Abstract
Over the past few years semi-autonomous driving functionality was introduced in the automotive market, and this trend continues towards fully autonomous cars. While in autonomous vehicles data from various types of sensors realize the new highly safety critical autonomous functionality, the already complex system architecture faces the challenge of designing highly reliable and safe autonomous driving system. Since sensors are prone to intermittent faults, using different sensors is better and more cost effective than duplicating the same sensor type because of diversity of reaction of different sensor typesto the same environmental condition. Specifying and validating sensors and providing technical means that enable usage of data from different sensors in case of failures is a challenging, time-consuming and error-prone task for engineers. Therefore, in this paper we present our model-based approach and a run-time system that improves the safety of autonomous driving systems by providing reusable framework managing different sensor setups in a vehicle in a case of a error. Moreover, the solution that we provide enables adaptive graceful degradation and reconfiguration by effective use of the system resources. At the end we explain in an example when and how the approach can be applied.
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References
Laprie, J.C.C., Avizienis, A., Kopetz, H.: Dependability: Basic Concepts and Terminology. Springer-Verlag New York, Inc. (1992)
Lehmann, G., Blumendorf, M., Trollmann, F., Albayrak, S.: Meta-modeling Runtime Models. In: MoDELS Workshops (2010)
Roth, E., Dirndorfer, T., von Neumann-Cosel, K., Fischer, M.-O., Ganslmeier, T., Kern, A., Knoll, A.: Analysis and Validation of Perception Sensor Models in an Integrated Vehicle and Environment Simulation. In: Proceedings of the 22nd Enhanced Safety of Vehicles Conference (2011)
Mamun, M., Berger, C., Hansson, J.: MDE-based Sensor Management and Verification for a Self-Driving Miniature Vehicle. In: Proceedings of the 13th Workshop on Domain-Specific Modeling (2013)
Frtunikj, J., Rupanov, V., Camek, A., Buckl, C., Knoll, A.: A Safety Aware Run-Time Environment for Adaptive Automotive Control Systems. In: Embedded Real-Time Software and Systems, ERTS2 (2014)
Shelton, C.P., Koopman, P., Nace, W.: A framework for scalable analysis and design of system-wide graceful degradation in distributed embedded systems. In: Proceedings of the Eighth International Workshop on Object-Oriented Real-Time Dependable Systems (2003)
Tichy, M., Giese, H.: Extending Fault Tolerance Patterns by Visual Degradation Rules. In: Proceedings of the Workshop on Visual Modeling for Software Intensive Systems, VMSIS (2005)
Urmson, C., et al.: Autonomous driving in urban environments: Boss and the Urban Challenge. Journal of Field Robotics Special Issue on the 2007 DARPA Urban Challenge, Part I (2008)
Bernhard, M., et al.: The Software Car: Information and Communication Technology (ICT) as an Engine for the Electromobility of the Future, Summary of results of the “eCar ICT System Architecture for Electromobility” research project sponsored by the Federal Ministry of Economics and Technology (2011)
Dmitri, D., et al.: Path Planning for Autonomous Vehicles in Unknown Semi-structured Environments. Sage Publications, Inc. (2010)
International Organization for Standardization: ISO/DIS 26262 - Road vehicles. Functional safety. Technical Committee 22, ISO/TC 22 (2011)
Broy, M., Kruger, I.H., Pretschner, A., Salzmann, C.: Engineering Automotive Software. Proceedings of the IEEE (2007)
Sommer, S., et al.: RACE: A Centralized Platform Computer Based Architecture for Automotive Applications. In: Vehicular Electronics Conference (VEC) and the International Electric Vehicle Conference, IEVC (2013)
Adler, R., Schaefer, I., Schuele, T.: Model-Based Development of an Adaptive Vehicle Stability Control System, Modellbasierte Entwicklung von eingebetteten Fahrzeugfunktionen, MBEFF (2008)
AUTOSAR Group: AUTomotive Open System ARchitecture (AUTOSAR) Release 4.1 (2013)
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Frtunikj, J., Rupanov, V., Armbruster, M., Knoll, A. (2014). Adaptive Error and Sensor Management for Autonomous Vehicles: Model-Based Approach and Run-Time System. In: Ortmeier, F., Rauzy, A. (eds) Model-Based Safety and Assessment. IMBSA 2014. Lecture Notes in Computer Science, vol 8822. Springer, Cham. https://doi.org/10.1007/978-3-319-12214-4_13
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DOI: https://doi.org/10.1007/978-3-319-12214-4_13
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-12213-7
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