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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...
In comparison to event-triggered systems, the time-triggered paradigm enhances the design flow with the definition of the system timing behavior. This approach provides positive aspects with regards to the development of predictable systems. However, the migration to a time-triggered scheme presents different challenges such as the efficient definition and management of timing information during the...
Vehicles may be recognized from the sound they emit when driving along a road. Characteristic acoustic finger prints and audio features can be used to increase the robustness of existing video based vehicle tracking and classification algorithms. Using this information in a multisensor surveillance system helps to improve various parameters such as recognition rates, detection times and robustness...
In this paper we describe a low level method for detecting and locating faults in the electrical physical layer of automotive networks based on time-domain reflectometry. Especially for safety-critical networks this approach could be a valuable complement for the existing network management layers, since it has the potential to detect damaged cables and plugs even before they cause serious malfunctions...
Failure Mode and Effect Analysis (FMEA) is a standardized approach during the development of safety-relevant systems in order to systematically identify and address the possible system failures as well as analysis their effects. In the case of FlexRay-based distributed systems, the communication network technology is complex and presents high variability due to the large range of allowed topologies...
I-SENSE demonstrates the potential of combining the scientific research areas multi-sensor data fusion and pervasive embedded computing. The main idea is to provide a generic architecture which supports a distributed online data fusion on an embedded system. Due to their high onboard processing and communication power our proposed architecture is designed to perform sophisticated data fusion tasks...
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