Formulation of energy exertion in bicycle networks and estimation of its impact on route choices

Abstract Despite strong indirect evidence that physical energy exertion shapes cycling behaviour, it has never been explicitly incorporated into route choice models. This paper introduces a generalisable, individual-specific, physics-based energy model that computes expected energy expenditure (Joules) and energy intensity (Joules per metre) for every link in the network. The model accounts for slope, individual cruising speed preferences, and acceleration losses at intersections using empirically derived, intersection-specific stopping probabilities. Calibration is performed on a large-scale GPS dataset from the Greater Copenhagen Area. Descriptive analysis of observed routes reveals that excess energy is mainly driven by frequent stopping on major roads and dedicated cycleways. We then demonstrate one key application of the model by integrating both total energy (Joules) and energy intensity (Joules per metre) into a series of route choice models (Multinomial Logit, Latent Class, and Mixed Logit). Results confirm statistically significant dispreference for energy attributes and reveal substantial taste heterogeneity: a substantial subset of cyclists exhibits strong dispreference for high-intensity links and is willing to accept considerable detours to avoid them. This study provides a methodological foundation for integrating mechanical energy into route choice models in a way that is individually calibrated, physically grounded, and adaptable to diverse contexts and datasets. By grounding route choice in a quantity that combines slope, stop-and-go dynamics, and cyclist-specific cruising speed into a single measure of effort, the framework both improves the empirical fit of route choice models and offers a more interpretable account of the mechanisms behind observed preferences. The energy model itself has applications beyond route choice, and opens the door to understanding cyclists’ behaviour through more fundamental physical quantities.