Towards a demand estimation adapted to hyperconnected transport systems in regional areas
Résumé
The transportation sector faces challenges in meeting sustainable development goals, especially in regional areas where transportation services are limited. The concept of the physical internet offers solutions to improve the efficiency and sustainability of hyperconnected transport systems in these areas. To achieve this, it is necessary to understand and predict transportation demand while considering the geographic and temporal characteristics of regional areas. Existing research has identified several factors that influence transportation demand, but the proposed models have limitations in terms of accuracy and incorporating additional data sources. To address these limitations, this research proposes a data-driven approach to predict demand for different market segments in hyperconnected regional transport systems. This approach should contribute to the production of demand profiles capable of adapting service offerings based on operational variability, allowing hyperconnected transport systems in regional areas to increase their agility and sustainability. This research will be developed in the context of the ECOTRAIN project, which aims to propose autonomous rail shuttles for the transportation of freight and passengers in regional areas.
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