January 2012 

NASA/TM–2012-217324 

Awareness and Detection of Traffic and 

Obstacles Using Synthetic and Enhanced Vision 

Systems

Randall E. Bailey 

Langley Research Center, Hampton, Virginia 
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January 2012 

NASA/TM–2012-217324 

Awareness and Detection of Traffic and 

Obstacles Using Synthetic and Enhanced Vision 

Systems

Randall E. Bailey 

Langley Research Center, Hampton, Virginia 
Available from: 

NASA Center for AeroSpace Information 

7115 Standard Drive 

Hanover, MD 21076-1320 

443-757-5802 

Acknowledgments 

This work was jointly sponsored by the NASA Aviation Safety Program, Intelligent 

Integrated Flight Deck project, led by Dr. Steve Young (Principal Investigator), and the 

FAA Human Factors R&D Project for NextGen, led by Dr. Tom McCloy and Mr. Dan 

Herschler. This cooperative research was formally established under an Interagency 

Agreement between the FAA and NASA (IA1-973, Technical Direction 5). 

This support and sponsorship is gratefully appreciated. 

The use of trademarks or names of manufacturers in this report is for accurate reporting and does not constitute an 

official endorsement, either expressed or implied, of such products or manufacturers by the National Aeronautics 

and Space Administration. 
iii

Table of Contents

1. INTRODUCTION............................................................................................................................... 1

2. BACKGROUND ................................................................................................................................. 2

2.1. SV AND EFVS OPERATIONS ...................................................................................................... 3

2.2. SEVS RESEARCH ISSUES AND REPORT ORGANIZATION ............................................... 5

2.3. ASSUMPTIONS AND LIMITATIONS ........................................................................................ 6

3. TRAFFIC AND OBSTACLE DETECTION .................................................................................... 8

3.1. TARGET DETECTION BY A HUMAN OBSERVER ................................................................ 8

3.2. TARGET PERCEPTION BY A PILOT WITH AND WITHOUT EV ...................................... 8

3.2.1. SOURCE .................................................................................................................................. 9

3.2.2. DETECTION MECHANISMS .............................................................................................. 9

3.2.3. DETECTION AVENUES ..................................................................................................... 10

3.3. JOHNSON’S CRITERIA ............................................................................................................. 12

3.4. VISUAL SEARCH AND GAZE .................................................................................................. 14

4. HEAD-DOWN AND HEAD-UP OPERATIONS ........................................................................... 15

4.1. “SEE-AND-AVOID” ..................................................................................................................... 15

4.2. VISIBILITY CONDITIONS AND MANUAL CONTROL ....................................................... 16

4.3. VISUAL REFERENCES .............................................................................................................. 17

4.4. CREWED PROCEDURES ........................................................................................................... 19

4.4.1. PILOT-MONITORED APPROACH .................................................................................. 20

4.4.2. PILOT-IN-ACTIVE CONTROL LOOP ............................................................................. 21

4.5. EFVS PROCEDURES .................................................................................................................. 21

4.5.1. EFVS CREW PROCEDURES .............................................................................. 21

4.5.2. EV HEAD-DOWN CREW PROCEDURES ........................................................ 23

4.5.3. EV SINGLE-PILOT PROCEDURES ................................................................... 24

5. TRAFFIC/OBSTACLE DETECTION USING SEVS TECHNOLOGIES ................................. 25

5.1. AUTOMATIC TARGET DETECTION AND RECOGNITION .............................................. 25

5.2. RESOLUTION INFLUENCE OF DETECTION AND RECOGNITION ............................... 26

5.3. TRAFFIC/OBSTACLE DETECTION BY PM WITH SEVS TECHNOLOGIES .................. 29

5.4. TRAFFIC/OBSTACLE DETECTION BY PF WITH SEVS TECHNOLOGIES ................... 32

5.5. CLUTTER ..................................................................................................................................... 33

5.6. ATTENTION CAPTURE ............................................................................................................. 35

5.6.1. OTW VISUAL FIDELITY ................................................................................................... 37

5.6.2. HUD OPTICS ........................................................................................................................ 38

5.6.3. CONFORMAL SYMBOLOGY ........................................................................................... 40

5.6.4. BRIGHTNESS, CONTRAST, AND DECLUTTER ........................................................... 40

5.6.5. TYPE OF EVENT ................................................................................................................. 41

5.6.6. PILOT EXPERIENCE AND TRAINING ........................................................................... 42

6. COCKPIT DISPLAY OF TRAFFIC INFORMATION WITH SEVS ......................................... 44

6.1. OBJECT/TRAFFIC DETECTION AND USE OF CDTI .......................................................... 44

6.2. OBJECT/TRAFFIC DETECTION AND USE OF CDTI WITH SEVS – EXO-CENTRIC ... 46

6.3. INTEGRATION OF CDTI WITH SEVS – EGO-CENTRIC ................................................... 48

7. CONCLUDING REMARKS AND RECOMMENDATIONS ...................................................... 50

7.1. RECOMMENDATIONS .............................................................................................................. 50

REFERENCES ........................................................................................................................................... 54
iv

List of Figures 

FIGURE 1: HONEYWELL SYNTHETIC VISION CONCEPT ................................................................................... 3

FIGURE 2: ENHANCED FLIGHT VISION SYSTEM CONCEPT .............................................................................. 4

FIGURE 3: TARGET DETECTION DIAGRAM ...................................................................................................... 9

FIGURE 4: PROBABILITY OF DETECTION AND RECOGNITION AS FUNCTION OF RESOLUTION ACROSS

CRITICAL TARGET DIMENSIONS (FROM RATCHES, 1997). ................................................................... 13

FIGURE 5: VIEW OF C-172 HOLDING SHORT FROM AIRCRAFT AT 500 FT HAT ............................................ 27

FIGURE 6: VIEW OF C-172 HOLDING SHORT FROM AIRCRAFT AT 300 FT HAT ............................................. 27

FIGURE 7: VIEW OF C-172 HOLDING SHORT FROM AIRCRAFT AT 200 FT HAT ............................................ 28

FIGURE 8: VIEW OF C-172 HOLDING SHORT FROM AIRCRAFT AT 100 FT HAT ............................................ 28

FIGURE 9: PM EVALUATIONS USING SEVS TECHNOLOGY .......................................................................... 31

FIGURE 10: DATA FROM FISCHER ET AL (1980) FOR RUNWAY INCURSION EVENT ...................................... 36

FIGURE 11: 4D SURFACE CDTI CONCEPTS .................................................................................................. 48

FIGURE 12: HEAD-WORN DISPLAY CONCEPT WITH TRAFFIC REPRESENTED BY A VIRTUAL MODEL .......... 49
v

List of Tables 

TABLE I-JOHNSON’S CRITERIA - RESOLUTION REQUIREMENTS ................................................................... 13

TABLE II - REQUIRED VISUAL REFERENCES, 14 CFR 91.175 (C) AND (L) ...................................................... 19

TABLE III - EFVS CREW PROCEDURES ......................................................................................................... 23

TABLE IV– PIXELS SUBTENDING THE LATERAL EXTENT (36 FT) OF C-172 ................................................... 26
vi

Nomenclature 

AC Advisory Circular 

ADS-B Automatic Dependent Surveillance-Broadcast 

ANSP Air Navigation Service Provider 

CDTI Cockpit Display of Traffic Information 

CFR Code of Federal Regulations 

CRT Cathode Ray Tube 

DA Decision Altitude 

DH Decision Height 

DOT Department of Transportation 

EP Evaluation Pilot 

EFVS Enhanced Flight Vision System 

EV Enhanced Vision 

EVS Enhanced Vision System 

FAA Federal Aviation Administration 

FAR Federal Aviation Regulation 

FLIR Forward Looking Infra-Red 

FOV Field-of-View 

HAT Height Above TDZE 

HDD Head-Down Display 

HUD Head-Up Display 

ILS Instrument Landing System 

GA General Aviation 

LaRC Langley Research Center 

MASPS Minimum Aviation System Performance Standard 

MDA Minimum Descent Altitude 

NASA National Aeronautics and Space Administration 

ND Navigation Display 

NextGen Next Generation Air Transportation System 

OTW Out-the-Window 

PF Pilot-Flying 

PFD Primary Flight Display 

PNF Pilot-Not-Flying 

PM Pilot-Monitoring 

PMA Pilot-Monitored Approach 

RIPS Runway Incursion Prevention System 

RVR Runway Visibility Range 

SEVS Synthetic and Enhanced Vision Systems 

SOP Standard Operating Procedure 

SURF-IA Surface Indications and Alerts 

SV Synthetic Vision 

SVS Synthetic Vision System 

TDZE Touchdown Zone Elevation 

T-NASA Taxiway Navigation And Situation Awareness 

VFR Visual Flight Rules 
1

1. Introduction

The NASA Langley Research Center (LaRC) and the Department of 

Transportation/Federal Aviation Administration (DOT/FAA) are conducting 

collaborative research activities to ensure effective technology development and 

implementation of regulatory and design guidance to support the use of Synthetic Vision 

Systems (SVS) and Enhanced Flight Vision Systems (EFVS) advanced cockpit vision 

technologies in Next Generation Air Transportation System (NextGen) operations. 

SVS/EFVS technologies have the potential to provide an additional margin of safety and 

performance to enable the implementation of operational improvements for low visibility 

surface, arrival, and departure operations with equivalent efficiency as visual operations. 

SVS uses a terrain and obstacle database to present a computer-generated view of the 

outside world, often on a Head-Down Display (HDD). While HDDs are cheaper and 

more widely available than Head-Up Displays (HUDs), presentation of SVS information 

on a HDD display has the potential to significantly increase pilot head down time which 

may detract from ground-referenced navigation and hazard detection/avoidance. 

EFVS uses active or passive sensors to present a visual image of the outside view on a 

HUD. Previous research on HUD use in airborne applications suggests that clutter and 

masking can lead to decreased conflict detection. Safe and effective use of EFVS 

information presented on a HUD will require assessment of the impact of EFVS 

presentation on ground conflict detection and avoidance. 

In this report, the research literature is reviewed to assess awareness and detection of 

traffic and obstacles when using SVS and EFVS systems, as follows: 

Qualify the critical issues influencing the time required, accuracy, and pilot 

workload associated with recognizing and reacting to potential collisions or 

conflicts with other aircraft, vehicles and obstructions related to the use of SVS 

and EFVS (SEVS) technologies during approach, landing, and surface operations.

o This work includes the effect of HDD and HUD implementations of SVS 

and EFVS, respectively, as well as the influence of single and dual pilot 

operations.

Identify methods and strategies of adding Cockpit Display of Traffic Information 

(CDTI) with head-down SVS and head-up EFVS in low-visibility landing and 

surface operations and their effect on time required, accuracy, and pilot workload 

for recognizing and reacting to potential ground collisions or conflicts. This work 

includes the impact of emerging requirements for CDTI and alerting for NextGen. 

Based on this review, a knowledge gap assessment is conducted to create 

recommendations for subsequent ground and flight testing which promote the safe and 

effective implementation of SEVS technologies for NextGen. 
2

2. Background

Synthetic vision (SV) is a computer-generated image of the external scene topography 

that is generated from aircraft attitude, high-precision navigation, and data of the terrain, 

obstacles, cultural features, and other required flight information (Figure 1). The term, 

SVS, as opposed to SV, is often used to indicate that this database information is 

enhanced with integrity monitoring to ensure the validity of the databases and/or 

independent navigation accuracy verification. Part of this integrity monitoring function 

may also include real-time traffic surveillance and obstacle/object detection (Parrish et al, 

2008).

Under NASA’s Aviation Safety Program/Synthetic Vision Project, NASA and its 

partners in industry and the FAA, developed and deployed SVS technologies for 

commercial, business, and general aviation (GA) aircraft. SVS concepts were shown to 

provide significant improvements in terrain awareness and reductions for the potential of 

Controlled-Flight-Into-Terrain incidents/accidents compared to current generation 

cockpit technologies (Kramer, 2004; Kramer, 2005; Arthur 2003; Parrish et al, 2008). 

Enhanced Vision (EV) is an electronic means to provide a display of the external scene 

by use of an imaging sensor, such as a Forward-Looking InfraRed (FLIR) or millimeter 

wave radar. EV has been used for decades by the military for night missions, especially 

for low-level navigation and targeting. Various development activities and 

demonstrations have been conducted. The FAA conducted its own EV technology 

demonstration program – then called a Synthetic Vision System – to assess the state-ofthe-art and the operational implications of the technology (Burgess, 1993). As HUD 

technology has migrated into commercial and business aircraft, EV technology and its 

potential for all-weather operations and improved safety naturally followed (e.g., see 

Looking Ahead, 1993). EV has been shown to be complementary to SV due to their 

inherently different technological bases (Bailey, 2008).

The applications of EV technology for commercial, business, and GA aircraft were 

energized in January 2004 (FAA, 2004a) when Title 14 of the US Code of Federal 

Regulations (CFR) §91.175 was amended such that operators conducting straight-in 

instrument approach procedures (in other than Category II or Category III operations) 

may now operate below the published Decision Altitude (DA)/Decision Height (DH) or 

Minimum Descent Altitude (MDA) when using an approved EFVS. An EFVS, in this 

application, is an integrated conformal display of EV and symbology shown on the pilot’s 

HUD (see Figure 2). The required conformal symbology includes the flight path vector, 

flight path angle reference, and flight guidance with other non-conformal flight 

information shown as necessary and appropriate. The EFVS is approved for use in lieu 

of natural vision. This rule change provides “operational credit” for EV equipage. No 

such credit exists for SV. 

Minimum Aviation System Performance Standards (MASPS) have been published as 

DO-315 (RTCA, 2008), which provides the system performance standards for EFVS 

(“operational credit”) and SV (“no operational credit”). 
3

Figure 1: Honeywell Synthetic Vision Concept 

2.1. SV and EFVS Operations

Even though SV and EFVS are certified and operational, research issues still abound, 

especially as the applications for these technologies are broadened and expanded. 

SEVS technologies have been identified as fundamental building blocks to NextGen 

(FAA, 2004b); integral to the concept of “equivalent visual operations.” Equivalent 

visual operations imply the ability to achieve or even improve on the safety of currentday Visual Flight Rules (VFR) operations, maintain the operational tempos of VFR, and 

even, perhaps, retain VFR-derived procedures independent of the actual weather and 

visibility conditions. These vision technologies (SEVS) serve as enabling technologies to 

meet that challenge following the precedent that SEVS may be used in lieu of a pilot’s 

natural vision. This is currently only the case for EFVS under §91.175 (l) and (m). 
4

Figure 2: Enhanced Flight Vision System Concept

In this report, a truly “equivalent visual operation” is not assumed. While this is the 

ultimate objective of using this technology, this initial work examines SEVS technologies 

only to enable or assist in low visibility approach and landing, surface, and takeoff/departure operations where there is no change in the present-day roles and 

responsibilities of Air Navigation Service Providers (ANSPs) for spacing and separation.

Future growth and usage of SV and EV “vision systems” technology may eventually 

enable the flight crew to perform VFR-like operational capability (i.e., “see-to-follow,” 

“see-and-avoid,” and “own navigation” including the pilot’s ability and responsibility to 

self-separate from other traffic, terrain, and obstacles) but in this report, the implications 

of creating these capabilities are not considered. Future work should investigate the 

vision system technology (SEVS) requirements for an equivalent visual operational 

capability (R-1).

In this work, the current and incremental improvements in operational capabilities using 

SVS and EFVS are considered as follows:

SEVS technologies are used under VFR and Instrument Flight Rules operations, 

day and night.

In addition to the current “no operational credit” use of SV, the use of SV is 

examined to enable descent below the published DA or DH to 100 ft height above 

the touchdown zone elevation (TDZE) from a straight-in instrument approach 

procedures with published vertical guidance.
5

In addition to the current “operational credit” use of EFVS identified under 14 

CFR §91.175 (l) and (m), the use of EFVS is examined to enable descent below 

the published DA or DH, landing and roll-out in visibility as low as 1000 ft 

Runway Visual Range (RVR) flying a straight-in instrument approach procedure 

with published vertical guidance.

Further, the use of EFVS is assumed to enable take-off and surface operations in 

visibility conditions down to 700 ft RVR.

2.2. SEVS Research Issues and Report Organization 

Two overarching research issues are addressed in this report arising from present and 

future operational concerns associated with SEVS technology: 

1) SV operations are presently focused on HDD implementations since they are less 

expensive and have a broader user base (i.e., it is not practical to install a HUD in 

many aircraft). Presentation of SV information on a HDD during low altitude and 

surface operations has the potential to significantly increase pilot head-down time 

which may detract from ground-referenced navigation and hazard 

detection/avoidance.

2) In EFVS operations, the HUD display must present all EFVS-required imagery 

and symbology and for compliance with 14 CFR §25.1301 and §25.1303, data 

elements of primary flight displays which are essential or critical to the phase of 

flight. Conversely, for compliance with 14 CFR §25.773, HUD symbology must 

not excessively interfere with a pilots’ forward view and their ability to visually 

maneuver the airplane, acquire opposing traffic, and see the runway environment. 

These conflicting requirements necessitate an examination of how EFVS 

information presented on a HUD impacts its safe and effective use and especially, 

the potential for HUD clutter and obscuration to negatively impact traffic and 

obstacle collision detection and avoidance.

In both cases, a critical issue is the ability of a human observer to perform “target 

detection.” In Section 3, a review of traffic and obstacle detection by a human observer 

is presented. This work points to the wealth of data pertaining to this activity, and more 

importantly, highlights that the speed and accuracy of traffic and obstacle detection is a 

function of awareness (i.e., is the observer alerted to the conflict?), workload (i.e., is the 

observer engaged in a divided attention or full attention task?), localization (i.e., does the 

user have other information directing them where to look?), and the characteristics of the 

object to be seen, the device being used to image and display the object, and the 

atmospheric properties, lighting, and background in which the object/traffic is being 

viewed.

Research is then reviewed, in Section 4, regarding pilot/flight crew tasking for awareness 

and detection of targets/obstacles. Head-down to head-up transitions and pilot/crew roles 

and responsibilities are presented. This work discusses the issues of transitioning from 

head-down to head-up operations and emphasizes how this impacts target (i.e., traffic or 
6

obstacle/object) detection, recognition, and resolution while attending to required flight 

deck and piloting tasks. 

To address the specific nuances of the second issue, the state-of-the-art regarding clutter, 

obscuration (masking), and attention capture using HUDs is reviewed in Section 5. 

These issues have garnered a wealth of study and merit special consideration as to its 

direct applicability in this research. This work is also related to target (i.e., traffic or 

obstacle/object) detection, recognition, and resolution while attending to required flight 

deck and piloting tasks. 

In Section 6, these two topics are considered as they might be influenced and affected by 

the design and use of CDTI for approach and landing, surface, and take-off/departure 

operations. This work includes the impact of emerging technology for traffic indication, 

warning, and alerting during approach, landing, and surface operations. 

Finally, in Section 7, concluding remarks and recommendations are presented. This 

section summarizes the critical research areas that need to be explored further to advance 

the state-of-the-art and to effectively implement and possibly expand the operational 

capabilities of SEVS technologies for NextGen.

2.3. Assumptions and Limitations 

Several assumptions and limitations have been invoked for this work. 

First, the limitations: 

1. This work is not intended to be stand-alone; instead, numerous references are 

used to point the reader where additional, important information is contained. 

The intent of this work is to integrate numerous disparate pieces of information 

from which to form a unifying picture as well as to identify knowledge gaps 

which highlight future research requirements for SEVS technologies. 

2. This work focuses on the use of CDTI and the pilot’s awareness and detection of 

traffic and obstacles almost exclusively on the runway and airport surface. This 

emphasis examines traffic detection issues in those operations (i.e., during final 

approach and landing, taxi, and departure/take-off) where SEVS technologies 

provide notable operational benefits. Significant work has been conducted in 

other flight phases (e.g., en-route merging and spacing) and this work may be 

referenced as relevant, but it is not extensively reviewed. 

3. The work considers only fixed-wing aircraft operations. The analyses may be 

applicable to vertical take-off and landing or rotary wing vehicles, but this work 

has not been validated for the unique operational aspects of these vehicles. No 

warranty as to the applicability of this review should be assumed or implied. 

4. This work assumes that the imaging sensor for the EFVS is a FLIR. This 

limitation may not be a serious limitation since only FLIR sensors have been 
7

approved to date as an EFVS, but it does merit note as a slight loss in generality is 

created. 

The primary assumption imposed in this review is that the pilots (and crew) are 

sufficiently trained in the use and operation of the equipment. Also, that during crewed 

operations, both pilots are effectively functioning as a crew and a break-down in crew 

coordination or crew resource management has not occurred. 

At present, the roles and responsibilities of the ANSPs for spacing and separation from 

other traffic are assumed to be unchanged by the presence or use of these flight deck 

technologies. These technologies are not intended to change the roles and responsibilities 

of the airport services providers for foreign object damage control, wildlife control, or 

other airport infrastructure and service functions. Future work should explore the impact, 

if any, of SEVS in changing the roles and responsibilities of the ANSP (R-2).

SEVS technologies also offer unique capabilities which might be used in lieu of certain 

airport and aircraft infrastructure or equipment for low visibility approach, landing, 

surface, and take-off/departure operations. Future work should explore the potential for 

SEVS to replace the need for or functional elements currently required for Surface 

Movement Guidance and Control Systems and for approach lighting systems (R-3).

SEVS technologies may eventually enable the pilot/crew to perform “see-to-follow,” 

“see-and-avoid,” and “self-navigation” including the ability and responsibility of the 

pilot/crew to self-separate from other traffic, terrain, and obstacles. As previously 

mentioned, this work does not focus on these new capabilities but the work is 

fundamentally applicable to it. 
8

3. Traffic and Obstacle Detection

The visual traffic and obstacle detection task is, in essence, a human observer performing 

“target acquisition” of which a wealth of data and research are available, mostly in the 

military domain. These works are too numerous to detail; instead, key findings are 

extracted from this work and briefly summarized to establish “first-principles.” From 

this basis, later sections extend these principles into research specific to SEVS operations 

and display design issues to qualify the time required, pilot workload, and accuracy of 

traffic and obstacle detection and the attendant critical issues. 

Two perceptual mechanisms are considered in this research: 

Target detection by a human observer looking through cockpit windows; 

Target detection by a human observer looking at cockpit displays, using a 

HUD or HDD. 

3.1. Target Detection by a Human Observer 

While a wealth of research and data are available, the target detection task by a human 

observer is complicated by many complex and incompletely understood processes and 

interactions, especially when applied to the flight environment. 

Target detection research (Boff and Lincoln, 1988) shows that the probability that a target 

will be recognized by a human observer is a function of: 

• the probability that the observer is searching an area that is known to 

contain a target, looks with his/her foveal vision for a specified glimpse 

time (s) in the direction of the target; and, 

• the probability that the displayed target image is viewed foveally for one 

glimpse period with sufficient contrast and size to be detected; 

The later element – the saliency of the object in terms of whether the target is of 

sufficient contrast and size – can be considered as a necessary but perhaps not sufficient 

prerequisite for successful target detection by a human observer. 

3.2. Target Perception By A Pilot With and Without EV 

The concept of target saliency and the use of SEVS technologies for target detection by a 

pilot is schematically diagramed in Figure 3. The diagram does not attempt to map out a 

cognitive process, but rather, tries to capture the physical effects and perceptual 

mechanisms involved in determining if the necessary but not necessarily sufficient 

condition for visual target acquisition exists (i.e., whether the human’s perception of the 

target has sufficient contrast and size). 
9 

Figure 3: Target Detection Diagram

3.2.1. Source

The perceived target contrast and size is obviously driven by the contrast and size of the 

“source information.” In Figure 3, this source information, shown in a bottom-up 

paradigm, drives the perceptual paths (i.e., “Enhanced Vision” or “Natural Vision”)

The target angular size and the apparent target-background luminance ratio (contrast) of 

the “source information” depend primarily on four factors (see Boff and Lincoln, 1988): 

x the target attributes 

x the attributes of the target background 

x the medium through which it is viewed (i.e., the atmospheric properties such as, 

fog, haze, moisture content, etc.) 

x and the characteristics that illuminate the target, background, and atmosphere 

(i.e., sun angle, moon phase, etc.). 

3.2.2. Detection Mechanisms

This “source information” flows into two possible perception mechanisms: 
10 

1. Using Enhanced Vision 

2. Using Natural Vision (i.e., the out-the-window (OTW) view) 

(The use of SV or CDTI is not considered in this process since this section is concerned 

with unaided visual target detection by a human observer.) 

The perception of the target – whether the target is of sufficient size and contrast - is thus 

affected by how this source information (i.e., the target-background-medium attributes) is 

modified along these paths before it is presented to the human observer. 

In the case of EV, these modifications include how this source information is “perceived” 

by the EV sensor and what image transformations or distortions are introduced in the 

process. Present-day FLIRs transform the radiated thermal energy into gray-scale level 

(monochromatic) imagery; that is, the thermal signature. 

The first-principle involves the sensor detector characteristics including its wave-length, 

resolution, sensitivity, noise, and image processing characteristics. Target detection is 

critically dependent on how these image properties are “matched” to the imaging sensor 

and the characteristics of the environment in which the imaging occurs. For EFVS 

applications, the FLIR sensor typically provides a wide bandwidth of detector 

wavelengths, designed to provide a best-case compromise between thermal sensitivity 

and transmissivity through atmospheric moisture content for runway, terrain, and 

airport/approach lighting systems. 

Analytical tools have been developed to predict infrared sensor system performance in 

this task. Moderate resolution atmospheric transmission simulations (Beier and 

Gemperlein, 2004) model the atmosphere and can predict the radiative properties for a 

wide range of wavelengths and spectral resolutions, enabling the calculation of 

transmittance and radiance from a target. It uses different climate models, geographical 

latitudes, time of year (i.e., seasons influencing, for example, sun angle and prevailing 

atmospheric temperature) and with each climate model, different aerosol types. 

However, the conditions of the atmosphere alone aren’t enough to predict performance. 

The size of the target and the radiated/reflective/emitted differences against the 

background as well as the spatial resolution and sensitivity of the optics and the detector, 

and the noise of the detector and signal processing alter the target prominence against the 

background.

3.2.3. Detection Avenues

Visual target detection is shown through any of four possible avenues:

1. Using EV on a HDD 

2. Using EV on a HUD 

3. Using the OTW view, through a HUD 

4. Using the OTW view 

These four avenues subtend different fields-of-regard/fields-of-view (FOV) and also, 

invoke different transformational processes of the source information to the pilot 

perception of the image. For instance: 
11 

Using the OTW view: Target detection using natural vision OTW occurs by the 

pilot/crew looking through the aircraft windows. The field-of-regard for which 

this detection is possible is the extent of the windows and the range of head/eye 

movement available by the crew to look around any aircraft structure. Guidance 

for this field-of-regard (i.e., window size) for target detection (i.e., collision 

avoidance) is given under Advisory Circular (AC) 25-773. In this detection task, 

the “source image” properties are modified by the optical characteristics of the 

windscreen. Although the goal in the design and development of the windscreen 

optical characteristics is to provide no modification, perfection is not possible. 

Under 14 CFR §23.773, “The windshield and side windows forward of the pilot's 

back when the pilot is seated in the normal flight position must have a luminous 

transmittance value of not less than 70 percent.“ Testing has shown that these 

optical performance requirements has generally been achieved and maintained 

through an aircraft’s service life (Quinn et al, 1996). The influence of canopy 

distortion in a target detection task for civil transport aircraft should not be a 

factor, unlike military/fighter aircraft (Task and Goodyear, 1999). 

Using the OTW view, through a HUD: Target detection using natural vision 

OTW can also occur by the pilot/crew looking through the HUD and aircraft 

windows. In this case, the target must be located within the HUD field-of-regard. 

In this detection task, the “source image” properties are modified by the optical 

characteristics of the windscreen as well as the optical characteristics of the HUD 

(i.e., transmissivity) and any symbology or imagery that may obscure this 

detection. SAE Aeronautical Standard AS-5088, “Minimum Performance 

Standard for Airborne Head Up Display (HUD)” specifies that the light 

transmissivity of the HUD combiner shall be greater than 70%. This degradation 

is in addition to possible canopy transmissivity losses, resulting in some potential 

visual performance degradation. The issues of obscuration due to symbology and 

attentional influence of HUD operations are discussed in following sections. 

Using EV on a HUD: Target detection using EV can occur by the pilot/crew 

looking at the HUD. EV shown on a HUD is, by EFVS definition, conformally 

drawn (i.e., the field-of-regard of the sensor and the HUD are matched and the 

imagery overlays the real world as seen through the HUD combiner); thus, for a 

target to be detected using an EV-HUD, the target must be located within the 

HUD FOV. 

Using EV on a HDD: For the EV detection task shown on the HDD, the field-ofregard of the EV sensor and whether it is fixed or slewable to the aircraft affect 

whether the target is visible to the EV sensor. Also, the effects from minification 

and magnification of the imagery (i.e., non-conformal display) must be 

considered in the detection task. Both the display as well as the sensor, dictate the 

image resolution presented to the human for the target detection task. In addition 

to resolution, the magnification and minification of the information affects human 

performance. 
12 

The detection of targets and obstacles using EV imagery critically depends on the display 

device characteristics. The distinction between head-up and head-down displays is not 

only important for their spatial location but also due to their optical characteristics. 

HDDs afford much greater resolution, more gray scales, luminance, and contrast 

sensitivity than HUDs. HUD gray shades, defined as an increase in brightness by 

a factor of 1.41 (square root of 2), are typically no greater than 7 and rapidly 

reduce as the ambient background luminance increases toward 10,000 ft-Lamberts 

(Karim, 1992). This loss of apparent contrast degrades human performance 

(Lloyd and Reinhart, 1993). 6 shades of gray are typically required for imagery 

(i.e., video) (Rash, 1999). HDDs do not have to contend with a variable visual 

background, they employ much higher luminance and contrast optical properties 

and can use glareshields and other optics to shade the displays from direct and 

diffuse sun light effects (Karim, 1992). 

Chromaticity can be put into effect on HDDs unlike monochromatic HUDs (e.g., 

see Scribner, Warren, and Schuler, 2000). Typically, EV imagery is 

monochromatic, but the HDD may highlight data aspects using false color cueing 

(e.g., see Toet, 2002).

3.3. Johnson’s Criteria 

Numerous and sometimes elaborate analyses have been developed to predict human 

detection performance, essentially quantifying whether the perceived target is of 

sufficient contrast and size (e.g., to name just a few: Aviram and Rotman, 2000 and 2001, 

Vollmerhausen, Jacobs, and Driggers, 2004; Watson, Ramirez, and Salud, 2009; see also 

Boff and Lincoln, 1988).

Instead of using these models, a rough-order-of-magnitude criterion, for comparative 

analysis only, is used here. Johnson’s criteria attempts to quantify minimum resolution 

requirements for human awareness, detection, recognition and identification of traffic or 

objects/obstacles.

A series of experiments (Ratches et al, 1997) were conducted to quantify target detection 

probability as a function of the resolution of the sensor/display system (i.e., the target 

angular size). This work showed that, whether using an unaided eye or other sensors, 

such as night-vision goggles or thermal imaging systems, four tasks were involved in the 

target acquisition process: 

1) Detection: correctly discriminating an object in the image from background and 

system noise. 

2) Orientation: correctly determining the detected target aspect or direction of 

movement. 

3) Recognition: correctly determining the class membership of the target. For 

example, is it a truck? A tank? etc. 

4) Identification: correctly determining the exact identity of the target, e.g., for 

automobiles, is it a Ford or Chevrolet? 
13 

These same and similar processes in detection, recognition, and identification for air-toair target acquisition tasks have also been found (e.g., see Rohrer, 1996). 

These experimental data led to the development of Johnson’s criteria for target 

acquisition. Johnson’s work presumed that the ability of the observer to detect, recognize 

and identify a target were a function of how well a critical dimension of the target could 

be resolved by the sensor-display system. An example of the data is shown in Figure 4, 

indicating the probability of detection and recognition (of a man or a vehicle) is a 

function of the number of sensor-display cycles (sensor/display line pairs or roughly 

pixels) depicting the object.

Figure 4: Probability Of Detection And Recognition As Function Of Resolution Across 

Critical Target Dimensions (from Ratches, 1997). 

Johnson’s work evolved into straight-forward criteria for display and sensor requirements 

for visual acquisition as shown in Table I. The “critical target dimension” was based on 

intuition and was usually chosen to be the minimum dimension. 

Table I - Johnson’s Criteria - Resolution Requirements

Task Line Resolution per Minimum 

Dimension

Detection 1.0 ± 0.25 line pairs 

Orientation 1.4 ± 0.35 line pairs 

Recognition 4.0 ± 0.8 line pairs 

Identification 6.4 ± 1.5 line pairs 

These criteria only pertain to the target size of the problem; that is, the angular extent of 

the target and the associated resolution of the display and sensor to generate the image for 
14 

human visual acquisition. The other components of the visual acquisition task – e.g., the 

apparent target-background contrast - are dependent upon innumerable other factors such 

as atmospheric conditions (clouds, fog, haze, moisture content, etc.), target 

color/material, background illumination and color, sun angle, background (sky/ground), 

etc and sensor/display contrast performance. Even though these are critical issues to the 

task, these are not influenced by the display resolution directly.

Johnson’s criteria has been shown to be a rough, first-order approximation as numerous 

analyses have shown it to be flawed in several respects (McDonald and Vorst, 2002); 

however, for comparative analyses associated with angular extent and resolution of a 

target, Johnson’s criteria is applied herein to evaluate EV and display sensor resolution 

effects on visual target acquisition.

3.4. Visual Search and Gaze 

Whether a target, in a visual detection task, is of sufficient contrast and size can be 

considered as a necessary but perhaps not sufficient prerequisite for successful target 

detection by a human observer. However, most of the elements that dictate this 

prerequisite - other than the design characteristics of the EV sensor and display system - 

are not directly a function of the SEVS technologies. They are a function of the task, the 

proximity of the aircraft to the obstacle or traffic, or the weather and time of day. 

The other critical element required for visual target detection is that of the pilot/crew’s 

visual search and gaze.

Wickens et al (2001) hypothesized that visual gaze was a function of: 

(1) the salience of objects that affect attention capture 

(2) the effort required to move attention, 

(3) the expectancy that information will be obtained; and, 

(4) the value of the information to be found there. 

These characteristics that govern visual gaze are defined by the roles and responsibilities 

of the pilot/flight crew and are possibly influenced by CDTI or the presence of 

traffic/obstacle indications, cautions, or warnings. These elements are to various degrees 

influenced by the design of and technologies on the flight deck, as described in the 

following sections.
15 

4. Head-Down and Head-Up Operations

The crew/pilot tasking and their roles and responsibilities during SEVS operations are 

explored as they impact the pilot’s/crew’s workload, the available time to perform object 

and traffic detection, and their visual scan patterns.

The detection of traffic and obstacles is not the only tasking of a pilot or crew member. 

Within the operating paradigm of “aviate, navigate, and communicate,“ detection of 

traffic and obstacles is certainly one of the tasks contained within the “navigate” element. 

However, the concept of “see-and-avoid” is engrained within all FAA operations under 

both Instrument Flight Rules and VFRs and certainly is of critical importance. “See-andavoid” requires that each person operating an aircraft maintains vigilance at all times. 

During crewed operations, the flight duties of the crew members are dependent upon 

many factors, and tasking can be distributed, with certain crew members having more or 

less responsibility for “see-and-avoid.” For single pilot operations, vigilance for “seeand-avoid” must be attended to as part of all required pilot duties. 

In all cases, the cockpit display of traffic information greatly influences the pilot’s ability 

to perform the task of traffic/obstacle awareness and detection. 

4.1. “See-and-avoid”

The FAA requires under 14 CFR Part 91.113, across all classes of airspace, that “when 

weather conditions permit, regardless of whether an operation is conducted under 

instrument flight rules or visual flight rules, vigilance shall be maintained by each person 

operating an aircraft so as to see-and-avoid other aircraft.”

Pilots are trained, and through experience, adopt visual scanning procedures both in their 

use of instruments (i.e., a visual scan pattern of the cockpit displays) and in scanning outthe-window for other traffic and/or objects (Bellenkes, Wickens, and Kramer, 1997). The 

FAA’s Aeronautical Information Manual (Section 8-1-6) emphasizes that “the time a 

pilot spends on visual tasks inside the cabin should represent no more than 1⁄4 to of the 

scan time outside, or no more than 4 to 5 seconds on the instrument panel for every 16 

seconds outside.” The criticality of outside scanning to meet the see-and-avoid safety 

principle and how to effectively scan for outside traffic is explained in numerous areas 

(see FAA AC 90-48C, “Pilot’s Role In Collision Avoidance”). Unfortunately, studies 

(e.g., Colvin, Dodhia, and Dismukes, 2005) have shown that pilots do not adhere to these 

recommendations and spend considerably more time head-down than head-out. VFR 

pilots in small GA aircraft have been shown to be preoccupied with in-cockpit duties and 

are head-down at least 40% of the time (Sulzer and Skelton, 1976). Significant 

individual differences have been noted (e.g., see Wickens et al, 2001). 

Measured flight performance for aircraft detection is remarkably poor, often casting 

doubt on the effectiveness of the see-and-avoid principle (see Graham and Orr, 1970; 

Andrews, J,W., 1991a, 1991b) In particular, Andrews showed that only 56% of 64 near-
16 

collision encounters were sighted by GA pilots during en-route operations. Although 

some studies show an eight to nine times improvement in detection when alerted, others 

have still shown relatively poor performance (Moore, 1998). 

The merit of see-and-avoid operations and the associated human visual, human attention, 

and operational issues have been studied extensively (e.g., see Australian Transport 

Safety Board, 1991; Graham, 1989). Whether see-and-avoid is actually effective or not is 

immaterial. The FAA requires, under 14 CFR Part 91.113, across all classes of airspace 

that see-and-avoid shall be conducted. This work examines the influence of SEVS 

technologies on traffic and obstacle detection which forms part of “see-and-avoid.” It 

should be noted that most of the research cited above for see-and-avoid were almost 

exclusively conducted enroute or outside of the airport terminal maneuvering area. This 

analysis of SEVS technologies focuses instead on low visibility approach, landing, 

departure, and surface operations. 

4.2. Visibility Conditions and Manual Control 

The weather conditions in which the operation is conducted obviously affect the usable 

visual cues outside the aircraft (i.e., OTW visibility). These weather conditions typically 

also affect the visibility of an imaging sensor in an EFVS. 

Less obvious is that the weather conditions also dictate (by FAA regulations) the onboard and off-board systems required to conduct the operation. These systems 

significantly alter the degree to which the pilot must “aviate;” that is, how much the pilot 

manually flies the aircraft. These requirements, thus, impact the crew duties and the 

associated workload and attention demands of the pilot during low visibility approach 

and landing operations. The general assumption is that a pilot who is manually flying 

would have less spare attention to devote to target/obstacle detection and avoidance. 

The landing minima classifications of Category I, II, and III are defined as follows: 

Category (Cat.) I is an instrument approach or approach and landing with a 

decision altitude (height) or minimum descent altitude (height) not lower than 200 

ft and with either a visibility not less than 1/2 statute mile, or a runway visual 

range (RVR) not less than 1800 ft. 

Cat. II is an instrument approach or approach and landing with a decision height 

lower than 200 ft but not lower than 100 ft and a runway visual range not less 

than 1200 ft. 

Cat. III is an instrument approach or approach and landing with a decision height 

lower than 100 ft, or no decision height, or a runway visual range less than 1200 

ft.

Guidance for US approval of low visibility approach, take-off and surface operations are 

contained in AC120-29A (“Criteria For Approval Of Category I And Category II 

Weather Minima For Approach”) and 120-28D (“Criteria For Approval Of Category III 

Weather Minima For Takeoff, Landing, And Rollout”). These works do not contain the 

latest regulatory changes associated with EFVS, such as 14 CFR §91.175 (l) and (m), or 
17 

special authorizations/changes provisioned through FAA Order 8400.13 (‘Procedures for 

the Evaluation and Approval of Facilities for Special Authorization Category I 

Operations and All Category II and III Operations”). These materials show that: 

Cat. I approaches can be manually flown with reference to raw data or to flight 

director commands or automatically with the autopilot engaged. 

Cat. II/Cat. III approaches are flown using an automatic landing system. For Cat. 

II minima, a flight director, autopilot, or HUD with approved flight guidance is 

used but the landing can be manually-flown. 

For Cat. III minima, an autopilot or HUD with approved flight guidance is used to 

fly the approach, landing, and roll-out. The HUD system provides head-up 

guidance to the pilot so, by manual control, an equivalent level of performance 

(and safety) to an auto-land system is demonstrated. A Decision Height not less 

than 50 ft. height above Touchdown Zone Elevation (TDZE) is used.

4.3. Visual References 

The concept of visual flight references creates an important distinction for automatic and 

manual landing systems, as well as EFVS operations. For Cat. I and Cat. II approaches, 

visual reference means being able to see to land (i.e., being able to conduct a hand-flown 

landing). For Cat III approaches, visual reference means being able to see to verify 

aircraft position, if ever so briefly. It’s important to understand the use of visual 

references to appropriately gauge pilot workload and attention demands during low 

visibility approach and landing operations.

At DA(H) or prior to the MDA on an instrument approach in other than Cat. III 

conditions, the pilot makes a decision whether to continue descending below DA(H) or 

MDA. This decision is made using natural vision or using an EFVS if equipped. The 

decision and the subsequent “visual segment” is based on this visual information, the 

comprehension of its meaning, and the projection of its status in the near future. 

Regulations in effect as 14 CFR §91.175 and its companion regulations under §121 and 

§135 identify the required visual references which, from a historical basis, support the 

flight crew’s informational needs to safely complete this operation. In Table II, the 

required visual landing references for §91.175 (c) (Non-EFVS flight operations) and (l) 

(EFVS flight operations) are detailed to descend below the published DA(H) or MDA 

and to descend below the 100 ft Height Above TDZE (HAT). 

From an equivalent performance perspective, the required visual references in Cat I/II 

conditions must provide information sufficient to: 

– Portray the present descent rate, its status with respect to normal operations and 

normal maneuvering limits and provide trend information that the descent rate 

and aircraft position will continually allow a safe descent to landing. 

– Provide status and trend information that may indicate if, with normal maneuvers, 

a touchdown can occur with acceptable descent rate and within the intended 

touchdown zone. 
18 

Ideally, during this visual flight segment, the pilot would be able to visually identify that 

the path toward the intended touchdown point is free of all obstacles, charted or 

otherwise. This task is typically performed today by operational procedure. By Terminal 

Instrument Procedures (TERPS) design, obstacle protections are provided to the landing 

runway in the visual segment of a standard instrument approach procedure and Air 

Traffic Control (ATC) procedures are in effect to keep vehicles and other aircraft clear of 

the landing runway. However, there is no instrumentation or display currently in use that 

annunciates or informs the pilot/crew that they are in the ‘approved’ visual segment 

although the use of published vertical and lateral guidance may provide this type of 

information. 

A missed approach/go-around is executed at the DA(H) or the charted missed approach 

point or so as to not descend below the MDA if the required visual references are not 

visible and distinctly identifiable or if the aircraft is not in a position to land safely. 

The task demands for the flight crew/pilot – i.e., to pick up the required visual references, 

and successfully complete their flying duties – greatly influences their time, workload, 

and ability to be aware of and detect traffic or obstacles. These task demands and by 

inference, the display designs, are affected by the assigned roles and responsibilities for 

the flight crew.
19 

Table II - Required Visual References, 14 CFR 91.175 (c) and (l)

Required Visual References Using 

Natural Vision 

(14 CFR 91.175 (c))

Required Visual References Using an 

Enhanced Flight Vision System 

(14 CFR 91.175 (l)) 

For operation below DA/DH or MDA – 

At least one of the following visual references for the 

intended runway must be distinctly visible and 

identifiable: 

Approach light system 

Threshold 

Threshold markings 

Threshold lights 

Runway end identifier lights 

Visual approach slope indicator 

Touchdown zone 

Touchdown zone markings 

Touchdown zone lights 

Runway 

Runway markings 

Runway lights 

For operation below DA/DH or MDA – 

The following visual references for the intended runway 

must be distinctly visible and identifiable: 

Approach light system 

OR

Visual references in BOTH paragraphs 91.175(l)(3)(ii)(A) 

and (B) -- 

(l)(3)(ii)(A) The runway threshold, identified by at 

least one of the following – 

 -- beginning of the runway landing surface, 

 -- threshold lights, or 

 -- runway end identifier lights 

AND

(l)(3)(ii)(B) The touchdown zone, identified by at 

least one of the following – 

 -- runway touchdown zone landing surface, 

 -- touchdown zone lights, 

 -- touchdown zone markings, or 

 -- runway lights. 

Descent below 100 feet height above TDZE – 

At least one of the following visual references for the 

intended runway must be distinctly visible and 

identifiable: 

Approach light system, as long as the red terminating 

bars or red side row bars are also distinctly visible 

and identifiable 

Threshold 

Threshold markings 

Threshold lights 

Runway end identifier lights 

Visual approach slope indicator 

Touchdown zone 

Touchdown zone markings 

Touchdown zone lights 

Runway 

Runway markings 

Runway lights

Descent below 100 feet height above TDZE – 

The following visual references for the intended runway 

must be distinctly visible and identifiable: 

The lights or markings of the threshold 

 OR

The lights or markings of the touchdown zone 

4.4. Crewed Procedures 

The roles and responsibilities for the pilot/flight crew are identified by the Standard 

Operating Procedures (SOPs) in effect. SOPs are universally recognized to promote safe 

flight operations (see AC120-71A, “Standard Operating Procedures for Flight Deck 
20 

Crewmembers” 27 Feb 2003). This AC provides general guidance for the development 

of SOPs for crew sharing of responsibilities and duties in low visibility approach and 

landing operations. Further guidance is available for taxi operations (AC120-74A, “Parts 

91, 121, 125, and 135 Flight Crew Procedures During Taxi Operations,” 26 Sept 2006 

and AC91-73A, “Part 91 and Part 135 Single Pilot Procedures During Taxi Operations”).

These SOPs generally define who is responsible for the specific “aviate, communicate, 

and navigate” functions and how they are performed. These SOPs may change based on 

company/air carrier, but more typically, the SOPs change based on cockpit display 

configuration. The ACs do not, however, consider the impact of SEVS technologies and 

how roles and responsibilities may be modified by the introduction of these technologies. 

4.4.1. Pilot-Monitored Approach

The pilot-monitored approach (PMA) is commonly employed for head-down lowvisibility approaches.

As noted in the Commercial And Business Aviation Advisory Circular No. 0239 (dated 8 

Sept 2006) “proper use of the PMA permits the left seat pilot to improve safety related to 

making the decision to transition from instrument conditions to visual conditions for the 

landing. During a PMA, the left seat pilot has significantly more ‘heads-up’ time for 

visual scanning outside the flight deck. This extra time permits the pilot conducting the 

landing to determine whether sufficient visual references exist to judge the position and 

rate of change of position of the airplane in order to decide to continue the approach 

visually to a safe landing.” 

This operating policy minimizes the problem of visually transitioning from instrument 

flying to visual flying. Unfortunately, this operating policy involves a change of control. 

The left seat pilot (PNF or pilot-monitoring, PM) handles communications with the 

ANSP and makes decisions, while monitoring the flying performance. The right seat pilot 

(PF) may fly the approach with or without the engagement of autopilot or auto-thrust. 

The PF is engaged directly in either: 

Hand-flying the airplane, by flying the raw data (Cat. I) 

Actively following the flight director commands and monitoring the raw data 

(Cat. I or Cat. II); or, 

Supervising autopilot operation and being ready to take manual control of the 

aircraft, if required. 

The PNF scans alternatively inside and outside, calls flight parameter deviations (i.e., 

excess deviations in airspeed, pitch, bank, track, glideslope, altitude and vertical speed) 

and altitudes (e.g., “one hundred above” then “minimums”). 

Before or upon reaching the DA(H) or MDA, 

If visual references are acquired, the left-seat pilot calls “landing” takes over the 

controls and lands; or, 
21 

If visual references are not acquired, the left-seat pilot calls “go-around” and the 

right seat pilot initiates the go-around and flies the missed approach. 

If the left seat pilot commands a go-around, the right seat pilot (PF) flies the go-around 

procedure and missed approach as briefed. 

If the left seat pilot takes control for landing (now the PF), the right seat pilot (now the 

PNF) continues to monitor the aircraft performance on instruments (i.e., head-down) and 

calls out deviations.

In this procedure, the PNF recognizes and identifies the required landing visual 

references, assesses the suitability of the landing zone, and then is tasked with flying the 

approach, landing and roll-out without the assistance of the (formerly) PF (i.e., they are 

asked to remain head-down in the event of a go-around). The PNF does not have a visual 

transition from head-down to head-up at the instantaneous moment control is transferred. 

4.4.2. Pilot-In-Active Control Loop

The so-called “Pilot-in-Active Control Loop” assumes that there is only one HUD and it 

is equipped on the left-hand pilot side. The left-hand seat pilot flies the entire approach 

(as PF) with or without the engagement of autopilot or auto-thrust.

The right-seat pilot (PNF or PM) handles communications with the ANSP, monitors the 

approach, and assists in the acquisition of outside visual references. The PNF scans 

alternatively inside and outside, calls flight parameter deviations and altitudes. 

The PF confirms the acquisition of visual references and calls “landing” (or “go around” 

if visual references are not adequate). 

If “landing” is called, the PF progressively transitions from instrument flight conditions 

to external visual references using the HUD. 

There is no transfer of control and the PF is head-out through the entire approach and 

landing obviating the need to visually accommodate or re-focus. The PNF is both headout and head-down monitoring all systems and functions. With this procedure, two pilots 

are involved in identifying the required landing visual references and assessing the 

suitability of the landing zone.

4.5. EFVS Procedures 

4.5.1. EFVS Crew Procedures

Adaptations of the Pilot-In-Active Control Loop procedure have been created for EFVS 

operations. Since the regulation permits descent below the published DA/DH or MDA if 

the pilot distinctly identifies the required visual references (see Table II), additional callouts and procedures are used to distinguish between EFVS required visibility and natural 
22 

vision and the fact that only the PF, using the EFVS, can positively identify and use the 

required EFVS visual references.

In a crewed experiment, various display formats for the PF HUD and the PNF repeater 

display of EV imagery were experimentally tested while using these crew procedures (see 

Bailey, Kramer, Prinzel, and Wilz, 2009). In Table III, the crew call-outs are shown, 

indicating that an aditional step – the call-out and identification of “EV Lights” – was 

required to descend below the published DH. If the “EV Lights” was not called out, a 

go-around was executed at the DH. If “EVS Lights” was called, the next decision 

altitude was at 100 ft HAT where the lights or markings of the threshold or the lights or 

markings of the touchdown zone had to be distinctly identified by the PF to continue the 

approach to landing.

The PF was responsible for flying the aircraft, confirming the acquisition of visual 

references; first, the EFVS visual references and then, the natural vision references (or 

“go around” if visual references are not adequate). The PF had the option to declutter the 

HUD and not use EV imagery for the landing; although the PFs thought the procedure to 

identify the landing references with natural vision was awkward (e.g., they would 

momentarily declutter the HUD to remove the EV imagery or look around the HUD), the 

PFs kept the EV on the HUD and used this information to complete the landing and rollout (Kramer, Bailey, and Prinzel, 2009b). 

The experiment generally showed the effectiveness of EFVS and the EFVS crew 

procedures. Improvements to the procedures and call-outs were suggested, but in 

general, the roles and responsibilities of the crew using EFVS procedures extended from 

current Pilot-in-the-Active Control Loop were validated. 

Head-position and orientation tracking data was collected of the PM to quantify display 

usage and visual gaze/attention. The data showed that attention was divided between a 

repeater display of EV information, the normal flight instruments, and the forward, OTW 

view from 1000 ft AFL until 200 ft AFL. The PM scanned alternatively inside and 

outside, called flight parameter deviations and altitudes. Below 200 ft AFL, the PM was 

almost exclusively head-up, looking OTW, searching and clearing the landing runway 

area (Bailey, Kramer, and Prinzel, 2007). 
23 

Table III - EFVS Crew Procedures

Altitude-Based Events PF

Tasks / Callouts 

PNF 

Tasks / Callouts 

500 feet HAT Response: “Systems Normal, EV 

Normal”

Call “500 feet”

100 feet Above 

Minimums 

Response: “Check” Call “100 feet Above”

Published Minimums 

(200 ft HAT) 

With EV Visual Cues,

Call “EV Lights”

When Visual Cues Appear,

Call “Lights” or “Field in Sight”

Without EV Visual Cues,

Call “Going Around”

Without PF Call of ‘EVS Lights’, Call

“Go Around”

EFVS Decision Altitude 

(100 ft HAT) 

When Actual Visual Cues,

Call “Landing”

When Visual Cues Appear,

Call “Lights” or “Field in Sight”

Without Actual Visual Cues,

Call “Going Around”

Without PF Call of ‘Landing’,

Call “Go Around”

4.5.2. EV Head-Down Crew Procedures

Head-down EFVS operations are not currently authorized by the FAA; however, since 

HDDs are cheaper and more widely available than HUDs, evaluation of their potential for 

EFVS has been explored.

Two variations of the PMA crew procedures have been tested. In both cases, the PF was 

using a HDD of EV information and guidance to descend to the published DA/DH. Two 

different piloting procedures were tested once the required landing visual references were 

identified:

1) The PF transitions from EV head-down to head-up, using natural vision; or, 

2) Aircraft control is transferred from the head-down PF to the head-out pilot, who 

continues the approach to landing using natural vision. 

Four subject pilots flew these two HDD EFVS procedures and in comparison, a standard 

head-down PMA to 200 ft Instrument Landing System (ILS) minimums and an EFVS 

Pilot-in-Active Control Loop procedure using a HUD. 

This work showed that there were no performance differences between the procedures. 

No problems were reported in immediately identifying the runway OTW after 

transitioning from head-down to head-up. The depiction of the runway in the EFVS 

guided them to the right location to look for the runway. The post-flight debriefings 

indicated that the pilots had “good and comprehensive transition from EV head-down 

segment to visual flight without impairing flight path.” 

However, the results for the PMA procedures using a control transition at the EV 

transition height evoked some controversy among the pilots. Two pilots liked this 
24 

switching from PNF to PF and vice versa whereas the other two stated that this was not a 

good idea below the DA(H). One pilot had a “crash” where the landing sink rate 

exceeded acceptable structural limits. 

4.5.3. EV Single-Pilot Procedures

Single pilot EFVS operations are not currently approved or authorized by the FAA. The 

pilot in this operation would have to successfully fulfill all required duties and complete 

all tasks currently conducted by two pilots, with acceptable pilot workload and safety 

margins. 
25 

5. Traffic/Obstacle Detection Using SEVS Technologies

Within the context of the crewed and single pilot procedures for low visibility approach 

and landing operations, the influence of SEVS technologies are discussed as they pertain 

to pilots performing the role of PM or of PF. 

Visual target detection using SEVS technologies can be achieved through any of four 

possible avenues: 

1. Using EV on a HDD 

2. Using EV on a HUD 

3. Using the OTW view, through a HUD 

4. Using the OTW view 

5.1. Automatic Target Detection and Recognition 

This work does not currently consider concepts for fused or combined EV and SV 

systems although they have been studied and some of the results are germane to this 

discussion.

Several studies (Parrish et al, 2003; McKay et al, 2002) have shown that the optimal 

combination of SV and EV technology is one that provides the direct display of SV to the 

flight crew without direct display of EV. Instead, EV technology is used “behind the 

glass” for automatic navigation error detection, database integrity monitoring, and realtime obstacle/object detection. Image processing performs these functions automatically 

without intervention by the flight crew.

This arrangement provides a highly usable display presentation (i.e., SV) that is 

unaffected by the actual weather and visibility conditions, yet if un-charted obstacles, 

traffic, database errors or navigation errors are detected by the EV running in the 

background, the situation is annunciated, and almost “perfect” decision-making by the 

pilot occurs. This advantage was also shown by Jennings and Powell (2004) where 

runway incursion scenarios were detected during simulated instrument conditions much 

more quickly using Automatic Dependent Surveillance-Broadcast (ADS-B) transmission 

of traffic data and graphical representation on an SV display than OTW visual detection. 

While degrees of success in developing these decision aids have been met, technology for 

“perfect” object detection and database/navigation error detection does not yet exist. 

Further, there may always be gaps, such as minimal radar cross-section objects or 

‘below-detection’ threshold errors, which may still warrant flight deck procedures and 

human interventions for integrity and error monitoring. Research should be conducted to 

determine the desired/required missed detection and false alarm rates for a SV which 

utilizes ‘behind the glass’ processing for automatic database, obstacle/object, and 

navigation error and omission checking (R-4). 
26 

5.2. Resolution Influence of Detection and Recognition 

In the absence of “behind the glass processing,” EV imagery has been touted as providing 

an element of traffic detection above and beyond unaided natural vision. While this 

seems intuitive, the capabilities of the imaging sensor and the prevailing weather, target 

and background determine the level of success. Detection and recognition is dependent 

upon the sensor resolution and its sensitivity to the environment and “target,” the size and 

contrast of the obstacle/object against the image background, and the display resolution 

(Mendez, Freitag, and Zinn, 1972; Arthur et al, 2005)

To illustrate technological capabilities and limitations, Johnson’s criteria is used. The 

hypothesized scenario is a Cessna-172 holding short for take-off the runway threshold.

Computer-generated images of the scenario are shown in Figure 5 at 500 ft height above 

the TDZE (HAT), Figure 6 at 300 ft HAT, Figure 7 at 200 ft HAT, and finally, Figure 8 

at 100 ft HAT. The C-172 is 27 ft in length and 36 ft in span. The images show 43 

degrees horizontal field-of-view with a 4:3 H:V aspect ratio. A ‘best-case’ scenario is 

considered in these examples, where the larger dimension (span) is used to predict the 

detection and recognition range. Also, no degradation in target contrast is implied due to 

atmospheric effects or background characteristics. 

Using Johnson’s criteria (see Table I) and computing the number of pixels required as 

being twice the number of line pairs plus one, 3 and 9 pixels are required for detection 

and recognition, respectively, of the C-172. Using these assumptions, the number of 

pixels that the C-172 subtends in an image is computed in Table IV. 

Two different resolutions are shown comparing a typical EV system performance and a 

hypothetical sensor system could theoretically provide eye-limiting resolution. Presentday commercial FLIRs (for EFVS applications) employ approximately 320 x 256 pixel 

resolution, spanning a typical HUD Field-of-View (FOV) of 32o

 H x 24o V for the 

conformal image. This provides approximately 10 pixels per degree visual resolution. In 

comparison, the Snellen visual acuity equivalent to 20/20 of 60 pixels per degree is also 

shown. The sensor in this latter case would employ 1920 x 1440 pixels. 

Table IV– Pixels Subtending the Lateral Extent (36 ft) of C-172

Altitude 320x256 pixel EV 

(10 pixels per degree) 

20:20 Snellen Equivalent EV 

(60 pixels per degree) 

500 ft HAT 2 pixels 14 pixels 

300 ft HAT 4 pixels 26 pixels 

200 ft HAT 7 pixels 43 pixels 

100 ft HAT 22 pixels 136 pixels 
27 

Figure 5: View of C-172 Holding Short From Aircraft at 500 ft HAT

Figure 6: View of C-172 Holding Short From Aircraft at 300 ft HAT 
28 

Figure 7: View of C-172 Holding Short From Aircraft at 200 ft HAT 

Figure 8: View of C-172 Holding Short From Aircraft at 100 ft HAT 
29 

These numbers highlight that a typical EV resolution is relatively poor and the range for 

target detection is typically much closer than if the human were viewing OTW. The C172 will only subtend sufficient angular size in the EV for detection at approximately 300 

ft HAT and for recognition only after descending below 200 ft HAT. The performance, 

based on resolution comparisons, is 6 times worse than a human observer looking out the 

window.

This is not to say that the EV can’t provide detection of the target. The advantage of an 

EV system is that it may provide a higher contrast image than the out-the-window view 

(e.g., a hot C-172 imaged against a cold runway background). It may also be that the EV 

can penetrate the atmosphere whereas the human’s natural vision is obscured. 

However, this simple example highlights that resolution is just one ingredient – but an 

important prerequisite - to traffic/obstacle detection. Performance data for target 

detection tasks must colored by the resolving capabilities of the EV and the OTW visual 

system especially when flight simulation is used. The resolution capabilities of 

simulators are typically much, much less than that of the human vision system. 

5.3. Traffic/Obstacle Detection by PM With SEVS Technologies 

In a crewed experiment, the presence and absence of symbology on a head-down repeater 

display of EV imagery for the PNF was experimentally tested while EFVS approaches 

were flown (see Bailey, Kramer, Prinzel, and Wilz, 2009). Runway incursions were 

introduced on two occasions unbeknowst to the crew and interspersed in a large number 

of nominal data runs. 

As noted by Kramer et al (2009b), almost all obstacle detections were made by the PNF 

using their natural OTW vision. 

It was hypothesized that the PNF made almost all of the detections because the PF is 

primarily focused on flying the aircraft, while the PNF, serving as a PM, had the primary 

responsible responsibility of monitoring and verifying flight path performance, crosschecking guidance and raw data indicators, and identifying the visual runway 

environment and clearing the landing area. 

This work also suggests that the PNF could not effectively use the repeater display of EV 

information for “clearing” the runway for obstacles. Johnson’s criteria, applied to the EV 

system and the runway “targets,” indicated that the EV information was not of sufficient 

resolution to be useful at 400 to 500 ft HAT for target detection, in the area where the 

PNF was using the repeater display (Bailey, Kramer, and Prinzel, 2007). Below 200 ft 

HAT, the EV repeater would be effective at showing traffic on the runway, but by this 

altitude, the PNF had transitioned to OTW and was not using the repeater display. 

This work showed that the PM has the attentional resources and innate responsibilities for 

runway incursion detection (i.e., target detection). However, the HDD of EV imagery 

was not tailored for this obstacle/object detection task. To detect obstacles using this 

device required higher sensor resolution to detect objects at the altitudes and ranges 
30 

where the PM desired to use the display (above 200 ft HAT). A zoom (magnification) 

capability would be needed to effectively increase the resolution of the sensor/display 

image before the aircraft transitioned into the visual segment. Magnification was also 

shown to be desirable in a study by Theunissen (2004). 

This work had some limitations which influence the global applicability of the data: 

1) This work did not look at the presence or absence of a repeater display. In the 

US, a repeater display of EV information is not required during EFVS 

applications; however, in Europe, a repeater display is required.

2) This work did not look at variations in size or display minification/magnification 

effects for the repeater display of EV information. 

3) CDTI influences were not evaluated. 

4) Variations in the repeater display location were not evaluated. The PNF display 

was located outside of the primary field-of-view of the crew (see AC25-11, 

“Electronic Flight Deck Displays,” 27 June 2007) to the outboard and right of the 

forward instrument panel. A forward primary location may have enabled the PNF 

to quickly glance at the repeater display at lower altitudes and still maintain 

vigilance OTW. 

An evaluation of EV/SV information for the PM to perform navigation integrity, obstacle 

detection, and runway incursion detection resulted in relatively mediocre performance 

(McKay, Guirguis, Zhang, and Newman, 2002). The evaluations were flown as a single 

pilot, with the lone pilot serving as a PM. During low-visibility auto-flight landings 

where all runs included an “anomaly” (e.g., SV database misalignment, runway 

incursions, or uncharted obstacles), the evaluations showed that (see Figure 9): 

• The best performance - fewest missed detections - were found when the PM had 

automatic, ‘behind-the-glass’ detection capability (i.e., “Threat Icons”). 

• Using an EV-only HUD (“EVS HUD” in Figure 9), 57% of the obstacles were 

undetected and 50% of the runs with the database misalignment went 

undetected 38% of the runway incursions went undetected. Despite this 

relatively poor performance, the pilots subjectively preferred this 

implementation overall. 

• A Primary Flight Display concept, showing SV with a pilot-controllable EV inset 

image (“EVS Insert” in Figure 9), exhibited the worst performance for 

anomaly detection. The PFD inset concept “missed” 100% of the uncharted 

obstacles and a 33% rate of missed detections for the database misalignments. 

Detection of runway incursions showed a missed detection rate of 33%. The 

poor performance and low-acceptance of the head-down EV insert concept 

was attributed to the clutter of the image, the small EV image size, and 

confusion between the SV/EV images. A preference for control of the EV 

sensor image in an inset display has been shown elsewhere (Theunissen et al, 

2004), but pilot workload was shown to increase because of the additional 

pilot control for display management. 
31 

• With EV-only shown on a HDD (“EVS HDD” in Figure 9), all uncharted 

obstacles were successfully detected but 33% of the runs missed the database 

misalignment. A missed detection rate of 22% for runway incursions was 

found. This concept was well liked for its large image size and minimal 

display clutter, but disliked because of the workload in transitioning from 

head-down to head-up flight.

The data suggests that a head-down display without imagery provides the best 

opportunity for obstacle and traffic detection. The larger the display the better, but a 

HUD presentation was preferable, especially if all symbology could be decluttered and if 

the full dynamic range of the EV image could be presented. Research should be examine 

head-down vs. head-up performance for the PM, with experimental variations in display 

size, location, and minification/magnification (R-5)

0% 20% 40% 60% 80% 100%

EVS Insert 

EVS HDD

EVS HUD

Threat Icons

Miss Rate - SV Misalign

Miss Rate - Incusions

Miss Rate - Obstructions

Runway Incursion 

Icon

Figure 9: PM Evaluations Using SEVS Technology
32 

5.4. Traffic/Obstacle Detection by PF With SEVS Technologies 

The use of a HUD is deemed an essential “characteristic and feature” of the EFVS 

operation (FAA, 2004a) and as such, HDD implementations for EFVS are currently not 

allowed. The “essential features” of the HUD were described as follows: 

• The display should provide the EV image and spatially-referenced flight 

symbology so that they are aligned with and scaled to the external view (i.e., 

conformally drawn). 

• The display should be located so the pilot is looking forward along the flight path 

(i.e., looking at and through the imagery to the out-of-the window view) to 

readily enable a transition from EFVS imagery to the out-the window view. 

• The display should not require the pilot to scan up and down between a head 

down display of the image and the out-the-window view looking for primary 

flight reference information. This transition would be hindered by repeatedly 

re-focusing from one view to the other. 

In contrast to this mandate, the feasibility of an EFVS head-down procedure has been 

examined in simulation (Korn, Lenz, and Biella, 2007). This work was a follow-on to 

previous experimentation on crew coordination which focused principally on head-down 

displays and the application of a millimeter-wave radar sensor for EFVS (and its 

idiosyncrasies associated with transformation from an azimuth and range data to an 

egocentric, perspective display) (Lorenz and Korn, 2004). This work suggested that 

head-down operations in low visibility conditions was feasible, although not necessarily 

without potential limitations, especially if a change in aircraft control, from PF to PM, 

was necessary at low altitude.

Head-down to head-up transitions from instrument to visual flight conditions without a 

HUD - the process of looking up from a head-down instrument panel, refocusing and 

accommodating to the outside visual field, and perceiving and reacting to visual stimuli 

in the external scene - may take as long as 2 to 5 sec (Fisher, 1979). Pilots were observed 

to make from 4 to 14 separate head-down to head-up transitions during low visibility 

approaches, dependent on the simulated visibility and ceiling height. More transitions 

were made for higher ceiling heights and visibility conditions as the pilot’s maintained a 

continuing cross-check between the head-down instruments and external visual cues. 

The advantages of a HUD by minimizing visual scanning, accommodation, and refocusing when transitioning from instrument to visual flight conditions are well founded 

in research (Wickens and Long, 1994; Lauber et al, 1982; Martin-Emerson and Wickens, 

1997; Weintraub and Ensing, 1992; and Newman, 1995). The HUD visual transition 

effects have even been shown in ground vehicle transportation studies (e.g., Liu and 

Wen, 2004). These perceptual advantages were felt to contribute toward superior lateral 

touchdown performance using a HUD compared to HDDs for a transition to visual 

references, although no improvement in longitudinal touchdown performance was shown 

(Goteman, Smith, and Decker, 2007). 
33 

Wickens and Long (1994) also reported a significant improvement in tracking 

performance prior to breakout when GA pilots flew a HUD in an ILS approach task. The 

improvement was attributed to the fact that pilots didn’t have a need to “divert attention 

away from the symbology” when head-up to find the runway at the break-out from 

instrument conditions. This observation was also supported by an (non-significant) 

improvement to recognize and confirm when the runway first became visible. 

An attempt was made to quantify how these perceptual demands might impact 

quantitative approach performance. Performance-based approach standards from the 

Joint Aviation Authorities Joint Aviation Requirement All Weather Operations were 

applied to capture the effects of transition from head-down to head-up using natural 

vision or head-up EFVS to head-up natural vision (Kramer, et al, 2009a; Kramer et al., 

2009b). These analyses showed that eliminating any visual transition improved tracking 

performance. However, the differences were not large and not statistically significant. 

Nonetheless, the trends make intuitive sense. By allowing the pilot to concentrate on the 

task and display information, improved flight tracking performance results. The HUDvisual segment transition allows the pilots to simultaneously perform glideslope 

corrections and acquire the required landing visual references through normal vision. If 

the pilots did not have to shift their attention, tracking performance improved. 

These HUD advantages are not, however, provided without complications, limitations, or 

penalties as discussed in the following. When using HUDs (or other virtual displays), the 

pilot’s accommodation and cognition are influenced by numerous complex and 

interacting HUD factors, creating sometimes contradictory findings (Edgar, 2007). From 

Edgar (2007), these factors include: 

1. The HUD image occludes parts of the background; 

2. The HUD image is displayed proximal to the use (i.e., the HUD combiner), near 

an individual’s accommodation distance;

3. The user’s attention is directed to the HUD image; 

4. The HUD presents information to be processed by the user; 

5. The HUD image is monochromatic; 

These factors have been historically, but not necessarily accurately, lumped into two 

issues: clutter and attention capture. These are discussed in the following in reference to 

obstacle and traffic detection. 

5.5. Clutter 

Display clutter, especially for HUDs, has historically been a concern (e.g., Newman, 

1980) and the increased use of EFVS for HUDs pushes this issue to the forefront (e.g., 

see Zuschlag, 2001). The goal of a display design should always be to minimize visual 

clutter. Only graphical elements that “add useful information content, reduce flight crew 

access or interpretation time, or decrease the probability of interpretation error” should be 

used (AC 25-11).
34 

One universal definition of visual clutter is not available. Various clutter definitions have 

been proposed which typically group by (Kaber et al, 2008): 

Content or format of the data 

Degraded performance of the operator using the display 

Irrelevant information to the task at hand 

The current clutter definition under AC25-11 (“Electronic Flight Deck Displays”) 

includes each of these properties:

“A cluttered display presents an excessive number or variety of symbols, colors, 

and/or other unnecessary information and, depending on the situation, may 

interfere with the flight task or operation. A cluttered display causes increased 

flight crew processing time for display interpretation, and may detract from the 

interpretation of information necessary to navigate and fly the airplane.”

Note that the use of a “de-cluttering” function is also formalized for the express purpose 

“to enhance pilot performance” under AC25-11. In fact, under the EFVS rule within 

§91.175(m), the “displayed imagery and aircraft flight symbology do not adversely 

obscure the pilot’s outside view.” Under the MASPS for EFVS and SV (RTCA DO315), requirements are contained such that “a control shall be provided which permits the 

pilot flying to deactivate and reactivate the display of the EFVS image on demand 

without removing the pilot’s hands from the primary flight controls (yoke or equivalent) 

and thrust control.” 

Display clutter contains two critical aspects. 

First, clutter exists from a “bottoms-up,” data-driven aspect, addressing the effect 

of clutter to confuse or obscure visual information in terms of the “physical” 

attributes of the display due to the number of display elements, their size, form, 

proximity, and luminance (Alexander et al, 2008). These issues are influential 

both in a local domain, referring to the area immediately surrounding “critical” 

display areas and in the global domain, associated with entire display and display 

area, in general.

Display clutter also includes a “top-down,” knowledge-driven aspect, addressing 

the effect of visual information on human cognitive processing and attention. The 

issues of particular interest are the relevancy and redundancy of the displayed 

information. Clutter involves the display content and its influence/relevancy to 

the piloting task at hand (Kaber et al, 2008). 

Display clutter, therefore, involves the physical attributes of the display and its content 

and its influence/relevance y to the piloting task and cognitive/attentional demands 

(Kaber et al, 2008). Experimental evidence suggests that pilot experience modulates the 

perceptions of clutter with high-time, HUD experienced pilots being more accurate and 

consistent in judging the occurrence of clutter. Pilots with prior HUD experience also 

appear to be more consistent in relating display clutter to perceptions of cognitive load. 
35 

Clutter is linked – as discussed below – with attention capture. 

A key element that is missing in this foundational work is the influence of actual HUD 

operations in relevant weather and operational contexts especially considering the 

inherent luminance limitations of the HUD and the seemingly unlimited luminance and 

coloration of the real-world. Research should be conducted evaluating qualitative and 

quantitative metrics of clutter in actual flight conditions (R-6).

5.6. Attention Capture 

Attention capture is the phenomenon wherein a pilot fixates their attention to one 

task/element at the expense of ignoring other potentially critical task information. This 

phenomenon has been reported in human factors and aviation psychology research 

literature and attributed to several accidents, particularly associated with the use of a 

HUD (e.g., see Crawford and Neal, 2006; Prinzel and Misser, 2004). In those cases where 

it was observed, the authors typically concluded that pilots flying with a HUD were less 

likely to detect an unexpected “event” in the “far domain” because of their fixation on the 

HUD and its symbology (i.e., the “near domain”). 

Because of the great emphasis on attention capture with HUD usage, and its potential role 

in traffic/object awareness and detection, pertinent literature are reviewed. 

The most often cited case of HUD attention capture was a simulation experiment using 8 

pilots (Fischer, Haines, and Prince, 1980) flying a low visibility approach and landing 

task. Four runs were flown without expectancy for the runway incursion with the HUD; 

four runs without HUD. The simulated weather had a 180 ft cloud deck, in 2000 ft RVR. 

With this weather, if the aircraft were on glideslope, the pilots might be able to first 

detect the incursion at approximately 160 ft HAT. 

The data, at first glance, makes a compelling case for HUD attention capture. In all of 

the non-HUD runs, the flight crew noted the incurring vehicle. In half of the HUD runs, 

the runs “resulted” in an incursion. 

Upon closer inspection, however, the data (shown in Figure 10) contained many 

unintentional confounds and it isn’t nearly as neat as described as above. First, two of 

non-HUD runs were spoiled by experiment protocol. The confederate FO inadvertently 

contaminated or terminated the runs. Thus, two out of four non-HUD runs did not result 

in an incursion; the other two didn’t count. Second, one of the HUD runs which was 

claimed to “result” in a runway incursion was actually terminated at an altitude higher

than one of the “detected incursions” in the no-HUD condition (i.e., the HUD run 

terminated at 67 ft HAT, whereas the pilot in a non-HUD run spotted the incursion at 63 

ft HAT). Finally, inspection of the data showed that the non-HUD pilots had relatively 

poor ILS tracking performance and were significantly below the glideslope, resulting in a 

longer time for “visual conditions” than the HUD pilots who flew on glideslope. As a 

rule of thumb, the pilot only had ~10 seconds from 160 ft HAT to 60 ft HAT to see the 

traffic and initiate a go-around or the confederate FO would terminate the run. 
36 

(Note that their second runs – with full expectancy of an incursion event – resulted in 

better detection performance with the HUD. The pilot’s were flying head’s up and 

therefore, had better performance since they didn’t have to transition from head-down to 

head-up.)

Despite these confounds, the “attention capture” conclusion from this work spawned 

numerous other research efforts to identify its physical and/or psychology mechanisms. 

Figure 10: Data From Fischer et al (1980) For Runway Incursion Event

Excellent summaries of attention capture and associated research are contained in Prinzel 

and Risser, (2004), Crawford and Neal (2006), and Edgar, 2007. Weintraub and Ensing 

(1992) suggest that cognitive switching is “impeded by: a) optical clutter; b) the 

conformal aspects of the symbology; c) the lack of physiological change (e.g., in 

accommodation, in convergence, in gaze angle) to serve as cognitive signals to switch 

attention.” The cognitive switch might also be impeded by the compelling nature of the 

HUD flight-director/command symbology. 

With 20/20 hindsight provided by the many years and the numerous studies conducted 

since on this subject, six factors seem to emerge as profoundly influential in HUD 

attention capture research: 

1. OTW Visual Fidelity 

2. HUD Optics 

3. Conformal Symbology 

4. Brightness, Contrast, and Declutter 
37 

5. Type of Event 

6. Pilot Experience and Training 

These factors follow Edgar’s list of confounding factors (Edgar, 2007) in accommodation 

and cognition using virtual displays and include some of what is already known about 

perceptual grouping and attention capture for virtual displays and HUDs (see for 

example, McCann, Foyle, and Johnson, 1993). 

More importantly, these factors are expanded upon as they are not often considered or 

factored into the empirical/applied aviation research which identified “attention capture” 

as a safety factor in the use of HUDs. These factors possibly describe how attention 

capture “problems” found in laboratories, run counter to operational data: 

A study by the Flight Safety Foundation (2009) found that HUDs prevented or 

positively influenced 38% of accidents overall in modern glass cockpits. Of these 

accidents where the pilot was directly involved, such as takeoff or loss-of-control, 

the “safety advantage” of the HUD became much higher (69% and 57%, 

respectively).

Development and certification flight testing of Head-up Guidance Systems for 

manual Cat. III landings (Green, 1988) initially included concerns for HUD 

attention capture. However, test experience noted that “a pilot can become 

engrossed with any control task. Fixation, or a narrowing of his horizon of 

perception to extraneous cues, can occur heads-down in a tracking task as well as 

heads-up.” The flight data noted that “at no time in the flight program did any 

pilots comment about a fixation problem associated with the HUD, or notice any 

reduced capability to either scan for traffic or detect unexpected traffic while 

maneuvering in a terminal area.” 

5.6.1 OTW Visual Fidelity

A critical aspect of attention capture is the saliency or similarity between the HUD (“near 

field”) and OTW visual field (“far field”). As noted by Crawford and Neal (2006), “if the 

HUD is more salient of the two domains, these elements of the external world, especially 

those that are unexpected, may be more difficult to detect.” 

The OTW visual fidelity in laboratory or simulator evaluations creates a critical 

difference of HUD attention capture compared to the flight environment. Notable 

laboratory / simulation tests showing attention capture (e.g., Hofer et al, 2000; Fischer, 

Haines, and Prince; 1980; Wickens and Long, 1995) provided 20:60 visual acuity at best. 

Based on acuity alone, with these degraded visuals, pilots must be twice to three-times as 

close to an incurring vehicle for detection as could be expected in-flight. As noted in 

Section 5.2, the visual acuity of present-day EFVS HUDs provides only 10 pixels per 

degree resolution – one-sixth of a human’s normal visual acuity. Therefore, in-flight, 

there is a significant difference in acuity between the HUD and the OTW, promoting 

salient differences. In laboratory or simulator evaluations, these acuity and saliency 

differences may not be present. 
38 

Because of degraded OTW visuals, pilots were deprived of or received degraded OTW 

visual cues critical to the task. In the absence of OTW visual cues, pilots can become 

reliant on the HUD guidance symbology for flight control, drawing attention and focus 

unnaturally toward the HUD at the expense of the OTW (Weintraub and Ensing, 1993). 

Another notable component in far-field/near-field saliency is the visual cueing/fidelity of 

the OTW target depiction and lighting. Especially in low-visibility and night operations, 

airport and traffic lighting is a critical visual cue. Calligraphic lighting is critical 

simulation tool to mimic realistic lighting effects; these point light source effects were 

notably absent in almost all instances of HUD attention capture research. Their absence 

degrades the saliency of the OTW scene and thus, promotes HUD attention capture. One 

could argue that not all “targets” of interest have lights. However, even though a target 

may not have lights, the fact that a repeatable pattern of lights is absent due to 

obscuration or shadowing also provides visual cues (e.g., see AC91-73A).

Emerging technology trends suggest possible trending toward HUD attention capture: 

State-of-the-art Liquid Crystal Display HUDs are moving to much higher 

resolutions, nearing eye-limiting acuity. This trend would suggest a reduction in 

saliency differences between the HUD and OTW visual fidelity.

Fortunately, the underlying resolution of FLIRs are remaining, for the foreseeable 

future, at approximately 320 Horizontal x 240 Vertical pixel resolution because 

higher FLIR resolution would trigger unwanted export restrictions associated with 

International Trafficking Acquisition Regulations. (The lower resolution FLIR 

signals are being mapped to the higher resolution HUD video formats.) 

EFVS HUD operations would suggest a trend toward HUD attention capture 

given that, by definition, the HUD imagery contains more information than 

provided in the natural vision spectrum. The HUD attention capture literature is 

also devoid of this effect, as discussed in Section 5.3.

Research should be conducted using high fidelity simulation and flight testing; evaluating 

HUD attention capture effects in very low visibility operations (visibilities less than 700 

ft) where the saliency becomes less distinct (R-7). 

5.6.2 HUD Optics

A vast majority of HUD attention capture research didn’t, in fact, use a real HUD, but 

instead, simulated HUD operations by embedding the HUD imagery into the OTW visual 

scene (e.g., Fischer, Haines, and Prince, 1980; Weintraub, Haines, and Randle; 1985; 

Wickens and Long, 1995; Ververs and Wickens, 1998; Hofer, et al, 2000). The 

simulations created the case where the OTW and HUD imagery were at the same optical 

distance. Using this simulation methodology, unfortunately, masks the perceptual 

differences of the HUD and the OTW. It also emphasizes obscuration of the OTW by 

HUD symbology. 
39 

HUDs also include other critical factors which optically promote the differentiation 

between the HUD and the OTW visual scene: 

1. Real HUDs are not focused at infinity (Gibson, 1980).

The design goal of a HUD is to provide a virtual image at optical infinity but 

HUD optical systems are not perfect; there are residual uncompensated optical 

errors in the optical system. As such, HUDs are typically focused inside of 

optical infinity. (As described in SAE AS8055, minimum acceptable errors in 

monocular positional accuracy are specified. The complication arises that these 

errors can cause binocular parallax errors. Stringent requirements are in place to 

limit optical errors which might cause a pilot’s eyes to angle outward (divergent 

errors) because pilots cannot easily accommodate these errors (Gibson, 1980). As 

such, HUD optics are typically biased toward convergent errors (apparent display 

depth to vary inside of optical infinity across the field-of-view) but beyond 

resting-eye focus. The net effect is that perfect conformal overlay is not provided 

by a real HUD. Head movement will generate some degree of differential motion 

between the HUD symbology and the OTW visuals, thus, promoting attention 

switching.)

2. Pilots don’t have perfect vision: 

Disparity between the HUD virtual image and the OTW imagery is further 

differentiated by pilots not having perfect vision. Any disparity in visual 

performance between a pilot’s left and right eye will exacerbate the imperfection 

from an ideal “optical infinity” design. 

3. HUDs have distinct eye boxes: 

HUD optics have a distinct eye box over which the exacting design requirements 

for monocular and biocular performance are specified. However, outside of this 

eye box, the pilot can view an unobstructed, uncluttered view of the world by 

head movement, which clearly separates the “near domain” and “far domain” 

information. 

4. Real HUDs have limited luminance and distinct coloration: 

P-43 phosphor provides a unique green color which is almost unique in the 

outside world, so the probability of “color obscuration or clutter” with an object in 

the real-world is improbable, lending support that the HUD will be perceived as a 

separate entity from the OTW, supporting attention switching (McCann, Foyle, 

and Johnson, 1993).

Emerging technology trends are, again, trending toward HUD attention capture 

principles:

Color HUDs are not yet a present-day reality but if they come to fruition, very 

careful color coding will be necessary to ensure a minimum of color-obscuration 

and to support attention/domain switching by color differentiation. 

Optics designs are emerging to create much larger design eye boxes. Increasing 

the size of the eye box would lessen the perceptual switch between the “near 

domain” HUD and “far domain” OTW visual information. 
40 

Research should be conducted evaluating the impact of color HUDs (and head-worn 

display or virtual display) on attention capture, clutter, and target detection (R-8). 

5.6.3 Conformal Symbology

Human information processing is constrained by attention limitations. Scene-linked 

symbology has been shown to be a necessary but perhaps not sufficient means to support 

simultaneous processing on instrument information and far domain information. 

(McCann and Foyle, 1995). This use of “scene-linked symbology” - where these 

symbolic references are located such that they overlay a real-world position and move 

and transform as though they were actual objects in the world - facilitates efficient 

cognitive processing and mitigates problems of attention tunneling and symbology 

fixation.

Real HUDs are composed of conformal and non-conformal elements. This mix of 

symbology types emphasizes attention/domain switching via differential motion 

(McCann and Foyle, 1995).

HUD symbolic changes and aural cues are employed by design and/or standard operating 

procedures to ensure attention/domain switching. For instance, HUD systems may use 

conformal runway edges for visual momentum and acquisition on the approach, but they 

disappear at 50 ft, creating a visual change - a visual vacuum as it were - that is filled by 

the outside runway edge environment (Green, 1985). Automatic or crew call-outs of 

altitudes and runway status aid this attention switch. 

Perfectly conformal symbology in real HUDs is not possible. In Section 5.2.2, the optical 

distortions of real HUDs were discussed and these negatively impact conformality. 

Further, the latency involved in signal processing to sense, compute, and draw conformal 

HUD imagery creates inaccuracies in its representation against a real-world object. 

Excessive delay creates symbology “swimming” which, as the latency increases, 

eventually becomes unacceptable (Bailey et al, 2004). 

Research should be conducted evaluating the impact of imprecision in conformal HUD 

symbology (statically and dynamically) on attention capture effects and the ability of the 

pilot to use EFVS imagery especially as it is the predominant source of visual 

information for landing in very low visibilities (<700 ft visibility) (R-9). 

5.6.4 Brightness, contrast, and declutter

HUD attention capture (and clutter) has been shown to be dependent upon the symbology 

contrast (Ververs and Wickens, 1996 and 1998). This result is intuitive, given that the 

apparent contrast (luminance of the “near domain” symbology against the background 

“far domain” background) directly impacts saliency. 

Unfortunately, this degree of freedom has too often been an experimental confound in the 

attention capture research. It was noted in Hofer et al (2000) that “one of the pilots 
41 

commented that the HUD was worse for switching and would induce tunneling, when the 

tactical symbology was too bright; this is why it was suggested to turn down the 

symbology brightness to make it less compelling and to detract less of the pilot’s 

attention.” Ground simulation is notoriously poor at reproducing real-world HUD 

operations - critical in the evaluation of cognitive switching (and the potential for 

cognitive capture) and occlusion.

While real-HUDs may be used in simulation – simulating eye box effects and imperfect 

optics - the evaluations are compromised by the very limited luminance output of the 

external scene, out-the-window projectors. The limited luminance (less than 50 ft-L 

typically) of the OTW often creates a biased evaluation between the HUD imagery and 

the OTW – critical for object and obstacle detection – especially without experimental 

control of the HUD brightness settings. The transmissivity of the HUD combiner also 

corrupts the contrast and brightness of objects when looking through the HUD to the 

point where they may not be perceptible. “Burn-through” of landing lights is an 

important visual element of HUD low visibility EFVS operations which is not often 

simulated because of the limited luminance output of the OTW visuals and the HUD 

combiner transmissivity. Thus, the low luminance of the OTW background may bias the 

perception of the HUD imagery as it depends upon the background illumination. 

Emerging technology is trending toward HUD attention capture concerns: 

Emerging Liquid Crystal Display HUDs replacing CRT-based systems can 

provide much higher luminance outputs, enabling full sunlight-readable imagery. 

Moving toward much higher luminance levels would suggest: a) a possible 

reduction in saliency differences between the HUD and OTW visual fidelity; and 

b) a higher propensity for symbology obscuration of OTW visual information. 

Research should be conducted evaluating the impact of HUD brightness as well as 

simulated OTW visual luminance (apparent target contrast) on attention capture effects 

and the ability of the pilot to detect target (R-10). 

5.6.5 Type of Event

A meta-analysis found that, although improved tracking performance can obtained with 

HUDs, “detection performance was found to be worse when a HUD was used during the 

landing phase of flight, a HUD cost that is amplified when events are unexpected” 

(Fadden, Wickens, and Ververs, 2000). 

Hofer et al (2000) also found that HUD performance was inferior to HDDs in expected

event detection, and far inferior in the detection of significant events leading to a possible 

incident or accident (i.e., runway incursion). (Nevertheless, the subjective results 

revealed that the pilots judged the HUD as being lower in overall workload and more 

usable than the HDD. The perception also was that it is easier to switch between the 

displayed information on the HUD and the outside scene, than it is to switch between the 

HDD and the outside scene.) 
42 

As noted by Wickens and Alexander (2009), “the implications are not that HUDs are 

problematic, but rather than imposing an event or visual item within the foveal vision 

does not guarantee its detection, if it is unexpected and not salient.”

In contrast, in terms of responding to unexpected occurrences, the detection rates and 

response times were comparatively higher and faster, respectively, when subjects used a 

HUD (Weinrauch et al., 1989; Sojourner and Antin, 1990); however, reaction times were 

faster using the HUD only in a low-workload situation. When the workload condition 

was high, on the other hand, the HUD users had longer reaction times when compared to 

the HDD (Fischer et al., 1980; Iarish and Wickens, 1991; Wickens et al., 1993). 

Automotive HUD research (Wolffsohn, McBrien, Edgar and Stout, 1998) has shown that 

response times to and detection of changes in the HUD image and outside world scene 

were significantly worse with increased cognitive demand. Response times to and 

detection of changes in the HUD image and outside world scene also increased with age. 

Research should be conducted evaluating the impact of experience and training in HUD 

operations for runway incursion detection and attention capture effects (R-11). 

5.6.6 Pilot Experience and Training

Another unfortunate confound in the HUD attention capture literature is the experience 

base of the subjects. HUD experience has been found to be critical in understanding and 

correct use of HUDs (Kaber et al, 2008). 

Many of the subjects in attention capture research were General Aviation (GA) pilots, 

(e.g., Wickens and Long, 1993) without prior HUD experience and even in those tests 

that used highly experience flight crews, HUD experience was limited or non-existent 

(e.g., Hofer et al, 2000; Atkins et al, 2001). As Hofer (2000) noted, “it was commented 

that a major training effect is to be expected with the HUD. That is, it is felt that pilots 

can be trained at what they need to do and get significantly better at performing all 

required tasks at a desired level of performance. To rely solely on the HUD is considered 

a learning curve, but the learning curve is expected to be moderately steep.” 

HUD experience brings two key points:

Understanding of HUD brightness and implications for clutter and how to 

declutter the HUD effectively; 

Understanding of HUD attention capture and transition to the OTW. Hofer et al, 

2000 theorized that pilots are “trained to make a physical switch between the two 

planes of information (head-up OTW and head-down) in a non-HUD aircraft;” 

whereas, using a HUD, a deliberate “attention” switch is required of the pilot to 

shift from information gathered from the HUD-symbology (near field) to the 

OTW visual (far field). As noted (Weintraub and Ensing, 1992), “when switching 

from a head-down display instrument panel to the outside world, there are three 

strong cues conveying the message that a switch is in progress from display 

information to outside scene information: The pilot looks up, the pilot changes 
43 

focus, and the pilot changes convergence form the outside world. They are 

powerful reminders to switch attention.” 

A pilot can become engrossed with any control task. Fixation, or a narrowing of their 

perception to other cues, can occur heads down as well as heads-up. This attention 

switch during HUD operations is promoted by judicious use of HUD brightness. For 

instance, the importance of HUD brightness and declutter controls are commonly trained 

in HUD operations (G. Saylor and R. Moreau, personnel communication, 29 May 2010) 

although standard operating procedures (SOPs) are not in place nor are SOPs expected 

since straight-forward rules for SOPs aren’t possible or practical. Training emphasizes 

the influence of HUD brightness, clutter/occlusion, and declutter controls. It stresses that 

the HUD brightness should be set as low as possible to keep the pilot looking through the 

HUD, yet still being able to see the HUD information. Pilot experience directly 

influences HUD brightness usage, with more experienced pilots tending to use less 

brightness as they have learned and become proficient in the HUD, its symbology and 

usage.
44 

6. Cockpit Display of Traffic Information with SEVS

The ability of a human to detect obstacles and traffic visually has been discussed and the 

impact of using a HUD or SEVS information on HUDs and HDDs has been discussed. 

This ability is also modulated by the roles and responsibilities defined for the flight crew 

(pilots). The emergence of ADS-B for Cockpit Display of Traffic Information (CDTI) 

creates the potential for significant improvements in traffic awareness and detection. 

Four tactical and strategic capabilities/operational benefits (McAnulty and Zingale, 2005) 

are envisioned by use of CDTI:

traffic awareness for the flight crew; 

airborne spacing where the flight crews achieve and maintain a given spacing 

with a designated aircraft, but controller remains responsible for separation; 

airborne separation where controller delegates separation relative to designed 

aircraft to the flight crew; or, 

airborne self-separation where a controller delegates separation relative to all 

known aircraft in accordance with applicable airborne separation minima. 

Numerous references describe potential applications for employment of CDTI (e.g., see 

McAnulty and Zingale, 2005; RTCA DO-289, MASPS for Aircraft Surveillance 

Applications). This technology is clearly one of the foundational enabling technologies 

for NextGen. These works have been expanded into government and industry consensus 

leading to Minimum Operational Performance Standards and Safety, Performance, and 

Interoperability Requirements for numerous CDTI-based operational capabilities. 

All of these works are pertinent but in this report, the use of CDTI for awareness of 

surface traffic is examined. In particular, research are reviewed as to how CDTI supports 

and/or modifies the pilots’ task of traffic detection and collision avoidance in the terminal 

maneuvering area (i.e., runway and low altitude safety) and during surface operations.

6.1. Object/Traffic Detection and Use of CDTI 

The process of “visual scanning” by a pilot (crew) is greatly influenced by the search 

importance, vigilance, and localization, such as: 

1) The current tasking of the pilot (crew) – i.e., what are the roles and 

responsibilities of the flight crew in the operation which dictates the time and 

attention available to perform a visual search. 

2) Whether the pilot’s search is localized or directed to look for a “target” in a 

certain area or location, as compared to very large, generalized area. 

3) Whether the pilot is alerted to potential collisions or conflicts with traffic or 

objects, thereby, increasing the pilot’s motivation and urgency in conducting a 

success search. 

CDTI has been shown to be an effective enhancement for visual acquisition of traffic 

(e.g., see Battiste, Ashford, and Olmos, 2000; Bone, Helleberg, and Domino, 2004; 
45 

Moore, 1997; Andrews, 1984 and 1991). CDTI creates an “alerted” search situation and 

also provides localization for the visual search. 

Some studies show an eight to nine times improvement in detection when alerted 

(Andrews, 1991; Boff and Lincoln, 1988). Un-alerted pilots were noted to concentrate 

their gaze in the forward direction (within 30° of straight ahead), but when informed that 

they were on a collision course, spread their glances more evenly over the visible area 

(Howell, 1957). Flight deck observations noted that, when available, CDTI was the first 

method used in the process of visually locating traffic (Joseph, Domino, Battiste, Bone, 

and Olmos, 2003), providing information for the pilots to localize their OTW visual 

search. CDTI provided increased positive visual acquisitions (Prinzo, 2003). However, 

dedicated studies in the use of CDTI (without collision detection and alerting) for traffic 

awareness and detection on the runway are few. 

For target detection using CDTI, operational differences (e.g., Part 91 versus Part 

121/135 operations) and airspace class differences likely influence CDTI usage, 

modulating the amount of head-down time caused by CDTI (Wickens et al, 2001). For 

instance, significant time is already required for head-down attention to the instruments 

for aircraft control - some aircraft and operations more than others. Airspace class 

dictates equipage and operational procedures so pilots may not have to attend to OTW 

scanning as much in controlled airspace as VFR airspace. These changes affect the 

“value” that the pilot places on OTW scanning viz-a-viz CDTI and head-down scanning. 

If the aircraft is operating in higher traffic density conditions or in uncontrolled airspace, 

OTW and CDTI vigilance changes because the “value” of scanning is significantly 

higher.

Wickens et al (2001) found that pilots used CDTI to guide them as to where to look to 

detect traffic, providing 5 seconds faster detection of non-conflict traffic than were pilots 

in the non-CDTI condition. However, during traffic conflict trials, pilots allocated 

relatively more attention to the CDTI, in order to plan their avoidance maneuvers, and 

this led to slower OTW detection times than in the baseline. 

Head-down time is a recurring, significant issue for CDTI suggesting that the use of 

CDTI draws pilots into the cockpit at the expense of scanning OTW for traffic (e.g., see 

McAnulty and Zingale, 2005; Battiste, Ashford, and Olmos, 2000). For instance, less 

head-down time and better integration of CDTI into the operation was found (Bone et al, 

2003) when using a forward, primary FOV CDTI versus a CDTI display located near the 

center aisle-stand/throttles. Pilots may be able to effectively integrate CDTI into this 

head-down scan. Workload was also found to be lower for the forward, primary FOV 

CDTI, but these differences were not considered to be operationally significant. An 

earlier study by Abbott and Moen (1981) had essentially reached the same conclusions. 

General design principles have recently been developed for 2-D traffic display 

symbology as part of RTCA SC-186 (Zuschlag, Chandra, Helleberg and Estes, 2010) 

with emphasize on how the symbology promotes intuitiveness, ease of learning, and ease 

of remembering. The additional of directional information to CDTI traffic symbols 

during airborne collision encounters was shown to not negatively affect pilot response to 
46 

TCAS resolution advisories (Olsen et al, 2009). The directional information also didn’t 

affect pilot scanning.

Research should be conducted evaluating the use of CDTI for traffic awareness and 

detection on the runway without traffic collision detection indications or alerting. This 

work would be complementary to research on indications, warnings, and alerting 

methodologies to establish the cognitive and human-centered and engineering design 

trade-offs of Terminal Maneuvering Area Conflict, Detection, and Resolution systems (R12). 

6.2. Object/Traffic Detection and Use of CDTI with SEVS – Exo-Centric 

The criticality of head-down time significantly influenced the development of airport 

moving map concepts (i.e., exocentric view of a synthetic airport layout, geo-referenced 

to ownship and CDTI) especially for the Taxiway Navigation And Situation Awareness 

(T-NASA) concept (Foyle, Andre, McCann, Wenzel, Begault, and Battiste, 1996). The 

T-NASA moving map was designed to promote eyes-out navigational awareness rather 

than eyes-in control functionality.

Eye-gaze tracking and analysis indicated that the amount of time dwelling on the moving 

map was significantly different depending upon the visibility condition (Graeber and 

Andre, 1999) but the operational significance of these differences (ranging from 38% to 

41%) is questionable. Pilots who were instructed on the intended use of the moving map 

gazed at the map less (35%) as opposed to those that were not instructed (44%). Using 

audio or visual "head-up" callouts as to the pilot’s visual attention to an airport moving 

map reduced the visual attention demand of the airport moving map display, without 

significant performance degradation relative to the no-callout condition (Purcell and 

Andre, 2001). 

As NextGen operations emerge - including concepts for 4D surface operations requiring 

runway to gate time-of-arrivals - the influence of CDTI, moving map concepts, and headdown time warrants renewed investigation. A study of these concepts (Shelton et al, 

2010) using “non-normals” to assess safety-critical scenarios showed that pilots were 

actively using and interacting with the surface map display concept only when there was 

valuable surface traffic and intent information. When flying ownship-only display 

concepts, the map was useful to support route and navigation awareness, but it was not 

often needed. But as traffic intent information and cleared route information was added, 

additional head-down time was attracted (Prinzel et al, 2010). The non-normals results 

showed the value of surface traffic CDTI and surface traffic ‘intent’ information but 

many of these potential incidents or accidents in the non-normals were also effectively 

mitigated by an EV-equipped HUD. Another study showed very similar results where 

four non-normals, involving taxiway or runway incursions studying the effect of the 

presence or absence of ‘party-line’ information were effectively mitigated by an EVequipped HUD instead (Prinzel et al, 2010). The role of the crew (pilots) and the fact 

that the pilot-flying must remain vigilant and head-out during surface operations 

significantly modulates the effectiveness of CDTI and how effective CDTI can be 

depends upon the display location and its content.
47 

The integration of CDTI with SEVS technologies must consider the presentation format 

and especially, the potential for clutter as traffic and terrain/flight reference information 

must be effectively integrated and quickly interpretable. Co-planar CDTI formats suffer 

from scanning-related integration that increases with conflict density. However, 

perspective CDTI formats suffer from perceptual ambiguity, such as range-to-traffic 

estimation difficulties (Alexander, Wickens, and Merwin, 2005). The use of highlighting 

can be useful but must be appropriately tailored (Johnson, Liao, and Tse, 2003). 

A runway incursion prevention system has been created to add another “safety wrapper” 

around the pilot/crew awareness provided by the airport moving map (such as T-NASA). 

The system adds aural and visual alerting of the incurring traffic to create awareness and 

localize the visual search. The importance of an ‘alerted’ search was highlighted in a test 

of incursion prevention concepts for GA pilots. An airport moving map with traffic was 

found to be only marginally beneficial without alerting. One pilot experienced a severe 

runway incursion despite having the traffic displayed on an airport moving map (Jones 

and Prinzel, 2006). The incursion resulted because the pilots had transitioned to out-thewindow and were not focused on the head-down display to locate incurring traffic. It was 

hypothesized that the utility of the surface map would be more effective if the display 

was located higher on the instrument panel, closer to the pilot’s head-up eye gaze. 

Continued enhancements for traffic awareness on airport moving maps are emerging, 

including initiatives under SC-186 Surface Indications and Alerts (SURF-IA) providing 

obvious and direct indication of runway occupancy and potential safety/runway traffic 

implications (Moertl and Nickum, 2008). Further, NextGen concepts for 4D trajectory 

based operations, including required time of arrivals in airborne and surface operations, 

are spawning new CDTI such as the explicit depiction of cleared taxi routes for ownship 

and traffic with their required and actual taxi performance graphically drawn (see Figure 

11).

The importance of CDTI and advisory, caution, and warning systems for NextGen 

include low altitude operations where desires for increased airport throughput will dictate 

more closely spaced arrivals. In an experimental simulator study (Pritchett and Hansman, 

1996), traffic displays with increasing amounts of traffic information were evaluated in 

closely-spaced parallel approaches. The results generally support the contention that with 

more and better trend information, improvement in performance for conflict detection can 

be attained.

Research should be conducted evaluating the optimal methods for integration of CDTI 

within SEVS ego-centric display concepts (R-13). 
48 

04:10

GS13 GS15

00:30

RTA - 12:40:30z ETA - 12:41:30z (+0:02) Distance to A: 2000 

Own Ship 

Chevron 

Own ship trend symbol - indication of position in 

30 seconds and is based on ships current speed.

Own Ship Intent symbol - Indication of position 

required in 30 seconds to achieve RTA 

Selected Traffic Chevron 

Selected Traffic’s Trend Symbol - Indicates 

position in 30 seconds and is based on current 

 speed. 

Own Route 

Selected Traffic Intent Symbol - Indication of 

Position required in 30 seconds, to achieve RTA 

Selected Traffic’s Route 

Over lapping 

Routes 

ETA & RTA 

Symbols 

Indicating ‘on 

time’ 

Figure 11: 4D Surface CDTI Concepts 

6.3. Integration of CDTI with SEVS – Ego-Centric 

CDTI research has predominately focused on exo-centric presentations of traffic (CDTI) 

and synthetic vision (airport moving maps) on a navigation display; that is, electronic 

moving map concepts. 

However, objective and subjective data from an empirical study suggested that CDTI 

should be presented both head-up and head-down rather than just head-down (Kramer 

and Norman, 2000). Pilot workload for traffic surveillance was lower and it made for 

quicker and easier visual acquisition when the CDTI information was presented both 

head-up and head-down. Traffic locator box icons on the head-up displays allowed for 

quick visual and therefore, much easier detection and assessment of traffic. Clutter was a 

concern but not significantly so. Range filtering of traffic data was shown effective in 

reducing clutter yet retaining critical CDTI information head-up (Wong, Kramer, and 

Norman, 2002). 

Representation of traffic location by icons within an ego-centric perspective display (i.e., 

a “traffic locator box”) creates localization cueing with minimal clutter (Jones, 2002; 
49 

Kramer and Norman, 2000). Questions emerge as to whether improvement in situation 

awareness can be gained by instead using virtual models of the traffic aircraft, in SV 

presentations. A virtual model, driven from ADS-B ‘In’ information, would theoretically 

provide a more intuitive representation of the traffic and could include aircraft type, 

heading, bank angle, etc. Preliminary evaluation of head-worn display concepts during 

surface operations have evaluated virtual models (see Figure 12) for traffic 

representation, but conclusive results are not yet available.

Research is needed to identify and quantity the design trade-offs between intuitive traffic 

representation and the potential increases in display clutter or occlusion for ego-centric 

SEVS display concepts (R-14). 

Figure 12: Head-Worn Display Concept With Traffic Represented By A Virtual Model 

Viewpoint considerations must be tailored to the application. Studies in closely-spaced 

parallel approach tasks, suggests that “virtual” viewpoints at other than the pilot eye point 

make a significant difference in traffic awareness and blunder detection (Azuma and 

Furmanski, 2005). In fact, they suggest that “the view that a pilot would normally see out 

of a cockpit was by far the worst option.”

Research has been conducted to determine minimum relevant traffic information for 

strategic traffic awareness during closely-spaced parallel approach tasks (e.g., Pritchett 

and Hansman, 1996). Others suggest that additional cues (traffic roll and heading) are 

also required to detect traffic blunder (Jennings, Charafeddine, and Powell, 2002). Their 

work suggested that a single synthetic vision display is insufficient to convey traffic 

information. The difficulties arise from an insufficient field-of-view of the PFD (or 

HUD) and that the distance cues are too weak in an ego-centric perspective display to 

precisely convey the location of the other aircraft. While the PFD does show traffic 

elevation and azimuth, additional display concepts have been evaluated to complement 

the SV PFD for traffic awareness, including exo-centric views. 
50 

7. Concluding Remarks And Recommendations 

NASA LaRC and the FAA are conducting collaborative research activities to ensure 

effective technology development and implementation of regulatory and design guidance 

to support introduction and use of SEVS technologies in NextGen. SEVS technologies 

have the potential to provide an additional margin of safety and aircrew performance to 

enable the implementation of operational improvements for low visibility surface, arrival, 

and departure operations in the terminal environment with equivalent efficiency as visual 

operations.

In this report, the research literature is reviewed to assess pilot awareness and detection 

of traffic and obstacles when using SVS and EFVS systems. 

Research was reviewed as to how the visual traffic and obstacle detection task is, in 

essence, a human observer performing “target acquisition.” The cognitive and physical 

mechanisms for acquisition and detection using natural vision and EV using head-down 

or head-up displays is discussed. The critical issues influencing the time required, 

accuracy, and pilot workload associated with recognizing and reacting to potential ground 

collisions or conflicts with other aircraft, vehicles and obstructions related to the use of 

SEVS technologies are described. In particular, the importance of sensor resolution and 

the relative contrast of the “target” are paramount. 

This work also discusses the effect of head-down and head-up operations with SV and 

EFVS, respectively, as well as the influence of single and dual pilot operations. The 

pilot’s role in the operation is a significant contributor to the attention directed to and the 

importance of the search task. 

Finally, research is reviewed in the methods and strategies of adding CDTI with headdown SVS and head-up EFVS in low-visibility landing and surface operations and their 

effect on time required, accuracy, and pilot workload for recognizing and reacting to 

potential ground collisions or conflicts. 

7.1. Recommendations 

Based on this review, numerous knowledge gaps have been identified and form the 

following recommendations for continued research and also, for specific empirical pilotin-the-loop ground and flight testing activities to support SEVS for NextGen: 

Future work should investigate the vision system technology (SEVS) requirements for an 

equivalent visual operational capability (R-1).

To achieve the equivalent visual operations, one could assume that the vision 

system technology must meet the same performance as that provided by aircraft 

windows with a human observer. Is our knowledge of human visual performance 

sufficient and/or correct so as to design and create a vision system which meets 

equivalent visual capabilities? Is this assumption valid? Are these requirements 

too strict? Too lax? 
51 

Are head-worn displays required to create this functionality? If so, what are the 

requisite cognitive and engineering issues? If not, what are the requisite cognitive 

and engineering issues with using HUDs and/or HDDs? 

Future work should explore the impact, if any, of SEVS in changing the roles and 

responsibilities of the ANSP (R-2).

Will new and expanded “operating credit” from the use of SEVS technologies 

require changes in ANSP roles or responsibilities? What impacts? 

Future work should explore the potential for SEVS to replace the need for or functional 

elements currently required for Surface Movement Guidance and Control Systems and 

for approach lighting systems (R-3).

Can equivalent visual capability on the flight deck obviate the need for certain 

requirements currently stipulated for Surface Movement Guidance and Control 

Systems and for approach lighting systems? What are the system characteristics 

required for these credits? 

Research should be conducted to determine the desired/required missed detection and 

false alarm rates for a SV which utilizes ‘behind the glass’ processing for automatic 

database, obstacle/object, and navigation error and omission checking (R-4). 

Research suggests that the ‘ideal’ vision system is a SV presentation with 

processing ‘behind-the-glass’ to support integrity and accuracy requirements. 

What level of human interaction with this process is required/desired? What type 

of interaction is required/desired? 

Research should be examine head-down vs. head-up performance for the PM, with 

experimental variations in display size, location, and minification/magnification (R-5)

During EFVS operations, the PM has specific roles and responsibilities. Research 

is needed to identify the display characteristics required to best support these roles 

and responsibilities for current and emerging operational capability. 

Research should be conducted evaluating qualitative and quantitative metrics of clutter 

in actual flight conditions (R-6).

Display clutter is critical. Qualitative and quantitative metrics have been 

proposed but they have only been tested in ground simulation. 

Research should be conducted using high fidelity simulation and flight testing; evaluating 

HUD attention capture effects in very low visibility operations (visibilities less than 700 

ft) where the saliency becomes less distinct (R-7). 

Emerging trends suggest that HUD attention capture could be on the increase. 

Research is needed to develop counter-measures and establish 

guidelines/requirements to ensure that attention capture is mitigated. 
52 

Research should be conducted evaluating the impact of color HUDs (and head-worn 

display or virtual display) on attention capture, clutter, and target detection (R-8). 

Only a very limited research basis is available regarding the application of color 

virtual displays, head-worn displays, and HUDs. Research is needed in 

“augmented reality” scenarios, especially for attention capture, clutter, and target 

detection, where the interaction of displayed information and real-world visual 

cues are paramount. 

Research should be conducted evaluating the impact of imprecision in conformal HUD 

symbology (statically and dynamically) on attention capture effects and the ability of the 

pilot to use EFVS imagery especially as it is the predominant source of visual 

information for landing in very low visibilities (<700 ft visibility) (R-9). 

What are the static conformal and dynamic response requirements for an EFVS 

system to conduct operations in very low visibilities where the EFVS provides the 

vast majority, if not the sole source of usable visual cues for the pilot? 

Research should be conducted evaluating the impact of HUD brightness as well as 

simulated OTW visual luminance (apparent target contrast) on attention capture effects 

and the ability of the pilot to detect target (R-10). 

Data are needed to guide the use and training of the HUD controls to ensure its 

effective operational use. 

Research should be conducted evaluating the impact of experience and training in HUD 

operations for runway incursion detection and attention capture effects (R-11). 

The human factors research data on HUD effects do not adequately or 

appropriately reflect trained HUD operators and these influences. Selected data 

should be collected to quantify these impacts. 

Research should be conducted evaluating the use of CDTI for traffic awareness and 

detection on the runway without traffic collision detection indications or alerting. This 

work would be complementary to research on indications, warnings, and alerting 

methodologies to establish the cognitive and human-centered and engineering design 

trade-offs of Terminal Maneuvering Area Conflict, Detection, and Resolution systems (R12). 

SURF-IA and other initiatives are creating significant safety enhancements using 

ADS-B traffic information and attendant CDTI in exo-centric applications. 

However, several gaps in this research and application are apparent, including: 

o Is CDTI on head-down displays sufficient if the pilot’s attention (i.e., roles 

and responsibilities) are directed elsewhere? What display concepts / 

alerting will help this scenario? Display location effects? 

o How does the use of CDTI and instantiations of traffic information 

(including trend information, cleared traffic route, and intent) modulate 

head-down time and attention? 
53 

o How do pilot roles and responsibilities modulate head-down time and 

attention? 

o Most CDTI studies have assumed “perfect” traffic position reporting. 

What are the influences of realizable/realistic ADS-B accuracies? What 

are the influences of these accuracies on the task and performance? What 

about mixed equipage? ADS-B faults or failures? 

Research should be conducted evaluating the optimal methods for integration of CDTI 

within SEVS ego-centric display concepts (R-13). 

What methods and presentation formats for ego-centric CDTI are optimal? What 

display concepts / alerting will help this scenario? 

Research is needed to identify and quantity the design trade-offs between intuitive traffic 

representation and the potential increases in display clutter or occlusion for ego-centric 

SEVS display concepts (R-14). 

Display clutter is critical. Is symbolic representation of traffic on a head-up or 

head-down display sufficient or preferable to actual traffic models? 

Ego-centric CDTI presentations are likely impacted by “imperfect” ADS-B 

accuracies. What are the influences of these accuracies on the task and 

performance? What methods can be used to compensate for realizable/realistic 

ADS-B accuracies? 
54 

References

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REPORT DOCUMENTATION PAGE Form Approved

OMB No. 0704-0188

2. REPORT TYPE 

Technical Memorandum

 4. TITLE AND SUBTITLE

Awareness and Detection of Traffic and Obstacles Using Synthetic and 

Enhanced Vision Systems 

5a. CONTRACT NUMBER

 6. AUTHOR(S)

Bailey, Randall E.

 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES)

NASA Langley Research Center

Hampton, VA 23681-2199

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National Aeronautics and Space Administration

Washington, DC 20546-0001

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 REPORT NUMBER

L-20100

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NASA

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Unclassified - Unlimited

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Availability: NASA CASI (443) 757-5802

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STI Help Desk (email: help@sti.nasa.gov)

14. ABSTRACT

Research literature are reviewed and summarized to evaluate the awareness and detection of traffic and obstacles when using 

Synthetic Vision Systems (SVS) and Enhanced Vision Systems (EVS). The study identifies the critical issues influencing the 

time required, accuracy, and pilot workload associated with recognizing and reacting to potential collisions or conflicts with 

other aircraft, vehicles and obstructions during approach, landing, and surface operations. This work considers the effect of 

head-down display and head-up display implementations of SVS and EVS as well as the influence of single and dual pilot 

operations. The influences and strategies of adding traffic information and cockpit alerting with SVS and EVS were also 

included. Based on this review, a knowledge gap assessment was made with recommendations for ground and flight testing to 

fill these gaps and hence, promote the safe and effective implementation of SVS/EVS technologies for the Next Generation 

Air Transportation System. 

15. SUBJECT TERMS

Enhanced Vision; HUD; Object Detection; Runway Incursion; Synthetic Vision

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69

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(443) 757-5802

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