Christian Grünler

Design Methods for Augmented Reality In-Vehicle Infotainment Systems

We have experienced rapid development of augmented reality (AR) systems and platforms in the automotive industry. However, to bring AR into production cars, we still face a range of challenges to design an AR system that meets vehicle specific requirements. Based on our experience with an AR prototype car, we analyze the influence of augmented reality on the design of the in-vehicle electric/electronic (E/E) architecture.

AR-IVI — Implementation of In-Vehicle Augmented Reality

In the last three years, a number of automotive Augmented Reality (AR) concepts and demonstrators have been presented, all looking for an interpretation of what AR in a car may look like. In October 2013, Mercedes-Benz exhibited to a public audience the AR In-Vehicle Infotainment (AR-IVI) system aimed at defining an overall in-vehicle electric/electronic (E/E) architecture for augmented reality rather than showing specific use cases. In this paper, we explain the requirements and design decisions that lead to the system-design, and we share the challenges and experiences in developing the AR-IVI system in the prototype vehicle. Based on our experiences, we give an outlook on future software and E/E architectural challenges of in-vehicle augmented reality.

Stixel on the Bus: An Efficient Lossless Compression Scheme for Depth Information in Traffic Scenarios

The modern automotive industry has to meet the requirement of providing a safer, more comfortable and interactive driving experience. Depth information retrieved from a stereo vision system is one significant resource enabling vehicles to understand their environment. Relying on the stixel, a compact representation of depth information using thin planar rectangles, the problem of processing huge amounts of depth data in real-time can be solved. In this paper, we present an efficient lossless compression scheme for stixels, which further reduces the data volume by a factor of 3.3863. The predictor of the proposed approach is adapted from the LOCO-I (LOw COmplexity LOssless COmpression for Images) algorithm in the JPEG-LS standard. The compressed stixel data could be sent to the in-vehicle communication bus system for future vehicle applications such as autonomous driving and mixed reality systems.