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Improving the assessment of slopes and flatness of the surfaces of runways and highway

Published online by Cambridge University Press:  14 July 2025

Denys Smolych
Affiliation:
School of Civil Engineering, North Minzu University, Yinchuan, NingXia, P.R. China Department of Avionics, AirSpace Faculty, National Aviation University, Kyiv, Ukraine
Svitlana Pavlova
Affiliation:
School of Software, Shanxi Agricultural University, Taigu, Shanxi, P.R. China
Andrii Bieliatynskyi
Affiliation:
School of Civil Engineering, North Minzu University, Yinchuan, NingXia, P.R. China
Shilin Yang
Affiliation:
Department of Computer Technologies of Construction and Reconstruction of Airports, Faculty of Architecture, Civil Engineering and Design, National Aviation University, Kyiv, Ukraine
Mingyang Ta*
Affiliation:
School of Civil Engineering, North Minzu University, Yinchuan, NingXia, P.R. China
*
Corresponding author: Mingyang Ta; Emails: tmy_1258@126.com

Abstract

The transport industry of Ukraine is an integral part of its economy. According to the National Transport Strategy of Ukraine, a critical strategic goal is to enhance transport safety. Currently, there is a gap in mobile devices capable of automatically measuring slopes and evenness of both runways and road surfaces in two coordinates. This paper addresses the creation of new methods for assessing longitudinal and transverse slopes using micromechanical systems. The study highlights international experiences, presents practical applications and proposes strategies for overcoming implementation challenges. A detailed roadmap for deployment and further improvements is provided.

Information

Type
Research Article
Copyright
© The Author(s), 2025. Published by Cambridge University Press on behalf of The Royal Institute of Navigation

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References

Ahlefeldt, T., Haxter, S., Spehr, C., Ernst, D. and Kleindienst, T. (2021). Road to acquisition: Preparing a MEMS microphone array for measurement of fuselage surface pressure fluctuations. Micromachines, 12(8), 961. https://doi.org/10.3390/mi12080961.CrossRefGoogle ScholarPubMed
Bieliatynskyi, A., Shilin, Y., Pershakov, V., Meiyu, S. and Ta, M. (2022a). Features of the hot recycling method used to repair asphalt concrete pavements. Materials Science-Poland, 40(2), 181195.10.2478/msp-2022-0021CrossRefGoogle Scholar
Bieliatynskyi, A., Shilin, Y., Pershakov, V., Meiyu, S. and Ta, M. (2022b). Investigation of the properties and technologies of epoxy asphalt concrete preparation with the addition of fiber from fly ash of thermal power plants. European Journal of Environmental and Civil Engineering, 27(5), 20702087. https://www.tandfonline.com/doi/full/10.1080/19648189.2022.2110160.CrossRefGoogle Scholar
Bieliatynskyi, A., Shilin, Y., Pershakov, V., Meiyu, S. and Ta, M. (2022c). Study of carbon nano-modifier of fly ash in cement concrete mixtures of civil engineering. Science and Engineering of Composite Materials, 29(1), 227241.10.1515/secm-2022-0018CrossRefGoogle Scholar
Bieliatynskyi, A., Shilin, Y., Pershakov, V., Meiyu, S. and Ta, M. (2022d). The use of fiber made from fly ash from power plants in China in road and airfield construction. Construction and Building Materials, 323, 110.10.1016/j.conbuildmat.2022.126537CrossRefGoogle Scholar
Bieliatynskyi, A., Shilin, Y., Pershakov, V., Meiyu, S. and Ta, M. (2022e). Study of crushed stone-mastic asphalt concrete using fiber from fly ash of thermal power plants. Case Studies in Construction Materials, 16, e00877.10.1016/j.cscm.2022.e00877CrossRefGoogle Scholar
Bieliatynskyi, A., Shilin, Y., Pershakov, V., Meiyu, S. and Ta, M. (2022f). Peculiarities of the use of the cold recycling method for the restoration of asphalt concrete pavements. Case Studies in Construction Materials, 16, e00872.10.1016/j.cscm.2022.e00872CrossRefGoogle Scholar
DBN V.2.3-4:20015. (2015). Automobile roads. Designing. Construction. https://dbn.co.ua/load/normativy/dbn/1-1-0-197.Google Scholar
Deng, Zh., Xie, K., Li, T., Su, Q., Han, Zh. and Xiao, X. (2024). Uncertainty measurement and application of high-speed railway slope displacement prediction based on machine learning. Zhongguo Tiedao Kexue/China Railway Science, 45(1), 5667. https://doi.org/10.3969/j.issn.1001-4632.2024.01.06.Google Scholar
DSTU 3587-97. (1997). Traffic Safety. Roads, Streets and Railway Crossings. Requirements for Operational Condition. https://kyivaudit.gov.ua/vr/ka/company.nsf/0/CAB40CFE80943DCDC2257DF8004657D6/$file/DSTY%203587-97.pdf.Google Scholar
Ghani, N.A.F.A., Ismail, N.N., Azahar, W.N.A.W., Rahman, F.A., Azman, A.W., Yusoff, N.I.M. and Rosyidi, S.A.P. (2022). Classification of Rigid pavement at airport taxiway using shear wave velocity and elastic modulus derived from spectral analysis of surface waves (SASW) method. Journal of Failure Analysis and Prevention, 22, 333345. https://doi.org/10.1007/s11668-021-01301-9.CrossRefGoogle Scholar
Guan, J., Zhou, X., Liu, L., Ran, M. and Yan, Y. (2022). Investigation of tri-axial stress sensing and measuring technology for tire-pavement contact surface. Coatings, 12(4), 491. https://doi.org/10.3390/coatings12040491.CrossRefGoogle Scholar
Guidi, G., Russo, M., Magrassi, G. and Bordoni, M.A (2010). Performance evaluation of triangulation based range sensors. Sensors, 10, 71927215.10.3390/s100807192CrossRefGoogle ScholarPubMed
Hauswirth, D., Tsirantonaki, D., Fischli, F., Rabaiotti, C. and Puzrin, A.M. (2024). Measuring strain distributions in an asphalt pavement using fibre optic sensors under static loading by test vehicles. Road Materials and Pavement Design, 26(5), 10231040. https://doi.org/10.1080/14680629.2024.2398480.CrossRefGoogle Scholar
Hayama, M., Sekiya, H. and Nagai, M. (2022). Verification of the reinforcement effect of an SFRC pavement under a live load based on visualization of deformation of a trough rib of an orthotropic steel deck using MEMS IMUs and contact displacement gauges. Journal of Bridge Engineering, 27(5). https://doi.org/10.1061/(ASCE)BE.1943-5592.0001863.CrossRefGoogle Scholar
Horb, A.A. and Horb, A.I. (2011). Determination of the evenness index by the method of terrestrial laser scanning. Modern Achievements of Geodetic Science and Production, 21, 145149.Google Scholar
Huft, D.L. (1984). South Dakota Profilometer. Transportation Research, 1000, 17.Google Scholar
Kiyashko, D.I., Savenko, V.Ya. and Kiyashko, I.V. (2014). Justification of normative indicators for assessing the longitudinal evenness of road surfaces. Roads and Bridges, 14, 9095.Google Scholar
Liu, S., Wang, Ch., Du, Sh., Yong, R., Yu, Y. and Sun, H. (2022). 3D morphology reconstruction of rock joints from 2D profile measurement by a profilograph. Measurement, 203, article number 112008. https://doi.org/10.1016/j.measurement.2022.112008.CrossRefGoogle Scholar
Matsko, P.V. (2002). Space Geodesy. Global Satellite Navigation and Geodetic Systems in Land Management. Ailant.Google Scholar
Muttuvelu, D.V., Wyke, S. and Vollertsen, J. (2024). Measuring infiltration rates in permeable asphalt pavement in urban landscapes. KSCE Journal of Civil Engineering, 28, 52555265. https://doi.org/10.1007/s12205-024-0014-y.CrossRefGoogle Scholar
Pavlyuk, D.O., Rybitsky, L.L., Lebedev, O.S. and Ivanytsia, E.V. (2004). Experience in production operation of PKRS-2U car trailer and “VSVP-UTU” push gauge. Highway of Ukraine, 2, 2527.Google Scholar
Pavlyuk, D.O., Tereshchuk, V.P., Lebedev, O.S. and Shuryakov, M. (2014). Application of spectral density to assess the quality of coatings. Modern Technologies in Mechanical Engineering and Transport, 1, 8488.Google Scholar
P-G.1-218-113:2009. (2009). Technical Rules for Repair and Maintenance of Public Highways of Ukraine. https://ukryama.com/files/P-G.1-218-113-2009.pdf.Google Scholar
Roy, N., Baditha, A.K., Biswas, S. and Kuna, K.K. (2024). Measuring the macrotexture of pavement surface using an image processing technique. Transportation Research Record, 2678(8), 184197. https://doi.org/10.1177/03611981231214519.CrossRefGoogle Scholar
Savenko, V.Ya. and Kiyashko, D.I. (2011). The relationship between estimates of road surface evenness based on shock gauge indicators and IRI. Bulletin of KHNADU, 53, 8386.Google Scholar
Sayers, M.W. and Karamihas, S.M. (1998). The Little Book of profiling. Basic information about Measuring and Interpreting Road Profiles. The University of Michigan Transportation Research Institute.Google Scholar
Senseney, C.T. and Suermann, P.C. (2021). Design, construction and monitoring of concrete roadway pavement at extremely steep longitudinal slopes. International Journal of Pavement Engineering, 24(1). https://doi.org/10.1080/10298436.2021.2011277.Google Scholar
Shilin, Y., Bieliatynskyi, A., Pershakov, V., Meiyu, S. and Ta, M. (2022). Asphalt concrete based on a polymer-bitumen binder nanomodified with carbon nanotubes for road and airfield construction. Journal of Polymer Engineering, 42(5), 458466.Google Scholar
Skrypets, A.V., Krasnov, V.M., Kireev, M.E., Smolych, D.V. and Sagidaev, Yu.M. (2013c). Construction and experimental research of the automatic roughness meter of the ZPS. Bulletin of the National Transport University, 89, 118134.Google Scholar
Skrypets, A.V., Krasnov, V.M., Melnikov, D.E., Boyko, V.I. and Sagidaev, Yu.M. (2013a). Construction and experimental research of a mobile automatic inclinometer. Roads and Road Construction, 90, 118134.Google Scholar
Skrypets, A.V., Krasnov, V.M., Melnikov, D.E., Volkov, O.E., Volosheniuk, D.O, Smolych, D.V. and Kireev, M.E. (2013b). Patent No. 49339 “Computer program “of the automated robot-platform operating module for determining the longitudinal and transverse slopes and evenness of the surface of airfield surfaces””. https://ukrpatent.org/atachs/AvtorPravo_%E2%84%9631_2013.pdf.Google Scholar
Skrypets, A.V., Krasnov, V.M., Smolych, D.V. and Kireev, M.E. (2014a). Development of a device for measuring longitudinal and transverse slopes and unevenness of runways. Science and World Scientific Review, 3(7), 208210.Google Scholar
Skrypets, A.V., Krasnov, V.M., Smolych, D.V. and Kireev, M.E. (2014b). A device for measuring the surface roughness of runways. Science and World, 3(7), 211214.Google Scholar
Smolyanyuk, R.V. and Kiyashko, I.V. (2009). Using the LVS-2-KHNADU system to assess the evenness of road surfaces. Highway of Ukraine, 5, 2426.Google Scholar
Smolych, D.V., Kireev, M.E. and Krasnov, V.M. (2014). Slope and evenness meter of airfield structures with remote data processing. In Collection of Abstracts of Scientific and Technical Conference Reports “Problems of Development of the Global System of Communication, Navigation, Surveillance and Organization of Air Traffic CNC/ATM”. National Aviation University.Google Scholar
Yevdokimov, A.A. (2016). Electronic Geodetic Devices: The Text of Lectures for Students of the Training Direction 6.080101. Geodesy, Cartography and Land Management. Kharkiv National University of Urban Agriculture named after O. M. Beketov.Google Scholar
Zapateiro, M., Pozo, F., Karimi, H.R. and Luo, N. (2012). Semiactive control methodologies for suspension control with magnetorheological dampers. IEEE/ASME Transactions on Mechatronics, 17(2), 370380.10.1109/TMECH.2011.2107331CrossRefGoogle Scholar
Zaremotekhases, F., Hunsaker, A., Dave, E.V. and Sias, J.E. (2023). Performance of the UAS-LiDAR sensing approach in detecting and measuring pavement frost heaves. Road Materials and Pavement Design, 25(2), 308325. https://doi.org/10.1080/14680629.2023.2207658.CrossRefGoogle Scholar
Zhao, Y., McDaniel, J. and Wang, M. (2013). IRI estimation using probabilistic analysis of acoustic measurements Materials Performance and Characterization, 2(1), 339359.10.1520/MPC20130018CrossRefGoogle Scholar
Zhu, J., Gao, Y., Huang, S., Bu, T. and Jiang, S. (2023). Measuring surface deformation of asphalt pavement via airborne LiDAR: A pilot study. Drones, 7(9), 570. https://doi.org/10.3390/drones7090570.CrossRefGoogle Scholar