IISE

@DerbyUniIISE papers in: 2015 IEEE 18th International Conference on Intelligent Transportation Systems

2015 IEEE Intelligent Transportation Systems Conference (ITSC 2015), September 15-18, 2015, in Las Palmas de Gran Canaria, Spain.

September 15-18, 2015, in Las Palmas de Gran Canaria, Spain.

 

Title

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

Authors
Jun Chen (University of Lincoln, UK)
Michal Weiszer (University of Lincoln, UK)
Paul Stewart (Institute for Innovation in Sustainable Engineering)
Abstract
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.

Title

Preference-based evolutionary algorithm for airport runway scheduling and ground movement optimisation
Authors
Michal Weiszer (University of Lincoln, UK)
Jun Chen (University of Lincoln, UK)
Paul Stewart (Institute for Innovation in Sustainable Engineering)
Abstract
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.

Paul Stewart
Director of Innovation Mel Morris Endowed Chair in Intelligent Systems University of Derby UK email: p.stewart1@derby.ac.uk
http://www.pesri.net

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