Sampling Protocol for Condition Assessment of Selected Assets
Publication: Journal of Transportation Engineering
Volume 135, Issue 4
Abstract
This study addresses the development of a sampling protocol for condition assessment of selected assets in the state of Maryland. The proposed sampling protocol targets a desired precision and level of confidence in the estimates of levels of service (LOS) for individual assets at each maintenance shop. This work includes the evaluation of the effect of sample size [i.e., number of roadway sections] on the accuracy of estimates of LOS. The distribution of sample sizes among the various maintenance shops accounts for factors such as roadway functional classification, average annual daily traffic, geographical location, the approximate distribution of assets, and the variability in estimates of LOS for each individual asset. The implementation of the proposed sampling protocol will allow maintenance personnel to make reasonable inferences regarding the condition level of the entire asset population. This information will be useful to prioritize areas of need and determine levels of funding, personnel, and equipment. Three different variations of the proposed sampling protocol are evaluated. These variations are a function of how sample sizes are calculated: Option 1—sample size based on the asset with the largest number of required samples; Option 2—sample size based on the asset with the largest number of required samples from a selected group of assets; and Option 3—sample size based on the average number of required samples for all assets. It was concluded that, for a given confidence level, if a minimum precision is to be met for all assets, Option 1 should be used. However, if the sample size is to be limited and a minimum precision is to be met only for a selected group of assets, then Option 2 would be the best alternative. The framework proposed in this study can be modified so that it can be applied to other geographical regions.
Get full access to this article
View all available purchase options and get full access to this article.
Acknowledgments
This study was sponsored by the Maryland State Highway Administration. This financial support is gratefully acknowledged. The writers would also like to acknowledge the contributions and information provided by Len Schultz and Marc Lipnick from the SHA Office of Maintenance, as well as Hua Xiang and Allison Hardt from the SHA Office of Policy and Research, which were essential for the successful completion of the project.
References
De la Garza, J. M., Pinero, J. C., and Ozbek, M. E. (2008). “Sampling procedure for performance-based road maintenance evaluations.” Proc., 7th Transportation Research Board Annual Meeting, Transportation Research Board, Washington, D.C., Paper No. 1095.
Dornan, D. L. (2002). “Asset management: Remedy for addressing the fiscal challenges facing highway infrastructure.” Int. J. Transp. Manag., 1, 41–54.
Foyle, R., Farin, S., and Johnson, T. (2006). “Maintenance condition assessment sampling study.” Final Rep. Project No. HWY-0875, The Institute for Transportation Research and Education, North Carolina State Univ., Raleigh, N.C.
Haas, K., and Hensing, D. (2005). “Why your agency should consider asset management systems for roadway safety.” Rep. No. HRT-05-077, Federal Highway Administration, McLean, Va.
Harris, E. A., Rasdorf, W., Hummer, J. E., and Yeom, C. (2007). “Analysis of traffic sign asset management scenarios.” Transportation Research Record. 1993, Transportation Research Board, Washington, D.C., 9–15.
Juni, E., Adams, T., and Sokolowski, D. (2008). “Relating cost to condition in routing highway maintenance.” Proc., 87th Transportation Research Board Annual Meeting, Transportation Research Board, Washington, D.C., Paper No. 2402.
Larson, C., and Skrypczuk, O. (2003). “Comprehensive data collection supporting asset management at Virginia DOT.” Proc., 83rd Transportation Research Board Annual Meeting, Transportation Research Board, Washington, D.C., Paper No. 4675.
Maji, A., and Manoj, K. J. (2007). “Modeling highway infrastructure maintenance schedules with budget constraints.” Transportation Research Record. 1991, Transportation Research Board, Washington, D.C., 19–26.
Medina, R. A., Haghani, A., and Harris, N. (2007). “Development of a sampling protocol for condition assessment.” Rep. Submitted to the Maryland State Highway Administration, Baltimore.
Perrin, J., and Dwivedi, R. (2006). “Need for culvert asset management.” Transportation Research Record. 1957, Transportation Research Board, Washington, D.C., 8–15.
Piyatrapoomi, N., Kumar, A., Robertson, N., and Weligamage, J. (2005). “A probability method for assessing variability in budget estimates for highway asset management.” Proc., 5th Int. Conf. on Road and Airfield Pavement Technology, COEX, Seoul, Korea, Korean Society of Road Engineers.
Quality Assurance Team. (2002). “2001 Peer review measurement program.” Final Rep., Highway Maintenance Division, Office of Maintenance, Maryland State Highway Administration, Hanover, Md.
Sampath, S. (2005). Sampling theory and methods, Alpha Science International, Harrow, U.K.
Thompson, S. (2002). Sampling, Wiley, New York.
Yamane, T. (1967). Elementary sampling theory, Prentice-Hall, Englewood Cliffs, N.J.
Information & Authors
Information
Published In
Journal of Transportation Engineering
Volume 135 • Issue 4 • April 2009
Pages: 183 - 196
Copyright
© 2009 ASCE.
History
Received: Feb 27, 2008
Accepted: Aug 11, 2008
Published online: Apr 1, 2009
Published in print: Apr 2009
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.