{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T01:13:14Z","timestamp":1760058794748,"version":"build-2065373602"},"reference-count":14,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2025,5,1]],"date-time":"2025-05-01T00:00:00Z","timestamp":1746057600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Portuguese Foundation for Science and Technology (FCT)","award":["UIDB\/04524\/2020"],"award-info":[{"award-number":["UIDB\/04524\/2020"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Future Transportation"],"abstract":"<jats:p>This work explores the classification of driving behaviors using a hybrid deep learning model that combines Convolutional Neural Networks (CNNs) with Long Short-Term Memory (LSTM) networks (ConvLSTM). Sensor data are collected from a smartphone application and undergo a preprocessing pipeline, including data normalization, labeling, and feature extraction, to enhance the model\u2019s performance. By capturing temporal and spatial dependencies within driving patterns, the proposed ConvLSTM model effectively differentiates between normal and aggressive driving behaviors. The model is trained and evaluated against traditional stacked LSTM and Bidirectional LSTM (BiLSTM) architectures, demonstrating superior accuracy and robustness. Experimental results confirm that the preprocessing techniques improve classification performance, ensuring high reliability in driving behavior recognition. The novelty of this work lies in a simple data preprocessing methodology combined with the specific application scenario. By enhancing data quality before feeding it into the AI model, we improve classification accuracy and robustness. The proposed framework not only optimizes model performance but also demonstrates practical feasibility, making it a strong candidate for real-world deployment.<\/jats:p>","DOI":"10.3390\/futuretransp5020052","type":"journal-article","created":{"date-parts":[[2025,5,2]],"date-time":"2025-05-02T07:44:23Z","timestamp":1746171863000},"page":"52","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Driving Behavior Classification Using a ConvLSTM"],"prefix":"10.3390","volume":"5","author":[{"given":"Alberto","family":"Pingo","sequence":"first","affiliation":[{"name":"School of Technology and Management, Polytechnic University of Leiria, 2411-901 Leiria, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-4440-8120","authenticated-orcid":false,"given":"Jo\u00e3o","family":"Castro","sequence":"additional","affiliation":[{"name":"School of Technology and Management, Polytechnic University of Leiria, 2411-901 Leiria, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6711-1384","authenticated-orcid":false,"given":"Paulo","family":"Loureiro","sequence":"additional","affiliation":[{"name":"Computer Science and Communication Research Centre, School of Technology and Management, Polytechnic University of Leiria, 2411-901 Leiria, Portugal"}]},{"given":"S\u00edlvio","family":"Mendes","sequence":"additional","affiliation":[{"name":"Computer Science and Communication Research Centre, School of Technology and Management, Polytechnic University of Leiria, 2411-901 Leiria, Portugal"}]},{"given":"Anabela","family":"Bernardino","sequence":"additional","affiliation":[{"name":"Computer Science and Communication Research Centre, School of Technology and Management, Polytechnic University of Leiria, 2411-901 Leiria, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4213-9302","authenticated-orcid":false,"given":"Rolando","family":"Miragaia","sequence":"additional","affiliation":[{"name":"Computer Science and Communication Research Centre, School of Technology and Management, Polytechnic University of Leiria, 2411-901 Leiria, Portugal"}]},{"given":"Iryna","family":"Husyeva","sequence":"additional","affiliation":[{"name":"Computer Science and Communication Research Centre, National Technical University of Ukraine Igor Sikorsky Kyiv Polytechnic Institute, 03056 Kyiv, Ukraine"}]}],"member":"1968","published-online":{"date-parts":[[2025,5,1]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"14128","DOI":"10.1109\/ACCESS.2023.3243865","article-title":"Driver Behavior Classification: A Systematic Literature Review","volume":"11","author":"Bouhsissin","year":"2023","journal-title":"IEEE Access"},{"key":"ref_2","first-page":"182","article-title":"Utilizing LSTM Networks for the Prediction of Driver Behavior","volume":"100","author":"Darsono","year":"2024","journal-title":"Prz. 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