Physiological energy demand modeling for cycling and network graphs

Abstract

While the health benefits of cycling are well established, its role as a primary mode of sustainable daily transport and how to promote it remains less explored. Route selection and energy expenditure of cyclists are influenced by factors such as network availability, terrain, traffic, and environmental conditions. We propose the physiological energy demand model for cycling (PEDMC) that links network conditions with human energy effort by considering real-world urban cycling conditions, including slope, wind, and stop-and-go traffic. The PEDMC is grounded in interpretable physical relations without the need for data-driven calibration. It enables detailed analysis of the physiological energy consumption of cycling and allows comparisons with traditional routing algorithms based on time or distance. Applied to a cycling network in Vienna, the PEDMC demonstrates that using physiological energy consumption as a path search criterion leads to significantly different route selection compared to distance- or time-based route planning approaches. Employing the PEDMC reduces cycling effort by up to 6 % in flat areas and up to 30 % in hilly terrain. By evaluating cycling routes based on physiological energy expenditure, the PEDMC not only supports energy-efficient mobility planning but also contributes to the development of health-supportive, inclusive, and accessible cycling infrastructure. As such, the proposed model offers a valuable tool for advancing active travel strategies and promoting sustainable and healthy urban transport systems. It supports designing clean, healthy, and inclusive urban mobility systems.