GreenTwin: Green digital twin with artificial intelligence for CO2-saving cooperative mobility & logistics in rural areas

 

Mobile traffic is a major contributor to CO2 emissions in Germany. Above all, traffic, which is particularly generated in logistics, must be reduced to ensure greatly reduced CO2 consumption.

The GreenTwin project is dedicated to the development of sustainable regional logistics and supply for rural areas in the last mile. The project thus addresses in particular the CO2 source caused by private and business trips on the last mile in rural areas. There is great potential for improvement, as rural areas are heavily dependent on cars. As an example, we would like to investigate this problem in a model region Birkenfeld - Trier, to subsequently transfer the results to other rural regions. The heavy commuting and car traffic concerns trips to towns with shopping facilities, supermarkets and gastronomy, as well as post office or pharmacy. Food deliveries could particularly improve the supply situation of people with limited mobility and reduce CO2 emissions from car journeys. At the same time, we want to maintain and improve the quality of life, work and stay in rural areas. Regionalization and the promotion of regional production and logistics networks are important building blocks here, especially in rural areas. The marketplace we envisage based on GreenTwin is intended to bundle regional products and logistics in a CO2-saving way and thus has great scaling effects.

The team of the Chair of Communication Science ,HCIC Prof. Ziefle, empirically collect user requirements. This includes estimations of problem perception and a generation of needs for the acceptance of solution approaches, such as adigital marketplace, combined with micro-hub. In order to obtain a generalisable and independent assessment, a census-representative survey will be conducted, which allow to estimate perceived advantages and disadvantages of the digital marketplace and associated services. To understand the local acceptance for such requirements, interviews with different stakeholders will be conducted to map local narratives.