Knowledge Distillation for Travel Time Estimation
文献类型：期刊论文
| 作者 | Zhang, Haichao2; Zhao, Fang2; Wang, Chenxing2; Luo, Haiyong1; Xiong, Haoyu2; Fang, Yuchen2 |
| 刊名 | IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
 |
| 出版日期 | 2024-03-22 |
| 页码 | 12 |
| 关键词 | Computational modeling Trajectory Roads Global Positioning System Predictive models Estimation Context modeling Spatial-travel time estimation temporal data mining knowledge distillation deep learning |
| ISSN号 | 1524-9050 |
| DOI | 10.1109/TITS.2024.3374325 |
| 英文摘要 | Travel time estimation(TTE) is a critical component of intelligent transportation systems. To achieve efficient and accurate trajectory-based travel time estimation, it is essential to design a streamlined model that reduces computation and memory costs. However, this is challenging as traditional deep neural networks are limited in their calculation capabilities and can be cumbersome due to the high number of model parameters. To overcome these challenges, we propose a novel approach to travel time estimation, utilizing a well-designed deep neural network model called Knowledge Distillation for Travel Time Estimation (KDTTE). By implementing knowledge distillation techniques, the model's computational and memory requirements are reduced, while simultaneously improving its accuracy. The student model leverages the knowledge of the Teacher model to learn features it would not have been able to on its own, thereby enhancing the overall accuracy of the model. Our approach, referred to as KDTTE, was tested on two real-world datasets and showed improved accuracy compared to nine state-of-the-art baselines, demonstrating a 34.0% and 86.8% increase in accuracy on the Chengdu and Porto datasets, respectively. |
| 资助项目 | National Natural Science Foundation of China |
| WOS研究方向 | Engineering ; Transportation |
| 语种 | 英语 |
| WOS记录号 | WOS:001193997400001 |
| 出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
| 源URL | [http://119.78.100.204/handle/2XEOYT63/38770]  |
| 专题 | 中国科学院计算技术研究所期刊论文_英文 |
| 通讯作者 | Zhao, Fang; Luo, Haiyong |
| 作者单位 | 1.Chinese Acad Sci, Beijing Key Lab Mobile Comp & Pervas Device, Inst Comp Technol, Beijing 100080, Peoples R China 2.Beijing Univ Posts & Telecommun, Sch Comp Sci, Natl Pilot Software Engn Sch, Beijing 100876, Peoples R China |
| 推荐引用方式 GB/T 7714 | Zhang, Haichao,Zhao, Fang,Wang, Chenxing,et al. Knowledge Distillation for Travel Time Estimation[J]. IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS,2024:12. |
| APA | Zhang, Haichao,Zhao, Fang,Wang, Chenxing,Luo, Haiyong,Xiong, Haoyu,&Fang, Yuchen.(2024).Knowledge Distillation for Travel Time Estimation.IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS,12. |
| MLA | Zhang, Haichao,et al."Knowledge Distillation for Travel Time Estimation".IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS (2024):12. |
入库方式： OAI收割
来源：计算技术研究所
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