Abstract: An aircraft can include a stacked propeller to generate lift during assent and descent. The stacked propeller includes a first propeller and a second propeller that co-rotate about an axis of rotation. In one embodiment, the blades are coupled to a rotor mast that contains an internal cavity. In one mode of operation, the first propeller and/or the second propeller can be stored in the internal cavity in order to reduce drag during flight. The aircraft can include one or more stacked propellers, such as a port propeller and a starboard propeller, which rotate in opposite directions during one or more modes of flight.

Abstract: Disclosed herein are systems and methods for planning a multimodal itinerary. The systems and methods may include receiving a transportation request. The transportation request may include a starting location, a final destination, and an estimated payload data. During a first leg of the multimodal itinerary, an updated payload data may be received. An aerial vehicle may be assigned to a subsequent leg of the multimodal itinerary based on the updated payload data.

Abstract: A request for transport services that identifies a rider, an origin, and a destination is received from a client device. Eligibility of the request to be serviced by a vertical take-off and landing (VTOL) aircraft is determined based on the origin and the destination. A transportation system determines a first and a second hub for a leg of the transport request serviced by the VTOL aircraft and calculates a set of candidate routes from the first hub to the second hub. A provisioned route is selected from among the set of candidate routes based on network and environmental parameters and objectives including pre-determined acceptable noise levels, weather, and the presence and planned routes of other VTOL aircrafts along each of the candidate routes.

Abstract: An aerial vehicle that uses motor pulsed-induced cyclic control is provided. In example embodiments, the aerial vehicle comprises a fuselage incorporating a battery system and a payload bay for operatively receiving and holding a payload and at least one mono-blade rotor coupled to an electric motor and an electric motor control system. The electric motor control system controls the electric motor using pulse-induced cyclic control. The aerial vehicle further includes at least one wing, at least one cruise propeller, and an avionics system. The avionic system is configured to transition the aerial vehicle between a vertical take-off and landing mode in which the at least one mono-blade rotor is primarily engaged to propel the aerial vehicle vertically and a cruising mode in which the at least one cruise propeller is primarily engaged to propel the aerial vehicle horizontally.

Abstract: Systems and methods for multi-modal transportation simulation verification are provided. A system includes a simulation system configured to generate simulation data, a planning system configured to determine a multi-modal transportation itinerary based on the simulation data, and a verification system configured to recommend modifications to the generation or selection of a multi-modal transportation itinerary. The verification system can obtain the simulation data and operational data indicative of a performed flight itinerary. The performed flight itinerary can correspond to a simulated flight itinerary of the simulation data. The system can determine performance deviations between the performed flight itinerary and the simulated flight itinerary. The system can generate corrective actions based on the performance deviations and provide the corrective actions to a respective system responsible for the performance deviation.

Abstract: Example embodiments are directed to generating an optimized network of flight paths and an operations volume around each of these flight paths. A network system creates a source network of paths, whereby the source network comprises a set of possible paths between two locations. The network system assigns a cost for traversing each edge of each path of the source network and aggregates the cost for traversing each edge of each path to obtain a cost for each path of the source network. Based on the cost for each path, the network system identifies a path having the lowest cost, whereby the path having the lowest cost is the optimized route between the two locations. The network system then generates an operations volume for the optimized route. The operations volume represents airspace surrounding the optimized route. The operations volume is transmitted to a further system for use.

Abstract: Systems and methods for optimizing multi-modal transportation over a time period are provided. A system includes a simulation system configured to generate simulation data, a servicing system configured to generate servicing data, and a planning system configured to determine a multi-modal transportation itinerary based on the simulation and servicing data. The simulation data can identify a plurality of simulated flights performed in a simulated world corresponding to the real world. The system can determine the impact of scheduling a multi-modal transportation itinerary based on the impact of the multi-modal transportation itinerary on the simulated flights. The servicing data can include a servicing schedule that plans anticipated servicing events based on the impact of the servicing event to the simulated itineraries. Once scheduled, future simulated flights can be generated that account for the multi-modal transportation itinerary and the servicing schedule.

Abstract: A vertical takeoff and landing (VTOL) aircraft, configured to transport passengers and/or cargo, uses propellers during vertical flight and wings during forward flight to generate lift. The VTOL aircraft includes a front wing and a rear wing connected by inboard booms. The rear wing may include a wingtip boom attached to each free end of the wing. A propeller may be attached to each inboard boom and each wingtip boom. The propellers attached to the inboard booms may be stacked propellers including at least two co-rotating propellers. The aircraft can also include a cruise propeller attached to the tail region of the fuselage, where the cruise propeller is configured to rotate in a plane approximately perpendicular to the fuselage to generate thrust during forward flight.

Abstract: A computing system configured to perform operations is provided. The operation operations include obtaining multi-modal transportation data associated with a multi-modal transportation service. The multi-modal transportation data includes user data indicative of a multi-modal transportation itinerary for a user. The operations include obtaining facility data associated with an aerial transport facility. The facility data is indicative of parameters associated with each of a plurality of transition points at the aerial transport facility. The operations include determining one of the plurality of transition points as a selected transition point for the user based, at least in part, on the multi-modal transportation data and the facility data. The operations further include communicating one or more command signals associated with controlling operation of the selected transition point for the user.

Abstract: The present application describes a payload management system that routes a payload item associated with an individual from an origin to a destination. In some examples, the payload item is routed from the origin to the destination separate from a travel itinerary associated with the individual. For example, the payload item can be routed via a vehicle other than a VTOL aircraft that is assigned to the individual for a multi-modal transportation service.

Abstract: Systems and methods for facilitating aerial vehicle services are provided. A service entity system can obtain multi-modal transportation services data indicative of a plurality of anticipated aerial transportation service. The service entity system can obtain vehicle attributes associated vehicle(s) of an aerial vehicle provider and determine an expected performance of the vehicle(s) based on the vehicle attributes and the anticipated aerial transportation services. The service entity system can generate an aerial vehicle service request that requests access to the vehicle(s) for providing aerial transportation services for the service entity based on the expected performance of the vehicle(s). A vehicle provider system can obtain a number of different aerial vehicle service requests from a number of different service entities.

Abstract: A request for transport services that identifies a rider, an origin, and a destination is received from a client device. Eligibility of the request to be serviced by a vertical take-off and landing (VTOL) aircraft is determined based on the origin and the destination. A transportation system determines a first and a second hub for a leg of the transport request serviced by the VTOL aircraft and calculates a set of candidate routes from the first hub to the second hub. A provisioned route is selected from among the set of candidate routes based on network and environmental parameters and objectives including pre-determined acceptable noise levels, weather, and the presence and planned routes of other VTOL aircrafts along each of the candidate routes.

Abstract: Example embodiments are directed to generating an optimized network of flight paths and an operations volume around each of these flight paths. A network system creates a source network of paths, whereby the source network comprises a set of possible paths between two locations. The network system assigns a cost for traversing each edge of each path of the source network and aggregates the cost for traversing each edge of each path to obtain a cost for each path of the source network. Based on the cost for each path, the network system identifies a path having the lowest cost, whereby the path having the lowest cost is the optimized route between the two locations. The network system then generates an operations volume for the optimized route. The operations volume represents airspace surrounding the optimized route. The operations volume is transmitted to a further system for use.

Abstract: Example embodiments are directed to providing periodic vertiport usage and capacity data exchange, A cloud service system generates, based on historical data, a flight operation set that comprises a simulation of flight operations for time buckets in the future, where the simulation of flight operations include transportation services between vertiports. The system then receives, within a predetermined time period of the time buckets, real-time data including weather forecasts and actual demand for transportation services. The real-time data is analyzed to determine any deviations from the flight operation set for the time buckets. The system then presents the flight operation set including any deviations. Additionally, the system receives, after the time buckets has passed, real-time data indicating actual flight operations, compares the real-time data to the flight operation set to identify deltas, and provides the deltas as feedback to refine the generating of future flight operation sets.

Abstract: Systems and methods for transferring aircraft within a landing area of an aerial transport are provided. A system includes a plurality of robotic devices configured to move aircraft within the landing area. The system obtains facility data to dynamically determine accessible and prohibited areas of the landing area. The system determines a robotic device to transfer an aircraft based on map data representing the prohibited/accessible areas of the landing area and robotic data representing attributes of each robotic device. The system determines a number of routes for the selected robotic device to transfer the aircraft within the landing area while avoiding prohibited areas of the landing area. The system generates command instructions for the selected robotic device and provides the command instructions to the selected robotic device to travel in accordance with the number of routes.

Abstract: In one aspect, a system for charging an aircraft can include a robotic charging device, and a computing system configured to obtain data associated with a transportation itinerary and energy parameter(s) of the aircraft. The data associated with the transportation itinerary can be indicative of an aircraft landing facility at which the aircraft is to be located. The computing system can determine (e.g., select) a robotic charging device from among a plurality of robotic charging devices for charging the aircraft based on the transportation itinerary data and energy parameter(s) of the aircraft; determine charging parameter(s) for the robotic charging device based on the transportation itinerary data; and communicate command instruction(s) for the robotic charging device to charge the aircraft according to the charging parameter(s). The robotic charging device can be configured to automatically connect with a charging area of the aircraft for charging a battery onboard the aircraft.

Abstract: Systems and methods for communicating aircraft sensory cues are provided. A method can include obtaining aerial vehicle data and facility data for an aerial portion of a multi-modal transportation service. The method can include determining a plurality of sensory cues indicative of information for the aerial portion of the transportation service such as a safe path across a landing pad of the facility, a seating assignment for a passenger, etc. The method can include communicating sensory data indicative of the plurality of sensory cues to at least one of a facility computing system associated with the facility or an aerial computing system associated with the at least one aerial vehicle. The facility computing system and/or aerial computing system can output the sensory cue(s) to at least one passenger or operator of the aerial portion of the multi-modal transportation service in, for example, the facility's landing area.

Abstract: Systems and methods for improving aerial ride quality based on user feedback accessed from an aerial vehicle and devices associated with passengers are provided. A network system receives, from one or more devices associated with a passenger on an aerial vehicle, feedback data regarding a flight, whereby the feedback data is associated with an issue experienced by the passenger. The network system then identifies a root cause of the issue experienced by the passenger on the aerial vehicle. The identifying may include correlating the feedback data with other data associated with the flight. A mitigation action to mitigate the issue is determined. The network system may determine whether to trigger the mitigation action based on a corresponding threshold and can trigger the mitigation action to occur accordingly.

Abstract: Various examples are directed to an aerial vehicle comprising a fuselage, a first wing member, and a second wing member. The fuselage may have a nose end and a tail end. The first wing member may extend from the fuselage and comprise a first drive motor coupled to the first rotor. The second wing member may also extend from the fuselage substantially opposite the first wing member and may comprise a second drive motor coupled to a second rotor. A first motor may be coupled to rotate the first wing member and the first rotor about a first axis substantially perpendicular to a fuselage axis extending from the nose end to the tail end. A second motor may be coupled to rotate the second wing member and the second rotor about a second axis substantially perpendicular to the fuselage axis. A controller circuit may be configured to differentially actuate the first motor and the second motor.

Abstract: Disclosed are embodiments for determining efficient utilization of drones. In some aspects, a drone may be performing a task, and a new task may be identified. Whether the drone should be diverted from the existing task to the new task, in some embodiments, is based on a number of factors. These factors include, for example, a value associated with the existing task and a value associated with the new task. The values are based on, for example, a potential delay introduced in completing the existing task if the drone is diverted to the new task.