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Investigation of Typical Distresses of Flexible Pavements in Dhaka City and Possible Remedies

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Abstract

Pavement condition rating (PCR) is a popular indicator for prioritizing maintenance of flexible pavements. Flexible pavements are vulnerable because of inappropriate geometric design, reduced maintenance, and climate hazards. This study investigates the condition of the flexible pavements in the arterial roads of Dhaka city. Currently, no database exists for the pavement condition of the roads of Dhaka. This study is undertaken to rank roads based on pavement condition ratings and to recommend maintenance alternatives. The pavement evaluation is done manually through visual inspection of recorded images of the distress of the selected road sections. Eighteen representative road sections from four zones of Dhaka were examined. In 2019, the length and frequency of pavement cracks, drainage deficiencies, traffic volume, and driving discomfort were measured. The PCR values for the examined roads ranged from 58 to 92 on a scale of 0–100. Riding quality was related to edge cracking, block cracking, drainage inadequacy, and Annual Average Daily Traffic (AADT) in a correlation test of the connected variables. Based on the PCR value and kind of cracks, general and crack-specific maintenance suggestions for the selected roadways and associated costs were presented. Potholes and Alligator cracks were more noticeable than patching, raveling, and shoving. More than half of the road sections needed regular maintenance, while others required overlay. Interestingly, no pavement needed reconstruction as the maintenance option. Some suggestions to modify existing pavement maintenance practices, such as increasing curing time, scra** older pavements, and using cost-effective treatment solutions, were recommended. This condition rating can be used to repair pavement distresses and ensure proper pavement maintenance across Dhaka city.

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References

  1. Aldagheiri, M. (June 2009). The role of the transport road network in the economic development of Saudi Arabia (pp. 275–285). https://doi.org/10.2495/UT090251

  2. Sinanmis, R., & Woods, L. (2018). Investigation into the pavement condition rating (PCR) of selected roads in a Nottingham case study. In University transport study group (UTSG) (pp. 1–11). University College of London.

  3. Queiroz, C., & Gautam, S. (1992). Road infrastructure and economic development some diagnostic indicators.

  4. Avinash, N. R., Vinay, H. N., Prasad, D., Dinesh, S. V., & Dattatreya, J. K. (May 2014). Performance evaluation of low volume flexible pavements—A case study. In T&DI congress 2014 (pp. 69–78). American Society of Civil Engineers. https://doi.org/10.1061/9780784413586.007

  5. Hafizyar, R., & Mosaberpanah, M. A. (2018). Evaluation of flexible road pavement condition index and life cycle cost analysis of pavement maintenance: A case study in Kabul Afghanistan. International Journal of Scientific and Engineering Research, 9(8), 1909–1919.

    Google Scholar 

  6. Issa Sarsam, S. (2008). Development of pavement maintenance management system using visual evaluation of asphalt concrete surface condition and expert system. In 7th international conference on managing pavement assets.

  7. Zumrawi, M., & Zumrawi, M. M. E. (2013). Survey and evaluation of flexible pavement failures soil stabilization view project performance and treatment of expansive soils view project survey and evaluation of flexible pavement failures (Online). Available: www.ijsr.net

  8. Salvatore, C., Di Alessandro, G., & Sebastiano, B. (October 2006). Evaluation of pavement surface distress using digital image collection and analysis. In 7th international congress on advances in civil engineering, Istanbul.

  9. Amekudzi, A. A., & Attoh-Okine, N. O. (1996). Institutional issues in implementation of pavement management systems by local agencies. Transportation Research Record: Journal of the Transportation Research Board, 1524(1), 10–15. https://doi.org/10.1177/0361198196152400102

    Article  Google Scholar 

  10. Lippmann, S. A. (1986). Effects of tire structure and operating conditions on the distribution of stress between the tread and the road. ASTM International.

  11. Gerritsen A. H., Gurp C., Heide J., Molenaar A., & Pronk A. (1987). Prediction and prevention of surface cracking in asphaltic pavements. Sixth international conference. In International conference on the structural design (pp. 378–391).

  12. Perdomo, D., & Nokes, B. (1993). Theoretical analysis of the effects of wide-base tires on flexible pavements using CIRCLY. In Transportation research board (pp. 108–119).

  13. Hajj, E. Y., Loria, L., Sebaaly, P. E., Borroel, C. M., & Leiva, P. (2011). Optimum time for application of slurry seal to asphalt concrete pavements. Transportation Research Record: Journal of the Transportation Research Board, 2235(1), 66–81. https://doi.org/10.3141/2235-08

    Article  Google Scholar 

  14. Standard practice for roads and parking lots pavement condition index surveys, 2011.

  15. Coenen, T. B. J., & Golroo, A. (2017). A review on automated pavement distress detection methods. Cogent Eng, 4(1), 1374822. https://doi.org/10.1080/23311916.2017.1374822

    Article  Google Scholar 

  16. Roads and Highway Department, “Road maintenance manual”, Dhaka, 2005.

  17. Ragnoli, A., De Blasiis, M., & Di Benedetto, A. (2018). Pavement distress detection methods: A review. Infrastructures (Basel), 3(4), 58. https://doi.org/10.3390/infrastructures3040058

    Article  Google Scholar 

  18. Zakeri, H., Nejad, F. M., & Fahimifar, A. (2017). Image based techniques for crack detection, classification and quantification in asphalt pavement: A review. Archives of Computational Methods in Engineering, 24(4), 935–977. https://doi.org/10.1007/s11831-016-9194-z

    Article  Google Scholar 

  19. Loprencipe, G., & Pantuso, A. (2017). A specified procedure for distress identification and assessment for urban road surfaces based on PCI. Coatings, 7(5), 65. https://doi.org/10.3390/coatings7050065

    Article  Google Scholar 

  20. El Hakea, A. H., & Fakhr, M. W. (2023). Recent computer vision applications for pavement distress and condition assessment. Automation in Construction, 146, 104664. https://doi.org/10.1016/j.autcon.2022.104664

    Article  Google Scholar 

  21. Wang, K. C. P., & Smadi, O. (2011). Automated imaging technologies for pavement distress surveys (Online). Available: www.TRB.org

  22. Lei, X., Liu, C., Li, L., & Wang, G. (2020). Automated pavement distress detection and deterioration analysis using street view map. IEEE Access, 8, 76163–76172. https://doi.org/10.1109/ACCESS.2020.2989028

    Article  Google Scholar 

  23. Al-Falahi, M., & Kassim, A. (February 2019). Automated data collection system of pavement distresses: development, evaluation & validation of distress types and severities. In IOP conference series: Materials science and engineering. Institute of Physics Publishing. https://doi.org/10.1088/1757-899X/471/6/062015

  24. Ghosh, R., & Smadi, O. (2021). Automated detection and classification of pavement distresses using 3D pavement surface images and deep learning. Transportation Research Record: Journal of the Transportation Research Board, 2675(9), 1359–1374. https://doi.org/10.1177/03611981211007481

    Article  Google Scholar 

  25. Nguyen, S. D., Tran, T. S., Tran, V. P., Lee, H. J., Piran, Md. J., & Le, V. P. (2023). Deep learning-based crack detection: A survey. International Journal of Pavement Research and Technology, 16(4), 943–967. https://doi.org/10.1007/s42947-022-00172-z

    Article  Google Scholar 

  26. Wang, K. C. P., & Gong, W. (2002). Automated pavement distress survey: A review and a new direction. In 2002 pavement evaluation conference, Roanoke, Virginia, 2002 (pp. 21–25) (Online). Available: https://www.researchgate.net/publication/238694797

  27. Imam, A. I., & Suleiman, A. (2023). Development of a flexible pavement condition rating model using multi-attribute utility theory. International Journal of Pavement Research and Technology, 16(5), 1079–1100. https://doi.org/10.1007/s42947-022-00183-w

    Article  Google Scholar 

  28. Sun, J., Chai, G., Oh, E., & Bell, P. (2023). A review of PCN determination of airport pavements using FWD/HWD test. International Journal of Pavement Research and Technology, 16(4), 908–926. https://doi.org/10.1007/s42947-022-00170-1

    Article  Google Scholar 

  29. Park, K., Thomas, N. E., & Wayne Lee, K. (2007). Applicability of the international roughness index as a predictor of asphalt pavement condition. Journal of Transportation Engineering, 133(12), 706–709. https://doi.org/10.1061/(ASCE)0733-947X(2007)133:12(706)

    Article  Google Scholar 

  30. Bektas, F., Smadi, O., & Nlenanya, I. (2015). Pavement condition. Transportation Research Record: Journal of the Transportation Research Board, 2523(1), 40–46. https://doi.org/10.3141/2523-05

    Article  Google Scholar 

  31. Attoh-Okine, N., Adarkwa, O. (2013) Pavement condition surveys–overview of current practices. Newark, DE, USA.

  32. Boyapati, B., & Prasanna Kumar, R. (2015). Prioritisation of pavement maintenance based on pavement condition index. Indian Journal of Science and Technology. https://doi.org/10.17485/ijst/2015/v8i14/64320

    Article  Google Scholar 

  33. Hadjidemetriou, G., Tsangaris, M., & Christodoulou, S. (July 2019). Pavement condition and traffic indices for prioritizing road maintenance (pp. 213–221). https://doi.org/10.35490/EC3.2019.239

  34. Tawalare, A., & Vasudeva Raju, K. (2016). Pavement performance index for Indian rural roads. Perspectives in Science (Netherlands), 3(1), 447–451. https://doi.org/10.1016/j.pisc.2016.04.101

    Article  Google Scholar 

  35. Mane Ajnkya S., Gujarathi Siddhesh N., Arkatkar Shriniwas S., Ashoke Kumar, S., & Ajit Pratap, S. (August 2016). Methodology for pavement condition assessment and maintenance of rural roads. In A national conference on fifteen years of PMGSY (FYPMGSY), India (pp. 1–14).

  36. Hamim, O. F., & Hoque, M. S. (July 2019). Prediction of pavement life of flexible pavements under the traffic loading conditions of Bangladesh. In Airfield and highway pavements 2019 (pp. 21–31). American Society of Civil Engineers. https://doi.org/10.1061/9780784482452.003

  37. Rana, S., Bagha, M. H., Saha, B., & Azam, M. G. (February 2019). Vibration based pavement condition monitoring using smartphone as a sensor. In Architecture and civil engineering (pp. 7–09). Rajshahi University of Engineering & Technology.

  38. Mohammad Shah, A., Sohel, M. S. M., & Shamsul, H. M. (December 2011). Road accident trends in Bangladesh: A comprehensive study. In 1st civil engineering congress, Dhaka (pp. 172–181).

  39. Mamun, S. (August 17, 2017). What Dhaka’s transport system might be like in 2019. Dhaka Tribune, Dhaka, Bangladesh.

  40. Roy, U., Farid, A., & Ksaibati, K. (2023). Effects of pavement friction and geometry on traffic crash frequencies: A case study in Wyoming. International Journal of Pavement Research and Technology, 16(6), 1468–1481. https://doi.org/10.1007/s42947-022-00208-4

    Article  Google Scholar 

  41. Miller, J. S., & Bellinge, W. Y. (May 2014). Distress identification manual for the long-term pavement performance program.

  42. Xu, B., & Huang, Y. (2003). Automated pavement cracking rating system: A summary. Austin.

  43. Flamarz Al-Arkawazi, S. A. (2017). Flexible pavement evaluation: A case study. Kurdistan Journal of Applied Research, 2(3), 292–301. https://doi.org/10.24017/science.2017.3.33

    Article  Google Scholar 

  44. Yilmaz, A., & Sargin, Ş. (2012). Water effect on deteriorations of asphalt pavements [Online]. Available: www.tojsat.net

  45. Rokade, S., Agarwal, P. K., & Shrivastava, R. (2012). Study on drainage related performance of flexible highway pavements. International Journal of Advanced Engineering Technology, 3(1), 334–337.

    Google Scholar 

  46. Shah, Y. U., Jain, S. S., Tiwari, D., & Jain, M. K. (2013). Development of overall pavement condition index for urban road network. Procedia—Social and Behavioral Sciences, 104, 332–341. https://doi.org/10.1016/j.sbspro.2013.11.126

    Article  Google Scholar 

  47. Mokhtarimousavi, S., Anderson, J. C., Hadi, M., & Azizinamini, A. (2021). A temporal investigation of crash severity factors in worker-involved work zone crashes: Random parameters and machine learning approaches. Transportation Research Interdisciplinary Perspectives, 10, 100378. https://doi.org/10.1016/j.trip.2021.100378

    Article  Google Scholar 

  48. Thapngam, T., Yu, S., Zhou, W., & Beliakov, G. (April 2011). Discriminating DDoS attack traffic from flash crowd through packet arrival patterns. In 2011 IEEE conference on computer communications workshops (INFOCOM WKSHPS) (pp. 952–957). IEEE. https://doi.org/10.1109/INFCOMW.2011.5928950

  49. Ratner, B. (2009). The correlation coefficient: Its values range between +1/−1, or do they? Journal of Targeting, Measurement and Analysis for Marketing, 17(2), 139–142. https://doi.org/10.1057/jt.2009.5

    Article  Google Scholar 

  50. Abadin, Md. J., & Hayano, K. (2022). Investigation of premature failure mechanism in pavement overlay of national highway of Bangladesh. Construction and Building Materials, 318, 126194. https://doi.org/10.1016/j.conbuildmat.2021.126194

    Article  Google Scholar 

  51. Johnson, C., Chorzepa, M. G., Durham, S., & Kim, S. S. (2017). Forensic investigation of pavement: practices in North America and a pilot investigation. Journal of Performance of Constructed Facilities. https://doi.org/10.1061/(ASCE)CF.1943-5509.0001029

    Article  Google Scholar 

  52. Behiry, A.E.A.E.-M. (2012). Fatigue and rutting lives in flexible pavement. Ain Shams Engineering Journal, 3(4), 367–374. https://doi.org/10.1016/j.asej.2012.04.008

    Article  Google Scholar 

  53. Weissman, S. L. (1999). Influence of tire-pavement contact stress distribution on development of distress mechanisms in pavements. Transportation Research Record: Journal of the Transportation Research Board, 1655(1), 161–167. https://doi.org/10.3141/1655-21

    Article  Google Scholar 

  54. Hasan, A. S., Tabassum, K., Bin Kabir, M. A., & Roksana, K. (2019). Maintenance and possible remedy for pavement distress in flexible pavement using pavement condition rating. World Journal of Science and Engineering (Online). Available: https://www.researchgate.net/publication/336265054

  55. Naziur, M. S. M., Touhidul, I. M., & Fazle, R. M. (2015). Typical pavement distresses of Dhaka City roads. In International conference on recent innovation in civil engineering for sustainable development (pp. 763–768). Dhaka

  56. Bhuyan, M. A. (2009). Evaluation of flexible and rigid pavements construction in Bangladesh. Bangladesh University of Engineering and Technology.

    Google Scholar 

  57. Khahro, S. H., Memon, Z. A., Yusoff, N. IMd., Gungat, L., & Yazid, M. R. M. (2022). Pavement maintenance management framework for flexible roads: A case study of Pakistan. Environmental Science and Pollution Research, 29(7), 10771–10781. https://doi.org/10.1007/s11356-021-16499-2

    Article  Google Scholar 

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Acknowledgements

The authors gratefully acknowledge the contribution of Arnob Ghosh, Sajib Ahmed, and Shohag Patwari to the collection of on-road data. The authors deeply acknowledge Dhaka City Corporation for their cooperation.

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Authors and Affiliations

Authors

Contributions

The authors confirm contributions to the paper as follows: study conception and design: ASH, KR, SKFK; data collection: ASH, KR, and MJA; data analysis: ASH, KR, MJA, SKFK, and MNU draft manuscript preparation: ASH, KR, SKFK, MJA, and MNU. All authors reviewed the results and approved the final version of the manuscript.

Corresponding author

Correspondence to Ahmed Sajid Hasan.

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Appendix

Appendix

See Tables 5, 6, 7, 8 and Figs. 12a, b, 13.

Table 5 Reported values of the distress survey (Zone A)
Table 6 Reported values of the distress survey (Zone B)
Table 7 Reported values of the distress survey (Zone C)
Table 8 Reported values of the distress survey (Zone D)
Fig. 12
figure 12figure 12

Some typical distresses of flexible pavement. a Alligator cracking, b longitudinal cracking, c transverse cracking, d block cracking, e slippage cracking, and f edge cracking. Some typical distresses of flexible pavement g rutting, h shoving, i depressions, j potholes, k raveling, and l bleeding

Fig. 13
figure 13

Data collection sheet for PCI index

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Hasan, A.S., Roksana, K., Kabir, S.F. et al. Investigation of Typical Distresses of Flexible Pavements in Dhaka City and Possible Remedies. Int. J. Pavement Res. Technol. (2024). https://doi.org/10.1007/s42947-023-00409-5

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