80
Views
0
CrossRef citations to date
0
Altmetric
Research Article

Enhancing pavement performance prediction with traffic speed deflection data

Article: 2343090 | Received 04 Oct 2023, Accepted 09 Apr 2024, Published online: 25 Apr 2024

References

  • Alharbi, F., and Smadi, O., 2017. ANN models to correlate structural and functional conditions in AC pavements at network level. International Journal of Advanced Engineering, Management and Science, 3 (9), 504–508.
  • Amin, M. S. R., 2015. The pavement performance modeling: deterministic vs. stochastic approaches. In: Numerical methods for reliability and safety assessment: multiscale and multiphysics systems: Springer International Publishing. doi:10.1007/978-3-319-07167-1__5
  • Arambula, E., et al., 2011. Development and validation of pavement performance models for the state of Maryland. Transportation Research Record: Journal of the Transportation Research Board, 2225, 25–31.
  • Bryce, J., et al., 2013. Developing a network-level structural capacity index for asphalt pavements. Journal of Transportation Engineering, 139 (2), 123–129.
  • Bryce, J., 2023. Consideration of information loss in the transportation asset management process. Transportation Research Record, 2678 (2), 1–12.
  • Bryce, J., et al., 2023. Evaluation of pavement performance models using historical condition data for the US national parks pavement network. Transportation Research Record: Journal of the Transportation Research Board, 2677 (9), 188–198.
  • Bryce, J., Elkins, G., and Thompson, T., 2020. Sensitivity analysis of highway economic requirements system pavement performance models. Journal of Transportation Engineering, Part B: Pavements, 146 (2), 04020006.
  • Canestrari, F., et al., 2023. A new methodology to assess the remaining service life of motorway pavements at the network level from traffic speed deflectometer measurements. International Journal of Pavement Engineering, 24 (2). doi:10.1080/10298436.2022.2128349.
  • Chu, J., and Durango-Cohen, P. L., 2008. Empirical comparison of statistical pavement performance models. ASCE Journal of Infrastructure Systems, doi:10.1061/(ASCE)1076-0342(2008)14:2(138).
  • FHWA, 2014. FHWA distress identification manual for the national park service road inventory program. Washington, DC: Federal Highway Administration.
  • Flintsch, G., et al., 2013. Assessment of continuous pavement deflection measuring technologies. Washington, DC: The National Academies Press.
  • Gelman, A. and Hill, J., 2006. Data analysis using regression and multilevel/hierarchical models. New York: Cambridge University Press.
  • Gopisetti, P., et al., 2022. Assessment of satellite-based MERRA climate data in AASHTOWare pavement mechanistic-empirical design. Road Materials and Pavement Design, 23 (12), 2876–2885.
  • Hallenbeck, M., Selezneva, O. and Quinley, R., 2014. Verification, refinement, and applicability of long-term pavement performance vehicle classification rules. McLean, VA: Federal Highway Administration.
  • Hosseini, S. A., 2021. How prediction accuracy can affect the decision-making process in pavement management system. Infrastructures, 6, 1–10.
  • Katicha, S., et al., 2017. Development of enhanced pavement deterioration curves. Charlottesville: Virginia Transportation Research Council.
  • Katicha, S., Flintsch, G., and Diefenderfer, B., 2022. Ten years of traffic speed deflectometer research in the United States: a review. Transportation Research Record, 2676 (12), 152–165.
  • Kim, Y. R., Hibbs, B. O., and Lee, Y.-C., 1995. Temperature correction of deflections and backcalculated asphalt concrete moduli. Transportation Research Record, 1473, 55–62.
  • Manoharan, S., Chai, G. and Chowdhury, S., 2022. Development of structural deterioration models for flexible pavement using traffic speed deflectometer data. International Journal of Pavement Engineering, 23 (9), 3167–3181.
  • Mills, L. N. O., Attoh-Okine, N. O., and McNeil, S., 2012. Developing pavement performance models for Delaware. Transportation Research Record: Journal of the Transportation Research Board, 2304, 97–103.
  • Nakagawa, S., Johnson, P., and Schielzeth, H., 2017. The coefficient of determination R2 and the intraclass correlation coefficient from generalized linear mixed effects models revisited and explained. Journal of the Royal Society Interfaces, 14 (134), 1–10.
  • Nasimifar, M., et al., 2019. Pavement structural capacity from traffic speed deflectometer for network level pavement management system application. Transportation Research Record, 2673, 456–465.
  • Nasimifar, M., Kamalizadeh, R., and Heidary, B., 2022. The available approaches for using traffic speed deflectometer data at network level pavement management system. Measurement, 202, 111901.
  • Nielsen, C., 2019. Visco-elastic back-calculation of traffic speed deflectometer measurements. Transportation Research Record, 2673 (12), 439–448.
  • Nielsen, C., et al., 2022. Traffic speed Deflectometer measurements at the aurora instrumented road test site. Trondheim: Taylor and Francis.
  • Nielsen, C. P., Nahoujy, M. R., and Jansen, D., 2023. Measuring joint movement on rigid pavements using the traffic speed Deflectometer. Journal of Transportation Engineering, Part B: Pavements, 149 (2), 38. doi:10.1061/JPEODX.PVENG-925.
  • Pantuso, A. G. W. F., et al., 2021. Development of network-level pavement deterioration curves using the linear empirical Bayes approach. International Journal of Pavement Engineering, 22 (6), 780–793.
  • Prozzi, J. A., and Madanat, S. M., 2004. Development of pavement performance models by combining experimental and field data. ASCE Journal of Infrastructure Systems, 10 (1), 9–22.
  • Rada, G. R., et al., 2016. Pavement structural evaluation at the network level: final report. McLean, VA: Federal Highway Administration.
  • Shrestha, S., et al., 2018. Application of traffic speed deflectometer for network-level pavement management. Transportation Research Record, 2672 (40), 348–359.
  • Silva, F., et al., 2000. Proposed pavement performance models for local government agencies in Michigan. Transportation Research Record, 1699, 81–86.
  • Sun, Z., et al., 2023. A parameter identification technique for traffic speed deflectometer tests of pavements. Road Materials and Pavement Design, 24 (4), 1065–1087.
  • Zihan, Z. U. A., et al., 2018. Development of a structural capacity prediction model based on traffic speed deflectometer measurements. Transportation Research Record, 2672, 315–325.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.