Transport Transitions: Advancing Sustainable and Inclusive Mobility

Table of Contents

1. Digital Transition

   1. Frontmatter

   2. Boosting Public Transport Through Innovative IT Solutions that Match the Needs and Expectations of All Stakeholders

      • Open Access

      Mehdi Zarehparast Malekzadeh, Francisco Enrique Santarremigia, Gemma Dolores Molero, Ashwani Kumar Malviya, Aditya Kapoor, Rosa Arroyo, Tomás Ruiz Sánchez

      Abstract

      Considering the significant growth rate of population in the urban area, public transport has become vital to urban living. It has become unavoidable to promote the culture of using Mobility as a Service (MaaS) among travellers to address climatic challenges, especially the global warming phenomenon. To encourage the use of public transport, It is important to introduce innovative IT solutions to the ecosystem of TSPs (Transport Service Providers) backed by an in-depth impact analysis to meet the expectations and the needs of the TSPs and the travellers. This work introduces an assessment methodology to calculate the “Effectiveness” of the innovative IT solutions for TSPs and travellers through a series of data analysis methods using the Bayesian Network, Regression analysis, and ANOVA tests. The assessment is based on two types of quantitative datasets: operational KPIs (Key Performance Indicators) and USI (User Satisfaction Index) surveys to evaluate how the expectations and needs of travellers with different socio-demographic profiles (by gender, age, income level, and impairments) are met by these IT solutions. This methodology is the foundation for the IP4MaaS Project supported by the Europe’s Rail Joint Undertaking. The paper presents the results of applying this methodology to data collected in six sites (Athens, Barcelona, Liberec, Osijek, Padua, and Warsaw). The presented methodology will be helpful to the IT developers and TSPs for assessing their own IT solutions. The findings will help researchers, policymakers, and others in the transport sector to assess public transport services. This assessment methodology is scalable to other demo sites and datasets.

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   3. Train Dispatcher in the Cloud – Digitalising Track Warrant Control for Safe Train Operations in Structurally Transforming Areas

      • Open Access

      Lukas Pirl, Heiko Herholz, Dirk Friedenberger, Arne Boockmeyer, Andreas Polze, Birgit Milius

      Abstract

      To mitigate the adverse effects of climate change, greenhouse gas emissions need to be minimised. The FlexiDug project investigates sustainable transport perspectives for structurally transforming areas where coal mining phases out. This work presents a safe, economical, and extendable approach on reusing industrial railways for passenger transport. We have digitalised the Zugleitbetrieb, a mode of operation that requires no trackside equipment. Our Train Dispatcher in the Cloud (German Zugleiter in der Cloud, henceforth ZLiC) has been developed ontology- and model-based. It also takes a railway network model as input, e.g., for the generic interlocking logic. Speech to text, naturallanguage understanding, and text to speech recreate the established speech interface towards conductors. A state machine ensures the prescribed voice procedure. Custom voice-activated recording allows using COTS radio devices. ZLiC has been evaluated successfully in simulations and field tests. We plan further improvements, evaluations, and a risk assessment.

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   4. The Missing Piece to the Puzzle: Advancing Train Planning for a Digital Great British Railway

      • Open Access

      Nadia Hoodbhoy, Gemma Nicholson, Heather Steele, Nicola Furness, Timothy James, Rob Goverde, Nikola Besinovic

      Abstract

      Along with much of Europe and the global trend towards in-cab signalling, Great Britain (GB) rail is transitioning to Radio-based European Train Control System (ETCS). In collaboration with several universities and research partners, Network Rail have undertaken a programme of R&D to build on the opportunities that Radio-based ETCS offers, including the move towards automatic train operation (ATO), and integrated, centralised traffic management systems that maximise the potential in capacity, performance and energy efficiency for passenger and freight customers. Bringing the train planning and timetabling capabilities into the modernised, data driven, information rich world is a significant puzzle piece of turning opportunities offered by the signalling and control technologies into the day-to-day operations of the railway. This paper covers the research carried out into the characteristics of a radio-based ETCS railway that can be analysed for a goal-based state of the art train planning capability. It considers the advancement of tools, techniques, processes and skills that are required to plan, operate and regulate the railway through automatic train operations and future traffic management systems, ultimately harmonising planning, real-time operations and post-operations performance analysis.

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   5. A Real Time Decision-Support Tool for Traffic Management

      • Open Access

      Charles-Frédérick Amaudruz, Valentina Pozzoli

      Abstract

      SNCF Voyageurs/TGV-Intercités operates over 800 highspeed trains (TGVs) per day in France. The system can be highly tense during peaks with up to 13 trains per hour on the same track section. Thus, minor delays can affect operations, especially for long-distance trains. Supervision of the system and real-time rescheduling are difficult tasks given the complexity of the rail network and the cohabitation of different train services.

      In this work, we present a real-time decision-support tool providing estimations on the arrival time of trains at each station and at destination and helping comparisons between rescheduling choices.

      The estimations of future delays have a focus on explainability, with information on the causes of the delay and on the possibility to recover the delay. The operators can use the tool to test different rescheduling choices and see the impact of each scenario on the traffic, helping them deciding the actions to take to minimize delays. The predictions of arrival times of trains are based on a macroscopic discrete event simulator, coupling the theoretical timetabling with real-time information on the trains’ positions.

      Arrival times are displayed on the interface of the developed web application, where the user can interact with the simulation by adding information and comparing different disruption management scenarios.

      The tool has been tested with success in an operational environment. The operators gave positive feedback on the tool, underlying its capacity to give them more insight on the expected delay evaluations and on potential conflicts. The information displayed was judged relevant and reliable. This is confirmed by our analysis of the quality of the simulation.

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   6. Motorway Traffic Flow Optimization: From Theory to Practice

      • Open Access

      Robert Corbally, Erik Giesen Loo, Lewis Feely, Andrew O’Sullivan

      Abstract

      Variable speed limits (VSL) are currently being introduced on Ireland’s M50 motorway on a phased basis. To manage general everyday congestion associated with peak-period traffic, proactive speed management plans have been developed to allow control room operators to initiate speed reductions to optimize traffic flows and reduce the impact of traffic flow breakdown. The national roads authority in Ireland, Transport Infrastructure Ireland (TII), collects significant levels of data from the M50, and this paper outlines how the application of traffic-flow theory to the measured data has been used to identify when certain sections of the road are approaching capacity. This has enabled the provision of real-time data-driven alerts to control room operators, to identify when proactive speed management plans should be initiated. The measured data is then used to assess the effectiveness of the VSL plans, and it is shown that improvements in throughput are being achieved, along with a reduction in congestion and shockwave behavior. The findings of this study will ultimately inform the automation of proactive speed management plans on the M50.

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   7. Achievements and Future Priorities of Artificial Intelligence in Transport Systems

      • Open Access

      Elodie Petrozziello, Alessandro Marotta, Marcin Stępniak, Ilias Cheimariotis, Chiara Lodi

      Abstract

      This paper aims at defining future research priorities for artificial intelligence (AI) in transport systems. The point of the departure is the state of the art regarding the application of AI in transport combined with the EU policy needs and the assessment of the recent European projects. The paper presents an overview of the potential benefits that the deployment of AI has for transport. Special focus is put on results of European projects funded within Horizon 2020 Framework Programme. The main achievements of the research have shown that AI can help in the optimisation of applications within the transport means. It can also aid public authorities in improving the overall infrastructure thanks to data gathering and first screening. Further, the deployment of AI is a source of profitable opportunities for various sectors like automotive, software, waterborne, aviation, passenger and freight transport. The final aim of these projects is to boost efficiency, sustainability, and safety by having a human centric AI, aware of every situation it is facing and able of taking prompt decisions. The paper concludes by discussing selected cross-cutting concerns regarding the application of AI in the transport sector. They include definition of software updates for autonomous vehicles’ algorithms, the need for liability regimes and the issue of data scarcity.

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   8. Gamification of Early-Stage Planning, Participation and Education in Urban Mobility: The MobileCityGame

      • Open Access

      Claus Doll, Susanne Bieker, Dorien Duffner-Korbee, Konstantin Krauss

      Abstract

      Strategic planning is of utmost importance for cities to achieve climate targets, while maintaining citizen satisfaction and meeting financial constraints. However, large assessment models are often costly and too complex for smaller cities. Thus, we designed a simplified, intuitive and dynamic transport simulation tool and serious game MobileCity to run on mobile devices for strategy processes, participation and teaching. A real transportation model running on local devices allows the free combination of different mobility interventions and shows dynamic indicators for climate, finances and livability, while offering an intuitive interface with supporting information. We currently extend the free iOS and Android demonstrator for Karlsruhe (Germany) and transfer it to European cities within the DUT project “CarGoNE-City”. In this paper, we present its core functionalities and features, before assessing scenarios and concluding on lessons learned and applications. Our main messages from applying the MobileCity-App are: the timing of interventions matters for all output indicators and a sound combination of push and pull measures helps meeting climate, livability and financial targets without going into extremes.

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   9. Can European Shipyards Be Smarter? A Proposal from the SEUS Project

      • Open Access

      Henrique M. Gaspar, Ícaro A. Fonseca, Ludmila Sepällä, Herbert Koelman, José Jorge Garcia Agis

      Abstract

      Improving the efficiency and competitiveness of European Shipyards is one of the priorities of the HORIZON program, funded by the European Commission. The proper use of computational tools can accelerate this improvement, given that the shipbuilding industry faces a digitalization gap compared to other manufacturing industries. Our proposal is based on the ongoing Smart European Shipyard (SEUS) project, which aims to bridge the digital gap, focusing on integrating available computational tools, and converging into a new platform that enables faster engineering and technical management. This platform intends to provide a holistic approach to product lifecycle management (PLM) for shipbuilding, integrating existing and proven solutions in CAD/CAE with new data-driven technologies to handle shipbuilding knowledge efficiently. The paper presents a link between current challenges and possible ways to tackle them and a summary of the possible impacts this platform can achieve if adequately implemented. The paper closes with a call for peers to contribute to the discussion.

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   10. Smart Self-sensing Composite Marine Propeller: Increased Maintenance Efficiency Through Integrated Structural Health Monitoring Systems

       • Open Access

       Aldyandra Hami Seno, Dimitrios Fakis, Sadik Omairey, Akram Zitoun, Nithin Jayasree, Mihalis Kazilas, Maria Xenidou, Andreas Kalogirou, Kyriaki Tsirka, Alkiviadis Paipetis, Marion Larreur

       Abstract

       CoPropel is a Horizon Europe funded project which aims to develop marine propellers for cargo vessels that are more fuel and cost efficient to operate than their more common metallic counterparts. One of the areas the project aims to tackle is the maintenance aspect of marine propellers, which can be very cost intensive. This is due to the difficulty of inspection or maintenance since the components are underwater and quite significant in size, which may lead to the need for divers or dry-dock time. The way the project aims to address this is by taking advantage of the non-monolithic construction of the composite propeller to integrate a Structural Health Monitoring (SHM) system to monitor the strain, and subsequently infer the condition, of the propeller during operation without the need to stop for inspection. This paper explores the challenges encountered in the development of the SHM system, including: 1.) inspection requirements as set out by existing guidelines and regulations, 2.) sensor integration in the composite structure, 3.) data transmission from a rotating underwater component to a data acquisition system within the ship and 4.) usage of the acquired data for maintenance decision making. Feasible alternative systems are explored including Rayleigh Backscatter based Fibre Optic Systems (FOS) for distributed strain sensing as well as a strain gauge system with wireless underwater data transmission. Preliminary small scale underwater tests are conducted to evaluate the performance of the explored concepts under simulated operational conditions. Finally, we combine the strain data acquired from the SHM system with numerical models of the propeller through a multifidelity approach. The first aim is to create a better spatial distribution of the strain measurements across the propeller by fusing data from sensors covering a limited area, with strain data from numerical models that have better distribution across the propeller. The second goal is to provide digital twinning capability through the use of the numerical model to provide extrapolated estimates (calibrated by live sensor data) of maintenance requirements (i.e. remaining life) based on current and hypothetical operational profiles to better inform operators when making future operational decisions. Through the combination of the SHM system and digital twinning capabilities we provide increased data driven decision making capabilities to better improve operational efficiency and maintenance costs.

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   11. MAPSIA: Automatic Pavement Distress Detection for Optimal Road Maintenance Planning

       • Open Access

       Saúl Cano-Ortiz, Lara Lloret Iglesias, Pablo Martinez Ruiz del Árbol, Daniel Castro-Fresno, Pedro Lastra-González, Carlos Real-Gutiérrez, Eugenio Sainz-Ortiz

       Abstract

       An inadequate road maintenance planning coupled with funding constraints, traffic volume rising and lack of data, results in aging pavements with increased fuel consumption and diminished user safety as well as exorbitant corrective preservation costs. Assessing road conditions for pavement distress detection currently involves two approaches: human visual inspection, which is labour intensive and time-consuming, and the use of multipurpose pavement inspection vehicles. Notwithstanding, the latter is expensive to purchase, operate and maintain, which may pose challenges for departments of transportation with limited budgets. This project automates the process of recognizing superficial road defects with an innovative solution based on Artificial Intelligence, thereby adding significant value to road rehabilitation decision-making. Our low-cost image acquisition system collects thousands of geotagged road images. Then, multiple Deep Learning (DL) algorithms belonging to the YOLOv5 family are trained to establish a functional mapping between the inputs (raw images) and the outputs (defect location and type). Also, validation metrics are calculated in order to identify the optimal DL architecture. Subsequently, a rule-based postprocessing is devised for the finest model, with the goal of mitigating false positive detections. The enhanced model outputs are utilized to engineer a pavement condition index, which is integrated in our software.

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   12. Efficient Pavement Crack Monitoring for Road Life Cycle Management

       • Open Access

       Raquel Pena, Nuno C. Marques, Fátima A. Batista, João Manso, João Marcelino

       Abstract

       Road pavements are vital for transportation infrastructure, yet they deteriorate over time due to traffic loads and environmental factors, resulting in cracks and damage. This paper introduces an innovative method for crack detection on road pavements using digital imagery. Our approach incorporates geo-localization, annotates, characterizes, and quantifies crack severity. This empowers experts to monitor crack progression, a critical element in pavement management. The methodology allows for seamless result comparison and augments existing techniques, aiding in condition assessment and conservation strategy determination. Timely detection of cracks enables proactive maintenance, preventing structural degradation, and ensuring user safety and comfort. Leveraging deep learning and open-source frameworks like TensorFlow and QGIS, our approach automates road pavement image analysis and crack identification, providing a cost-effective, accessible solution for crack detection. This research offers significant advantages in resource efficiency and accessibility, especially in areas without regular manual inspections or dedicated vehicles, thereby enhancing road pavement monitoring and maintenance.

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   13. OMICRON. An Intelligent Road Asset Management Platform

       • Open Access

       Jose Solis-Hernandez, Concepcion Toribio-Diaz, Noemi Jimenez-Redondo, Mara van Welie, Ander Ansuategi, Federico di Gennaro

       Abstract

       The OMICRON project develops an Intelligent Road Asset Management Platform integrating a broad portfolio of area specific innovative technologies to enhance the construction, maintenance, renewal and upgrade of the European road network. The project improves the whole asset management pipeline focusing on four pillars: modular construction of bridges, road inspection digitalisation, predictive maintenance and smart execution of intervention actions.

       OMICRON’s Intelligent Platform enables the digitalisation and automation of a relevant portfolio of road management tasks which are still very labour intensive. Thereby, OMICRON aims to pave the way to the roads of the future, addressing the reduction of fatal accidents related to maintenance actions, the reduction of traffic disruptions, the reduction of maintenance costs, and the increase in road network capacity.

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   14. Geofencing to Accelerate Digital Transitions in Cities: Experiences and Findings from the GeoSence Project

       • Open Access

       Lillian Hansen, Sven-Thomas Graupner, Kristina Andersson, Anna Fjällström, Jacques Leonardi, Rodrigue Al Fahel

       Abstract

       Geofencing is a tool that offers innovative solutions to manage and control traffic, transport, and mobility. The technology enables cities to define digital zones and to create dynamic rules for mobility within these zones. Here we report on three geofencing use cases, their results and lessons learned that were conducted as part of the joint European project GeoSence. In the city of Gothenburg, the performance of a geofencing-based retro-fitted intelligent speed assistance system was tested and evaluated in 20 vehicles of publicly procured transport services to support drivers in complying with new speed regulations around schools. In Munich, geofencing was used to implement and enforce a new station-based parking regulation for shared e-scooters in the city’s old town. Thirdly, in Stockholm preconditions, processes and workflow for continuous changes and updating of the underlying digital geo-data bases were analysed to better understand institutional and practical challenges to implement geofencing-based digital transitions in future. Findings from the use cases and project accompanying surveys are evaluated regarding the general topics of transport management, including issues of data sharing and management, stakeholder involvement, technical & vehicle readiness, feasibility of technical platforms, as well as institutional problems related to governance, policies, resources and the acquiring of necessary competencies.

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   15. Digital Transformation in the Transportation Sector: Unleashing the Power of Data

       • Open Access

       Drew Waller, Andreas Galatoulas, Yuelin Liang, James Colclough, Stephen Lavelle, Lee Street, John Song, Suzanne Murtha

       Abstract

       The transportation sector is undergoing a profound transformation, utilizing digital technologies to move people and goods more efficiently. Data and analytics play a pivotal role as the core of digital transformation and insights-based decision making, as organizations are realizing the necessity of effectively leveraging their data assets. This paper discusses how advanced data analytics techniques, such as artificial intelligence, and solutions can be harnessed to embrace digital innovation and improve operations and services while respecting the transportation industry’s unique requirements regarding stakeholder engagement, user needs, supply chain, legacy systems, stringent safety and security regulations, and system interoperability. This discussion is built around project examples: a Digital Engineering Information Management solution for managing large and complex road construction programs; natural language processing on traffic incident data; a telematic assessment of fuel consumption and emissions from road traffic; and the predictive maintenance of transportation infrastructure. This paper concludes with the proposal of a systematic framework that encourages best practices, clarity, efficiency, and successful outcomes and value extraction from data analytics projects for the transportation sector.

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   16. Collaboratively Developing Mobility as a Service as a Digital Policy-Enabler

       • Open Access

       Oliver Coltman, John Bradburn, Melinda Matyas

       Abstract

       As a new digital tool, Mobility as a Service (MaaS) provides the opportunity for novel approaches in delivering policy outcomes when led by public authorities. Harnessing the opportunity offered by MaaS requires not only a behavioural, operational and commercial transition for public bodies, but also a digital transition. Whilst complex, this transition opens up opportunities. Collaborative digitalisation means recognising that participating actors and stakeholders can often have competing motivations and objectives, reflecting the complexity of delivering MaaS as a system of digital and commercial relationships. However, with the right behaviours and frameworks, all parties can align towards a common goal. This cannot be achieved by chance, but only through concerted and considered effort to develop a culture of collaboration. This paper explores the evolving collaborative delivery model being taken by the West of England Combined Authority in its digital transition to deliver a policy led, customer focussed MaaS solution.

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   17. MegaBITS: Greening Urban Mobility Through Smart Cycling

       • Open Access

       Ronald Jorna, Wim Dijkstra

       Abstract

       To achieve a 90% reduction in the transport sector’s greenhouse gas emissions by 2050, the North Sea Region has to move (among others) from fossil fuelled vehicles to cycling, especially in urban areas. All kinds of projects are initiated to contribute to this objective, each with their own objectives and means. The MegaBITS project, and its predecessor BITS, are aiming at greening the European transport system through the use of Intelligent Transport Systems (ITS) in the cycling domain. ITS can contribute to the attractiveness of cycling, by improving cycling safety, improving speed, improve convenience and comfort and by giving the cyclist a better experience. This paper highlights the results of the BITS project, shows the first results of the MegaBITS project and sheds a light on the prospects of smart cycling.

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   18. Privacy-Preserving and Passenger-Oriented Solutions for Air-Rail Multimodal Travels

       • Open Access

       Stefano Sebastio, Hubertus Wiese, Marco De Vincenzi, Ilaria Matteucci, Riccardo Orizio, Georgios Giantamidis, Shane Daly

       Abstract

       Nowadays passenger travels are more and more multimodal. Often advocated as the way to follow to strike a balance between sustainability and travel time, air-rail is a prominent example of multimodality. To accommodate the fast-growing business the travel and tourism industry is experiencing, operators are going through a continuous digital transformation including solutions based on wireless connectivity, smart-sensors, Internet of Things, and Artificial Intelligence. The goal is twofold: improving passenger processing and operations, and passenger experience. On the other hand, significant challenges to tackle and opportunities to unfold in terms of security, privacy, and optimization, are still only partially addressed. The EU H2020 E-CORRIDOR project develops a secure, collaborative, and confidential framework for information sharing and analysis. Solutions for the air-rail multimodal pilot seek to improve passenger experience, perform seamless authentication, enhance the cybersecurity posture of the transport operators, break down data silos existing among stakeholders, and better support Passenger with Reduced Mobility (PRM) and coordination among operators. This paper presents some of such solutions where privacy is the keystone.

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   19. Spatial Density to Supplement Factors Used for a Screen Line Analysis and Travel Demand Estimation

       • Open Access

       Florian Lammer, Martin Fellendorf

       Abstract

       Origin-destination (OD) matrices from floating phone data (FPD) are a valuable data source for screen line analysis. However, FPD does not contain any trip purpose information. To get additional information regarding the trip purpose distribution at a screen line, manual surveys with a huge sample size would be needed. Such surveys are very complex and expensive. Hence, they are rarely conducted in practice.

       This study aims to overcome these shortcomings and presents a novel approach for assigning trip purpose distributions to OD-matrices. Based on limited but geocoded survey data, spatial structural data and routing information trip purpose distributions can be mapped on OD-matrices from readily available FPD. By using k-means based clustering techniques the spatial structure is used as a link between FPD and survey data.

       The developed methodology was successfully applied to the Graz region in Austria, with approximately 300.000 residents and showed promising results. The derived trip purpose distributions were verified by utilising traditionally survey data. Therefore, this method is transferable and can be used as supplement to traffic volume screen line analysis to gain valuable planning information while keeping the survey effort and related costs to a minimum.

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   20. Collaborative Digitalisation and the Future of Networked Production: Exploring Decentralised Technical Intelligence in Supply Chains

       • Open Access

       Stefan Walter

       Abstract

       Networked production, supported by advanced logistics and supply chain processes, is crucial for companies to stay competitive and foster cooperation and integration of production resources. It replaces sequential processes with dynamic arrangements, presenting challenges like managing product variants, short life cycles, and process optimisation. Agility is vital for adapting to changes and natural disasters. Decentralised Technical Intelligence (DTI) is an approach that manages complexity and incentivises integrating new technologies in planning and manufacturing.

       DTI involves distributed and autonomous intelligence embedded in interconnected systems, where humans and machines collaborate to achieve common goals. Humans bring unique skills like creativity and intuition, complementing AI’s capabilities. DTI relies on a multi-agent architecture, enabling trust, interoperability, and data sharing for better decision-making and efficiency. The EU knowlEdge project exemplifies this by providing AI solutions that are distributed, secure, standardised, and collaborative, integrating cognitive technologies, data analytics, IoT and more.

       DTI’s human-centric design fosters a different quality of intelligence, leading to greater autonomy within multi-agent systems. To realise advanced networked production, a roadmap must be implemented, focusing on a vision, value promise, and development pathway. Europe can maintain its leadership in future networked production through this approach.

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   21. Processing Digital Railway Planning Documents for Early-Stage Simulations of Railway Networks

       • Open Access

       Arne Boockmeyer, Julian Baumann, Benedikt Schenkel, Clemens Tiedt, Dirk Friedenberger, Lukas Pirl, Andreas Polze

       Abstract

       The digitalization of the railway domain is a key enabler for more efficient railway operations matching the future needs of society. One part of this process is the digitalization of planning processes, replacing the use of paper-based plans with digital formats. Digital planning documents also open new possibilities, e.g., deriving representative simulation in early project stages. A commonly used simulator for such purposes is the Simulation of Urban Mobility (SUMO). To use the capabilities of SUMO, we are presenting a tool chain for unifying planning documents and generating simulation configurations from them. The core of this tool chain is the yaramo model, covering mainly the topology, geography, and the control command and signaling (CCS) infrastructure of the railway network. The tool chain consists of three major layers: Importers to support multiple data sources (such as PlanPro or OpenRailwayMap), processors to enrich the model, and exporters to support various consumers of the model. This leads to several applications, such as rail network performance evaluations and test automation for CSS infrastructure. Ultimately, our work aims to support the digitalization process of the railway domain, especially the digital planning and development of railway networks.

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   22. Interactive Tool for Strategic Planning in a Railway Environment

       • Open Access

       Paula Lopez-Arevalo, Jose Solis-Hernandez, Noemi Jimenez-Redondo, Thomas Fontville, Henk Samson

       Abstract

       An interactive tool for strategic planning is developed as part of the decision support and operational planning enhancements in the framework of the In2Smart2 project [1], working with Strukton Rail as the technology demonstrator.

       The tool objective is to assist workers which form part of the decision process of strategic planning to visualize and analyze information, providing insights and useful conclusions in an interactive and straightforward way. The tool scope is the optimization of resources and company availability analysis to obtain forecasted workload optimization, the reduction of idle times and mobilization of adequate volumes of extra (external) capacity among others. It can be applied to a long-time horizon and to a short one.

       The tool is implemented in Powe BI, elaborating methodologies and workflows for the implementation of the various interactive reports which support the decision-making and other managing and organizational tasks.

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   23. Artificial Intelligence (AI) System for Traffic Flows Monitoring. Evidences from the Interreg Mimosa Project

       • Open Access

       Denis Grasso, Giuseppe Luppino

       Abstract

       The traffic flows monitoring in a specific area is often an expansive and complicated activity for a public administration. Nevertheless, these data are fundamental for improving the urban and transport planning processes at local and regional levels. In the Italy-Croatia Interreg Mimosa project, an innovative opensource traffic flows monitoring system based on Artificial Intelligence (AI) was crated and tested. The collected results showed as the system is able to correctly recognize different typologies of vehicles (cars, bicycles, motorbikes, persons, light freight vehicles and heavy freights vehicles) using only open-source libraries. The aim is to provide to the decision makers new tools for the traffic monitoring and data-oriented decisions making on the topic of sustainable transport promotion. The Mimosa AI tool was published on GitHub and it is open access for all the interested public and private stakeholders. The paper presents the informatic architecture adopted, the key open-source AI tools used and it explores strengths and weaknesses related to the use of this AI tool.

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   24. Railway System Digital Twin: A Tool for Extended Enterprises to Perform Multimodal Transportation in a Decarbonization Context

       • Open Access

       Moussa Issa, Alexis Chartrain, Flavien Viguier, Bruno Landes, Gilles Dessagne, Noël Haddad, David R.C. Hill

       Abstract

       To achieve our long-term goal of doubling the modal share of freight transport by rail and develop multi-modality in transports in France, a fine control over the railway network management is required to better synchronize rail transport with other modes of transport e.g., cars, trucks, trams. The Digital Twin (DT) of the railway system and the extended enterprise are central concepts in our approach to answer this problem. Our method aims at giving access to our railway system's Digital Twin through a Service Oriented Architecture (SOA). This architectural choice facilitates seamless communication and interaction with our partners, fostering a dynamic exchange of information critical for effective multimodal transportation planning. This article describes our approach with a successful implementation of an initial version of our infrastructure Digital Twin, complemented by services designed to meet the diverse expectations of users. This milestone underscores our commitment to leveraging cutting-edge technology and collaborative frameworks to enhance railway management, promote sustainable transportation practices, and contribute significantly to the reduction of GHG (Greenhouse Gas) emissions. As we continue to refine and expand our Digital Twin capabilities, we remain dedicated to advancing the future of intelligent and eco-friendly transportation systems.

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   25. Sustainability and Circularity-Related Information Requirements for a Digital Product Passport for the Electric Vehicle Battery

       • Open Access

       Antonia Pohlmann, Katharina Berger, Julius Ott, Martin Popowicz, Josef-Peter Schöggl, Johann Bachler, Jakob Keler, Patrick Lamplmair, Rupert J. Baumgartner

       Abstract

       Digital Product Passports (DPPs) have increasingly gained attention as enablers of more transparent and traceable electric vehicle battery (EVB) value chains. The new EU Battery Regulation requires all EVBs to have a digital record until 2026 and defines sustainability/ circularity-related requirements to be included in such a digital battery passport (DBP). This study goes beyond the legal requirements by systematically investigating which type of information a DBP would need to contain to comprehensively support sustainability/circularity-related decision-making of value chain actors. This is done by a mixed-methods approach divided into two phases: 1) a literature review, an industry actor survey and an EV user survey, and 2) two sets of interviews with experts from the battery’s End-of-Life (EoL) and Battery Second Use (BoL) phases. The results consist of a refined and prioritized overview of information requirements that are of particular relevance for EVB value chain actors. They also allow for a differentiated insight into the requirements of specific use cases from the EoL and BoL stages. The paper thus serves as the foundation for developing a DPP prototype and for conducting sustainability assessments by providing a holistic perspective on EVB value chain actors’ battery management and data requirements.

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   26. Recommendations and Roadmaps Towards Intelligent Railways

       • Open Access

       Lorenzo De Donato, Ruifan Tang, Nikola Bešinović, Francesco Flammini, Rob M. P. Goverde, Zhiyuan Lin, Ronghui Liu, Stefano Marrone, Elena Napoletano, Roberto Nardone, Stefania Santini, Valeria Vittorini

       Abstract

       This paper provides an overview of the main results achieved within the Horizon 2020 Shift2Rail project named RAILS (Roadmaps for Artificial Intelligence Integration in the Rail Sector). The RAILS roadmapping process provided state-of-the-art, taxonomy, future research directions, and recommendations in three macro areas: Railway Safety and Automation, Predictive Maintenance and Defect Detection, and Traffic Planning and Management. RAILS findings shed light on the potential of intelligent technologies and provided essential guidelines for integrating machine learning into next-generation smart railways.

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   27. The TANGENT Project Architecture: Towards New Traffic Management Approaches

       • Open Access

       Hugo Landaluce, Leire Serrano, Antonio David Masegosa, Arka Gosh, Ander Arrandiaga, Tiago Dias, Ana V. Silva, Lara Moura

       Abstract

       The TANGENT project (www.tangent-h2020.eu/) aims to address the challenges of urban transportation, including traffic accidents, greenhouse gas emissions, and congestion. The project focuses on optimizing traffic management and enhancing mobility through a distributed, modular, and scalable architecture. TANGENT collects and harmonizes data from various sources, including sensors, users, vehicles, schedules, pricing, and traffic flows. It uses this data to create enriched information for different transport stakeholders. The project combines technologies such as data gathering, travel behavior modeling, traffic prediction and simulation, and transport network optimization to provide advanced transport management services. This paper is focused on presenting the project architecture developed to implement four services: data collection and harmonization, enhanced information service, real-time traffic management, and transport network optimization. The project involves a consortium of organizations from nine European countries and aims to pilot its integrated tool in multiple cities in 2024.

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   28. Rail Defect Detection Using Distributed Acoustic Sensing Technology

       • Open Access

       Annie Ho, Gabriel Papaiz Garbini, Ali Kabalan, Martin Ruffel, Abdelkader Hamadi, Katia Amer Yahia, Imen Benamara, Tilleli Ayad, Walid Talaboulma, Pierre-Antoine Lacaze, Tarik Hammi

       Abstract

       In recent years, advances in Distributed Acoustic Sensing (DAS) technology have resulted in significant progress in the detection of vibration sources. However, its use in railway monitoring is still relatively new, even though thousands of kilometers of optical fiber cables are already set up for telecommunication purposes, thus potentially exploitable.

       In this paper, we explore the possibility of using a DAS system and machine learning tools to detect rail defects along the track. Rail defects are defined as anything other than a smooth rail, and we focus on the detection of rail joints, which are common elements along the track. In this study, measurements were carried out on a short railway section of a few kilometers between two train stations in Paris. The results show that nearly all rail joints along the track are correctly detected, demonstrating the ability of the system to detect these elements with a spatial accuracy of a few meters. Lastly, some future perspectives for the study are proposed, such as a more in-depth analysis of the detected locations or the integration of field information to enhance the reliability of detections.

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   29. Railway Ground Truth and Digital Map Based on GNSS and Multi-sensor Big-Data Acquisition

       • Open Access

       Alessandro Neri, Alessia Vennarini, Agostino Ruggeri, Juliette Marais, Nourdine Aït Tmazirte, Omar Garcia Crespillo, Anja Grosch, María-Eva Ramírez, Juan-Gabriel Arroyo, Massimiliano Ciaffi, Giusy Emmanuele, Vittorio Cataffo, Ricardo Campo Cascallana, Daniel Molina Marinas, Alessandro Valentini, Stefano Neri, Fabrizio Memmi, Ramiro Valdés Alvarez-Palencia, Gianluigi Lauro, Pasquale Natale

       Abstract

       Satellite-based localization solutions are expected to boost railway digitalization and in particular, they will enhance evolution and efficiency of railway signaling systems. The development of multi-sensor solutions is ongoing, but some gaps remain. This paper addresses two of them: the need for innovative high accuracy and precision Ground Truth and Digital Maps, essential elements of a EGNSS train positioning system and a V&V environment. These two objectives are focused in the RAILGAP EU project. For each of these tools, this paper presents the main high-level requirements and the selected architectural design exploiting specific data fusion algorithms. The novelty of the EGNSS multi-sensor solution proposed is that it does not require to install or modify any equipment on the track. It is based on datasets acquired through commercial runs in Italy and Spain, leveraging on regular train trips in different operational scenarios and time.

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   30. Fiber Optic Sensors in Asphalt Pavements: Investigation of the Sensor and the Asphalt Pavement

       • Open Access

       Leandro Harries, David Kempf, Ilaria Ingrosso, Daniel Luceri, Alessandro Largo

       Abstract

       Implementing fiber optic sensors (FOS) in asphalt pavements provides a wealth of data with multiple applications. Successful integration of FOS into asphalt pavements depends on two key requirements. First, the sensor embedded in the asphalt must withstand the paving process without damage. Second, the cable must neither compromise the performance nor the durability of the asphalt.

       These requirements were rigorously evaluated in a joint effort between the Technical University of Darmstadt and RINA Consulting S.p.A. Using realistic forces and material temperatures, asphalt samples were compacted and cable functionality and integrity were non-destructively evaluated. Standardized mechanical tests were used to conduct asphalt performance under dynamic loading. Void distribution within the asphalt specimens were evaluated using asphalt petrology techniques.

       Results confirmed the integrity of nearly all cables tested, with minimal impact on asphalt void content and structure. Mechanical tests provided insight into the durability and performance of FOS-containing specimens.

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   31. Unlocking Digital Collaboration: The MINERVE Project as Catalyst for the Railway Infrastructure

       • Open Access

       Elodie Vannier, Judicael Dehotin, Pierre Jehel, Camille Saleix

       Abstract

       The railway sector brings together heterogeneous industry bodies and actors to design, build, and operate railway systems. The digitalization of the rail sector is supported by numerous technologies and the abundant developments go beyond the organization level and require coordination at the sectorial level. As French railway infrastructure manager, SNCF Réseau has launched the innovative research and development project MINERVE. This project brings together the main players in the French rail sector to build a collaborative ecosystem around railway infrastructures challenges and to develop a shared vision of digital continuity. The challenges addressed in MINERVE are related to the transition towards a more efficient, reliable, and environment-friendly railway operation by designing and building with collaborative digital methods and tools. The main objective is to reduce the overall cost and impact of the railway system while increasing collaboration between stakeholders.

       MINERVE outcomes are related to specific, standardized, and interoperable methods and tools, for all technical fields, and that can be implemented and adopted by all stakeholders. The MINERVE project is a one-of-a-kind project to unlock digital collaboration at the sectorial French industry level to improve the life span of the infrastructure as well as the environmental performance of railway projects including biodiversity and resilience to climate change.

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   32. A Schematic Plan for Train Position Identification Using Digital Twin and Positioning Sensors

       • Open Access

       Albert Lau, Hongchao Fan, Hailun Yan

       Abstract

       This paper presents a schematic plan outlining a methodology for determining train positions using digital twin technology and commercially available positioning sensors. The plan involves an offline step and an online step. The task in the offline step includes: building a library of 3D models for objects on railway tracks, and constructing a real digital twin environment. Then in the online step, train positions can be accurately determined by automatically generating real-time semantic point clouds from images and matching them with the 3D objects in the digital twin. Along with these tasks, a City Geography Markup Language (CityGML) Application Domain Extension (ADE) for modeling railway tracks in 3D will be developed and suggested as Open Geospatial Consortium (OGC) standard for similar applications. All these procedures will be conducted in a controlled environment using remote-controlled cars before being applied to an actual railway track. It is hoped that this localization methodology can enhance traditional positioning methods, ultimately leading to improved network operation and maintenance.

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   33. Designing the Procurement Logistics Processes of a Smart Factory Based on Virtual Building Models

       • Open Access

       Bennet Zander, Kerstin Lange, Chris Gieling, Christian Struck

       Abstract

       Smart factory research has primarily concentrated on the manufacturing sector, without taking the building sector into closer consideration. Combining these two ventures can lead to a variety of synergies to minimize the CO₂ emissions of existing buildings. By producing facade and roof panels on an industrial scale for energetic refurbishments, Construction 4.0 and prefabrication can make a significant contribution to achieving climate targets. In this context, the purpose of this paper is to identify, how data of a virtual building can be used in procurement logistics of a smart factory. To achieve this, this paper follows a case study analysis. At the beginning, the procedure of developing a virtual building model is described. This is followed by the design of the inbound workflows of a smart factory in the construction industry. The findings demonstrate how the information from virtual building models can be leveraged to control procurement processes of a smart factory.

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   34. A Framework for Compliance Verification Based on Trusted Data and Blockchain Identity

       • Open Access

       Nikita Karandikar, Knut Erik Knutsen

       Abstract

       Ships generate huge amounts of sensor data, which is largely underutilized due to lack of standardization. The ad-hoc data collection and transmission procedures and proprietary nature of sensor naming conventions make it challenging to implement and scale digital solutions based on this data. Ensuring data integrity can present an additional challenge as data is generated by multiple sensors onboard a ship with constrained connectivity to shore. Sensor as well as stakeholder identities are significant here, in order to reflect ownership structures, maintain access control and link actions with the entity that performed it. In this paper we present Vidameco, an integrated hardware and software framework for standardized data collection and tamperproofing. Dockerized microservices are developed for data collection, hashing, publication of hashes on the blockchain and verification by data consumers. Further, we present an architecture to integrate this tamperproofed data with sensor and stakeholder identity in order to create an underpinning for a digitalized value chain. Sensors are named in a hierarchical structure using the ISO19848 standard and this structure is interfaced with digital identities of stakeholders on the blockchain such as from the European Blockchain Services Infrastructure (EBSI). Finally, taking EU’s Monitoring Recording and Verification (MRV) regulations as a case study we conceptually demonstrate this framework. MRV reporting is a complex value chain involving multiple stakeholders and extensive documentation and forms the basis for EU’s Emissions Trading System (ETS), which is set to include shipping from 2024. This case study presents and evaluates an end-to-end digitalized ETS ecosystem based on tamperproofed data using MRV as the Oracle in smart contracts for ETS trading.

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   35. MOTIONAL: Advancing the Future of European Railway Systems Through Digitalization and Integration

       • Open Access

       Marco Ferreira, Magnus Wahlborg, Lars Deiterding, Anders Johnson

       Abstract

       The Flagship Project “MOTIONAL”, supported by Europe’s Rail initiative, paves the way for implementation of the future European Capacity Planning and Traffic Management System, built on digitalisation, automation, connectivity and multimodal integration.

       Lead jointly by Hacon and Trafikverket “MOTIONAL” with its 89 partners aim to achieve a significant advancement in the state-of-the-art railway systems by pursuing the way to digitalization and interoperability across Europe. To achieve the expected results activities are carried out in two different working domains. The first domain covers three focus areas; planning, operational activities - which includes managing future interactively coupled timetable planning; and finally operational traffic management systems - which also includes integration activities for door-to-door mobility. The second domain refers to the delivery of a set of digital enablers for all European rail destinations, i.e., crosscutting, to support the development of destination-specific digitalisation solutions. The main outputs of the project will be significant improvements to the railway systems in Europe through the development and implementation of a range of technical enablers. The results of FP1 MOTIONAL will enhance the strategic and tactical capacity planning of the network by enabling a seamless cross border planning and integrated yard and station capacity planning and using modern optimisation and simulation technologies.

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   36. Intelligent Access, e-waybills and eFTI Developments in Estonia

       • Open Access

       Taavi Tõnts, Marko Jürimaa, Eva Killar, Ulrika Hurt

       Abstract

       The research objective is to contribute to more effective and greener road freight transport with HV’s, without damaging aging road infra below. One of the best solutions in 21st century is to use all kinds of digital data (temperature; GNSS; OBW etc.) and road maps to control the logistics in the most optimum way, depending on the used vehicle’s load type (Intelligent Access IA). It’s a very cost-effective system. Since the HVTT15 & HVTT16 conferences, much work has been done in Estonia in the logistics digitalization area. In Transport Administration the e-waybill has been piloted to become in 2024 as a compulsory measure in building contracts for the greener infra buildings. Estonian Ministry of Climate has developed the architecture and started to pilot eCMR and eFTI in wider scale and also more widely all over Europe.

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   37. Hybrid Approach for Estimation of Traffic Hazards: Fusion of ML and Pure Statistical Model

       • Open Access

       Natasa Mojic, Vijay Mudunuri, Radim Slovák, Thomas Mariacher, Peter Hrassnig

       Abstract

       Precise travel and traffic information are becoming increasingly important to road users. This is backed up by a growing number of users who are planning their trips before they start their journey. People primarily aim to avoid or minimize the travel delays by knowing alternative routes or changing the departure time beforehand. Furthermore, they are increasingly customizing their travels to maximize efficiency and convenience. From years of experience, and considering the Traffic telematics report [1], ASFINAG, as the national operator of Austrian motorways and highways, has recognized this need and has focused on bringing the accuracy of our traffic information to real traffic conditions. In this paper we present our hybrid approach that combines two methodologies to provide traffic information that is closer to the real traffic conditions, with a special focus on the traffic jams and delays. Our main goal is to improve the accuracy of the travel delays and traffic jams both in terms of time and location. The first methodology, which is a fusion of data from various data sources, is based on pure statistical model, whereas the second methodology is a machine learning (ML) model. This hybrid approach is not a comprehensive one but rather restricted to selected road sections.

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   38. Future Mobility Campus Ireland: A Testbed for Advanced and Autonomous Vehicles

       • Open Access

       Diarmuid Ó Conchubhair, Russell Vickers, Wassim Derguech, Danijel Benjak, Brían ó Cualáin

       Abstract

       The Future Mobility Campus Ireland (FMCI) was founded with the sole purpose of creating and delivering future mobility testbed facilities for stimulating research, development and innovation in the area of Autonomous Connected Electric Shared Vehicles (ACES), including Connected and Autonomous Vehicles (CAV) and Advanced Air Mobility (AAM), in Ireland. FMCI focuses on comprehensive mobility technologies that span both ground (autonomous driving, micro-mobility, smart cities, V2X communications) and air (unmanned drones, eVTOL, AAM, UTM) uses.

       FMCI supports a range of parties, from individual researchers to multi-national corporations, as well as start-ups and government entities. FMCI assists organisations to conceive, develop, trial, and deploy societally transformative transport solutions both nationally and internationally.

       The installation of state-of-the-art connectivity technologies at the FMCI testbed is providing an environment for the automotive industry, component suppliers, telecommunications companies and research institutions with the opportunity to adopt new approaches to develop innovation for future technologies. FMCI has been operational for over a year and is already facilitating various companies and higher education institutes (HEIs) to further their innovation and/or technologies.

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   39. The More You Know: Digital Twins of Travelers

       • Open Access

       David Käthner, Klas Ihme, Erik Grunewald

       Abstract

       Despite increasing digitalization, rail operators and other mobility service providers often need more real-time information regarding the occupancy of trains and stations. Worse, only general assumptions regarding passengers’ specific destinations, individual needs, and current and past experiences can be made. Digital Twins of Travelers (DTT) address the issue by holding real-time digital representations of passengers throughout their journey from start to destination. Being informed about a passenger’s route instead of isolated sections enables customized real-time forecasts, accessibility information for each transfer location, and veridical updates about how much time may be spent there. For example, a traveler would benefit directly when parts of a journey must be rescheduled due to delays on the original route. When continuing with means of transportation different from those chosen initially, forecasts and other information can be immediately adapted to the new route. In the same scenario, mobility service providers would benefit by being informed about occupancy changes, allowing them to prioritize scheduled connections if necessary. DTT consist of a real-world twin, its digital counterpart, and an interchange component linking them. The digital twin represents how travelers experience current events, holds information regarding their individual itineraries’ progress, and can exchange information with mobility service providers. DDT's purposes range from supporting passengers in real-time by providing information relevant to their journey milestones, analyzing the effect of events such as delays on the travel experience, to helping to align transport services with the existing demand.

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   40. Different Facets of Artificial Intelligence-Based Predictive Maintenance for Electric Powertrains

       • Open Access

       Ali Serdar Atalay, Ahu Ece Hartavi Karcı, İbrahim Arif, Salih Ergün, Alper Kanak

       Abstract

       Maintenance, traditionally perceived as a reactive cost and a hindrance, poses challenges to efficiency when components succumb to unforeseen breakdowns. In addition to the financial implications, the repair process also incurs substantial time wastage. To overcome these obstacles and achieve enhanced efficiency and cost savings within the manufacturing sector, this paper presents a conceptual study of a technologically advanced predictive maintenance (PdM) approach, particularly in the realm of artificial intelligence-powered digital twins. The effectiveness of these solutions hinges on their data-driven nature, technical feasibility, and acceptance by industry stakeholders.

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   41. Analyzing the Enabling Factors to Implement MaaS in Asian, African and Latin American Cities

       • Open Access

       María Rosa Muñoz B., George Panagakos, Shritu Shrestha, Emilie Martin, Marc Hasselwander, Samuel Bonsu, Grace López Realpe, Fabio Bachetti, Michael Bruhn Barfod

       Abstract

       The EU-funded SOLUTIONSplus project, which aims at kick starting urban e-mobility in developing countries, included the provision of a white label app customizable to the needs of the cities as part of its offer to its 7 demonstration cities in Asia, Africa and Latin America. Despite having the possibility of testing the customized app free of charge for the duration of the project, only 2 out of 7 cities, Quito (Ecuador) and Kigali (Rwanda), started and continued the process. Yet, only Quito was able to test the customized app in real operations. Thus, the paper analyzes the MaaS level and implementation barriers of the 7 cities and conducts an in-depth expert assessment of the technology, organization and environment enabling factors (TOE) to implement the MaaS concept in Quito, Kathmandu and Kigali. The results show that despite some progress towards an intelligent and integrated transport system in the analyzed cities, an important number of conditions that are a given in the Global North (e.g.: formality and integration of PT system), still need to be met in cities in developing countries before MaaS could be realized.

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   42. Designing Mobility Systems-of-Systems

       • Open Access

       Pontus Svenson, Jakob Axelsson, Charlotta Glantzberg, Robert Nilsson

       Abstract

       In this paper we describe the results of a study on the design of open and co-opetitive systems of systems for mobility. A system of systems (SoS) is a set of independent systems (CS – Constituent Systems) that interact to create capabilities that none of the constituent systems can accomplish on their own. A CS can be simultaneously part of several SoS. The independence of the constituent systems is an important and central ingredient in an SoS, and is often divided into managerial and operational independence.

       We argue that the mobility SoS of the future can benefit from being open and co-opetitive (i.e., simultaneously collaborating and competing) to enable combined mobility (MaaS) for real. If competition between CS is not allowed, new entrants will choose to compete with the SoS instead of becoming part of it. If a new entrant develops much better vehicles or better ways to find transport solutions for users, that entrant must be able to become part of the SoS and take market share from other actors.

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