249
Views
9
CrossRef citations to date
0
Altmetric
Articles

Wavelength sensitivity of roughness measurements using connected vehicles

ORCID Icon, , &
Pages 566-572 | Received 10 Nov 2016, Accepted 28 Mar 2017, Published online: 18 Apr 2017

References

  • Akbarian, M. , et al. , 2015. Network analysis of Virginia’s interstate pavement-vehicle interactions: mapping of roughness and deflection-induced excess fuel consumption. Proceedings of 94th Annual Meeting of the Transportation Research Board , Washington, DC.
  • Akinwande, V. , et al. , 2015. Automatic and real-time pothole detection and traffic monitoring system using smartphone technology. International Conference on Computer Science Research and Innovations (CoSRI 2015) , Ibadan, Nigeria.
  • Bilodeau, J.-P. , Gagnon, L. , and Doré, G. , 2015. Assessment of the relationship between the international roughness index and dynamic loading of heavy vehicles. International Journal of Pavement Engineering , 1–9. doi:10.1080/10298436.2015.1121780.
  • Bridgelall, R. , 2014a. Connected vehicle approach for pavement roughness evaluation. J. Infrastruct. Syst. , 20 (1), 1–6.
  • Bridgelall, R. , 2014b. Inertial sensor sample rate selection for ride quality measures. Journal of Infrastructure Systems , 21 (2), 1–5.
  • Bridgelall, R. , 2015a. Precision bounds of pavement distress localization with connected vehicle sensors. Journal of Infrastructure Systems , 21 (3), 1–7.
  • Bridgelall, R. , 2015b. Precision bounds of pavement deterioration forecasts from connected vehicles. Journal of Infrastructure Systems , 21 (1), 1–7.
  • Bridgelall, R. , et al. , 2016a. Use of connected vehicles to characterize ride quality. Transportation Research Record , 2589, 119–126. doi:10.3141/2589-13.
  • Bridgelall, R. , et al. , 2016. Error sensitivity of the connected vehicle approach to pavement performance evaluations. International Journal of Pavement Engineering , 1–6. doi:10.1080/10298436.2016.1162307.
  • Cruz, J.F. and Castro, J.T. , 2015. Estimating road roughness conditions using ubiquitous smartphones and geographic information systems and its application to road network planning in the Philippines. Proceedings of the 11th International Conference of the Eastern Asia Society for Transportation Studies (EASTS 2015) . Cebu City, Philippines: University of the Philippines.
  • Dawkins, J. , et al. , 2011. Investigation of pavement maintenance applications of intellidrive . Pooled Fund Study, Charlottesville, VA: University of Virginia.
  • Ghosh, L.E. , et al. , 2015. Effects of pavement surface roughness and congestion on expected freeway traffic energy consumption. The 94th Annual Meeting of the Transportation Research Board , Washington, DC
  • Gillespie, T.D. , Sayers, M.W. , and Queiroz, C.A.V. , 1986. The international road roughness experiment: establishing correlation and calibration standard for measurement . Washington, DC: The World Bank.
  • González, O.D. , 2016. Quantification of the impact of roadway condition on gas emissions. The 95th Annual Meeting of the Transportation Research Board , Washington, DC.
  • Islam, S. , et al. , 2014. Measurement of pavement roughness using android-based smartphone application. Transportation Research Record: Journal of the Transportation Research Board , 2457, 30–38.10.3141/2457-04
  • Karamihas, S.M. , 2015. Measuring, Characterizing, and Reporting Pavement Roughness of Low-Speed and Urban Roads . Research in Progress, Washington, DC: Transportation Research Board of the National Academies. Available from: http://apps.trb.org/cmsfeed/TRBNetProjectDisplay.asp?ProjectID=3404 [Accessed 1 November 2016].
  • Lak, M.A. , Degrande, G. , and Lombaert, G. , 2011. The influence of the pavement type on ground-borne vibrations due to road traffic. In: G. De Roeck , et al. , ed. Proceedings of the 8th International Conference on Structural Dynamics . Leuven, Belgium: EURODYN 2011, 777–784.
  • Louhghalam, A. , Tootkaboni, M. , and Ulm, F.-J. , 2015. Roughness-induced vehicle energy dissipation: statistical analysis and scaling. Journal of Engineering Mechanics , 141 (11), 04015046.10.1061/(ASCE)EM.1943-7889.0000944
  • Louhghalam, A. , Akbarian, M. and Ulm, F.-J. , 2017. Carbon management of infrastructure performance: integrated big data analytics and pavement-vehicle-interactions. Journal of Cleaner Production , 142, 956–964.10.1016/j.jclepro.2016.06.198
  • Papagiannakis, A.T. , 1997. The Need for a New Pavement Roughness Index; RIDE. International Truck & Bus Meeting & Exposition . Washington, DC: Society of Automotive Engineers International.
  • Papoulis, A. , 1991. Probability, random variables, and stochastic processes . New York : McGraw-Hill.
  • Steyn, W.V. , et al. , 2015. Evaluation of the effect of rural road condition on agricultural produce transportation. Transportation Research Record: Journal of the Transportation Research Board , 2473, 33–41.10.3141/2473-04
  • MnROAD , 2015. Safer, smarter, sustainable pavements through innovative research . Brochure, Monticello, MN: Minnesota Department of Transportation.
  • Yi, C.-W. , Chuang, Y.-T. , and Nian, C.-S. , 2015. Toward crowdsourcing-based road pavement monitoring by mobile sensing technologies. IEEE Transactions on Intelligent Transportation Systems , 16 (4), 1905–1917.10.1109/TITS.2014.2378511

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.