Title: Minimising yard congestion in container ports with autonomous transportation vehicles

Authors: Jeong-Hwa Lee; Dong-Hyun Kang; Hoon Lee; Min-Chan Kim; Tae-Sun Yu

Addresses: Department of Industrial and Data Engineering, Pukyong National University, Nam-gu, Busan, South Korea ' Department of Industrial and Data Engineering, Pukyong National University, Nam-gu, Busan, South Korea ' Total Soft Bank Ltd., Haeundae-gu, Busan, South Korea ' Department of Industrial and Systems Engineering, Korea Advanced Institute of Science and Technology (KAIST), Yuseong-gu, Daejeon, South Korea ' Department of Industrial and Data Engineering, Pukyong National University, Nam-gu, Busan, South Korea

Abstract: We examine operational-level port optimisation models with an objective of improving the transportation efficiency of autonomous yard trucks. We aim to provide managerial insights into how job assignment and path finding decisions affect the operational efficiency of transportation resources in the presence of yard congestion. Through this research we assess whether an alternative detouring method can surpass conventional vehicle optimisation methods based on the shortest path approach. Furthermore, we develop a physics-based port digital twin environment to precisely measure and quantify yard congestion induced by the spatial interference among transportation vehicles. We also introduce a modified network flow model that facilitates the identification of a vehicle operational schedule to minimise yard congestion. [Submitted: 26 September 2024; Accepted: 6 January 2025]

Keywords: port optimisation; autonomous yard trucks; AYTs; yard congestion; port digital twin; network model.

DOI: 10.1504/EJIE.2026.155546

European Journal of Industrial Engineering, 2026 Vol.22 No.1, pp.53 - 84

Received: 26 Sep 2024
Accepted: 06 Jan 2025
Published online: 05 Aug 2026 *

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