and determine the updated configuration of the vertiport based on the received current configuration of the vertiport.
17. The non-transitory computer-readable medium of claim 14 , wherein the vehicle routing data includes:
a number of inbound vehicles expected to land at the vertiport within the time frame; and
a number of outbound vehicles expected to takeoff from the vertiport within the time frame.
18. The non-transitory computer-readable medium of claim 17 , wherein the vehicle routing data further includes an amount of charge to be added to an incoming vehicle, and wherein the updated configuration includes a parking area having a charging system for the incoming vehicle.
19. The non-transitory computer-readable medium of claim 18 , wherein the non-transitory computer-readable medium further comprises instructions that when executed by a computer processor causes the computer processor to responsive to adding the amount of charge to an outbound vehicle parked at a parking pad associated with the second lighting pattern, convert the parking pad into a FATO pad associated with the first lighting pattern.
20. The non-transitory computer-readable medium of claim 18 , wherein the non-transitory computer-readable medium further comprises instructions that when executed by a computer processor causes the computer processor to responsive to adding the amount of charge to an outbound vehicle parked at a parking pad, provide instructions to the outbound vehicle to navigate to a FATO pad via a taxiway.
21. The non-transitory computer-readable medium of claim 14 , wherein determining an updated configuration of the vertiport further comprises:
applying a machine-learned model to the predicted vertiport usage, the machine-learned model outputting the updated configuration, wherein the machine-learned model has been trained with a goal of maximizing passenger throughput.
22. A system comprising:
a processor; and
a non-transitory computer-readable medium comprising computer program instructions that when executed by the processor of an online system causes the processor to perform steps comprising:
predicting vertiport usage for a vertiport for a time frame using vehicle routing data, wherein the vertiport is associated with a current configuration indicative of a current number of parking pads and a current number of final approach and takeoff (FATO) pads for the vertiport, wherein at least one FATO pad of the current number of FATO pads is associated with a first lighting pattern and at least one parking pad of the current number of parking pads is associated with a second lighting pattern that is different than the first lighting pattern;
determining a desired number of parking pads and a desired number of FATO pads for the vertiport during the time frame based on the predicted vertiport usage;
determining an updated configuration of the vertiport based on the desired number of parking pads, and the desired number of FATO pads, wherein the desired number of parking pads is different than the current number of parking pads or the desired number of FATO pads is different than the current number of FATO pads; and
updating the vertiport from the current configuration to the updated configuration for at least a portion of the time frame, wherein updating the vertiport comprises changing at least one of: the first lighting pattern associated with the at least one FATO pad or the second lighting pattern associated with the at least one parking pad.