Prediction of Flight Taxi-out Time in A Busy Airport Based on LWSVR

doi:10.16182/j.issn1004731x.joss.18-0598

Abstract

Abstract: Aiming at improving the accuracy of predicting the flight taxi-out time in a busy airport, based on the local regression and weighted support vector regression, a prediction model of the locally weighted support vector regression is proposed. The model uses the K nearest neighbor method to reduce the capacity of the training sample set and build a predictive model for each predicted sample. The bandwidth parameter of the Gaussian weighting function is optimized with the Mahalanobis distance between the forecast sample and training samples, and the weighting coefficients are obtained. Combining the airport departure flight data in simulation analysis, the experimental results show that the accuracy of LWSVR within the error range is 83.33%, and the model is more stable.

Key words: taxi-out time, local regression, weighted support vector regression, KNN(K-Nearest Neighbor), Gaussian weighting function

CLC Number:

U8
TP391.9

Xing Zhiwei, Jiang Songyue, Luo Qian, Luo Xiao. Prediction of Flight Taxi-out Time in A Busy Airport Based on LWSVR[J]. Journal of System Simulation, 2020, 32(5): 927-935.

References 16

[1]	Jordan R, Ishutkina M A, Reynolds T G.A statistical learning approach to the modeling of aircraft taxi time[C]. Digital Avionics Systems Conference. Salt Lake City: IEEE, 2010.
[2]	Ravizza S, Atkin J A D, Maathuis M H, et al. A combined statistical approach and ground movement model for improving taxi time estimations at airports[J]. Journal of the Operational Research Society (S0160-5682), 2013, 64(9): 1347-1360.
[3]	Balakrishn A P, Ganesan R, Sherry L.Accuracy of reinforcement learning algorithms for predicting aircraft taxi-out times: A case-study of Tampa Bay departures[J]. Transportation Research Part C Emerging Technologies (S0968-090X), 2010, 18(6): 950-962.
[4]	Idris H, Clarke J P, Bhuva R, et al.Queuing Model for Taxi-Out Time Estimation[J]. Air Traffic Control Quarterly (S1064-3818), 2001, 10(1): 1-22.
[5]	Lee H, Malik W, Jung Y C.Taxi-out time prediction for departures at charlotte airport using machine learning techniques[C]. Aiaa Aviation Technology, Integration, and Operations Conference. Washington, D.C: AIAA, 2016: 3910.
[6]	刘丽华. 市场机制下飞机推出时隙分配模型与算法研究[D]. 哈尔滨: 哈尔滨工业大学, 2017.Liu Lihua.Research on model and algorithm for aircraft pushback slot allocation under market mechanism[D]. Harbin: Harbin Institute of Technology, 2017.
[7]	Zeng J S, Gao C H, Luo S H.Identification of LPV system using locally weighted technique[J]. Applied Mathematics: A Journal of Chinese Universities (S1005-1031), 2010, 25(4): 411-419.
[8]	Wang H, Cao C, Leung H.An improved locally weighted regression for a converter re-vanadium prediction modeling[C]. World Congress on Intelligent Control and Automation. Dalian: IEEE, 2006: 1515-1519.
[9]	石柯, 陈洪生, 张仁同. 一种基于支持向量回归的802. 11无线室内定位方法[J]. 软件学报, 2014, 25(11): 2636-2651.Shi Ke, Chen Hongsheng, Zhang Rentong.Indoorlocation method based on support vector regression in 802. 11 wireless environments[J]. Journal of Software, 2014, 25(11): 2636-2651.
[10]	王翔, 陈小鸿, 杨祥妹. 基于K最近邻算法的高速公路短时行程时间预测[J]. 中国公路学报, 2015, 28(1): 102-111.Wang Xiang, Chen Xiaohong, Yang Xiangmei.Short term prediction of expressway travel time based on KNN algorithm[J]. China Journal of Highway and Transport, 2015, 28(1): 102-111.
[11]	Wang Z Y, Peng Z R.A PSO-SVM model for short-term travel time prediction based on bluetooth technology[J]. Journal of Harbin Institute of Technology (S1005-9113), 2015, 22(3): 7-14.
[12]	Ravizza S, Chen J, Atkin J A D, et al. Aircraft taxi time prediction: comparisons and insights[J]. Applied Soft Computing (S1568-4946), 2014, 14(1): 397-406.
[13]	张洪海, 杨磊, 别翌荟, 等. 终端区进场交通流广义跟驰行为与复杂相变分析[J]. 航空学报, 2015, 36(3): 949-961.Zhang Honghai, Yang Lei, Bie Yihui, et al.Analysis on generalized following behavior and complex phasetransition law of approaching traffic flow in terminal airspace[J]. Acta Aeronautica Et Astronautica Sinica, 2015, 36(3): 949-961.
[14]	戴文雯, 别翌荟, 张洪海, 等. 基于NetLogo的终端区交通流仿真[J]. 航空计算技术, 2014, 44(1): 30-33.Dai Wenwen, Bie Yihui, Zhang Honghai, et al.Simulation of Air Traffic Flow Based on Net Logo[J]. Aeronautical Computing Technique, 2014, 44(1): 30-33.
[15]	谷润平, 崔朋, 唐建勋, 等. 基于D算法的场面滑行动态规划研究[J]. 科学技术与工程, 2015, 15(1): 315-319.Gu Runping, Cui Peng, Tang Jianxun, et al.Research on Dynamic Planning of Taxi Path Based on D Algorithm[J]. Science Technology and Engineering, 2015, 15(1): 315-319.
[16]	Chatterji G, Zheng Y.Wheels-off time prediction using surface traffic metrics[C]. Aiaa Aviation Technology, Integration, & Operations. Indianapolis: AIAA, 2012: 5699.