Print Email Facebook Twitter A Comparative Study on Unsupervised Machine Learning Models for Detecting Sudden Lane Changes Title A Comparative Study on Unsupervised Machine Learning Models for Detecting Sudden Lane Changes Author Zhang, Lanxin (TU Delft Civil Engineering & Geosciences) Contributor Farah, H. (mentor) Dong, Y. (graduation committee) Degree granting institution Delft University of Technology Programme Civil Engineering | Transport and Planning Date 2023-06-30 Abstract Lane-changing behaviour detection is a critical aspect of driving safety and traffic management. This study focuses on detecting sudden lane changes as a subset of abnormal driving behaviours. By analyzing the characteristics of abrupt lane changes, the aim is to develop effective data-driven unsupervised machine learning (ML) methods for their detection and classification. Three unsupervised ML models, namely Isolation Forest, Local Outlier Factor, and Robust Covariance are evaluated and compared using a dataset of lane-change events. The results show that the Isolation Forest and Local Outlier Factor models outperform the Robust Covariance model, with the Local Outlier Factor model excelling in precision and overall accuracy, achieving the best overall detection rate. Both Robust Covariance and Isolation Forest deliver satisfactory results. Conversely, the Robust Covariance model exhibits poor performance. The findings verify the capability of data-driven ML methods for enhancing road safety and driving experiences through effective detection of sudden lane changes using vehicle motion information data. Future work involves further improving the accuracy and reliability of the ML models, validating their generalizability on larger datasets, incorporating contextual information, and exploring their real-time implementation in driving assistance systems. To reference this document use: http://resolver.tudelft.nl/uuid:06b7bf6a-09ae-4703-8663-07ffd60397a8 Part of collection Student theses Document type student report Rights © 2023 Lanxin Zhang Files PDF A_Comparative_Study_on_Un ... hanges.pdf 783.69 KB Close viewer /islandora/object/uuid:06b7bf6a-09ae-4703-8663-07ffd60397a8/datastream/OBJ/view