Climate Crisis and Resilient Transportation Systems

This paper delves into the aftermath of Storm Daniel on bridge infrastructure within Greece’s Magnesia region, scrutinizing the root causes of catastrophic collapses while providing an overview of advancements in protective measures. Amidst the destructive passage of Storm Daniel, the vulnerability of infrastructure, notably bridges, to extreme weather became glaringly apparent. Emphasizing the imperative for resilience measures and proactive infrastructure management, the study underscores the necessity of safeguarding transportation networks against the escalating threats posed by climate change. Specifically, the paper investigates the role of Structural Health Monitoring and Non-Destructive Evaluation techniques in fortifying bridge resilience against future extreme weather events.

The H2020 RESOLUTE research project, led by University of Florence with co-participation of ATTIKO METRO, belongs to programmes aiming an enhancement of resilient urban transport systems (UTS). The paper validates operationally the European resilience management guidelines (ERMG) developed with regard to the flood resilience of UTS in Florence, Italy. Florence, a world heritage site, suffered at 1966 a 200-year Arno river flood disaster devastating i.a. invaluable Renaissance artworks. ERMG follow the FRAM concept, the most refined resilience framework so far. Thus, the data-driven approach of the project is theoretically informed. A collaborative evacuation app developed and validated during an assumed 30-year flood pilot case, involves citizens to be rescued as well as first responders. A dashboard managed by civil protection and public administrators coordinates remotely the emergency response. The dashboard collects actual crowdsourced and sensor information (e.g. gauge pressure of inundated network links indicating flood depth) as well as weather information. Rainstorm forecasting and rainfall nowcasting (1–2 h’s periods) make valuable time available for a timely evacuation action. The dashboard platform aggregates and integrates heterogeneous data sources, i.a. topographic features as depressed links and their distance from the river.Beyond the absorb /response phase, the dashboard provides during the flood recovery phase, information about passable paths and parts of the transport network, advising riders and drivers via bulk SMS/VMS alerts and other public address systems. Traffic diversion and control as well as alternative routes dampen the flood-related UTS performance variability.

The adverse effects of the climate crisis on urban areas hinder the functions of the city and threaten the anthropogenic environment. When the climate hazards manifest in the road network and public spaces, they directly impact human health and safety, affecting the quality of life and livability. The subject of this study is the environmental redesign of urban roads using bioclimatic design tools. The aim is to improve the microclimatic conditions of public spaces and enhance sustainable mobility and urban resilience. The Profitis Ilias Street in the Municipality of Pylaia-Hortiatis, Thessaloniki, Greece is studied, which is characterized by a significant lack of safe and comfortable infrastructure for walking and cycling, lack of green spaces that exacerbate high temperatures during heatwaves, as well as the occurrence of floods in case of intense and rapid rainfall due to the absence of an integrated stormwater drainage network. By applying the Urban Adaptation Support Tool of the European Environment Agency, the risks and vulnerability of the road axis were assessed, a resilience strategy was developed, and specific adaptation measures to climate change impacts (urban heat island effect, floodings) were proposed in combination with traffic calming measures at urban design scale of 1:1000. The use of cool and permeable paving, the installation of blue and green infrastructure, and the restriction of motorized traffic are fundamental prerequisites for achieving urban resilience. We suggest that the bioclimatic approach, so far implemented to a limited extent in urban street design, should become an integral part of transport planning.

When cities face emergencies like the COVID-19 pandemic, they need to respond quickly while keeping their long-term urban mobility plans on track. Sustainable Urban Mobility Plans (SUMPs) should be flexible enough to handle immediate crises and still focus on long-term goals. SUMPs provide a great framework for building a resilient transport system that can adapt in emergencies and continue to pursue sustainable mobility. To address pandemic-specific challenges, we suggest adding a second layer to the SUMP cycle. This layer includes extra actions for each step of the process. Cities with an existing SUMP can use this model to see what additional steps are needed during a pandemic. For cities that haven’t implemented a SUMP yet, this model shows how to integrate these extra measures from the start. This revised SUMP cycle is a valuable tool for planning and decision-making in pandemic situations. It ensures that cities can adapt quickly while still prioritizing long-term sustainability. By combining the initial SUMP steps with new pandemic-specific steps, cities can better navigate the new reality. This approach helps maintain both short-term responses and long-term urban mobility strategies, incorporating social and economic sustainability principles. This study focuses on redefining the SUMP cycle within the RESCUE framework (REinventing SUMP Cycle Under pandemic Era). Our main goal is to update the SUMP cycle to better handle pandemic challenges. We aim to give policymakers and planners a useful tool for making decisions about mobility measures during crises, ensuring that social and economic sustainability principles are included for maximum effectiveness.

The aim of this paper is to analyze geographic characteristics of urban regions that may have an effect, positive or negative, on Covid’s transmission. The overwhelming majority of articles found on urban design don’t seem to provide a unanimous answer.Therefore, a comparative analysis of Covid-19 cases at regional-level in Greece was made, to investigate geographic, urban and traffic characteristics which influence Covid-19 transmission. Results show that islands and cities in the southern parts of Greece seem to be sanitary safer. Moreover the greater the distance from a metropolitan center, the less Covid-19 cases were recorded. Finally accessibility of a city measured as “covered area” by car has also a positive effect on Covid-19 transmission. On the other hand urbanization at the regional level and density at the city-level did not correlate with Covid-19 cases.

In an era of pressing environmental concerns, social equity considerations, and the urgent need for resilient urban infrastructure, the issue of sustainable transportation systems takes center stage. While standard definitions and theoretical frameworks for sustainable transport systems exist, there is a significant gap in our understanding of individual sustainable transport literacy (STL). STL is a pivotal factor in the development of environmentally responsible, cost-effective, and socially inclusive transport systems. Like other literacies, STL aims to elevate the level of communication and interaction, empowering individuals to understand the world and make informed choices that contribute to creating sustainable, liveable, and happy communities.This paper suggests the Sustainable Transport Literacy framework, a powerful tool designed to define and assess STL. This multidimensional eight-step framework includes key components and indicators that collectively measure a person’s understanding, skills, and commitment to sustainable transport. Based on the careful development of terminology, typology and system classification for STL concepts, as well as on the basis of overarching concepts of literacy, a definition of STL was proposed, and a preliminary assessment tool was developed. These efforts included creating a pilot test and questionnaire to assess knowledge and understanding of sustainable transportation principles, which underwent initial testing and content analysis.

Technology has rapidly changed the opportunities available to solve main problems, such as congestion and CO2 emissions. The increasing car ownership levels and population of today’s cities have created more congestion at intersections located in popular destinations, such as CBDs or stadiums, as these attract flows from origins spatially distributed across a metropolis. According to the literature, solutions, such as Adaptive Traffic Control Systems (ATCSs) and Artificial Intelligence (AI), are essential tools to improve traffic conditions. However, in these destinations, when events take place or there is an emergency, oversaturated traffic conditions may occur and it has been judged from the literature that the green timings allocated to the critical approaches from these systems may not be enough to decongestion the network. As a result, additional signal plans specified for such cases can be implemented to support and improve traffic conditions. These additional signal plans could be later fed to the algorithms of ATCSs, in order to make ATCSs applicable to all possible circumstances. In this paper, a practical application has been developed for the Olympic Stadium in Athens, for the majority of events that take place in this area. A substantial number of signal programs were designed using specified criteria to adjust the green timings needed during these events. These new signal plans have been designed by the Athens Traffic Management Centre and aim to support policy makers to plan towards sustainability, efficiency and resilience.

The European transportation sector confronts significant challenges, in-cluding traffic congestion, safety concerns, greenhouse gas emissions, and associated costs. The development of disruptive technologies and the emer-gence of new mobility solutions generate a revolution in the transport net-work and traffic management. To address these issues, SYNCHROMODE introduces an innovative data-driven decision support system, aimed at en-hancing multimodal network and traffic management. This paper presents the development process for this system, which incorporates the data quali-ty assessment, the modelling and simulation of multimodal transport, traf-fic prediction, network optimization techniques, and definition of novel multimodal Key Performance Indicators (KPIs). The proposed system facilitates the prediction and optimization of multi-modal transport supply and demand, the instantaneous and effective reac-tion to and management of various types of events, both planned and un-planned, as well as the communication and coordination of the various in-volved actors. The practicality and effectiveness of elements of this toolbox will lead to the creation of three distinct services, and specifically those of a) Network-wide data exchange and integration, b) Cooperative dashboard for real-time monitoring and prediction of network-wide multimodal transport and traffic, and c) Resilient multimodal transport network and traffic management support tool. The services of the SYNCHROMODE Toolbox will be assessed in three case studies in Greece (Thessaloniki), the Netherlands, and Spain (Madrid), highlighting their potential to revolution-ize transport network and traffic management across Europe.

Daily issues that directly affect overall urban mobility such as traffic flow, air pollution, economic development, and access to essential public and private services are directly affected by parking. Based on this, the main objective of the research is to investigate the critical characteristics that affect parking duration in private parking lots . For this purpose, a large central was developed, which included data from the Cityzen company, consisting of various records of passenger vehicles from 13 parking areas inside and outside the Attica Region. These records accounted in total more than 520,000 individual parking recordings and included information such as the type of customer, the date and time of entry and exit from the parking lot, the duration of parking, the square meters and the levels of the parking facility. Moreover, additional variables were calculated to further analyze the data, such as the distance from the nearest bus stop and metro station, the commercial use of the area, and the population of the municipality where the parking lot is located. Then, three models were created, with the parking duration set as the dependent variable. Specifically, the data were grouped as follows: the first model included all the records, while the other two were classified based on their location (inside or outside Attica). Statistical analysis revealed that drivers tend to park for longer periods during the morning hours and mainly in spring, while parking duration does not show a strong correlation with the type of customer. The results provide the potential to develop innovative and more efficient methods for managing parking lots.

The increasing demand for efficient and resilient transportation systems in the face of climate change necessitates innovative solutions for parking management. Dynamic pricing, also known as demand-based pricing, is a pricing strategy that adjusts prices in real-time based on demand and supply. This approach has been widely adopted in various industries, including airlines, hotels, and ride-sharing services. In recent years, there has been a growing interest in applying dynamic pricing to parking management. This paper proposes a dynamic pricing algorithm for private parking lots that utilizes real-time data on parking occupancy and traffic conditions within a 500-m radius to optimize parking revenue, minimize congestion, and encourage alternative transportation modes. The algorithm employs a dynamic pricing mechanism that adjusts parking rates in real-time based on occupancy data. This approach ensures optimal utilization of parking spaces, minimizing congestion and maximizing revenue generation. Additionally, the algorithm considers traffic conditions in the immediate vicinity, enabling a responsive and adaptable pricing strategy that aligns with the broader objectives of sustainable urban transportation. By aligning parking pricing with dynamic demand factors, this algorithm contributes to a more efficient, resilient, and environmentally responsible urban transportation system.

The interplay between autonomous and manual vehicles in mixed traffic situations is a matter of concern as it may significantly affect the overall performance of the transportation system. Furthermore, two critical issues must be addressed: the transportation system's energy consumption and environmental impact. A more profound comprehension of mixed traffic dynamics, where autonomous and human-driven cars coexist, is necessary to navigate the transition from current conditions to an ecosystem entirely dominated by autonomous vehicles. To tackle these issues, this article aims to develop eco-driving approaches that reduce environmental effects and enhance energy efficiency. The case study under consideration is a roundabout with heavy traffic, and it examines how the total number of vehicles exiting the roundabout varies based on multiple input criteria. As a result, it was noted that the quantity and manner in which autonomous vehicles enter the roundabout from the priority road could affect the number of traditional vehicles that enter the yielding road. Increasing traffic flow in the roundabout can mean less fuel consumed and reduced emissions. To simulate the traffic in the roundabout, a model was developed in the MATLAB® program, and the actors, which are autonomous or classic vehicles characterized by functional characteristics, ran in various scenarios to determine optimal solutions for smoothing the traffic.

We deal with the improvement of public transportation service as for its enormous influence on the lives of residents and government spending. From the policymakers’ point of view the primary goal is to assess the level of public transportation and pinpoint practical ways to improve it in order to increase passenger satisfaction and draw in new customers. Two well-known multi-criteria decision-making techniques, the Fuzzy Analytical Hierarchy Process (FAHP) and the Fuzzy Technique for Order Performance by Similarity to Ideal Solution (FTOPSIS), were used through a dynamic questionnaire survey to accomplish this goal. The robust FAHP technique provides a systematic evaluation framework by taking feedback and interrelationships between different criteria levels. However, to obtain a thorough grasp of experts’ opinions about the quality of public transportation services, both approaches had to be used. A real-world situation for the city of Larissa, Thessaly was used in empirical research to show how these ideas can be applied in practice. The usefulness of these decision-making techniques is demonstrated by this study, which also emphasizes how crucial it is to prioritize public transportation system improvements in order to improve citizen lives.

Urban transport is a key factor in the economic, cultural and productive development of any society. However, today's road networks are burdened with a much larger volume of traffic as they were designed to serve earlier societies. In order to meet the new travel needs, it is necessary to implement new methods and systems that not only respond to the new challenges and needs but also provide travelers with sustainable travel solutions.Mobility as a Service (MaaS) aims in this direction by ensuring the cooperation of different mobility providers by integrating all public transport modes with sharing and pooling services (e.g. carsharing, carpooling) and various means of micro-mobility (e.g. e-scooter, e-bike) as well as subscriptions and travel pack-ages to meet and serve every need of citizens. The investigation of the acceptance of Mobility as a Service by the residents of Patras through a questionnaire survey showed that most of them, although they understand the benefits of implementing this platform, are quite reluctant to adopt it.This paper is about investigating the acceptance of Mobility as a Service by the residents of Patras through a questionnaire survey. A great number of the people who participated in this questionnaire prefer to make their transfer by private car, by their own time and comfort. Therefore, for this implementation of such a needed mobility platform to make sense, it is necessary both to keep the residents in Patras informed about the innovative technological developments and to upgrade the infrastructure. Mainly to change the public transport in Patras in order to make it more accessible and efficient for its inhabitants.

Understanding the complex field of extreme events management and its impact on sustainable development especially in time of crisis is an opportunity to shape integrated management strategies that can facilitate the mitigation of challenges posed by climate change, while advancing sustainable development goals in urban areas. The goal of this paper is to explore the latest achievements in cutting-edge literature and predictive models to monitor and spatially analyze extreme events to prioritize resilient and sustainable urban planning towards the achievement of a more sustainable urban development. The overarching outcome is to provide a set of policy and practical recommendations and highlight the necessity for further specific analyses, acknowledging that sustainable urban planning and risk management can significantly contribute to climate-induced management crisis.

Predictive Maintenance (PM) represents a transformative approach applied in industry and, naturally, within the transportation sector, optimizing infrastructure functionality and resilience, while minimizing resources and costs. Diverging from traditional maintenance strategies, such as reactive and corrective methods, PM employs digital technologies—Edge and Cloud Computing, Internet of Things (IoT), Artificial Intelligence (AI)—to proactively anticipate and prevent potential failures, ensuring continuous operational efficiency, an essential factor in transportation industry.This is crucial for further reducing operational expenses (OPEX), while avoiding unexpected losses and enhancing system reliability through multi-objective optimization. Moreover, PM's integration of reporting models, structural assessment methods, forecasting systems and remote infrastructure management forms a comprehensive framework that supports data-driven decision-making, early defect detection, predictive analysis and real-time health monitoring of transport infrastructure. These advancements not only contribute to material and energy savings, but also support the efforts to mitigate climate change effects, positioning PM as a milestone of progress and sustainability.This paper presents an innovative integration of disciplines and specialties applied to the creation of holistic familiarization content on Predictive Maintenance, adapted to meet contemporary requirements and hence, demonstrating its critical role in the evolution of maintenance methodologies and its impact on transportation sector's future. It is structured to cover the theoretical framework (comparison with traditional maintenance and key technologies), applications (examples of PM application in transportation), benefits (financial and environmental advantages, increased system reliability and safety), challenges (technical and financial), future directions and solutions to overcome existing limitations of PM, concerning the area of modern transportation.

Predictive Maintenance (PM) is crucial for optimizing economic resources, operational efficiency and fundamental infrastructure systems. Its primary function is to foresee and prevent critical infrastructure breakdowns or failures through digital approaches. As industries increasingly rely on data-driven approaches, the need for a skilled workforce proficient in predictive maintenance systems becomes paramount. Recognizing the transformative impact of emerging technologies on the transportation landscape, this paper envisions a future employee profile characterized by a multidisciplinary skill set, encompassing data analytics and domain-specific expertise. This study proposes six matrices covering the competence areas as defined by key actors in the transportation sector during multiple online workshops. These matrices could operate as an educational benchmark to identify the potential challenges and opportunities within the transportation workforce industry. They could also equip transportation sector employees with the requisite skills contributing to more resilient and efficient transportation infrastructures. Finally, a comprehensive training toolkit is proposed i) to include multiple modules (each for a specific competence area) and ii) to provide a structured course that integrates theoretical foundations with practical applications.

Climate change and aging infrastructure have elevated the importance and role of resilience for transport infrastructure. This research paper introduces a robust risk analysis tool, specifically designed to improve the benefit of investments in infrastructure resilience, particularly in the context of road transportation networks vulnerable to floods. The HAzard & Risk Multiregional Assessment tool (HARMA), integrates multiple modeling perspectives and exploits a wide variety of data sources to evaluate both the direct and the indirect cost of hazard-induced damages and disruption to the transport network. Key features of the tool include its ability to quantify the likelihood and severity of identified hazards, locate the exposed assets and links of the network, assess the extent of damages, and evaluate the socio-economic impact due to the disruption of transportation activities. Additionally, the tool facilitates scenario analysis, enabling decision-makers to explore different risk mitigation strategies, optimize interventions, and prioritize investments for enhanced resilience under varying budget constraints. One of the key strengths of the tool is its global applicability even in data-poor environments, while not limiting users from inputting region-specific data if available. This study offers a practical application of HARMA in the region of Thessaly, Greece, which has been the hot-spot of major, destructive floods in the recent past, after storm Daniel (2023) and Medicane Ianos (2020).

Amidst escalating threats from disasters compounded by the climate crisis, communities globally are intensifying efforts to bolster disaster resilience. Recognizing the pivotal role of Information and Communication Technology (ICT) in disaster risk management, there is a growing emphasis on addressing the intricacies involved, including diverse actors, infrastructures, and datasets with distinct functions, rules, and protocols. This complex landscape poses challenges for decision-making and event coordination, highlighting the crucial need for effective semantic interoperability among stakeholders. This paper introduces the RES-Q (RESCUE) approach, an innovative information technology solution prioritizing real-time recommendation and orchestration of post-disaster response plans, with a specific focus on enhancing the mobility of relevant actors. The RES-Q approach seamlessly integrates an expert system, a workflow execution engine, and a Reinforcement Learning (RL) agent. A multi-layered ontological model encapsulates the essential knowledge streams and a semantic rule repository for the modeling of response plans. During the design mode, the RL agent optimizes response plans for stakeholders, emphasizing their efficient mobility and actions within the ontological infrastructure. Throughout the execution of post-disaster plans, the system reasons over the rules and recommends the next steps of the orchestration process. The paper elaborates on the key modeling artifacts of the proposed approach and outlines the architecture of the system, providing a comprehensive overview of its components and functionalities.

In the aftermath of natural disasters, first responders are responsible for conducting search and rescue operations, assessing the extent of damage, and initiating recovery efforts. These activities play a pivotal role in mitigating the impact of disasters and facilitating the restoration of normalcy. Yet, they face formidable challenges due to the necessity for rapid, time-sensitive decisions amidst an environment where information is both abundant and fragmented, and conditions evolve swiftly. This underscores the pressing need for more robust decision-making frameworks that enhance the effectiveness of responses in dynamic disaster environments. In response to these challenges, this study introduces the First Responders System (FiReS), an advanced system designed to optimize first responders’ response plans by utilizing Semantic web technologies and Artificial Intelligence (AI). Central to the architecture of the FiReS system are two core components: a comprehensive ontology and an intelligent agent. The ontology provides a structured framework that organizes disaster-related data, ensuring consistent interpretation and integration across diverse sources. Concurrently, the intelligent agent utilizes advanced machine learning algorithms to process this data and generate actionable recommendations. This strategic integration streamlines the decision-making processes and enhances the system's adaptability to evolving emergency scenarios. Overall, the proposed architecture positions the FiReS system as a significant advancement in the field of post-disaster response.

With the increasing unpredictability of climate change and the resulting rise in flood incidents, accurate and timely flood mapping is essential for efficient disaster relief. This study examines the use of satellite and aerial images taken during flood events to map floods in the Larissa region using a Decision Support System (DSS). The suggested DSS analyzes aerial photos using sophisticated image processing and Machine Learning (ML) methods to extract relevant data essential for mapping flood extents. The DSS takes a holistic approach, combining meteorological inputs, topographical features, and historical flood data to improve the accuracy and reliability of flood mapping. The technology uses Artificial Intelligence (AI) to automate decision-making so that it can provide quick and precise flood estimates. Our system supports early warning via real-time monitoring, giving authorities the ability to proactively handle any flood concerns in the city. Moreover, this work emphasizes the need of customized decision support systems for flood mapping in geographically particular areas, adding to the ongoing efforts to use technology for disaster risk reduction and emergency response. The results have important ramifications for strengthening resilience and lessening the effects of flooding in Larissa and similar areas.

Centered around transformative change for urban sustainability and resilience is a circular economy (CE) strategy to energy and material resources, which offers manufacturing businesses benefits on an economic, environmental, and social map. While this adoption encourages the application of new governance strategies that consider the intricacy of urban systems and the knowledge and perspectives of related stakeholders, it also makes significant economic growth possible by ensuring that energy and material resources are used appropriately across manufacturing industries. Our work focuses on identifying the indicators in the context of urban resilience and transformation via CE and developing a DEMATEL in conjunction with an FCM Decision Support System to facilitate the decarbonization of urban regions through plausible policy scenarios. The findings show that implementing circular and green practices, using resources responsibly, and combining institutional and social action at the local level may be the best ways to promote an efficient and long-lasting change in the urban energy system. We focus on the importance of the energy system's connectedness, which is discovered to present conflicting potential for resilience and transformation, as we specifically examine the features of the resulting cognitive network.

Developing information and communication technologies are effective in city structures as in every field. Cities that cannot make use of technological facilities properly cannot respond to the needs and expectations of citizens. The purpose of this research is to reveal how participation can be developed in smart cities, why cities should turn into a smart city and to what extent smart city applications can be used.With digital transformation, the groundwork has been laid for the formation of a society model that can correctly interpret and process information in people's daily lives, question the environment they live in and adopt the principle of lifelong learning. It is aimed to increase the quality of life of citizens by saving cost, time, and energy.Smart cities are evaluated with six basic dimensions: smart economy, citizens, governance, mobility (incl. Transport), environment, and life.To achieve the objectives determined within the scope of this research, the description method was used. In the collection of data, a survey technique was used. The questionnaire created within the scope of the research was applied in the partner countries of the project: Bulgaria, Greece, Poland Spain, and Türkiye). In total, 505 people from five countries participated in the survey.

Tourism is a leading sector for Bulgaria, the Thracian tourist region and destination Plovdiv. This article aims to analyse the destination’s transport issues in search of safe and sustainable transport solutions for urban mobility that actively support cultural tourism. The study is part of the “living laboratories” of the project “Investing for excellent uses in regional sustainability” (INVEST4EXCELLENCE) in search of a model for innovative use of transport infrastructure by the tourist flow. Policies focused on the mobility needs of the city’s guests and businesses, as well as the functionality of the area and improving the quality of life of the local people in the next decade are discussed.At the centre of the discussion are the challenges, risks and opportunities for the sustainability of the tourist destination Plovdiv such as: transport and mobility, which promote social innovations in providing accessibility to cultural attractions, tourist sites and services. Urban mobility planning is commented on - types of trips; measures to promote active movement patterns and use of public transport; synergy between car, pedestrian and bicycle traffic; integrated routes aimed at satisfying cultural needs.

Electrically assisted bicycles are emerging as a sustainable and eco-friendly solution in transportation. Range anxiety and poor understanding of the energy expenditure required for a specific route are some of the barriers limiting wider adoption. The current work serves as a proof of concept for an e-bike digital twin designed to address these issues. The digital twin’s input signals are GPS coordinates and altitude recorded with a smartphone and charging power recorded with a smartplug, as well as weather conditions typically available online. First, a theoretical model for the dynamics and the energy exchange of the bicycle is formulated based on literature. Then a methodology for the fit of unknown parameters with dedicated tests is applied. Finally the digital twin is validated in the field and its range estimate is compared to the actual distance traveled during a full discharge consisting of several trips. Possible improvements are discussed, as well as the potential of the digital twin to predict range under transient road and weather conditions, achieving better accuracy than the last leg projections currently used in e-bike displays.

Many cities are recognizing the need to transform their urban freight mobility systems towards more sustainable ones. This transition in urban logistics is pivotal in addressing critical challenges such as air and noise contamination, in contributing effectively to climate change mitigation efforts as well as in tackling problems like double parking and congestion. Therefore, a strategic transition in habits, technologies, delivery concepts and approaches necessitate either their cessation or adaptation. This process can be encapsulated by the term ‘exnovation’, which is defined as the deliberate discontinuation of current infrastructures, technologies, products, and practices, highlighting its critical role in altering the existing framework. Thus, the paper conceptually elaborates on the advancements in transformation and transition studies to analyze the role of urban freight policy for reducing undesirable developments and increasing the certainty of more sustainable last mile delivery approaches. The paper empirically analyses key characteristics of urban freight policy and critically discusses its potential for transforming the urban freight sector, based on a qualitative case study of the City of Berlin, Germany. The findings indicate that selective urban logistics issues are addressed by some exnovation policies, such as phasing-out diesel delivery vehicles, restricting the use of polluting motor vehicles in some parts of the city. However, there is still a lack for a systematic exnovation approach alongside the innovation policies. Furthermore, future urban freight research benefits from adopting more change-oriented sustainability transition approach.

UNCHAIN is Horizon Europe innovation project, aiming to boost the cooperation between public authorities and logistics stakeholders, and to create a set of services for optimal and flexible urban logistics operation, management, planning and policymaking. This cooperation will unleash the potential that digitalization can bring to sustainable urban logistics, moving towards climate-neutral smart cities. As part of the project’s work plan, the consortium partners have identified emerging needs and requirements of all stakeholders involved in and affected by city logistics, leading to the definition of technical, operational and policy-based requirements user-centric, data-driven logistic cooperation framework and tools. The objective of this paper is to present the methodology and the results of the UNCHAIN project requirements analysis which includes a collaborative framework for identifying barriers, enablers, and recommendations regarding the improvement of urban logistics operations and policy making. The user requirements analysis was complemented with the analysis of Sustainable Urban Logistics Plans (SULPs), and Sustainable Urban Mobility Plans (SUMPs) of the cities involved in the UNCHAIN project demonstration sites, and the identification of the initial list of Key Performance Indicators that will be used to assess the UNCHAIN project outcomes.

The study aims at investigating the crucial barriers and enablers in the application of same-day delivery logistics in Hanoi, Vietnam – a city with very high-speed e-commerce development. A questionnaire survey has been conducted with the involvement of customers and e-commerce retailers to rate affecting factors based on their respective importance about same-day delivery in Hanoi, Vietnam. The findings revealed that the most important factors that affect same-day delivery substantially are infrastructure, traffic congestion, weather conditions, high logistics costs, limited payment options, and limited customer awareness. The study results confirm that while same-day delivery offers a competitive advantage for e-commerce businesses, it also presents significant logistical and financial challenges in Vietnam. Such findings facilitate the recommendations for e-commerce service providers on requiring careful planning and coordination of various logistics processes, including order processing, inventory management, and last-mile delivery. The results also provide practical evidence to transport authorities to provide a possible reduction of logistics costs in the long term.

Shared micro consolidation centers represent a pivotal innovation in urban logistics. They not only streamline the distribution process by centralizing deliveries, thereby reducing traffic congestion and emissions but also foster cooperative synergies between logistics service providers, leading to more efficient use of resources and enhanced service quality in last-mile delivery. This study aims to explore and analyze the integration and impact of a white-label scheme in the operation of a shared micro consolidation center in an urban setting, specifically in the center of Athens, Greece. This will be achieved by (i) describing the white-label integration, i.e. how such a scheme can be effectively integrated into an existing framework of a shared micro consolidation center, highlighting the process, strategies, and technologies involved, and (ii) identifying challenges and solutions with a business context that can be applied in similar logistics scenarios. Early conclusions drawn suggest that the potential of white-label schemes in transforming urban logistics is substantial, primarily due to their inherent flexibility in adapting to and supporting policies implemented by city authorities.

Logistics plays a crucial role in modern society, particularly in densely populated urban areas, facilitating the transportation of goods. Last-mile e-commerce deliveries are emissions-intensive, contributing significantly to CO2 levels and traffic congestion. Addressing this challenge requires systemic changes in last-mile delivery ecosystems. Based on this observation, in alignment with the EU decarbonisation goals, the URBANE project (GA101069782) aims to promote the adoption of sustainable and environmentally friendly last-mile delivery solutions by introducing a collaborative layered “Platform as a Service” (PaaS) paradigm. The initiative focuses on establishing Physical Internet (PI) inspired interventions combined with the implementation of innovative tools, such as agent-based and AI models, employing a Digital Twin platform addressing the operational and strategic planning challenges of city logistics networks. A multi-factorial impact assessment radar further enhances the evaluation of the PI interventions’ effectiveness. The platform fosters collaboration among urban logistics stakeholders governed through “green” smart contracts, addressing security and privacy concerns by using a blockchain infrastructure and digital IDs, creating a trustworthy system for collaboration.The paper showcases the applicability of the URBANE Innovation Transferability Platform in designing, measuring, testing, and validating targeted logistics interventions in Lighthouse Living Labs. Cities and logistic operators receive suggestions for informed data-driven decision-making coupled with integrated and transferable applications that can be standardised and structured, aligned with the targets set in a citie’s Sustainable Urban Logistics Plan (SULP).

This paper aims to investigate the possible impacts of e-shopping on shopping trips for five types of commodities (foods, clothes and shoes, electronics, books and stationery, cosmetics) with evidence from Vietnam. The study utilized data from structured interviews with 442 respondents in Hanoi, the study implemented the regression models to identify factors affecting e-shopping and shopping travel behavior. The findings indicate that e-shopping and shopping travel behavior of consumers are significantly influenced by socio-demographics, working-travel distance, start-working time, vehicle ownership and size of family. In many cases, the frequency of in-store shopping trips is replaced by online shopping. Therefore, it could be recommended that e-shopping might be a solution for urban logistics to reduce traffic congestion. Considering the longer term, the physical stores and supper markets of five types of commodities might be reduced that might change significantly urban logistics activities.

Data-driven operations are critical for an efficient and compliant European transport ecosystem. Real-time analysis and visualisation of data about vehicles, drivers and goods being transported across Europe enable optimisation and compliance. However, progress is limited by legacy systems, fragmented data, capability gaps and barriers to data sharing. The project Knowledgeable comprehensive and fully integrated smart solution for resilient, sustainable, and optimised transport operations (KEYSTONE (Official website of the project: https://www.keystone-project.com/ )) aims to contribute to a roadmap for the digital transformation of the European transport ecosystem by creating standardised, truly Plug and Play solutions that will bridge the gaps and pave the way towards this goal, regardless of the existing legacy systems. The project is a major step forward in current efforts to build data-driven operations capabilities by integrating existing data-driven platforms, services, and skill development solutions across a range of European stakeholders. In addition to its technology and management components, the project will provide policy recommendations to address shortages in data literacy and digital leadership, fostering collaboration between regulators, operators, and service providers to capitalise on data for the purpose of compliance. This paper provides an overview of the initial findings in the efforts by the KEYSTONE consortium to unify transport data for compliant operations across Europe, with particular emphasis on the current state of the art, interoperability challenges and requirements as perceived by key European stakeholders.

European Inland Waterway Transport (IWT) plays a crucial role in moving large volumes of cargo and goods across extensive inland water networks. It is a sustainable alternative that helps reduce road traffic emissions. In the context of climate change, IWT is both impacted by and contributes to environmental resilience. In this paper, we propose the application of ontology for decision-making in the context of climate change scenarios that could affect the IWT network. To achieve this objective, we have conceptualized an ontology, the so-called IWT2Onto, which models the IWT network as well as resilience and sustainability Key Performance Indicators (KPIs). We have used open data sources, such as EuRIS ( https://www.eurisportal.eu/ ), along with data coming from IWT partners to populate the ontology and the underlying Knowledge Graph with static and dynamic data. Finally, using an assessment framework, we demonstrate in a real-world scenario how our ontology-based approach can help monitor the IWT system via related KPIs and its potential to facilitate dynamic decision-making for IWT during flood scenarios. This integrated approach effectively demonstrates the use of advanced data-driven strategies in optimizing navigation and operational responses under challenging climate conditions.

The logistics and supply chain ecosystem undergoes continual transformation due to global economic shifts, growing demands for sustainability, the COVID-19 pandemic, and various unforeseen disruptions that can lead to detrimental operational and financial consequences and, in some cases, even loss of life. This study indicates that Greek entrepreneurs understand supply chain resilience in a slightly outdated way compared to other modern practices. Considering the information mentioned above, research on the concept of supply chain resilience and logistics services resilience was conducted. Additionally, an analysis of the existing knowledge on this topic in companies operating in the Greek network, with a particular focus on the factors that impact supply chain resilience. For this paper, an extensive review of relevant international literature was conducted, followed by a research study in domestic areas using questionnaires. Furthermore, experts were interviewed, and their responses were analyzed to analyze the results further. The methodology employed utilizes quantitative and qualitative methods, specifically focusing on the convergent parallel design. Purposive Sampling was used to select participants who could provide the most relevant and rich information for research purposes. The analysis results indicate that companies in the domestic market employ effective, reasonable strategies to ensure the resilience of their supply chain. These practices have seen notable improvement since the onset of the COVID-19 pandemic. Nevertheless, their supply chain resilience shielding, management, and measurement practices have significant space for improvement.

The Smart Mobility and Logistics Solutions Cluster constitutes the 1st collaboration effort of different types of involved bodies in the productive sector of the Greek economy in the fields of Transport and logistics. Its emphasis is on urban mobility and the distribution of “last mile” goods within cities. The purpose of the M&L Cluster is the development in cooperative forms of products and services that will meet the goals of the Cluster for smart mobility and logistics solutions on the one hand and the triple European goal of developing safe, sustainable and integrated transport on the other hand. This paper will focus on one of the ten products developed in this context, namely “Product 9 - Neutral Intelligent Logistics data hub” which aims at the implementation of a central, “neutral” supply chain data analysis node that includes the following functions: Real-time interfacing with telematics devices to obtain a wide range of data. Bidirectional interface with public and local government databases (where available) Automated Business Intelligence module to extract performance indicators and optimize the operation of the distribution network. Distribution network planning support module with the indicative example of site selection for lockers & microconsolidation centers. With the implementation of the data hub, all partners involved can work more closely together, better monitor transport alternatives and adapt them dynamically.

This paper explores the integration of the Physical Internet (PI) into the supply chain (SC) resilience literature, and proposes a protocol framework aligned with fundamental Internet principles to operationalize the PI. Unlike traditional hierarchical networks, the PI enables dynamic routing and collaboration, potentially increasing SC-resilience to disruptions. By adopting the TCP/IP protocol suite from the Internet, this study introduces protocols that address operational and resilience aspects of the PI. The analysis emphasizes the protocol's role in facilitating efficient and resilient SC-operations, and offers implications for improving SC-management in the context of the PI.

As road transport maintains its predominant role in the modal split of inland freight transport within the EU, heavy trucks emerge as a substantial contributor to the total ton-kilometres in road freight transport, constituting 78.9%. Despite demonstrating commendable volume performance, the industry faces several challenges, including a shortage of experienced truck drivers, an aging workforce, safety, security and connectivity challenges. In addition to the aforementioned factors, drivers engaged in long-haul trips must also consider the regulatory framework of EU concerning driving and rest times, as well as the unexpected delays occurring at different stages within a supply chain. To this end, a survey was undertaken, resulting in 38 completed questionnaires. The outcomes of the survey contribute to the formulation of innovative integrated services tailored for truck drivers and supply chain companies, aimed at enhancing their operational efficiency during journeys. These services could be used during their trips aligned with the initiative of establishing an extensive network of Safe and Secure Truck Parking Areas (SSTPAs) along the motorways within the Trans-European Transport Network (TEN-T) in Greece.

The paper examines opportunities for development of alternative food networks (AFNs) in Bulgaria in their essence of short production and distribution chains focusing on their contribution to sustainable rural development through climate-wise transition of transportation and social innovation. The concept of alternative food networks is considered in the context of its potential to overcome the most pressing problems in rural regions in Bulgaria nowadays connected to local businesses and community development, on one hand, and the climate change and business efficiency challenges in modern transport and business logistics on the other. The issue of local food and marketing is scrutinized by the point of view of the 4Cs model of marketing, namely customer, cost, convenience, and communication.The paper presents the main results of a study, implemented in the INVEST Regional Living Lab in Bulgaria under the research task of Alternative food chains and new business models. Alternative food networks are accepted as part of the sustainable agri-food systems of the future encouraging sustainable production and consumption and minimizing the impact of transportation both on price and climate, and particularly in their close connection to community development via environmental, business and social innovations. The study makes a proposal for a new model of AFNs in Bulgaria based on an online platform with a shared delivery transportation system.

Integrated Pest Management (IPM) offers a holistic approach to pest control that aligns with the principles of sustainability in agriculture and balances ecological integrity with crop productivity. This article explores the key role of IPM strategies in supporting sustainable agriculture by minimizing reliance on synthetic pesticides, preserving biodiversity, and enhancing ecosystem resilience. It provides an in-depth exploration of various IPM strategies including biological control, cultural practices, mechanical and physical control, chemical control, monitoring and surveillance, education and training, and ecosystem management, and their application in promoting sustainable agricultural practices. These strategies, when integrated synergistically, empower farmers to manage pest populations effectively while minimizing environmental impact and promoting long-term sustainability. We examine the effectiveness of IPM in enhancing crop productivity, conserving biodiversity, and supporting farmer livelihoods. Furthermore, we explore emerging technologies and practices that complement traditional IPM approaches, such as precision agriculture, biocontrol agents, and digital tools for pest monitoring. Scaling up IPM adoption globally is to address the challenges of food security, climate change, and environmental degradation, paving the way for sustainable agriculture.

The INVEST European University Alliance aims at shaping a more sustainable and responsible future across Europe. Sustainability and responsibility are the guiding principles in all the processes related to the alliance’s research, education, administration, and service to society. The key actions addressing the diverse, multi-professional and transdisciplinary group of researchers, educationalists, and practitioners in the field, aim at building competences and skills for a brighter future in all the partner regions. To make this real, the alliance has established a community of practice to frame, support and foster the systematic and strategic development of competences, skills, and actions.This study reports the research-based establishment process of the INVEST alliance’s Community of Practice (CoP) for sustainability. The paper first valorises the principles of CoP and its theoretical foundations. It then sheds light on the processes of building the key CoP elements: strategic planning process, and capacity building. Finally, it discusses, how the INVEST CoP aims to foster sustainability and responsibility holistically to promote more sustainable regional development throughout the alliance partner countries.This paper aims to enrich the conceptual discussion and long-term capacity-building process addressing sustainability and responsibility across European higher education and its regional stakeholders. This research also supports the European Union’s goal of increasing CoPs by giving valuable insight into CoPs in the context of higher education and European University Alliances.

Windbreaks, linear plantings of trees or shrubs, serve as vital components in reducing wind erosion, enhancing biodiversity, and augmenting agricultural productivity in rural landscapes. Despite their ecological and economic significance, their presence is declining due to intensified agricultural practices. This paper proposes a methodology to map windbreaks in Slovakia using remote sensing data and integrates information from the LANDSAT satellites. Novel methods, comprising image processing techniques and algorithms tailored to detect linear vegetation patterns characteristic of windbreaks, are developed, and evaluated for their effectiveness in identifying windbreak elements. Additionally, the study investigates the ecological roles of windbreaks in enhancing biodiversity conservation. Using publicly available data from airborne laser scanning and digital terrain models, the research aims to quantify windbreak characteristics such as length, width, optical transparency, functionality, and species composition. Open-source tools are utilized for spatial analysis, terrain measurements, and data validation. The paper highlights the importance of windbreaks in mitigating soil erosion, conserving water, and promoting biodiversity. It underscores the need for increased attention to the restoration and establishment of windbreaks, especially in agricultural areas, to counteract the adverse impacts of climate change and land degradation. Through the integration of ecosystem service indicators, the study provides insights into the multifunctionality and irreplaceable role of windbreaks in landscape management, particularly in the context of climate change adaptation.

The global pursuit of sustainable development has given rise to the concept of a green economy, emphasizing the integration of environmental conservation and economic prosperity. One crucial aspect of this paradigm shift is the transition to renewable and clean energy sources in the transportation sector. This scientific article delves into the challenges, opportunities, and advancements in incorporating green economy principles to drive the adoption of sustainable energy in transportation.

In today’s dynamic business environment, companies are increasingly recognizing the importance of integrating sustainability and resilience into their supply chains while adapting modern business models for effective sales and customer relationship management (CRM). This paper explores the interconnection between sustainable and resilient supply chains and traditional as well as modern business models for sales and CRM. Through a comprehensive review of existing literature, this article highlights the significance of aligning supply chain strategies with sales and CRM approaches to achieve long-term competitiveness and customer satisfaction. Strategies for integrating sustainability and resilience into supply chains are discussed, along with an analysis of traditional and modern business models for sales and CRM. Case studies and examples illustrate how companies can successfully implement these strategies to create value for stakeholders while mitigating risks and enhancing customer relationships.

Around 80% of global trade volumes are transported by ships. The shipping sector is responsible for approximately 2.89% of anthropogenic greenhouse gas emissions due to its prevailing dependency on fossil fuels. However, the tightening of environmental regulations urges shipping to shift to fossil-free energy sources, such as biofuels and synthetic fuels. In this paper, we analyze the sustainability of methanol, produced either from natural gas or biomass, and liquefied biogas. For this, we utilize a sustainability index combining environmental and economic indices. The environmental index demonstrates the environmental harms from emissions derived from producing and consuming the fuels. The economic index includes the fuels’ life-cycle costs. Our results reveal that biofuels’ environmental sustainability depends on how CO2 emissions are calculated during their life cycle. Burning biofuels produces CO2 emissions, but the emissions from biofuel production depend on the biomass source. Environmental regulations are not unanimous about treating CO2 emissions from biofuels: In the EU Emissions Trading System, if the biomass is from sustainable sources, CO2 emissions from biofuel consumption are considered zero, in contrast to IMO regulation. Moreover, the economic index is highly influenced by fuel prices, which are difficult to predict. With alternative fuels, the life-cycle perspective is especially important since emissions from production dominate more than with fossil fuels. Therefore, the importance of the holistic analysis of shipping fuels, which we conducted here, will increase.

This research paper offers an exploration of the techniques and processes involved in supporting an electrically powered boat for ferrying passengers, between Kameiros Skala in Rhodes and Chalki Island. The proposed boat aims to address the need for environmentally friendly transportation in this sector by incorporating an electric drive boat with onboard storage systems that draw its energy from onshore renewable energy production. The design incorporates technologies, effective propulsion systems, and considerations for passenger comfort and safety. One innovative aspect of this design involves establishing a charging system for the boat by using an existing photovoltaic park on Chalki Island. This collaboration between the boat and the photovoltaic park enhances sustainability and self-sufficiency within the transportation system. The paper delves into aspects such as integrating panels, storing battery power, hull design, navigation systems, and developing electric charging infrastructure. Special attention is given to the challenges and opportunities associated with this route. By providing an analysis of these methods and mechanisms, this paper contributes insights to sustainable maritime transportation by showcasing an integrated approach that utilizes renewable energy sources for both propulsion and charging purposes.

The MvI project aims to implement and examine the onshore supply of electricity and hydrogen to watercraft alongside land vehicles. The primary goals are to advise on how supply units across modes of transport should be designed to achieve synergy effects, cut costs, and enable a transition towards alternative drive technologies especially for inland shipping. The study specifies the various users’ infrastructure requirements for onshore power supply and compiles possible configurations based on available grid expansion. For examining the infrastructure, the test platform ELEKTRA is used. Designed as a towboat, it has an accumulator capacity of approximately 2.5 MWh and carries 750 kg of hydrogen in exchangeable Multi-Element-Gas-Containers (MEGCs). It is equipped with various power connections to test new charging technologies (via Marechal, DC) as well as using established connections in shipping (CEE and Powerlock, both AC). This enables the infrastructure to be used by the ELEKTRA and other commercially used inland vessels. Charging capacities of up to 350 kW will be available. Evaluation of the supply infrastructure takes place in Westhafen Berlin and Lüneburg which will enable the towboat to perform tours to Hamburg. Furthermore, various scenarios for the supply of hydrogen are being studied. Those are, next to others, the use of MEGCs. Additionally, business models to ensure the supply of inland shipping with energy sources are developed. Aiming to describe how ownership of the infrastructure can be designed and the resulting corresponding economic perspectives.

Member States, as well as most countries outside the EU, are concerned about environmental protection and measures for decreasing pollution, motivating researchers around the world to find solutions for decarbonization. One such solution may be the widespread use of hydrogen. The transport sector is one of the most difficult sectors to decarbonise, ranking first on GHG emitting sectors list. Vehicles using hydrogen as fuel to power their own propulsion systems are expected to be used more than those that work on electric batteries, ensuring the transition of the transport industry to a “green” future. Environmentally friendly technologies must overcome a number of challenges, an important issue being the safety in use. Hydrogen applications in the transport sector face challenging conditions, including very high pressures, extreme temperatures, and imminent fire and explosions risks. This is because H2 has an extremely low ignition energy, with much wider flammability limits compared to other fuel. As hydrogen refuelling station numbers are expected to increase in the comping years, special attention has to be granted for ensuring their safety in operation. Computational safety studies therefore represent a useful tool for preventing the occurrence of accidents which may lead to significant material damages or even to the loss of human lives. For modelling accidental releases and ignitions of hydrogen within a hydrogen refuelling station, specialized consequence modelling software for simulating the diffusion, jetfire and explosion of the gas has been used, the current article presenting the results and the main conclusions of the performed simulations.

This paper describes the international standard for the electric road system for the sustainable mobility and transportation for smart city and communities. The international standard is being created by ISO/TC268/SC2/WG2. The electric road system is particularly needed for long-haul transport battery powered electric vehicles. The framework, concept of operations (How roadside feeding electric road system can be configured and integrated in a sustainable mobility and transportation), and system components are explained.

In this study, the influencing factors of e-bus users’ overall satisfaction were investigated using the bus user satisfaction questionnaires. The study established the hypothetical relationships between overall satisfaction and the intention to continue using e-buses in the future and constructed an e-bus travel behaviour structural equation model. Through a direct questionnaire survey, the survey data of 394 e-bus users were obtained and verified for analysis. The results show that bus and bus-stop tangible, the operating indicators, safety and security, the perceived advanced technology application, and the perceived environmental performance have a positive impact on the overall satisfaction of the young e-bus user group. The study also revealed a positive association between customer satisfaction and intention to continue using e-buses in the future. From the young user’s point of view, this study plays a positive role in a more comprehensive understanding of the factors enhancing the application of e-buses. Meanwhile, it provides a strong basis for government departments, industry management departments and bus companies to formulate policies.

We present a new version of the BEST tool, namely BEST_CP, aimed at the estimation of the Charging Profiles (CP) of electric urban buses.Both the original BEST and the new version have been developed by ENEA, within the Electric System Research framework, since 2016.In the original version, BEST aimed at exploring the technical and economic feasibility to serve bus-lines by battery electric buses (BEB) instead of conventional ones (diesel and methane).In the current version, BEST_CP focuses on the estimation of the electric buses charging impacts on the electric grid, also representing a useful tool for recharge infrastructure sizing.Starting from data on the annual bus service scheduling, for each bus-line, the model selects the more convenient recharge solution among the three considered: only at depot, just on night-time (Arch. A); only at depot, both day and night-time (Arch. AB); both at depot, night-time, and terminus, daytime (Arch. B).A simulation of the recharge operations is performed hourly, considering six typical running days, in order to quantify the amount of required recharge power and its spatial and time distribution.The analysis is performed using GTFS data made available by the TPL companies for seasonal bus service, and climatological observations at the locations considered. A description of the new procedures for GTFS processing and subsequent fleet, batteries and charging stations sizing is provided, as well as for the estimate of the daily Charging Profiles at terminus and depot. Finally, the platform for a user-friendly application of BEST_CP is described along with the results obtained for the Rome case-study.

To measure the success of a research and development project and assess its impact, an evaluation methodology has to be established. The proposed methodology in the NextETRUCK project follows best practices in validation and draws on insights from previous support projects such as CONVERGE and FESTA. It outlines a set of research hypotheses and associated goals for different innovation aspects of the project, forming the basis for evaluation. Key elements of this evaluation plan include defining Key Performance Indicators (KPIs).A total of 28 KPIs have been identified, covering areas such as vehicle and charging performance, digital tools, driver/fleet operator experiences, and market/total cost of ownership considerations. These KPIs can be measured during the demonstration and digital twin operations, using both quantitative and qualitative measures. Objective data, subjective evaluations, and inputs such as vehicle data, questionnaires, and driver interviews can all contribute to the assessment. The evaluation plan takes a structured approach, detailing each KPI’s description, assessment methods, parameters, and necessary information to address potential risks and challenges during the evaluation phase.

For urban freight delivery trucks to switch to electric batteries, they would need to either need to operate at a short enough range that does not require recharging in the middle of a “single-charge shift”, or to deviate from their current tours to recharge en-route, which can be costly. However, limitations in data prevent policymakers from identifying the fraction of the market feasible for single charge shifts as the likely adopters. We propose using synthetic tours of trucks to identify this portion of the fleet for electrification. The framework is applied in a case study to a synthetic aggregate urban truck tour population in New York City to assess what portion of total freight routes can be delivered with electric trucks. Results suggest 64.6% percent of tours are electrifiable with the average tour consuming 45.2 kWh on a single charge. This scenario would lead to consumption of an extra 6.4 GWh/day of energy or a 4.5% increase for New York City. The most and least electrifiable industries are reported along with industries consuming the most kWh. Feasible operational cost conditions are established based on price per kWh versus price per gallon, added road damage due to the battery weight is assessed, and emission investment breakpoints are calculated based on CO2 emissions reductions from operations versus increases from battery construction.

One of the most relevant factors for the widespread adoption of battery electric vehicles is an effective recharge infrastructure, in terms of location, power and costs for users. This is an ambitious objective mainly in urban areas, where recharge networks can assume diverse alternative configurations. In such contexts, private and public infrastructure can overlap or have deficiencies, causing investment waste or supply shortages.Generally, surveys are powerful tools for investigating demand preferences and guiding offer development, mainly at its early stages.In Italy, electric mobility struggles to catch on, so we considered it useful to investigate Italian attitudes toward electric car recharging.With this aim, we carried out a first survey addressed to electric car early adopters, performed with the Revealed Preferences technique, and a second one addressed to potential electric car users, set on the Stated Preferences technique.Both surveys were mainly focused on urban context and daily mobility, with special attention on the choice of recharge location with respect to the stopping places (home, work, other destinations).This paper describes only the Stated Preference survey, which is more significant for the setting up and calibration of a behavioral model on electric car recharge in urban areas.Results on the representativeness of the sample are reported, as well as the charging behaviour expressed in different situations of battery level, recharge time, and costs.

The current era where living demands an accelerated digital transition mainly focused on encouraging a smarter, healthier, and more sustainable mobility, in all its dimensions – a must concern for the young generations. The convergence through several digital services and APP can be an attitudes and perception changer within the group of academic mobility users’, promoting a more sustainable and better mobility choices that impact on the academic user’s mobility routines. Thus, encouraging a global shift to shared and active mobility services and systems bringing significant contributions to environmental sustainability and, also, to users’ health. The Academic Mobility as a Service (AMaaS) provide a digital service with mobility alternatives to support the academic population geographically located in different faculty campuses and Higher Education Institutions (HEI). The AMaaS applied to a restrict group is helpful to test innovative transport solutions and its high cybersecurity vulnerabilities. Despite the shortage of AMaaS case studies and the lack of security reference, it is imperative that a cybersecurity by design is planned and included in AMaaS design. In this paper AMaaS critical cybersecurity challenges, and potential risks are discussed and AMaaS Security by Design framework is described.

Over the past decade, MaaS has gained traction among transport planners and policymakers as an evolving paradigm that consolidates diverse transportation options to cater to individual preferences under a unified system. Numerous studies have examined factors influencing MaaS adoption in developed countries using behavioural theories like the Theory of Planned Behaviour, Technology Acceptance Model, and Unified Theory of Acceptance and Use of Technology. In developing economies where cultural and social settings differ, the impact of these factors may vary significantly, limiting the generalizability of existing research findings. Based on the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2), this study establishes an analysis framework to assess factors influencing MaaS adoption intention in the Indian context. The study is conducted in Kochi, India, to elicit information from participants (n = 118) about their attitude towards MaaS. The factor analysis and linear regression identify five significant factors influencing MaaS adoption: ‘Technological Affinity’, ‘Utility’, ‘Social Influence’, ‘Mobility Assistance’, and ‘Monetary Gain’. The study findings provide insights for designing MaaS and mobility bundles, emphasising factors crucial for consideration in developing countries. Additionally, results shed light on existing transport infrastructure inefficiencies and the need for enhancements to boost MaaS adoption.

This study examines attitudes of Swedish transportation experts and stakeholders regarding Shared Autonomous Vehicles (SAVs) for public transport, juxtaposed with stakeholder perspectives from New South Wales, Australia. Through qualitative interviews with strategists, operators, academics, and regulators, we investigate the factors influencing societal acceptance and readiness for SAVs. The analysis reveals a complex landscape of regulatory environments, cultural readiness, and innovation challenges in public transit, emphasizing the nuanced interplay between technological advancement and societal norms. In Sweden, there is a notable emphasis on collaborative ethos and customer logic, highlighting the importance of aligning individual mobility behaviors with broader environmental objectives. This contrasted with the Australian results, where a deregulated market and the responsibility of transit authorities are seen as catalysts for enhancing mobility options. The study identifies’sharing anxiety’ as a significant barrier to SAV adoption, proposing targeted policy interventions such as promoting dynamic ride-pooling, tax incentives for shared mobility, and the development of standardized interfaces for on-demand transport services. Additionally, the research underscores the challenges of introducing SAVs in rural and sparsely populated areas, advocating for extended pilot programs to culturally establish sharing behavior, especially in areas with strong car dependency. By integrating insights from both Swedish and Australian contexts, this paper offers policy considerations aimed at fostering public acceptance and support for SAVs, contributing to the global discourse on sustainable mobility and the future of public transport.

The escalating challenges posed by urbanization and increased private car usage which result in environmental degradation and congestion have emphasized the critical need for sustainable urban mobility systems. There is a growing imperative to embrace eco-friendly alternatives, among which is autonomous urban transit. The penetration of the new systems in the travel market raises safety issues. This study addresses the issue of safety, as perceived by the travelers, and correlates it with the acceptance for using the various autonomous public transport modes.The research work involves a questionnaire survey which was used to collect knowledge, attitudes, intentions, and behaviors of travelers in regard to the safety related aspects of autonomous transportation. Participants’ perceptions were collected separately for metro, bus/trolley, tram, and urban rail, so as to identify possible differences owing to the operational characteristics of the alternative modes. Specific safety components of the respective autonomous vehicles were considered, which revealed the users’ preferences and in parallel the means for achieving higher acceptance, comfort, and market penetration, in using the new systems.

Cooperative, Connected and Automated Mobility (CCAM) has great potential to improve traffic efficiency and road safety and is expected to play an essential role in realizing Vision Zero and meeting global climate goals for the mobility sector, despite the continuously increasing traffic. The successful realization of the CCAM vision relies heavily on the advancement of both the physical and the digital infrastructure (PDI).In the physical realm, roadways and vehicles are evolving to become smart entities, fully equipped with sensors, cameras, and advanced computing capabilities. Simultaneously, in the digital infrastructure realm, vehicle-to-everything (V2X) real-time communication and edge computing enable novel CCAM services based on data fusion. In the near future, vehicles are expected to interact with all the elements of the urban environment and with intelligent traffic management systems.The envisioned role of PDI includes i) precise environment modelling based on a multitude of different data sources for enhanced resilience and ii) real-time traffic planning in challenging environments such as urban intersections. From monolithic vehicle-centric Advanced Driver-Assistance Systems (ADAS), we are moving to more distributed architectures with only parts of the information processing and storage being executed locally on the vehicle while data fusion is taking place on the edge, with ultra-reliable and low-latency connectivity being a key enabler.In this paper we provide an overview of the latest PDI enhancements implemented by the PoDIUM project and we analyze the resulting ecosystem, namely we identify all the involved actors and roles, their relationships and revenue streams.

This paper delves into the Cooperative Intelligent Transport Systems (C-ITS) architecture of the on-site pilot conducted in the city of Trikala, Greece, as part of the EU-funded project, IN2CCAM. The pilot tests and demonstrates innovative Cooperative, Connected, and Automated Mobility (CCAM) services through the deployment of autonomous vehicles (AVs) and their integration with a C-ITS platform. Featuring a fleet of autonomous electric minivans on a predefined route equipped with advanced smart digital infrastructure, this initiative aligns with the city’s vision to tackle congestion, promote the use of shared transport services, and enhance the equity of the local transport system. Furthermore, a Mobility as a Service (MaaS) mobile application enables the public to plan multimodal trips, integrating on-demand shared passenger transport services with AVs, public transport services, shared micromobility solutions, and active mobility, such as walking or cycling. The proposed C-ITS architecture includes: a) AV fleet management and monitoring, b) a Green Light Optimal Speed Advisory (GLOSA) functionality to achieve smoother and more fuel-efficient journeys, c) a traffic-based green wave system to contribute to high traffic efficiency by adjusting traffic signals according to real-time congestion levels, and d) C-ITS messages between the infrastructure and the AVs to alert about uncontrolled crossings of Vulnerable Road Users (VRUs). This paper aims to outline the architectural components of this pilot and discuss future work, which will include evaluating the feasibility, effectiveness, and societal impact of the proposed innovations in the local ecosystem of Trikala.

Existing traffic management solutions face limitations as they have not been designed to use latest technology developments and accommodate latest forms of transport, including connected and autonomous mobility, towards addressing resilience and seamless operations. Innovative Traffic Management Systems (ITMS), such as the one developed within FRONTIER project (*), satisfy this need to increase the efficiency of current traffic management systems and improve the resilience of transport systems. However, different factors such as technological, legal, data-privacy, financial and other factors could impact the deployment of new traffic management systems. This paper presents a SWOT analysis that has been conducted in three european cities (Athens, Antwerp and Oxford) to explore and analyse these factors. The cities were carefully selected to capture a wide spectrum of functionalities and support research outcomes which could be further adopted throughout Europe. Based on the results of this paper, ITMS offer a promising path to addressing mobility challenges in Europe, but they also come with various weaknesses and complexities that need to be managed to ensure their successful implementation. Technical support, robust funding mechanisms, and effective collaboration among stakeholders are crucial in overcoming these challenges.

This paper investigates the differences in the environmental and economic impacts of applying a prospective free-flow Open Road Tolling (ORT) system in Greece, compared with conventional tolling focusing on Road Freight Transport (RFT). The sector of RFT highlights the negative impact of frequent stops for toll payment: increased travel time, reduced road safety, high traffic accident risk, fuel consumption, air pollutant emissions, etc. This research includes a comprehensive international comparison of relevant systems, providing a global perspective on tolling practices. The environmental and economic impacts on a local scale are estimated, and, in addition, there is a rough estimation of the annual cost of fuel consumption of RFT due to the non-application of ORT in Greece, aiming to highlight the need for implementation of ORT in Greece. Only using RFT fuel consumption cost during the year 2017, while the diesel cost was much lower than today, and the same goes for the number of toll stations in Greek motorways, it was found that each year 15 million euros more are spent due to the absence of free-flow ORT in Greek motorways. This amount probably has already tripled.

The European Commission emphasizes mass transit system resilience for a successful shift to sustainable mobility, urging specific actions. Urban resilience, emphasizing public transport performance amid various hazards, prioritizes redundancy through network restructuring to enhance disruption resilience. This study aims to design efficient transit networks, while also enhancing resilience against link failures by maximizing alternative paths for passengers. In the multi-objective setting considered, the goal is to obtain non-dominated solutions, considering two distinct objectives: maximizing path redundancy and minimizing passenger inconvenience, captured by a weighted score of average travel time and transfer shares. To obtain high-quality results, this study leverages reinforcement learning (RL) and multi-objective Particle Swarm Optimization (MOPSO), under the novel concept of intelligent optimization, where a learning component is used to guide the search. The proposed MOQLPSO exploits an adaptive search mechanism, with particles acting as self-interested agents within the solution space, incorporating dominance rules within the RL reward function. Benchmarking against a naive MOPSO version on two literature-based networks reveals the proposed approach's superiority. Results highlight trade-offs between efficiency and resilience, demonstrating denser and higher-quality pareto fronts in less computational time. The study underscores the importance of the reward function and emphasizes benchmarking as crucial for advancing the proposed concept.

Smart Enforcement of Transport Operations (SETO) is a Horizons Europe project that supports digital transformation in transportation, including access to data of interest to regulators. The goal is to provide authorities with access to relevant data so that enforcement activities become more efficient for both the enforcer and the transporter. The concept is multi-modal and includes the design of an on-board unit for ships, like what is already available for trucks, which will store data about the skipper, journey, e-documents, etc.. This innovation will be tested in a Living Lab in Belgium. For roads, a key element in the enforcement process is the vehicle weight and technologies which allow for on-board vehicle self-weighing. This paper presents the concept of an on-board tamper-proof vehicle weighing solution. Truck axles are equipped with accelerometers whose signals are indirectly affected by the road profile and the vehicle weight. If the vehicle properties, including weight, are known, the road profile can be calculated. As many trucks pass over the same profile, it is possible to compare calculated profiles and to use this to back-calculate each vehicle weight. As the road profile is part of the calculation, it is difficult for any driver to tamper with the vehicle self-weighing system.

As cities Digital Twins (DT) blend the digital, physical, and human worlds, they offer a precise and trustworthy reference. They also enable stakeholders to evaluate the effects of planned interventions prior to investments and implementations. METACITIES is an Excellence Hub of Southeastern Europe, represented by three innovation ecosystems in Cyprus, Greece, and Bulgaria. Each ecosystem is Quadruple Helix Model-based and involves partners representing scientific, industrial, civic, and public sectors. They aim to collaboratively define and implement common digital Research and Innovation strategies, policies, and joint projects-pilots, coordinated for the growth of the entire Southeast European region as well as the benefit of the people living there and the stakeholders in the regional innovation ecosystems.A key expected outcome of METACITIES is the development and adoption of an Open Digital Twin framework (ODTF) that facilitates the collaborative development of Digital Twins of complementary future city domains, focusing on use cases with high social impact such at Smart Mobility, Energy Efficient Buildings and Urban Planning, while conducting a socio-techno-economic requirements analysis.In this paper, the strategic objectives, methodology, the quadruple helix model of collaboration of the Excellence Hub and the way these are applied to the digital transformation of the City’s mobility sector are presented. Aspects to be addressed include monitoring of traffic volume, identification and tracking of emergency incidents, real-time information and notifications on parking availability, etc.

Resilience-centric Smart, Green, Networked EU Inland Waterways (ReNEW) is a Horizons Europe project that aims to address IWT systems’ dynamicity, heterogeneity, and complexity as well as to develop strategies for making IWT systems smarter, greener, more sustainable, and climate-resilient. A Digital Twin (DT) is a powerful tool for modelling the complexity and interdependencies of complex systems, such as IWT systems. Data in digital twins can be represented by knowledge graphs (KG), which efficiently store information in a structured way and capture the complexity of the real world. Ontology-based knowledge graphs capture all entities within IWT systems hierarchically, allowing humans and machines to easily interpret and analyse the data. This paper introduces the concept of creating a probabilistic digital twin using Bayesian networks to account for uncertainty and forecast how the IWT system will respond to predicted and unexpected events. A Bayesian Network is a probabilistic graphical representation that combines expert belief alongside sensor data to model the relationship between the system’s entities. As the evidence changes, the model is updated to provide more accurate results. Risk and safety analyses are then performed to assess the reliability of IWT infrastructure.

Level of Service (LOS) is a metric that assesses the capacity and quality of traffic flow in a road or transportation system. It takes into account factors like speed, traffic density, delays, and driver comfort, and assigns them various levels to determine the level of traffic congestion or improvement. Different definitions of LOS are used for designing and planning, such as the widely used Highway Capacity Manual (HCM) or the German Handbuch zur Bemessung von Straßenanlagen (HBS). Realtime monitoring of LOS typically relies on detection infrastructure like loops or aerial monitoring, but both methods cannot be continuously employed in time and space.In this paper, we propose an online LOS monitoring service based on Vehicle-to-Everything (V2X) communication. We rely on the fact that connected mobility is becoming a reality, with more and more connected infrastructure available (through EU-project C-Roads and others) and connected vehicles on the street (mainly the Volkswagen brand). We use the Cooperative Awareness Message (CAM), which provides basic information about the position and dynamics of the vehicle, to generate Origin-Destination relations as well as determining queue length and delay.This information is combined with phase state information provided by the connected infrastructure using Signal Phase and Timing (SPAT) messages. The advantage of this approach is that only one V2X-receiver is required for monitoring. We will provide a description of the system as well as measurement results from an existing intersection.

In the face of mounting environmental concerns, air quality has become a pressing public health issue, necessitating advanced monitoring systems. This paper introduces R-TAMS, an innovative system designed to fulfil the need for precise air quality monitoring. Beyond real-time assessment, R-TAMS serves as a robust decision support tool for local authorities, navigating the intricate landscape of traffic emissions and environmental impacts in urban settings.Key functionalities encompass the real-time monitoring of diverse pollutants, including nitrogen oxides, carbon dioxide, carbon monoxide, hydrocarbons, and fine particles, originating from both exhaust and non-exhaust sources like brake and tire abrasion. R-TAMS also monitors real-time traffic noise and allows conducting prospective scenarios to evaluate the effectiveness of public policies, such as the establishment of low-emission zones and reduced speed limits areas.R-TAMS models were trained on data from real driving conditions, facilitating automated and replicable estimations of traffic flow and pollutant emissions. This replicability to any kind of territory allows automatic identification of critical areas that require priority interventions from the policy makers and local authorities.The paper further elucidates R-TAMS’ building blocks relying strongly on artificial intelligence, showcasing its innovative use for precise estimations, and contributing to a scalable solution adaptable to diverse local contexts.Future steps involve the seamless integration of atmospheric dispersion capabilities and air quality visualization maps, reinforcing R-TAMS as a holistic tool. This strategic expansion will provide comprehensive insights, enhancing its utility in addressing the urgent challenges posed by deteriorating air quality in contemporary urban environments.

The objective of this study is to develop a data-based mobility dashboard that monitors key aspects of mobility in the Athens Metropolitan Area (AMA), providing stakeholders with insights for assessing and developing mobility solutions, policies and measures. Traffic flow variations are observed, and ridership data are collected for different modes of public transport in order to understand mobility patterns from 2020 until today. In addition, relative indicators, such as travel delays regarding traffic, average travel speed, and the ratio of peak travel time to off-peak travel times are presented and estimated considering 15-day periods, with traffic data being reported in real-time. The dashboard, developed in a WebGIS environment, is comprised of a set of 11 critical routes which show high spatiotemporal traffic flow variations, while with the help of spatiotemporal visualizations, useful comparisons can be made in relation to public transport ridership. Using Google Traffic Maps, route travel times are collected and analyzed at 07:45, 08:45, 14:45 and 17:45 on weekdays. The dashboard is developed in such a way so to provide policymakers, practitioners, researchers, and the public with comprehensive and detailed information about mobility trends in the AMA, while further facilitating the decision-making process for policymakers by highlighting areas where targeted interventions may be necessary.

Quality of Service (QoS) is crucial for public transport (PT) systems, as it directly impacts user satisfaction. Customer Satisfaction Surveys (CSS) measure how satisfied PT users are with various QoS attributes and gather additional data on socioeconomic characteristics and trip details. However, these surveys are often costly, time-consuming, and limited in sample size. To ensure reliable responses and shorter completion times, only a few QoS attributes are usually included. This research explores whether social media can measure customer satisfaction with PT services. We review previous studies and analyze how big data from social media can be used in PT systems. Social media can gauge PT customer satisfaction using techniques like semantic analysis, sentiment analysis, and social network analysis. Benefits include low-cost, real-time data collection and insights into user-specific needs and sentiments. Our analysis shows that social media can provide valuable insights for PT services but should not replace traditional CSS due to limitations, particularly in sample representativeness. We propose a framework to enrich PT QoS measurement surveys with big social media data. This framework outlines the technological and operational requirements for using social media in QoS assessment. It highlights its potential for improving our understanding of gaps in PT QoS data, monitoring specific PT QoS attributes, and enhancing the efficiency of QoS measurement programs.