Microscopic traffic simulation of free-riding cyclists in downhills

Abstract: A key component of traffic models for simulating bicycle traffic focuses on capturing the interactions between cyclists and the cycling infrastructure. One of the most relevant features of the infrastructure that has a significant impact in bicycle traffic is the gradient of a bicycle path. Bicycle traffic simulations are a rather uninvestigated topic since historically, most focus on simulations has been on cars. However, bicycle simulations are an important tool to further investigate and understand cyclist’s behaviour. Therefore, the main objective of this thesis is to investigate and simulate free-riding behavior of cyclists in connection to the gradient, particularly on downhills. To do so, trajectory data of cyclists traveling on a downhill with a maximum gradient of 5.5\% are analysed to identify the impact of gradient on the speed and acceleration. The data received needed processing in order to be useful. This included filtering of the trajectories and excluding the data from cyclists which could not to be regarded as free-riding. As a result, a linear correlation is found between pedaling power and the gradient that can be used in microscopic bicycle traffic simulation. Based on this knowledge regarding this linearity, the approach used for modeling the gradient’s effect on the pedaling power is linear regression. The model can be developed in various ways, so instead of only choosing one model, several were developed and compared against each other. These models are then used for the simulation. The results indicate that the simulation captures well the impact of downhill gradients in a population of cyclists as it reproduces similar speed profiles to the ones observed. Therefore, it can be concluded that a power-based model is suitable for simulating free-riding behaviour of cyclists traveling in downhills.