| 1. |
- Besinovic, Nikola, et al.
(författare)
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Artificial Intelligence in Railway Transport : Taxonomy, Regulations, and Applications
- 2022
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Ingår i: IEEE transactions on intelligent transportation systems (Print). - : IEEE. - 1524-9050 .- 1558-0016. ; 23:9, s. 14011-14024
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Tidskriftsartikel (refereegranskat)abstract
- Artificial Intelligence (AI) is becoming pervasive in most engineering domains, and railway transport is no exception. However, due to the plethora of different new terms and meanings associated with them, there is a risk that railway practitioners, as several other categories, will get lost in those ambiguities and fuzzy boundaries, and hence fail to catch the real opportunities and potential of machine learning, artificial vision, and big data analytics, just to name a few of the most promising approaches connected to AI. The scope of this paper is to introduce the basic concepts and possible applications of AI to railway academics and practitioners. To that aim, this paper presents a structured taxonomy to guide researchers and practitioners to understand AI techniques, research fields, disciplines, and applications, both in general terms and in close connection with railway applications such as autonomous driving, maintenance, and traffic management. The important aspects of ethics and explainability of AI in railways are also introduced. The connection between AI concepts and railway subdomains has been supported by relevant research addressing existing and planned applications in order to provide some pointers to promising directions.
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| 2. |
- De Donato, Lorenzo, et al.
(författare)
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Artificial intelligence in railways : current applications, challenges, and ongoing research
- 2023
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Ingår i: Handbook on Artificial Intelligence and Transport. - : Edward Elgar Publishing. - 9781803929538 - 9781803929545 ; , s. 249-283
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Bokkapitel (refereegranskat)abstract
- This chapter presents applications, challenges, and opportunities for the integration of artificial intelligence in rail transport, based on the current results of the European project Roadmaps for AI integration in the rail sector (RAILS). Past and ongoing research directions are briefly outlined, and then the regulatory landscape is presented as well as the main barriers to overcome. Some technical aspects are addressed to provide some valuable references, and a high-level description of ongoing research work is given, spanning from innovative studies on smart maintenance, collision avoidance, delay prediction, and incident attribution analysis to visionary scenarios such as intelligent control and virtual coupling.
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| 3. |
- De Donato, Lorenzo, et al.
(författare)
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Artificial intelligence in railways : Current applications, challenges, and ongoing research
- 2023
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Ingår i: Handbook on Artificial Intelligence and Transport. - : Edward Elgar Publishing. - 9781803929545 - 9781803929538 ; , s. 249-283
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Bokkapitel (refereegranskat)abstract
- This chapter presents applications, challenges, and opportunities for the integration of artificial intelligence in rail transport, based on the current results of the European project Roadmaps for AI integration in the rail sector (RAILS). Past and ongoing research directions are briefly outlined, and then the regulatory landscape is presented as well as the main barriers to overcome. Some technical aspects are addressed to provide some valuable references, and a high-level description of ongoing research work is given, spanning from innovative studies on smart maintenance, collision avoidance, delay prediction, and incident attribution analysis to visionary scenarios such as intelligent control and virtual coupling.
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| 4. |
- De Donato, Lorenzo, et al.
(författare)
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Intelligent detection of warning bells at level crossings through deep transfer learning for smarter railway maintenance
- 2023
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Ingår i: Engineering applications of artificial intelligence. - : Elsevier Ltd. - 0952-1976 .- 1873-6769. ; 123
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Tidskriftsartikel (refereegranskat)abstract
- Level Crossings are among the most critical railway assets, concerning both the risk of accidents and their maintainability, due to intersections with promiscuous traffic and difficulties in remotely monitoring their health status. Failures can be originated from several factors, including malfunctions in the bar mechanisms and warning devices, such as light signals and bells. This paper focuses on the intelligent detection of anomalies in warning bells through non-intrusive acoustic monitoring by: (1) introducing a new concept for autonomous monitoring of level crossings; (2) generating and sharing a specific dataset collecting relevant audio signals from publicly available audio recordings; (3) implementing and evaluating a solution combining deep learning and transfer learning for warning bell detection. The results show a high accuracy in detecting anomalies and suggest viability of the approach in real-world applications, especially where network cameras with on-board microphones are installed for multi-purpose level crossing surveillance.
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| 5. |
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| 6. |
- Dirnfeld, Ruth, et al.
(författare)
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Low-Power Wide-Area Networks in Intelligent Transportation : Review and Opportunities for Smart-Railways
- 2020
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Ingår i: 2020 IEEE 23rd International Conference on Intelligent Transportation Systems, ITSC 2020. - : IEEE. - 9781728141497 - 9781728141503 ; , s. 1-7
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Konferensbidrag (refereegranskat)abstract
- Technology development in the field of the Internet of Things (IoT) and more specifically in Low-Power Wide-Area Networks (LPWANs) has enabled a whole set of new applications in several fields of Intelligent Transportation Systems. Among all, smart-railways represents one of the most challenging scenarios, due to its wide geographical distribution and strict energy-awareness. This paper aims to provide an overview of the state-of-the-art in LPWAN, with a focus on intelligent transportation. This study is part of the RAILS (Roadmaps for Artificial Intelligence integration in the raiL Sector) research project, funded by the European Union under the Shift2Rail Joint Undertaking. As a first step to meet its objectives, RAILS surveys the current state of development of technology enablers for smart-railways considering possible technology transfer from other sectors. To that aim, IoT and LPWAN technologies appear as very promising for cost-effective remote surveillance, monitoring and control over large geographical areas, by collecting data for several sensing applications (e.g., predictive condition-based maintenance, security early warning and situation awareness, etc.) even in situations where power supply is limited (e.g., where solar panels are employed) or absent (e.g., installation on-board freight cars). © 2020 IEEE.
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| 7. |
- Donato, Lorenzo De, et al.
(författare)
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A Survey on Audio-Video Based Defect Detection Through Deep Learning in Railway Maintenance
- 2022
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Ingår i: IEEE Access. - : IEEE. - 2169-3536. ; 10, s. 65376-65400
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Tidskriftsartikel (refereegranskat)abstract
- Within Artificial Intelligence, Deep Learning (DL) represents a paradigm that has been showing unprecedented performance in image and audio processing by supporting or even replacing humans in defect and anomaly detection. The railway sector is expected to benefit from DL applications, especially in predictive maintenance applications, where smart audio and video sensors can be leveraged yet kept distinct from safety-critical functions. Such separation is crucial, as it allows for improving system dependability with no impact on its safety certification. This is further supported by the development of DL in other transportation domains, such as automotive and avionics, opening for knowledge transfer opportunities and highlighting the potential of such a paradigm in railways. In order to summarize the recent state-of-the-art while inquiring about future opportunities, this paper reviews DL approaches for the analysis of data generated by acoustic and visual sensors in railway maintenance applications that have been published until August 31st, 2021. In this paper, the current state of the research is investigated and evaluated using a structured and systematic method, in order to highlight promising approaches and successful applications, as well as to identify available datasets, current limitations, open issues, challenges, and recommendations about future research directions.
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| 8. |
- Flammini, Francesco, Senior Lecturer, 1978-, et al.
(författare)
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A Petri Net pattern-oriented approach for the design of physical protection systems
- 2014
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Ingår i: Computer Safety, Reliability, and Security. SAFECOMP 2014. - Cham : Springer. - 9783319105055 ; , s. 230-245
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Konferensbidrag (refereegranskat)abstract
- The design of complex Physical Protection Systems (PPSs) still raises some challenges despite the high number of technologies for smart surveillance. One reason is the lack of effective methodologies able to support the PPS designer in evaluating the effectiveness of the system on varying design choices. Indeed, an estimation of the system vulnerability should be performed in the early phases of the PPS design. This paper introduces a model-based methodology for the quantitative estimation of the vulnerability of a PPS. The proposed methodology clearly defines a compositional approach which takes advantage from the usage of predefined patterns for the creation of vulnerability models. In particular, the paper proposes some Petri Net patterns able to capture the behavioural aspects of several assets and actors involved in attacking/defending scenarios. © 2014 Springer International Publishing.
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| 9. |
- Flammini, Francesco, Senior Lecturer, 1978-, et al.
(författare)
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Compositional modeling of railway Virtual Coupling with Stochastic Activity Networks
- 2021
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Ingår i: Formal Aspects of Computing. - : Springer. - 0934-5043 .- 1433-299X. ; 33, s. 989-1007
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Tidskriftsartikel (refereegranskat)abstract
- The current travel demand in railways requires the adoption of novel approaches and technologies in order to increase network capacity. Virtual Coupling is considered one of the most innovative solutions to increase railway capacity by drastically reducing train headway. The aim of this paper is to provide an approach to investigate the potential of Virtual Coupling in railways by composing stochastic activity networks model templates. The paper starts describing the Virtual Coupling paradigm with a focus on standard European railway traffic controllers. Based on stochastic activity network model templates, we provide an approach to perform quantitative evaluation of capacity increase in reference Virtual Coupling scenarios. The approach can be used to estimate system capacity over a modelled track portion, accounting for the scheduled service as well as possible failures. Due to its modularity, the approach can be extended towards the inclusion of safety model components. The contribution of this paper is a preliminary result of the PERFORMINGRAIL (PERformance-based Formal modelling and Optimal tRaffic Management for movING-block RAILway signalling) project funded by the European Shift2Rail Joint Undertaking.
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| 10. |
- Flammini, Francesco, Senior Lecturer, 1978-, et al.
(författare)
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Model-driven V&V processes for computer based control systems : A unifying perspective
- 2012
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Ingår i: Leveraging Applications of Formal Methods, Verification and Validation. Applications and Case Studies. ISoLA 2012. - Berlin, Heidelberg : Springer. - 9783642340314 ; , s. 190-204
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Konferensbidrag (refereegranskat)abstract
- A recent trend in software engineering is to support the development process by providing flexible tool chains allowing for effective Model-Driven approaches. These solutions are very appealing in industrial settings since they enable the creation of development and verification processes, enhancing abstraction and reuse, and hence improving productivity. This paper addresses advantages and challenges in extending Model-Driven approaches to system engineering and specifically to verification and validation (V&V) of critical computer-based systems. Specifically, the paper highlights the needs for real-world industrial contexts and proposes the definition of a unifying Model-Driven process for V&V of functional and non-functional system properties. Some enabling techniques which aim at improving the reuse of Model-Driven artifacts are addressed to deal with process scalability and effectiveness. Two sample applications are described for ERTMS/ETCS signalling system in order to show the advantages of the approach: formal modeling for performance evaluation of message delivery between train and track controllers and test case generation for the verification of functional requirements of trains outdistancing. © 2012 Springer-Verlag.
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