The operation time of external trucks in a container terminal is one of port operation key performance
indicators concerned by port operators, external truck operators and related government authorities. With the
traffic big data combined with the operation characteristics of the container terminal, the system dynamics method
is used to build the simulation model of the operation system for external trucks. The simulation results of the
operation time of external trucks are consistent with the actual situation, which provides an effective way to
eliminate the “black box” of the operation time of the external trucks. The model can also be applied in multiple
scenarios by using the traffic big data, and the simulation results can be adopted by the relevant organizations.
DU Ye1 (杜晔), ZHAO Yifei2 (赵一飞), GAO Deyi1 (高德毅)
. Predictive Simulation of External Truck Operation Time in a
Container Terminal Based on Traffic Big Data[J]. Journal of Shanghai Jiaotong University(Science), 2024
, 29(5)
: 801
-808
.
DOI: 10.1007/s12204-022-2415-8
[1] HAN X L. Resources allocation in container terminal charge/discharge operation [D]. Shanghai: Shanghai Maritime University, 2005 (in Chinese).
[2] KAPLAN R S, ANDERSON S. Time-driven activity based costing: A simpler and more powerful path to higher profits [M]. Boston: Harvard Business School Press, 2007.
[3] PHAN M H, KIM K H. Collaborative truck scheduling and appointments for trucking companies and container terminals [J]. Transportation Research Part B: Methodological, 2016, 86: 37-50.
[4] TENG T. Truck arrival volume prediction method research of container terminals [D]. Dalian: Dalian Maritime University, 2017 (in Chinese).
[5] SHAO Q Q, JIN Z H, XING L. Simulation optimization of consolidation and configuration in container terminals based on cooperative appointment [J]. Journal of Transportation Systems Engineering and Information Technology, 2016, 16(4): 217-224 (in Chinese).
[6] TORKJAZI M, HUYNH N, SHIRI S. Truck appointment systems considering impact to drayage truck tours [J]. Transportation Research Part E: Logistics and Transportation Review, 2018, 116: 208-228.
[7] NADI A L, SHARMA S, SNELDER M, et al. Shortterm prediction of outbound truck traffic from the exchange of information in logistics hubs: A case study for the port of Rotterdam [J]. Transportation Research Part C : Emerging Technologies, 2021, 127: 103111.
[8] DU Y, ZHAO Y F. Classification and prediction of social container trucks in container terminal by decision tree method [J]. Industrial Engineering and Management, 2021, 26(1): 183-190 (in Chinese).
[9] WANG J F, LU H P, PENG H. System dynamics model of urban transportation system and its application [J]. Journal of Transportation Systems Engineering and Information Technology, 2008, 8(3): 83-89 (in Chinese).
[10] ZHAO P. Research on the allocation of resources for the container terminal based on system dynamics [D]. Dalian: Dalian Maritime University, 2012 (in Chinese).