  Increasing the modal share of bicycle traffic to reduce carbon emissions,
reduce urban car traffic, and to improve the health of citizens, requires a
shift away from car-centric city planning. For this, traffic planners often
rely on simulation tools such as SUMO which allow them to study the effects of
construction changes before implementing them. Similarly, studies of vulnerable
road users, here cyclists, also use such models to assess the performance of
communication-based road traffic safety systems. The cyclist model in SUMO,
however, is very imprecise as SUMO cyclists behave either like slow cars or
fast pedestrians, thus, casting doubt on simulation results for bicycle
traffic. In this paper, we analyze acceleration, deceleration, velocity, and
intersection left-turn behavior of cyclists in a large dataset of real world
cycle tracks. We use the results to improve the existing cyclist model in SUMO
and add three more detailed cyclist models and implement them in SUMO.
