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

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.

Keywords: Internet-of-vehicles; Live road assessment; Machine-learning; Pavement analysis; Road damage detection; Road energy consumption; Road friction; Vehicle dynamics.