Autonomous port management based AGV path planning and optimization via an ensemble reinforcement learning framework

X Chen, S Liu, J Zhao, H Wu, J Xian… - Ocean & Coastal …, 2024 - Elsevier
The rapid development of shipping trade pushes automated container terminals toward the
direction of intelligence, safety and efficiency. In particular, the formulation of AGV …

Exploring the factors affecting the performance of shipping companies based on a panel data model: A perspective of antitrust exemption and shipping alliances

G Xiao, T Wang, W Shang, Y Shu, SA Biancardo… - Ocean & Coastal …, 2024 - Elsevier
Globally, some large shipping companies have started large-scale joint ventures to seek
future development and cooperation while seizing the opportunities of the times. Meanwhile …

Optimizing anti-collision strategy for MASS: A safe reinforcement learning approach to improve maritime traffic safety

C Wang, X Zhang, H Gao, M Bashir, H Li… - Ocean & Coastal …, 2024 - Elsevier
Maritime autonomous surface ships (MASS) promise enhanced efficiency, reduced human
errors, and to improve maritime traffic safety. However, MASS navigation in complex …

Data-driven approach for port resilience evaluation

B Gu, J Liu, X Ye, Y Gong, J Chen - Transportation Research Part E …, 2024 - Elsevier
As pivotal nodes in international trade, ports have faced unprecedented challenges,
particularly in the context of the COVID-19 pandemic. From the perspective of port …

Port Congestion and Urban Particulate Matter Concentration: A Machine Learning Based Study

M Su, J Li, Z Su, W Kim - Available at SSRN 4853508 - papers.ssrn.com
Port congestion has become a critical transportation issue that port cities urgently need to
address. More importantly, there has been limited research focusing on the impact of port …