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O'Hare Airport Short-Term Ground Transportation Modal Demand Forecast Using Gaussian Processes
| 题名： | O'Hare Airport Short-Term Ground Transportation Modal Demand Forecast Using Gaussian Processes |
| 正文语种： | eng |
| 作者： | Natalia Zuniga-Garcia;Arindam Fadikar;Damola M. Akinlana;Joshua Auld |
| 作者单位： | Energy Systems Argonne National Laboratory 9700 S. Cass Ave. Lemont IL 60439;Mathematics and Computer Science Argonne National Laboratory 9700 S. Cass Ave. Lemont IL 60439;Dept. of Mathematics and Statistics Univ. of South Florida College of Art |
| 关键词： | Transportation network companies (TNC); Urban rail transit; Airport demand; Airport management; Demand forecast; Heteroscedastic Gaussian process (GP) regression |
| 摘要： | The principal objective of this study is to analyze the spatial and temporal variation of ground transportation airport demand and provide demand forecast to inform planning capability and explore alternatives for investments to accommodate airport growth |
| 出版年： | 2024 |
| 期刊名称： | Journal of Transportation Engineering, Part A: Systems |
| 卷： | 150 |
| 期： | 3 |
| 页码： | 04023143.1-04023143.18 |
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