تطوير برنامج أولوية لنظام إدارة صيانة الطرق

Developing Priority Program for Pavement Maintenance Management System

    The holy city of Karbala is facing big challenges due to the substantial deterioration in its infrastructure of roads network. Improper management method (if existing) leads to increased depreciation. This study aims at developing an optimized priority system within pavement maintenance management system (PMMS) in the network level.

    PAVER 6.5.7 software was used to compute Pavement Condition Index (PCI) values for a selected zone of road network in Karbala City. Visual inspection survey was conducted to investigate the type, severity level, and extent of failure at sections and sample units of selected roads. The area under study has 56.8 km length, and contained functionally almost types of urban roads. The data collection is achieved for a total of 109 road sections in; 20 major arterials, 28 minor arterials, 14 collectors, and 47 local sections. Further, the collected data for each section were inventoried and evaluated using PAVER software. Also, analysis and prediction of the PCI curve for different sections were determined for different design lifes and prediction modeling. PAVER software was linked with GIS to layout the established results and show the priority of maintenance and rehabilitation for the whole network using the critical PCI values.

     In addition to the simple ranking method by PCI’s resulted from the output of PAVER, the study introduces two other measures for each section of roadways. The first is the maintenance priority index (MPI), which is based on multiple measures investigated through expert knowledge about measures that affect prioritization and their irrespective weights due to a pre-designed questionnaire. MPI is related to multiple measures such as the cost of a proper proposed maintenance, easiness of proposed maintenance, average daily traffic and functional classification of the roadway in addition to PCI. The Second was the Incremental Benefit-Cost Ranking (BCR) analysis which is provide an optimized process due to benefit and cost of maintenance.

     The study also introduced efficient display of layout and ranking for the selected zone of roadway system based on MPI index and incremental BCR method. The statistical test shows that there is no significant difference in ranking in all methods of prioritization. The developed method can be used as an extension for pavement condition.

     Further more, statistical model of PCI developed showed that 70% of variation in PCI can be explained by multiple regression model in relation with (Age, ADT, SN). The resulted PCI indicated that 35% of roadway sections in the selected study area have good condition (PCI = (85-100)), 26.5 % have satisfactory condition (PCI = (70-85)), 12% have fair condition (PCI = (55-70)), 18% have poor condition (PCI = (40-55)), 6.5% have very poor condition (PCI = (25-40)), 2% have serious condition (PCI = (10-25)), and 0% failed condition (PCI = (0-10)).

    It can be concluded that the two optimized methods of prioritization developed in the study can be used successfully in addition to the simple ranking of PAVER. Also, developed models for PCI introduce a good correlation with independent variables of; age, ADT and structure number, can be used to estimate the pavement condition of roadways.