{"data":{"id":"10.4121/0dbf6809-9c88-4967-8556-c798621ebfa4","type":"dois","attributes":{"doi":"10.4121/0dbf6809-9c88-4967-8556-c798621ebfa4","prefix":"10.4121","suffix":"0dbf6809-9c88-4967-8556-c798621ebfa4","identifiers":[],"alternateIdentifiers":[],"creators":[{"name":"Yao, Xue","nameType":"Personal","givenName":"Xue","familyName":"Yao","nameIdentifiers":[{"nameIdentifier":"0000-0002-6575-8758","nameIdentifierScheme":"https://orcid.org/"}],"affiliation":[]}],"titles":[{"title":"Data pertaining to Chapter 4 \"Identification of Driving Heterogeneity using Action-chains\""}],"publisher":"4TU.ResearchData","container":{},"publicationYear":2025,"subjects":[{"subject":"Civil Engineering","subjectScheme":"Australian and New Zealand Standard Research Classification (ANZSRC), 2008","classificationCode":"0905"},{"subject":"FOS: Civil engineering","schemeUri":"http://www.oecd.org/science/inno/38235147.pdf","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"Environmentally Sustainable Transport","subjectScheme":"Australian and New Zealand Standard Research Classification (ANZSRC), 2008","classificationCode":"8898"},{"subject":"Interdisciplinary Engineering","subjectScheme":"Australian and New Zealand Standard Research Classification (ANZSRC), 2008","classificationCode":"0915"},{"subject":"FOS: Other engineering and technologies","schemeUri":"http://www.oecd.org/science/inno/38235147.pdf","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"Ground Transport","subjectScheme":"Australian and New Zealand Standard Research Classification (ANZSRC), 2008","classificationCode":"8801"},{"subject":"Engineering","subjectScheme":"Australian and New Zealand Standard Research Classification (ANZSRC), 2008","classificationCode":"09"},{"subject":"Transport","subjectScheme":"Australian and New Zealand Standard Research Classification (ANZSRC), 2008","classificationCode":"88"},{"subject":"Driving behavior"},{"subject":"Driving behaviour"},{"subject":"Identification"},{"subject":"Action phase"},{"subject":"Traffic flow analysis"}],"contributors":[{"name":"TU Delft, Faculty of Civil Engineering and Geosciences, Department of Transport and Planning, Traffic Systems Engineering","nameType":"Organizational","affiliation":[],"contributorType":"Other","nameIdentifiers":[]}],"dates":[{"date":"2025-07-07","dateType":"Issued"}],"language":"en","types":{"ris":"DATA","bibtex":"misc","citeproc":"dataset","schemaOrg":"Dataset","resourceType":"Dataset","resourceTypeGeneral":"Dataset"},"relatedIdentifiers":[{"relationType":"IsSupplementTo","relatedIdentifier":"10.1109/itsc57777.2023.10421850","relatedIdentifierType":"DOI"},{"relationType":"IsVersionOf","relatedIdentifier":"10.4121/0dbf6809-9c88-4967-8556-c798621ebfa4.v1","relatedIdentifierType":"DOI"}],"relatedItems":[],"sizes":[],"formats":["*.xlsx, *.pdf, *.txt, *.csv i.e., script/.py, spreadsheet/.xlsx, image/.jpeg, image/.pdf"],"version":"1","rightsList":[{"rights":"Creative Commons Attribution Non Commercial 4.0 International","rightsUri":"https://creativecommons.org/licenses/by-nc/4.0/legalcode","schemeUri":"https://spdx.org/licenses/","rightsIdentifier":"cc-by-nc-4.0","rightsIdentifierScheme":"SPDX"}],"descriptions":[{"description":"This dataset accompanies the paper \u003cem\u003e“Identification of Driving Heterogeneity using Action-chains”\u003c/em\u003e (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 (\u003ccode\u003e.ipynb\u003c/code\u003e) and supporting files in \u003ccode\u003e.xlsx\u003c/code\u003e, \u003ccode\u003e.csv\u003c/code\u003e, \u003ccode\u003e.mat\u003c/code\u003e, \u003ccode\u003e.m\u003c/code\u003e, \u003ccode\u003e.txt\u003c/code\u003e, and \u003ccode\u003e.pdf\u003c/code\u003e formats. A \u003ccode\u003ech4_Readme.txt\u003c/code\u003e file is included to guide users on the structure, usage, and purpose of the 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