Large Car-following Dataset Based on Lyft level-5: Following Autonomous Vehicles vs. Human-driven Vehicles

DOI:10.4121/1255994c-c64f-40f5-8121-9e952e308c9a.v4
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: 10.4121/1255994c-c64f-40f5-8121-9e952e308c9a
Datacite citation style:
Li, Guopeng; Jiao, Yiru; Victor Knoop; Simeon Calvert; van Lint, Hans (2024): Large Car-following Dataset Based on Lyft level-5: Following Autonomous Vehicles vs. Human-driven Vehicles. Version 4. 4TU.ResearchData. dataset. https://doi.org/10.4121/1255994c-c64f-40f5-8121-9e952e308c9a.v4
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite

Dataset

choose version:
version 4 - 2024-10-15 (latest)
version 3 - 2024-08-14 version 2 - 2023-08-30 version 1 - 2023-05-31
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Usage statistics

1871
views
1848
downloads

Geolocation

Palo Alto, California, US

Studying how human drivers react differently when following autonomous vehicles (AV) vs. human-driven vehicles (HV) is critical for mixed traffic flow. This dataset contains extracted and enhanced two categories of car-following data, HV-following-AV (H-A) and HV-following-HV (H-H), from the open Lyft level-5 dataset.

History

  • 2023-05-31 first online
  • 2024-10-15 published, posted

Publisher

4TU.ResearchData

Format

zipped files of 6 .zarr trajectory folders and 6 .csv regime index files in regimes.zip, 2 .npz driver id files, 1 zip file for full regimes of each timestamp, and an extra readme.md file

Funding

  • MiRRORs (grant code 16270) NWO/TTW

Organizations

TU Delft, Faculty of Civil Engineering and Geosciences, department of Transport & Planning

DATA

Files (6)