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Code accompanying the paper "Validating human driver models for interaction-aware automated vehicle controllers: A human approach”

Code accompanying the paper "Validating human driver models for interaction-aware automated vehicle controllers: A human approach”

3
contributors

Description

This python package contains scripts needed to train IRL Driver models on HighD datasets. This code is accompanying the paper "Validating human driver models for interaction-aware automated vehicle controllers: A human factors approach - Siebinga, Zgonnikov & Abbink 2021" and should be used in combination with TraViA, a program for traffic data visualization and annotation. A preprint of this paper can be found on arxiv: https://arxiv.org/abs/2109.13077

Logo of Code accompanying the paper "Validating human driver models for interaction-aware automated vehicle controllers: A human approach”
Keywords
automated driving
driver model validation
interaction-aware controllers
inverse-reinforcement-learning driver-model
License
  • GPL-3.0-only
</>Source code
Not specified
Packages

Contributors

AZ
Arkady Zgonnikov

Member of community

4TU