Limited Movement through the Airspace - Coursework Example

Table of Contents Table of Contents 2 Abstract 3 Introduction 4 Decision training 5 Aiding decision making 6 Spatial Information System-SIS 6 Remote Sensing 7 Geographical Information System (GIS) 8 Application of GIS 8 Global Positioning System 9 Integrated spatial information system (ISIS 10 AIRCRAFT TRAJECTORY PREDICTION PROCESS 11 Disaster management 13 Assessment 14 Simulation exercise 15 Inter – organizational communication 16 Mental models 16 Tacit knowledge 17 Situation awareness 19 Self efficacy 22 References 23 Abstract Decision making is a complex process that requires participants to chosen a course of action from a wide multiple options, and to minimize error. Decisions made in aviation environment involve pertinent decisions by the pilot, controller or other participants before, during and after the flight through systematic approach to the mental process so as to come up with the best course of action in response to particular circumstances. Introduction Air travel like road allows limited movement through airspace. They are limited to departure and arrival on airport runways and follow stipulated air routes. Although modern air transport has expanded the scope of human spatial cognition, they have similarly controlled individual spatial decision making through restriction of travel choices to a specific networks and nodes. This study presents an analysis of aviation route planning with respect to geographical factors with the aimed at developing methodologies to support decision making process in aviation and in disaster situation. Decision making is a cognitive process of selecting a particular course of action from different alternatives. Decisions made in aviation environment involve any pertinent decisions by the pilot and shareholders during the flight through systematic approach to the mental process so as to come up with the best course of action in response to particular circumstances. Decision making is strongly dependent on the environment through Decision Support System (DSS).The decision support systems are a distinct class. It is an information system that involves the integration of specific with general-use decision support information devices (Filip, 2004). According to Clement, (1995) there are four factors which controls the decision-making process (Hellstom & Kvist, 2003). These includes: the complexity of the problem, uncertainty degree of the problem, the fact that some decision made may be right for a short term but wrong in a long term. Humans have limited capacities of solving complex problems and therefore building simple mental models of real events. Decisions made based on this model may lead to errors. The decision made has to be well informed so as to make the best decision. the decision maker should have access adequate information and high quality models ranging from simple to sophisticated mathematical models (Hellstom & Kvist, 2003). Decision training Although, military and large commercial aircrafts may afford to use powerful decision making aids devices, it may not be the case for small aviation aircrafts. According to orasanu (1993), it may not be possible to increase the all purposeful decision making skills, but specific skills and components must be developed. Westerlund (1991) urged that the attitude and motivation of a pilot influence decisions making, and therefore, training along this line will help in decision process. Such attitudes and motivations would decrease hazardous thought patterns which include anti-authority, invulnerability, impulse and resignation (Diehl &Buch, 1984). If pilots can control these attitudes then there will be efficient and safe decision making. Hazardous attitudes cause pilots to make counter-intuitive, inappropriate decisions and that may defy common sense. Metacognition training allows pilots to regulate and be aware their cognitive processes and behaviours. Pilots can learn to monitor decision making processes so as to manage time and recognize whether they have a workable solution and neglecting the need to search further. It will assist inexperienced pilots from getting blogged down with options and information enabling faster and intuitive decision process. According to Moray (1990) pilots should be trained on ‘how to change one's mind’ to ‘avoid cognitive lockup’ by being aware of their capabilities and limitations. Those with good metacognitive skills have better ideas of their weakness, strength and the potential challenges, and therefore can factor in consideration and as a result being flexible and effective. Pilots are trained on how to make mental simulation so as to anticipate future events, decision outcomes and critique their own plans. They cam modify their plans or implement new plans. Closely related to mental simulation and situation assessment is mental models. This is achieved by effective interaction and communication skills (Houghton, 1999). Aiding decision making Computer can be used by decision makers to compute and depict important situational features that can be use to select a course of action (Noble), 1993). This is focused on improving operator situation awareness and also helps the pilot through improving the salient of the most significant features of a situation for correct interpretation. It may also help in by suggesting different effective course of action. Although, the decision aiding system should not be made to be a decision making system, it can help less experienced pilots to interpret a situation just like an experienced pilot, through selection and presentation of significant information that is normally interrogated by an experienced pilot. The aid can also assist an experienced pilot under stressful condition to interpret a situation better like it would be when not in stress, through presentation of specific data, rather than a large quantity of data (Wickens et al, 1998). Humans are known to be inaccurate in approximating the probabilities and the decision aid can be used to help to remove this fault. It was reported that decision aids were installed into a fighter aircraft and it help the least experienced pilots. Spatial Information System-SIS This is combination of Geographical Information System (GIS) technologies with computer models and algorithms so as to obtain the Spatial Decision Support System. The combination can be weak or strong. Sometimes the numerical methods can only access non-spatial data but the other software modules which utilizes numerical methods require access to GIS options, resulting in an integrated modeling and management system used in modeling and formulating various scenarios (Houghton, 1999). There are two forms of interaction of the two technologies which include: a) Preparation of non-spatial data input for numerical models through operations done spatial data. d) Using spatial data to start a set of operations with the aim of evaluating the impact of the solution found through numerical methods. For example, if a school building is selected for the first alternatives, the neighbourhoods and access ways might be visualized before making a decision (Wickens et al, 1998). Information, communication, and space technologies (ICST) have been used widely in disaster management. The main information systems include: Remote Sensing This is an investigative technique which uses recording device to acquire information on a distant object in which vital information on the environment are accumulated. It comprises Aerial Remote Sensing, a process of recording data like images and photographs from sensors on Satellite and aircrafts. Satellite remote sensors consist of various sensing systems used to integrate natural hazard assessments into development plan study (Wickens et al, 1998). Geographical Information System (GIS) Geographical Information System (GIS) is hardware and software system used in measurement, storage, monitoring retrieval, analyzing, mapping and modeling different data types related geographical phenomena. It is a computer-based system that enables the user to organize the data depending on the geographical or spatial coordinates and to integrate, store, edit, analyze display or share geographically-referenced information. The information contains the spatial features like longitude, latitude or state plane which represents a given position on earth. The GIS tool aids manipulation and efficient storage of remotely sensed information including spatial and non-spatial data for both policy making and scientific management. Application of GIS GIS is used in management of resources, developing plans and in scientific investigations. Its analytical potential is used in all phases of disaster management which includes: prediction, response and recovery. In addition, it facilitates the ordering of the large data required in hazard and risk assessment and uses models to combine various data types, spatial, non-spatial and attribute data, which provides useful information at different stages of disaster management (Houghton, 1999). GIS support decision making by delivering multilayer geo-referenced data, which includes mapping, hazard zoning, critical infrastructure, accessible resources for response and real-time images from the satellite. Such information enhances efficient planning and quick assess to emergency on a geographic platform. It is also combined with GPS in search and rescue operations in areas where operations may be difficult. In addition, it is used by emergency planners to calculate emergency response times in the event of a disaster. The disaster mangers can quickly visualize and access important information by looking t the location. Such information can easily be shared among the disaster response personnel who can coordinate and implement emergency work (Wickens et al, 1998). Global Positioning System This is a satellite – based radio navigation system which provide place and time data at any weather condition around the globe. It provides flexible and accurate geographical positions and navigation systems and enables one to locate or position oneself with respect to the surrounding objects (Gopi, 2005). These system works well within some limitations like when it is cloudy. a position on the surface of the earth is descried geographical coordinates: longitude and latitude. a three dimension positioning includes the height. The advantages of GPS are: (a) Provides position accuracy (b) Can determine velocity and time (c) The signal is available to users around the globe (d) It provides three dimension information which includes: the height as well as the horizontal data. (e) It is available for 24 hrs a day with no user charges and low cost hardware. (Gopi, 2005) GPS navigation is useful to pilots, since they facilitate better navigation capability and improves situational awareness, and also reduce operation costs due to ease in flying through direct routes. On the other hand, care must be taken to ensure that the system capabilities are not exceeded. GPS navigation uses various receivers ranging from full IFR installation being used to support a VFR flight, to hand-held receiver and to a VFR only installation. The pilots must understand there limitation so as not to misuse navigation information. VFR pilots must not rely in only one system of navigation. GPS navigation should be integrated with other forms of electronic navigation as well as well as pilot’s experience. This will ensure that the pilots can navigation accurately (Houghton, 1999). Integrated spatial information system (ISIS This is the use of geo-spatial and supporting information technologies for the acquisition and processing of data from satellites, airborne sensors, ice and weather models and many other sources of data; and for the dissemination of products. CIS works under ISIS to process and integrate real-time reports, remotely sensed images and provide forecasts through model simulations. From this analysis, bulletin and charts are automatically disseminated in various formats. They are archived in spatially enabled repository and put in the web (Houghton, 1999). The integrated spatial information system (ISIS) is efficient and reliable, but can also adapt to new data sources, platforms and products. ISIS is built on software making it viable to integrate, create and distribute geo-reference images and other GIS products within the limits of CIS daily production schedules. ISIS architecture ISIS comprised of six sub-systems, each of which they provide the following functions: a. Data acquisition and processing – the data is automatically received from different platforms and sources, vector model are converted, raw images are imported through de-compression, enhancing modules and geo-referencing, and all results are placed in central repository. This subsystem requires parallel processing, balancing of load and distributed database so as to meet the dictated requirements. b. Central data repository which has rational database management system that contains data and metadata. The data is streamlined ready to be used so that expired data are recycled to along term archive automatically, but can support the analysis of the trends. c. Production sub-system is located in a workstation which provides access to data supplied by central data repository. Custom tools are used for display, sorting, integration and analysis of data in order to reveal characteristics of the environment. Maps and other spatial products are generated to enable the analysts to extract useful information from the data. This system makes use of ESRI ArcGIS and ERDAS Imagine software and include the following modules: Geo-spatial metabrowser used as an interface to the depository. The data is tabulated and spatial and temporal filters help in extraction and rapid discovery of data. d. Data order subsystem presents schedules for aircraft flight plan and downlink data. (Houghton, 1999) AIRCRAFT TRAJECTORY PREDICTION PROCESS Decision support tools can assist in mitigating many of the workload and capacity constraints of the system if there is effective integration with advance automation solutions in the ground and air systems. The tools have many purposes, but mainly serve to reduce cognitive workload of the airspace problems encountered in the decision making process. Some tools are used to predict future conflicts between aircraft, for controllers on the ground and the pilots, which allow a advance strategic management of the aircraft. The tools use in air traffic management includes the capability to forecast when and where traffic workload would stress the system, thus allows air traffic supervisors to make adjustment s to either evade the conditions or change staff or airspace where necessary (Donohue, 2001; Salas and Maurino, 2010). These also include air traffic metering tools used to sequence the aircraft into the arrival flows, increasing the system capacity. A common challenge to all these tools is making accurate and timely modeling of the current state of the current state of the aircraft and predicts the future. This is trajectory predictor (TP) process. The trajectory prediction process as applied to a commercial flight on route. An example is a generation process and a generic ground-based trajectory prediction; some TPs may re-quire more or less information. A more complex process includes more sophisticated steps like the aircraft behavior modeling, parameter estimation of in-flight or monitoring trajectory error. The TP requires access to the flight plan with the flight number, for example AAA123, the type of aircraft such as B-757-200, the filed speed, the flight altitude like 30,000 feet, and the flight route such from one point X, to A, then D, and finally to Y through the BUC 7 STAR. In addition, the TP will have an estimate of the initial status such as the current aircraft position, the altitude and the ground speed. Before undertaking trajectory prediction, the flight plan route, expressed as named jet routes or waypoints is converted to a sequence of geographical points like longitude and latitude through a process is called route conversion (Donohue, 2001). After the route has been converted, the initial condition to the converted route is joined through a mechanism process called lateral path initialization. This process involves the identification of the initial location on the route, but sometimes, the initial condition will be slightly out of route and thus connection from the initial condition to the route is needed. A more general form of this trajectory service includes lateral intent modeling, where lateral path is created based on the assumed pilot or controller procedures of operation (Wickens et al, 1998). Apart from determining the lateral path, speed and vertical factors at different points along the flight route must also be considered. This process is dictated by constraint specification, for example, speed below 10,000 feet is applied as altitude constraints on a standard terminal arrival route. Modeling along the longitudinal direction is implicit in some TPs, especially in the addition of altitude and speed which reflect how the combined pilot, controller and aircraft guidance system guide the aircraft. An example is estimation of the strategic descent speed. The above steps are based physics modeling. Another way of predicting the flight is by use of computation of aircraft trajectory. In this step, vertical and lateral route is combined to predict the behavior of the flight process, which include following the converted route, appropriate air dynamics, meeting particular constraints like speed and altitude, and reflecting the aircraft and environment effects. This will result in the predicted evolution of the state of the aircraft as a function of time (Donohue, 2001). Disaster management Disaster risk management can be facilitated by consistent accessibility of current and accurate data and as thus, information exchange and easy accessible communication practices plays a vital role disaster management. Data is also used in important ongoing research, assessing risks and monitoring of potential hazards. If information management and early warning systems are neglected in management of disaster, serious consequences may arise. A correct decision can be made at any stage of disasters if a considerable amount of data and information are available. The most important processes that relate information for disasters are: monitoring, recording, processing, sharing and dissemination (Salas and Maurino, 2010). On the other hand, information technology facilitates receiving, classifying, analyzing and disseminating of the information in real-time for the necessary decision making. The main information and data necessary for efficient disaster management are obtained from: observatory stations, data from satellite, station to station, classified experiences, training, reports, news and results obtained from research (Houghton, 1999). Assessment This involves participation by a team of trained personnel, in multiple simulations and exercises, observations and performance evaluation against the determined phenomena (Povah and Ballantyne, 1995). They do their assessment process by combining exercise and methods obtained from task analysis and operating contexts, to access behavior and to compile a profile of each individual, based how they performed on each exercise (Chan, 1996; Thornton, 1992; Joyce et al., 1994; Carrick and Williams, 1999) Multiple exercises and simulations in the assessment centers ensure high predictability. Robertson et al. (1987) and Lowry (1995) suggest that the assessment exercise should be treated as stand alone work behavior samples. In this model, the performance of an individual on the exercise is assessed based on specific behavior rating scale, rather than make reference to the underlying trait (Lowry, 1995). Assessment centers therefore allow both multi-facet emergency and specific aspects of complex management tasks and roles to be developed and practiced by an individual and through the use multiple simulation and exercises, participants are provided with opportunity to integrate them and thus foster a more holistic appreciation of the overall management of disaster. A comprehensive cover of critical competence and role also renders the centers appropriate for emergency manager selection and training (Houghton, 1999). It has been shown that, assessment center method is suitable for developing disaster management competences. it does not only use situational tests , expert observations and evaluation to perform the assessment, but also facilitate specific development of skills through the experiential approach which promote the development of cognitive competence that are useful in emergency performance. in particular, assessment centers provide development of tacit knowledge (Thackeer and Blanchard, 1999; Sternberg, 2000). In addition, simulations and exercise facilitate the creation of mental shared models (Quuanjel et al., 1998), and provide feedback to the actors (Thornton, 1992 Simulation exercise In 1999, Thacker and Blanchard state that simulation facilitates the integration of theory and application, which is essential given the rare occurrence of disaster and the need to extract and apply the lessons learned from the previous disasters during the training program. Such training allows the participants to apply knowledge to goal –oriented work, and gets feedbacks to facilitate action on the training needs (Thacker and Blanchard, 1999). simulations gives opportunities for emergency managers to develop, review and rehearse management and technical skills in a realistic environment , practice dealing with high pressure situation in supportive and safe environment as they would adopt in a disaster situation, get feedback on their performance and point out areas which require personal development, facilitate rehearsal and improve awareness of stress reactions so as to minimize negative reactions, and identify the constraints on the effective management response (Paton and Flin, 1999). They also promote inter-organizational communication during the time of crisis (Matthews and Johnson, 1995; Paton et al., 1999). Inter – organizational communication This communication is important for understanding the dynamic, complex and evolving emergency and for providing essential information in decision making. Decision is effective if it is a product of diverse sources and is meaningful within the time duration dictated by urgent or upcoming demands. As a result, information should be considered in relation to those from whom the data are obtained, those whom they collaborate with in hazard management and those to be provided with information for performance of their task (Paton et al., 1999). The effectiveness is as a result of shared mental models through collaborative work. Because of the limited time for actual experience, simulation becomes the best alternative for facilitating the outcome. Mental models In an integrated emergency situation, effective and coherent response is developed. Such environment is characterized by evolving, dynamic emergency demands, sharing of mental models which contain the participant’s background, needs, goals and interest, and the information availability (Paton, 1996; Quanjel et al., 1998). Salas et al. (1999) urged that team performance was a result of teamwork activity and joint planning by those who are to respond to a disaster. The improved performance is due to the information sharing. Serfaty and Entin (1999) in their study demonstrated that effective members of the team supply more unprompted information. The decision maker in a group can switch form implicit from where information is provided and explicit form where the information is requested. The implicit information gathering, the team members need a better understanding of the information needed by the decision maker at critical moments. Therefore, they should have a good team model. A good multi-disciplinary and multi-organizational performance and coordination requires mental models especially relating to the information needed for the accomplishment of the common goal. The people who engage in activity planning with other teams would develop similar metal model s of the work and will be engaged in unprompted sharing of information in the work periods, and thus facilitating team performance on the work (Stout et al., 1999; Cooke et al., 2000). The quality of the model reflects on the ability of the team to do implicit communication in a high task load. Assessment centers are best suited for developing mental models for effective disaster response. During the development process, the members develop an implicit knowledge of procedure and activities inside and outside their profession. due to its implicit and subconscious nature, it is essential to understand its development and effectiveness in emergency response. Tacit knowledge Simulation exercise promote consolidation and development of facts and procedural understanding of how do various tasks, and theirs application by repeatedly using the factual information (Thacker and Blanchard, 1999). The participants can be able to see the links among various sections of knowledge. New strategies including those from other professionals can therefore be learned. By emphasizing the procedural knowledge through knowing how as opposed to knowing what would create a state whereby an individual can use and develop the current, tacit knowledge useful for disaster response. Tacit knowledge is the implicit knowledge that enables people to learn from experience and apply the knowledge in a goal oriented way within the operating limits (Sternberg et al., 2000). Tacit knowledge promotes the ability to adapt and shape the real world situations, and is thus essential in determining the effects of performance in ambiguous and unpredictable emergency response. Sternberg et al. (2000) stated that tacit knowledge has three mechanisms. The first is that it is acquired independently from environmental support, tacit knowledge usually remain implicit regarding its relative value for performing duties, specifically in a typical context (Paton, 1996). Secondly, tacit knowledge is associated with practical action. It controls the behavior in unconscious way and is created out of combination of particular goals and rules. As a result, the third tacit knowledge plays a key role in attaining the real goal and in imposing meaningful and coherent relationship on complex situations when targeting multiple goals. A procedural knowledge can easily be acquired through experience. Assessment and simulation centers provides experiential learning which promote development of tacit knowledge putting emphasis on getting more information from less important, since the emergency decision makers usually work in a situation characterized by ambiguous and incomplete information, recalling of memories that are relevant to the current situation which also useful for naturalistic decision making and selective combination of information in a goal-directed manner (Thacker and Blanchard, 1999). Assessment and simulation centers makes tacit knowledge to be more manifested in an environment almost similar to that in which the performance will occur (Sterberg et al., 2000). The fact that the assessment centers can facilitate the development of tacit knowledge makes it suitable for exploring development of cognitive competence such as situation awareness that is basic to emergency decision making in integrated management (Paton et al., 1999). It is essential to understand the tacit knowledge that an individual brings to the emergency management and that which is acquired through training and experience. Since they facilitate performance under unique cases, care is taken to ensure that tacit knowledge obtained before and during routine performance, the organizational conditions and requirements does not limit the performance in a normal disaster (Paton, 1996). Simulations and exercises should therefore assume and examine the conceptual issues in operations and organization phases. Situation awareness Situation awareness plays a key role in effective emergency decision making (Cook et al., 2007). It comprises of three levels. Understanding of essential features in the environment Its integration to create a mental model of emergency situation and the environment in which it has occurred so that meaningful tasks can be selected in the light of relevant goals. The ability to predict the future events and expectation of the work to manage them These models control the attention in the most efficient ways. Maintenance of situational awareness involves monitoring of the environment, being aware of the multiple goals and the ability understands when it is important to switch from one goal to another. This depends on the ability of the operator to derive maximum information necessary for the multiple goals together with information relevant to the achievement of specific goals (Cook et al., 2007). The similarity between tacit knowledge and the cognitive competence that underpin this capability shows that the assessment centers is the best forum for developing situational awareness. The essential cues used to activate mental models should be determined and made relevant within decision support systems and simulation exercise. Goal-directed process in situation awareness is essential for reducing cognitive demands on the decision maker and expands the capacity to respond to the emerging issues. this is similar to the tacit knowledge obtained from the assessment center performance (Thacker and Blanchard, 1999, Cook et al., 2007). The decision makers should be able to point out cues that indicate new goals in the environment, and take a relevant decisive action. Multiple simulations and expert evaluation is used within the assessment centers. This represents a mechanism that is able to facilitate the all inclusive hazard capability. Situation awareness plays an important role in decision making plans. The study of naturalistic decision making (NDM) is focused on emergency decision making. Instead of using exhaustive search for options and relative advantages for various actions, emergency decisions are made naturalistically. Klein (1997) urged that in emergencies persons makes recognition-based decisions. In the face of a problem, individuals recall an event based on situation awareness from experience, which shares the key elements with the current one and apply the solutions that worked previously. By comparing the previous effective action with the present scenario, the necessary action is recalled and applied immediately. NDM has been seen in fire-fighting, emergency evacuation and in aviation accidents (Flin et al., 1996; Hendry and Burke, 1997; Orasanu, 1997). Groups and individuals in an emergency environment, where there are more options to undertake, affect the success of recognition-based decision making. the experience in this direction is obtained in simulated exercise (Flin, 1996). Another key issue in emergency decision process is distributed decision making which recognize the fact that for effective disaster response it requires the contribution by the people with different profession, functions, roles, geographical location and expertise (Samurcay and Rogalski, 1993). the effectiveness of a decision is as a result of the extent to which the participants share a mental model of the response situation, including how actions changes with time, and how their expertise add value to different parts of the same plan, but at the same time working towards a common goal (Flin, 1996; Paton et al., 1999). The capability of the emergency group to effectively use their combined expertise is determined by the quality of the shared understanding, even if they are contributing different perspectives, for problem response and for efficient and effective use of scarce resources. Simulation and collaborative exercise is required for this shared understanding, which is developed from comprehensive analysis of the possible scenarios that involves key agencies and critical evaluation (Paton et al., 1998) Evaluation is necessary to establish the extend to which the participants revered their mental models when working together under pressure, and whether and how those mental models distort or restrict the flow of information and how its utilized Weir and Smallman, 1999). The feedback and expert evaluation within the assessment centers process may help in the evaluation of the issue and recommend ways to remedy the situation where necessary. The manger must also be capable of implementing decisions. Self efficacy This ability of an individual to plan and execute a particular course of action required to achieve a given goal or work on it in a specific way (Cook et al., 2007). It predicts the work performance, persistency and effort of an individual on a specific task. The persistent of and individual is very important especially for those people who are working over a prolonged time period in ambiguous, complex situation, where the success of the outcome depends on the event being managed. Strong self efficacy is also important fro those who are exposed to high level of stress due to disaster response environment. in addition, it is useful in predicting learning in training environment as it is transferred to the actual work (Cook et al., 2007). References Gopi S., 2005. Global positioning system: principles and applications, New Delhi: Tata McGraw-Hill Pub. Co.Federal research and technology for aviation.ISBN1428920536, 9781428920538, p 16 Westerlund, E, J. (1991). The pilot judgement styles model: A new tool for training indecision making. In R. S. Jensen (Ed), Proceedings of the Sixth International Conferenceon Aviation Psychology. Columbus, OH : Ohio State University Press. Orasanu, J., & Salas, E. (1993). Team decision making in complex environments. In G.A. Klein, J. Orasanu, R. Calderwood, & C. E. Zsambok (Eds.), Decision Making inAction: Models and Methods. Norwood, NJ: Ablex Publishing. Buch, G., & Diehl, A. (1984). An investigation into the effectiveness of pilot jet training.Human Factors, 26 (5), 557-564. Noble, D. (1993). A model to support development of situation assessment aids. In G.A. Klein, J. Orasanu, R. Calderwood, & C. E. Zsambok (Eds.), Decision Making inAction: Models and Methods. Norwood, NJ : Ablex Publishing. O'Hare, D. (1990). Pilots perception of risk and hazard in generasl aviation. Aviation,Space & Environmental Medicine, 61 (17), 599-603. O'Hare, D. (1992). The ARTFUL decision maker: A framework model for aeronauticaldecision making. International Journal ofAviation Psychology, 2 (3), 175-191. Klein, G. A. (1993a). A recognition primed decision model of rapid decision making. InG. A. Klein, J. Orasanu, R. Calderwood, & C. E. Zsambok (Eds.), Decision Making inAction : Models and Methods. Norwood, NJ: Ablex Publishing. Klein, G. A., & Woods, D. D. (1993). Conclusions: Decision making in action. In G. A.Klein, J. Orasanu, R. Calderwood, & C. E. Zsambok (Eds.), Decision Making in Action: Models and Methods. Norwood, NJ: Ablex Publishing. Cook M.; Noyes J. M.; Masakowski Y., 2007. Decision making in complex environments, Aldershot, England; Burlington, VT: Ashgate Thacker J. W. and Blanchard P.N., 1999. Effective training systems, strategies and practices, Prentice-Hall, New Jersey, NJ. Klein G. 1997. Recognition-primed decision making, in Zsambo, C. and Klein G. (Eds), Naturalistic decision making, Lawrence Erlbaum, Hillsdale,NJ. Williams R. and Carrick P., 1999. Development centers – a review of assumptions, Human resource management Journal, Vol. 9, P 78-90 Houghton B., Johnston D., Flin R., Scott B. Paton D. and Ronan K., 1999. Managing natural hazards consequences: information management and decision making, Journal of America society of Professional Emergency managers, Vol 6, P 40 -48 G.L. Donohue, 2001. Air transportation systems engineering Reston, Va. American Inst. of Aeronautics and Astronauti, p 272 Wickens C.D.; et al, 1998. The future of air traffic control: human operators and automation, D.C.: National Academy Press, Salas E. and Maurino D. E., 2010. Human factors in aviation, Amsterdam; Boston: Academic Press/Elsevier Read More

Decision training Although, military and large commercial aircrafts may afford to use powerful decision making aids devices, it may not be the case for small aviation aircrafts. According to orasanu (1993), it may not be possible to increase the all purposeful decision making skills, but specific skills and components must be developed. Westerlund (1991) urged that the attitude and motivation of a pilot influence decisions making, and therefore, training along this line will help in decision process.

Such attitudes and motivations would decrease hazardous thought patterns which include anti-authority, invulnerability, impulse and resignation (Diehl &Buch, 1984). If pilots can control these attitudes then there will be efficient and safe decision making. Hazardous attitudes cause pilots to make counter-intuitive, inappropriate decisions and that may defy common sense. Metacognition training allows pilots to regulate and be aware their cognitive processes and behaviours. Pilots can learn to monitor decision making processes so as to manage time and recognize whether they have a workable solution and neglecting the need to search further.

It will assist inexperienced pilots from getting blogged down with options and information enabling faster and intuitive decision process. According to Moray (1990) pilots should be trained on ‘how to change one's mind’ to ‘avoid cognitive lockup’ by being aware of their capabilities and limitations. Those with good metacognitive skills have better ideas of their weakness, strength and the potential challenges, and therefore can factor in consideration and as a result being flexible and effective.

Pilots are trained on how to make mental simulation so as to anticipate future events, decision outcomes and critique their own plans. They cam modify their plans or implement new plans. Closely related to mental simulation and situation assessment is mental models. This is achieved by effective interaction and communication skills (Houghton, 1999). Aiding decision making Computer can be used by decision makers to compute and depict important situational features that can be use to select a course of action (Noble), 1993).

This is focused on improving operator situation awareness and also helps the pilot through improving the salient of the most significant features of a situation for correct interpretation. It may also help in by suggesting different effective course of action. Although, the decision aiding system should not be made to be a decision making system, it can help less experienced pilots to interpret a situation just like an experienced pilot, through selection and presentation of significant information that is normally interrogated by an experienced pilot.

The aid can also assist an experienced pilot under stressful condition to interpret a situation better like it would be when not in stress, through presentation of specific data, rather than a large quantity of data (Wickens et al, 1998). Humans are known to be inaccurate in approximating the probabilities and the decision aid can be used to help to remove this fault. It was reported that decision aids were installed into a fighter aircraft and it help the least experienced pilots. Spatial Information System-SIS This is combination of Geographical Information System (GIS) technologies with computer models and algorithms so as to obtain the Spatial Decision Support System.

The combination can be weak or strong. Sometimes the numerical methods can only access non-spatial data but the other software modules which utilizes numerical methods require access to GIS options, resulting in an integrated modeling and management system used in modeling and formulating various scenarios (Houghton, 1999). There are two forms of interaction of the two technologies which include: a) Preparation of non-spatial data input for numerical models through operations done spatial data. d) Using spatial data to start a set of operations with the aim of evaluating the impact of the solution found through numerical methods.

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