CAF SIGNALLING HAS BEEN WORKING IN CV&AI BASED RAILWAY SIGNAL DETECTOR/IDENTIFIER TECHNIQUES.
CAF Signalling already has started exploring (developing and testing) computer vision (CV) and artificial intelligence (AI) enhanced technologies for fully autonomous train operation (visual odometry, automatic object and traffic signal detection and identification, rolling stock automatic coupling…) in order to offer to its clients, the benefits of operation cost reduction, railway products life-cycles enlargement and safety increase.
CV&AI technologies are facing up different Validation and Verification (V&V) challenges due to they are based on non-deterministic algorithms. All AI-enhanced algorithm must to V&V under diverse scenarios in order to get certified. However, it is not easy to collect a real database containing different real scenarios to validate computer vision-based AI techniques. In other to conduct a research in this field, CAF Signalling joined VALU3S project consortium
The ECSEL JU project VALU3S aims to evaluate the state-of-the-art V&V methods and tools, and design a multi-domain framework to create a clear structure around the components and elements needed to conduct the V&V process. The main expected benefit of the framework is to reduce time and cost needed to verify and validate automated systems with respect to safety, cyber-security, and privacy requirements. This is done through identification and classification of evaluation methods, tools, environments and concepts for V&V of automated systems with respect to the mentioned requirements.
CAF Signalling has been working in CV&AI based railway signal detector/identifier techniques:
- light signals (green, red, orange),
- static speed restrictions panels,
- platform stopping point signals,
- platform proximity signals…
Although, the resulting models show accurate performances in nominal scenarios, they must be tested in higher variety of situations, extreme conditions and hazard situations in order to consider them really validated and vitrificated.
CAF Signalling will use the VALU3S V&V approach on AI-enabled verification and validation processes to simulate in virtual environment all possible scenarios, especially those scenarios that are unprovable (not real imagery database to test them) but critical from a safety point of view (i.e. people crossing railways, reduce visibility due meteorological conditions…).
VALU3S project has received funding from the ECSEL Joint Undertaking (JU) under grant agreement No 876852. The JU receives support from the European Union’s Horizon 2020 research and innovation programme and Austria, Czech Republic, Germany, Ireland, Italy, Portugal, Spain, Sweden, Turkey.