郑州大学学报（理学版）2025，Vol.57Issue(6)：8-15,8.DOI:10.13705/j.issn.1671-6841.2024099
融合不确定性建模的行程时间与置信区间估计
Estimation of Travel Time and Confidence Interval with Uncertainty Modeling
摘要
Abstract
In response to the difficulty 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 overall routes and each local segment,as well as their uncertainties.Secondly,a multi-granular-ity quantile regression approach was adopted,considering both global and local features to provide accu-rate confidence interval estimation.The experimental results demonstrated that the proposed method could effectively quantify uncertainties while ensuring accuracy and offering reliable confidence intervals,there-by enhancing the usability and credibility of the results.关键词
行程时间估计/不确定性量化/置信区间/时空数据挖掘Key words
travel time estimation/uncertainty quantification/confidence interval/spatial-temporal data mining分类
信息技术与安全科学引用本文复制引用
申泽楷,郭晟楠,毛潇苇,吕聪康,贾宇欣,林友芳,万怀宇..融合不确定性建模的行程时间与置信区间估计[J].郑州大学学报（理学版）,2025,57(6):8-15,8.基金项目
国家自然科学基金青年基金项目(62202043) （62202043）
