Modeling the Speed, Acceleration, and Deceleration of Bicyclists for Microscopic Traffic Simulation

Abstract

Models were developed, calibrated, and evaluated to describe the acceleration and deceleration processes of bicyclists in three states: while they accelerate from a stop, decelerate to a stop, and fluctuate around the desired traveling speed. Such models are necessary to simulate the speed profiles of bicyclists reliably in microscopic traffic simulations. To accomplish this aim, a sample of 1,030 processed trajectories from bicyclists at four intersections in Munich, Germany, was used to analyze the dynamic characteristics of bicyclists. The average crossing speed, the fluctuation in crossing speed, and the minimum and the maximum speeds of uninfluenced bicyclists who crossed at a green light were analyzed, and correlations between these variables were investigated. The acceleration and deceleration profiles of bicyclists who stopped at a red light but were uninfluenced by other bicyclists, were used to evaluate four acceleration–deceleration models: the constant model, the linear decreasing model, the two-term sinusoidal models, and a polynomial model. Two adaptations of the models were developed and evaluated: one to derive acceleration and deceleration as a function of speed rather than time, and the other to account for the observed fluctuation in bicyclist traveling speed. The polynomial model was found to be the most flexible and to produce the overall best estimates of the acceleration profiles. The constant model was found to estimate best the deceleration, acceleration, and deceleration while fluctuation occurred around the desired speed.