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• W3174485517 abstract "This paper proposes a statistical framework to assess the risk of passing a non-signalized intersection for vehicles. First, an intensity model of the near-accident event is established by regarding the near-accident event as a non-homogeneous Poisson process. The non-homogeneous Poisson process is defined on the sigma-algebra of the 2-dimension plane of vehicle velocity and distance to the intersection instead of in the time axis. On the other hand, the pedestrian intention is defined as a binary variable with 1 as passing through the crosswalk and 0 as stopping. Logistic function is applied to model the probability of pedestrian intention. The proposed statistical models are evaluated by the residual analysis-based model checking method. Besides, based on the two models, the pedestrian-aware risk model is established to give a predictive risk metric quantitatively when pedestrian appears." @default.
• W3174485517 created "2021-07-05" @default.
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• W3174485517 date "2022-07-01" @default.
• W3174485517 modified "2023-10-16" @default.
• W3174485517 title "Pedestrian-Aware Statistical Risk Assessment" @default.
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• W3174485517 doi "https://doi.org/10.1109/tits.2021.3074522" @default.
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