• Aircraft taxi time prediction: Comparisons and insights

      Ravizza, Stefan; Chen, Jun; Atkin, Jason A. D.; Stewart, Paul; Burke, Edmund K.; University of Lincoln (Elsevier, 2014-01)
      The predicted growth in air transportation and the ambitious goal of the European Commission to have on-time performance of flights within 1 min makes efficient and predictable ground operations at airports indispensable. Accurately predicting taxi times of arrivals and departures serves as an important key task for runway sequencing, gate assignment and ground movement itself. This research tests different statistical regression approaches and also various regression methods which fall into the realm of soft computing to more accurately predict taxi times. Historic data from two major European airports is utilised for cross-validation. Detailed comparisons show that a TSK fuzzy rule-based system outperformed the other approaches in terms of prediction accuracy. Insights from this approach are then presented, focusing on the analysis of taxi-in times, which is rarely discussed in literature. The aim of this research is to unleash the power of soft computing methods, in particular fuzzy rule-based systems, for taxi time prediction problems. Moreover, we aim to show that, although these methods have only been recently applied to airport problems, they present promising and potential features for such problems.
    • Optimal speed profile generation for airport ground movement with consideration of emissions

      Chen, Jun; Weiszer, Michal; Stewart, Paul; University of Derby (IEEE, 2015-09)
      Emissions during the ground movement are mostly calculated based on International Civil Aviation Organisation (ICAO) emission databank. The fuel flow rate is normally assumed as a constant, hence the emission index. Therefore, no detailed discrimination of power settings during ground movement is considered to account for different emissions at different power settings. This may lead to a suboptimal and often unrealistic taxi planning. At the heart of the recently proposed Active Routing (AR) framework for airport ground movement is the unimpeded optimal speed profile generation, taking into account both time and fuel efficiency. However, emissions have not been included in the process of generating optimal speed profiles. Taking into account emissions in ground operations is not a trial task as not all emissions can be reduced on the same path of reducing time and fuel burn. In light of this, in this paper, a detailed analysis of three main emissions at the airports, viz. CO, Total Hydrocarbon (HC), and NOx, are carried out in order to obtain a minimum number of conflicting objectives for generating optimal speed profiles. The results show that NOx has a strong linear correlation with fuel burn across all aircraft categories. For the heavy aircraft, HC and CO should be treated individually apart from the time and fuel burn objectives. For medium and light aircraft, a strong correlation between HC, CO and time has been observed, indicating a reduced number of objectives will be sufficient to account for taxi time, fuel burn and emissions. The generated optimal speed profiles with consideration of different emissions will have impact on the resulted taxiing planning using the AR and also affect decisions regarding airport regulations.
    • Preference-based evolutionary algorithm for airport runway scheduling and ground movement optimisation

      Weiszer, Michal; Chen, Jun; Stewart, Paul; University of Derby (IEEE, 2015-09-15)
      As airports all over the world are becoming more congested together with stricter environmental regulations put in place, research on optimisation of airport surface operations started to consider both time and fuel related objectives. However, as both time and fuel can have a monetary cost associated with them, this information can be utilised as preference during the optimisation to guide the search process to a region with the most cost efficient solutions. In this paper, we solve the integrated optimisation problem combining runway scheduling and ground movement problem by using a multi-objective evolutionary framework. The proposed evolutionary algorithm is based on modified crowding distance and outranking relation which considers cost of delay and price of fuel. Moreover, the preferences are expressed in a such way, that they define a certain range in prices reflecting uncertainty. The preliminary results of computational experiments with data from a major airport show the efficiency of the proposed approach.
    • Preference-based evolutionary algorithm for airport surface operations.

      Weiszer, Michal; Chen, Jun; Stewart, Paul; Zhang, Xuejun; Queen Mary University of London; University of Derby; Beihang University; National Key Laboratory of CNS/ATM (Elsevier, 2018-04-21)
      In addition to time efficiency, minimisation of fuel consumption and related emissions has started to be considered by research on optimisation of airport surface operations as more airports face severe congestion and tightening environmental regulations. Objectives are related to economic cost which can be used as preferences to search for a region of cost efficient and Pareto optimal solutions. A multi-objective evolutionary optimisation framework with preferences is proposed in this paper to solve a complex optimisation problem integrating runway scheduling and airport ground movement problem. The evolutionary search algorithm uses modified crowding distance in the replacement procedure to take into account cost of delay and fuel price. Furthermore, uncertainty inherent in prices is reflected by expressing preferences as an interval. Preference information is used to control the extent of region of interest, which has a beneficial effect on algorithm performance. As a result, the search algorithm can achieve faster convergence and potentially better solutions. A filtering procedure is further proposed to select an evenly distributed subset of Pareto optimal solutions in order to reduce its size and help the decision maker. The computational results with data from major international hub airports show the efficiency of the proposed approach.
    • A real-time Active Routing approach via a database for airport surface movement

      Weiszer, Michal; Chen, Jun; Stewart, Paul; Institute for Innovation in Sustainable Engineering, Derby, United Kingdom (2015-07-29)
      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.
    • Toward a more realistic, cost-effective, and greener ground movement through active routing: A multiobjective shortest path approach

      Chen, Jun; Atkin, Jason A. D.; Locatelli, Giorgio; Weiszer, Michal; Ravizza, Stefan; Stewart, Paul; Burke, Edmund K.; University of Derby (IEEE, 2016-10-31)
      This paper draws upon earlier work, which devel- oped a multiobjective speed profile generation framework for unimpeded taxiing aircraft. Here, we deal with how to seamlessly integrate such efficient speed profiles into a holistic decision- making framework. The availability of a set of nondominated unimpeded speed profiles for each taxiway segment, with respect to conflicting objectives, has the potential to significantly impact upon 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 implica- tions are exploited over a day of operation, to take into account cost differences between busier and quieter times of the airport. Therefore, a more cost-effective and tailored decision can be made, respecting the environmental impact. Preliminary results based on the proposed approach show a 9%–50% reduction in time and fuel respectively for two international airports: Zurich and Manchester. 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, ground operations may simultaneously improve both time and fuel efficiency. The work described in this paper aims to open up the possibility to move away from the conventional distance-based routing and scheduling to a more comprehensive framework, capturing the multifaceted needs of all stakeholders involved in airport ground operations.
    • Toward a More Realistic, Cost-Effective, and Greener Ground Movement Through Active Routing—Part I: Optimal Speed Profile Generation

      Chen, Jun; Weiszer, Michal; Stewart, Paul; Shabani, Masihalah; University of Derby - IISE (2015-11-05)
      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 time efficient 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.
    • The trade-off between taxi time and fuel consumption in airport ground movement

      Ravizza, Stefan; Chen, Jun; Atkin, Jason A. D.; Burke, Edmund K.; Stewart, Paul; University of Lincoln (2013-02-13)
      Environmental issues play an important role across many sectors. This is particularly the case in the air transportation industry. 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 a key area of study is whether fuel burn and environmental impact improvements 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.