Calibrating car‐following parameters for snowy road conditions in the microscopic traffic simulator VISSIM

Abstract

Calibrated simulation models taking into account adverse weather conditions can be used to optimise traffic management strategies, such as speed adaptation and signal timing optimisation. On snowy road conditions, car-following behaviour changes because drivers tend to accelerate more slowly, increase their following distance and drive with lower speeds. Such changes results in lower saturation flow rates at intersections. In order to simulate traffic on snowy road conditions in a valid way, the parameters of a simulation have to be calibrated for adverse weather. This study identifies the parameters of the car-following model in the microscopic simulator VISSIM that are sensitive to snowy road conditions and indicates valid parameter subspaces leading to a good match of simulation model output with observed saturation flow rates and start-up delays. In combination with green time of a signalised intersection, saturation flow rate is essential for correctly estimating road capacity.