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Large-Scale Freeway Traffic Flow Estimation Using Crowdsourced Data: A Case Study in Arizona
| 题名： | Large-Scale Freeway Traffic Flow Estimation Using Crowdsourced Data: A Case Study in Arizona |
| 正文语种： | eng |
| 作者： | Adrian Cottam;Xiaofeng Li;Xiaobo Ma;Yao-Jan Wu |
| 作者单位： | Auburn Univ. Transportation Research Institute Samuel Ginn College of Engineering Auburn Univ. 311 W Magnolia Ave. Auburn AL 36849;School of Travel Industry Management Shidler College of Business Univ. of Hawaii at Manoa 2560 Campus Rd. Honolulu |
| 关键词： | Crowdsourced data; Machine learning; Ensembles; Traffic flow estimation |
| 摘要： | Vehicular flow rate is an essential measure commonly collected by inductive-loop detectors for transportation agencies to evaluate freeways and highways. Loop detectors are typically located in urban areas due to installation and maintenance costs, and do |
| 出版年： | 2024 |
| 期刊名称： | Journal of Transportation Engineering, Part A. Systems |
| 卷： | 150 |
| 期： | 7 |
| 页码： | 04024030.1-04024030.15 |
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