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Home My WebLink AboutITEM IV-A emoran u m - . Date: November 17, 2009 To: Pete Lewis, Mayor Public Works Committee Members From: Seth Wickstrom, Street Systems Engineer CC: Dennis Dowdy, Public Works Director Dennis Selle, City Engineer Ingrid Gaub, Assistant City Engineer Re: Report On City's Pavement Database During the July 20, 2009 Public Works Committee meeting, the Committee requested that staff write a brief summary of the information available in the City's pavement database. Attached is the requested report. This report is scheduled to be discussed at the December 2009 Public Works Committee meeting. REPORT ON AUBURN'S PAVEMENT MANAGEMENT COMPUTER SOFTWARE INTRODUCTION The City's pavement management computer software is called `StreetSaver' which was created by the Metropolitan Transportation Commission (the planning and financing agency for the San Francisco Bay Area}. The StreetSaver program was specifically designed to help local jurisdictions efficiently manage their pavement infrastructure. The program is used by over 300 local governments in the United States (mainly in California, Oregon, and Washington}. Auburn has been using StreetSaver since 2002. StreetSaver is a fairly intricate computer program; however, all the feature of the program can be essentially reduce down into two main elements: 1. Pavement Database -The City's pavement database is part of the StreetSaver program. The pavement database stores pavement information for every street in the City including pavement condition data and a maintenance history. 2. Budget Scenarios -StreetSaver uses the data stored in the pavement database to run `budget scenarios' that predict the future condition of Auburn streets at different levels of funding. Each of these elements is explained further in the following two sections. THE PAVEMENT DATABASE There are three main types of data stored in the pavement database for every street in the City: • Core Data -Includes basic information about the street like the name of the street, the beginning and ending location, the length and width, the pavement type and function classification of each street segment. • Pavement Condition Data -Includes the information from the most recent pavement condition survey and past pavement condition surveys including the different type of pavement distresses that were found and the calculated PCI (pavement condition index} value for the street. Currently, there is information from three different pavement condition survey stored in the pavement database; one survey done in the summer of 2002, one done in the summer of 2006, and one done only in the annexation areas in the summer of 2008. • Maintenance Data - Includes information on past maintenance treatments. The maintenance history in the database only goes back to 2002 (when Auburn's pavement database was created}. All of the maintenance treatments that have been done after 2002 have been entered into the pavement database at the end of each year. The table below shows two examples of the data that is currently stored in the pavement database for a section of West Valley Hwy and A St NE. 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To run a budget Scenario you first have to enter in the parameters of the scenario. For example, the table below shows the parameters that would be used to run a budget scenario for our arterial & collector pavement preservation program at the current funding level: N Bud et Amount = $1,500,000 per year as Amount Allocated to Preventative ~ ~ Maintenance Crack Sealin = $100,000 per year ~ ~ ) _ 00 i Streets to Anal ze All Arterials and Collector Streets Time Period of Scenario = 10 Years a Inflation Rate = 3% N Condition of Cost of Treatment ~ ~ Pavement Treatment to Use (per square yard or linear ~ ~ foot of pavement} ~ ~ Good Condition i i PCI 70 -100 Crack Seal $3 per linear foot ( } a Fair Condition Pavement Patching 25 er s uare and ~ PCI 50 - 70 and Overla $ p q y a~ ~ ( } y ~ v Poor Condition Extensive Pavement > PCI 25 - 50 Patchin and Overla $35 per square yard ( } 9 Y a ~ Very Poor Condition PCI 0 - 25 Rebuild $95 per square yard ( } Once the parameters are set, the budget scenario can be run. StreetSaver starts by picking streets to treat in the first year of the scenario. Streets are selected based on a ratio of the estimated increase in pavement life versus the cost of the treatment. Basically, the longer life the treatment will add to the pavement and the lower the cost of the treatment; the greater chance the street will be selected. This method of selecting streets typically results in streets in better condition getting treated first since the cost of treating them is significantly cheaper than streets in worse condition. For example, when the parameters in the above table are used to run a budget scenario, StreetSaver chose about 7.5 miles of streets in good condition to crack seal and a little more than 2 miles of streets in fair condition to patch and overlay in the first year. After the first year streets are treated in the scenario, StreetSaver predicts what the PCI values will be for the remaining streets for the second year of the scenario (based on standard pavement deterioration rates}. StreetSaver then picks what streets to treat in the second year using the same method it did in the first year. This process continues for the third year, fourth year, fifth year, etc. up to number of years specified in the parameters (10 years in the example above). Once the scenario is complete, StreetSaver calculates useful summary statistics that show how the pavement condition of the streets responded to the given funding level. The tables below show some of the most important statistics that StreetSaver calculated given the parameters listed in the table above. Printed: 12/29/2009 2:34 PM Page 3 of 4 ~OCatIOn: H:1PW COMMITTEE1Agenda Bills and Attachments101-04-101Discussion & Info A1Report.doc The first table (below) shows the average PCI of the streets during each year of the budget scenario. StreetSaver calculates the average PCI of the street at both the specified funding level ($1,500,000) and the $0 funding level for comparison. There average PCIs are only for the streets analyzed in the scenario (all arterial and collector streets in this example) and not the average PCI of the entire street system. Average PCI of Average PCI of Streets Streets with Budget with Budget of Year of $0 per year $1,500,000 per ear 2009 65 66 2010 63 65 2011 60 63 2012 58 61 2013 55 59 2014 52 57 2015 50 55 2016 47 54 2017 44 52 2018 42 50 The next table (below) shows the breakdown of the pavement condition of the street at the beginning and end of the scenario. For example, StreetSaver predicts that the percentage of arterial and collector streets in very poor condition will increase from the current 8.2% to 32.6% at the end of 2018 when $1,500,000 is budgeted each year for pavement preservation. Again, these percentages are for the streets analyzed in the scenario only (all arterial and collector streets in this example) and not for the entire street system. Condition of Condition of Streets at Start Streets at Pavement Condition of 2009 End of 2018 Good (PCI 70 -100) 58.2% 38.6% Fair (PCI 50 - 70) 15.2% 23.1 Poor (PCI 25 - 50) 18.5% 5.8% Very Poor (PCI 0 - 25) 8.2% 32.6% IMPORTANT NOTES Selecting Specific Streets for a Pavement Preservation Project StreetSaver was designed mainly to analyze the overall condition and the budget needs of a local jurisdiction's pavement. When it comes to selecting individual streets for a pavement preservation project (a crack seal project, an overlay project, etc.), StreetSaver is helpful but has limitations. StreetSaver can provide a list of streets that should be good candidates, but ultimately selecting the final streets for a pavement preservation project is done by visually inspecting streets to determine which ones are good candidates for the preservation treatment being planned. Making Pavement Condition Maps The StreetSaver program cannot make maps. The City's Information Services department has manually linked the pavement database with their GIS system. Maps using information from the pavement database (pavement condition maps for example} are created by the Information Services Department using their GIS software. Printed: 12/29/2009 2:34 PM Page 4 of 4 ~OCatIOn: H:1PW COMMITTEE1Agenda Bills and Attachments101-04-101Discussion & Info A1Report.doc