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A stochastic jump-process driving dynamic model with application to traffic safety
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DOI：10.1016/j.trb.2026.103518.png)
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Abstract
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• Proposed a stochastic jump-process driving dynamic model. • Developed a non-parametric estimation approach for the jump based stochastic driving model and derived a novel Jump Size metric. • Demonstrated the superior performance of the model to though application to the SHRP2 Naturalistic Driving Study data. • Derived the theoretical properties of the jump-based stochastic model and confirmed through Monte Carlo simulations.
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