Calibrating the Wiedemann 99 Car-Following Model for Bicycle Traffic

Abstract

Car-following models are used in microscopic simulation tools to calculate the longitudinal acceleration of a vehicle based on the speed and position of a leading vehicle in the same lane. Bicycle traffic is usually included in microscopic traffic simulations by adjusting and calibrating behavior models developed for motor vehicle traffic. However, very little work has been carried out to examine the following behavior of bicyclists, calibrate following models to fit this observed behavior, and determine the validity of these calibrated models. In this paper, microscopic trajectory data collected in a bicycle simulator study are used to estimate the following parameters of the psycho-physical Wiedemann 99 car-following model implemented in PTV Vissim. The Wiedemann 99 model is selected due to the larger number of assessable parameters and the greater possibility to calibrate the model to fit observed behavior. The calibrated model is validated using the indicator average queue dissipation time at a traffic light on the facilities ranging in width between 1.5 m to 2.5 m. Results show that the parameter set derived from the microscopic trajectory data creates more realistic simulated bicycle traffic than a suggested parameter set. However, it was not possible to achieve the large variation in average queue dissipation times that was observed in the field with either of the tested parameter sets.