Data and Results for the Benchmark of Gap Acceptance Models

DOI:10.4121/21334548.v3
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: 10.4121/21334548

Datacite citation style

Julian Schumann (2022): Data and Results for the Benchmark of Gap Acceptance Models. Version 3. 4TU.ResearchData. dataset. https://doi.org/10.4121/21334548.v3
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite

Dataset

Version 3 - 2022-12-05 (latest)
Version 2 - 2022-10-26 Version 1 - 2022-10-17

This dataset allows the addition of the missing parts of the framework for benchmarking gap accetpance models (https://github.com/julianschumann/Framework-for-benchmarking-gap-acceptance). This are:

- The raw data of the CoR dataset

- The results at every stage of the framework for the implemented modules. The results shown in the corresponding paper are based thereon.


The information on how to include this data in the corresponding code base can be found on the github project README

History

  • 2022-10-17 first online
  • 2022-12-05 published, posted

Publisher

4TU.ResearchData

Format

Two .zip files, including *.csv and *.npy files

Organizations

TU Delft, Faculty of Mechanical, Maritime and Materials Engineering (3mE), Department of Cognitive Robotics

DATA

Files (2)