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DOI：10.1109/MITS.2025.3606735.png)
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Abstract
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Human driving behavior is inherently heterogeneous, shaped by individual differences in perception, decision making, risk tolerance, and control strategies. These behavioral variations significantly influence traffic dynamics, affecting traffic safety, flow stability, energy consumption, and emissions. With the emergence of automated vehicles (AVs), understanding and modeling this behavioral variability has become increasingly important, particularly for ensuring seamless human–AV interaction in mixed-traffic environments.
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