A 3D Time-of-Flight Mixed-Criticality System for Environment Perception

Automated driving systems have to operate at the highest level of robustness and safety. Thus, redundancy and diversity of the deployed systems are inevitable in order to guarantee the functionality in any possible scenario. Today, the most used sensor technologies for environment perception are color cameras, radar, light detection and ranging (LIDAR), and ultrasonic sensors. This work evaluates the feasibility of a 3D Time-of-Flight (ToF) camera to be used as environmental perception sensor in robotics and automated/assisted driving. To examine the performance of the sensor in the field, a ToF processing platform is attached to a 1:5 scaled remote control vehicle. An algorithm, which detects and reacts to obstacles in real-time, is designed and implemented on an AURIX automotive safety-microcontroller as major part of a mixed-criticality application. The embedded system highly benefits from the low computational effort required by ToF imaging (in contrast to stereo vision). Utilizing all three cores of the AURIX, the system achieves frame-rates of up to 30 frames per second (FPS).