Multiple model stochastic filtering for traffic density estimation on urban arterials
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DOI: 10.1016/j.trb.2019.06.009
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Cited by:
- Wang, Jiawen & Zou, Linzhi & Zhao, Jing & Wang, Xinwei, 2024. "Dynamic capacity drop propagation in incident-affected networks: Traffic state modeling with SIS-CTM," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 637(C).
- Guan, Xiangyang & Chen, Cynthia, 2021. "A behaviorally-integrated individual-level state-transition model that can predict rapid changes in evacuation demand days earlier," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 152(C).
- Storm, Pieter Jacob & Mandjes, Michel & van Arem, Bart, 2022. "Efficient evaluation of stochastic traffic flow models using Gaussian process approximation," Transportation Research Part B: Methodological, Elsevier, vol. 164(C), pages 126-144.
- Ngoduy, D., 2021. "Noise-induced instability of a class of stochastic higher order continuum traffic models," Transportation Research Part B: Methodological, Elsevier, vol. 150(C), pages 260-278.
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Keywords
Traffic state estimation; Stochastic Kalman filtering; Urban arterial; Multiple model filtering; SCATS data;All these keywords.
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