Car-Following Models

Traffic flow theories seek to describe in a precise mathematical way the interactions between the vehicles and their operators (the mobile components) and the infrastructure (the immobile component). The latter consists of the highway system and all its operational elements: control devices, signage, markings, etc. As such, these theories are an indispensable construct for all models and tools that are being applied in the design, operation, and development of advanced transportation systems.

This report provides an updated survey of the most important models and theories that characterize the flow of highway traffic in its many facets. It was prepared by the TRB Committee on Traffic Flow Theory and Characteristics of the Transportation Research Board (TRB) and was published in 2001.

This report follows in the tracks of two previous reports that were sponsored by the (formerly called) Committee on Theory of Traffic Flow of the Transportation Research Board (TRB) and its predecessor the Highway Research Board (HRB). The first report was published as HRB Special Report 79 in 1964. A revised version was published as TRB Special Report 165 in 1975. The present publication is the third updated edition of the report.

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.