Imperial College London

Dr Ke Han

Faculty of EngineeringDepartment of Civil and Environmental Engineering

Senior Lecturer



+44 (0)20 7594 5682k.han Website CV




Mrs Maya Mistry +44 (0)20 7594 6100




605Skempton BuildingSouth Kensington Campus






BibTex format

author = {Sidiropoulos, S and Han, K and Majumdar, A and Ochieng, W},
doi = {10.1016/j.trc.2016.12.011},
journal = {Transportation Research Part C - Emerging Technologies},
pages = {212--227},
title = {Robust identification of air traffic flow patterns in Metroplex terminal areas under demand uncertainty},
url = {},
volume = {75},
year = {2016}

RIS format (EndNote, RefMan)

AB - Multi-Airport Systems (MAS), or Metroplexes, serve air traffic demand in cities with two or more airports. Due to the spatial proximity and operational interdependency of the airports, Metroplex airspaces are characterized by high complexity, and current system structures fail to provide satisfactory utilization of the available airspace resources. In order to support system-level design and management towards increased operational efficiency in such systems, an accurate depiction of major demand patterns is a prerequisite. This paper proposes a framework for the robust identification of significant air traffic flow patterns in Metroplex systems, which is aligned with the dynamic route service policy for the effective management of Metroplex operations. We first characterize deterministic demand through a spatio-temporal clustering algorithm that takes into account changes in the traffic flows over the planning horizon. Then, in order to handle uncertainties in the demand, a Distributionally Robust Optimization (DRO) approach is proposed, which takes into account demand variations and prediction errors in a robust way to ensure the reliability of the demand identification. The DRO-based approach is applied on pre-tactical (i.e. one-day planning) as well as operational levels (i.e. 2-h rolling horizon). The framework is applied to Time Based Flow Management (TBFM) data from the New York Metroplex. The framework and results are validated by Subject Matter Experts (SMEs).
AU - Sidiropoulos,S
AU - Han,K
AU - Majumdar,A
AU - Ochieng,W
DO - 10.1016/j.trc.2016.12.011
EP - 227
PY - 2016///
SN - 0968-090X
SP - 212
TI - Robust identification of air traffic flow patterns in Metroplex terminal areas under demand uncertainty
T2 - Transportation Research Part C - Emerging Technologies
UR -
UR -
UR -
VL - 75
ER -