Automatic Headlight Leveling System with a Modular Design for the Automotive Aftermarket The automotive sector is currently in a dynamic change by the introduction of new vehicle concepts, like electric and autonomous vehicles, and innovative driver assistance systems like systems for a precise adaptive headlight adjustment. The continuous adjustment of the headlamps is very important for the correct illumination of the road and prevention of blinding the oncoming traffic, respectively. Hence, a great share of new vehicles possess an automatic headlight adjustment. In some countries, like Germany, these systems are legally required for some kinds of headlights. Nevertheless, there are only a few suppliers for aftermarket products and thus, the product range of automatic headlamp adjustment systems for existing vehicles is low. This paper presents a system concept for the aftermarket that is modular designed and easy to integrate in existing vehicles. In addition, the concept includes a novel approach by the application of a smart tire pressure monitoring system for the detection of the tilt angle of the vehicle. Therefore, consumers who like to change their light technology (e.g. LED instead of halogen headlights) and to integrate a system for headlight adjustment can benefit from the system shown in this paper.

Development Environment Proposal for Automotive VisionBased Algorithms Next generation autonomous driving functions heavily depend on various computationally intensive algorithms based on machine vision. Design and development of such algorithms is challenging, requiring engagement of a wider community and the availability of appropriate, costeffective tooling. Setting up a hardware and software environment that would both reflect actual automotive requirements and facilitate development and prototyping, is an uneasy task. In this paper, we analyze the available development platforms which could be utilized in automotive machine vision, with specific regard to new algorithm requirements, such as the utilization of AI, hardware acceleration and low latency. We give a proposal of an affordable and scalable development setup consisting of heterogeneous, visionenabled SoCs and automotive interfaces.