Abstract
Driving assistance or automated driving depends to a large extent on the correct perception of the environment. Because automated driving functions have to be proven safe under all operational conditions, worst-case assumptions concerning the sensors and also the environment have to be assumed. In this paper, we propose a scheme that allows taking weaker assumptions. This is based on a continuous assessment of the quality of sensor data, a model of the interaction between the control process and the environment and the possibility to adapt the performance. We present an example of a car autonomously driving a simple course and adapting its speed according to the environment and the confidence in the perceived sensor data. We derive a set of simple safety rules used to adjust performance that, in the case given in the example affects the cruising speed.
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References
(ISO), ISO 26262-1 to ISO 26262-9, 1st edn. (2011)
Casimiro, A., Kaiser, J., Schiller, E.M., Costa, P., Parizi, J., Johansson, R., Librino, R.: The karyon project: Predictable and safe coordination in cooperative vehicular systems. In: 2013 43rd Annual IEEE/IFIP Conference on Dependable Systems and Networks Workshop (DSN-W), pp. 1–12. IEEE (2013)
Brade, T., Zug, S., Kaiser, J.: Validity-based failure algebra for distributed sensor systems. In: 2013 IEEE 32nd International Symposium on Reliable Distributed Systems (SRDS), pp. 143–152. IEEE (2013)
Ni, K., Ramanathan, N., Chehade, M.N.H., Balzano, L., Nair, S., Zahedi, S., Kohler, E., Pottie, G., Hansen, M., Srivastava, M.: Sensor network data fault types. ACM Transactions on Sensor Networks (TOSN) 5(3), 25 (2009)
Zug, S., Dietrich, A., Kaiser, J.: Fault-handling in networked sensor systems. In: Fault Diagnosis in Robotic and Industrial Systems (2012)
Moffat, R.J.: Describing the uncertainties in experimental results. Experimental Thermal and Fluid Science 1(1), 3–17 (1988)
Stamatis, D.H.: Failure Mode and Effect Analysis: Fmea from Theory to Execution. ASQ Quality Press, Milwaukee (2003)
Elmenreich, W.: Fusion of continuous-valued sensor measurements using confidence-weighted averaging. Journal of Vibration and Control 13(9-10), 1303–1312 (2007)
Piontek, H.-M.: Self-description mechanisms for embedded components in cooperative systems. Der Andere Verlag (2007)
Duta, M., Henry, M.: The fusion of redundant seva measurements. IEEE Transactions on Control Systems Technology 13(2), 173–184 (2005)
Blanke, M., Schröder, J.: Diagnosis and fault-tolerant control, vol. 115. Springer (2003)
Frank, P.M.: Fault diagnosis in dynamic systems using analytical and knowledge-based redundancy: A survey and some new results. Automatica 26(3), 459–474 (1990)
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Brade, T., Jäger, G., Zug, S., Kaiser, J. (2014). Sensor- and Environment Dependent Performance Adaptation for Maintaining Safety Requirements. In: Bondavalli, A., Ceccarelli, A., Ortmeier, F. (eds) Computer Safety, Reliability, and Security. SAFECOMP 2014. Lecture Notes in Computer Science, vol 8696. Springer, Cham. https://doi.org/10.1007/978-3-319-10557-4_7
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DOI: https://doi.org/10.1007/978-3-319-10557-4_7
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-10556-7
Online ISBN: 978-3-319-10557-4
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