Autonomous driving paper index
Visualizing the future of the trucking industry by identifying strategic driving variables through MICMAC analysis
One-line summary
Artificial intelligence, autonomous trucks, and other technologies are reshaping the trucking industry.
Engineering notes
Key topics: autonomous driving. See the paper for implementation details and experimental results.
Chinese explanation / 中文解读
中文解读待补充：本站会优先为端到端自动驾驶、BEV感知、3D目标检测、轨迹预测、路径规划、LiDAR感知等高价值论文补充中文说明。
Original abstract
Artificial intelligence, autonomous trucks, and other technologies are reshaping the trucking industry. Given trucking’s crucial role in global and domestic supply chains, understanding the strategic variables that will drive its evolution and exploring their interconnections is vital. Therefore, this study examines these strategic variables and aims to provide insights into the industry’s current landscape and potential scenarios by 2030. The study focuses on thirteen strategic variables across the political, economic, social, technological, legal, and environmental domains, using cross-impact matrix multiplication applied to a ranking (MICMAC) analysis to assess their interrelations and indirect influences. The findings reveal that adopting modern technologies, such as digitalization and artificial intelligence, will be highly influential in the future of trucking. Meanwhile, the companies’ economy will remain the most dependent variable in the system, and the influence of policy is expected to decrease into the 2030s. This research offers valuable insights for academics, policymakers, and industry stakeholders. The findings provide a roadmap for navigating industry pressures and supporting the transitions toward emerging technologies, decarbonization, and efficiency.
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