ENRI Int. Workshop on ATM/CNS. Tokyo, Japan. (EIWAC 2010)[EN­049] Risk Compensation in General Aviation: The Effect ofBallistic Parachute Systems(EIWAC 2010)+

C. Hartman*, I. Dabipi*, J. Dodoo**, J. Burrows-McElwain**Department of Engineering and Aviation Sciences
University of Maryland Eastern Shore
Princess Anne, Maryland, USA
chartman@umes.edu**Department of Natural Sciences
University of Maryland Eastern Shore
Princess Anne, Maryland, USA

Abstract: In evaluating pilot’s risk and decision making profiles, this paper explores the possibility that pilots may exhibit
risk compensation and make riskier decisions due to the perceived additional level of safety that a ballistic parachute systemprovides. An available population of pilots was asked to take part in a survey that posed various flight scenarios andprovided multiple-choice style “decisions”. The decisions had been previously ranked by subject matter experts andassigned a risk score. Pilots responding to the online survey were assigned to one of two groups. Pilots from group one
were asked to assume that they were flying a Cirrus SR-20 equipped with a ballistic parachute system. Pilots from thesecond group were asked to assume that they were flying a Piper Arrow. The two group’s decisions were then compared. A
correlational method was also employed to determine if certain demographic features, including age and total flight time,
were associated with increased risk taking.
Keywords: Human Factors, Decision Making, Risk Compensation, Ballistic Parachutes
The 2005 Nall Report, a yearly summary of General
Aviation (GA) accidents published by the Aircraft
Owners and Pilot’s Association (AOPA), states that midair collisions in general aviation are “relatively” rare andthat “pilot incapacitation happens very rarely” [2]. The
Nall Report also indicates that failures of an aircraft or its
systems are also relatively rare. So while a ballistic
parachute system does provide an additional level ofsafety, the valid reasons for deploying such a system arerare in comparison with the most common accident types.

1. INTRODUCTION
Ballistic parachute systems have been promoted by their
manufacturer, Ballistic Recovery Systems (BRS), andCirrus Design Corporation, manufacturer of the Cirrus
SR20 and SR22 aircraft, as safety enhancing devices. A
ballistic parachute system has been included on all
production Cirrus SR20 and SR22 aircraft. Installed on
Cirrus aircraft, this system is known as CAPS or Cirrus
Airframe Parachute System. Widely advertised as anenhancement to safety, a ballistic parachute system isdesigned to be deployed in an emergency situation.

Much more common are accidents due to pilot-relatedcauses or accidents due to the “improper action or inactionof the pilot”, for which the Nall Report attributes 75.5
percent of all accidents and 78.6 percent of all fatal
accidents [2]. Despite the additional level of safety that
the CAPS system advertises, the NTSB database lists
sixty-nine accidents and twenty-five fatal accidents
resulting in 52 deaths in Cirrus aircraft during the periodof April 2001 through February 2007 [3]. It could beargued that this was in fact due to the same common
causes seen elsewhere in general aviation, most notably
pilot-related causes.

After being deployed in such an emergency situation, theparachute system is designed to lower the entire aircraft tothe ground at a rate that will save the occupants fromserious injury. BRS has documented 199 saves or lives
that its system has saved since its inception in the 1980s[1]. Some of the emergency situations in which thesedevices are meant to be deployed, as listed by Cirrus and
BRS, are: mid-air collisions, pilot incapacitation, loss ofcontrol, engine failure over rough terrain, and engine
failure at night.

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C. Hartman, I. Dabipi, J. Dodoo, J. Burrows-McElwain
One principal pilot related cause of general aviation
accidents is failures in decision making. Proper decisionmaking is vital to safe flying. Poor decision-making bypilots has been recognized as a major factor in generalaviation accidents [4]. Faulty decision making has been
blamed for as many as 50 percent (50%) of all accidents[5]. A FAA study on the decision--making skills ofgeneral aviation pilots found that young pilots and pilots
with a considerable amount of flight experience were more
likely to make riskier decisions than older pilots or thosewith less experience [5].

drivers compensate for road lighting with both increased
speed and decreased concentration. Assum et al. conclude
that road lighting would have a greater “accident-reducing
effect if compensation could be avoided” [10].
Another study found that children behaved in a more
reckless manner when outfitted with safety equipment
than they did when no safety gear was worn [11]. In aclosely related study, Morronngiello, Walpole andLanesby found that “children believed wearing safety gear
made them invulnerable to any degree of injury, protected
them from serious injury, and resulted in them somehow
being more competent to perform a higher-risk activity”[12, p 56].

Additionally, unnecessary risk-taking and inaccurate risk
assessment can be said to contribute to a large percentageof aviation accidents. Hunter states that “poor risk
assessment can contribute significantly to poor decision
making” and that high levels of risk tolerance in pilots
may lead them to take hazardous actions [6]. Decisionmaking and risk assessment play a role in each and every
flight a pilot makes. This project seeks to explore the roleof risk assessment as it applies specifically to flight inCirrus Design aircraft equipped with a ballistic parachutesystem.

Risk compensation with respect to safety gear has beenfound to apply not only to children, but to their adultparents as well. Morrongiello and Major found thatparents would allow their children to take significantly
greater risks when equipped with safety gear than theywould when the children wore no such gear [13]. Thesestudies call for education and training that addresses theproper use of safety gear and promotes the understandingthat safety gear is not a universal protection from all injury.
Haigney, Taylor and Westerman studied the effect ofcellular phone use on user’s behavior while driving. It was
found that the perceived increased level of risk led todrivers slowing their speed during times of cell phone
conversation [14]. This study provides an example of risk
compensation in response to a perceived increased risk.

2. RISK COMPENSATION
Risk compensation is the theory that persons adapt their
behavior based on their perceived risk of theirsurroundings. According to this theory, when humans
perceive that risk or danger has increased, they will act
more cautiously. Conversely, when risk is perceived to beless or a person feels safer, he or she will behave lesscautiously. Hedlund states that “people modify their
behavior in response to changes in the reward and penalty
structure of their environment” [7, p. 86]. Morecontroversial, and beyond the scope of this project, is thetheory of risk homeostasis-the idea that humans will adjust
their level of risk to a point that negates the benefit ofmandatory safety improvements [8].

Schindler explored the possibility that firefighters carrying
an improved fire shelter may take more risks than theywould if not equipped with the new shelter. It was foundthat risk compensation may occur in this field due to theadditional perceived level of safety; therefore mitigationof risk compensation was encouraged through targetedtraining [15].
3. RISK IN AVIATION
An accurate assessment of risk is critical for good decision
making. Kirkbride, Jensen, Chubb and Hunter encouragepilots to create a personal minimums checklist of risk
factors for assistance in preflight decision making. This
process encourages pilots to consider all potential factors,
from the aircraft to the environment to themselves andevaluate the risk based on all of these factors [16]. A
follow-up study found that a training program toencourage pilots to create such a personal minimums
checklist was well received by attendees [17].

The idea that persons behave less cautiously or makeriskier decisions in response to a perceived added level ofsafety is well documented in literature. Noland found that
improvements in bicycle safety led to an increase inbicycle commuting [9]. Persons who would not haveotherwise commuted by bicycle chose to commute bybicycle because of the perceived safety improvements.
Conversely, Noland concluded that “increases in theperceptions of the risk of using a given transportation
mode may reduce the probability of commuting by that
mode.” Although the findings of this study may be
applicable to aviation, only walking, bicycling, and travelby auto were explored.

Hunter sought to measure risk perception and risk
tolerance in general aviation pilots. This study found anegative correlation between a pilot’s risk perception of
weather and risk tolerance in weather-related situations [6].

Assum, Bjornskau, Fosser, and Sagberg documented risk
compensation in transportation when they found that174

ENRI Int. Workshop on ATM/CNS. Tokyo, Japan. (EIWAC 2010)
Therefore, the lesser the perceived weather risk, thegreater weather risk a pilot would tolerate.

certification while 16 (21.1%) reported Airline Transport
Pilot (ATP) certification. Sixteen (21.1%) of respondents
also reported Flight Instructor certification. Forty-three(56.6%) of the respondents reported possessing an
instrument rating while the remaining 33 (43.4%)
indicated that they did not possess an instrument rating.
Twenty-eight (36.8%) of the respondents reported
possessing a multi-engine rating, while 48 (63.2%)
reported no such rating.

Green found that more than one third of the flight
instructors interviewed for her study did not rate aviation
as a risky activity. Green concludes that recognition of risk
is an essential beginning of risk management, and that thisconcept should be integrated early in flight training inorder to improve pilot decision making [18]. The results ofa study conducted by Hunter agree with the conclusionthat training in risk recognition could be highly effective
in preventing accidents [6]. Molesworth, Wiggins andO’Hare concluded that pilots may gain risk assessment
skills through exposure to hazardous scenarios in asimulated environment [19].

Respondents were asked to report their total flight time bychoosing one of the following groups (number of
respondents, percent of total respondents): less than 100
hours (5, 6.6%), 101-250 hours (21, 27.6%), 251-500
hours (13, 17.1%), 501-1000 hours (10, 13.2%), 10012000 hours (6, 7.9%), 2001-5000 hours (9, 11.8%), or
more than 5000 hours (12, 15.8%). The largest respondentgroup was 101-250 with 21 pilots (27.6). A total of 39
pilots (51.3%) reported having 500 or fewer flight hours.

There is much literature on the topic of risk as it relates topilots and aviation. The topics of risk assessment, risk
management and risk tolerance are discussed; however, nodirect connection has been made between aviation and risk
compensation.

Respondents were also asked to pick one or two of thefollowing descriptions that best describes the majority of
their flying: Pleasure/Personal (50, 65.8%), Businessrelated (22, 28.9%), Charter (1, 1.3%), Airline (7, 9.2%),
Other Commercial (4, 5.3%), Military (7, 9.2%), Flight
Instruction (9, 11.8%), or Training (18, 23.7%).
Percentages do not equal 100% since some respondents
chose more than one category to describe their flying.

4. METHOD
4.1 Research ModelAn experimental research model was used for this project.
Pilots responding to the online survey were assigned to
one of two groups. The group assignment was based on
the question “Is your birthday on an even or odd day?”.
Pilots were assigned to one of the two groups dependingon their answer of “odd” or “even”. Pilots from group one
were asked to assume that they were flying a Cirrus SR-20
equipped with a ballistic parachute system. Pilots from thesecond group were asked to assume that they were flying a
Piper Arrow. The two group’s decisions were thencompared. A correlational method was also employed todetermine if certain demographic features (including age
and total flight time) were associated with increased risktaking.

4.3 Sources of Data
Data was collected through an electronic survey hosted bysurveymonkey.com. In addition to responses toquestionnaire items, the instrument collected demographic
information on each pilot including gender, age, flighttime, as well as pilot certifications and ratings.
4.4 The Data Collection Device
The questionnaire consisted of 16 scenario-type questions
and two opinion questions. The scenario-type questions
presented pilots with four possible responses to eachscenario. Pilots were asked to choose the response thatbest described the action they would take in the given
scenario. The scenarios used were originally developed
and used in conjunction with a project completed by
Driskill, et al in 1998 [5].

4.2 Survey Population
The population targeted for this survey was pilots. Ninetyfour (94) pilots responded to the survey, however, only 76
pilots completed the survey in its entirety. The data fromthe 18 pilots who did not complete the survey will beomitted from further discussion.

The opinion questions instructed pilots to rate the level towhich they agreed with two separate statements using a 5point Likert scale (Disagree Strongly = 1; Disagree
Somewhat = 2; Neutral/Don’t Know = 3; Agree
Somewhat = 4; Strongly Agree = 5). The statements were:Of the 76 respondents, 69 (90.8%) were male, and 7 werefemale (9.2%). The mean age for all respondents was 42.
Respondents were asked to report their pilot certifications.
Forty-seven (61.8%) reported holding Private Pilot
certification, while only 2 (2.6%) reported Recreational
Pilot certification. There were no Sport pilot respondents.
Twenty-three (30.3%) reported Commercial Pilot

1.

175

I feel that the airplane I am flying, considering its type,condition, and equipment installed, impacts theamount of risk I am willing to accept on a given flight.

C. Hartman, I. Dabipi, J. Dodoo, J. Burrows-McElwain
2.

I feel that I may be willing to take on greater risks
when flying an aircraft equipped with a ballistic
parachute system than I would in an aircraft without aballistic parachute system.

4.8 Instrument Validity
The scenarios to be used in the questionnaire wereoriginally ranked for risk by a panel of experts in Driskill
et al (1998). This ranking by subject matter experts
ensures that the instrument is an accurate assessment ofrisk taking. In Driskill, this score was referred to as the
Safety Deviation Index (SDI). However, the SDI used in
the study has not been correlated with other independentmeasures of risk such as participation in risky activities or
accident involvement. This will limit the ability tocorrelate the results of the study to factors such as accident
involvement in the future or future risk-taking.

Also included in the instrument was a disclaimer andinstructions for completing the questionnaire which gave
information to the pilots on the aircraft they were to
assume they were flying when responding to the scenarios.
4.5 Instrument Pretest
The questionnaire was used in Driskill [5]. However,some questions were eliminated and additional
information was added to the instructions regarding
aircraft type and equipment to be assumed in the scenarios.
A pretest was conducted during the Fall semester of 2007
using a group of 12 pilots from the University of
Maryland Eastern Shore to ensure clarity. This pretest
used paper questionnaires. As in the study, equal numbersof pilots (6) were assigned to each of the two groups.
Based on the feedback from the pretest, the number ofscenarios used was reduced from 20 to 16. This was donein order to shorten the amount of time necessary tocomplete the survey, thereby hopefully reducing thenumber of surveys that would be left incomplete.

4.9 Procedures
In Driskill, et al, pilots were given an option of four
responses to each of the scenarios. Each of the four
responses to the scenarios was individually graded for risk
by a panel of experts. Each of the responses was thenassigned a risk score. A higher score in the Driskill study
equated to a riskier decision. These same risk scores wereused to assess the risk taking of pilots participating in thecurrent study. Pilots received an overall risk score
calculated from the sum of the risk scores of each of theirdecisions. This score was referred to as the Safety
Deviation Index (SDI), as it was in the Driskill, et al study[5]. The mean SDI for pilots in group one, “flying” theballistic parachute-equipped Cirrus SR-20 was comparedto the mean SDI for pilots in group two, “flying” the Piper
Arrow. There was a directional expectation for the SDI. It
was expected that the mean SDI for group two would belower than the mean SDI for group one.

4.6 Distribution Method
The questionnaire was developed into an electronic
version that was presented via surveymonkey.com. A linkto the survey was sent out to pilots using the researcher’s
personal contacts via email with the request to continue
forwarding the link to other pilots. Pilots completed theelectronic questionnaire via computer and results weretracked electronically through surveymonkey.com.

In the current study, unlike in Driskill, et al, each pilot wasalso presented with two opinion questions to which they
were asked to indicate their level of agreement using afive-point Likert scale.

4.7 Instrument Reliability
Driskill concluded that the survey instrument used to
conduct that test had adequate reliability when measured
by coefficient alpha [5]. To ensure reliability in the current
study, scenarios in the study were chosen to ensure thateach scenario has a match, or a question that measures
decision-making based on a similar scenario. The
questionnaire was then tested for split-half reliability.
Each pilot’s risk score for one half of the questions wascompared to the pilot’s risk score for the other half. Thesescores were tested using SPSS Version 17.0 for correlation.
This yielded a Pearson correlation of .503. This
correlation is statistically significant at the p=0.01 level.
Based on this result, some amount of instrument reliability
can be assumed.

4.10 Treatment of Data
Data was collected in Microsoft Excel format fromsurveymonkey.com. This data was then imported into
SPSS v.17.0 for analysis. The SDI score for each pilot wascalculated using SPSS based on the individual pilot’s
response to each of the scenarios. Mean scores were thencalculated based on categories of respondents, includinggroup one (hereafter referred to as Cirrus Group) or grouptwo (hereafter referred to as Piper Group) and Instrumentrated or Visual Flight Rules (VFR) only.
The null hypothesis that there was no significant
difference between the mean SDI score of the Cirrus
Group pilots and the mean SDI score of the Piper Grouppilots was tested. A t-test was conducted to determine if
the difference in the mean SDI scores was significant at

176

ENRI Int. Workshop on ATM/CNS. Tokyo, Japan. (EIWAC 2010)
the p=.05 level. A correlational method was also employed
to determine if there were any significant correlations at
the p=.05 level between a pilot’s demographic features
and a pilot’s SDI.

Mean SDI

N

Std. Deviation

Cirrus Group 418.2327

15

79.13213

Piper Group

400.1483

1865.67336

Total

408.3685

33

71.51555

Instrum Cirrus Group 410.4479
entrated
Piper Group 447.6967
pilotsTotal
431.2379

19

92.79381

24

98.5009443

96.71535

Total

34

85.84110427.31884288.30812

421.307876

86.89384

VFRonlypilots5. RESULTS
5.1 Safety Deviation Index (SDI) Scores
The mean SDI for all pilots completing the survey was
421.31 with a Median Score of 414.62. The highest risk
score was 735.15 and the lowest was 265.75, a range of
469.40. The mean SDI for the Cirrus Group was 413.88,
while the mean SDI for the Piper Group was 427.31. It is
important to note that this result is opposite of that which
was expected.

Cirrus Group 413.8824(All
respond Piper Group
ents)
Total

Further analysis of the data shows a mean SDI for
Instrument-rated pilots of 431.24 and a mean SDI of
408.37 for VFR-only pilots. Further breakdown showsthat VFR-only pilots in the Cirrus Group had a mean SDI
score of 418.23 compared to the VFR-only Piper Group’s
400.15. See Table 1, right, for SDI scores broken down by
category.

Table 1 Instrument rated versus VFR-only pilot’s SDI scores

Opinion Question 2 asked pilots to rate their level ofagreement with the following statement “I feel that I may
be willing to take on greater risks when flying an aircraft
equipped with a ballistic parachute system than I would in
an aircraft without a ballistic parachute system.” Pilots
disagreed with this statement, giving a mean response of
1.68. VFR-only pilots disagreed less strongly (1.97), while
Instrument-rated pilots disagreed somewhat more strongly.
Of all pilots, VFR-only Cirrus Group pilots respondedwith the least disagreement with a mean of 2.13.

5.2 Analysis of SDI scores
A t-test of the mean SDI scores of the Cirrus Group ascompared to the mean SDI scores of the Piper Groupreveals that t = -.668. This result is not statisticallysignificant at the p = 0.05 level with 72 degrees of
freedom. Again, the directionality of these mean scores is
opposite that which was expected.
A second t-test was completed to compare the mean SDI
scores of VFR-only Cirrus Group and Piper Group pilots
as these means matched directional expectations. The ttest yielded a t of .718, which is not statistically significant
at the p = 0.05 level with 31 degrees of freedom.

5.4 Correlations
A Pearson Correlation analysis was performed in order todetermine if any correlations existed between key
demographic features and SDI or responses to opinion
questions. As seen in Table 2, below, significant statisticalcorrelations exist between pilot’s responses to Opinion
question 2 and the pilot’s age as well as his or her total
flight time.

5.3 Opinion Question Response
Opinion Question 1 asked pilots to rank their level ofagreement with the statement “I feel that the airplane I am
flying, considering its type, condition, and equipment
installed, impacts the amount of risk I am willing to accept
on a given flight.” Overall, pilots agreed, however slightly,
with this statement, giving a mean response of 3.58. VFRonly pilots were slightly less likely to agree (3.36) while
Instrument-rated pilots indicated slightly stronger
agreement (3.74).

Cirrus or Piper Total
Age

Group

flight time

SDI

-.177

.077

.103

Opinion Question 1

-.099

-.026

.163

Opinion Question 2-.227*-.068-.241*

Table 2 Correlations with Demographic Data
* Correlation is significant at the 0.05 level (2-tailed)177

C. Hartman, I. Dabipi, J. Dodoo, J. Burrows-McElwain
In these cases an inverse relationship exists between theage and total flight time of a pilot and the pilot’s level ofagreement with Opinion Question 2. No such significant
correlations exist between these demographic features anda pilot’s SDI or responses to Opinion Question 1.

time and his or her answer to opinion question 2. These
results seemed to signify that the older and the moreexperienced a pilot is, the less likely they are to agree thatthey may take on additional risks in response to additionalsafety equipment.
This result has several possible explanations. First, pilots,
as they get older and gain experience, may simply be
unwilling to accept certain risks, regardless of the aircraft
equipment. The second possible explanation of this result
is that older and more experienced pilots are simply lesswilling to admit that they may take on greater risks inballistic-parachute equipped aircraft. Both explanations
have ramifications for the design of future training
programs.

6. DISCUSSION
6.1 SDI Scores
Although statistically significant differences did not exist
between the SDI scores of pilots in the Cirrus group ascompared to pilots in the Piper group, some interestingobservations can still be made. First, it is important tounderstand that the survey, as originally designed, wasintended for VFR-pilots only. In this project, theresearcher was unable to achieve a substantial sample sizeof VFR-only pilots. Since the sample was chosen fromavailable sources, a mix of VFR and Instrument-rated
pilots resulted. Since the scenarios in this survey wereoriginally written with VFR-only pilots in mind, they did
not present options that Instrument-rated pilots would be
likely to use. For example, several Instrument-rated pilots
commented that they would have filed and proceeded
under Instrument Flight Rules given the situation
presented to them in the scenario. That option was notavailable, however.

7. CONCLUSIONSIt has been demonstrated in the past that individual pilots
are willing to accept varying levels of risk and may evenbe unaware of the risk they are undertaking. The effect ofrisk compensation has been well documented in fields
other that aviation and it has been demonstrated thathumans do in fact alter their behavior in response toperceived safety. Simply put, humans tend to behave more
recklessly when they feel safer. Given these points, it ishighly probable that some sort of risk compensation may
play a part in the decision making of general aviation
pilots.

In light of this, it is interesting to observe the SDI scoresof just VFR-only pilots. This further diminishes the
sample size to only 33 pilots (See Table 1, page 21). VFRonly pilots in the Cirrus Group had a mean SDI of 418.2,
while VFR-only Piper pilots had a mean SDI of 400.1.
This result lines up with initial expectations that Cirrus
pilots would have higher SDI scores, and therefore makeriskier decisions, than Piper pilots. This result, however,
was not statistically significant, given the small sample
size. This small sample size also inhibits the ability togeneralize this result to the pilot population as a whole.

A ballistic parachute system is one of many safetyenhancements that may potentially lead pilots to takegreater risks. Weather radar, moving map GPS, radar
altimeters, TCAS (Traffic Avoidance and Collision
Systems), among others may all serve to make pilots“feel” safer with respect to their current situation. These
devices certainly enhance safety and their value in thisregard is not being questioned. However, the possibility
that these devices lead to a level of complacency or agreater willingness to accept risks must be further
explored.

Also interesting to note is that pilots with the greatest
flight time, those reporting more than 5,000 hours, havethe highest overall SDI score with a mean of 455.2 (Table2). This may be due to the fact that pilots with greaterlevels of experience feel at greater ease with a wider
variety of situations than do pilots with less flight time,
and therefore fewer experiences.

Although a multitude of proven safety enhancements are
employed on Cirrus Design Corp. SR-20 and SR-22
aircraft, fatal accidents continue to occur. In spite of thefact that the final cause of many of the most recent
accidents is still unknown, several have been attributed tofaulty pilot decision making and risk-taking. One such
accident occurred on January 13, 2006, when a pilot
decided to fly into known icing conditions for which theaircraft was not equipped. All aboard were saved when theballistic parachute was deployed [20].

6.2 Correlations
Several significant correlations are of interest in this study.
First, the negative correlation (-.227) between a pilots age
and his/her response to opinion question 2 indicated thatthe older a pilot is, the more strongly they disagree with
the idea that they may take on greater risks in a ballisticparachute equipped aircraft. Similarly, a negative
correlation (-.241) existed between a pilot’s total flight

Exploring the possibility of risk compensation in thisexample involves asking a simple question. That question
is: would the accident pilot have made the decision tocontinue flight into icing conditions had his aircraft notbeen equipped with a ballistic parachute system and other178

ENRI Int. Workshop on ATM/CNS. Tokyo, Japan. (EIWAC 2010)
safety devices? If the answer is no, then risk compensation
did play a part in this accident. The pilot made riskier
decisions as a result of a perceived increased level ofsafety provided by the safety devices installed on theaircraft. Unfortunately, only the failures in decision
making can be examined when it comes to accidents. The
reasons for the decisions can only be speculated. The
accident pilot may have made the same poor decisions
regardless of equipment.

9. REFERENCES[1] Ballistic Recovery Systems, Inc. (2005). Lives saved.

Retrieved March 14, 2007 from http://www.brsparachutes.com/Lives+Saved/default.aspx.
[2] Aircraft Owners and Pilots Association. (2005). 2005

Nall Report: Accident trends and factors for 2004.
AOPA Air Safety Foundation: Krey, Neil C.

The TAA safety study team found that althoughTechnically Advanced Aircraft (TAA) provide a potential
for increased safety, this safety can only be achieved
through additional training so that pilots learn to operate
within the limitations of those systems. The TAA safety
study team goes on to state that “the traditional GA
training system… does not include training on how tomake accurate flight risk assessments and manage flightrisk properly” [21].

[3] National Transportation Safety Board. (2007).

Accident Database & Synopses. Retrieved March 14,
2007 from http://www.ntsb.gov/ntsb/query.asp.
[4] Joint Safety Analysis Team. (2002). General aviation

aeronautical decision-making. Final Report.
Washington, DC: Federal Aviation Administration.
[5] Driskill, W. E., Weissmuller, J. J., Quebe, J. C., Hand,

D. K., & Hunter, D. R. (1998). Evaluating thedecision-making skills of general aviation pilots.
DOT/FAA/AM-98/7.

This research, although limited in sample size, does
demonstrate that pilots may, in fact, take on greater risks
in an aircraft equipped with a ballistic parachute system.
This trait in pilots may in fact vary with their level ofexperience and/or age. It is also interesting to note thatyounger, less experienced pilots seem to be more willingto admit that they would take on these additional risks in aballistic-parachute equipped aircraft. These findings makeit clear that additional research is necessary in order tobetter understand the decision-making process of pilots.

[6] Hunter, D. R. (2002). Risk perception and risk

tolerance in aircraft pilots. DOT/FAA/ AM-02/17[7] Hedlund, J. (2000). Risky business: safety

regulations, risk compensation, and individual
behavior. Injury Prevention, 6, 82–90.
[8] Wilde, G. J. S., & Robertson, L. S. (2002). For andagainst: Does risk homoeostasis theory have
implications for road safety. BMJ, 324, 1149-1152.

7.1 Recommendations[9] Noland, R. B. (1995). Perceived risk and modal

Research has always attempted to discover the root causesof aviation accidents so they can be avoided in the future.
A thorough understanding of the causes of accidents leads
to improvements in training and design. Much of thedesign of Cirrus aircraft is owed to an attempt to design asystem that protects pilots and passengers from injury.
Since so many aviation accidents can be attributed tofaulty pilot decision making, it is vital that further researchattempts to understand how pilots think. This researchshould further explore, with a greater sample size than thecurrent project, the possibility that pilots make riskier
decisions when equipped with “safer” equipment. Should
this prove to be true, additional training should be
developed, and methodically tested to ensure that it
effectively combats this issue.

choice: Risk compensation in transportation systems.
Accident Analysis and Prevention, 27(4), 503-521.
[10] Assum, T., Bjornskau, T., Fosser, S., & Sagberg, F.

(1999). Risk compensation—the case of road lighting.
Accident Analysis and Prevention, 31, 545–553.
[11] Morronngiello, B. A., Walpole, B. & Lanesby, J.

(2006). Understanding children’s injury-risk
behavior: Wearing safety gear can lead to increased
risk taking, Accident Analysis and Prevention,
doi:10.1016/j.aap.2006.10.006.
[12] Morronngiello, B. A., Walpole, B. & Lanesby, J.

(2007). Risk compensation in children: Why dochildren show it in reaction to wearing safety gear?.
Journal of Applied Developmental Psychology, 28,
56–63.
[13] Morrongiello, B. A., & Major, K. (2002). Influence of

8. ACKNOWLEDGEMENTS

safety gear on parental perceptions of injury risk andtolerance for children’s risk taking. Injury Prevention,
8, 27-31.

The author completed this paper in fulfillment of the
Graduate Capstone Project while pursuing a Master’s of
Aeronautical Science Degree from Embry Riddle
Aeronautical University. Special thanks to Dr. Roxanna
Austin and Mr. Terry Cobb.

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10. COPYRIGHT
Copyright Statement[17] Jensen, R. S., Guilkey, J. E., & Hunter, D. R. (1998).

The authors confirm that they, and/or their company or
institution, hold copyright of all original material includedin their paper. They also confirm they have obtained
permission, from the copyright holder of any third party
material included in their paper, to publish it as part oftheir paper. The authors grant full permission for the
publication and distribution of their paper as part of the
EIWAC2010 proceedings or as individual off-prints from theproceedings.

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