OR/MS Today, August 1997 When it Comes to Air Travel There's Safety in Numbers

By Kathleen L. McFadden OR/MS Models can be used to expand our knowledge of factors in airline safety and form the basis for setting national and international policies Many of us have traveled on an airliner at some point in our lives, possibly to attend an INFORMS conference or to reach an exciting vacation destination. But studies show that the majority of passengers aboard flights are not relaxed, but instead are quite afraid of flying. This may be partially explained by the fact that airline crashes, although rare, receive a lot of media coverage. So one might ask, "What are my odds of being killed in an airline accident?" Arnold Barnett, an aviation safety expert at MIT, has found that the current risk per scheduled U.S. domestic flight is about 1 in 7 million [1]. In other words, if you picked one flight at random each day, it would take you 19,000 years before your number was up. These odds sound comforting unless you or your loved one happen to be one of the unfortunate statistics. Many individuals in both the public and private sector continually work to improve airline safety. For example, the operations research department of the Federal Aviation Administration was established in 1988. More recently, a Center for Excellence in Operations Research was formed to address various aviation safety issues. While regulations and strategies are already in place to support the effort of reducing the risk of aviation accidents and incidents, many more are likely in the future. One major recommendation of the air safety commission headed by Vice President Al Gore was to strive to achieve a five-fold reduction in airline accidents over the next 10 years. The role of academicians in this process is to conduct safety-related research and generate safety recommendations to help prevent future aviation accidents and incidents. Researchers routinely analyze accident and incident data and use the information to build practical tools that are useful in solving aviation safety problems. Pilot Error The National Transportation Safety Board and the FAA perform investigations subsequent to an aviation mishap to determine probable cause. Pilot error, maintenance and manufacturing design flaws are typically cited as cause factors. This discussion focuses on pilot error, the major cause of aviation accidents. The airline industry is somewhat unique in that the consequences of even a small error may be fatal. Pilots will inevitably make mistakes. The challenge for OR/MS professionals is to identify and analyze factors that are associated with pilot error so that decision-makers might use this information to effectively manage and reduce that risk. Factors that influence pilot error accidents and incidents can be broken down into two major categories as depicted in Figure 1: those that are individual (internal to the pilot) and those that are situational (external to the pilot). In the past most researchers have relied on only rudimentary statistical methods in analyzing accident and incident data. Recently, researchers have begun to see the potential of OR/MS techniques in contributing to the solutions of aviation safety problems. Advanced modeling offers a richer, more comprehensive approach to addressing aviation safety concerns. The new thrust is to expand the range of models and statistical tools that are used to analyze safety data. My research has applied OR/MS modeling techniques and has focused on the individual factors associated with pilot error accidents and incidents, specifically gender and medical (alcohol misuse). Policy-relevant aviation research coupled with the use of advanced modeling, as opposed to rudimentary statistical methodologies, can provide the information needed to have an impact on the decision-making process. My intent is to illustrate this point using examples. General and Pilot Error Accidents Females have recently become a more significant group in the airline pilot profession. It has been argued that differences (e.g. physical, physiological, psychological) between males and females may affect their flying performance. It is well established in the literature that a wide variety of aptitudes, skills and cognitive abilities differ among the sexes. The largest cognitive gender differences are found in visual-spatial abilities. Research shows that males have greater visual-spatial skills than females. Males also tend to be superior in the quantitative area, while females tend to have better verbal skills. Cognitive performance and spatial abilities are among the most important attributes of flying. Verbal skills are also important to maintain safe air traffic control communication and facilitate crew coordination. To address possible gender differences in pilot flying performance, I first used contingency table analysis. With this simple approach, I found that female airline pilots were significantly more likely to have aviation accidents than their male counterparts. After exploring the data further, I discovered that female airline pilots, on average, were less experienced and much younger than males. Studies of the effect of age on pilot error accidents have demonstrated that accident rates decrease with age, but may level off for older pilots. Accident rates also tend to decrease as experience (measured by total flying hours) increases. Therefore, it was important to use a more sophisticated modeling technique that could address the issue of confounding of factor effects. Since males were older and more experienced, this explained their lower accident rates. The differences in age and experience levels of males and females were due to the fact that females have only recently entered the airline pilot profession in any significant number. After adjusting for variables in a logistic regression model, accident rates of male and female airline pilots were not significantly different [2]. These findings suggest that airlines should recruit and retain experienced pilots regardless of gender. It also cautions against affirmative action programs that lower the flying standard for females in order to increase the number of female airline pilots. More research could be done in this area using OR/MS models. For instance, it may be worthwhile to analyze other measures of flying performance for gender differences. Incidents, pilot deviations and simulator check-ride performance errors occur with greater frequency than accidents and may provide higher statistical power. Future studies might also compare the flying performance of those pilots trained in the military versus those trained through the civilian ranks. As OR/MS professionals, it may seem somewhat obvious that important factors should be adjusted for in a model. However, some prior aviation safety researchers have based their conclusions on simple statistical tests that may provide misleading results. As an example, one published gender study in aviation [3] was criticized because it used a simple approach that failed to control for recent flying hours, a measure of exposure of pilots to risk. The theory behind adjusting for risk exposure is that pilots who fly more frequently may be exposed to a greater risk of being involved in an accident. The study reported that females flying in general aviation (private flying) had significantly lower accident rates than males, and were a safer pilot group. But, if males had more recent flight time, this could explain their higher accident rates. More advanced modeling techniques should be applied to the data in general aviation to confirm prior findings of gender differences. Alcohol Misuse and Pilot Error Accidents Another one of my projects involved analyzing two strategies for reducing pilot-error aviation accidents: conducting background checks on pilots for driving-while-intoxicated (DWI) convictions and random alcohol testing of airline pilots [4]. DWI background checks have been in effect since 1987, while random alcohol testing began in 1995. Although both policies had been implemented, no empirical research had previously been conducted to justify either strategy. Random alcohol testing has imposed substantial costs on the airline industry. In contrast, the cost of verifying DWI information has been quite inexpensive, only about $2.50 per pilot. The FAA may suspend or revoke a pilot's certificate or rating if the pilot has two or more DWI convictions within a three-year period. The FAA verifies DWI information on pilots by querying the National Driver Register. Information in the NDR was unreliable prior to 1986. Therefore, the scope of my study was limited to the years 1986-1992. I found that the vast majority of airline pilots (97.55 percent) had neither flying accidents nor DWI convictions over the seven-year period. However, 1,372 pilots had DWI convictions, 1.96 percent of the airline pilot population. Table 1 compares the number of pilot-error accidents for pilots with no DWI, one DWI and two or more DWI convictions.

To address the association between DWI convictions and pilot flying performance, I applied loglinear modeling techniques. The primary advantage of this approach was that it allowed me to access multiple factors simultaneously (age, experience, gender, risk exposure and major/non-major airline employment) and to partition the contribution to variance of DWI over and above the contribution of the other factors. The results showed that DWI was significant even after adjusting for important factors. The presence of even one DWI conviction was associated with a doubling of the risk of pilot-error accidents. The presence of two or more DWIs almost quadrupled that likelihood. In contrast, my study found no evidence to support the concept of using random preflight alcohol testing as a method for preventing airline accidents. The findings suggest that cost-effectiveness and increased airline safety could be realized by improving the DWI program and reducing expenditures on random alcohol testing. I presented recommendations for policy improvements to both the FAA and the NTSB based on these findings. They were also made part of the public docket on the alcohol testing rule. My first recommendation was that the FAA continue to penalize pilots with two or more DWI convictions but use the first DWI as a trigger to identify and assist the potentially risky pilot. My second recommendation was to reduce the current random alcohol testing sampling rate based on these findings. This twofold strategy could result in greater improvements in aviation safety and reduced overall costs. Future Research and Directions It has been estimated that airline travel will increase at a rate of about 5 percent per year. While our nation's current level of air safety is remarkably high, simply maintaining that level may be inadequate for the future. Aviation safety research is critical to our success in coping with this rapidly expanding environment. Examples of just a few current and proposed research activities include the following: Developing an information infrastructure, known as the Global Analysis and Information Network (GAIN), for collecting, analyzing and disseminating aviation safety information. Developing technologies to be used in cockpits and ground control systems that reduce pilot error and pilot complacency. Examining trends in national and international airline safety data using new methodologies. Developing a computer program to study the errors of airline maintenance workers and determine solutions. Examining the challenges and opportunities surrounding global airline mergers and alliances. Barry Valentine, the former acting FAA administrator, has stated that the FAA, "is committed to continually working to make the safest air transportation system in the world even more safe." Researchers are also committed to keeping one step ahead of change in this dynamic world of aviation, and OR/MS models may well be the key to achieving this goal. Concluding Remarks I hope to have conveyed how valuable OR/MS skills are in the area of aviation safety. Aviation safety research offers exciting opportunities for OR/MS professionals. The aviation industry and the government are moving toward a more heightened technological environment. As they begin to incorporate more rapid and advanced database systems that collect and store a vast amount of information, it becomes essential to effectively analyze the data to help prevent future mishaps. This is the area where people trained in OR/MS can make valuable contributions. OR/MS models can be used to expand our knowledge of factors in airline safety and form the basis for setting new, important national and international policies. As we become more involved in aviation safety issues, a broader range of alternative and more sophisticated modeling techniques can be applied to aviation safety research which in turn will improve the safety of our nation's air transportation system. REFERENCES 1. Barnett, A., "Aviation Safety, Another Decade," Presentation at Informs San Diego, May, 1997. 2. McFadden, K. L., "Comparing Pilot-error Accident Rates of Male and Female Airline Pilots," Omega, Vol. 24, No. 4, 1996, pp. 443-450. 3. Vail, G. J. and Eckman, L.G, "Pilot-error Accidents: Male vs. Female," Applied Ergonomics, Vol. 17, 1986, pp. 297-303. 4. McFadden, K.L., "Policy Improvements for Prevention of Alcohol Misuse by Airline Pilots," Human Factors, Vol. 39, No. 1, 1997, pp. 1-8. Kathleen L. McFadden, Ph.D., is an assistant professor of Operations Management at Northern Illinois University, DeKalb, Ill. For more information, put the number 3 in the appropriate space on the Reader Service Form

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