融合不确定性建模的行程时间与置信区间估计

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中图分类号：TP391 文献标志码：A 文章编号：1671-6841（2025）06-0008-08

DOI： 10. 13705/j. issn.1671-6841. 2024099

Abstract ： In response to the diffculty of uncertainty quantification for travel time estimation in intelligent transportation systems，a global and local uncertainty-aware travel time estimation （GLUTTE）method Was proposed.Firstly，a multi-task learning strategy was employed to model the travel time relationship between overallroutes and each local segment，as well as their uncertainties. Secondly，a multi-granularity quantile regression approach was adopted，considering both global and local features to provide accurate confidence interval estimation.The experimental results demonstrated that the proposed method could effectively quantify uncertainties while ensuring accuracy and ofering reliable confidence intervals，therebyenhancing the usability and credibility of the results.

Key Words ： travel time estimation；uncertainty quantification；confidence interval; spatial-temporal data mining

0 引言

行程时间估计（travel timeestimation，TTE）任务是根据给定路线和出发时刻预测行程时间。（剩余13035字）