The present disclosure provides vehicle collision avoidance system (CAS) that includes a first CAS module for a robotic vehicle that includes an interface to a first network; a hard stop interface communicatively coupled to the robotic vehicle; one or more computer processors; one or more computer readable storage media; and program instructions stored on the one or more computer readable storage media for execution by at least one of the one or more computer processors, the stored program instructions including instructions to: determine a relative position of a second CAS module based on information from the first network; responsive to determining that the second CAS module is within a first distance from the first CAS module, issue an alert; and responsive to determining that the second CAS module is within a second distance from the first CAS module, transmit a hard stop signal to the robotic vehicle.

Methods, systems and apparatus, including computer programs encoded on computer storage media for unmanned aerial vehicle visual line of sight flight operations. A UAV computer system may be configured to ensure the UAV is operating in visual line of sight of one or more ground operators. The UAV may confirm that it has a visual line of sight with the one or more user devices, such as a ground control station, or the UAV may ensure that the UAV does not fly behind or below a structure such that the ground operator would not be able to visually spot the UAV. The UAV computer system may be configured in such a way that UAV operation will maintain the UAV in visual line of sight of a base location.

Apparatus and methods relate to a controller configured to monitor incident risk levels of multiple independently governed autonomous vehicles remote from the controller simultaneously; and, in response to an unsafe incident risk level for one or more vehicles, take control of vehicles having an unsafe incident risk level, to restore a safe incident risk level; and, in response to determining incident risk has been restored to a safe level, returning control to the autonomous vehicles. Incident risk may be determined for multiple vehicles individually, and as a group, based on data from sensors distributed across multiple vehicles. Sensor data from multiple vehicles may be fused, permitting accurate incident risk determination for a vehicle group. Safety measures may be targeted by artificial intelligence to an individual vehicle or a vehicle group, to reduce incident risk by increasing separation between vehicles, or reducing vehicle speed.

A transport facility includes a mobile body configured to move separately from a transport vehicle, a mobile body control system configured to control the mobile body, and a management terminal for a manager. In a case where an abnormality occurs in the transport vehicle, the mobile body control system performs an abnormality handling process of a state information acquisition device sequentially acquiring state information including a state of the transport vehicle in a state where the mobile body can acquire the state information by means of the state information acquisition device, and sequentially transmitting the acquired state information to the management terminal.

A transport facility includes a mobile body configured to move separately from a transport vehicle, a mobile body control system configured to control the mobile body, and a management terminal for a manager. In a case where an abnormality occurs in the transport vehicle, the mobile body control system performs an abnormality handling process of a state information acquisition device sequentially acquiring state information including a state of the transport vehicle in a state where the mobile body can acquire the state information by means of the state information acquisition device, and sequentially transmitting the acquired state information to the management terminal.

A flight management system for an aircraft, includes a critical first avionics module for trajectory calculation, i.e. a module the integrity level and availability level of which are specified by regulatory standards in force, delivering as output a safe trajectory, based on a flight plan; a second module for trajectory calculation that is less critical than the critical first module, i.e. a module the integrity level and availability level of which are lower than those of the first module, delivering as output an improved trajectory that is less safe than the trajectory delivered by the critical first avionics module, based on a flight plan; a critical avionics module for trajectory verification, configured to validate or invalidate the safety of the less safe improved trajectory; and a critical avionics module for decision-making configured to select a trajectory from the safe trajectory and the less safe trajectory.

A method for generating at least one trajectory element (T) for controlling an aircraft (1) according to the trajectory element (T), the generation method being at least partially implemented by a generation system (2) on board the aircraft (1), and comprising the steps of: receiving a first initial data stored in a first database (6), the first database (6) presenting a first predefined level of integrity, called the initial level of integrity; receiving a second initial data stored in a second database (8), the second database (8) presenting said initial level of integrity, the first database (6) being dissimilar relative to the second database (8); comparing at least one first trajectory data (D1) with at least one second trajectory data (D2); obtaining the trajectory element (T).

This disclosure relates to apparatuses, systems, and methods for handling faults on vehicles. One or more processors in a vehicle may receive, from a control unit in response to a detection of a fault in the vehicle, an indication of a degradation in a performance constraint of the vehicle. The processors may determine, responsive to the degradation in the performance constraint, that the vehicle is unable to execute a set of commands to control a movement of the vehicle along a trajectory. The processors may generate, in accordance with the degradation in the performance constraint, a modified set of commands that the vehicle is able to execute to control the movement of the vehicle along at least a portion of one or more trajectories. The processors may provide the modified set of commands to the control unit of the vehicle to control the movement of the vehicle.

This disclosure relates to apparatuses, systems, and methods for handling faults on vehicles. One or more processors in a vehicle may receive, from a control unit in response to a detection of a fault in the vehicle, an indication of a degradation in a performance constraint of the vehicle. The processors may determine, responsive to the degradation in the performance constraint, that the vehicle is unable to execute a set of commands to control a movement of the vehicle along a trajectory. The processors may generate, in accordance with the degradation in the performance constraint, a modified set of commands that the vehicle is able to execute to control the movement of the vehicle along at least a portion of one or more trajectories. The processors may provide the modified set of commands to the control unit of the vehicle to control the movement of the vehicle.

A waypoint correction device and waypoint correction method are provided. In response to a positioning signal of an unmanned aerial vehicle at a predetermined waypoint, the waypoint correction device obtains a real-time image from the unmanned aerial vehicle. The waypoint correction device calculates a feature point distribution in the real-time image based on the real-time image. The device generates an adjusted viewing angle signal based on the feature point distribution to control the unmanned aerial vehicle to rotate in place based on the adjusted viewing angle signal and capture an adjusted real-time image. The device generates a correction route based on a plurality of three-dimensional feature points, the adjusted real-time image, and a sampling number threshold to control the unmanned aerial vehicle to move from an actual position to a predetermined waypoint based on the correction route.