The variety in accident causation has led to the development of several different traffic safety systems (TSS) for collision avoidance or reduction of collision severity. Hence, a question of prioritisation for the market introduction of these systems arises. The project describes a method which investigates the benefit potential of different systems. The in-depth accident database ZEDATU, including fatal accidents, in Austria is used. The pre-collision phase was investigated with numerical accident reconstruction using PC-Crash. The efficiency of safety systems is calculated either by integration of intervention systems in the simulation (ESC, ABS, Brake Assist and Evasive Manoeuvre Assistant) or by subjective evaluation of the pre-collision situation. The main advantage of the presented method is that many different traffic safety systems are analysed in detail using the same representative sample
with comparatively high case numbers, thereby leading to improved comparability. The present study
weights the selected sample (n = 217) to make it statistically representative. For each of the selected
43 systems, the potential for collision avoidance or the reduction of fatalities is analysed. The results
are compared with findings in the literature and the authors propose a prioritisation for traffic safety
systems. The results especially indicate that systems effective in lateral vehicle dynamics (Evasive
Manoeuvre Assistant, Lane Keeping Assist, ESC) offer a significant potential to avoid fatal injuries,
in addition to autonomous Brake Assist, Collision Warning Systems and Driver Vigilance Monitoring.
Introduction
Due to the variety of traffic accident causations,
many different countermeasures for traffic accidents
have been developed and will be developed
in the future. Countermeasures for traffic accidents
can operate on the primary (collision avoidance
and mitigation), secondary (reduction of
injury risk) or tertiary (post-crash treatment) safety
level of the involved traffic element (human,
vehicle or environment).