Christian Lauerer

Modeling and simulation of rain for the test of automotive sensor systems

This paper presents a new approach for the test of automotive sensor systems in rain. The approach is based on an indoor test method, which helps to save test kilometers and test effort. For the activation of safety systems detailed information about the vehicles environment is necessary. Laser scanners provide precise information about the environment and a high angular resolution in contrast to radar sensors [1]. The performance of laser scanners depends on their local environment, because of the attenuation of the ambient atmosphere, precipitation and on the reflectivity of objects. False measurements in the field of vehicle safety can result in severe injury or death, so high reliability is essential. For this purpose a theoretical model is developed in order to determine the sensor behavior. Subsequently, a rain simulator is constructed to validate the theoretical model. Furthermore the developed rain simulator is validated by comparison with real rain. Based on determined rain disturbances benchmark tests of different sensor systems and algorithm approaches can be performed.

Advantages in Crash Severity Prediction Using Vehicle to Vehicle Communication

The paper discusses a new approach in contactless crash detection combining measurements of vehicle dynamics, exteroceptive sensors and vehicle-to-vehicle (V2V) communication data. The proposed architecture aims to activate vehicle safety functions prior an imminent collision to minimize the risk of suffering a major injury. An activation needs a precise prediction of time to collision (TTC), the crash severity (Cs) and other relevant crash parameters. This paper studies the contribution of V2V communication data to predict potential collisions and to realize a reliable activation. An algorithm is presented, that merges fused measurements of a video camera, a laser range finder (LRF) and ego vehicle motion sensors with V2V communication data to predict collisions. The benefit using V2V communication is demonstrated by evaluating collision prediction errors. This analysis is carried out based on experimental data produced by two scale model vehicles.