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Asset Management | Bridge Technology | Operations | Pavement

Relationships Between Asset Management and Travel Demand:
Findings and Recommendations from Four State DOT Site Visits

Exhibit 1-1 : Growth of U.S. highway miles and VMT, 1936 to 2004

Chart shows a normalized trend of increasing vehicle-miles traveled (VMTs), from 100 in 1936 to 1200 in 2004. Meanwhile, national roadway miles have remained flat, increasing only from 100 to approximately 120 over the same time period.

Exhibit 1-1 Data
YearNational Roadway MilesVMTs
1936100.00100.00
193799.33107.13
193899.69107.56
1939100.21113.20
1940100.61119.85
1941101.29132.32
1942101.29106.38
1943101.3582.57
1944101.3584.37
1945101.5999.22
1946101.50135.20
1947101.81147.11
1948101.71157.84
1949101.68168.35
1950101.41181.75
1951101.81194.78
1952102.33203.70
1953103.03215.94
1954103.92222.89
1955104.62240.21
1956104.99250.33
1957105.69255.82
1958106.49263.62
1959107.47277.83
1960108.54285.08
1961109.37292.48
1962110.19304.11
1963110.81319.38
1964111.54335.66
1965112.95352.13
1966113.19367.23
1967113.47382.35
1968112.79402.92
1969113.56421.13
1970114.20440.14
1971115.06467.54
1972115.92499.66
1973116.56520.81
1974116.80507.89
1975117.48526.58
1976118.06556.22
1977118.30581.86
1978118.92612.67
1979119.93606.49
1980118.15605.76
1981117.92616.87
1982118.33632.62
1983118.75655.54
1984119.11682.30
1985118.27703.94
1986118.70727.75
1987118.58762.00
1988118.48803.55
1989118.67831.52
1990118.36850.51
1991118.88861.49
1992119.41891.27
1993119.54910.80
1994119.58935.08
1995119.75960.95
1996119.97984.50
1997120.741,016.03
1998119.571,041.28
1999119.901,067.34
2000120.481,090.64
2001120.861,109.47
2002121.411,132.66
2003121.641,146.42
2004121.871,175.00

[ Back to Exhibit 1-1 ]

Exhibit 2-1: Primary TAM functions and their relationships

Flow chart of the asset management process, in the following order:

  1. Goals and objectives
  2. Asset inventory
  3. Condition assessment and performance modeling
  4. Alternatives evaluation and program optimization
  5. Short- and long-range plans (project selection)
  6. Program implementation
  7. Performance monitoring, which feeds back into "goals and objectives" and "condition assessment and performance modeling."
  8. "Budget/allocations" is an independent step that feeds into "goals and objectives" and "short- and long-range plans (project selection)."

[ Back to Exhibit 2-1 ]

Exhibit 2-2: Growth of population, GDP, vehicles, and total highway lane-miles

Graph shows the increase of U.S. Gross Domestic Product (GDP), population, vehicles, and lane-miles from 1980-2003. All items have a normalized value of 1 in 1980. By 2003, lane-miles increased to 1.05, population increased to 1.28, vehicles increased to 1.47, and GDP increased to 2.00.

Exhibit 2-2 Data
 1980198519901991199219931994199519961997199819992000200120022003
GDP1.001.171.381.381.421.461.521.561.611.691.761.831.901.921.952.00
Population1.001.051.101.111.131.141.161.171.191.201.211.231.241.251.271.28
Per capita GDP1.001.121.251.241.261.281.311.331.361.411.451.491.531.531.541.56
Vehicles1.001.101.201.191.201.231.251.271.301.311.331.371.401.461.451.47
Total Mileage1.001.001.001.011.011.011.011.011.021.021.011.011.021.021.031.03
Total Lane-Miles1.001.011.021.021.031.031.031.031.031.041.031.031.041.041.051.05

[ Back to Exhibit 2-2 ]

Exhibit 2-3: Growth of PMT, VMT, truck ton-miles, and total highway lane-miles

Graph shows the increase of lane-miles, person-miles traveled (PMT), VMT, and truck ton-miles from 1990-2003. All values have a normalized value of 1 in 1990. By 2003, lane-miles increased to 1.03, PMT increased to 1.33, VMT increased to 1.35, and truck ton-miles increased to 1.48.

Exhibit 2-3 Data
 19901991199219931994199519961997199819992000200120022003
Lane-miles1.001.001.011.011.011.011.021.021.011.021.021.021.031.03
PMT1.001.011.041.061.081.091.111.151.181.211.231.301.311.33
VMT1.001.011.051.071.101.131.161.191.231.251.281.301.331.35
Truck Ton-miles1.001.021.051.101.171.221.251.311.341.391.411.431.471.48

[ Back to Exhibit 2-3 ]

Exhibit 2-4: Growing share of truck ton-miles as percentage of total U.S. freight ton-miles

Graph shows the share of trucking in total ton-miles of freight from 1990-2003. The chart shows that trucking's share increased from 23.83% in 1990 to 29.01% in 2003.

Exhibit 2-4 Data
 19901991199219931994199519961997199819992000200120022003
Share of trucking in total ton-miles of freight23.83%24.28%24.18%25.10%25.50%25.65%25.92%27.06%27.44%27.84%28.08%28.35%28.75%29.01%

[ Back to Exhibit 2-4 ]

Exhibit 2-5: Growth in capacity, volume, and loadings on the Interstate system (Index: 1995=1)

This graph is a comparison of growth in volume and loadings on the urban and rural interstate system. It measures the percent change from 1995-2003 of rural average daily traffic, urban average daily traffic, rural average daily load, urban average daily load, urban interstate, and rural interstate traffic.

Adjusted data: 1995=1.00
Comparison of growth in volume and loadings on the urban and rural interstate system
Measurement: Percent change since 199
 Rural Average Daily TrafficUrban Average Daily TrafficRural Average Daily LoadUrban Average Daily LoadUrban Interstate Lane-milesRural Interstate lane-miles
19951.001.001.001.001.001.00
19961.041.031.051.051.011.01
19971.081.061.071.081.011.01
19981.121.101.101.161.021.01
19991.171.121.151.221.031.02
20001.201.151.191.341.041.02
20011.231.171.201.381.041.02
20021.251.201.221.441.051.02
20031.211.281.241.451.120.99

[ Back to Exhibit 2-5 ]

Exhibit 2-6: Urban functionally deficient bridges in 1990-2004

The bar graph shows the number of urban functionally deficient bridges each from 1990-2003. The greatest number of deficient bridges occurred in 1991, followed by the low in 1992, followed by a steadily increasing number of deficient bridges each year until 2003.

Condition of U.S. Highway Bridges
 199019911992199319941995199619971998199920002001200220032004
Functionally30,26630,84226,24326,51127,02427,48728,08726,86527,58829,06529,39829,38329,67529,88630,298

[ Back to Exhibit 2-6 ]

Exhibit 2-7: Growth of total and deficient bridges, 1990-2004

The graph shows the growth of number of total bridges compared to the number of deficient bridges. All trend lines have a normalized value of 1 in 1990. The total number of bridges increased slightly from 1990-2003, but the number of deficient bridges decreased. Lines represent the total number of deficient bridges as well as urban structurally deficient, urban functionally deficient, rural structurally deficient, and rural functionally deficient bridges.  

Exhibit 2-7 Data
 199019911992199319941995199619971998199920002001200220032004
Total bridges1.001.001.001.001.011.021.021.021.021.021.031.031.031.031.04
Total deficient bridges1.000.970.840.810.790.780.770.740.720.710.690.690.680.670.66
Total structurally deficient1.000.980.860.810.780.760.740.710.680.640.610.610.590.580.56
Total functionally deficient1.000.970.800.800.800.810.810.770.790.820.810.810.810.810.80
Urban structurally deficient1.001.010.970.950.930.900.900.880.840.770.750.750.740.730.72
Urban functionally deficient1.001.020.870.880.890.910.930.890.910.960.970.970.980.991.00
Rural structurally deficient1.000.970.850.790.760.740.710.690.650.620.590.590.570.560.54
Rural functionally deficient1.000.950.770.760.750.760.760.720.740.750.740.740.740.730.72

[ Back to Exhibit 2-7 ]

Exhibit 2-8: Urban and rural VMT per lane-mile

The bar graph shows urban and rural VMT per lane-mile from the years 1990-2003. In each year, the graph depicts both types of VMTs.

Exhibit 2-8 Data
 19901991199219931994199519961997199819992000200120022003
Urban VMT per lane-mile, total (thousands)764766775782794810820825844858869852861856
Rural VMT per lane-mile, total (thousands)136138139140144148152157165169172176179175

[ Back to Exhibit 2-8 ]

Exhibit 2-9: Roadway congestion index

The line graph shows the Roadway Congestion Index in 85 urbanized areas from 1982-2003. The average congestion in the 85 areas in 1990 is the base value for the graph. The graph includes several lines corresponding to the congestion index of small, medium, large, and very large areas as well as the aggregate congestion index. All indices increase over the period.

Exhibit 2-9 Data
 1982198519901991199219931994199519961997199819992000200120022003
85-Area Average0.810.871.001.001.011.021.031.051.071.091.101.121.141.151.161.17
Very Large Area Average0.921.001.141.131.141.141.151.171.191.211.231.251.271.281.301.30
Large Area Average0.740.810.920.930.940.960.980.991.011.031.041.071.081.091.101.11
Medium Area Average0.660.700.820.830.850.860.880.900.920.930.940.950.960.970.980.99
Small Area Average0.580.630.700.710.730.730.740.750.760.780.800.820.830.830.840.85

[ Back to Exhibit 2-9 ]

Exhibit 2-10: Travel time index

The line graph shows the Travel Time Index in 85 urbanized areas from 1982-2003. The average travel times in the 85 areas in 1990 are base values for the graph. The graph includes several lines corresponding to the travel time index of small, medium, large, and very large areas as well as the aggregate travel time index. All indices increase over the period.

Exhibit 2-10 Data
 1982198519901991199219931994199519961997199819992000200120022003
85-Area Average1.121.161.281.271.281.281.271.291.311.321.341.351.341.351.371.37
Very Large Area Average1.181.231.401.391.391.381.371.401.431.431.461.461.451.471.491.48
Large Area Average1.071.101.171.181.181.191.201.211.231.241.251.261.261.271.281.28
Medium Area Average1.051.061.091.091.101.111.121.131.141.151.151.161.161.171.181.18
Small Area Average1.031.041.051.061.061.061.061.071.071.081.081.091.101.101.101.10

[ Back to Exhibit 2-10 ]

Exhibit 2-11: Projected investment requirements versus current spending

The bar graph shows the percent above current spending required from 2001-2020 as compared to 2000. The cost to maintain highways and bridges (low scenarios) is 17.5% while the cost to improve highways and bridges (high scenario) is 65.3%.

2002 Average annual investment requirements for 2001-2020 compared to 2000 spending
 Cost to maintain highways and Bridges (low scenarios*)Cost to Improve Highways & Bridges (high scenario*)
2001-2020 vs. 200017.50%65.30%

[ Back to Exhibit 2-11 ]

Exhibit 3-1: Travel demand as inputs to and outputs of TAM processes

Flow chart of the State DOT inputs, processes, and outputs in the following order (from left to right):

  • 1.0 - Travel Demand Inputs
  • 2.1 - Processes: User of Travel Demand Measures as Inputs
  • 2.2 - Processes: Impact Travel Demand Related Outcome
  • 3.0 - Travel Demand Outcomes.

[ Back to Exhibit 3-1 ]

Exhibit 3-3: Total lane-miles statewide in sample states

The bar graph shows demographic, roadway, and travel demand characteristics. Left to right, it shows lane-miles in California, Michigan, North Carolina, and Utah in 2004 as a combination of state-controlled lane-miles and federal, municipal, and county lane-miles.

Exhibit 3-3 Data
 CaliforniaMichiganNorth CarolinaUtah
State Controlled Lane Miles50,52227,578168,02915,260
Federal, Municipal and County Lane Miles327,913229,66647,67974,028

[ Back to Exhibit 3-3 ]

Exhibit 3-4: State-controlled lane-miles in sample states

The line graph shows total lane-miles in California, Michigan, North Carolina, and Utah from 1994-2004. All the states show a relatively flat pattern of total lane miles.

Exhibit 3-4 Data
 19941995199619971998199920002001200220032004
California49,28549,34149,32549,27549,36749,45949,46349,70550,45150,34050,522
Michigan26,77426,93326,93927,02927,37627,33527,34627,42827,45627,58427,578
North Carolina163,554164,009164,287165,159165,712165,622166,157166,574166,979167,331168,029
Utah14,85614,88214,92114,87815,09515,08415,07915,10215,17815,17815,260

[ Back to Exhibit 3-4 ]

Exhibit 3-5: Average annual increase in state-controlled lane-miles

The bar graph shows the total state-controlled lane-miles (in thousands) in California, Michigan, North Carolina, and Utah.

Exhibit 3-5 Data
 Lane Miles
(Thousands)
California124
Michigan80
North Carolina448
Utah40

[ Back to Exhibit 3-5 ]

Exhibit 3-6: Percentage of state-controlled highways located in urban areas

The line graph shows the percent of urban state-controlled lane-miles in California, Michigan, North Carolina, and Utah from 1994-2004. All the lines are relatively flat except two sharp increases, the first in Michigan from 2002-2003 and the second in Utah from 2003-2004.

Exhibit 3-6 Data
 19941995199619971998199920002001200220032004
California40%41%41%41%41%41%41%41%41%41%42%
Michigan31%32%32%32%32%32%32%32%32%39%39%
North Carolina14%14%14%14%14%14%14%14%14%14%14%
Utah19%19%19%19%19%19%19%20%20%20%25%

[ Back to Exhibit 3-6 ]

Exhibit 3-7: Daily VMT on state-controlled highways

The line graph shows the average number of daily VMT in California, Michigan, North Carolina, and Utah from 1994-2004. Michigan, North Carolina, and Utah showed a slight increase in daily VMT over the period. California showed a much steeper increase in daily VMT over the same period.

Daily VMT (in thousands)
 19941995199619971998199920002001200220032004
California394,049400,417405,968403,592419,488433,029447,888459,679476,038490,495502,858
Michigan124,533124,744128,210149,676156,727157,637159,910159,469162,762159,415159,951
North Carolina170,922180,300186,971193,646203,370209,894213,355218,368221,691223,193227,536
Utah35,54037,07138,13040,64642,05543,72743,94945,66348,14546,82047,575

[ Back to Exhibit 3-7 ]

Exhibit 3-8: AADT per lane on state-controlled highways

This exhibit presents the mix of alignment lengths and grades for the nineteen projects included in the database. The database sample includes a broad range of alignment types, ranging from those that are entirely at-grade to those with no at-grade and only elevated and underground segments. The guideway lengths range from a minimum of 30,000 lineal feet to a maximum of 140,000 lineal feet.

AADT per Lane
 19941995199619971998199920002001200220032004
California7,9958,1158,2308,1918,4978,7559,0559,2489,4369,7449,953
Michigan4,6514,6324,7595,5385,7255,7675,8485,8145,9285,7795,800
North Carolina1,0451,0991,1381,1721,2271,2671,2841,3111,3281,3341,354
Utah2,3922,4912,5552,7322,7862,8992,9153,0243,1723,0853,118

[ Back to Exhibit 3-8 ]

Exhibit 3-9: AADT per lane on urban versus rural state-controlled highways

The line graph shows the Average Annual Daily Traffic (AADT) in California, Michigan, North Carolina, and Utah for urban and rural roads from 1994-2004. There are 8 lines on the graph, an urban and a rural line for each state. All of the lines show a slight increase in AADT, except urban roads in California which showed a much steeper increase in AADT over the same period.

AADT per Lane on Rural Highways
 19941995199619971998199920002001200220032004
California3,4053,4683,5093,5723,4113,7923,9274,2064,2844,5104,601
Michigan2,9232,8922,9883,9604,0834,1094,1224,1364,2163,7213,747
North Carolina692725754766796825832851866869877
Utah1,2601,3221,3581,4361,4921,5521,5851,6371,7081,6161,463
AADT per Lane on Urban Highways
 19941995199619971998199920002001200220032004
California14,78214,87915,11514,93915,57415,99316,49416,57816,75417,19017,433
Michigan8,4138,3718,5728,9309,2509,3059,5229,3859,5679,0439,048
North Carolina3,2173,3923,5113,6953,8544,0004,0654,1394,1584,2384,238
Utah7,2317,4867,6618,2588,1578,4948,4428,7429,2019,1028,074

[ Back to Exhibit 3-9 ]

Exhibit 3-11: Total annual travel delay in sample state urban areas

The bar graph show the total annual delay in hours for travelers in select cities in California, Michigan, North Carolina, and Utah. The graph includes 9 cities from California, 2 cities from Michigan, 2 cities from Utah, and 1 city from North Carolina. LA-Long Beach (624 million hours), Detroit (120 million hours), Charlotte (17 million hours), and Salt Lake City (15 million hours) had the greatest number of delay hours for each state, respectively.

Annual Travel Delay (Millions of Hours)
Source: The 2005 Urban Mobility Report, Texas Transportation Institute
 CaliforniaMichiganNorth CarolinaUtah
Los Angeles-Long Beach, CA624   
San Francisco-Oakland, CA152   
San Diego, CA82   
Riverside-San Bernardino, CA50   
San Jose, CA48   
Sacramento, CA36   
Oxnard-Ventura, CA10   
Fresno, CA4   
Bakersfield, CA2   
Detroit, MI 120  
Grand Rapids, MI 6  
Charlotte, NC  17 
Raleigh-Durham, NC  11 
Salt Lake, UT   15

[ Back to Exhibit 3-11 ]

Exhibit 3-12: Annual delay per traveler in sample state urban areas

The bar graph shows the average annual delay in hours per traveler for travelers in select cities in California, Michigan, North Carolina, and Utah. The graph includes 9 cities from California, 2 cities from Michigan, 2 cities from Utah, and 1 city from North Carolina. LA-Long Beach (93 hours), Detroit (57 hours), Charlotte (43 hours), and Salt Lake City (31 hours) had the greatest number of hour for each state, respectively.

Annual Travel Delay Per Traveler (Hours of Delay Per Traveler)
Source: The 2005 Urban Mobility Report, Texas Transportation Institute
 CaliforniaMichiganNorth CarolinaUtah
Los Angeles-Long Beach, CA93   
San Francisco-Oakland, CA72   
San Diego, CA52   
Riverside-San Bernardino, CA55   
San Jose, CA53   
Sacramento, CA40   
Oxnard-Ventura, CA33   
Fresno, CA13   
Bakersfield, CA7   
Detroit, MI 57  
Grand Rapids, MI 19  
Charlotte, NC  43 
Raleigh-Durham, NC  27 
Salt Lake, UT   31

[ Back to Exhibit 3-12 ]

Exhibit 3-13: Truck traffic as a share of statewide VMTs

The bar graph compares the percentage of trucks' share of total VMT for urban and rural roads in California, Michigan, North Carolina, Utah and the national average.

Exhibit 3-13 Data
 RuralUrban
California15.7%7.1%
Michigan10.4%7.1%
North Carolina12.6%9.1%
Utah26.7%11.4%
National Average15.6%7.7%

[ Back to Exhibit 3-13 ]

Exhibit 3-14: Capital and maintenance expenditures from federal, state and local sources (2004)

The chart is a combination of a bar graph and a line graph. The bar graph represents the total annual funds expended on state-controlled roadways. The line graph represents the average amount of expenditures per lane-mile on these roadways. The graph shows that Michigan and Utah spend a comparatively higher amount per lane-mile as compared to total number of lane-miles. North Carolina spends a comparatively lower amount. California falls in between.

Exhibit 3-14 Data
 CaliforniaMichiganNorth CarolinaUtah
Expenditures per Lane Mile ($Thousands)$95.8$48.6$14.3$36.6
Capital and Maintenance Expenditures ($Billions)$4.84$1.34$2.40$0.56

[ Back to Exhibit 3-14 ]

Exhibit 4-1: MDOT's organizational structure

This is an organization chart for the Michigan State Department of Transportation. The key information from this chart is that "Asset Management," "Statewide Planning," and "Project Planning" are all sub-entities of the "Transportation Planning" Bureau.

[ Back to Exhibit 4-1 ]

Exhibit 4-2: Example RQFS output based on a hypothetical investment scenario

The bar graph compares 2004 remaining service life (RSL) for pavements to 2015 RSL. For each year, it shows the percentage of pavement surface miles that have an expected RSL of 0-2 years, 3-7 years, 8-12 years, 13-17 years, and 18+ years. The graph also indicates that RSL of 0-2 years is "poor" while RSL greater than 3 years is "good." The graph indicates that in 2004, a greater percentage of roads have a service life of 0-7 years than in 2015. In 2015, there a higher percentage of roads is expected to have RSL longer than 2 years than the percentage of roads with RSL longer than 2 years in 2004.

Exhibit 4-2 Data
 2004 RSL2015 RSL
0-2 Yrs18%12%
3-7 Yrs32%23%
8-12 Yrs35%38%
13-17 Yrs6%19%
18+ Yrs3%2%

[ Back to Exhibit 4-2 ]

Exhibit 4-3: MDOT's organizational structure

This is an organization chart for the Utah Department of Transportation. The key information from this chart is that "Project Planning and Programming," "Transportation Planning," "Pavement Management," "Program Financing," and "Engineering Planning Statistics" are all sub-entities of the "Systems Planning and Programming" Division.

[ Back to Exhibit 4-3 ]

Exhibit 4-4: Caltrans' organizational structure

This is an organization chart for the Utah Department of Transportation. The key information from this chart is that "Project Planning and Programming," "Transportation Planning," "Pavement Management," "Program Financing," and "Engineering Planning Statistics" are all sub-entities of the "Systems Planning and Programming" Division.

[ Back to Exhibit 4-4 ]

Exhibit 5-1: Similarities between TAM and SLRP processes

2 Flow charts side-by-side, in order to highlight the similarities between them.

Chart 1 - Transportation Asset Management Process, in the following order:

  1. Goals and objectives
  2. Asset inventory
  3. Condition assessment and performance modeling
  4. Alternatives evaluation and program optimization
  5. Short-and long-range plans (project selection)
  6. Program implementation
  7. Performance monitoring, which feeds back into "goals and objectives" and "performance modeling."
  8. Budget allocations is an independent step that feeds into "goals and objectives" and "short- and long-range plans (project selection).

Chart 2 - Statewide Long Range Planning Process, in the following order:

  1. Vision, goals and objectives
  2. Condition and performance assessment
  3. Investment strategies
  4. Needs identification
  5. Project selection/prioritization
  6. Performance monitoring
  7. Long range budget (optional) is an independent step that feeds into "Project selection/prioritization"

[ Back to Exhibit 5-1 ]

Exhibit 5-2: Michigan: Congested Vs. UnCongested VMTs on State Controlled Routes

The bar graph compares congested and uncongested VMTs on state-controlled roads in Michigan in 2000 and 2005. It shows the total VMTs in each year and the portion of congested and uncongested VMTs for each.

Exhibit 5-2 Data
 20002025
UnCongested44.854.3
Congested6.711.2

[ Back to Exhibit 5-2 ]

Exhibit 5-3: Number of SLRPs containing various pieces of information

The bar graph shows the number of states that took certain topics into consideration when outlining long-range plans. The topics included include (from left to right): "amount & source of revenues" (30), "amount & source of expenses" (23), "amount of shortfall" (14), and "ways to meet shortfall" (18).

Exhibit 5-3 Data
Amount & Source of Revenues30
Amount & Source of Expenses23
Amount of Shortfall14
Ways to Meet Shortfall18

[ Back to Exhibit 5-3 ]

Exhibit 5-4: MDOT road, bridge and routine maintenance program (un-prioritized)

The chart shows the budget for the Michigan DOT road and bridge program and routine maintenance. It shows the amount of money required for various expenditures in 2003 and the expected expenditures required in 2025. It also shows the 2003 and 2025 revenues as compared to the total cost, resulting in a funding gap.

MDOT Road & Bridge Program and Routine Maintenance (Unprioritized)
($Millions)
 20032025
Routine Maintenance245500
Congressional Set Asides3050
Federal Special Programs (e.g., CMAQ)60190
Safety4590
Bridge100406.7
Road Preservation530970
State Programs2550
Capacity Improvement250510
New Roads660270
Unfunded program 1130
Total annual investment19454166.7

[ Back to Exhibit 5-4 ]

North Carolina's Transportation Spending: 1995-2000

A pie chart that exhibits North Carolina's transportation spending from 1995 to 2000 including: "highway expansion" (45%), "highway maintenance and preservation" (31%), "highway modernization" (17%), and "transit, rail, ferry, ITS" (7%).

[ Back to Exhibit 555a ]

North Carolina Transportation Funding By Source

A pie chart that exhibits North Carolina's transportation funding by source (2000-2001 average) including: "motor fuels" (39%), "federal aid" (26%), "highway use" (18%), "registration fees" (12%), "titles" (12%), and "other" (2%).

[ Back to Exhibit 555b ]

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Updated: 11/06/2012