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

doi: 10.4121/1255994c-c64f-40f5-8121-9e952e308c9a.v2
The doi 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 (2023): Large Car-following Dataset Based on Lyft level-5: Following Autonomous Vehicles vs. Human-driven Vehicles. Version 2. 4TU.ResearchData. dataset. https://doi.org/10.4121/1255994c-c64f-40f5-8121-9e952e308c9a.v2
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite
Dataset
choose version:
version 2 - 2023-08-30 (latest)
version 1 - 2023-05-31
Delft University of Technology logo
usage stats
1621
views
1330
downloads
geolocation
Palo Alto, California, US
licence
cc-by-nc.png logo CC BY-NC 4.0

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
  • 2023-08-30 published, posted
publisher
4TU.ResearchData
format
zipped files of 6 .zarr trajectory folders and 3 .csv index files, 2 .npz driver id files, 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 (4)