TY - JOUR
T1 - Calibration and validation of cellular automaton traffic flow model with empirical and experimental data
AU - Jin, Cheng Jie
AU - Knoop, Victor L.
AU - Jiang, Rui
AU - Wang, Wei
AU - Wang, Hao
N1 - Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.
PY - 2018/6/1
Y1 - 2018/6/1
N2 - For traffic flow models, calibration and validation are essential. Cellular automaton (CA) models are a special class of models, describing the movement of vehicles in discretised space and time. However, the previous work on calibration and validation does not discuss CA models systematically. This study calibrates and validates a stochastic CA model. The authors use a simple CA model, which only has two important parameters to be calibrated. The methodology for optimisation is to minimise the relative root mean square error between two properties: The averaged velocity and the variation of velocities in a platoon at a given density. Three different sites are used as cases to show the methodology, for which different types of data (video trajectories or GPS data) are available. The authors find that the best model parameters vary for the different locations. This may result from various driving strategies and potential tendencies. Thus, it is concluded that for CA models, various traffic flow phenomena need to be simulated by various parameters.
AB - For traffic flow models, calibration and validation are essential. Cellular automaton (CA) models are a special class of models, describing the movement of vehicles in discretised space and time. However, the previous work on calibration and validation does not discuss CA models systematically. This study calibrates and validates a stochastic CA model. The authors use a simple CA model, which only has two important parameters to be calibrated. The methodology for optimisation is to minimise the relative root mean square error between two properties: The averaged velocity and the variation of velocities in a platoon at a given density. Three different sites are used as cases to show the methodology, for which different types of data (video trajectories or GPS data) are available. The authors find that the best model parameters vary for the different locations. This may result from various driving strategies and potential tendencies. Thus, it is concluded that for CA models, various traffic flow phenomena need to be simulated by various parameters.
UR - http://www.scopus.com/inward/record.url?scp=85046895215&partnerID=8YFLogxK
U2 - 10.1049/iet-its.2016.0275
DO - 10.1049/iet-its.2016.0275
M3 - Article
AN - SCOPUS:85046895215
SN - 1751-956X
VL - 12
SP - 359
EP - 365
JO - IET Intelligent Transport Systems
JF - IET Intelligent Transport Systems
IS - 5
ER -