The trade-off between taxi time and fuel consumption in airport ground movement

Abstract

Environmental impact is a very important agenda item in many sectors nowadays, which the air transportation sector is also trying to reduce as much as possible. One area which has remained relatively unexplored in this context is the ground movement problem for aircraft on the airport's surface. Aircraft have to be routed from a gate to a runway and vice versa and it is still unknown whether fuel burn and environmental impact reductions will best result from purely minimising the taxi times or whether it is also important to avoid multiple acceleration phases. This paper presents a newly developed multi-objective approach for analysing the trade-off between taxi time and fuel consumption during taxiing. The approach consists of a combination of a graph-based routing algorithm and a population adaptive immune algorithm to discover different speed profiles of aircraft. Analysis with data from a European hub airport has highlighted the impressive performance of the new approach. Furthermore, it is shown that the trade-off between taxi time and fuel consumption is very sensitive to the fuel-related objective function which is used.

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

“…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.…”

“…Stricter emissions regulations together with efforts of airlines to reduce fuel costs result in a demand to cut fuel consumption. As shown in (Ravizza et al, 2013b), minimum time taxiing and minimum fuel burn are conflicting objectives, as shorter times normally lead to higher rates and longer periods of acceleration. Ideally, both time and environmental objectives should be minimized simultaneously, in a form of a global optimum.…”

“…A recently published paper by Ravizza et al (2013b) presents a new concept for the ground movement problem which uses multi-objective optimisation to simultaneously optimise routing, scheduling and speed profiles, with regard to taxi time and fuel consumption. In their approach, the routing and scheduling algorithm (Ravizza et al, 2013a) is combined with the Population Adaptive based Immune Algorithm (PAIA) (Chen and Stewart, 2011;Chen and Mahfouf, 2006) in search of the trade-off between the total taxi time and fuel consumption.…”

“…However, fuel consumption is represented by a fuel index rather than actual fuel burn, and the final decision is left to controllers' subjective judgement without any quantitative indicators. Based upon (Ravizza et al, 2013b), an Active Routing (AR) framework is proposed in (Chen et al, 2015b,a), aiming at more seamless integration of speed profiles into route and schedule optimisation. A more detailed actual fuel burn modelling and an airport economic optimisation framework are also introduced to facilitate controllers making a more objective decision.…”

“…In contrast to previous research (Ravizza et al, 2013b;Weiszer et al, 2014) which considered whole routes for taxiing aircraft, in this paper we deconstruct the original problem into a set of independent subproblems for individual taxiway segments and by doing so take advantage of using stored speed profiles in a database instead of costly on-line optimisation, 2. a database of optimised speed profiles is initialized with a limited set of solutions such that the combination of speed profiles retrieved from the database can represent any possible route on the airport.…”