Physical characterisation of urban cyclists for advanced bicycle travel models

Urban cyclist’s physical characteristics are important for advanced modelling of bicycle speed and energy expenditure, with applications including infrastructure design, network analysis, and health and safety assessments. However, representative values for diverse urban travellers have not been established. This study investigates the physical characteristics of real-world urban cyclists, including rolling and drag resistance parameters, and bicycle and cargo masses. Relationships among physical characteristics socio-demographics and travel behaviour are also analysed, and a bicycle cruising speed model is derived to illustrate usefulness of the sought parameters. Firstly, a 12-sensor, 100-meter coast-down test setup is developed and indoor and outdoor validation tests are performed. Outdoor validation tests generate rolling resistance coefficient estimates of 0.0064 ±0.0013 and effective frontal area estimates of 0.63 ±0.11 m². Secondly, resistance parameters were measured utilizing the novel coast-down test for 557 intercepted cyclists in Vancouver, Canada.. The average (standard deviation) of coefficient of rolling resistance (), effective frontal area (), bicycle plus cargo mass, and bicycle-only mass were 0.0077 (0.0036), 0.559 (0.170) m², 18.3 (4.1) kg, and 13.7 (3.3) kg, respectively. The range of measured values is wider and higher than suggested in the literature. Thirdly, the sample of intercepted cyclists is categorised based on observed physical attributes of the bicycle and rider. Three typologies defined through cluster analysis were identified as Road (R), Hybrid (H) and Mountain (M) style urban cyclists. The analysis indicates that cycling efficiency, perceptions, preferences, and habits are related to physical typology in a complex but consistent manner. M, H, and R cyclists are, in that order, increasingly more efficient, more comfortable in mixed traffic, more II consistently year-round cyclists, self-reportedly faster, and engage in more physical activity. Physical typologies might help unveil new motivations in active travel behaviour and encourage urban cycling by a wider range of people. Finally, a mathematical framework is derived from first principles to determine speed from cyclist characteristics (power output, gearing, resistance parameters) and roadway attributes. Application of the speed estimation framework to the problem of traffic signal clearance interval timing illustrates the utility for probabilistic, context- sensitive roadway design.Applied Science, Faculty ofCivil Engineering, Department ofGraduat