Practical approach for travel time estimation from point traffic detector data

被引:18
|
作者
Shen, Luou [1 ]
Hadi, Mohammed [2 ]
机构
[1] S China Univ Technol, Sch Civil & Transportat Engn, Dept Transportat Engn, Guangzhou 510641, Guangdong, Peoples R China
[2] Florida Int Univ, Coll Engn & Comp, Dept Civil & Environm Engn, Miami, FL 33174 USA
关键词
travel time estimation; trajectory method; traffic detector; data filling; speed transformation; SINGLE-LOOP DETECTORS; MISSING DATA; DUAL-LOOP;
D O I
10.1002/atr.180
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Accurate estimation of travel time is critical to the success of advanced traffic management systems and advanced traveler information systems. Travel time estimation also provides basic data support for travel time reliability research, which is being recognized as an important performance measure of the transportation system. This paper investigates a number of methods to address the three major issues associated with travel time estimation from point traffic detector data: data filling for missing or error data, speed transformation from time-mean speed to space-mean speed, and travel time estimation that converts the speeds recorded at detector locations to travel time along the highway segment. The case study results show that the spatial and temporal interpolation of missing data and the transformation to space-mean speed improve the accuracy of the estimates of travel time. The results also indicate that the piecewise constant-acceleration-based method developed in this study and the average speed method produce better results than the other three methods proposed in previous studies. Copyright (c) 2011 John Wiley & Sons, Ltd.
引用
收藏
页码:526 / 535
页数:10
相关论文
共 50 条
  • [1] Improved Flow-Based Travel Time Estimation Method from Point Detector Data for Freeways
    Vanajakshi, Lelitha D.
    Williams, Billy M.
    Rilett, Laurence R.
    JOURNAL OF TRANSPORTATION ENGINEERING, 2009, 135 (01) : 26 - 36
  • [2] A travel time estimation algorithm based on point and interval detector data over the national highway section
    Kim, Sunghyun
    Lim, Kangwon
    Lee, Youngin
    MUE: 2007 INTERNATIONAL CONFERENCE ON MULTIMEDIA AND UBIQUITOUS ENGINEERING, PROCEEDINGS, 2007, : 459 - +
  • [3] Travel time estimation from sparse floating car data with consistent path inference: A fixed point approach
    Rahmani, Mahmood
    Koutsopoulos, Haris N.
    Jenelius, Erik
    TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES, 2017, 85 : 628 - 643
  • [4] Estimation of the time-dependency of values of travel time and its reliability from loop detector data
    Liu, Henry X.
    He, Xiaozheng
    Recker, Will
    TRANSPORTATION RESEARCH PART B-METHODOLOGICAL, 2007, 41 (04) : 448 - 461
  • [5] Travel time estimation with correlation analysis of single loop detector data
    Guo, Huairui
    Jin, Jionghua
    ARTIFICIAL INTELLIGENCE AND ADVANCED COMPUTING APPLICATIONS, 2006, (1968): : 10 - 19
  • [6] Travel Time Estimation Using Freeway Point Detector Data Based on Evolving Fuzzy Neural Inference System
    Tang, Jinjun
    Zou, Yajie
    Ash, John
    Zhang, Shen
    Liu, Fang
    Wang, Yinhai
    PLOS ONE, 2016, 11 (02):
  • [7] Calculation of travel time variability from loop detector data
    Oh, Jun-Seok
    Chung, Younshik
    TRAFFIC AND URBAN DATA, 2006, (1945): : 12 - 23
  • [8] Urban network travel time estimation from stop-line loop detector data and signal controller data
    Bhaskar, A.
    Chung, E.
    Kuwahara, M.
    de Mouzon, O.
    Dumont, A. -G.
    URBAN TRANSPORT XIII: URBAN TRANSPORT AND THE ENVIRONMENT IN THE 21ST CENTURY, 2007, 96 : 147 - +
  • [9] Estimation of Travel Time from Taxi GPS Data
    Lee, Kelvin
    Prokhorchuk, Anatolii
    Dauwels, Justin
    Jaillet, Patrick
    2017 IEEE SYMPOSIUM SERIES ON COMPUTATIONAL INTELLIGENCE (SSCI), 2017,
  • [10] Sparse Travel Time Estimation from Streaming Data
    Jabari, Saif Eddin
    Freris, Nikolaos M.
    Dilip, Deepthi Mary
    TRANSPORTATION SCIENCE, 2020, 54 (01) : 1 - 20