In this research a dynamic time and energy model is constructed to simulate free flow utility cycling. Using a Monte Carlo simulation and distributions of rider and bicycle characteristics a population of cyclists is modelled to find the difference in time and energy expenditure
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In this research a dynamic time and energy model is constructed to simulate free flow utility cycling. Using a Monte Carlo simulation and distributions of rider and bicycle characteristics a population of cyclists is modelled to find the difference in time and energy expenditure on six different bicycle routes. The riders use realistic like power inputs and braking behaviour based on the rider and the route characteristics. While travel times are almost always lower for all cyclists when comparing routes, there are cyclists for who a shorter route distance does not equal a lower energy expenditure. For simpler routes (less elevation difference, traffic lights and shorter distance) the standard deviation of both time and energy decreases, showing that slow cyclist have a relative higher gain. For e-bike users there is even almost no difference in energy expenditure between the six evaluated routes that have varying elevation, traffic signals and routing, while travel times show a similar trend as for regular bicycles. With this model difference in routes can be quantified in matters of time and energy expenditure for a population of cyclists giving an objective picture of the differences between routes, which can be a useful tool for city planning and evaluation of bicycle infrastructure.