Multi Level Fusion for an Automotive Pre-Crash Safety System

The fusion of data from different sensorial sources is today the most promising method to increase robustness and reliability of environmental perception. Automotive safety systems like "Adaptive Cruise Control" (ACC) and "Lane Change Assist" are nowadays dealing with the detection of vehicles on the road. New sensors like 3-dimensional measuring multilayer laser scanner systems will be introduced in the near future to deliver environment information for these systems. By fusing multiple sensors like laser and radar systems the reliability level of automotive safety applications will be improved significantly. The paper presents an approach for the fusion of muitilayer laser scanner (lidar) data with radar measurements for the detection of vehicles in road environments. The lidar data is processed using a new 3-dimensional occupancy grid. An example is given for the fusion of lidar and radar information for a pre-crash application.