Reducing the impact of vibration-caused artifacts in a brain-computer interface using gyroscope data

We implemented an artifact prediction method for a saline-pad wireless electroencephalograph equipped with two-axis gyroscope used as a basic brain-computer interface (BCI). The BCI unit serves two purposes in the scope of the project Innotruck. Firstly, it enables remote control of vehicles and other systems over a limited set of trained mental activity. Secondly, it is a source of data for the passive analysis of the operator's mental fitness, which is further integrated into the driver assistance systems. The latter aspect has been the focus of our work. Saline-pad electrodes used in consumer grade electronics are prone to errors stemming from vibrations and sudden head movements. The implemented approach successfully preconditions the signal processing pipeline to take such artifacts into account and reduces the later processing overhead

A case study on implementing future human-machine interfaces

In the scope of the Diesel Reloaded project, we conducted a study on future automotive human-machine interfaces (HMI) with an overview of their relationship to driver assistance systems (DAS). Furthermore, we implemented a series of HMI and DAS concepts in our prototype vehicle and in a modified driving simulator. Emphasis was placed on the following goals: Pushing the complexity away from the driver and inside the intelligent vehicle, developing unified and extendable descriptions of interaction context, defining transitional steps to the long-term goal of user interfaces which augment the driver, leveraging cross-domain technology transfer and addressing relevant societal trends. In this work, we provide a top-level overview of our results and conclusions we drew based upon our two-year research and prototype construction and deployment in the area of human-machine interfaces and driver assistance

An Improvement

of the driving safety using a virtual drive

RACE: A Centralized Platform Computer Based Architecture for Automotive Applications

In the last couple of years software functionality of modern cars increased dramatically. This growing functionality leads directly to a higher complexity of development and configuration. Current studies show that the amount of software will continue to grow. Additionally, advanced driver assistance systems (ADAS) and autonomous functionality, such as highly and fully automated driving or parking, will be introduced. Many of these new functions require access to different communication domains within the car, which increases system complexity. AUTOSAR, the software architecture established as a standard in the automotive domain, provides no methodologies to reduce this kind of complexity and to master new challenges. One solution for these evolving systems is developed in the RACE project. Here, a centralized platform computer (CPC) is introduced, which is inspired by the well-established approach used in other domains like avionics and automation. The CPC establishes a generic safety-critical execution environment for applications, providing interfaces for test and verification as well as a reliable communication infrastructure to smart sensors and actuators. A centralized platform also significantly reduces the complexity of integration and verification of new applications, and enables the support for Plug&Play