Little progress has been made in recent years toward achieving a fully circular economy by 2050. Implementing circular urban supply chains is a major economic transformation that can only work if significant coordination problems between the actors involved are solved. On the one hand, this requires the implementation of efficient urban collection technologies, where process industries collaborate hand-in-hand with manufacturers, urban waste treatment, and city logistics specialists and are supported by digital solutions for visibility and planning. But on the other hand, it also requires implementing regional and urban ecosystems connected by innovative CO2-neutral circular city logistics systems smoothly and sustainably managing the regional flow of resources and data, often at large and with interfaces between industrial processes and private and private and public actors. What are relevant research questions from a city logistics perspective?
MULTIFILE
Municipalities play an important role in tackling city logistics related matters, having many instruments at hand. However, it is not self-evident that all municipalities use these instruments to their full potential. A method to measure city logistics performance of municipalities can help in creating awareness and guidance, to ultimately lead to a more sustainable environment for inhabitants and businesses. Subsequently, this research is focused on a maturity model as a tool to assess the maturity level of a municipality for its performance related city logistics process management. Various criteria for measuring city logistics performance are studied and based on that the model is populated through three focus fields (Technical, Social and Corporate, and Policy), branching out into six areas of development: Information and communication technology, urban logistics planning, Stakeholder communication, Public Private Partnerships, Subsidisation and incentivisation, and Regulations. The CL3M model was tested for three municipalities, namely, municipality of Utrecht, Den Bosch and Groningen. Through these maturity assessments it became evident the model required specificity complementary to the existing assessment interview, and thus a SWOT analysis should be added as a conclusion during the maturity assessment.
The demand for the transport of goods within the city is rising and with that the number of vans driving around. This has adverse effects on air quality, noise, safety and liveability in the city. LEFVs (Light Electric Freight Vehicles) offer a potential solution for this. There is already a lot of enthusiasm for the LEFVs and several companies have started offering the vehicles. Still many companies are hesitating to start and experience. New knowledge is needed of logistics concepts for the application of LEFVs. This paper shows the outcomes of eight case studies about what is needed to successfully deploy LEFVs for city logistics.
Drones have been verified as the camera of 2024 due to the enormous exponential growth in terms of the relevant technologies and applications such as smart agriculture, transportation, inspection, logistics, surveillance and interaction. Therefore, the commercial solutions to deploy drones in different working places have become a crucial demand for companies. Warehouses are one of the most promising industrial domains to utilize drones to automate different operations such as inventory scanning, goods transportation to the delivery lines, area monitoring on demand and so on. On the other hands, deploying drones (or even mobile robots) in such challenging environment needs to enable accurate state estimation in terms of position and orientation to allow autonomous navigation. This is because GPS signals are not available in warehouses due to the obstruction by the closed-sky areas and the signal deflection by structures. Vision-based positioning systems are the most promising techniques to achieve reliable position estimation in indoor environments. This is because of using low-cost sensors (cameras), the utilization of dense environmental features and the possibilities to operate in indoor/outdoor areas. Therefore, this proposal aims to address a crucial question for industrial applications with our industrial partners to explore limitations and develop solutions towards robust state estimation of drones in challenging environments such as warehouses and greenhouses. The results of this project will be used as the baseline to develop other navigation technologies towards full autonomous deployment of drones such as mapping, localization, docking and maneuvering to safely deploy drones in GPS-denied areas.
The developments of digitalization and automation in freight transport and logistics are expected to speed-up the realization of an adaptive, seamless, connected and sustainable logistics system. CATALYST determines the potential and impact of Connected Automated Transport (CAT) by testing and implementing solutions in a real-world environment. We experiment on smart yards and connected corridors, to answer research questions regarding supply chain integration, users, infrastructure, data and policy. Results are translated to overarching lessons on CAT implementations, and shared with potential users and related communities. This way, CATALYST helps logistic partners throughout the supply chain prepare for CAT and accelerates innovation.
The developments of digitalization and automation in freight transport and logistics are expected to speed-up the realization of an adaptive, seamless, connected and sustainable logistics system. CATALYST determines the potential and impact of Connected Automated Transport (CAT) by testing and implementing solutions in a real-world environment. We experiment on smart yards and connected corridors, to answer research questions regarding supply chain integration, users, infrastructure, data and policy. Results are translated to overarching lessons on CAT implementations, and shared with potential users and related communities. This way, CATALYST helps logistic partners throughout the supply chain prepare for CAT and accelerates innovation.
