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.

Based on the multi-objective optimal speed profile generation framework for unimpeded taxiing aircraft presented in the precursor paper, this paper deals with how to seamlessly integrate such optimal speed profiles into a holistic decision making framework. The availability of a set of non-dominated unimpeded speed profiles for each taxiway segment with respect to conflicting objectives can significantly change the current airport ground movement research. More specifically, the routing and scheduling function that was previously based on distance, emphasizing time efficiency, could now be based on richer information embedded within speed profiles, such as the taxiing times along segments, the corresponding fuel consumption, and the associated economic implications. The economic implications are exploited over a day of operation to take into account cost differences between busier and quieter times of the airport. Therefore, the most cost-effective and tailored decision can be made, respecting the environmental impact. Preliminary results based on the proposed approach are promising and show a 9%-50% reduction in time and fuel respectively for two international airports, viz. Zurich and Manchester Airports. The study also suggests that, if the average power setting during the acceleration phase could be lifted from the level suggested by the International Civil Aviation Organization (ICAO), ground operations may achieve the best of both worlds, simultaneously improving both time and fuel efficiency. Now might be the time to move away from the conventional distance based routing and scheduling to a more comprehensive framework, capturing the multi-facetted needs of all stakeholders involved in airport ground operations.

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With increasing air traffic, rising fuel costs and tighter environmental targets, efficient airport ground operations are one of the key aspects towards sustainable air transportation. This complex system includes elements such as ground movement, runway scheduling and ground services. Previously, these problems were treated in isolation since information, such as landing time, pushback time and aircraft ground position, are held by different stakeholders with sometimes conflicting interests and, normally, are not shared. However, as these problems are interconnected, solutions as a result of isolated optimisation may achieve the objective of one problem but fail in the objective of the other one, missing the global optimum eventually. Potentially more energy and economic costs are thus required. In order to apply a more systematic and holistic view, this paper introduces a multi-objective integrated optimisation problem incorporating the newly proposed Active Routing concept. Built with systematic perspectives, this new model combines several elements: scheduling and routing of aircraft, 4-Dimensional Trajectory (4DT) optimisation, runway scheduling and airport bus scheduling. A holistic economic optimisation framework is also included to support the decision maker to select the economically optimal solution from a Pareto front of technically optimal solution. To solve this problem, a multi-objective genetic algorithm is adopted and tested on real data from an international hub airport. Preliminary results show that the proposed approach is able to provide a systematic framework so that airport efficiency, environmental assessment and economic analysis could all be explicitly optimised.

Airports face challenges due to the increasing volume of air traffic and tighter environmental restrictions which result in a need to actively integrate speed profiles into conventional routing and scheduling procedure. However, only until very recently, the research on airport ground movement has started to take into account such a speed profile optimisation problem actively so that not only time efficiency but also fuel saving and decrease in airport emissions can be achieved at the same time. It is envisioned that the realism of planning could also be improved through speed profiles. However, due to the multi-objective nature of the problem and complexity of the investigated models (objective functions), the existing speed profile optimisation approach features high computational demand and is not suitable for an on-line application. In order to make this approach more competitive for real-world application and to meet limits imposed by International Civil Aviation Organization for on-line decision time, this paper introduces a pre-computed database acting as a middleware to effectively separate the planning (routing and scheduling) module and the speed profile generation module. Employing a database not only circumvents duplicative optimisation for the same taxiway segments, but also completely avoids the computation of speed profiles during the on-line decision support owing a great deal to newly proposed database initialization procedures. Moreover, the added layer of database facilitates, in the future, more complex and realistic models to be considered in the speed profile generation module, without sacrificing on-line decision time. The experimental results carried out using data from a major European hub show that the proposed approach is promising in speeding up the search process.