Estimating the Effects of Pavement Condition on Vehicle Operating Costs (2012)

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62 A t t A c h m e n t User Guide for Vehicle Operating Cost Model The vehicle operating cost (VOC) model is an engineering software application that allows you to calculate vehicle operating costs at the network and project levels. For network analysis, data for traffic, environmental, and pavement conditions [e.g., international reference index (IRI), mean profile depth (MPD), and pavement type) are the input to the model. For project analysis, profiles can be imported in text format and the model will calculate the IRI. Entire analysis projects can be saved, which preserves user information and analysis inputs. After analy- ses have been performed, you can export a report of the results of any analyses. The purpose of this document is to describe all software operations. Software Installation Hardware While the VOC model should run on any system from the past several years, the following systems are recommended, at a minimum: • 2 GHz processor, • 2 GB RAM, and • 1024 × 768 display resolution. Software Supported operating systems are Microsoft® Windows™ XP Professional Service Pack 3+, Windows Vista, and Windows 7. The VOC model is a Microsoft Excel file with macros. Macros are written in Visual Basic. Microsoft Excel 2003 or more recent is required. Installation Once the installation kit is launched, the installation wizard will run automatically. To com- plete the process, click first on the “MATLAB Component Runtime Installer” link (Figure 1). A new window will open. Follow the steps to copy the files necessary for the software to work. Then, to install the software, click on the “VOC Module Setup” link in the installation wizard (Figure 1). You will need to unzip the file to a preferred location on the hard drive. Once the file is unzipped, click on the “VOC Module” Excel spreadsheet to launch the program. You will also be able to see an example of project-level analysis data and the data collected as part of NCHRP Project 1-45.

63 Getting Started To make sure that the software is running, the security level for Excel must be set to “Medium” or “Low.” Figure 2a shows the path to follow to change the security level in Excel 2003. For Excel 2007, you should go to the Developer tab and select “Macro security.” Figure 2b shows how to change the security level in Excel 2007 and up. Home Screen Figure 3 shows the home screen of the VOC model. This is the starting screen when no proj- ect is currently open. It consists of two main sections: analysis levels (i.e., project or network levels) and unit system (i.e., US customary units or International System of units). You should choose an option from each section and click on the “Run” button, which will open the main spreadsheet. The VOC model calculates vehicle operating costs based on traffic and highway conditions. Three components are included in cost calculations (fuel consumption, tire wear, and repair and maintenance cost). The variables used to predict consumption rates of each VOC component include: • IRI, • Texture, • Grade, • Superelevation, • Pavement type, • Speed, and • Temperature. Network-Level Analysis The general algorithm for estimating vehicle operating costs at the network level is: VOC VMT i i = × ×( ) = ∑ Rate Price 1 3 1( ) Figure 1. Installation wizard.

64 (a) For Microsoft Excel 2003 (b) For Microsoft Excel 2007 and up Figure 2. Set up of the security level.

65 where: VOC = Vehicle operating cost VMT = Vehicle miles traveled (mi) Rate = Consumption rate Price = Unit price i = Index for VOC components (fuel consumption, tire wear, and repair and mainte- nance costs) At the network level, a grade of 0% and a superelevation of 0% are reasonable assumptions to calculate VOC savings unless there is a change in the radius of curves or grades. To take into account traffic, input the total vehicle miles traveled (VMT) and the traffic distri- bution. If the traffic distribution is different for each scenario, click on the “Traffic Distributions” button to open a new spreadsheet and provide the distributions in each row. Then, click on the “Return” button. Delete any value in the “Percentage” column. To calculate vehicle operating costs, click on the “Run” button. Two new spreadsheets will be created: “Partial Costs” and “Total Costs.” To save the results, click on the “Export” button, which opens a new screen asking the user to choose a file name and its path. Then, results can be exported to Excel using the “Save” button. Enter a file name followed by the extension “.xls” to export to an Excel file (Figure 4). Project-Level Analysis The general algorithm for estimating vehicle operating costs at the project level is: VOC i i = ∗ × × ×( ) = ∑365 2 1 3 Distance AADT Rate Price ( ) Figure 3. Home screen.

66 where: VOC = Vehicle operating cost AADT = Average annual daily traffic Distance = Project length Rate = Consumption rate Price = Unit price i = Index for VOC components (fuel consumption, tire wear, and repair and main- tenance costs) You will have two options: 1. Import the raw profile of the project so that the software will calculate the IRI every 0.16 km (0.1 mi), or 2. Input the IRI and section length. For option 1, click on the “Import” button. A new screen will open asking you to choose a file name and its path (Figure 5). To look for the file, click on the “Browse” button (Figure 6). After locating the raw profile file (which should have the extension “.txt”), click on the “Open” button. The software will calculate IRI every 0.16 km (0.1 mi) and copy it to the input column. It should be noted that the profile elevation should be in inches. For option 2, you will have to input the IRI and the length of the section. At the project level, a grade of 0% and a superelevation of 0% are reasonable assumptions to calculate VOC savings unless there is a change in the radius of curves or grades. To take into account traffic, input the AADT and the traffic distribution. To calculate vehicle operating cost, click on the “Run” button. Two new spreadsheets will be created: “Partial Costs” and “Total Costs.” To save the results, the user should click on the “Export” button, which opens a new screen asking the user to choose a file name and its path. Then, results can be exported to Excel using the “Save” button. Enter a file name followed by the extension “.xls” to export to Excel file (Figure 7). Figure 4. Export screen. Figure 5. Import screen.

67 Examples This section shows examples of how the VOC models will be used in practice. Three different examples are presented for (1) deterministic analysis, (2) project-level analysis, and (3) network- level analysis. The default values for vehicle characteristics used in these examples are presented in Chapters 3 through 5 of NCHRP Report 720. The unit costs are presented in Table 7-4. The software developed in this study was used to generate the results presented below. Example 1: Deterministic Analysis In this example, the sensitivity of the total vehicle operating cost to pavement conditions at 56, 88, and 112 km/h (35, 55 and 70 mph) is investigated. The pavement conditions considered are IRI and texture. IRI is a measurement of “roughness” that has a wavelength of 0.5 m (1.65 ft) and more. Texture refers to the categories of microtexture, macrotexture, and megatexture. Effect of Roughness on Vehicle Operating Cost The effect of pavement roughness (IRI) on vehicle operating cost is estimated for all vehicle classes using the models developed in this study. Figures 8 through 10 show examples of fuel, tire, and repair and maintenance costs expressed in cents per kilometer. Table 1 presents examples Figure 6. File browsing screen. Figure 7. Export screen.

68 (a) Light vehicles at 56 km/h (35 mph) (b) Trucks at 56 km/h (35 mph) (c) Light vehicles at 88 km/h (55 mph) (d) Trucks at 88 km/h (55 mph) (e) Light vehicles at 112 km/h (70 mph) (f) Trucks at 112 km/h (70 mph) 6 7 8 9 0 1 2 3 4 5 6 F ue l c os t (c en ts /k m ) IRI (m/km) 22 24 26 28 30 32 34 0 1 2 3 4 5 6 F ue l c os t (c en ts /k m ) IRI (m/km) 7 8 9 10 11 0 1 2 3 4 5 6 F ue l c os t ( ce nt s/ km ) IRI (m/km) 32 36 40 44 48 52 0 1 2 3 4 5 6 F ue l c os t (c en ts /k m ) IRI (m/km) 10 11 12 13 14 15 0 1 2 3 4 5 6 F ue l c os t (c en ts /k m ) IRI (m/km) 48 52 56 60 64 68 72 76 0 1 2 3 4 5 6 F ue l c os t (c en ts /k m ) IRI (m/km) Passenger car SUV Van Articulated truck Heavy truck Figure 8. Effect of roughness on fuel costs.

69 Figure 9. Effect of roughness on tire costs. (a) Light vehicles at 56 km/h (35 mph) (b) Trucks at 56 km/h (35 mph) (c) Light vehicles at 88 km/h (55 mph) (d) Trucks at 88 km/h (55 mph) (e) Light vehicles at 112 km/h (70 mph) (f) Trucks at 112 km/h (70 mph) 0.5 0.54 0.58 0.62 0.66 0.7 0 1 2 3 4 5 6 T ir e co st (c en ts /k m ) IRI (m/km) 0.5 0.54 0.58 0.62 0.66 0.7 0 1 2 3 4 5 6 T ir e co st (c en ts /k m ) IRI (m/km) 0.58 0.63 0.68 0.73 0.78 0.83 0.88 0 1 2 3 4 5 6 T ir e co st (c en ts /k m ) IRI (m/km) 1.5 2 2.5 3 3.5 4 0 1 2 3 4 5 6 T ir e co st (c en ts /k m ) IRI (m/km) 0.74 0.84 0.94 1.04 1.14 1.24 1.34 0 1 2 3 4 5 6 T ir e co st (c en ts /k m ) IRI (m/km) 2 2.5 3 3.5 4 4.5 5 5.5 0 1 2 3 4 5 6 T ir e co st (c en ts /k m ) IRI (m/km) Passenger car SUV Van Articulated truck Heavy truck

70 of total cost expressed in cents per kilometer. The figures and the table were generated at 17°C (62.6°F), with mean profile depth of 1 mm (0.04 in.) and grade of 0%. Effect of Texture on Vehicle Operating Cost The effect of pavement surface texture (MPD) on vehicle operating cost is investigated for all vehicle classes using the models developed in this study. Table 2 presents examples of total cost expressed in cents per kilometer. Discussion The combined effect of MPD and IRI can be predicted by multiplying the roughness and texture factors. For example, if you would like to estimate the total vehicle operating cost for IRI = 3 m/km (190 in./mi) and MPD = 2 mm, for an articulated truck at 88 km/h (55 mph), (a) Light vehicles at 56 km/h (35 mph) (b) Trucks at 56 km/h (35 mph) (c) Light vehicles at 88 km/h (55 mph) (d) Trucks at 88 km/h (55 mph) (e) Light vehicles at 112 km/h (70 mph) (f) Trucks at 112 km/h (70 mph) 1 1.5 2 2.5 3 3.5 4 4.5 0 1 2 3 4 5 6 R ep ai r a nd m ai nt en an ce c os t (c en ts /k m ) IRI (m/km) 4 5 6 7 8 9 0 1 2 3 4 5 6 R ep ai r a nd m ai nt en an ce c os t (c en ts /k m ) IRI (m/km) 1.5 2.5 3.5 4.5 5.5 6.5 0 1 2 3 4 5 6 R ep ai r a nd m ai nt en an ce c os t (c en ts /k m ) IRI (m/km) 4 5 6 7 8 9 10 11 12 0 1 2 3 4 5 6 R ep ai r a nd m ai nt en an ce c os t (c en ts /k m ) IRI (m/km) 1.5 2.5 3.5 4.5 5.5 6.5 7.5 0 1 2 3 4 5 6 R ep ai r a nd m ai nt en an ce c os t (c en ts /k m ) IRI (m/km) 7 8 9 10 11 12 13 14 0 1 2 3 4 5 6 R ep ai r a nd m ai nt en an ce c os t (c en ts /k m ) IRI (m/km) Passenger car SUV Van Articulated truck Heavy truck Figure 10. Effect of roughness on repair and maintenance costs.

71 Speed Vehicle Class Total Vehicle Operating Costs per Vehicle (¢/km) IRI (m/km) 1 1.5 2 2.5 3 3.5 4 4.5 5 5.5 6 56 km/h (35 mph) Passenger Car 8.8 8.9 8.9 9.0 9.1 9.2 9.5 9.8 10.1 10.4 10.7 Van 10.0 10.1 10.1 10.1 10.2 10.3 10.5 10.8 11.1 11.5 11.8 SUV 10.2 10.3 10.3 10.4 10.5 10.7 11.1 11.7 12.3 12.9 13.6 LT 15.0 15.1 15.1 15.2 15.3 15.5 15.9 16.4 17.0 17.6 18.2 HT 28.8 29.1 29.3 29.6 29.8 30.2 30.9 31.8 32.8 33.8 34.9 AT 35.9 36.2 36.5 36.9 37.2 37.6 38.4 39.5 40.5 41.6 42.8 88 km/h (55 mph) Passenger Car 10.5 10.6 10.7 10.8 10.9 11.0 11.3 11.7 12.0 12.4 12.8 Van 12.6 12.6 12.7 12.7 12.8 12.9 13.2 13.5 13.9 14.4 14.8 SUV 13.0 13.1 13.2 13.3 13.4 13.6 14.1 14.8 15.5 16.3 17.2 LT 21.8 21.9 22.0 22.0 22.1 22.3 22.9 23.6 24.4 25.2 26.1 HT 43.3 43.6 43.8 44.1 44.4 44.8 45.7 46.9 48.1 49.4 50.8 AT 56.5 56.8 57.2 57.5 57.9 58.4 59.5 60.8 62.1 63.6 65.1 112 km/h (70 mph) Passenger Car 13.4 13.5 13.6 13.7 13.8 14.0 14.3 14.8 15.2 15.6 16.1 Van 16.5 16.5 16.6 16.6 16.7 16.8 17.2 17.6 18.1 18.6 19.1 SUV 17.5 17.6 17.8 17.9 18.0 18.3 18.9 19.7 20.6 21.6 22.6 LT 30.3 30.4 30.5 30.6 30.7 31.0 31.6 32.5 33.4 34.4 35.5 HT 61.1 61.4 61.7 62.0 62.3 62.9 64.0 65.4 67.0 68.7 70.4 AT 80.9 81.3 81.7 82.1 82.5 83.2 84.4 85.9 87.6 89.3 91.1 1 km = 0.62 mi; 1 mm = 0.039 in.; 1 m/km = 63.4 in./mi; MPD = 1 mm, grade = 0%; temperature = 17°C (62.6°F). Table 1. Effect of roughness on vehicle operating cost. Speed Vehicle Class Total Vehicle Operating Cost per Vehicle (¢/km) Mean Profile Depth (mm) 1 1.5 2 2.5 3 3.5 4 4.5 5 5.5 6 56 km/h (35 Mph) Passenger Car 8.8 8.8 8.8 8.8 8.8 8.9 8.9 8.9 8.9 8.9 8.9 Van 10.0 10.1 10.1 10.1 10.2 10.2 10.3 10.3 10.3 10.4 10.4 SUV 10.2 10.2 10.2 10.2 10.2 10.3 10.3 10.3 10.3 10.3 10.3 LT 15.0 15.1 15.1 15.2 15.3 15.4 15.4 15.5 15.6 15.7 15.7 HT 28.8 29.1 29.3 29.6 29.8 30.0 30.3 30.5 30.8 31.0 31.2 AT 35.9 36.2 36.5 36.9 37.2 37.5 37.8 38.1 38.4 38.7 39.0 88 km/h (55 mph) Passenger Car 10.5 10.5 10.5 10.5 10.6 10.6 10.6 10.6 10.6 10.7 10.7 Van 12.6 12.6 12.7 12.7 12.8 12.8 12.9 12.9 13.0 13.0 13.0 SUV 13.0 13.0 13.0 13.0 13.1 13.1 13.1 13.1 13.1 13.2 13.2 LT 21.8 21.9 22.0 22.0 22.1 22.2 22.3 22.4 22.5 22.6 22.6 HT 43.3 43.6 43.8 44.1 44.4 44.6 44.9 45.2 45.4 45.7 46.0 AT 56.5 56.8 57.2 57.5 57.9 58.2 58.6 58.9 59.3 59.6 60.0 112 km/h (70 mph) Passenger Car 13.4 13.4 13.4 13.4 13.4 13.5 13.5 13.5 13.5 13.6 13.6 Van 16.5 16.5 16.6 16.6 16.7 16.7 16.8 16.8 16.9 16.9 17.0 SUV 17.5 17.5 17.6 17.6 17.6 17.6 17.7 17.7 17.7 17.8 17.8 LT 30.3 30.4 30.5 30.6 30.7 30.8 30.9 31.0 31.1 31.2 31.3 HT 61.1 61.4 61.7 62.0 62.3 62.6 62.9 63.2 63.5 63.8 64.1 AT 80.9 81.3 81.7 82.1 82.5 82.9 83.3 83.7 84.1 84.5 84.9 1 km = 0.62 mi; 1 mm = 0.039 in.; 1 m/km = 63.4 in./mi; IRI = 1 m/km, grade = 0%; temperature = 17°C (62.6°F). Table 2. Effect of texture on vehicle operating cost.

72 divide 57.2 by 56.5 from Table 2 (i.e., the table describes the effect of changing texture, holding IRI constant at 1 m/km), then multiply this ratio by 57.9 from Table 1 (i.e., the table describes the effect of changing IRI, holding MPD constant at 1 mm). The cost obtained for these condi- tions is 58.6 ¢/km (94 ¢/mi). Example 2: Project-Level Analysis This example uses the mechanistic-based approach developed in this study to calculate the vehicle operating costs (fuel consumption, tire wear, and repair and maintenance) for a 7.2 km long rigid pavement section on I-69 near Lansing, Michigan. The average daily traffic (ADT) for this section is 29,145 in both directions, with 60% passen- ger cars, 15% commercial trucks, 10% heavy trucks, 7% SUV, 4% vans, 2% light trucks, and 2% buses. The pavement condition data (raw profile and texture depth) were collected by Michigan Department of Transportation using a Rapid Travel Profilometer and a Pavement Friction Tes- ter. The grade was measured using a high-precision GPS. Figure 11 shows the raw profile of the section. Figure 12 summarizes the distributions of its pavement conditions. 1 mm = 0.039 in.; 1 km = 0.62 mi -40 -30 -20 -10 0 10 20 30 40 0 1 2 3 4 5 6 7 8 E le va ti on (m m ) Distance (km) Figure 11. Raw profile of the analysis section. (a) IRI Distribution (b) Texture Distribution (c) Grade Distribution 1 m/km = 63.4 in./mi 0 5 10 15 20 25 30 1 1.5 2 2.5 3 3.5 N um be r o f s ub se ct io ns IRI (m/km) 1 mm = 0.039 in. 0 5 10 15 20 25 30 0.4 0.5 0.6 0.7 0.8 0.9 1 N um be r o f S ub se ct io ns MPD (mm) 0 2 4 6 8 10 12 -1 -0.8-0.6-0.4-0.2 0 0.2 0.4 0.6 0.8 1 N um be r o f S ub se ct io ns Grade (%) Figure 12. Pavement conditions of the analysis section.

73 Figure 13. Costs per year induced by subsection. 1 subsection = 0.16 km; 1 km = 0.62 mi 0 0.05 0.1 0.15 0.2 0.25 0 1 2 3 4 5 6 7 8 C os t ( M ill io n $/ ye ar ) Distance (km) Fuel Consumption Tire Wear Repair and Maintenance Figure 14. Simulated raw profile with an average IRI of 1 m/km (63.4 in./mi). 1 mm = 0.039 in.; 1 km = 0.62 mi -40 -30 -20 -10 0 10 20 30 40 0 1 2 3 4 5 6 7 8 E le va ti on (m m ) Distance (km) The following procedure was followed to calculate vehicle operating cost: • For repair and maintenance costs, the profile was input to the VOC model. The software cal- culated the accumulated damage in the suspension system, which was translated into repair and maintenance costs. • For fuel consumption and tire wear, the raw profile was divided into 0.16 km long (0.1 mi) sub- sections, and the IRI values were computed for each subsection. The other pavement conditions (grade, texture depth, and curvature) were input to the calibrated HDM 4 models (described in Chapters 3 and 4 of NCHRP Report 720) to estimate fuel consumption and tire wear. • The total costs were calculated according to the proportion of vehicle class mentioned above, and assuming average environmental conditions [temperature = 17°C (62.6°F)]. Figure 13 shows the costs for each subsection (0.16 km or 0.1 mi) for the traffic distribution generated at 96 km/h (60 mph) for trucks and buses and at 112 km/h (70 mph) for passenger cars, vans, and SUVs. Each point represents a subsection. To estimate the reduction in vehicle operating cost from rehabilitating the I-69 project, a raw profile of a newly overlayed pavement with an average IRI of 1 m/km (63.4 in./mi) was simu- lated. The generated road profile is shown in Figure 14. It was assumed that the grade and texture distribution were not affected by the rehabilitation. Figure 15 shows the reduction in vehicle operating cost for each subsection. The total reduc- tion in vehicle operating cost from rehabilitating this project will be about $2.46 million per year.

74 1 km = 0.62 mile 0.04 0.05 0.06 0.07 0 1 2 3 4 5 6 7 8 R ed uc ti on in V O C (M ill io n $/ ye ar ) Distance (km) Rough Section Smooth Section Figure 15. Reduction in vehicle operating cost from rehabilitating each section of the I-69 project. Figure 16. Assumed roughness distribution for network pavement. 0 10 20 30 0 1 2 3 4 5 P ro ba bi lit y D is tr ib ut io n (% ) IRI (m/km) Before Rehabilitation After Rehabilitation of 90% of the Network After Rehabilitation of 50% of the Network These costs could be considered in a life cycle cost analysis. This detailed analysis would help identify the segments of the pavement section that would result in higher operating costs. These segments would be considered for early maintenance. Example 3: Network-Level Analysis In this example the developed models are used to compare the influence of maintaining the entire network versus maintaining a proportion of it (e.g., 50% or 90%) for simulated pavement networks of urban interstate highways in different states. A roughness range of 1 to 5 m/km was assumed. Figure 16 shows the assumed roughness distributions before and after rehabilitation. The distribution before rehabilitation was obtained by specifying a normal distribution with the desired IRI range. For the other two distributions, an IRI value of 1 m/km was assigned to reha- bilitated sections. The remaining sections were then randomly assigned an IRI value from the original distribution. The vehicle kilometers traveled (VKT) for each state was estimated using Tables VM-3 and VM-1 from Highway Statistics (FHWA, 2008). Table 3 shows the speed limit for trucks and cars by state used in this example (Governors Highway Safety Association, 2011). Table 4 presents the estimated reduction in vehicle operating cost resulting from rehabilitating 50% versus 90% of the network for each state. According to a study conducted by the Pennsylvania Transportation Institute (Kilareski et al., 1990), 95% of the road network in the United States is flat and straight (grade is 0% and superelevation is 0%). Therefore, at the network level, a grade of 0% and a superelevation of 0% are reasonable assumptions to calculate VOC savings.

75 Table 3. Speed limits used in Example 3. STATE URBAN INTERSTATES STATE URBAN INTERSTATES Cars (km/h) Trucks (km/h) Cars (mph) Trucks (mph) Cars (km/h) Trucks (km/h) Cars (mph) Trucks (mph) Alabama 104 104 65 65 Montana 104 104 65 65 Alaska 88 88 55 55 Nebraska 104 104 65 65 Arizona 104 104 65 65 Nevada 104 104 65 65 Arkansas 88 88 55 55 New Hampshire 104 104 65 65 California 104 88 65 55 New Jersey 88 88 55 55 Colorado 104 104 65 65 New Mexico 104 104 65 65 Connecticut 88 88 55 55 New York 88 88 55 55 Delaware 88 88 55 55 North Carolina 112 112 70 70 Dist. of Columbia 88 88 55 55 North Dakota 120 120 75 75 Florida 104 104 65 65 Ohio 104 104 65 65 Georgia 104 104 65 65 Oklahoma 112 112 70 70 Hawaii 80 80 50 50 Oregon 88 88 55 55 Idaho 120 120 75 75 Pennsylvania 88 88 55 55 Illinois 88 88 55 55 Rhode Island 88 88 55 55 Indiana 88 88 55 55 South Carolina 112 112 70 70 Iowa 88 88 55 55 South Dakota 120 120 75 75 Kansas 112 112 70 70 Tennessee 112 112 70 70 Kentucky 104 104 65 65 Texas 112 112 70 70 Louisiana 112 112 70 70 Utah 104 104 65 65 Maine 104 104 65 65 Vermont 88 88 55 55 Maryland 104 104 65 65 Virginia 112 112 70 70 Massachusetts 104 104 65 65 Washington 96 96 60 60 Michigan 112 96 70 60 West Virginia 88 88 55 55 Minnesota 104 104 65 65 Wisconsin 104 104 65 65 Mississippi 112 112 70 70 Wyoming 96 96 60 60 Missouri 96 96 60 60 US Total 104 104 65 65

76 Table 4. Estimated vehicle operating costs for different scenarios. STATE Vehicle Operating Costs per Year ($ Billions) Reduction in VOC per Year ($ Millions) STATE Vehicle Operating Costs per Year ($ Billions) Reduction in VOC per Year ($ Millions) Original 50% 90% 50% 90% Original 50% 90% 50% 90% Alabama 2.49 2.47 2.46 25.0 34.9 Montana 0.12 0.12 0.12 1.2 1.6 Alaska 0.23 0.22 0.22 2.3 3.2 Nebraska 0.46 0.46 0.46 4.6 6.5 Arizona 2.02 2.00 1.99 20.2 28.3 Nevada 1.19 1.17 1.17 11.9 16.6 Arkansas 1.33 1.31 1.31 13.3 18.6 New Hampshire 0.53 0.53 0.52 5.3 7.4 California 23.42 23.18 23.09 234.3 327.5 New Jersey 4.67 4.63 4.61 46.8 65.3 Colorado 2.50 2.47 2.46 25.0 34.9 New Mexico 0.91 0.90 0.90 9.1 12.7 Connecticut 3.27 3.24 3.23 32.7 45.8 New York 7.00 6.93 6.90 70.1 97.9 Delaware 0.43 0.42 0.42 4.3 6.0 North Carolina 4.77 4.72 4.70 47.7 66.7 Dist. of Columbia 0.14 0.14 0.14 1.4 2.0 North Dakota 0.13 0.13 0.13 1.3 1.8 Florida 8.41 8.32 8.29 84.1 117.6 Ohio 7.66 7.58 7.55 76.6 107.1 Georgia 6.52 6.46 6.43 65.3 91.2 Oklahoma 1.59 1.57 1.56 15.9 22.2 Hawaii 0.64 0.63 0.63 6.4 8.9 Oregon 1.50 1.48 1.48 15.0 21.0 Idaho 0.43 0.42 0.42 4.3 6.0 Pennsylvania 5.05 5.00 4.98 50.5 70.7 Illinois 7.66 7.58 7.55 76.6 107.1 Rhode Island 0.59 0.59 0.58 5.9 8.3 Indiana 3.25 3.22 3.21 32.5 45.5 South Carolina 2.06 2.04 2.03 20.6 28.8 Iowa 0.87 0.86 0.85 8.7 12.1 South Dakota 0.21 0.21 0.21 2.1 2.9 Kansas 1.26 1.25 1.24 12.6 17.6 Tennessee 3.90 3.86 3.84 39.0 54.5 Kentucky 2.06 2.04 2.03 20.6 28.9 Texas 13.48 13.34 13.29 134.9 188.5 Louisiana 2.45 2.43 2.42 24.5 34.3 Utah 2.00 1.98 1.97 20.0 27.9 Maine 0.27 0.27 0.27 2.7 3.8 Vermont 0.13 0.13 0.12 1.3 1.8 Maryland 4.51 4.47 4.45 45.2 63.1 Virginia 5.13 5.08 5.06 51.4 71.8 Massachusetts 5.14 5.09 5.07 51.4 71.9 Washington 3.65 3.61 3.59 36.5 51.0 Michigan 5.24 5.19 5.16 52.4 73.2 West Virginia 1.06 1.05 1.04 10.6 14.8 Minnesota 2.90 2.87 2.86 29.0 40.6 Wisconsin 1.76 1.74 1.74 17.6 24.6 Mississippi 1.19 1.18 1.17 11.9 16.6 Wyoming 0.16 0.16 0.16 1.6 2.2 Missouri 4.17 4.13 4.11 41.7 58.3 U.S. Total 162.47 160.85 160.20 1625.6 2272.1