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Abstract
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Safety performance functions are frequently used to describe the relation of various factors to the number of accidents, often focusing on exposure of vulnerable road users. Those studies require reliable data regarding exposure, but collecting such data is resource demanding, often resulting in short observational periods. This might produce measurement errors, influencing the reliability of the models.
The aim of this work is twofold: to create a safety performance functions for pedestrian and bicyclist accidents at urban intersections, and to analyze the reliability of accident models based on short observational periods, i.e. how does random variation, resulting from short observational periods influence the models? This provides an aid for choosing between increasing the number of sites and the length of the observational period at each site. Accident data were compiled and traffic counting was conducted at 113 urban intersections in Sweden. Multiple samples were created from the counting sessions, facilitating tests of the models' reliability based on lengths of observational periods between 15 and 180 min. Four safety performance functions (accident types) were created. All models showed a safety in numbers effect, including the model for single pedestrian accidents, which might suggest that maintenance and infrastructure quality constitute an important factor for the safety in numbers effect. A sensitivity analysis showed geometric factors, describing the infrastructure quality, influencing the safety in numbers effect, further supporting this hypothesis. The safety performance functions based on short observational periods showed low reliability, indicating that those models are subjected to a considerable measurement error. |