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To reduce accidents and fatalities on the roads, active safety systems which can avoid accidents or mitigate their effects are increasingly required. Contrary to already available driver assistance systems a future system can be a Collision Avoidance System which will be able to solve many critical traffic situations by warning, braking or steering. This paper will present a system consisting of environment sensing and situation analysis blocks as well as intervening strategy blocks. The main focus will be put on the scene interpretation of a situation and its optimization. Therefore a rule-based Fuzzy System will be described. Furthermore the Strategy Selection and the Path Planning in case of system intervention will be shown by simulation. The system has been developed during the work at the Adam Opel GmbH.

Faults in the intake and exhaust path of turbocharged common-rail Diesel engines can lead to an increase of emissions and performance losses. Standard fault detection strategies based on plausibility checks and trend checking of sensor data are not able to detect and isolate all faults appearing in the intake and exhaust path without employing additional sensors. By applying model based methods a limited sensor configuration can be used for fault detection. Therefore a model based fault diagnosis concept with parity equations is considered, [1]. In this contribution the fault diagnosis system, which comprises semi-physical thermodynamic turbocharger model, models of gas pressure in the intake and exhaust manifold, residual generation, residual to symptom transformation and fault diagnosis is presented.