Systems and methods are disclosed for transporting people using air vehicles.

Systems and corresponding methods are provided for moving object predictive locating, reporting, and alerting. This method includes receiving moving object data corresponding to a moving object; receiving sensor data from a sensor and merging the received moving object data and the received sensor data into a set of merged data. The example method further includes based on the set of merged data, automatically determining one or more of a predicted location or range of locations for the moving object, a potential path of travel for the moving object, an alert concerning the moving object, and providing the alert. The automatically determining may be further based on one or more historical traits concerning the object, and the geographic medium the object is moving through. The geographic medium may include one or more of terrain, air, water, and space. The object may be a soldier, vehicle, drone, or ballistic.

Navigation beacons may be trained to receive signals of opportunity from one or more vehicles, to recognize their own position based on such signals, and to transmit information regarding their own position to one or more other vehicles accordingly. The navigation beacons may be of small size and feature a basic construction including one or more transceivers, power sources and the like, and may communicate via a Bluetooth® Low Energy, Ultra Wideband or long-range low-power wireless standard, or any other standard. The navigation beacons may be installed in any location, preferably being mounted to one or more existing fixed structures or facilities (e.g., transportation structures or facilities), and may operate in active and/or passive modes when learning their positions or servicing position information to one or more remote devices.

Systems and vehicle are provided. A vehicle system for a vehicle includes: a trajectory selection module configured to select a potential vehicle path relative to a current vehicle movement condition; a trajectory movement condition module configured to estimate a modeled movement condition of the vehicle along the potential vehicle path; a limit comparison module configured to determine whether the modeled movement condition violates vehicle limits; and a violation indicator module configured to generate an indication of impending violation.

An airport ground collision alerting system and a method of operating an airport ground collision alerting system. The airport ground collision alerting system comprises an automatic dependent surveillance-broadcast, ADS-B, receiver; a first database coupled to the ADS-B receiver and configured for look-up of aircraft type data based on aircraft ID data received via the ADS-B receiver and for storing aircraft position and heading data received via the ADS-B receiver; a second database configured to store digital map data for one or more airports; a processor unit coupled to the first and second databases and an application programming interface, API, configured to couple the airport ground collision alerting system to a display device.

The present disclosure is directed to systems and methods for trajectory and route planning including obstacle detection and avoidance for an aerial vehicle. For example, an aerial vehicle's flight control system may include a trajectory planner that may use short segments calculated using an iterative Dubins path to find a first path between a start point and an end point that does not avoid obstacles. Then the trajectory planner may use a rapidly exploring random tree algorithm that uses points along the first path as seed points to find a trajectory or route between the start point and end point that avoids known or detected obstacles.

Systems and methods for providing surveillance services for an unmanned vehicle are described herein. One embodiment of a method includes receiving surveilled data from a surveillance monitor regarding the unmanned aerial vehicle and at least one other aircraft, receiving trajectory data from at least one trajectory data source, and comparing the surveilled data with the trajectory data to determine whether the unmanned aerial vehicle is on path to collide with a third party aerial vehicle. In some embodiments, in response to determining that the unmanned aerial vehicle is on path to collide with the third party aerial vehicle, the method includes determining an alternate route for the unmanned aerial vehicle; and communicating at least a portion of the alternate route to the unmanned aerial vehicle.

An anti-collision system for an aircraft and an aircraft including the anti-collision system are disclosed including a sensor data processing unit configured to process data received from multiple sensors installed on a tow tug to detect objects around the aircraft, and output information about detected objects; a safeguarding box building unit configured to generate, based on an aircraft geometry database, a three-dimensional safeguarding box for the aircraft; and a risk assessment unit configured to update the safeguarding box based on data corresponding to different operation modes of the tow tug, calculate relative distances between the detected objects and the aircraft based on the information about the detected objects that is output from the sensor data processing unit, and determine whether there is a collision risk between the aircraft and an object, among the detected objects based on the updated safeguarding box. The system is configured to output an alarm or a warning when there is the collision risk.

Disclosed are methods, systems, and non-transitory computer-readable media for transmitting obstacle information to one or more operator displays associated with an aircraft. For instance, the method may include obtaining aircraft flight information including a current position and altitude; retrieving obstacle information for a flight area; scanning the flight area with environment sensors to identify observed obstacles and generate observed obstacle information. The method may further include aggregating the obstacle information with the observed obstacle information of the observed obstacles identified by the environment sensors to generate aggregated obstacle information identifying obstacles in the flight area; determining obstacle characteristics of the obstacles located in the flight area; assigning visual characteristics to each of the obstacles based at least in part on the determined obstacle characteristics; determining a subset of the obstacles relevant to the aircraft; and transmitting information on the relevant subset of obstacles to a display of the aircraft.

A terrestrial acoustic sensor array for detecting and preventing airspace collision with an unmanned aerial vehicle (UAV) includes a plurality of ground-based acoustic sensor installations, each of the acoustic sensor installations including a sub-array of microphones. The terrestrial acoustic sensor array may further include a processor for detecting an aircraft based on sensor data collected from the microphones of at least one of the plurality of acoustic sensor installations and a network link for transmitting a signal based on the detection of the aircraft to a control system of the UAV.