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The evolution of the complexity map for Sector B by adding aircraft. 34 Complexity map for the traffic situation in Sectors A and B. The plot contours indicate the number of heading changes required by aircraft for all combinations of entering aircraft bearing and position angles. 36

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In this paper, we identify the requirements for effective function allocation within teams of human and automated agents. These functions include all the activities in the team's environment required to meet collective work goals, that is, taskwork functions. In addition, the allocation of taskwork functions then creates the need for additional teamwork functions to coordinate between agents. Key requirements include that each agent must be capable of each individual function it is allocated and must be capable of its collective set of functions, including teamwork. Of note, many important attributes may be observed only within the detailed dynamics of simulation or actual operations, particularly when a function allocation requires tightly coupled interactions and when teamwork (including humanautomation interaction) may support or detract from effective performance. Finally, we note that function allocation is a key design decision that should be made deliberately. By addressing function allocation early in design, before technologies and interfaces are created, key trade-offs can be considered and fundamental concerns with human factors addressed.

Function allocation is the design decision in which work functions are assigned to all agents in a team, both human and automated. Building on the preceding companion papers' review of the requirements of effective function allocation and discussion of a computational framework for modeling function allocation, in this paper, we develop specific metrics of function allocation that can be derived from such models as well as from observations in high-fidelity human-inthe-loop simulations or real operations. These metrics span eight issues with function allocation: (a) workload, (b) stability of the work environment, (c) mismatches between responsibility and authority, (d) incoherency in function allocations, (e) interruptive automation, (f) automation's boundary conditions, (g) function allocations limiting human adaptation to context, (h) and mission performance. Some of the metrics measure distinct issues whereas others assess different causes of issues that can manifest in similar ways; collectively, they are intended to be comprehensive in their ability to discriminate for a range of issues. Trade-offs may exist between these metrics, and they need to be examined collectively to identify potential trade-offs or conflicts between them. This paper continues the example given in the preceding companion paper, demonstrating how these metrics of function allocation can be assessed from computational simulations of an air transport flight deck through the descent phase of flight.

The collective taskwork of a team spans the functions required to achieve work goals. Within this context, function allocation is the design decision in which taskwork functions are assigned to all agents in a team, both human and automated. In addition, the allocation of taskwork functions then creates the need for additional teamwork functions to coordinate between agents. In this paper, we identify important requirements for function allocation within teams of human and automated agents. Of note, many important attributes may be observed only within the detailed dynamics of simulation or actual operations, particularly when a function allocation requires tightly coupled interactions. Building on the preceding companion paper's conceptual review of the requirements of effective function allocation, in this paper we develop a modeling framework that increases the number of aspects of function allocation that can be examined simultaneously through both static analysis and dynamic computational simulations. The taskwork and teamwork of a modern air transport flight deck with a range of function allocations is used as an example throughout, highlighting the range of phenomenon these models can describe. A follow-on companion paper discusses specific metrics of function allocation that can be derived both from such models and from observations in high-fidelity human-in-theloop simulations or real operations.

The application of intelligent cockpit systems is examined to aid air transport pilots at the task of planning and then following a safe four-dimensional trajectory to the runway threshold during emergencies. The design of a proof-of-concept system is described, including the use of embedded fast-time simulation to predict the trajectory de ned by a series of discrete actions, the models of aircraft and pilot dynamics required by the system, and the pilot interface. Then results of a ight simulator evaluation with airline pilots are detailed. In 6 of 72 simulator runs, pilots were not able to establish a stable ight path on localizer and glideslope, suggesting a need for cockpit aids. However, results also suggest that, to be operationally feasible, such an aid must be capable of suggesting safe trajectories to the pilot; an aid that only veri ed plans entered by the pilot was found to have signi cantly detrimental effects on performance and pilot workload. Results also highlight that the trajectories suggested by the aid must capture the context of the emergency; for example, in some emergencies pilots were willing to violate ight envelope limits to reduce time in ight, in other emergencies the opposite was found. IntroductionR ESPONSIBILITY for the safe completion of a ight rests primarily with the pilot in command. During emergencies onboard air transport aircraft, this responsibility can be demanding, due to the large number of tasks to which the pilot must attend, including detecting and resolving failures in aircraft systems; continuing to monitor aircraft system health; coordinating with cabin crew, airline dispatchers, and air traf c control; controlling the aircraft; and deciding on (and then following) a course of action that will result in a safe landing. This inherent dif culty is compounded by a signi cant number of stressors, including physical danger, an uncomfortable physical environment (heat, smoke, noise, etc.), an overwhelming amount of information to consider, and the need to make decisionsin a short periodof time. In addition,the aircraftmay have degraded performance and handling qualities, limiting the extent to which the pilot's past experience is relevant to the present problem.The objectives of this research were to investigate how pilots generateand then follow a four-dimensionaltrajectoryto the runway threshold during emergencies and to examine the functions needed in pilot aids for these tasks. This paper rst presentsrelevantresearch from a number of domains, highlighting the important aspects of these tasks, pilots' needs in cockpit aids, and availabletechnologies. Then, the design of a prototype aid is described. The results of a ight simulator evaluation with airline pilots are detailed.The paper concludes with a discussion of pilot performance at these tasks and design recommendations for future cockpit systems.

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