According to crash data reports, most collisions between cyclists and motorized vehicles occur at unsignalized intersections (where no traffic lights regulate vehicle priority). In the era of automated driving, it is imperative for automated vehicles to ensure the safety of cyclists, especially at these intersections. In other words, to safely interact with cyclists, automated vehicles need models that can describe how cyclists cross and yield at intersections. So far, only a few studies have modeled the interaction between cyclists and motorized vehicles at intersections, and none of them have explored the variations in interaction outcomes based on the type of drivers involved. In this study, we compare non-professional drivers (represented by passenger car drivers) and professional drivers (truck and taxi drivers). We also introduce a novel application of game theory by comparing logit and game theoretic models’ analyses of the interactions between cyclists and motorized vehicles, leveraging naturalistic data. Interaction events were extracted from a trajectory dataset, and cyclists’ non-kinematic cues were extracted from videos and incorporated into the interaction events’ data. The modeling outputs showed that professional drivers are less likely to yield to cyclists than non-professional drivers. Furthermore, the behavioral game theoretic models outperformed the logit models in predicting cyclists’ crossing decisions.

High pre-World-War-2 modal shares of cycling in European countries sharply decreased during the post-war decades. In the 1990s, European governments introduced policies to increase bicycle use. However, a database or longitudinal study on the development of bicycle use in European countries is lacking. The goal of this paper is to examine to what degree the amount of cycling has increased over the past decades, also in the context of potentially competing modes. Distances travelled per capita according to National Travel Surveys have been collected and were aggregated to seven 4-year periods between 1990 and 2017. Multilevel regression analyses on distance travelled per capita by bicycle, on foot, by public transport, and by passenger car were conducted for all countries. Additionally, analyses were conducted for which the 14 countries with data on bicycle use were divided in three groups categorised according to distance cycled per capita at the beginning of the study period. Distance cycled per capita per year ranged from some 30 km to 900 km. The results of all four regression analyses suggested that distance cycled per capita remained fairly constant over the past decades. Germany is an exception with some 150 km per capita more, in relative terms a 50% increase. Geographical variation in development is evidenced by a substantial increase of distance cycled per inhabitant in the capital cities of the countries included in the study. The outcomes suggest distance travelled on foot and by public transport (bus, tram, and metro) also remained fairly constant while the distance travelled by car increased by about 10% during the study period. We did not find indications that cycling substitutes travel on foot, by public transport or by car.