Moving people and goods by air, water, road and rail. The degree to - PowerPoint PPT Presentation

Moving people and goods by air, water, road and rail. The degree to which transportation infrastructure systems serve the US economic and business community objectives.

In 2000, The World Bank projected the world economy  to grow 33% between years 2000 and 2010, increasing from $31.8 trillion to $40 trillion. It reached $60.5 trillion in 2008 ($78.9 trillion in 2011  est). By the year 2050, the world economy is projected to  increase to between $135 trillion to $216 trillion. Are our infrastructure systems ready for the growth? Are the investments in US infrastructure adequate?

 Transparency  Accountability  Gaps › Currently no “rigorous” index for measuring US infrastructure, specifically in relation to economic growth › Need a well-defined methodology for creating an index › Existing methods for creating indices should be applied

 Develop methodology for constructing a US Transportation Performance Index (TPI) › Repeatable › Transparent › Use to evaluate trends in infrastructure performance  Main goal of index: measure the effect of infrastructure performance on economic prosperity

 F r agile F oundations (1988) “the a mo unt o f infra struc ture o r its c o nditio n did no t c a pture the a b ility o r c a pa b ility o f the infra struc ture to de live r the se rvic e e xpe c te d o r re q uire d”  NRC study (1997) “the de g re e to whic h the syste m se rve s multile ve l c o mmunity o b je c tive s. I de ntifying the se o b je c tive s a nd a sse ssing a nd impro ving infra struc ture pe rfo rma nc e o c c ur thro ug h a n e sse ntia lly po litic a l pro c e ss invo lving multiple sta ke ho lde rs”  T his study “the de g re e to whic h the infra struc ture syste m se rve s U.S. e c o no mic a nd multi-le ve l b usine ss c o mmunity o b je c tive s”

1. Definitions 2. Geographic Samples 3. Create Models of the Sectors and Criteria 4. Identify Indicators 5. Explore Data Sources & Assemble Data 6. Weight the Indicators 7. Compute the Index with Economic Correlation Phases  Initiation Phase – Prototype transportation index  National Complete Transportation Performance Index (TPI) (1990-2008, 2015 projections)  State by State Transportation Performance Index (1995, 2000, 2007, 2015 projections)  Update TPI for 2009

 Based on MSAs (366 in 2007) Organized based on sector › Stratified Random › Weighted based on economic contribution ›  MSA Sample for Transportation = 36 total Classifying MSA by Economic Sector › Classifying MSAs by Population › › Combining Population and Economic Sector Classifications Determining Sample Size by Economic › Classification and Population Group Selecting MSAs for the Sample ›

 Five-step process  Brainstorming (Literature review)  Exploring data (Initiation phase)  Expert meeting  Stakeholders workshops (Chicago, Atlanta, Houston, San Jose)  Revisions and data assembly

 Supply- availability and coverage  What geographical area is covered?  Quality of Service- inconvenience cost of disruption, and reliability  How well service is provided?  Efficiency- the cost of service  Does the service provide full value for cost?  Utilization- whether growth can be accommodated  How fully the existing facilities are used?

Quality of Supply Utilization Se r vic e • Highway Reserve • Highway Density • Travel Time Capacity Reliability • Transit Density • Air Reserve • Highway Safety • Airport Access Capacity • Road Roughness • Airport Capacity • Transit Reserve • Bridge Integrity • Rail Density Capacity • Air Congestion • Waterway Density • Rail Reserve • Air Safety Capacity • Port Access • Rail Safety • Intermodal – • Waterway Freight Access Congestion • Transit Safety

Quality of Supply Utilization Se r vic e • Highway Reserve • Highway Density • Travel Time Capacity Reliability • Transit Density • Air Reserve • Highway Safety • Airport Access Capacity • Road Roughness • Airport Capacity • Transit Reserve • Bridge Integrity • Rail Density Capacity • Air Congestion • Waterway Density • Rail Reserve • Air Safety Capacity • Port Access • Rail Safety • Intermodal – • Waterway Freight Access Congestion • Transit Safety Safe ty Syste m Re liability Infr astr uc tur e Condition F r e ight Move me nt and E c onomic Vitality Conge stion Re duc tion

Indicator Measure Route miles per 10,000 population Highway Density Transit Density Miles of transit per 10,000 population % of population within 50 miles of major airport Airport Access AAR/ADR per hour Airport Capacity Rail Density Route miles per 10,000 population Miles of inland waterways per sq mi Waterway Density Port Access Distance to closest international port Freight Access Numb e r o f fa c ilitie s pe r 10,000 po pula tio n Travel time index Travel time reliability Safety Fatalities per 100 million VMT % of road with IRI > 170 in./mi. Road Roughness Bridge Integrity % of bridges structurally deficient or obsolete % on time performance for departures Air Congestion Runway incursions per million operations Air Safety Rail Safety # incidents per million operations Average lock delay per tow Waterway Congestion Transit Safety # incident per million PMT % of lane miles at level of service ‘C’ or better Highway Reserve Capacity % capacity used between 7am to 9pm Air Reserve Capacity Transit Reserve Capacity PMT per capacity Ton-miles per track mile Rail Reserve Capacity

 Population over 1 million (all MSAs have airports) – 23 MSAs; 21 indicators  Population under 1 million with a primary airport – 7 MSAs; 18 indicators  Population under 1 million without a primary airport – 6 MSAs; 15 indicators.

 Bureau of Transportation Statistics (BTS)  National Transportation Atlas Data (NTAD)  Highway Performance Monitoring Systems (HPMS)  National Bridge Inventory (NBI)  National Transit Database (NTD)  Aviation System Performance Metrics (ASPM)  FAA’s Runway Safety Database  Terminal Area Forecast (TAF)  Fatal Accident Reporting System (FARS)  Federal Railroad Administration (FRA)  U.S. Army Corps of Engineers • 1990 to 2008  U.S. Bureau of Census • 10,440 pie c e s o f da ta • >10GB

Indicator #9 Highway Congestion Definition: The travel time reliability is measured by the Travel Time Index (TTI) which is the ratio of peak period travel time to free flow travel time. Why it’s The TTI expresses the average amount of extra time it takes to travel important: during peak hours relative to free‐flow travel. A TTI of 1.3, for example, indicates a 20‐minute free‐flow trip will take 26 minutes during the peak travel times, a 6‐minute (30 percent) travel time penalty. Criteria Quality of Service metric: Historical Values: Over 1 million with one or more airports (MSA Type 11) 1.40 1.20 1.00 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 Year Observations:  Congestion problems tended to be more severe from 1990 to 2007 in large urban areas. The average increase in the travel time was about 10% during this period.  As economy goes down, travel time indices slightly decrease in 2006 and 2007, probably due to less traffic on the highways. Contribution to Index: MSA type 00 (population under 1 million without primary airport) – 0.000 MSA type 01 (population under 1 million with primary airport(s)) – 0.000 MSA type 11 (population over 1 million with primary airport(s)) – 0.113 The weight factors are determined and calculated from Analytical Hierarchical Process based on a survey of U.S. Chamber members. Primary data Texas Transportation Institute, The Annual Urban Mobility Report, sources: available at http://mobility.tamu.edu, currently available from 1982 to 2007. Data issues & Detailed data are available only for most urbanized areas over 1 million opportunities population based on the availability of data provided.

 Re vie w o f the type o f da ta a nd the ra ng e o f the da ta  Gra phs o f indic a to rs b y MSA a nd o ve r time to c he c k fo r c o nsiste nc y.

 Sc a le a nd L e ve l o f Ag g re g a tio n  Missing a nd E rro ne o us Da ta › Da ta no t re po rte d o r c o lle c te d › Cha ng e s in fo rma t o r inc o nsiste nt re po rting › E rro rs in so urc e s da ta  F o re c a sting a nd Pre dic tio n  I nstitutio na l Co nstra ints

0.000 0.050 0.100 0.150 0.08 0.09 0.10 0.11 1990 1990 Over 1 million with one or more airports Under 1 million with no airports (MSA 1991 1991 1992 1992 1993 1993 1994 1994 1995 1995 (MSA Type 11) 1996 1996 1997 1997 Type 00) Year Year I 1998 1998 nte rmo da l c o nne c tivity (ra mps/ 10,000 po pula tio n) 1999 1999 2000 2000 2001 2001 2002 2002 2003 2003 2004 2004 2005 2005 2006 2006 2007 2007 2008 2008 2009 2009 0.00 0.20 0.40 Under 1 million with one or more airports 1990 1991 1992 1993 1994 1995 (MSA Type 01) 1996 1997 Year 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009