Driving heterogeneity identification using machine learning: A review and framework for analysis
Driving heterogeneity significantly influences traffic performance, contributing to traffic disturbances, increased crash risks, and inefficient fuel use and emissions. With the growing availability of driving behaviour data, Machine Learning (ML) techniques have become widely used for analysing dri...
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Main Authors: | Xue Yao, Simeon C. Calvert, Serge P. Hoogendoorn |
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Format: | Article |
Language: | English |
Published: |
Elsevier
2025-07-01
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Series: | Transportation Research Interdisciplinary Perspectives |
Subjects: | |
Online Access: | http://www.sciencedirect.com/science/article/pii/S2590198225001903 |
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