References
- Aleadelat, W., & Ksaibati, K. (2017). Estimation of pavement serviceability index through android-based smartphone application for local roads. Transportation Research Record Journal of the Transportation Research Board, 2639(1), 129–135. https://journals.sagepub.com/doi/10.31412639-16 https://doi.org/10.3141/2639-16
- American Society of Testing & Materials. (2018). Standard guide for conducting subjective pavement ride quality ratings (ASTM E1927-98). http://www.astm.org/cgi-bin/resolver.cgi?E1927-98(2018)
- Arianto, T., Suprapto, M., & Syafi’i (2018). Pavement condition assessment using iri from roadroid and surface distress index method on national road in sumenep regency. Iop Conference, 333. https://iopscience.iop.org/article/10.10881757-899X/333/1/012091
- Bisconsini D., N., Nicoletti R, J. Y., & Fernandes, J. J. (2018). Pavement roughness evaluation with smartphones. International Journal of Science and Engineering Investigations, 7(72), 43–52. https://www.researchgate.net/publication/322917351_Pavement_Roughness_Evaluation_with_Smartphones
- Chen, G., & Zhang, J. (2021). Influence of unit length on pavement roughness evaluation results based on driving vibration data. IOP Conference Series: Earth and Environmental Science, 719(3), 032081 (7pp). https://iopscience.iop.org/article/10.10881755-1315/719/3/032081/pdf https://doi.org/10.1088/1755-1315/719/3/032081
- Chen, Z., Liang, Y. L., & Sun, L. J. (2019). Effect of vibration timeliness on road riding quality evaluation. Journal of Tongji University (Natural Science, 047(010), 1470–1476,1519. http://tjxb.cnjournals.cn/ch/reader/view_abstract.aspx?flag=1&file_no=18440&journal_id=jtuns
- Du, Y., Zhang, J., & Su, R. (2010). Study on distribution characteristics of roughness for asphalt pavement. Journal of Highway and Transportation Research and Development, 27(11), 242–246.
- Gao, Z. L., Zhang, Y. F., & Wang, J. L. (1995). Pavement characters affecting passengers` comfortness and its subjective index. China Journal of Highway Transport, 8(S1), 33–38.
- Giacomo, A., Alberto, C., Emanuele, L., Valerio, F., & Alessandro, B. (2017). A study on the influence of speed on road roughness sensing: The smartroadsense case. Sensors, 17(2), https://doi.org/10.3390/s17020305
- Jeong, J. H., Jo, H., & Ditzler, G. (2020). Convolutional neural networks for pavement roughness assessment using calibration-free vehicle dynamics. Computer-Aided Civil and Infrastructure Engineering, 35(11), 1209–1229. https://doi.org/10.1111/mice.12546
- Jr, W. C., & Irick, P. E. (1960). The pavement serviceability-performance concept. Highway Research Board Bulletin. http://onlinepubs.trb.org/Onlinepubs/hrbbulletin/250/250-003.pdf
- JW Stribling. (2016). Use of smartphones to measure pavement roughness across multiple vehicle types at different speeds. the University of Illinois at Urbana-Champaign. https://www.ideals.illinois.edu/handle/2142/95500
- Li, X., & Goldberg, D. W. (2018). Toward a mobile crowdsensing system for road surface assessment. Computers Environment & Urban Systems, 69(5), 51–62. https://www.sciencedirect.com/science/article/pii/S0198971517301333 https://doi.org/10.1016/j.compenvurbsys.2017.12.005
- Li, X. L., Yang, W. A., & Fu, W. K. (2019). Research on objective evaluation method of comfort of vehicles passing through unilateral pits (in Chinese). Shanghai Auto, (9), 31–35. https://kns.cnki.net/KCMS/detail/detail.aspx?dbcode=CJFD&filename=SHQC201909008
- Loprencipe, G., & Zoccali, P. (2017). Ride quality due to road surface irregularities: Comparison of different methods applied on a set of real road profiles. Coatings, 7(5), https://doi.org/10.3390/coatings7050059
- Lu, J. J., Zhu, C. K., & Pernia, J. (2003). Performance evaluation of roughness measuring devices to measure ride number and international roughness index, Florida Department of Transportation. http://ftp.fdot.gov/file/d/FTP/FDOT%20LTS/CO/research/Completed_Proj/Summary_SMO/FDOT_BC353_34rpt.pdf
- Meng, L. (2018). Signal analysis and application of smartphone accelerometer for pavement smoothness. Southeast University.
- Ministry of Transport of the People's Republic of China. (2016). Technical code of maintenance for urban road (JTG5210-2016).
- Ministry of Transport of the People's Republic of China. (2018). Highway performance assessment standard (JTG5210-2018).
- Múčka, P. (2017). International roughness index specifications around the world. Road Materials and Pavement Design, 18(4), 929–965. https://www.tandfonline.com/doi/abs/10.108014680629.2016.1197144?journalCode=trmp20 https://doi.org/10.1080/14680629.2016.1197144
- Múčka, P. (2017). Road roughness limit values based on measured vehicle vibration. Journal of Infrastructure Systems, 23(2), 1–13. https://doi.org/10.1061/(ASCE)IS.1943-555X.0000325
- Peter Múka. (2020). International roughness index thresholds based on whole-body vibration in passenger cars. Transportation Research Record Journal of the Transportation Research Board, 2675(3), 1–16. https://journals.sagepub.com/doi/10.11770361198120960475
- Sayers, M. W. (1998). The little book of profiling – basic information about measuring and interpreting road profiles. 30-31. https://deepblue.lib.umich.edu/handle/2027.42/21605
- Song, Z. G., & Jin, W. L. (2002). A fuzzy-stochastic model for human response to vibrations. Journal of Basic Science and Engineering, 10(3), 287–294. http://www.cnki.com.cn/Article/CJFDTotal-YJGX200203009.htm
- Thiandee, P., Witchayangkoon, B., Sirimontree, S., & Lertworawanich, P. (2019). An experiment on measurement of pavement roughness via android-based smartphones. International Transaction Journal of Engineering,: Management, & Applied Sciences & Technologies, 10. https://arxiv.org/ftp/arxiv/papers/1907/1907.13120.pdf
- Wang, C., Xu, S., & Yang, J. (2021). Adaboost algorithm in artificial intelligence for optimizing the IRI prediction accuracy of asphalt concrete pavement. Sensors, 21(17), 5682. https://doi.org/10.3390/s21175682
- Wang, L. (2019). Study on pavement performance Intelligent recognition method based on driving data. Beijing University of Technology.
- Wu, Y. (2020). Research on Intelligent Evaluation method of pavement riding quality RQI. Beijing University of Technology.
- Xiong, J., Liu, J., Guan, J. Z., Sun, J. P., Liu, X. J., & Wen, H. M. (2010). The minimum sample size determination of floating car in Beijing expressway. Journal of Transportation Systems Engineering and Information Technology, 10(04), 42–47. http://www.cqvip.com/QK/71135X/201107/34943336.html
- Xu, L. H., & Song, C. C. (2017). A study on evaluation of pavement roughness and riding comfort based on acceleration noise model. Science Technology and Engineering, 17(2), 116–119+125.
- Yan, C. Y. (2015). Study on vibration riding comfort of public transportation based on physiology and psychology indicators. Beijing Municipal Engineering Research Institute. http://kns-cnki-net-s.libziyuan.bjut.edu.cn:8118/kcms/detail/detail.aspx?dbcode=CMFD&dbname=CMFD201502&filename=1015378572.nh&uniplatform=NZKPT&v=3IX10dH33eWOvjv1D88oKesK6qcHmJGCJk0aS5Y1iguu0WfzyN%25mmd2BcRWGQ31KPak0q
- Yang, H. (2017). Research and application of fast detection technology of pavement condition based on smartphone, Southeast University.
- Yeganeh, S. F., Mahmoudzadeh, A., Azizpour, M. A., & Golroo, A. (2019). Validation of smartphone based pavement roughness measures. AUT Journal of Civil Engineering, 1(2), 135–144. https://arxiv.org/pdf/1902.10699.pdf
- Zhang, H., & Yang, W. (2010). Evaluation method of pavement roughness based on human-vehicle-road interaction. Tenth International Conference of Chinese Transportation Professionals, 3541–3551. https://ascelibrary.org/doi/10.106141127%28382%29383 https://doi.org/10.1061/41127(382)383
- Zhang, H. L., & Yang, W. Q. (2010). Evaluation method of pavement roughness based on 5-DOF human-vehicle-road vibration model. Journal of Traffic and Transportation Engineering, 10(4), 17–22. http://transport.chd.edu.cn/oa/DArticle.aspx?type=view&id=201004003
- Zhang, J. X., Wang, L., Jing, P., Wu, Y., & Li, H. M. (2020). IRI threshold values based on riding comfort. Journal of Transportation Engineering Part B Pavements, 146(1), https://doi.org/10.1061/JPEODX.0000144
- Zhang, J. X., Wang, M. X., Wang, D. W., Li, X. H., Song, B., & Liu, P. F. (2017). Feasibility study on measurement of a physiological index value with an electrocardiogram tester to evaluate the pavement evenness and driving comfort. Measurement, 117, 1–7. https://doi.org/10.1016/j.measurement.2017.11.060
- Zhang, J. X., Zhou, T. J., Wang, L., & Wu, Y. (2019). Comprehensive evaluation method of road driving comfort based on D-S evidence method. Journal of South China University of Technology (Natural Science Edition), 47((02|2)), 106–112. http://zrb.bjb.scut.edu.cn/CN/10.12141j.issn.1000-565X.180307
- Zhou, X., Yan, L., & Sun, L. (2007). Study and validation of the relationship between international roughness index and power spectral density. China Civil Engineering Journal, 40(01), 99–104.
- Zhou, X. Q., Sun, B., Chen, Z., & Sun, L. J. (2007). Method research on evaluation standard of pavement riding quality. Journal of Tongji University (Natural Science, 35(02), 213–217. http://www.cnki.com.cn/Article/CJFDTOTAL-TJDZ200702013.htm