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    jsp.display-item.identifier=請使用永久網址來引用或連結此文件: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/118967

    题名: Modeling Time-Varying Variability and Reliability of Freeway Travel Time Using Functional Principal Component Analysis
    作者: Jeng-Min Chiou;Han-Tsung Liou;and Wan-Hui Chen
    关键词: Reliability;Density functional theory;Logic gates;Traffic control;Analytical models;Kernel;Estimation
    日期: 2021
    上传时间: 2020-07-22 12:10:41 (UTC+8)
    出版者: IEEE Transactions on Intelligent Transportation Systems
    摘要: This paper presents an aproach for modeling travel time variability and reliability that accounts for time-of-day effects on travel time variations. The conditional probability density functions of travel time in each specific period play a fundamental role in the modeling of time-varying variability and reliability. Nonparametric kernel density estimation is applied to travel time data, which enhances the flexibility and accuracy in accommodating travel time distributions under various complex traffic conditions. The proposed functional travel time density model (FTTDM) uses functional principal component analysis in kernel density function estimates for modeling and depicting time-varying variability through the dependence on the departure time of day. The resulting quantile estimates are used to obtain time-varying reliability, which considers the addition of extra time to the average or the median for an on-time arrival. This study uses linked travel time data of an electronic toll collection system to estimate route travel times in the Taiwan Freeway system. As illustrated in the data applications, the FTTDM effectively captures the time-varying feature of travel time variability and reliability, and the reliability indicators identify the unreliable departure time of day of a route.
    關聯: IEEE Transctions on Intelligent Transportation Systems 221(1), p.257-266
    DOI: 10.1109/TITS.2019.2956090
    显示于类别:[運輸管理學系暨研究所] 期刊論文


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