Revised approach to assessing traffic speed deflectometer data and field validation of deflection bowl predictions

被引:53
|
作者
Muller, Wayne B. [1 ,2 ]
Roberts, Jon [3 ]
机构
[1] Queensland Dept Transport & Main Rd, Toowoomba, Qld 4350, Australia
[2] Univ Queensland, Sch Civil Engn, Brisbane, Qld 4072, Australia
[3] ARRB Grp Ltd, Vermont South, Vic 3133, Australia
关键词
pavement deflection; traffic speed deflectometer; falling weight deflectometer;
D O I
10.1080/10298436.2012.715646
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
This study presents a revised approach to conceptualising and analysing data from the traffic speed deflectometer (TSD) which enables full deflection bowl predictions. The approach was successfully applied to TSD surface velocity measurements collected at seven test sites as part of recent Australian trials. More than 1500 deflection bowls produced from the TSD data were validated against approximately 600 40- and 50-kN falling weight deflectometer (FWD) deflection bowl profiles. Overall, the results showed a clear correlation between the shape and magnitude of deflection bowls predicted by both methods. Estimates of maximum deflection (d(0)) and structural curvature index (SCI300) from both methods were also compared, showing a strong correlation. The results suggest that the TSD device has significant potential to be used to collect measurements of pavement deflection bowls at highway speeds which are comparable with FWD deflection bowl measurements.
引用
收藏
页码:388 / 402
页数:15
相关论文
共 50 条
  • [31] Field and Numerical Evaluation of Traffic Speed Surface Deflection Measurements to Estimate Load-induced Fatigue Response
    Nasimifar, M.
    Siddharthan, R. V.
    Thyagarajan, S.
    Motamed, R.
    JOURNAL OF TESTING AND EVALUATION, 2017, 45 (05) : 1702 - 1712
  • [32] A data-driven traffic shockwave speed detection approach based on vehicle trajectories data
    Yang, Kaitai
    Yang, Hanyi
    Du, Lili
    JOURNAL OF INTELLIGENT TRANSPORTATION SYSTEMS, 2024, 28 (06) : 971 - 987
  • [33] An Approach to Estimate Traffic Speed Based on Cellular Network Signaling Data on Highways
    Song, Zhixin
    Zhu, Tongyu
    Wu, Dongdong
    Liu, Shuai
    2014 IEEE 26TH INTERNATIONAL CONFERENCE ON TOOLS WITH ARTIFICIAL INTELLIGENCE (ICTAI), 2014, : 914 - 921
  • [34] Assessing Escherichia coli metabolism models and simulation approaches in phenotype predictions: Validation against experimental data
    Costa, Rafael S.
    Vinga, Susana
    BIOTECHNOLOGY PROGRESS, 2018, 34 (06) : 1344 - 1354
  • [35] Elastic and viscoelastic back-calculation of pavement layers' moduli using data obtained from traffic speed deflection devices
    Hamidi, Arman
    Hoff, Inge
    Mork, Helge
    CONSTRUCTION AND BUILDING MATERIALS, 2024, 447
  • [36] Assessing the phototransformation of diclofenac, clofibric acid and naproxen in surface waters: Model predictions and comparison with field data
    Avetta, Paola
    Fabbri, Debora
    Minella, Marco
    Brigante, Marcello
    Maurino, Valter
    Minero, Claudio
    Pazzi, Marco
    Vione, Davide
    WATER RESEARCH, 2016, 105 : 383 - 394
  • [37] Ex-ante data analysis approach for assessing the effect of variable speed limits
    van de Weg, G. S.
    Hegyi, A.
    Hoogendoorn, S. P.
    2014 IEEE 17TH INTERNATIONAL CONFERENCE ON INTELLIGENT TRANSPORTATION SYSTEMS (ITSC), 2014, : 1317 - 1322
  • [38] Effects of Traffic Cameras on Incident Management: Validation of Statistically Significant Effects Using Field Data
    Sun, Zhentian
    Yu, Mingyuan
    Wang, Hao
    Li, Xuhong
    TRANSPORTATION RESEARCH RECORD, 2015, (2484) : 31 - 38
  • [39] Online Traffic Speed Estimation for Urban Road Networks with Few Data: A Transfer Learning Approach
    Yu, James J.Q.
    2019 IEEE Intelligent Transportation Systems Conference, ITSC 2019, 2019, : 4024 - 4029
  • [40] Online Traffic Speed Estimation for Urban Road Networks with Few Data: A Transfer Learning Approach
    Yu, James J. Q.
    2019 IEEE INTELLIGENT TRANSPORTATION SYSTEMS CONFERENCE (ITSC), 2019, : 4024 - 4029