The Agency for Roads and Traffic and the Department of Mobility and Public Works together strive for safer traffic, with fewer accidents, fewer injuries and fewer deaths. Therefore - with regard to the identification of dangerous locations - they do not want to wait until an accident happens before addressing the dangerous situation, but to use a broader set of tools to achieve a more anticipatory and proactive identification of dangerous locations on both the main and secondary road network.

Regarding that identification of dangerous locations, there are three main groups of analysis methods:

• Reactive: dangerous points or road segments identified based on the analysis of accident data
• Proactive: dangerous points or road segments identified based on other available data sources, such as in-vehicle data, infrastructure and design features, etc.
• Participatory: dangerous points or road segments identified based on a subjective sense of unsafety among road users themselves.

The aim of this assignment is to develop an integrated tool in which the ‘traditional’ hazard points based on accident data are still the foundation, but can be strengthened and extended with insights from other objective and subjective data. Here, it will be up to decision-makers to determine, based on quality and availability, how heavily a particular data source weighs in prioritising the locations that will eventually be addressed.

Such an integrated tool will not only allow dangerous sites to be detected in a more proactive way, but, thanks to the wealth of information, will also make it possible to monitor better, faster and more efficiently whether tackled sites have actually become safer.