An Energy-Based Model for the Micro-Simulation of a Synthetic Population of Free Cyclists

Recent trends in mobility and transportation underscore the growing importance of promoting alternative, flexible, and environmentally friendly modes of transport—such as cycling—that not only contribute significantly to users’ health and well-being but also enable urban concepts like the 15-minute city. For cyclists, travel time is a critical factor influencing both route selection and the decision to choose cycling as a preferred mode of transportation. This paper presents an energy-based model of a synthetic population of free cyclists to analyze their speed profile characteristics, summarized in terms of average speeds. The proposed model is intended for use in evaluating infrastructure planning, optimizing green wave traffic light systems, and assessing the health benefits of cycling. The model is built on general data (not fitted to a certain dataset) and accounts for key factors such as rolling resistance and aerodynamic drag—both of which vary with ambient temperature—along with acceleration, road gradient, and other influences, including free rolling and deceleration or stopping at intersections and traffic lights. The results reveal a distribution of cycling speeds that show good agreement with field observations.