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Sensor-based flight vision systems enable approaches to altitudes closer to the runway that would otherwise be precluded due to low visibility ceilings. These systems have the potential to augment the safety in flight operations and enable improved crew performance irrespective of the visibility conditions. The sensor-based flight vision system utilizes imaging sensors capable of penetrating through obscuring weather conditions, thereby providing forward vision of the runway environment in real-time for display on a heads-up display (HUD). As the use of sensor-based flight vision system is likely to increase in general aviation operations due to recent FAA policy revision, it is necessary to evaluate the associated human performance implications, especially during offnominal conditions. Most of the previous studies were primarily limited to nominal cases and the assessment on off-nominal cases was limited only to HUD failures though the sensors integrated to these systems can produce degraded sensor output concerning atmospheric conditions. So, the objective of this thesis is to evaluate the human factors implications in using the flight vision system displaying poor sensor output. A pilot-in-the-loop experiment was conducted in a fixed-base flight simulator modeled with the sensor-based flight vision system. Evaluation pilots flew six different experimental trials with two visibility levels (i.e. 600ft RVR and 1000ft RVR) and three levels of sensor information quality (i.e. none, poor, and good sensor output). Measures of performance include approach and landing performance, attention allocation, workload, and decision-making. The experiment results indicated that the pilot’s landing performance and decision making were negatively impacted by poor sensor output. Neither workload nor situation awareness was impacted. Attention allocation results show that pilots had utilized the precision approach path indicator (PAPI) and runway threshold line (RTL) for touchdown operations and fixating on RTL was critical to avoid incorrect landing decisions. INTRODUCTION 1.1 Statement of Authorship Portions of Chapter 1-3 of this thesis work has appeared in Annamalai, Dorneich, and Tokadli (2019). Güliz Tokadli has contributed to the initial experimental design of the pilot study, contributed to the questionnaire design, and obtaining IRB approval for the pilot study. Ramanathan Annamalai performed the literature review, designed the flight simulations, developed the experimental design, conducted the pilot study, conducted the data analysis and results interpretation, and authored the conference paper. All these above-mentioned tasks were performed under the guidance of Dr. Michael Dorneich. 1.2 Objective Sensor-based flight vision systems utilize sensor-based information to present pilots with an enhanced view of the outside environment in degraded visual conditions. Such systems enable aircraft approaches to continue to altitudes closer to the runway that would otherwise be allowed due to low visibility and ceilings. These imaging sensors produce images of the forward scene of external topography. The use of such systems can enable all-weather approaches and landings, irrespective of the visibility conditions. 1n 2016, the FAA revised its existing policy on conducting approaches using these sensor-based flight vision systems, such as Enhanced Flight Vision Systems (EFVS); allowing pilots to land solely utilizing the resulting imagery displayed. The expected use of a sensor-based flight vision system is likely to increase in general aviation (GA) operations due to this policy revision (FAA, 2016). It is necessary to evaluate the associated human factors implications, especially during off-nominal conditions. Previous studies were primarily limited to nominal cases, and the only off-nominal cases tested were limited to HUD failures (Arthur et al., 2013; Kramer et al., 2014; Etherington et al., 2015). The thesis explores the human factors

Evaluating the effect of sensor limitations in flight vision systems on pilot performance