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The ongoing increase of bicycle traffic in urban areas forces transport authorities to reconsider the space allocation for different transport modes. Transport policies favor the introduction of high-quality bicycle infrastructure along urban corridors to improve the traffic quality and safety for bicyclists but more importantly to increase the attractiveness of bicycling and over vehicular modes. Especially in urban areas with an already established high and steadily increasing share of bicyclists, the introduction of bicycle highways is considered to further alleviate saturated interurban public transport and motor vehicle connections and increase the average traveled distance by non-motorized modes. Due to the expensive implementation costs and the space restrictions in already built-up urban environments, there should be an extensive planning phase for defining the expected changes in traffic efficiency and safety. However, the effects of urban bicycle highways on traffic performance metrics of bicyclists as well as other road users are not thoroughly studied. This paper aims to quantify and assess the potential effects of urban bicycle highway on road users. The study considers a possible inner-city pilot route in the city of Munich, where the present bicycle infrastructure is planned to be upgraded to a bicycle highway. A simulation model is designed using traffic data from field observations and future estimates for the traffic composition. Through microscopic traffic simulation, the potential effects of the introduced infrastructure on road users are determined for different study scenarios. Results show that traffic quality thresholds for bicycle highways, as defined in official guidelines, can only be fulfilled through the implementation of special bicycle traffic control measures such as bicycle coordination or bicycle passage time extension. Finally, unidirectional bicycle highways together with bicycle passage time extension provided the best overall traffic performance for bicycle traffic and motor vehicle traffic.

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Car-following models are used in microscopic simulation tools to calculate the longitudinal acceleration of a vehicle based on the speed and position of a leading vehicle in the same lane. Bicycle traffic is usually included in microscopic traffic simulations by adjusting and calibrating behavior models developed for motor vehicle traffic. However, very little work has been carried out to examine the following behavior of bicyclists, calibrate following models to fit this observed behavior, and determine the validity of these calibrated models. In this paper, microscopic trajectory data collected in a bicycle simulator study are used to estimate the following parameters of the psycho-physical Wiedemann 99 car-following model implemented in PTV Vissim. The Wiedemann 99 model is selected due to the larger number of assessable parameters and the greater possibility to calibrate the model to fit observed behavior. The calibrated model is validated using the indicator average queue dissipation time at a traffic light on the facilities ranging in width between 1.5 m to 2.5 m. Results show that the parameter set derived from the microscopic trajectory data creates more realistic simulated bicycle traffic than a suggested parameter set. However, it was not possible to achieve the large variation in average queue dissipation times that was observed in the field with either of the tested parameter sets.

Detailed specifications of urban traffic from different perspectives and scales are crucial for understanding and predicting traffic situations from the view of an autonomous vehicle (AV). We suggest a data-driven specification scheme for maneuvers at different design elements of the built infrastructure and focus on urban roundabouts in Germany. Based on real observations, we define classes of maneuvers, interactions and driving strategies for cyclists, pedestrians and motorized vehicles and define a matrix for merging different maneuvers, resulting in more complex interactions. The sequences of these interactions, which partially consist of explicit communications, are extracted from real observations and adapted into microscopic traffic flow simulations. The simulated maneuver sequences are then visualized in 3D environments and experienced by bicycle simulator test subjects. Using trajectory segments (in fictional space) from two conducted simulator studies, we relate the recorded movement patterns of test subjects with observed cyclists in reality.