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Smart freight TranspOrt and logistics Research Methodologies

Periodic Reporting for period 1 - STORM (Smart freight TranspOrt and logistics Research Methodologies)

Reporting period: 2021-01-01 to 2022-06-30

The European Union (EU) transportation sector is still largely reliant on fossil fuels, the use of which accounts for a quarter of the EU’s greenhouse gas (GHG) emissions (1). In 2017, 93% of the energy consumption in transportation – road, rail, sea or air – was fossil fuel based. The freight sector accounts for the second largest share of transport emissions after personal transport and is forecasted to increase by 40% of 2030 (2). Widely acknowledged evidence and Paris 2015 Agreements recognize that business as usual is not an option.

The mission of STORM project is to will explore novel concepts for freight and logistics, and business models, innovative solutions based on zero emission vehicles, with the aim to support the transition of the transportation sector towards a sustainable freight future, both for private and public stakeholders (G2B, B2B, B2G, G2G) (3). This will be done by using unconventional data sources and through Big Data analytics and integration in order to better understand the behavioral aspects of the actors at both user and system levels, and to develop new generations of models to provide operators, stakeholders and policy makers with better information and decision support systems to ultimately achieve such transition at multiple levels.


Bioenergy Europe report, 2019

IPCC. (2014). AR5 – Working Group 3, Mitigation of Climate Change – Contribution of Working Group III. Cambridge University Press.G: 3.

Government, B: Business. Please see page 6-7 of the COM(2020) 66 final https://ec.europa.eu/info/sites/info/files/communication-european-strategy-data-19feb2020_en.pdf
Over the first 18 months STORM was focused on identifying future trends, knowledge needs, policy analysis needs and potential roles and possibilities for new modelling for freight transport in the EU through literature review, stakeholder interviews and interactions, as well as a prepared survey. The stakeholder consultation was important to collect and summarize various views from a stakeholder’s business and operational perspective, as well as on future opportunities, needs and green transition bottlenecks.

In terms of the outputs and insight of freight transport modelling, this review has found some important areas where information and insights are lacking:
• Plausible projections of how the different aspects of change in logistics will drive structural change in logistics.
• Scenario simulations that are based on the interlinked system changes of new digitalised logistics structures and zero-carbon energy in freight transport.
• Policy package simulations that will deliver sustainability: since freight transport is facing non-marginal change, models that can represent processes of structural change will be needed to assess potential points of influence on transport system changes.

Another focus point for the project was to perform a review of the state-of-the-art and the current knowledge gaps for Big Data analytics, methods and algorithms in the freight sector. It was reviewed also relevant applications and prepared a summary of challenges and opportunities of big data in the freight sector. It was found out that there are a variety of challenges hindering access and utilization of Big Data for freight transport applications due to its nature and unique characteristics, including, but not limited to, data collection, data ownership and accessibility, heterogeneity and standardization, storage, privacy and legal constraints, technical challenges and expertise, quality, validation and representativeness of the data.

The lack of awareness or interest in data and data-driven decision-making by senior managers can be a major organizational challenge. Privacy issues often forbid the usage for purposes other than explicitly mentioned in the agreement or contract with the users. Likewise, to share data collected by companies with third parties, individual non-disclosure agreements need to be negotiated which forms a major obstacle in data collaboration and exchange. Finally, we identify few areas for further research including data collection and preparation, data analytics and utilization, and applications to support decision-making categories.

Based on the identified knowledge gaps and needs, as well as data sources outcomes were utilized to empower the on-going work on future models and use case demonstration scenarios for future opportunities in freight and logistics.
STORM aims to meet the long-term EU objectives with a specific focus on electrification, and system and behavioural modelling, by identifying key challenges and opportunities in the transition process, so to outline the future horizons and provide insights on the decision supporting tools and the expected technological changes. Our proposal on the implementation of innovative sustainable freight concepts and novel tools will contribute in particular to the requirements and outlining of novel perspectives for next generation fleets composed of electric vehicles interacting with the related infrastructure and services.ns to various actors and stakeholders from both transport domains.
STORM Response to the expected impacts

•Generating knowledge through identification of freight and logistics knowledge gaps and needs. STORM reviews and identifies conceptual, methodological and technical needs for analysis, monitoring and assessment of novel and emerging freight/logistics solutions.
•Developing novel freight and logistics concepts to enable the deployment of innovative sustainable transport systems. STORM focuses on the evolution of conventional concepts by identifying new societal and technology drivers, industrial structures, and increased availability of various data sources. The research explores new concepts and scenarios through use cases enabling the sustainable deployment of innovative transport systems, logistics models and potentials to induce the growth of novel business models.
• Enabling capabilities for research and business. The generated knowledge from STORM will be exploited throughout targeted dissemination activities, in order to support the project outcomes uptake from business and research communities, as well as policy makers.
•Combining the knowledge and requirements for analysis of new transport concepts, as well as new concepts for data collection, management and exploitation to create new methods and tools for analysis of novel and disruptive freight/logistics frameworks including novel technological trends and technologies such as: Big Data and AI, Digitalization, IoT, Green transportation etc.
•STORM aims to develop and refine policy assessment frameworks and models and define new methods and models where current model and assessment methods cannot incorporate the critical features of new logistics transition concepts and business models.
•New strategic assessment tools will be developed, with the main objective to assess the adoption of new low-carbon transport technologies to deliver logistics services across the whole supply chain toward large-scale emission reductions.
•Defining the future directions for specific target groups throughout innovative transport policies e.g. research community – to cultivate and empower future ideas and industrial stakeholders and service providers to boost their growth and competitiveness by adopting the latest technologies and solutions.
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