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DOI: 10.4121/f0d9d36b-6170-4a0d-836f-6e3bd8560ae9

Yao, Xue (2025): Data pertaining to Chapter 5 "A Novel Framework for Understanding and Identifying Driving Heterogeneity through Action Patterns". Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/f0d9d36b-6170-4a0d-836f-6e3bd8560ae9.v1

Categories

• Civil Engineering
• Environmentally Sustainable Transport
• Interdisciplinary Engineering
• Ground Transport
• Engineering
• Transport

Keywords

Attention-based LSTMs Driving behaviour analysis Driving heterogeneity Driving pattern classification

Licence

CC BY-NC 4.0

Interoperability

• RO-Crate Metadata

Collection

• PhD dissertation: Driving Heterogeneity in Traffic Flow Theory: An Action-based Framework for Identification, Modelling, and Simulation

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by Xue Yao

This dataset supports the paper “A Novel Framework for Understanding and Identifying Driving Heterogeneity through Action Patterns” (Chapter 5 of the PhD dissertation). The study focuses on data analysis and behavioural modelling, introducing a new framework for identifying driving heterogeneity based on underlying action patterns in driver behaviour. The framework includes three processes: Action phase extraction, Action pattern calibration, and Action pattern classification. Evaluation of the framework on a large-scale naturalistic driving dataset reveals six distinct Action patterns. The implementation of the attention mechanism to LSTM models significantly enhanced both the accuracy and time efficiency of Action pattern identification. The data was generated and processed using rule-based segmentation, unsupervised learning, feature extraction, and supervised learning techniques in Python. It is provided as a zipped folder containing two subfolders, with files in .xlsx, .csv, .mat, .m, .txt, and .pdf formats. A ch5_Readme.txt file is included to explain the structure of the data and provide instructions for use.

History

• 2025-07-07 first online, published, posted

Publisher

4TU.ResearchData

Format

*.xlsx, *.pdf, *.txt, *.csv i.e., script/.py spreadsheet/.xlsx, image/.jpeg, image/.pdf

Associated peer-reviewed publication

A Novel Framework for Understanding and Identifying Driving Heterogeneity through Action Patterns

Organizations

TU Delft, Faculty of Civil Engineering and Geosciences, Department of Transport and Planning, Traffic Systems Engineering