A method and apparatus dynamically update customized integrated terminal approach procedure interfaces based on changing real-time events associated with aircraft and airports. A dynamic approach procedures application extracts and analyzes terminal approach data, aircraft data, airport data and real-time weather data to automatically generate an integrated terminal approach interface. The integrated terminal approach interface presents dynamic digital approach information, the interface including a map interface and a procedure side bar displaying route-related procedures data to assist pilots with selecting a route into the destination airport. As conditions change, displayed terminal approach data within the map and procedure side bar is updated and route recommendations are refined, to assist a user in selecting destination airports, routes, and relevant approach procedures.

An aircraft includes a flight plan and contingency data including a plurality of contingency landing sites. An aircraft communication system communicates with a ground control station via a communication link and detects a lost communication scenario in response to degradation in the communication link. An aircraft flight control system controls the aircraft en route according to the flight plan. In response to detecting the lost communication scenario, the flight control system routes the aircraft back to a last known location in which the communication link was not degraded. In response to failure to re-establish the communication link, the flight control system selects a landing site based on a current aircraft location relative to a plurality of potential landing sites including an origin airport, a destination airport, and a first continency landing site. The flight control system controls the aircraft to approach and land at the selected landing site.

In an aspect of the present disclosure a pilot display system for an aircraft includes a sensor configured to measure an aircraft position and generate a position datum based on the aircraft position, a display incorporated in the aircraft, and a computing device communicatively connected to the sensor and the display, the computing device configured to receive a flight path including a transition point, determine, from the position datum, the aircraft position relative to the transition point, and command the display to display a visual representation of the aircraft position relative to the transition point.

In an aspect of the present disclosure a pilot display system for an aircraft includes a sensor configured to measure an aircraft position and generate a position datum based on the aircraft position, a display incorporated in the aircraft, and a computing device communicatively connected to the sensor and the display, the computing device configured to receive a flight path including a transition point, determine, from the position datum, the aircraft position relative to the transition point, and command the display to display a visual representation of the aircraft position relative to the transition point.

The embodiments are a method and apparatus for generating a safe flight path for an unmanned aerial vehicle, a control terminal and an unmanned aerial vehicle. The method includes: obtaining a path feature point set and attribute parameters, the path feature point set including at least one path planning key point and the attribute parameters including at least a flight height; generating a flight path according to the path feature point set, the attribute parameters and a preset path generation policy; and adjusting the flight path according to an elevation data file, to generate a flight path. According to embodiments of the present invention, elevation data is taken into consideration in the planning of the flight path, which avoids flight obstacles in a flight control process, thereby improving the safety of flight of the unmanned aerial vehicle.

The embodiments are a method and apparatus for generating a safe flight path for an unmanned aerial vehicle, a control terminal and an unmanned aerial vehicle. The method includes: obtaining a path feature point set and attribute parameters, the path feature point set including at least one path planning key point and the attribute parameters including at least a flight height; generating a flight path according to the path feature point set, the attribute parameters and a preset path generation policy; and adjusting the flight path according to an elevation data file, to generate a flight path. According to embodiments of the present invention, elevation data is taken into consideration in the planning of the flight path, which avoids flight obstacles in a flight control process, thereby improving the safety of flight of the unmanned aerial vehicle.

A device includes one or more processors configured to determine a probability that an airplane will follow a submitted flight path. The one or more processors are further configured to in response to a determination that the probability is less than a threshold, provide one or more alternate flight paths to a device.

A device includes one or more processors configured to determine a probability that an airplane will follow a submitted flight path. The one or more processors are further configured to in response to a determination that the probability is less than a threshold, provide one or more alternate flight paths to a device.

A system and method for a digital co-pilot are provided. The method includes receiving a plurality of inputs from a vehicle operating systems, wherein the plurality of inputs comprise engine parameters, control system parameters, or electrical system parameters, identifying one or more first trends in the plurality of inputs, diagnosing one or more first potential conditions based on the first trends, determining a first course of action based on diagnosing the one or more potential conditions, and generating one or more first commands to vehicle controls based on determining the first course of action.

Unmanned Aerial Vehicles also known as UAVs or Drones, either autonomous or remotely piloted, are classified as drones by the US Federal Aviation Administration (FAA) as weighing under 212 pounds. The system described herein details Autonomous Flight Vehicles (AFV) which weigh over 212 pounds but less than 1,320 pounds which may require either a new classification or a classification such as Sport Light Aircraft, but without the requirement of a pilot due to the safe autonomous flight system such as the Safe Temporal Vector Integration Engine or STeVIE. Safe Autonomous Light Aircraft (SALA) are useful as drone carriers, large scale air package or cargo transport, and even human transport depending on the total lift capability of the platform.