Toward a More Realistic, Cost-Effective, and Greener Ground Movement Through Active Routing—Part I: Optimal Speed Profile Generation

Abstract

Among all airport operations, aircraft ground movement plays a key role in improving overall airport capacity as it links other airport operations. Moreover, ever-increasing air traffic, rising costs, and tighter environmental targets create pressure to minimize fuel burn on the ground. However, current routing functions envisioned in Advanced Surface Movement, Guidance and Control Systems almost exclusively consider the most timeefficient solution and apply a conservative separation to ensure conflict-free surface movement, sometimes with additional buffer times to absorb small deviations from the taxi times. Such an overly constrained routing approach may result in either a too tight planning for some aircraft so that fuel efficiency is compromised due to multiple acceleration phases, or performance could be further improved by reducing the separation and buffer times. In light of this, Parts I and II of this paper present a new Active Routing (AR) framework with the aim of providing a more realistic, cost-effective, and environmental friendly surface movement, targeting some of the busiest international hub airports. Part I of this paper focuses on optimal speed profile generation using a physics-based aircraft movement model. Two approaches based, respectively, on the Base of Aircraft Data and the International Civil Aviation Organization engine emissions database have been employed to model fuel consumption. These models are then embedded within a multiobjective optimization framework to capture the essence of different speed profiles in a Pareto optimal sense. The proposed approach represents the first attempt to systematically address speed profiles with competing objectives. Results reveal an apparent tradeoff between fuel burn and taxi times irrespective of fuel consumption modeling approaches. This will have a profound impact on the routing and scheduling and open the door for the new concept of AR discussed in Part II of this paper.

Optimal Speed Profile Generation for Airport Ground Movement with Consideration of Emissions

“…In [5], [6], a new conceptual framework, namely the Active Routing and Scheduling (AR), has been proposed mainly to address the mentioned trade-off between the time and fuel efficiency. Emissions are assumed to be correlated either with the time or fuel burn objectives, and are not explicitly included in optimal speed profile generation.…”

A real-time Active Routing approach via a database for airport surface movement

“…However, as documented in (Weiszer et al, 2014;Chen et al, 2015b), PAIA required a comparatively large computation time. In this paper, a further simplified heuristic (Weiszer et al, 2014) is used for the speed profile optimisation.…”

“…Based on the derived speed profile, taxi time (objective g 1 ) and fuel consumption (objective g 2 ) are calculated. In this paper, the method based on the ICAO database (Chen et al, 2015b) is used to model fuel consumption, which consists of physics-based equations taking into account the acceleration force and rolling resistance to calculate thrust. The calculated thrust and aircraft engines will then be mapped into corresponding fuel flows according to the ICAO database.…”

“…type and length, therefore speed profile optimisation for segments with the same properties is duplicated. As shown in (Chen et al, 2015b), by using a generic optimisation algorithm, such as PAIA, long computational times were observed. Moreover, a tailored and simplified heuristic devised in (Weiszer et al, 2014), even seeded as an initial population in PAIA, did not improve the performance of the generic optimisation algorithm significantly.…”

“…In the context of the abovementioned issues, the research presented in this paper further extends the proposed ground movement optimisation framework in (Ravizza et al, 2013b;Weiszer et al, 2014;Chen et al, 2015b) to make it fully applicable in real-time airport management systems. The main idea is to use a pre-computed database consisting of optimised speed profiles in order to avoid duplicative optimisation for the same taxiway segments.…”