As bicycling becomes an integral part of sustainable mobility, it becomes essential to enhance planning strategies that ensure bicycling as an efficient mode of transport. While traffic simulation has been extensively utilized for traffic planning of various modes of transport, this type of modeling support is largely lacking in the planning of bicycle traffic.

Given the high heterogeneity in the characteristics of bicyclists, the use of microscopic traffic simulation, which incorporates the explicit inclusion of individual properties and preferences, becomes particularly useful for evaluating bicycle traffic performance.

By examining real-world traffic, the objective of this thesis is to investigate essential requirements for microscopic modeling and simulation of bicycle traffic on off-street bicycle path segments, and to further develop and evaluate modeling approaches suitable for bicycle traffic. Understanding the fundamentals of how bicyclists interact with the infrastructure and other bicyclists is a necessary step towards accurate simulation of bicycle traffic.

In this thesis, research gaps related to the evaluation of bicycle traffic performance and simulation are identified, and methods to validate bicycling data are proposed to determine its quality and suitability for traffic analysis. Furthermore, two distinct modeling approaches are investigated to simulate the impact of gradients in bicycle traffic. The first involves calibrating a car-based model using a widely-used microscopic traffic simulation software, and the second implements a power-based model rooted in the physical forces acting on a bicycle. Lastly, characteristics of bicycle traffic that are relevant for simulating bidirectional traffic are identified and described.

The work in this thesis offers a starting point towards enhanced microscopic bicycle traffic simulation that effectively assist the planning of efficient bicycle traffic.