Cargando…
Adaptive physics-informed trajectory reconstruction exploiting driver behavior and car dynamics
As more and more trajectory data become available, their analysis creates unprecedented opportunities for traffic flow investigations. However, observed physical quantities like speed or acceleration are often measured having unrealistic values. Furthermore, observation devices have different hardwa...
Autores principales: | Makridis, Michail A., Kouvelas, Anastasios |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9859820/ https://www.ncbi.nlm.nih.gov/pubmed/36670193 http://dx.doi.org/10.1038/s41598-023-28202-1 |
Ejemplares similares
-
An Experimental Urban Case Study with Various Data Sources and a Model for Traffic Estimation
por: Genser, Alexander, et al.
Publicado: (2021) -
A traffic signal and loop detector dataset of an urban intersection regulated by a fully actuated signal control system
por: Genser, Alexander, et al.
Publicado: (2023) -
The Driver in the Driverless Car
por: Wadhwa, Vivek
Publicado: (2019) -
Effect of Five Driver’s Behavior Characteristics on Car-Following Safety
por: Zhang, Junjie, et al.
Publicado: (2022) -
The Effects of Dynamic Complexity on Drivers’ Secondary Task Scanning Behavior under a Car-Following Scenario
por: Wang, Linhong, et al.
Publicado: (2022)