Paper
14 June 2023 The impact of conflict avoidance strategies of internal and external container trucks on the traffic scheduling in automated container terminals
Hao Chen, Xinglu Xu, Wenyuan Wang
Author Affiliations +
Proceedings Volume 12708, 3rd International Conference on Internet of Things and Smart City (IoTSC 2023); 127082R (2023) https://doi.org/10.1117/12.2683932
Event: 3rd International Conference on Internet of Things and Smart City (IoTSC 2023), 2023, Chongqing, China
Abstract
The current automated container terminal frequently completely isolates the external and internal container trucks in space for the safety of the vehicles. Physical isolation needs more space for roads and will reduce yard space. Furthermore, when a traditional container terminal is upgraded to an automated container terminal with physical isolation, the plan layout needs to be changed dramatically with substantial investment. With the development of technology, unmanned container trucks are gradually enabled in automated container terminals. It is necessary to ensure traffic safety in the absence of physical isolation in the port. To address path conflicts that arise when internal unmanned and external container trucks are combined in traffic, this article focuses on the impact of internal unmanned and external container truck avoidance strategies on traffic scheduling in automated container terminals. A mathematical model is built in this paper and solved by a genetic algorithm to study the influence of two avoidance methods: Internal Unmanned Container Truck First and External Container Truck First. The study's findings indicate a correlation between avoidance strategy benefits and drawbacks and the proportion of internal unmanned trucks to external container trucks.
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Hao Chen, Xinglu Xu, and Wenyuan Wang "The impact of conflict avoidance strategies of internal and external container trucks on the traffic scheduling in automated container terminals", Proc. SPIE 12708, 3rd International Conference on Internet of Things and Smart City (IoTSC 2023), 127082R (14 June 2023); https://doi.org/10.1117/12.2683932
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KEYWORDS
Safety

Transportation

Genetic algorithms

Mathematical modeling

Unmanned vehicles

Traffic management sensors

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