Abstract
Many companies are studying autonomous vehicles. One trend in the development of control algorithms for autonomous vehicles is the use of deep-learning approaches. The general idea is to simulate a human driver’s decision-making and behavior in various scenarios without necessarily knowing why the decision is made. In this position paper, we first argue that traditional safety analysis methods need to be extended to verify deep-learning-based autonomous vehicles. Then, we propose borrowing ideas from the process of issuing driving licenses to human drivers to verify autonomous vehicles. Verification of autonomous vehicles could focus on sufficient training as well as mental and physical health checks. Based on this position, we list several challenges that need to be addressed.
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Acknowledgements
This work is supported by the SAREPTA (Safety, autonomy, remote control and operations of industrial transport systems) project, which is financed by Norwegian Research Council with Grant No. 267860.
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Li, J., Zhang, J., Kaloudi, N. (2018). Could We Issue Driving Licenses to Autonomous Vehicles?. In: Gallina, B., Skavhaug, A., Schoitsch, E., Bitsch, F. (eds) Computer Safety, Reliability, and Security. SAFECOMP 2018. Lecture Notes in Computer Science(), vol 11094. Springer, Cham. https://doi.org/10.1007/978-3-319-99229-7_41
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DOI: https://doi.org/10.1007/978-3-319-99229-7_41
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