Certified Control for Train Sign Classification

• URL: http://arxiv.org/abs/2311.09778v1
• Date: Thu, 16 Nov 2023 11:02:10 GMT
• Title: Certified Control for Train Sign Classification
• Authors: Jan Ro{\ss}bach (Heinrich-Heine-Universit\"at D\"usseldorf), Michael Leuschel (Heinrich-Heine-Universit\"at D\"usseldorf)
• Abstract summary: The KI-LOK research project is involved in developing new methods for certifying such AI-based systems. Here we explore the utility of a certified control architecture for a runtime monitor that prevents false positive detection of traffic signs.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: There is considerable industrial interest in integrating AI techniques into railway systems, notably for fully autonomous train systems. The KI-LOK research project is involved in developing new methods for certifying such AI-based systems. Here we explore the utility of a certified control architecture for a runtime monitor that prevents false positive detection of traffic signs in an AI-based perception system. The monitor uses classical computer vision algorithms to check if the signs -- detected by an AI object detection model -- fit predefined specifications. We provide such specifications for some critical signs and integrate a Python prototype of the monitor with a popular object detection model to measure relevant performance metrics on generated data. Our initial results are promising, achieving considerable precision gains with only minor recall reduction; however, further investigation into generalization possibilities will be necessary.

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