Car-following informed neural networks for real-time vehicle trajectory imputation and prediction

IF 3.6 2区工程技术 Q2 TRANSPORTATION

Transportmetrica A-Transport Science Pub Date : 2024-07-09 DOI:10.1080/23249935.2024.2374523

Yu-Hang Yin, Xing Lü, Shu-Kai Li, Li-Xing Yang, Ziyou Gao

引用次数: 0

Abstract

Vehicle trajectory information is a crucial part of improving the efficiency and the safety of the ITS. Data missing or irregular sampling in the real-world road traffic makes it hard to obtain acc...

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用于实时车辆轨迹估算和预测的汽车跟踪信息神经网络

车辆轨迹信息是提高智能交通系统效率和安全性的关键部分。现实世界道路交通中的数据缺失或不规则采样导致很难获得准确的车辆轨迹信息。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Transportmetrica A-Transport Science TRANSPORTATION SCIENCE & TECHNOLOGY-

CiteScore

8.10

自引率

12.10%

发文量

期刊介绍： Transportmetrica A provides a forum for original discourse in transport science. The international journal''s focus is on the scientific approach to transport research methodology and empirical analysis of moving people and goods. Papers related to all aspects of transportation are welcome. A rigorous peer review that involves editor screening and anonymous refereeing for submitted articles facilitates quality output.