| 1. |
- Besinovic, Nikola, et al.
(author)
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Artificial Intelligence in Railway Transport : Taxonomy, Regulations, and Applications
- 2022
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In: IEEE transactions on intelligent transportation systems (Print). - : IEEE. - 1524-9050 .- 1558-0016. ; 23:9, s. 14011-14024
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Journal article (peer-reviewed)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.
(author)
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Artificial intelligence in railways : Current applications, challenges, and ongoing research
- 2023
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In: Handbook on Artificial Intelligence and Transport. - : Edward Elgar Publishing. - 9781803929545 - 9781803929538 ; , s. 249-283
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Book chapter (peer-reviewed)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.
(author)
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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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In: Engineering applications of artificial intelligence. - : Elsevier Ltd. - 0952-1976 .- 1873-6769. ; 123
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Journal article (peer-reviewed)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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| 4. |
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| 5. |
- Dirnfeld, Ruth, et al.
(author)
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Low-Power Wide-Area Networks in Intelligent Transportation : Review and Opportunities for Smart-Railways
- 2020
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In: 2020 IEEE 23rd International Conference on Intelligent Transportation Systems, ITSC 2020. - : IEEE. - 9781728141497 - 9781728141503 ; , s. 1-7
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Conference paper (peer-reviewed)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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| 6. |
- Donato, Lorenzo De, et al.
(author)
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A Survey on Audio-Video Based Defect Detection Through Deep Learning in Railway Maintenance
- 2022
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In: IEEE Access. - : IEEE. - 2169-3536. ; 10, s. 65376-65400
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Journal article (peer-reviewed)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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| 7. |
- Flammini, Francesco, Senior Lecturer, 1978-, et al.
(author)
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A Petri Net pattern-oriented approach for the design of physical protection systems
- 2014
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In: Computer Safety, Reliability, and Security. SAFECOMP 2014. - Cham : Springer. - 9783319105055 ; , s. 230-245
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Conference paper (peer-reviewed)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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| 8. |
- Flammini, Francesco, Senior Lecturer, 1978-, et al.
(author)
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Compositional modeling of railway Virtual Coupling with Stochastic Activity Networks
- 2021
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In: Formal Aspects of Computing. - : Springer. - 0934-5043 .- 1433-299X. ; 33, s. 989-1007
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Journal article (peer-reviewed)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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| 9. |
- Flammini, Francesco, Senior Lecturer, 1978-, et al.
(author)
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Model-driven V&V processes for computer based control systems : A unifying perspective
- 2012
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In: 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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Conference paper (peer-reviewed)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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| 10. |
- Flammini, Francesco, Senior Lecturer, 1978-, et al.
(author)
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Safety integrity through self-adaptation for multi-sensor event detection : Methodology and case-study
- 2020
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In: Future Generation Computer Systems. - : Elsevier. - 0167-739X .- 1872-7115. ; 112, s. 965-981
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Journal article (peer-reviewed)abstract
- Traditional safety-critical systems are engineered in a way to be predictable in all operating conditions. They are common in industrial automation and transport applications where uncertainties (e.g., fault occurrence rates) can be modeled and precisely evaluated. Furthermore, they use high-cost hardware components to increase system reliability. On the contrary, future systems are increasingly required to be "smart"(or "intelligent") that is to adapt to new scenarios, learn and react to unknown situations, possibly using low-cost hardware components. In order to move a step forward to fulfilling those new expectations, in this paper we address run-time stochastic evaluation of quantitative safety targets, like hazard rate, in self-adaptive event detection systems by using Bayesian Networks and their extensions. Self-adaptation allows changing correlation schemes on diverse detectors based on their reputation, which is continuously updated to account for performance degradation as well as modifications in environmental conditions. To that aim, we introduce a specific methodology and show its application to a case-study of vehicle detection with multiple sensors for which a real-world data-set is available from a previous study. Besides providing a proof-of-concept of our approach, the results of this paper pave the way to the introduction of new paradigms in the dynamic safety assessment of smart systems. (c) 2020 Elsevier B.V. All rights reserved.
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| 11. |
- Flammini, Francesco, Senior Lecturer, 1978-, et al.
(author)
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Towards Railway Virtual Coupling
- 2018
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In: 2018 IEEE International Conference on Electrical Systems for Aircraft, Railway, Ship Propulsion and Road Vehicles & International Transportation Electrification Conference (ESARS-ITEC). - : IEEE. - 9781538641927
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Conference paper (peer-reviewed)
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| 12. |
- Flammini, Francesco, Senior Lecturer, 1978-, et al.
(author)
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Using Bayesian Networks to evaluate the trustworthiness of '2 out of 3' decision fusion mechanisms in multi-sensor applications
- 2015
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In: IFAC-PapersOnLine. - : Elsevier BV. - 2405-8963. ; , s. 682-687
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Conference paper (peer-reviewed)abstract
- The use of smart-sensors to recognize automatically complex situations (anomalous behaviors, physical security threats, etc.) requires 'intelligent' methods to improve the trustworthiness of automatic decisions. Voting and consensus mechanisms can be employed whether supported by probabilistic formalisms to correlate event occurrence, to merge local events and to estimate the likelihood of overall decisions. This paper presents the results of a quantitative comparison of three different voting schemes based on Bayesian Networks. These models present a growing complexity and they are able to provide a trustworthiness estimation based on single nodes detection reliability in terms of false alarm probabilities. © 2015, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.
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| 13. |
- Marrone, Stefano, et al.
(author)
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On synergies of cyber and physical security modelling in vulnerability assessment of railway systems
- 2015
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In: Computers & electrical engineering. - : Elsevier. - 0045-7906 .- 1879-0755. ; 47, s. 275-285
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Journal article (peer-reviewed)abstract
- The multifaceted nature of cyber-physical systems needs holistic study methods to detect essential aspects and interrelations among physical and cyber components. Like the systems themselves, security threats feature both cyber and physical elements. Although to apply divide et impera approaches helps handling system complexity, to consider just one aspect at a time does not provide adequate risk awareness and hence does not allow to design the most appropriate countermeasures. To support this claim, in this paper we provide a joint application of two model-driven techniques for physical and cyber-security evaluation. We apply two UML profiles, namely SecAM (for cyber-security) and CIP-VAM (for physical security), in combination. In such a way, we demonstrate the synergy between both profiles and the need for their tighter integration in the context of a reference case study from the railway domain. Graphical abstract © 2015 Elsevier Ltd.
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| 14. |
- Marrone, Stefano, et al.
(author)
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Towards Model-Driven V&V assessment of railway control systems
- 2014
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In: International Journal on Software Tools for Technology Transfer. - : Springer. - 1433-2779 .- 1433-2787. ; 16:6, s. 669-683
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Journal article (peer-reviewed)abstract
- Verification and Validation (V&V) activities aiming at certifying railway controllers are among the most critical and time-consuming in system development life cycle. As such, they would greatly benefit from novel approaches enabling both automation and traceability for assessment purposes. While several formal and Model-Based approaches have been proposed in the scientific literature, some of which are successfully employed in industrial settings, we are still far from an integrated and unified methodology which allows guiding design choices, minimizing the chances of failures/non-compliances, and considerably reducing the overall assessment effort. To address these issues, this paper describes a Model-Driven Engineering approach which is very promising to tackle the aforementioned challenges. In fact, the usage of appropriate Unified Modeling Language profiles featuring system analysis and test case specification capabilities, together with tool chains for model transformations and analysis, seems a viable way to allow end-users to concentrate on high-level holistic models and specification of non-functional requirements (i.e., dependability) and support the automation of the V&V process. We show, through a case study belonging to the railway signalling domain, how the approach is effective in supporting activities like system testing and availability evaluation. © 2014, Springer-Verlag Berlin Heidelberg.
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| 15. |
- Meo, Carlo Di, et al.
(author)
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ERTMS/ETCS Virtual Coupling : Proof of Concept and Numerical Analysis
- 2019
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In: IEEE transactions on intelligent transportation systems (Print). - : IEEE. - 1524-9050 .- 1558-0016. ; 21:6, s. 2545-2556
-
Journal article (peer-reviewed)abstract
- Railway infrastructure operators need to push their network capacity up to their limits in high-traffic corridors. Virtual coupling is considered among the most relevant innovations to be studied within the European Horizon 2020 Shift2Rail Joint Undertaking as it can drastically reduce headways and thus increase the line capacity by allowing to dynamically connect two or more trains in a single convoy. This paper provides a proof of concept of Virtual coupling by introducing a specific operating mode within the European rail traffic management system/European train control system (ERTMS/ETCS) standard specification, and by defining a coupling control algorithm accounting for time-varying delays affecting the communication links. To that aim, we define one ploy to enrich the ERTMS/ETCS with Virtual coupling without changing its working principles and we borrow a numerical analysis methodology used to study platooning in the automotive field. The numerical analysis is also provided to support the proof of concept with quantitative results in a case-study simulation scenario.
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| 16. |
- Rajabli, Nijat, et al.
(author)
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Software Verification and Validation of Safe Autonomous Cars : A Systematic Literature Review
- 2021
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In: IEEE Access. - : IEEE. - 2169-3536. ; 9, s. 4797-4819
-
Research review (peer-reviewed)abstract
- Autonomous, or self-driving, cars are emerging as the solution to several problems primarily caused by humans on roads, such as accidents and traffic congestion. However, those benefits come with great challenges in the verification and validation (V&V) for safety assessment. In fact, due to the possibly unpredictable nature of Artificial Intelligence (AI), its use in autonomous cars creates concerns that need to be addressed using appropriate V&V processes that can address trustworthy AI and safe autonomy. In this study, the relevant research literature in recent years has been systematically reviewed and classified in order to investigate the state-of-the-art in the software V&V of autonomous cars. By appropriate criteria, a subset of primary studies has been selected for more in-depth analysis. The first part of the review addresses certification issues against reference standards, challenges in assessing machine learning, as well as general V&V methodologies. The second part investigates more specific approaches, including simulation environments and mutation testing, corner cases and adversarial examples, fault injection, software safety cages, techniques for cyber-physical systems, and formal methods. Relevant approaches and related tools have been discussed and compared in order to highlight open issues and opportunities.
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| 17. |
- Schlick, Rupert, et al.
(author)
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A proposal of an example and experiments repository to foster industrial adoption of formal methods
- 2018
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In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). - Cham : Springer Verlag. - 9783030034269 ; , s. 249-272
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Conference paper (peer-reviewed)abstract
- Formal methods (in a broad sense) have been around almost since the beginning of computer science. Nonetheless, there is a perception in the formal methods community that take-up by industry is low considering the potential benefits. We take a look at possible reasons and give candidate explanations for this effect. To address the issue, we propose a repository of industry-relevant example problems with an accompanying open data storage for experiment results in order to document, disseminate and compare exemplary solutions from formal model based methods. This would allow potential users from industry to better understand the available solutions and to more easily select and adopt a formal method that fits their needs. At the same time, it would foster the adoption of open data and good scientific practice in this research field. © Springer Nature Switzerland AG 2018.
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