An environmentally-aware dynamic planning of electric vehicles for aircraft towing considering stochastic aircraft arrival and departure times

IF 7.6 1区 工程技术 Q1 TRANSPORTATION SCIENCE & TECHNOLOGY Transportation Research Part C-Emerging Technologies Pub Date : 2024-09-21 DOI:10.1016/j.trc.2024.104857
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Abstract

Introducing electric vehicles that tow aircraft during taxiing is an emerging technology aimed at supporting climate neutrality for aviation. Planning electric towing operations is, however, impeded by the high uncertainty in aircraft arrival and departure times. We address the question of how to plan the operation of a fleet of Electric Towing Vehicles (ETVs) to maximize environmental benefits, given the uncertainty in aircraft arrival/departure times. For this, we propose a stochastic and dynamic planning framework for ETVs, where stochastic aircraft arrival and departure times are updated during the day. With this, the assignment of the ETVs-to-aircraft to replace conventional taxiing, and ETV battery charging times are planned such that the fuel savings are maximized. At the same time, we ensure that aircraft delays induced by the use of ETVs are minimized. We illustrate our framework for a large European airport. The results show that our framework achieves 79.5% of the highest possible cost reduction (fuel and ETV-induced delay), which is obtained when full knowledge of the arrival/departure times is available in advance. Furthermore, we show that considering the uncertainty in the arrival/departure times, rather than using point estimates of these times, leads to a 17.7% additional cost reduction. Overall, our framework supports the implementation of electric aircraft towing with maximum environmental benefits while considering the dynamic, uncertain arrival and departure times of aircraft.

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考虑随机飞机到达和起飞时间的飞机牵引电动车辆环境感知动态规划
在飞机滑行过程中引入电动车辆牵引飞机是一项新兴技术,旨在支持航空业的气候中和。然而,飞机到达和起飞时间的高度不确定性阻碍了电动牵引运行的规划。我们要解决的问题是,在飞机到达/起飞时间不确定的情况下,如何规划电动拖车(ETV)车队的运营,以实现环境效益最大化。为此,我们为电动拖车提出了一个随机和动态规划框架,其中随机飞机到达和起飞时间在一天中不断更新。有了这个框架,就可以规划 ETV 对飞机的分配,以取代传统的滑行和 ETV 电池充电时间,从而最大限度地节省燃料。同时,我们还确保将因使用 ETV 而导致的飞机延误降至最低。我们以一个大型欧洲机场为例说明了我们的框架。结果表明,我们的框架实现了 79.5% 的最高可能成本降低率(燃油和 ETV 引起的延误),而这是在提前完全了解到达/出发时间的情况下实现的。此外,我们还表明,考虑到到达/出发时间的不确定性,而不是使用这些时间的点估计值,可额外降低 17.7% 的成本。总之,我们的框架支持实施电动飞机牵引,在考虑飞机动态、不确定的到达和起飞时间的同时,实现最大的环境效益。
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来源期刊
CiteScore
15.80
自引率
12.00%
发文量
332
审稿时长
64 days
期刊介绍: Transportation Research: Part C (TR_C) is dedicated to showcasing high-quality, scholarly research that delves into the development, applications, and implications of transportation systems and emerging technologies. Our focus lies not solely on individual technologies, but rather on their broader implications for the planning, design, operation, control, maintenance, and rehabilitation of transportation systems, services, and components. In essence, the intellectual core of the journal revolves around the transportation aspect rather than the technology itself. We actively encourage the integration of quantitative methods from diverse fields such as operations research, control systems, complex networks, computer science, and artificial intelligence. Join us in exploring the intersection of transportation systems and emerging technologies to drive innovation and progress in the field.
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