Prediction method of truck travel time in open pit mines
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Date
2023-09-18
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Type
Conference
Peer reviewed
Yes
Abstract
Aiming at the prediction of truck travel time in open pit mines, we established a prediction model based on long short-term memory(LSTM). This model fully accounts for 11 factors, including the nature of trucks, weather, road conditions, and driver’s behaviors, as well as the influence of neighbor road segments in the route on the current predicted road segment. The experiment shows that the error of the LSTM prediction model is significantly reduced compared with SVR and BP models. In addition, the maximum absolute mean error under different conditions is less than 12 seconds.
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Keywords
Travel Time Prediction, Open Pit Truck, LSTM
Citation
M. Ao, C. Li, and S. Yang. (2023) Prediction method of truck travel time in open pit mines based on LSTM model. Proceedings of the 42nd Chinese Control Conference (CCC), Tianjin, China, 2023, pp. 8651-8656