22 & 23 May 2025: Mini-conference on Open and FAIR in Natural and Engineering Sciences. Register to attend.

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

Delft University of Technology logo

Usage statistics

2453
views
2463
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)