In search of surrogate safety indicators for vulnerable road users: a review of surrogate safety indicators

Surrogate indicators are meant to be alternatives or complements of safety analyses based on accident records. These indicators are used to study critical traffic events that occur more frequently, making such incidents easier to analyse. This article provides an overview of existing surrogate indicators and specifically focuses on their merit for the analyses of vulnerable road users and the extent to which they have been validated by previous research. Each indicator is evaluated based on its ability to consider the collision risk, which can be further divided into the initial conditions of an event, the magnitude of any evasive action and the injury risk in any traffic event. The results show that various indicators and their combinations can reflect different aspects of any traffic event. However, no existing indicator seems to capture all aspects. Various studies have also focused on the validity of different indicators. However, due to the use of diverse approaches to validation, the large difference in how many locations were investigated and variations in the duration of observation at each location, it is difficult to compare and discuss the validity of the different surrogate safety indicators. Since no current indicator can properly reflect all the important aspects underlined in this article, the authors suggest that the choice of a suitable indicator in future surrogate safety studies should be made with considerations of the context-dependent suitability of the respective indicator.     

The ‘safety in density’ effect for cyclists and motor vehicles in Scandinavia: An observational study

Safety in density (SID) potentially explains the safety in numbers (SIN) phenomenon by positing that ‘the SIN effect can be reproduced simply through encouraging behaviour that leads to the formation of higher-density cyclist groups’. The study further explores this hypothesis using event-based exposure, queues and groups of road users. Using three different definitions of encounters between road users, these were manually counted at signalized intersections, and their relationship to traffic volume was assessed. Based only on the frontmost motor vehicle in a queue and one cyclist among the several passing in front of that vehicle, the results show a less than linear relationship between meetings and traffic volume. An increase in the number of cyclists entails a general increase in cyclists passing in front of each motor vehicle, and an increase in motor vehicles increases queue lengths. However, crash data from the Swedish accident database (STRADA) show that it is exceedingly rare for multiple cyclists to be injured in the same crash. Together with results from a crash-encounter model, this suggests that the SID hypothesis may help to explain SIN