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

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

*Corresponding author for this work

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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.
Original languageEnglish
Article number109426
JournalData in Brief
Volume49
Number of pages15
ISSN2352-3409
DOIs
Publication statusPublished - 2023

Keywords

  • Live road assessment
  • Pavement analysis
  • Road damage detection
  • Road friction
  • Road energy consumption
  • Internet-of-vehicles
  • Machine-learning
  • Vehicle dynamics

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