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Leveraging AI for Sustainable Freight Transportation: Survey Insights from Moroccan Transport Companies

20251 citationOpen accessIbn Tofail University

Abstract

The global freight transportation industry has experienced exponential growth, significantly contributing to economic development. However, this expansion has also led to considerable environmental challenges, particularly due to the sector’s dependence on fossil fuels and inefficient logistical practices, resulting in high carbon emissions, air pollution, noise pollution, and resource depletion. The complex problems facing the freight transportation sector are directly impacting several United Nations Sustainable Development Goals (SDGs), particularly SDG 2, SDG 3, SDG 7, SDG 9, SDG 11, SDG 12, and SDG 13. This study addresses these challenges by first examining the direct contribution of sustainable freight transportation to the United Nations Sustainable Development Goals (SDGs). Building on this foundation, the paper explores the transformative potential of artificial intelligence (AI) to enhance sustainability in freight transportation. Focusing on advanced analytics, predictive modeling, and real-time optimization, AI provides opportunities to improve route planning, energy efficiency, and emission reduction, while supporting more resilient and sustainable logistics systems. The paper introduces a holistic framework, integrating AI seamlessly throughout the entire freight logistics process. To contextualize these insights, an empirical survey was conducted among Moroccan freight transportation companies, highlighting current practices, the perceived effectiveness of AI adoption, and the level of confidence in achieving long-term carbon neutrality targets. Finally, the paper introduces a practical framework for integrating AI into freight transportation systems, aligning technological innovation with sustainability goals, and offering actionable guidance for both industry stakeholders and policymakers.

Research topics

  • Urban and Freight Transport Logistics
  • Maritime Ports and Logistics
  • Supply Chain Resilience and Risk Management

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DOI: 10.3390/su172310628

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