Data underlying the publication: Inferring vehicle spacing in urban traffic from trajectory data

DOI:10.4121/8cadc255-5fd8-46ab-893a-64b76ca7b7f9.v1
The DOI displayed above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
DOI: 10.4121/8cadc255-5fd8-46ab-893a-64b76ca7b7f9

Datacite citation style

Jiao, Yiru; Simeon Calvert; van Cranenburgh, Sander; van Lint, Hans (2025): Data underlying the publication: Inferring vehicle spacing in urban traffic from trajectory data. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/8cadc255-5fd8-46ab-893a-64b76ca7b7f9.v1
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite

Dataset

This dataset includes the resulting data of the research: Inferring vehicle spacing in urban traffic from trajectory data. It contains the processed outputs generated from raw vehicle trajectory data in the pNEUMA dataset. The objective of this research is to infer average two-dimensional vehicle spacing and analyse the interactions between vehicles through empirical experiments, particularly around intersections. The study employs a combination of data preprocessing, spatial transformation, intersection detection, and statistical inference (yielding interaction Fundamental Diagrams) to capture and summarise vehicle speed, spacing, and positional data. Data are collected from real-world traffic records, then transformed and sampled into various output formats (such as CSV and HDF5) that encapsulate both the inferred interaction metrics and the underlying trajectory information. The scripts that produced these data are open-sourced at https://github.com/Yiru-Jiao/DriverSpaceInference


History

  • 2025-06-06 first online, published, posted

Publisher

4TU.ResearchData

Format

HDF5, CSV

Funding

  • TU Delft AI Labs programme [more info...] Delft University of Technology

Organizations

TU Delft, Faculty of Civil Engineering and Geosciences, Department of Transport and Planning, Traffic Systems Engineering

DATA

Files (2)