Control and optimization algorithms for air transportation systems

被引:16
|
作者
Balakrishnan, Hamsa [1 ]
机构
[1] MIT, Dept Aeronaut & Astronaut, Cambridge, MA 02139 USA
基金
美国国家科学基金会;
关键词
Air transportation; Congestion control; Large-scale optimization; Data-driven modeling; Human decision processes; TRAFFIC FLOW-CONTROL; AIRPORT; CONGESTION; IMPACT;
D O I
10.1016/j.arcontrol.2016.04.019
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Modern air transportation systems are complex cyber-physical networks that are critical to global travel and commerce. As the demand for air transport has grown, so have congestion, flight delays, and the resultant environmental impacts. With further growth in demand expected, we need new control techniques, and perhaps even redesign of some parts of the system, in order to prevent cascading delays and excessive pollution. In this survey, we consider examples of how we can develop control and optimization algorithms for air transportation systems that are grounded in real-world data, implement them, and test them in both simulations and in field trials. These algorithms help us address several challenges, including resource allocation with multiple stakeholders, robustness in the presence of operational uncertainties, and developing decision-support tools that account for human operators and their behavior. (C) 2016 International Federation of Automatic Control. Published by Elsevier Ltd. All rights reserved.
引用
收藏
页码:39 / 46
页数:8
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