Tunneling Effect Mitigation through Artificial Neural Network based Head Up Display Switching System

Abstract

Traditional aircraft cockpit contains a host of display systems with vital flight information like airspeed, artificial horizon, navigation, radar display, altitude, angle of attack, etc. displayed in different formats on separate instruments panels in the cockpit display suite. Such kind of cockpit arrangement requires the pilot to split his attention between outside world and different instrument panels. In fast-moving aircraft, flying close to the ground, operational environment changes so rapidly that pilot has little time to look down at head-down displays to obtain aircraft flight status information. This degrades his situation awareness. Pilot has to cope with continual eye adjustments (focus, luminance etc.) required in changing his line of sight between various displays and the outside world. This results in longer reaction times, pilot fatigue and decreased efficiency. In order to facilitate the view of all these displays without having to divert attention, display systems like head-up display (HUD) and helmet-mounted display (HMD) have been developed. The primary role of HUD is to provide flight, navigation, and guidance information to the pilot in forward field of view on a transparent screen known as beam combiner (hereafter referred in thesis as combiner). Its use avoids need of splitting pilot s attention between aircraft and outside world events which facilitates instant decision making. Main advantages of HUD as compared to head-down displays (HDD) include reduced scanning distance between instrument panels/gauges and outside world, improved situation awareness (SA) of outside world due to more visual attention to outside world, less head-down and look around time as well as less visual mis accommodation due to collimation principle of HUD. Therefore, HUD theoretically allows for optimal control of an aircraft through simultaneous scanning of both instrument data as well as out-of-the-window (OTW) scene.