Cooperative and Interconnected Green delivery solutions towards an era of optimized zero emission last-mile Logistics

Información del proyecto

GREEN-LOG

Identificador del acuerdo de subvención: 101069892

DOI

10.3030/101069892

Fecha de la firma de la CE 16 Diciembre 2022

Fecha de inicio 1 Enero 2023

Fecha de finalización 30 Junio 2026

Financiado con arreglo a

• Climate, Energy and Mobility

Coste total

€ 7 436 120,50

Aportación de la UE

€ 6 260 158,00

Coordinado por

NETCOMPANY S.A.
Luxembourg

Periodic Reporting for period 1 - GREEN-LOG (Cooperative and Interconnected Green delivery solutions towards an era of optimized zero emission last-mile Logistics)

Período documentado: 2023-01-01 hasta 2024-06-30

Resumen del contexto y de los objetivos generales del proyecto

GREEN-LOG accelerates systemic changes to create last-mile delivery ecosystems that are economically, ecologically, and socially sustainable. It establishes city platforms made up of inclusive stakeholder Urban Living Labs to foster social innovation, and design/implement cutting-edge delivery solutions. The GREEN-LOG approach offers a cutting-edge simulation environment for scenario building combining different solutions to enable the integration of last-mile delivery interventions with the highest possible impact on environmental sustainability and traffic reduction, also considering their financial viability. GREEN-LOG offers LaaS platforms for interconnected city logistics, automated delivery concepts using autonomous vehicles and delivery droids, cargo-bike-based innovations for sustainable micro-consolidation, and multimodal parcel deliveries integrating public transportation. The solutions are supported by networked city logistics dataspaces that supply dynamic services for proactive ecosystem optimisation while respecting the interests of stakeholders. The approach is deployed and validated in five Urban Living Labs and three follower cities re involved in testing innovations’ transferability.

Trabajo realizado desde el comienzo del proyecto hasta el final del período abarcado por el informe y los principales resultados hasta la fecha

Technical and scientific achievements have been implemented in WP1, WP2 and WP3. These can be found below:

WP1 Key Achievements until M18 are the following:
• Knowledge base (stakeholders/solutions) creation.
• Living Labs establishment and trading zones development.
• Living Lab requirements identification.
• Use cases and service blueprints definition.
• Conceptual architecture development.
• Investigation of the cost structure, potential revenue streams and pricing strategies for the GREEN-LOG services.
• Development of initial prototype cooperative business models and arbitration models
• KPI list identification and validation.
• Initial development of impact assessment and transferability framework.

WP2 Key Achievements until M18
• The initial version of the city logistics data space, which is based on the CKAN framework, and includes several components from the FIWARE ecosystem.
• The initial version of the spatio-temporal demand prediction component.
• The initial version of the optimisation component for the deployment of the mobile depots, functional for the operations of the four Living Labs mentioned above.
• Three simulation models for the areas of Oxford, Barcelona and Athens.
• The first version of the interoperability framework that allows interaction between the simulation engine and external components.
• The detailed specification of the Augmented Intelligence Modelling Platform component.
• Successful delivery and submission of the D2.1.

WP3 Key Achievements until M18
• Successful delivery and submission of the D3.1.
• Successful development of LaaS Marketplace prototype (MVP), including key features, user roles and interaction between them (T3.1).
• Successful redefinition and scope of Task 3.2 Online asset and monitoring tool (BYOD).
• Successful requirement analysis, functional architecture of BYOD, and the development two out of three SDKs (T3.2).
• Initial version of NFE in a controlled environment, plotting possible visualization that will later be used by other GREEN-LOG components (DCT, LaaS Marketplace) (T3.3).
• The initial version of the dynamic (re-)routing component, with a focus on optimizing multiple criteria such as travel time, carbon emissions, and costs. (T3.4)
• Successful design and setup of the Last Mile Digital Control Tower, involving wireframe creation, functionality definition based on D3.1 outputs, and initial technical framework establishment with detailed architecture and data models for integration. (T3.5)

Avances que van más allá del estado de la técnica e impacto potencial esperado (incluida la repercusión socioeconómica y las implicaciones sociales más amplias del proyecto hasta la fecha)

Currently, GREEN-LOG aims to advance the state of the art in various scientific domains as follows: (i) AI and Optimisation Tools for green logistics by developing demand and supply prediction models and optimisation algorithms for location-based and resource allocation services. This will involve the development of novel statistical, machine learning, deep learning and Mixed-Integer Linear Program (MILP) approaches; (ii) Logistics as a Service (LaaS), by the qualitative evaluation of the concept in real-world applications, as well as the development of a logistics services marketplace with embedded dynamic pricing and nudging services for incorporating consumers’ behaviours, logistic service providers’ priorities and city authorities’ policy objectives in the overall concept, (iii) European Mobility Data Spaces, by the development of a last-mile logistics data space, aiming to harmonise and govern data sharing amongst various stakeholders across logistics supply chains, and (iv) Autonomous vehicles for last-mile logistics, by investigating and formalising the integration of autonomous bots with conventional delivery methods. Further enhancements to the functionality of the above innovations, as well as additional innovations are planned for the second half of the project.