Data pertaining to Chapter 4 "Identification of Driving Heterogeneity using Action-chains"
Wat erin zit
This dataset accompanies the paper “Identification of Driving Heterogeneity using Action-chains” (Chapter 4 of the PhD dissertation). The research introduces a comprehensive framework for identifying driving heterogeneity from an action perspective. Driving trajectories are identified into Action phases with physical meanings based on rule-based segmentation techniques. The Action chain concept is then introduced by implementing the Action phase transition probability. Evaluating using a naturalistic dataset indicates that this approach effectively identifies driving heterogeneity while providing clear interpretations. The research includes data preprocessing to clean data, rule-based segmentation to extract Action phases, driving behaviour map establishment, Action chain modelling, and heterogeneous traffic flow evaluation. The dataset is provided as a zipped folder containing four Jupyter notebooks ( .ipynb ) and supporting files in .xlsx , .csv , .mat , .m , .txt , and .pdf formats. A ch4_Readme.txt file is included to guide users on the structure, usage, and purpose of the data.
Bestanden en diensten
- DataCite REST API (JSON)api.datacite.orgOpenen