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LiRA-CD:一个用于道路状况建模与研究的开源数据集。

LiRA-CD: An open-source dataset for road condition modelling and research.

作者信息

Skar Asmus, Vestergaard Anders M, Brüsch Thea, Pour Shahrzad, Kindler Ekkart, Alstrøm Tommy Sonne, Schlotz Uwe, Larsen Jakob Elsborg, Pettinari Matteo

机构信息

Environmental and Resource Engineering, Technical University of Denmark, 2800 Kongens Lyngby, Denmark.

Applied Mathematics and Computer Science, Technical University of Denmark, 2800 Kongens Lyngby, Denmark.

出版信息

Data Brief. 2023 Jul 17;49:109426. doi: 10.1016/j.dib.2023.109426. eCollection 2023 Aug.

Abstract

This data article presents the details of the Live Road Assessment Custom Dataset (LiRA-CD), an open-source dataset for road condition modelling and research. The dataset captures GPS trajectories of a fleet of electric vehicles and their time-series data from 50 different sensors collected on 230 km of highway and urban roads in Copenhagen, Denmark. Additionally, road condition measurements were collected by standard survey vehicles, which serve as high-quality reference data. The in-vehicle measurements were collected onboard with an Internet-of-Things (IoT) device, then periodically transmitted before being saved in a database. Researchers can use the dataset for prediction modelling related to standard road condition parameters such as surface friction and texture, road roughness, road damages, and energy consumption. Furthermore, researchers and pavement engineers can use the dataset as a template for future studies and projects, benchmarking the performance of different algorithms and solving problems of the same type. LiRA-CD is freely available and can be accessed at https://doi.org/10.11583/DTU.c.6659909.

摘要

本数据文章介绍了实时道路评估定制数据集(LiRA-CD)的详细信息,这是一个用于道路状况建模和研究的开源数据集。该数据集记录了一组电动汽车的GPS轨迹及其从丹麦哥本哈根230公里高速公路和城市道路上收集的50种不同传感器的时间序列数据。此外,由标准测量车辆收集道路状况测量数据,作为高质量的参考数据。车载测量数据通过物联网(IoT)设备在车内收集,然后定期传输,最后保存在数据库中。研究人员可以使用该数据集进行与标准道路状况参数相关的预测建模,如路面摩擦和纹理、道路粗糙度、道路损坏以及能源消耗。此外,研究人员和路面工程师可以将该数据集用作未来研究和项目的模板,对不同算法的性能进行基准测试并解决同类问题。LiRA-CD可免费获取,访问地址为https://doi.org/10.11583/DTU.c.6659909。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/df28/10375556/5e9f895bd91a/gr1.jpg

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本文引用的文献

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2
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