Empirical exploration of air traffic and human dynamics in terminal airspaces

Air traffic is widely known as a complex, task-critical techno-social system, with numerous interactions between airspace, procedures, aircraft and air traffic controllers. In order to develop and deploy high-level operational concepts and automation systems scientifically and effectively, it is essential to conduct an in-depth investigation on the intrinsic traffic-human dynamics and characteristics, which is not widely seen in the literature. To fill this gap, we propose a multi-layer network to model and analyze air traffic systems. A Route-based Airspace Network (RAN) and Flight Trajectory Network (FTN) encapsulate critical physical and operational characteristics; an Integrated Flow-Driven Network (IFDN) and Interrelated Conflict-Communication Network (ICCN) are formulated to represent air traffic flow transmissions and intervention from air traffic controllers, respectively. Furthermore, a set of analytical metrics including network variables, complex network attributes, controllers' cognitive complexity, and chaotic metrics are introduced and applied in a case study of Guangzhou terminal airspace. Empirical results show the existence of fundamental diagram and macroscopic fundamental diagram at the route, sector and terminal levels. Moreover, the dynamics and underlying mechanisms of "ATCOs-flow" interactions are revealed and interpreted by adaptive meta-cognition strategies based on network analysis of the ICCN. Finally, at the system level, chaos is identified in conflict system and human behavioral system when traffic switch to the semi-stable or congested phase. This study offers analytical tools for understanding the complex human-flow interactions at potentially a broad range of air traffic systems, and underpins future developments and automation of intelligent air traffic management systems.Comment: 30 pages, 28 figures, currently under revie

Heads, I Win. Tails, You Lose

To develop and deliver desirable and viable products, services, processes, and policy, government organizations rely on teamwork. Yet, most forms of organization cannot help but engender conflict in such areas as strategy, organization, people, business processes, and rewards and recognition. Organizational conflict, fuelled daily by such perennials as corporate silos, must be accepted then actively managed. Yet, most individuals and organizations are disappointingly poor at resolving problems, preferring instead to avoid or satisfice—the strategy for decision making whereby alternatives are considered until an acceptable option is found, not necessarily the optimal one. Promoting effective cross-functional collaboration demands that an enabling environment be built for that very purpose

Towards Autonomous Aviation Operations: What Can We Learn from Other Areas of Automation?

Rapid advances in automation has disrupted and transformed several industries in the past 25 years. Automation has evolved from regulation and control of simple systems like controlling the temperature in a room to the autonomous control of complex systems involving network of systems. The reason for automation varies from industry to industry depending on the complexity and benefits resulting from increased levels of automation. Automation may be needed to either reduce costs or deal with hazardous environment or make real-time decisions without the availability of humans. Space autonomy, Internet, robotic vehicles, intelligent systems, wireless networks and power systems provide successful examples of various levels of automation. NASA is conducting research in autonomy and developing plans to increase the levels of automation in aviation operations. This paper provides a brief review of levels of automation, previous efforts to increase levels of automation in aviation operations and current level of automation in the various tasks involved in aviation operations. It develops a methodology to assess the research and development in modeling, sensing and actuation needed to advance the level of automation and the benefits associated with higher levels of automation. Section II describes provides an overview of automation and previous attempts at automation in aviation. Section III provides the role of automation and lessons learned in Space Autonomy. Section IV describes the success of automation in Intelligent Transportation Systems. Section V provides a comparison between the development of automation in other areas and the needs of aviation. Section VI provides an approach to achieve increased automation in aviation operations based on the progress in other areas. The final paper will provide a detailed analysis of the benefits of increased automation for the Traffic Flow Management (TFM) function in aviation operations

Agent and cyber-physical system based self-organizing and self-adaptive intelligent shopfloor

The increasing demand of customized production results in huge challenges to the traditional manufacturing systems. In order to allocate resources timely according to the production requirements and to reduce disturbances, a framework for the future intelligent shopfloor is proposed in this paper. The framework consists of three primary models, namely the model of smart machine agent, the self-organizing model, and the self-adaptive model. A cyber-physical system for manufacturing shopfloor based on the multiagent technology is developed to realize the above-mentioned function models. Gray relational analysis and the hierarchy conflict resolution methods were applied to achieve the self-organizing and self-adaptive capabilities, thereby improving the reconfigurability and responsiveness of the shopfloor. A prototype system is developed, which has the adequate flexibility and robustness to configure resources and to deal with disturbances effectively. This research provides a feasible method for designing an autonomous factory with exception-handling capabilities

Conflict in Organizations

{Excerpt} Michael Cohen, James March, and Johan Olsen9 have developed an influential, agent-based representation of organizational decision-making processes. They submit that organizations are—at least in part and part of the time—distinguished by three general properties: (i) problematic preferences, (ii) unclear technology, and (iii) fluid participation. Citing, “Although organizations can often be viewed conveniently as vehicles for solving well-defined problems or structures within which conflict is resolved through bargaining, they also provide sets of procedures through which participants arrive at an interpretation of what they are doing and what they have done while in the process of doing it. From this point of view, an organization is a collection of choices looking for problems, issues and feelings looking for decision situations in which they might be aired, solutions looking for issues to which they might be the answer, and decision makers looking for work.” Decision opportunities characterized by problematic preferences, unclear technology, and fluid participation, viz., ambiguous stimuli, generate three possible outcomes, each driven by the energy it requires within the confines of organizational structure. These outcomes, whose meaning changes over time, are resolution, oversight, and flight. Significantly, resolution of problems as a style for making decisions is not the most common; in its place, decision making by flight or oversight is the feature. Is it any wonder then that the relatively complicated intermeshing of elements does not enable organizations to resolve problems as often as their mandates demand

Policy-based autonomic control service

Recently, there has been a considerable interest in policy-based, goal-oriented service management and autonomic computing. Much work is still required to investigate designs and policy models and associate meta-reasoning systems for policy-based autonomic systems. In this paper we outline a proposed autonomic middleware control service used to orchestrate selfhealing of distributed applications. Policies are used to adjust the systems autonomy and define self-healing strategies to stabilize/correct a given system in the event of failures