A novel network approach to study communication activities of air traffic controllers Yanjun Wang a,b , Jian Bu a,b , Ke Han a,c,⇑ , Rui Sun a,b , Minghua Hu a,b , Chenping Zhu d a College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China b National Key Laboratory of Air Traffic Flow Management, Nanjing 210016, China c Department of Civil and Environmental Engineering, Imperial College London, SW7 2BU, UK d Department of Physics, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China article info Article history: Received 26 January 2016 Received in revised form 6 April 2016 Accepted 21 April 2016 Keywords: Air traffic management Air traffic controller Voice communication Network science abstract Air traffic controllers play critical roles in the safety, efficiency, and capacity of air traffic management. However, there is inadequate knowledge of the dynamics of the controllers’ activities, especially from a quantitative perspective. This paper presents a novel network approach to uncover hidden patterns of the controllers’ behavior based on the voice com- munication data. We convert the time series of the controllers’ communication activities, which contain flights’ information, into a time-varying network and a static network, referred to as temporal network and time-aggregated network, respectively. These networks reflect the interaction between the controllers and the flights on a sector level, and allow us to leverage network techniques to yield new and insightful findings regarding regular pat- terns and unique characteristics of the controllers’ communication activities. The proposed methodology is applied to three real-world datasets, and the resulting networks are closely examined and compared in terms of degree distribution, community structure, and motifs. This network approach introduces a ‘‘spatial” element to the conventional analysis of the controllers’ communication events, by identifying connectivity and proximity among flights. It constitutes a major step towards the quantitative description of the controller- flight dynamics, which is not widely seen in the literature. Ó 2016 Elsevier Ltd. All rights reserved. 1. Introduction The past decade has seen a significant improvement in the air traffic management (ATM) system in terms of safety, capac- ity, and efficiency. Great efforts have been made to enhance the performance of the ATM system, including the introduction of new operational concepts and protocols, deployment of advanced automation systems, and strategic research and devel- opment activities. Despite the ongoing exercise of new operational concepts and deployment of technologies in both Single European Sky ATM Research (SESAR) in Europe, and Next Generation Air Transportation System (NextGen) in the US, air traf- fic controllers are, and continue to be, playing critical roles in the ATM system. The in-depth understanding of the controllers’ activities remains critical to ensure the safety and efficiency of the ATM system. In many problems arising from human-driven complex systems, it is necessary to evaluate the operator’s activities. Among various internal and external activities, mental workload has been the central focus of investigation in http://dx.doi.org/10.1016/j.trc.2016.04.017 0968-090X/Ó 2016 Elsevier Ltd. All rights reserved. ⇑ Corresponding author at: Center for Transport Studies, Imperial College London, SW7 2BU, UK. E-mail addresses: ywang@nuaa.edu.cn (Y. Wang), bj@nuaa.edu.cn (J. Bu), k.han@imperial.ac.uk (K. Han), rui.sun@nuaa.edu.cn (R. Sun), minghuahu@ nuaa.edu.cn (M. Hu), chenpingzhu@aliyun.com (C. Zhu). Transportation Research Part C 68 (2016) 369–388 Contents lists available at ScienceDirect Transportation Research Part C journal homepage: www.elsevier.com/locate/trc