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The Integrated Scheduling Optimization for Container Handling by Using Driverless Electric Truck in Automated Container Terminal

Cheng Hong, Yufang Guo, Yuhong Wang () and Tingting Li
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Cheng Hong: Faculty of Maritime and Transportation, Ningbo University, Ningbo 315211, China
Yufang Guo: Ningbo Shunyu Infrared Technology Co., Ltd., Ningbo 315400, China
Yuhong Wang: Faculty of Maritime and Transportation, Ningbo University, Ningbo 315211, China
Tingting Li: Faculty of Maritime and Transportation, Ningbo University, Ningbo 315211, China

Sustainability, 2023, vol. 15, issue 6, 1-22

Abstract: With the increasing maturity of automatic driving technology, the commercial value of driverless container trucks has been gradually excavated. Compared with social roads, the internal roads in the port area have certain practicing advantages. By taking into account the operational characteristics of the driverless electric container truck and the coordination of quay and yard cranes, this paper aims to explore the configuration and optimized scheduling model of the driverless electric container truck with the objective of minimizing overall energy consumption. The results show that the optimized allocation and scheduling of driverless electric trucks can minimize the total energy consumption of terminal operation without delaying the shipping schedule, and has obvious advantages over traditional manual driving diesel trucks and Automated Guided Vehicles in terms of operation efficiency, economy, and sociality. The results can also provide certain decision-making reference for the selection of horizontal transportation equipment and collaborative scheduling of multi-type loading and unloading equipment resources of container terminal operators.

Keywords: automated container terminal; driverless truck; resource allocation; scheduling optimization (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (1)

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