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Cities throughout the world have increasingly promoted walking and cycling as healthy and sustainable modes of travel. However, collisions between pedestrians and cyclists have remained largely unstudied, and existing accident statistics suffer from underreporting. This study aimed to explore near accidents and collisions between pedestrians and cyclists, assess the frequency of near accidents, and evaluate pedestrians’ and cyclists’ sense of safety in traffic. An online survey was directed to inhabitants of Finnish cities with populations greater than 100,000, and the resulting data included 1046 respondents who walk and/or cycle regularly.The main results show that near accidents between pedestrians and cyclists are around 50 times more frequent than collisions. Only 16 survey respondents had been involved in a collision during the 3-year period, whereas roughly a third had experienced at least one near accident. For both near accidents and collisions, the involved parties were usually travelling in the same direction. Most incidents occurred on pedestrian paths and shared pedestrian and bicycle paths. On shared pedestrian and bicycle paths separated by mode of transport, incidents were much rarer. Furthermore, sense of safety and willingness to walk and cycle were lower in environments where near accidents were more frequent.These findings tentatively suggest that spatially separating modes of transport could improve people’s sense of safety and prevent near accidents and collisions. Prevention of near accidents could increase the willingness to walk and cycle.

Complex social processes introduce difficulties to validating causal parameters and identifying the correct system structure in modelling. Policy impact assessment for sustainability transitions should therefore not expend too many resources modelling any single set of assumptions about the world. Furthermore, keeping models relatively simple allows more effective communication and stakeholder collaboration. This paper presents an exploratory system dynamics model of urban mode choice. We demonstrate that, despite structural and parametric uncertainty, it is possible to rank alternative policy approaches and identify high-leverage uncertainties as targets of policy action or further analysis. We also show how different narrative theories of change can have drastically different or unintuitive outcomes for the same intervention. Simulation can benefit both impact assessment and the further scrutiny and refinement of change narratives. We argue that the following methodological choices and their synergies made our modelling approach effective: exploratory modelling, focus on endogeneity, coarse resolution and avoidance of abstract variables.