Simulations on Consumer Tests: A Perspective for Driver Assistance Systems

This article discusses new challenges for series development regarding the vehicle safety that arise from the recently published AEB test protocol by the consumer-test-organisation EuroNCAP for driver assistance systems [6]. The tests from the test protocol are of great significance for an OEM that sells millions of cars each year, due to the fact that a positive rating of the vehicle-under-test (VUT) in safety relevant aspects is important for the reputation of a car manufacturer. The further intensification and aggravation of the test requirements for those systems is one of the challenges, that has to be mastered in order to continuously make significant contributions to safety for high-volume cars. Therefore, it is to be shown how a simulation approach may support the development process, especially with tolerance analysis. This article discusses the current stage of work, steps that are planned for the future and results that can be expected at the end of such an analysis.Comment: 6 pages, 5 figure, Proceedings of International Workshop on Engineering Simulations for Cyber-Physical Systems (ES4CPS '14

Sensormodelle zur Simulation der Umfelderfassung für Systeme des automatisierten Fahrens

The use of sensor models allows the simulation of environmental perception in automated driving systems, aiding in development and testing efforts. This work systematically discusses the different types of sensor models and introduces an architecture for statistics based as well as for physically motivated sensor models. Each approach is grounded in real world observations of sensor measurements and is designed for portability and the ease of further extensions.Die Nutzung von Sensormodellen für die Umfelderfassung ebnet den Weg für die simulationsgestützte Entwicklung von Systemen des automatisierten Fahrens. In dieser Arbeit wird eine Systematik für verschiedene Arten von Sensormodellen eingeführt und eine Umsetzung von statistischen sowie von physikalisch motivierten Modellen vorgestellt. Beide Ansätze basieren auf realen Sensormessdaten und zielen auf eine leichte Übertragbarkeit sowie die Möglichkeit der Erweiterung der Modelle für verschiedene Anwendungsbereiche

Sensormodelle zur Simulation der Umfelderfassung für Systeme des automatisierten Fahrens

The use of sensor models allows the simulation of environmental perception in automated driving systems, aiding in development and testing efforts. This work systematically discusses the different types of sensor models and introduces an architecture for statistics based as well as for physically motivated sensor models. Each approach is grounded in real world observations of sensor measurements and is designed for portability and the ease of further extensions.Die Nutzung von Sensormodellen für die Umfelderfassung ebnet den Weg für die simulationsgestützte Entwicklung von Systemen des automatisierten Fahrens. In dieser Arbeit wird eine Systematik für verschiedene Arten von Sensormodellen eingeführt und eine Umsetzung von statistischen sowie von physikalisch motivierten Modellen vorgestellt. Beide Ansätze basieren auf realen Sensormessdaten und zielen auf eine leichte Übertragbarkeit sowie die Möglichkeit der Erweiterung der Modelle für verschiedene Anwendungsbereiche

Computational Imaging Approach to Recovery of Target Coordinates Using Orbital Sensor Data

This dissertation addresses the components necessary for simulation of an image-based recovery of the position of a target using orbital image sensors. Each component is considered in detail, focusing on the effect that design choices and system parameters have on the accuracy of the position estimate. Changes in sensor resolution, varying amounts of blur, differences in image noise level, selection of algorithms used for each component, and lag introduced by excessive processing time all contribute to the accuracy of the result regarding recovery of target coordinates using orbital sensor data. Using physical targets and sensors in this scenario would be cost-prohibitive in the exploratory setting posed, therefore a simulated target path is generated using Bezier curves which approximate representative paths followed by the targets of interest. Orbital trajectories for the sensors are designed on an elliptical model representative of the motion of physical orbital sensors. Images from each sensor are simulated based on the position and orientation of the sensor, the position of the target, and the imaging parameters selected for the experiment (resolution, noise level, blur level, etc.). Post-processing of the simulated imagery seeks to reduce noise and blur and increase resolution. The only information available for calculating the target position by a fully implemented system are the sensor position and orientation vectors and the images from each sensor. From these data we develop a reliable method of recovering the target position and analyze the impact on near-realtime processing. We also discuss the influence of adjustments to system components on overall capabilities and address the potential system size, weight, and power requirements from realistic implementation approaches