City Council Agenda and Packet 2023 02 28 SP

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known. This ensures that the final outcome is consistent with overall city planning and accurately reflects current funding allocations. In terms of pavement management efficiency, a program based on worst -first, that is starting at the lowest rated street and working up towards the highest, does not achieve an optimal expenditure of funds. Generally, under this scenario, agencies can not sufficiently fund pavement rehabilitation and lose ground despite injecting large amounts of capital into the network. The preferred basis of rehabilitation candidate selection is to examine the cost of deferral of a street, against increased life expectancy. Funding analysis The actual process of determining where and when to spend funds is a function of inputs mentioned in the section. Information from the street section inventory, condition survey, deterioration modeling, rehabilitation activity protocols, prioritization, and project planner are all assessed to predict the outcomes of funding scenarios. These can either be goal -based or budget -based. A more detailed description is available in Section 5. Reporting Lucity has the ability to generate basic reports for common data requests through a set of predefined layouts. This allows for quick access to section condition summaries, inspection data, budget scenario summaries, and data charts. The GIS data used to generate this report is also linked to the section summary information to allow for quick and easy visualizations of the data if imported into a GIS utility. 2.5. Pavement Condition Survey The goal of the pavement condition survey is to determine an accurate rating for each pavement section. The process of collecting and assessing data involves both automated and manual observations that originate from the data collected with the Road Surface Tester using Pavemetrics Laser Crack Measuring System (LCMS-2) downward imaging lasers, an array of 4k cameras, and trained rating personnel. Surface Distress Index (SDI) ASTM D6433 categorizes surface distress observations based on the extent and severity of distresses encountered along the length of the roadway for asphalt and concrete pavements. Presented on a 0 to 100 scale, the Surface Distress Index (SDI) is an aggregation of the observed pavement defects. However, not all surface distresses are weighted equally. Certain load -associated distresses (LAD) (caused by traffic loading), such as rutting or alligator cracking on asphalt streets, or divided slabs on concrete streets, have a much higher impact on the SDI than non -load associated distresses (NLAD) such as raveling or longitudinal and transverse cracking. Even at low extents and moderate severity (less than 10% of the total area), LAD can drop the SDI considerably. The rating systems also incorporates algorithms to correct for multiple or overlapping distresses within a segment to account for multiple distresses that may arise from a single cause. The SDI inputs are shown in Figure 6. IMS Pavement Management Report Louisville, CO 2022 Page 18