IWAC2022 Program & Abstracts
Day 2 (Wednesday, 26 October) 16:15 - 17:45, Hall C

Technical Session 9

Air Traffic Management 2T9-1-A
Dynamic Airborne Delay Buffer Selection for Efficient Air Traffic Flow Management
Adriana Andreeva-Mori, Masahide Onji (Japan Aerospace Exploration Agency)

Air traffic flow management balances strategically demand and capacity by applying various initiatives such as grounddelay programs and controlled enroute delays. The delay assigned to each flight is determined by the estimated timeof arrival and the maximum allowed airborne delay (buffer) set to absorb uncertainties and minimize arrival runway
throughput and capacity loss. Current operations often use a constant buffer regardless of the projected traffic. This
research uses high-fidelity traffic simulations to investigate the effect of a dynamically-selected buffer optimizing thedaily flow. Three metrics are introduced to measure the performance- ground delay, airborne delay and capacity
loss. Simulations over 162 days of traffic show the potential for considerable savings using the proposed method.
Furthermore, initial feasibility investigation of machine learning applied to the dynamic buffer selection problem isperformed and it is concluded that despite a certain loss of optimality and estimation accuracy challenges, suchtechniques can be potentially used in real-life implementation.

T9-2-A
Non-CO2 Market-Based Incentives Towards Robust Climate Optimal Aircraft Trajectories
Abolfazl Simorgh, Manuel Soler (Universidad Carlos III de Madrid)

Over the past several years, the expansion of the aviation industry has created serious environmental challenges. By
using aircraft trajectory optimization to reroute climate-sensitive areas, there is a potential to reduce non-CO2 climateeffects, which account for approximately two-thirds of aviation radiative forcing. However, as the determination of suchclimate hotspots and aircraft trajectories requires meteorological variables obtained from weather forecasts, they areaffected by uncertainty. In addition, there is no climate policy for aviation non-CO2 emissions in the current plannedmarket-based instruments, implying that rerouting sensitive areas to climate increases the operational costs as theaircraft tends to fly longer routes. To this end, this study proposes the determination of robust aircraft trajectories
with objectives ranging from cost optimal to climate optimal routing options, accounting for uncertain meteorologicalconditions. To motivate airliners to utilize climate optimal routing strategy, the obtained robust trajectories are thenassessed in terms of considering charges for emitting in highly climate-sensitive regions. It is shown that by including thecost of climate impact in the operational cost, it is possible to find ”win-win” scenarios in which both the operational
cost and the climate impact are reduced. The uncertainty analysis shows that as we increase the charges for emittingin climate hotspots, the uncertainty in operational cost increases, which needs to be considered while setting up
market-based instruments for non-CO2 emissions. Such an increase in uncertainty is related to the effects of uncertain
meteorological conditions, mainly relative humidity, on quantifying the non-CO2 climate effects.

T9-3-A
Research on CDO Trajectory Optimization Based on Cost Index using Gaussian Pseudospectral
MethodZhiqiang Zhu (The Second Research Institute of CAAC), Yaoguang Diwu, Fengxun Gong, Qidong Yu (CivilAviation University of China)

The shortest descent time and the lowest fuel consumption are the research focus on CDO trajectory opti-mization.
Generally, the CDO trajectory optimization based on the best single parameter index has certain limi-tations. In thispaper, a direct optimization method of CDO trajectory based on the comprehensive index of fuel consumption andtotal flight time is presented, namely the CDO trajectory segmentation optimization method based on cost index with
Gaussian pseudospectral method. Theoretical analysis indicates that CDO tra-jectory optimization should mainly study
the optimization of segment 1 and segment 2. The results of status analysis show that CDO trajectory optimization
based on cost index is the optimum.

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