A COMPARATIVE STUDY OF MONITORING METHODS IN SUSTAINABLE PAVEMENT SYSTEM DEVELOPMENT
DOI:
https://doi.org/10.11113/jt.v81.13599Keywords:
Sustainable development, pavement management system, manual survey, smart sensor, optical image processingAbstract
Pavement management system (PMS) has been receiving increasing attention from both the government and private sectors in the attempt to ensure and keep the roads in good condition. The appropriate level of road maintenance activity is often contingent upon the type of pavement distress. Valid and reliable pavement data would lead to develop a PMS which is more suitable for agencies. Previous studies which attempted to identify modes of monitoring pavements were limited by constraints such as cost, time, and safety. This study was conducted to review some of the pavement monitoring modes introduced in previous studies. After completing a literature review, three mostly used modes, namely manual survey, smart sensor, and optical image processing, are selected for a comparative study to determine which mode is the most effective method in terms of cost, time, safety, accuracy, and sustainability. A data quality guideline was modified to produce a rating system for ranking the modes. In conclusion, the findings of this study could provide a guideline for the government and private sectors in determining the most effective pavement monitoring mode to be used in the sustainable PMS strategy.
References
APWA (American Public Works Association). 1993. Best Management Practices for Storm Water Permit Compliance. American Public Works Association, Chicago, IL.
Khan, M. A., Ahmed, A., & Kayani, W. I. U. H. 2018. Optimal Timing for Lane (s) Addition to an Existing Highway: A Benefit–cost Approach. Arabian Journal for Science and Engineering. 1-14.
Zhang, H., Keoleian, G. A., & Lepech, M. D. 2012. Network-level Pavement Asset Management System Integrated with Life-cycle Analysis and Life-cycle Optimization. Journal of infrastructure Systems. 19(1): 99-107.
Salpisoth, H. 2014. Simple Evaluation Methods for Road Pavement Management In Developing Country.
Chan, C. Y., Huang, B., Yan, X., & Richards, S. 2010. Investigating Effects of Asphalt Pavement Conditions on Traffic Accidents in Tennessee Based on the Pavement Management System (PMS). Journal of Advanced Transportation. 44(3): 150-161
Timm, D. H., & McQueen, J. M. 2004. A Study of Manual vs. Automated Pavement Condition Surveys. Alabama, EE. UU: Auburn University.
Santos, J., & Ferreira, A. 2013. Life-cycle Cost Analysis System for Pavement Management at Project Level. International Journal of Pavement Engineering. 14(1): 71-84.
Xue, W., Wang, D. & Wang, L. 2012. A Review And Perspective about Pavement Monitoring. International Journal of Pavement Research and Technology. 5(5): 295-302.
Babashamsi, P., Golzadfar, A., Yusoff, N. I. M., Ceylan, H., & Nor, N. G. M. 2016a. Integrated Fuzzy Analytic Hierarchy Process and VIKOR Method in the Prioritization of Pavement Maintenance Activities. International Journal of Pavement Research and Technology. 9(2): 112-120.
Torres-Machi, C., Chamorro, A., Videla, C., Pellicer, E. & Yepes, V. 2014. An Iterative Approach for the Optimization of Pavement Maintenance Management at the Network Level - ProQuest. Hindawi Publishing Corporation the Scientific World Journal Article. 201: 11.
Nikolaou, A. 2016. Study of Asphalt Pavement Deterioration through Remote Sensing.
Raya, J. K. 1992. A Guide to Visual Assessment of Flexible Pavement Surface Conditions. Kuala Lumpur. IKRAM.
Salleh, I. M., Toole, T., Bennett, D., & Hasan, Z. 2006. Evaluation and Monitoring of Toll Road Pavements in Malaysia from an Owner’s Perspective. In Research into Practice. 22nd ARRB Conference ARRB Group Limited.
Asphalt Institute. 2017. Asphalt Pavement Distress Summary. http://www.asphaltinstitute.org/asphalt-pavement-distress-summary/ [24 November 2017].
Wolters, A., Zimmerman, K., Schattler, K., & Rietgraf, A. 2011. Implementing Pavement Management Systems for Local Agencies: Implementation Guide (No. ICT-11-094-1).
Attoh-Okine, N., & Adarkwa, O. 2013. Pavement Condition Surveys—Overview of Current Practices. Delaware Center for Transportation, University of Delaware: Newark, DE, USA.
Cosentino, P. J., & Grossman, B. G. 2000. Optimization and Implementation of Fiber Optic Sensors for Traffic Classification and Weigh-in-Motion Systems (Phase 3) (No. FL/DOT/RMC/06650-7754).
Malla, R. B., Sen, A., & Garrick, N. W. 2008. A Special Fiber Optic Sensor for Measuring Wheel Loads of Vehicles on Highways. Sensors. 8(4): 2551-2568.
Zhang, W., Suo, C., & Wang, Q. 2008. A Novel Sensor System for Measuring Wheel Loads of Vehicles on Highways. Sensors. 8(12): 7671-7689.
Zhang, W., Wang, Q., & Suo, C. 2008. A Novel Vehicle Classification Using Embedded Strain Gauge Sensors. Sensors. 8(11): 6952-6971.
Lajnef, N., Rhimi, M., Chatti, K., Mhamdi, L., & Faridazar, F. 2011. Toward an Integrated Smart Sensing System and Data Interpretation Techniques for Pavement Fatigue Monitoring. Computerâ€aided Civil and Infrastructure Engineering. 26(7): 513-523.
Lajnef, N., Chatti, K., Chakrabartty, S., Rhimi, M. & Sarkar, P. 2013. Smart Pavement Monitoring System (May).
Zhou, Z., Liu, W., Huang, Y., Wang, H., Jianping, H., Huang, M., & Jinping, O. 2012. Optical Fiber Bragg Grating Sensor Assembly for 3D Strain Monitoring And Its Case Study In Highway Pavement. Mechanical Systems and Signal Processing. 28: 36-49.
Yang, S. 2014. Health Monitoring of Pavement Systems Using Smart Sensing Technologies. Doctoral Dissertation. Iowa State University.
Yi, C. W., Chuang, Y. T., & Nian, C. S. 2015. Toward Crowdsourcing-based Road Pavement Monitoring by Mobile Sensing Technologies. IEEE Transactions on Intelligent Transportation Systems. 16(4): 1905-1917.
Casifo, S., La Cava, G., Montella, A., Pappalardo, G. 2006. A Procedure to Improve Safety Inspections Effectiveness and Reliability on Rural Two–lane Highways. The Baltic Journal of Road and Bridge Engineering. 1(3): 143-150.
Chambon, S. & Moliard, J. M. 2011. Automatic Road Pavement Assessment with Image Processing: Review and Comparison. International Journal of Geophysics. 2011.
Ahsan, A. N. 2014. Pavement Performance Monitoring using Dynamic Cone Penetrometer and Geogauge during Construction. The University of Texas at Arlington.
Acquah, P. C., & Fosu, C. 2017. Implementation of Geographic Information System Application in the Maintenance Management of Roads in Ghana: A Case Study of Roads in Kumasi Metropolis. American Journal of Geographic Information System. 6(3): 90-102.
Cooper, J. S., & Kahn, E. 2012. Commentary on Issues in Data Quality Analysis in Life Cycle Assessment. The International Journal of Life Cycle Assessment. 17(4): 499-503.
Babashamsi, P. 2017. PAVECO: An Integrated Life Cycle Cost Analysis and Life Cycle Assessment toward Sustainable Airport Pavement Management System. Thesis PhD. Universiti Kebangsaan Malaysia.
Onn, L. 2001. Pavement Data Collection Strategy for JKR Malaysia. In ARRB Transport Research LTD Conference, 20th, 2001, Melbourne, Victoria, Australia.
Bogus, S. M., Song, J., Waggerman, R. & Lenke, L. R. 2010. Rank Correlation Method for Evaluating Manual Pavement Distress Data Variability. Journal of Infrastructure Systems. 16(1): 66-72.
Pierce, L. M., McGovern, G. & Zimmerman, K. A. 2013. Practical Guide for Quality Management of Pavement Condition Data Collection. 170.
Prakash, A., Sharma, B. N., & Kazmierowski, T. J. 1994, May. Investigation into Observational Variations in Pavement Condition Survey. Proceedings of the 3rd International Conference on Managing Pavements. 2: 290-301.
Babashamsi, P., Md Yusoff, N. I., Ceylan, H., Md Nor, N. G., & Salarzadeh Jenatabadi, H. 2016b. Sustainable Development Factors in Pavement Life-cycle: Highway/Airport Review. Sustainability. 8(3): 248.
Downloads
Published
Issue
Section
License
Copyright of articles that appear in Jurnal Teknologi belongs exclusively to Penerbit Universiti Teknologi Malaysia (Penerbit UTM Press). This copyright covers the rights to reproduce the article, including reprints, electronic reproductions, or any other reproductions of similar nature.
