About
Concept
The European freight Transport and Logistics (T&L) industry is undergoing an enormous shift into a new era, fueled by digitalization and technology innovations, presenting prospects for new business models and zero-emission freight transport. Technology innovations have been implemented separately across various transportation modes and sectors, often without incorporating a Human-in-Loop design approach. This approach results in gaps and disconnections in operations. Therefore, a comprehensive strategy guiding the integration of automation technologies is crucial. It necessitates efforts towards standardization, collaboration, and policy coordination to ensure seamless operation and interaction across different systems and sectors.
To address this challenge, AUTOSUP will support the smooth advancement of automation levels in multimodal hubs, which are crucial components of logistics networks. The Physical Internet (PI) is the perfect paradigm towards seamless multimodal automatic freight transport by interconnecting diverse and independent logistic networks into a common open logistics network. Nodes, i.e. the Hubs and Terminals of a multimodal logistics network, are one of the most complex parts of the PI concept as their role and functionality determine the efficiency and environmental impact of the whole PI network. Aiming to increase the PI node readiness, AUTOSUP will advance the following three autonomy factors:
- the level of automation integrated into its operations (Hub level )
- the level of connectivity (physical transport infrastructures like roads and ICT communications connectivity), operations digitalisation and information sharing
- the level of their operational interconnection (from a collaboration perspective) with other nodes (Network Level )
In this direction, AUTOSUP will identify the strain points, improve the links between nodes and hubs and will run alternative simulation scenarios towards identifying the parameters that optimise the operations of the network considering technological, operational, regulatory and governance aspects. This will be achieved through the development of Digital Twin (DT) models of automated Supply Chains (SC), integrated in an open, ready-to-use data-driven Decision Support System (DSS).
Objectives
- Define automation requirements for seamless multimodal automatic freight transport
- Empower T&L stakeholders with an open, ready-to-use DSS and customisable DT model of autonomous SCs, to help them implement and deploy automated processes and solutions for logistics and multimodal freight transport.
- Design new operational, governance and organisational change management models for autonomous SCs logistics that incentivise cross-mode collaboration and reduce investment costs.
- Validate operational and cost efficiencies of solutions and evaluate user acceptance in two multimodal Living Hubs via feasibility analysis, impact assessment and the engagement of representative stakeholder communities.
- Establish a strategic and cohesive alliance and thematic working group (TG) for the alignment of multimodal automation adoption roadmaps across rail, road, aviation, waterborne and alternative innovative modes of transport.
WPs
WP1 will
(a) Define the state of play of automation technology enablers in different subsystems of intermodal transport and intermodal links. Map and assess the individual transportation modes automation roadmaps and their interdependencies and classify logistics automation technologies,
(b) Specify the intermodal logistics systems and operations automation requirements in terms of strategy, business, functional, digital, and social perspectives. Map the requirements for the seamless automation of T&L, from the user’s point of view, towards fully covering end-to end logistics operations.
(c) Further detail use case scenarios and develop a validation methodology with performance indicators/metrics, based on the requirements gathered and the automation roadmaps.
WP2 aims to
(a) Develop DTs for the L-Hubs, comprising models related to multimodal freight flows and operational processes with the aim of supporting decision-making. The DT models will cover the use case scenarios requirements elicited in T1.3, serving as a virtual representation of the L-Hub logistics ecosystem including transport means, infrastructure, processes, geography etc. encompassing all transport modes and covering logistics operations.
(b) Deliver a robust and user-friendly DSS functioning as a dynamic simulation platform that will support feasibility studies and decision-making in the context of operational automation. It will integrate operational data and use advanced simulation techniques to provide actionable insights into various automation scenarios. It will enable logistics operators to make informed decisions about the targeted LoA for their Hub, and plan the introduction of new automation optimisation strategies.
(c) Generalise the L-Hubs DT models as a reusable reference DT model for autonomous SCs, encompassing all transport modes, ready to be used for future use cases beyond AUTOSUP.
WP3 aims to:
(a) Identify strategies to lower the economic barriers of adopting automation-driven innovations in freight transport; simplify decision making especially when a variety of players in the value chain are involved, and thereby accelerate investments.
(b) Generate viable and enticing business models, and identify market positioning of promising and tested innovations, forming ambitious exploitation pathways.
(c) Outline a PI governance model to address the challenges stemming from automation.
(d) Validate the L-Hubs results, providing insights into horizontal collaboration and intermodal aggregation processes.
WP4 aims to
(a) define and develop communication strategies targeting all relevant stakeholders,
(b) propagate significant engaging media content to maximise the project visibility and reach,
(c) develop policy guidelines for infrastructure managers, governmental agencies, and policymakers to assist them develop informed strategies,
(d) maximize the reach of AUTOSUP messages and outcomes, engaging the Forum of Stakeholders and Thematic Group,
(e) liaise with relevant EU projects and initiatives to increase visibility and to create synergies,
(f) develop a adoption roadmap with practical guidelines to support the transition to autonomous PI SCs.
WP5 will
(a) Guarantee efficient project management and teamwork among partners,
(b) Perform quality assurance and risk assessment activities to ensure outputs and deliverables meet their objectives, are of the highest quality, respect the agreed time, effort and resource planning and provide agile risk mitigation actions when needed;
(c) Monitor equity and ethics issues and enforce gender equality procedures,
(d) assure FAIR principles application in the project’s exchanged and generated data.