[Medical outcomes of emergency ejections from Russian aircrafts in 2003-2010].

Outcomes of 36 accidents with 37 aircrafts (one mid-air collision) in the period of 2003-2010 have been analyzed. Of 71 ejected crew members 14 pilots died (19.7%), 26 pilots (36.6%) suffered injuries of varying severity and 31 pilots (43.7%) escaped noticeable injuries. The major causes of the deaths were late emergency escape and failure of the eject mechanism (EM). The majority of harmed pilots (n = 18, 69.2%) had slight injuries; one crew member (3.9%) was injured moderately and 7 pilots (26.9%), substantively. Most of the injuries occurred on parachute landing (40.3%). The main reasons for severe injury were parachute landing impact (69.2%) and EM failure (23.1%). Commonly injuries were caused to the head and neck (30.7%) and a bit less often to the lower and upper extremities (22.6 and 19.4% respectively). 14.5% of the injuries were brought to the body and 11.3%--to the back. Severe injuries included fractures of the spine (42.9%) and lower and upper extremities (42.9 and 14.2% respectively).

Exploring human error in military aviation flight safety events using post-incident classification systems.

INTRODUCTION: Human error classification systems theoretically allow researchers to analyze postaccident data in an objective and consistent manner. The Human Factors Analysis and Classification System (HFACS) framework is one such practical analysis tool that has been widely used to classify human error in aviation. The Cognitive Error Taxonomy (CET) is another. It has been postulated that the focus on interrelationships within HFACS can facilitate the identification of the underlying causes of pilot error. The CET provides increased granularity at the level of unsafe acts. The aim was to analyze the influence of factors at higher organizational levels on the unsafe acts of front-line operators and to compare the errors of fixed-wing and rotary-wing operations. METHOD: This study analyzed 288 aircraft incidents involving human error from an Australasian military organization occurring between 2001 and 2008. RESULTS: Action errors accounted for almost twice (44%) the proportion of rotary wing compared to fixed wing (23%) incidents. Both classificatory systems showed significant relationships between precursor factors such as the physical environment, mental and physiological states, crew resource management, training and personal readiness, and skill-based, but not decision-based, acts. The CET analysis showed different predisposing factors for different aspects of skill-based behaviors. DISCUSSION: Skill-based errors in military operations are more prevalent in rotary wing incidents and are related to higher level supervisory processes in the organization. The Cognitive Error Taxonomy provides increased granularity to HFACS analyses of unsafe acts.

Identifying training deficiencies in military pilots by applying the human factors analysis and classification system.

Without accurate analysis, it is difficult to identify training needs and develop the content of training programs required for preventing aviation accidents. The human factors analysis and classification system (HFACS) is based on Reason's system-wide model of human error. In this study, 523 accidents from the Republic of China Air Force were analyzed in which 1762 human errors were categorized. The results of the analysis showed that errors of judgment and poor decision-making were commonly reported amongst pilots. As a result, it was concluded that there was a need for military pilots to be trained specifically in making decisions in tactical environments. However, application of HFACS also allowed the identification of systemic training deficiencies within the organization further contributing to the accidents observed.

Helicopter type and accident severity in Helicopter Emergency Medical Services missions.

OBJECTIVE: Whereas accident rates and fatal accident rates for Helicopter Emergency Medical Services (HEMS) were investigated sufficiently, resulting consequences for the occupants remain largely unknown. The present study aimed to classify HEMS accidents in Germany to prognosticate accident severity with regard to the helicopter model used. METHODS: German HEMS accidents (1 Sept. 1970-31 Dec. 2009) were gathered as previously reported. Accidents were categorized in relation to the most severe injury, i.e., (1) no; (2) slight; (3) severe; and (4) fatal injuries. Only helicopter models with at least five accidents were analyzed to retrieve representative data. Prognostication was estimated by the relative percentage of each injury type compared to the total number of accidents. RESULTS: The model BO105 was most often involved in accidents (38 of 99), followed by BK117 and UH-1D. OfN = 99 accidents analyzed, N = 63 were without any injuries (63.6%), N = 8 resulted in minor injuries of the occupants (8.1%), and N = 9 in major injuries (9.1%). Additionally, N = 19 fatal accidents (19.2%) were registered. EC135 and BK1 17 had the highest incidence of uninjured occupants (100% vs. 88.2%) and the lowest percentage of fatal injuries (0% vs. 5.9%; all P > 0.05). Most fatal accidents occurred with the models UH-1D, Bell 212, and Bell 412. DISCUSSION: Use of the helicopter models EC135 and BK117 resulted in a high percentage of uninjured occupants. In contrast, the fatality rate was highest for the models Bell UH-I D, Bell 222, and Bell 412. Data from the present study allow for estimating accident risk in HEMS missions and prognosticating resulting fatalities, respectively.

Fixed-wing medical transport crashes: characteristics associated with fatal outcomes.

INTRODUCTION: Previous studies within the aeromedical literature have looked at factors associated with fatal outcomes in helicopter medical transport, but no analysis has been conducted on fixed-wing aeromedical flights. The purpose of this study was to look at fatality rates in fixed-wing aeromedical transport and compare them with general aviation and helicopter aeromedical flights. METHODS: This study looked at factors associated with fatal outcomes in fixed-wing aeromedical flights, using the National Transportation Safety Board Aviation Accident Incident Database from 1984 to 2009. RESULTS: Fatal outcomes were significantly higher in medical flights (35.6 vs. 19.7%), with more aircraft fires (20.3 vs. 10.5%) and on-ground collisions (5.1 vs. 2.0%) compared with commercial flights. Aircraft fires occurred in 12 of the 21 fatal crashes (57.1%), compared with only 2 of the 38 nonfatal crashes (5.3%) (P < .001). In the multiple logistic regression model, the only factor with increased odds of a fatal outcome was the presence of a fire (56.89; 95% CI, 4.28-808.23). CONCLUSIONS: Similar to published studies in helicopter medical transport, postcrash fires are the primary factor associated with fatal outcomes in fixed-wing aeromedical flights.

Evaluation of a Human Factors Analysis and Classification System as used by simulated mishap boards.

BACKGROUND: The reliability of the Department of Defense Human Factors Analysis and Classification System (DOD-HFACS) has been examined when used by individuals working alone to classify the causes of summary, or partial, information about a mishap. However, following an actual mishap a team of investigators would work together to gather and analyze a large amount of information before identifying the causal factors and coding them with DOD-HFACS. METHOD: There were 204 military Aviation Safety Officer students who were divided into 30 groups. Each group was provided with evidence collected from one of two military aviation mishaps. DOD-HFACS was used to classify the mishap causal factors. RESULTS: Averaged across the two mishaps, acceptable levels of reliability were only achieved for 56.9% of nanocodes. There were high levels of agreement regarding the factors that did not contribute to the incident (a mean agreement of 50% or greater between groups for 91.0% of unselected nanocodes); the level of agreement on the factors that did cause the incident as classified using DOD-HFACS were low (a mean agreement of 50% or greater between the groups for 14.6% of selected nanocodes). DISCUSSION: Despite using teams to carry out the classification, the findings from this study are consistent with other studies of DOD-HFACS reliability with individuals. It is suggested that in addition to simplifying DOD-HFACS itself, consideration should be given to involving a human factors/organizational psychologist in mishap investigations to ensure the human factors issues are identified and classified in a consistent and reliable manner.

Evaluation of a human factors analysis and classification system used by trained raters.

BACKGROUND: The U.S. Department of Defense (DoD) has used the DoD Human Factors Analysis and Classification System (DoD-HFACS) to help identify and classify human factors that may have caused or contributed to aircraft mishaps since 2005. METHOD: In this study 22 military officers used DoD-HFACS to classify information obtained from an interview with an individual who had been involved in an aviation incident in which the potential for serious injury had been high. RESULTS: It was found that although the overall interrater reliability was generally acceptable (as reflected by a mean Fleiss' kappa of 0.75) and there were high levels of agreement regarding the factors that did not contribute to the incident (there was agreement of 50% or greater between raters for 84.4% of unselected nanocodes); the level of agreement on the factors that did cause the incident as classified using DoD-HFACS were lower than desirable (agreement of 50% or greater between raters that a particular nanocode was causal was found only for a mean of 22.5% of selected nanocodes). DISCUSSION: The findings from this study are consistent with the small number of other studies reporting an evaluation of the reliability of DoD-HFACS. It is recommended that organizations must evaluate the reliability and validity of mishap coding systems, as applied by the proposed end-users, prior to the widespread adoption of a system. It is only through the accurate identification of mishap causal factors that informed decisions can be made to prevent future mishaps.

Evaluation of the HFACS-ADF safety classification system: inter-coder consensus and intra-coder consistency.

This article evaluates an adaptation of the human factors analysis and classification system (HFACS) adopted by the Australian Defence Force (ADF) to classify factors that contribute to incidents. Three field studies were undertaken to assess the reliability of HFACS-ADF in the context of a particular ADF air traffic control (ATC) unit. Study one was designed to assess inter-coder consensus between many coders for two incident reports. Study two was designed to assess inter-coder consensus between one participant and the previous original analysts for a large set of incident reports. Study three was designed to test intra-coder consistency for four participants over many months. For all studies, agreement was low at the level of both fine-level HFACS-ADF descriptors and high-level HFACS-type categories. A survey of participants suggested that they were not confident that HFACS-ADF could be used consistently. The three field studies reported suggest that the ADF adaptation of HFACS is unreliable for incident analysis at the ATC unit level, and may therefore be invalid in this context. Several reasons for the results are proposed, associated with the underlying HFACS model and categories, the HFACS-ADF adaptations, the context of use, and the conduct of the studies.

Development of a bespoke human factors taxonomy for gliding accident analysis and its revelations about highly inexperienced UK glider pilots.

Low-hours solo glider pilots have a high risk of accidents compared to more experienced pilots. Numerous taxonomies for causal accident analysis have been produced for powered aviation but none of these is suitable for gliding, so a new taxonomy was required. A human factors taxonomy specifically for glider operations was developed and used to analyse all UK gliding accidents from 2002 to 2006 for their overall causes as well as factors specific to low hours pilots. Fifty-nine categories of pilot-related accident causation emerged, which were formed into progressively larger categories until four overall human factors groups were arrived at: 'judgement'; 'handling'; 'strategy'; 'attention'. 'Handling' accounted for a significantly higher proportion of injuries than other categories. Inexperienced pilots had considerably more accidents in all categories except 'strategy'. Approach control (path judgement, airbrake and speed handling) as well as landing flare misjudgement were chiefly responsible for the high accident rate in early solo glider pilots.

FIA Score: a simple risk index for predicting fatality in aviation crashes.

BACKGROUND: Previous studies have identified a variety of risk factors for occupant fatality in aviation crashes. A simple composite index measuring the risk of fatality in a given crash, however, is lacking. METHODS: The FIA Score is a four-point (0-3) index based on the number of three risk factors for occupant fatality present in a given aviation crash: fire, instrument meteorological condition, and being away from airport. We assessed the validity of this risk index using aviation crash investigation data from the National Transportation Safety Board for the years 1983 to 2005. Sensitivity, specificity, and area under the receiver operating characteristic curve according to the type of flight operations were computed. The analysis was first limited to pilot-in-command fatality and then replicated to any fatality. RESULTS: The study sample consisted of 44,828 aviation crashes, in which 7,889 (18%) pilots-in-command were fatally injured. The pilot crash fatality rate was 3%, 18%, 62%, and 89% for FIA Scores of 0 (none of the 3 risk factors present), 1, 2, and 3 (all 3 risk factors present), respectively. The FIA Score performed consistently well in predicting pilot fatality in crashes involving different types of flight operations. The area under receiver operating characteristic curve was 0.86 (95% confidence interval [CI]: 0.78-0.95) for major airline crashes, 0.83 (95% CI: 0.80-0.85) for commuter and air taxi crashes, and 0.81 (95% CI: 0.81-0.82) for general aviation crashes. The results were similar when the outcome was measured by whether or not the crash resulted in any fatality. CONCLUSIONS: The FIA Score appears to be a valid tool for measuring fatality risk in aviation crashes. Given its simplicity, the FIA risk index should be readily applicable to trauma research and prevention.

Recurrent error pathways in HFACS data: analysis of 95 mishaps with remotely piloted aircraft.

BACKGROUND: According to Reason's model of accident causation, mishaps tend to fall into recurrent patterns. This model is the foundation for the Human Factors Analysis and Classification System (HFACS), which is now widely used in aviation accident analysis. The purpose of this study was to determine if it was possible to use HFACS to identify recurrent error pathways within an existing mishap database. METHODS: All MQ-1 Predator remotely piloted aircraft (RPA) mishaps and safety incidents reported to the Air Force Safety Center during fiscal years 1997-2005 were evaluated and entered into a mishap database (N = 95). An exploratory principal component analysis (PCA) was used to assess the factorial structure within the set of crewmember-related mishaps (N = 48). The results of the PCA were used to define recurrent pathways from latent to active failure and hence mishaps. A tree diagram was subsequently created to quantitatively assess the associations identified in the PCA. RESULTS: Four factors were identified, each consisting of one of the HFACS categories of active failure and one or more categories of latent failure. Two additional factors were identified, consisting of fatigue and motivational latent failures. Based on analysis of the tree diagram, the majority of mishaps were caused by latent failures involving organizational factors and the technological environment. CONCLUSIONS: It was possible to identify four recurrent error pathways associated with the four types of HFACS active failures within this sample of RPA mishaps. Two of these error pathways, accounting for 57% of crewmember-related mishaps, were consistent with situation awareness errors associated with perception of the environment.

Development and validation of Aviation Causal Contributors for Error Reporting Systems (ACCERS).

OBJECTIVE: This investigation sought to develop a reliable and valid classification system for identifying and classifying the underlying causes of pilot errors reported under the Aviation Safety Action Program (ASAP). BACKGROUND: ASAP is a voluntary safety program that air carriers may establish to study pilot and crew performance on the line. In ASAP programs, similar to the Aviation Safety Reporting System, pilots self-report incidents by filing a short text description of the event. The identification of contributors to errors is critical if organizations are to improve human performance, yet it is difficult for analysts to extract this information from text narratives. A taxonomy was needed that could be used by pilots to classify the causes of errors. METHOD: After completing a thorough literature review, pilot interviews and a card-sorting task were conducted in Studies 1 and 2 to develop the initial structure of the Aviation Causal Contributors for Event Reporting Systems (ACCERS) taxonomy. The reliability and utility of ACCERS was then tested in studies 3a and 3b by having pilots independently classify the primary and secondary causes of ASAP reports. RESULTS: The results provided initial evidence for the internal and external validity of ACCERS. Pilots were found to demonstrate adequate levels of agreement with respect to their category classifications. CONCLUSIONS: ACCERS appears to be a useful system for studying human error captured under pilot ASAP reports. Future work should focus on how ACCERS is organized and whether it can be used or modified to classify human error in ASAP programs for other aviation-related job categories such as dispatchers. APPLICATION: Potential applications of this research include systems in which individuals self-report errors and that attempt to extract and classify the causes of those events.

A self-report critical incident assessment tool for army night vision goggle helicopter operations.

OBJECTIVE: The present study sought to examine the utility of a self-report tool that was designed as a partial substitute for a face-to-face cognitive interview for critical incidents involving night vision goggles (NVGs). BACKGROUND: The use of NVGs remains problematic within the military environment, as these devices have been identified as a factor in a significant proportion of aircraft accidents and incidents. The self-report tool was structured to identify some of the cognitive features of human performance that were associated with critical incidents involving NVGs. The tool incorporated a number of different levels of analysis, ranging from specific behavioral responses to broader cognitive constructs. METHOD: Reports were received from 30 active pilots within the Australian Army using the NVG Critical Incident Assessment Tool (NVGCIAT). RESULTS: The results revealed a correspondence between specific types of NVG-related errors and elements of the Human Factors Analysis and Classification System (HFACS). In addition, uncertainty emerged as a significant factor associated with the critical incidents that were recalled by operators. CONCLUSION: These results were broadly consistent with previous research and provide some support for the utility of subjective assessment tools as a means of extracting critical incident-related data when face-to-face cognitive interviews are not possible. APPLICATION: In some circumstances, the NVGCIAT might be regarded as a substitute cognitive interview protocol with some level of diagnosticity.

Human error and commercial aviation accidents: an analysis using the human factors analysis and classification system.

OBJECTIVE: The aim of this study was to extend previous examinations of aviation accidents to include specific aircrew, environmental, supervisory, and organizational factors associated with two types of commercial aviation (air carrier and commuter/ on-demand) accidents using the Human Factors Analysis and Classification System (HFACS). BACKGROUND: HFACS is a theoretically based tool for investigating and analyzing human error associated with accidents and incidents. Previous research has shown that HFACS can be reliably used to identify human factors trends associated with military and general aviation accidents. METHOD: Using data obtained from both the National Transportation Safety Board and the Federal Aviation Administration, 6 pilot-raters classified aircrew, supervisory, organizational, and environmental causal factors associated with 1020 commercial aviation accidents that occurred over a 13-year period. RESULTS: The majority of accident causal factors were attributed to aircrew and the environment, with decidedly fewer associated with supervisory and organizational causes. Comparisons were made between HFACS causal categories and traditional situational variables such as visual conditions, injury severity, and regional differences. CONCLUSION: These data will provide support for the continuation, modification, and/or development of interventions aimed at commercial aviation safety. APPLICATION: HFACS provides a tool for assessing human factors associated with accidents and incidents.

Analysis of 2004 German general aviation aircraft accidents according to the HFACS model.

INTRODUCTION: The number of aircraft accidents remains on a constant level since the late 1990s. Routine analysis in detail of the causative factors is not carried out in Germany. The analysis of flight mishaps has been demonstrated to be an important basis for flight safety. The Human Factors Analysis and Classification System (HFACS) model is best suitable for aircraft accident analysis. The aim of this study was to classify aircraft accidents in the General Aviation (GA) of Germany according to the HFACS model and to figure out the underlying causes. MATERIAL AND METHODS: The analysis was performed with the HFACS model and on the basis of the regularly published reports of the German state department for aircraft accident analysis (BFU) including accidents (but not incidents) of GA aircraft flown by German pilots in Germany and in other countries. The underlying reasons were classified as follows: pilot errors, organizational factors, ergonomic factors, aeromedical problems, and crew resource management. Additionally, the phase of the flight was classified. RESULTS: Two hundred thirty-nine GA aircraft accidents were registered in 2004 in Germany. Eighty-seven (36%) were reported in the class up to 2 tons, six (3%) in the class of 2.0 to 5.7 tons, 28 (12%) for Touring Motor Gliders (TMG), and 118 (49%) for gliders. Of these accidents, 54 (35 crewmembers and 19 passengers) aircraft occupants survived slightly injured, 35 (23 crewmembers and 12 passengers) were seriously injured, and 34 (21 crewmembers and 13 passengers) were killed. Data for uninjured aircraft occupants were not available. Most accidents happened on summer weekends during approach and landing (53%) due to pilot errors (84%). CONCLUSIONS: Our data mainly seem to be in concordance with previously published data on GA. An improvement of flight safety can be achieved only with a detailed analysis of the accident data. Therefore, more data on aircraft accidents in Germany are needed, for example, by adapting the German aircraft accident report form. Pilots should train in approaches and landings to conduct a higher level of proficiency.

Human factors analysis and classification system applied to civil aircraft accidents in India.

INTRODUCTION: The Human Factors Analysis and Classification System (HFACS) has gained wide acceptance as a tool to classify human factors in aircraft accidents and incidents. This study on application of HFACS to civil aircraft accident reports at Directorate General Civil of Aviation (DGCA), India, was conducted to ascertain the practicability of applying HFACS to existing investigation reports and to analyze the trends of human factor causes of civil aircraft accidents. METHOD: Accident investigation reports held at DGCA, New Delhi, for the period 1990--99 were scrutinized. In all, 83 accidents occurred during this period, of which 48 accident reports were evaluated in this study. RESULTS: One or more human factors contributed to 37 of the 48 (77.1%) accidents. The commonest unsafe act was 'skill based errors' followed by 'decision errors.' Violations of laid down rules were contributory in 16 cases (33.3%). 'Preconditions for unsafe acts' were seen in 23 of the 48 cases (47.9%). A fairly large number (52.1%) had 'organizational influences' contributing to the accident. DISCUSSION: These results are in consonance with larger studies of accidents in the U.S. Navy and general aviation. Such a high percentage of 'organizational influences' has not been reported in other studies. This is a healthy sign for Indian civil aviation, provided effective remedial action for the same is undertaken.

A classification on human factor accident/incident of China civil aviation in recent twelve years.

OBJECTIVE: To study human factor accident/incident occurred during 1990-2001 using new classification standard. METHOD: The human factor accident/incident classification standard is developed on the basis of Reason's Model, combining with CAAC's traditional classifying method, and applied to the classified statistical analysis for 361 flying incidents and 35 flight accidents of China civil aviation, which is induced by human factors and occurred from 1990 to 2001. RESULT: 1) the incident percentage of taxi and cruise is higher than that of takeoff, climb and descent. 2) The dominating type of flight incidents is diverging of runway, overrunning, near-miss, tail/wingtip/engine strike and ground obstacle impacting. 3) The top three accidents are out of control caused by crew, mountain collision and over runway. 4) Crew's basic operating skill is lower than what we imagined, the mostly representation is poor correcting ability when flight error happened. 5) Crew errors can be represented by incorrect control, regulation and procedure violation, disorientation and diverging percentage of correct flight level. CONCLUSION: The poor CRM skill is the dominant factor impacting China civil aviation safety, this result has a coincidence with previous study, but there is much difference and distinct characteristic in top incident phase, the type of crew error and behavior performance compared with that of advanced countries. We should strengthen CRM training for all of pilots aiming at the Chinese pilot behavior characteristic in order to improve the safety level of China civil aviation.

Light aircraft crash--a case analysis of injuries.

BACKGROUND: As air travel increases and the number of commercial and non-commercial flights rises, so does the number of aircraft accidents. The improved safety standards of the aviation industry result in a growing number of survivors of aircraft crashes, but there are no management guidelines for the treatment of these survivors. OBJECTIVES: To present our experience in treating five survivors of a light aircraft crash that occurred in August 1995 near Jerusalem. RESULTS: All five survivors sustained vertebral column injuries, which was the only injury in most of the survivors. We discuss the mechanism of injury. CONCLUSIONS: Investigation of injuries' pattern in survivors of aircraft crash is important for establishing management protocols in trauma centers.

Characteristics of general aviation crashes involving mature male and female pilots.

BACKGROUND: General aviation crashes in the United States were analyzed to identify differences between male and female pilots in the circumstances of their crashes and the types of pilot errors involved. METHODS: All 144 female pilots who were born between 1933 and 1942 and who were involved in general aviation crashes between 1983 and 1997 were matched 1:2 with 287 male pilots by age within 2 yr, medical certificate and pilot certificate, state or region of crash, and year of crash. RESULTS: Mechanical failure, gear up landings, improper IFR approaches, and collisions with wires or poles were more common in crashes of male pilots. Loss of control on landing/takeoff was more common in crashes of female pilots. Mishandling aircraft kinetics was the most common error of pilots of both genders and was noted more often in female pilots' crashes (81% vs. 48%) (p < 0.001). Males' crashes were more likely to involve flawed decisions (29% vs. 19% of females' crashes) (p = 0.027) or inattention (32% vs. 19%) (p = 0.004). Older pilots made fewer errors: among males age 55-63, 26% of crashes were without obvious pilot error compared with only 7% at age 40-49 (p = 0.003). CONCLUSION: There are large gender differences in the types of pilot error involved in general aviation crashes. Mishandling aircraft kinetics, poor decision making, and inattention are the most common pilot errors and merit increased attention in pilot training.

Spatial disorientation in U.S. Army rotary-wing operations.

This paper describes two surveys concerning spatial disorientation (SD) in U.S. Army rotary-wing operations that sought to assess the hazard and to identify recommendations to control it. One survey was of accident records, and the other was of aircrew experiences. Both surveys highlighted the magnitude of the problem. The accident survey showed that 30% of class A to C accidents involved SD as a significant factor, while the aircrew survey showed that 78% of aircrews have been disoriented (8% to the extent that flight safety was threatened). Both surveys showed a significant increase in SD associated with combat operations. Several differences between the two surveys were noted: 90% of the reviewed accidents were thought to involve type I (unrecognized) SD compared with only 43% of the reported incidents; both pilots in a particular aircraft were considered to have been disoriented in at least 59% of accidents compared with 23% of incidents; sudden loss of visual cues ("brownout," "whiteout," or inadvertent entry to instrument meteorological conditions) accounted for 25% of SD accidents compared with 13% of incidents; and 62% of the accidents occurred at night compared with only 36% of incidents. Neither survey showed any association between SD and fatigue or other human factors. The results of both surveys suggested that crew coordination, alerting devices (e.g., audio warnings on the radar altimeter), flight information displays, and autopilot functions would be good targets for improvement.