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Scientific paper ID 2677 : 2025/4
ANALYSIS OF THE ADDED VALUE OF DIGITAL TRANSPORT EXCHANGES: FOCUS ON ARTIFICIAL INTELLIGENCE APPLICATIONS AND EU POLICIES
Svetoslav Marinov The rapid digitalization of the transport sector, driven by the development of artificial intelligence, is transforming traditional supply chain management models. In the context of the European Union, where sustainability and digital transformation are key priorities, examining the added value of AI in transport exchanges appears crucial for achieving the goals of the Green Deal. Transport exchanges have become a critical element of modern logistics and passenger processes, thanks to the opportunities for optimization, transparency, and automation through artificial intelligence (AI). These platforms connect those seeking and offering transport services, using algorithms for dynamic pricing, automatic matching of goods and vehicles, and strategic planning of freight vehicle management through IoT sensors. In the European Union (EU), these technologies are supported by policies such as the ”EU Digital Strategy” and the ”Green Deal,” which aim to reduce the carbon footprint of transport.
дигитализация на транспорта добавена стойност изкуствен интелект (AI)digitalization of transport added value artificial intelligence (AI)Svetoslav Marinov BIBLIOGRAPHY [1].European Parliament (2024). AI Act: Ethical Implications for Transport. [2].European Commission (2024). Horizon Europe Work Programme 2023–2024: Climate, Energy and Mobility. [3].European Environment Agency (2023). Digital Freight Platforms and CO₂ Emissions. [4].European Commission (2023). AI in Transport: Challenges and Opportunities. [5].European Commission (2021). Digital Transformation in Transport. [6].McKinsey (2023). The Future of AI in EU Transport Policy. [7].McKinsey & Company (2023). AI in Logistics: Cutting Costs and Emissions. [8].McKinsey (2023). Regulatory Fragmentation in EU Logistics. [9].McKinsey (2024). The Future of Autonomous Freight. [10].EU AI Act (2024). Regulation on Artificial Intelligence in Transport. [11].DHL (2023). AI in Logistics: Efficiency Gains and Cost Reduction. [12].CEF Transport Annual Report (2023). Digital Infrastructure Projects. [13].ENISA (2023). Cybersecurity Risks in Digital Freight Platforms. [14].Nature Machine Intelligence (2023). Deep Learning for Predictive Maintenance. [15].MaaS Global (2023). Impact of MaaS on Rural Mobility. [16].BlaBlaCar (2023). Data Bias in Ride-Sharing Algorithms. [17].Transportation Research Part A (2022). Impact of Digital Freight Exchanges on Empty Mileage. |