EDI analyzed more than 100.000 critical incidents in traffic, specifically focusing on the drivers' decision-making process in those situations. In this context, the human anticipation of hazards plays an essential role to avoid accidents as well as uncomfortable situations. The relevant driving context parameters of those incidents were identified and quantified regarding their contribution to the criticality of a specific traffic situation. On this basis, the Dynamic Risk Management Algorithm that anticipates hazards based on the driving context just like experienced human drivers were developed.