Sampling Procedure for Performance-Based Road Maintenance Evaluations by Jesús M. de la Garza Juan C. Piñero and Mehmet Egemen Ozbek Virginia Tech Sponsored By: Virginia Department of Transportation (VDOT) 1) Background and Problem 2) Developed Sampling Procedure- Stage 1 Characteristics of Performance-Based Road Maintenance Evaluations Population and Sample Units Sample Size Determination: 6) Concluding Remarks 1)The developed procedure is effective Ensures that the findings from the field inspections will be reliable and representative with high confidence of the actual condition of the asset items in the entire population 2)The developed procedure is efficient Envisions visiting a minimal number of sample units with many asset items as opposed to a large number of units with a few asset items 3)The developed procedure is easy to implement Approaches are presented in a stage-by-stage and step-by-step manner in an effort to assist the interested transportation agencies to easily comprehend the concepts and implement the developed procedure 4)The developed procedure has been implemented since 2002 to assist the Virginia Department of Transportation to monitor the performance of its contractors These are long term contracts which necessitated the development of the three alternative approaches of sampling as the sampling needs to be performed not just once, but multiple times over the course of the contract’s duration Since 1990’s, countries around the world have been moving towards performance-based road maintenance Performance Evaluation Budget and Time Limitations The portion of the population to be inspected The frequency at which the inspections should be conducted The sampling methodology to collect the information needed  Population is defined by small road segments of a specific length (sample units)  Sample units are 0.1 mile-long  Sample units are considered independently on each direction (e.g., North and South)  In a portion of a road that is 10 miles long the total population size will be 200 sample units (10 miles x 2 directions x 10 segments)  Sample units have different asset items  Divide the population in groups exposed to similar conditions, such as: geographical location, weather variation, urban and rural settings, traffic volumes, and/or type of asset items. (Stratification)  Acceptable quality levels  Defined by the agency (i.e. state DOT)  Must be considered in the development of the sampling procedure  Different for each asset item  90% of pipes in a population should be in good condition ( i.e. meet specific performance criteria)  95% of traffic signs in a population should be in good condition ( i.e. meet specific performance criteria)  The variability in performance targets results in a significant difference when determining the minimum number of samples required for each asset item Performance Targets 3) Developed Sampling Procedure- Stage 2 where: e: the desired precision rate which should be specified by the road administrators N: population size : the confidence level coefficient p: population proportion (minimum of performance target or historical performance) : For simplicity, this factor can be set to 1 for large populations The result obtained ( ) for each asset item at the sample level can be generalized to the whole population with the following confidence interval at the relevant confidence level: Confidence Interval= 4) Developed Sampling Procedure- Stage 3 1)Stratify the population 2)Define the sample units 3)Identify the asset items in each sample unit 4)Create the database with the sample units containing each asset item 5)Define the values of parameters to be used in sample size formulas 6)Compute the required sample size for each asset item 7)Perform the random selection of sample units 5) Sampling Multiple Times Approach 1: Keeping the Desired Precision Rate (e) Constant over Multiple Samplings:  Findings are always in the desired precision  May result in substantial changes in the sample size from one evaluation to another Approach 2: Stating the Desired Precision Rate (e) Relative to the Population’s Coefficient of Variation over Multiple Samplings:  Sample size does not change significantly  The precision of the findings may be at stake Approach 3: Keeping the Sample Size Constant over Multiple Samplings  Sample size is constant from one evaluation to another  The precision of the findings stay in an acceptable range