This thesis work aims at performing a survey of those technologies generally called DriverAssistance Systems (DAS). This thesis work focuses on gathering information in terms ofaccident statistics, sensors and functions and analyzing this information and shall thruaccessible information match functions with accidents, functions with sensors etc.This analysis, based on accidents in United States and Sweden during the period 1998 – 2002and two truck accident studies, shows that of all accidents with fatalities or sever injuriesinvolving a heavy truck almost half are the result of a frontal impact. About one fourth of theaccidents are caused by side impact, whereas single vehicle and rear impact collisions causesaround 14 % each. Of these, about one fourth is collision with unprotected (motorcycles,mopeds, bicycles, and pedestrians) whereas around 60 % are collision with other vehicles.More than 90 % of all accidents are partly the result of driver error and about 75 % aredirectly the result of driver error. Hence there exist a great opportunity to reduce the numberof accidents by introducing DAS.In this work, an analysis of DAS shows that six of the systems discussed today have thepotential to prevent 40 – 50 % of these accidents, whereas 20 – 40 % are estimated to actuallyhaving the chance to be prevented.One of these DAS, automatic emergency brake (AEB), has been analyzed in more detail.Decision models for an emergency brake capable to mitigate rear-end accidents has beendesigned and evaluated. The results show that this model has high capabilities to mitigatecollisions.