Measure:

Fatalities per 100 million vehicle-miles-traveled (VMT) (CY)

Scope:

The number of fatalities is the total number of motor vehicle traffic fatalities which occur on public roadways within the 50 states and Washington, D.C.

Vehicle Miles of Travel (VMT) represent the total number of vehicle miles traveled by motor vehicles on public roadways within the 50 states and Washington, D.C.

Source:

Motor vehicle traffic fatality data are obtained from NHTSA’s Fatality Analysis Reporting System (FARS).  To be included in FARS, a motor vehicle traffic crash must result in the death of a vehicle occupant or a non-motorist within 30 days of the crash.  The FARS database is based on police crash reports and other state data. FARS includes fatalities on all roadways open to the public, using the National Highways System classification of roads.  Pedestrian and bicycle fatalities that occur on public highways, but do not involve a motor vehicle, are not recorded in FARS.  However, they constitute only a small number of fatalities.

VMT data are derived from FHWA’s Traffic Volume Trends (TVT); a monthly report based on hourly traffic count data in the Highway Performance Monitoring System (HPMS).  Information is transmitted to NHTSA where it is reviewed for consistency and accuracy before being entered into the system. These data, collected at approximately 4,000 continuous traffic counting locations nationwide, are used to determine the percentage change in traffic for the current month from the same month of the previous year.  The percentage change is applied to the nationwide travel for the same month of the previous year to obtain an estimate of nationwide travel for the current month.  The data are recorded as monthly totals and cumulative yearly totals.

Limitations:

VMT data are subject to sampling errors, the magnitude of which depends on how well the locations of the continuous counting locations represent nationwide traffic rates.  HPMS is also subject to estimating differences by States, even though FHWA works to minimize such differences and differing projections on growth, population, and economic conditions that impact driving behavior.

Statistical Issues:

The primary source of uncertainty in estimating fatality rates is the denominator.  While the estimate of total fatalities used in the numerator is relatively accurate, the estimate of total vehicle miles in the denominator has far more variability.

Estimates of the number of persons killed in motor vehicle traffic crashes during 2002 are preliminary and are based on incomplete data and statistical models.  NHTSA’s first official estimates for 2002, the Early Assessment, are being developed and will be completed in early April 2003.  Differences between the official Early Assessment estimates and those in this report are to be expected. 

Verification & Validation:

Fatality data from FARS are reviewed and analyzed by NHTSA’s National Center for Statistics and Analysis.  Quality control procedures are built into annual data collection at 6 and 9 months, and at year’s end.  A study was completed in 1993, looking at samples of FARS cases in 1989 through 1990 to assess the accuracy of data being reported.  VMT data are reviewed by FHWA for consistency and reasonableness.

Comment:

This data program has been in use for many years and is generally accepted for describing safety on the Nation’s highways.  Adjusting raw highway fatalities and injuries by VMT provides a means of portraying the changes in highway fatalities on a constant exposure basis and facilitates year-to-year comparisons.

Measure:

Fatalities in crashes involving large trucks per million truck VMT. (CY)

Scope:

The measure includes all fatalities (e.g., drivers and occupants of passenger cars, motorcycles, large trucks, or pedestrians) associated with crashes involving trucks with a gross vehicle weight rating of 10,000 pounds or more. The numerator (fatalities) comes from NHTSA’s Fatality Analysis Reporting System (FARS) data, a census of fatal traffic crashes within the 50 states, Puerto Rico, and Washington, D.C.  The denominator is vehicle miles of large truck travel (VMT).

Source:

NHTSA’s Fatality Analysis Reporting System (FARS) provides fatality data.  The VMT data are derived from the Federal Highway Administration’s (FHWA) Highway Performance Monitoring System (HPMS).

Limitations:

FARS data elements are modified from year to year to respond to emphasis areas, vehicle fleet changes, and other needs for improvement.  Large truck VMT reported to FHWA by each state is based on a sample of road segments and is not a census.  In addition, the methods used to calculate total VMT may vary from state to state. The methods used by the states to estimate the VMT contribution from rural and urban minor collectors are unknown. 

VMT data are subject to sampling errors, the magnitude of which depends on how well the locations of the continuous counting locations represent nationwide traffic rates.  HPMS is also subject to estimating differences by States, even though FHWA works to minimize such differences and differing projections on growth, population, and economic conditions that impact driving behavior.

Statistical Issues:

The fatality counts in FARS are generally quite accurate.  The major sources of error are underreporting by some precincts and inconsistent use of the definition of a truck. 

Verification & Validation:

Fatality data are reviewed and analyzed by NHTSA’s National Center for Statistics and Analysis.  Quality control procedures are built into data collection and data processing.  A study using samples of 1989-1990 FARS cases was completed in 1993 to assess the accuracy of data being reported.  FHWA routinely works with state data providers to modify reported VMT values that do not appear reasonable before incorporating them into its final master file.

Comment:

The FARS data have been around for many years and are generally accepted as a good source for describing fatal crashes on the Nation’s highways.  .

Measure:

Fatal aviation accidents (U.S. commercial air carriers) per 100,000 departures. (FY)

Scope:

This measure includes both scheduled and nonscheduled flights of large U.S. air carriers (14 CFR Part 121) and scheduled flights of commuter airlines (14 CFR Part 135).  It excludes on-demand (i.e., air taxi) service and general aviation.

Source:

Part 121 and Part 135 departure data is submitted to BTS under 14 CFR Parts 241 and 298, respectively.  NTSB provides accident data.

Limitations:

The fatal accident rate in these categories is small and could significantly fluctuate from year to year due to the occurrence or non-occurrence of a single accident.

Statistical Issues:

The switch from calendar to fiscal year in 2001, combined with the use of departures rather than flight hours as the activity measure for the denominator, presents problems.  To overcome reporting delays of 60 to 90 days, FAA must rely on historical data, partial internal data sources, and Official Airline Guide (OAG) scheduling information to project at least part of the fiscal year activity data.  Due to the reporting procedures in place, it is unlikely that calculation of future fiscal year departure data will be markedly improved.  Lacking complete historical data on a monthly basis and independent sources of verification increases the risk of error in the activity data. 

Verification & Validation

The FAA does comparison checking of the departure data collected by BTS.  FAA compares its list of carriers to the DOT list to validate completeness of the reporting list and places the carriers in the appropriate category (i.e., Part 121 or Part 135).  NTSB and FAA’s Office of Accident Investigation meet regularly to validate the accident count.

Comment:

The joint government/industry group working on improving the level of safety for U.S. commercial aviation has determined that the number of departures is a better denominator measure to use for determining accident rates.  In a recent report on the Safer Skies effort the Government Accounting Office agreed and recommended that the FAA use departures. 

Measure:

Number of fatal general aviation accidents. (FY)

Scope:

The measure includes on-demand (non-scheduled FAR Part 135) and general aviation.  General aviation comprises a diverse range of aviation activities.  The range of general aviation aircraft includes single-seat homebuilt aircraft, helicopters, balloons, single and multiple engine land and seaplanes including highly sophisticated extended range turbojets.

Source:

National Transportation Safety Board (NTSB).

Limitations:

The use of the 1996-1998 timeframe for the baseline represents one of the safest periods in general aviation history in terms of a decline in fatal accidents.  The number of general aviation accidents reported in any given year might change in subsequent years.  There are many reasons for these changes to the historical data.  Primary among them is that the accident had not been reported to the NTSB, or that it was misreported and the information corrected at a later date.

Statistical Issues:

There is no major error in the accident counts.  Random variation in air crashes results in a significant variation in the number of fatal accidents over time. 

Verification & Validation:

NTSB and FAA’s Office of Accident Investigation meet regularly to validate the information on the number of accidents. 

Comment:

It would be preferable to use fatal accident rates rather than fatal accidents as the performance measure. However, general aviation flight hours are based on an annual survey conducted by the FAA.  Response to the survey is voluntary.  The accuracy of the flight hours collected is suspect and there is no readily available way to verify or validate the data.  For this reason, the General Aviation community is unwilling to use a rate measure until the validity and reliability of the survey data can be assured.

Measure:

Train accidents and incidents per million train-miles. (FY)

Scope:

Train accidents include all reportable occurrences above a monetary damage threshold.  Train incidents include all collisions with on-track equipment and highway users at public and private grade crossings.

Source:

Railroad Safety Statistics – Annual Report.  Statistical data, tables, and charts depict the causes and nature of rail accidents.  Data on accidents, collisions, and train miles are reported to FRA by railroad companies.

Limitations:

This scope is consistent with the regulatory authority of the agency, but not consistent with other modes of transportation for comparative purposes.

Statistical Issues:

The reported estimates are based upon partially reported data from 2002. 

Verification & Validation:

Railroads are required by law to submit monthly accident/incident reports to FRA.  They are also required to update any inaccurate or incomplete information.  FRA conducts routine data audits (records inspections) to verify the adequacy of railroad reporting and record keeping requirements.

Comment:

None.

Measure:

Transit fatalities per 100 million passenger miles traveled. (CY)

Scope:

The data include both riders and employees.  A fatality is defined as a transit-caused death from collision, personal casualty, fire, derailment, or bus going off the road.

Source:

FTA’s Safety Management Information System (SAMIS), with data reported by transit operators to the National Transit Database (NTB).

Limitations:

Because of the scope of the reporting criteria, some fatalities that are counted are not associated directly with transit operation.  This scope is consistent with the regulatory authority of the agency, but not consistent with other modes of transportation for comparative purposes.

Statistical Issues:

The fatality counts in SAMIS are generally quite accurate---the major source of error in the measure comes from uncertainty in the passenger miles traveled

Verification & Validation:

An independent auditor and the transit agency’s CEO certify that data reported to the NTD are accurate.  Using data from the NTD to compile the SAMIS data, the Transportation Systems Center compares current safety statistics with previous years, identifies questionable trends, and seeks explanation from operators.

Comment:

None.

Measure:

Number of incident for natural gas and hazardous liquid pipelines. (FY)

Scope:

This measure is based on reported hazardous liquid and natural gas accidents that meet federal reporting criteria as defined in 49 CFR 191.1 and 191.15 for natural gas transmission pipeline incidents and in 49 CFR 195.50 for hazardous liquid pipelines. 

Source:

RSPA’s Natural Gas Distribution and Transmission Incident Reports and Hazardous Liquid Pipeline Accident Reports. Failure reports are filed within 30 days of the occurrence of reportable incidents.  Complete calendar year data are available by March 1 of the following year.  Data may change as operators file supplemental reports.

Limitations:

RSPA lacks adequate infrastructure information on pipeline operations and maintenance needed to fully characterize problems when they occur and lacks information on precursor conditions that contribute to incidents.  RSPA seeks further improvements in data collection in 2002 to address these concerns.

Statistical Issues:

Because of delays in mail delivery associated with 9/11/2001 terrorist activities, statistical close-out of the 2001 tally requires an extrapolation of number of reports anticipated for the last quarter of 2001.

Verification & Validation:

RSPA reviews/verifies data provided for accuracy and requests supplemental reports where shortcomings are indicated.

Comment:

None.

Measure:

Number of serious hazardous materials incidents in transportation. (CY)

Scope:

Serious hazardous materials incidents are those resulting in a fatality or major injury, the evacuation of 25 or more employees or responders or any number of the general public, the closure of a major transportation artery, the alteration of an aircraft flight plan or operation caused by the release of a hazardous material or the exposure of hazardous material to fire; plus any release of radioactive materials from Type B packaging, Risk Group 3 or 4 infectious substance, over 11.9 gallons or 88.2 pounds of a severe marine pollutant, or a bulk quantity (over 119 gallons or 882 pounds) of a hazardous material.  This measure tracks only transportation related releases of hazardous materials that are in commerce.  Volume of spills is not tracked, as this does not necessarily indicate risk.

Source:

Hazardous Materials carriers report data to RSPA for entry into the Hazardous Materials Information System (HMIS).

Limitations:

Data for all hazardous materials incidents is suspected of being incomplete due to under-reporting for minor incidents.  Most reportable serious incidents are in the system, making this a more consistent measure for program management.  However, it does not reflect all incidents.  RSPA has issued an NPRM to revise the reporting system.

Statistical Issues:

Although the number of incidents is likely to be underreported, such recording error is probably small in comparison to the annual variation due to chance. 

Verification & Validation:

RSPA verifies the data by periodic follow-up reviews of data entry by the manager of the Hazardous Materials Information System, and verification audits of the data entry process.  RSPA crosswalks HMIS reports against the National Response Center log of accidents.  RSPA is improving compliance with reporting requirements by correlating HMIS reports with FRA’s Accident Report data and the HMIS telephonic data.  RSPA is piloting and plans to incorporate procedures to correlate HMIS reports with FHWA’s Safetynet Accident File data.

Comment:

None.

Measure:

Percentage of travel on the National Highway System (NHS) meeting pavement performance standards for acceptable ride. (CY)

Scope:

Data include vehicle miles traveled on the HPMS reported NHS sections and pavement ride quality data reported using the International Roughness Index (IRI).

IRI is a quantitative measure of the accumulated response of a "quarter-car" vehicle suspension experienced while traveling over a pavement.

Vehicle Miles of Travel (VMT) represent the total number of vehicle miles traveled by motor vehicles on public roadways within the 50 states and Washington, D.C.

Source:

Data collected by the State Highway Agencies and reported to FHWA for the Highway Performance Monitoring System (HPMS).  They are obtained from calibrated measurement devices that meet industry set standards.  Measurement procedures are included in the HPMS Field Manual.

VMT is a calculated product of the annual average daily traffic (AADT) and the centerline length of the section for which the AADT is reported. In the HPMS, travel is accumulated for each universe section to develop appropriate totals for the higher functional systems. AADT is required for each section of Interstate, NHS, and other principal arterial; as a result, travel is computed for these functional systems on a 100-percent basis. For minor arterial, rural major collector and urban collector systems, travel is calculated from samples using the AADT, centerline length reported for each sample section and the HPMS sample expansion factor for each section. Travel for the NHS on all functional systems is computed from the universe AADT data.

For the most part, travel for the rural minor collector and rural/urban local functional systems is calculated by the States using their own procedures and is provided in HPMS on a summary basis. Some States use supplemental traffic counts outside of the HPMS procedures; others employ estimating techniques, such as fuel use, to determine travel on these systems. In general, these methods are used in both rural and urban areas, including the donut areas of nonattainment areas to meet Clean Air Act requirements.

Limitations:

IRI data for the approved NHS exist from 1995 onward. Past data (1993 and 1994) contain some variation as this data was on the proposed, rather than the existing NHS. No NHS IRI data are available prior to 1993.  The HPMS requires States to report IRI data every two years; however, following the requirements is not mandated, but voluntary.

VMT estimates reported via the HPMS should be of reasonable quality particularly for the higher order functional systems. AADT and travel data are edited by the HPMS software for unusual values and for unusual changes to previously reported values. FHWA routinely works with State data providers to modify reported AADT values that do not appear to be reasonable before final use. Although AADT is required to be updated annually in HPMS, counts are only required to be updated on a 3-year cycle. For any reporting year, AADT for uncounted sections is usually derived by factoring the latest year's count for those sections.

Statistical Issues:

The major source of error in the percentages is sampling error from selecting the segments of highway tested for smoothness. 

VMT data are subject to sampling errors, whose magnitude depends on how well the locations of the continuous counting locations represent nationwide traffic rates.  HPMS is also subject to estimating differences in the states, even though FHWA works to minimize such differences and differing projections on growth, population, and economic conditions which impact driving behavior.

Verification & Validation:

FHWA validates the data based on consistency reviews. States that follow the HPMS sampling instructions in developing traffic counting programs (Appendix F in the HPMS Field Manual) and the practices advocated in the Traffic Monitoring Guide have adequate counting and classification tools to prepare quality AADT and travel estimates for HPMS. The consistency of the sampling and counting procedures should also provide comparable State-to-State traffic data.

Comment:

None.

Measure:

Of total annual urban-area travel, percentage that occurs in congested conditions (CY)

Scope:

Data obtained from approximately 400 urban areas.  The data reflects the travel conditions of the freeway and principal arterial street networks.  Definitions:

1.       Urban area:  Developed area with a density of greater than 1,000 persons per square mile.

2.       Congested travel:  Traveling below the posted speed limit(s).

Source:

Data collected and provided by the State Departments of Transportation from existing State or local government databases, including those of Metropolitan Planning Organizations.  The Federal Highways Administration’s Highway Performance Monitoring System serves as the repository of the data.  The Texas Transportation Institute utilizes HPMS data to derive the above measures.  

Limitations:

Data is available through 2001.  The proportion of congested travel figures used in calculating the measures are computed rather than measured values.  The computed values may understate congestion, as delay from incidents is not calculated.  Performance evaluation is process-oriented.  Transportation programs that help combat highway congestion possess outcome-oriented, objective methods within the specific program areas; however, the causal relationship between the programs and overall highway congestion is inconclusive.

Statistical Issues:

Methodology used to calculate performance measures has been developed by the Texas Transportation Institute and used in their annual Mobility Study.  A detailed description of TTI’s methodology is available at http://mobility.tamu.edu/.

Verification & Validation:

State-reported HPMS data are reviewed by FHWA for completeness, consistency, and adherence to reporting guidelines.  When necessary, and with close State cooperation, data may be adjusted to improve completeness, consistency, and uniformity.

Comment:

The availability of Highway Performance Monitoring System (HPMS) data is approximately 9 months from the base year, e.g., 2002 actual numbers will not be available from HPMS until October 2003.  To accurately and reliably manage the transportation system, real-time (minute-by-minute) measurement of system speeds is needed and can only be achieved with automated instrumentation. 

Measure:

Average percent change in transit passenger-miles traveled per transit market, adjusted for employment . (FY)

Scope:

Includes revenue-passenger miles on publicly sponsored bus, transit rail, commuter rail, ferry, and vanpools in urbanized areas.  Also includes employment statistics from the U.S. Department of Labor, to weight the percent increase in revenue passenger miles per transit market, to normalize the data for relative levels of employment in urban areas.

Source:

National Transit Database (NTD), with information gathered from transit operators.  Bureau of Labor Statistics employment data.

Limitations:

Data is self-reported by transit agencies using an FTA-approved sampling methodology.  Although most data is reported in the National Transit Database each year, sample cycles may be annual, every three years, or every five years depending on the size of the urban area and the number of vehicles operated.  Ridership is an outcome indicator that reflects a variety of factors, including the capital investment of the Federal Government.  Ridership is also influenced by operational decisions of transit authorities, and the availability and cost of alternative modes of transportation.

Statistical Issues:

The sources of uncertainty include sampling error, annual chance variation, and auditing issues. 

Verification & Validation:

An independent auditor and the transit agency’s CEO certify that data reported to the NTD are accurate.  FTA also compares data to key indicators such as vehicle revenue miles, number of buses in service during peak periods, etc.

Comment:

None.

Measure:

1.  Percentage of on-time flights. (FY)

Scope:

The time of arrival of completed, scheduled passenger flights to and from the 32 DOT large-hub airports is compared to their scheduled time of arrival.  The sum of flights arriving on or before 15 minutes of scheduled arrival time is divided by the total number of completed flights.

Source:

Bureau of Transportation Statistics on-time flight database as reported by major air carriers under 14 CFR Part 234, Airline Service Quality Performance Reports,

Statistical Issues:

There is little major error in the count of completed flights or the count of flights that arrive on-time.

Limitations:

None.  

Verification & Validation:

BTS conducts various edit checks and data quality tests to ensure the airline-reported data is accurate.

Comment:

None. 

Measure:

Percentage of days in the shipping season that the U.S. sectors of the St. Lawrence Seaway locks are available, including the two U.S. Seaway locks in Massena, N.Y. (CY)

Scope:

The availability and reliability of the U.S. sectors of the St. Lawrence Seaway, including the two U.S. Seaway locks in Massena, N.Y., are critical to continuous commercial shipping during the navigation season (late March to late December).  System downtime due to any condition (weather, vessel incidents, malfunctioning equipment) causes delays to shipping, affecting international trade to and from the Great Lakes region of North America.  Downtime is measured in minutes/hours of delay for weather (visibility, fog, snow, ice); vessel incidents (human error, electrical and/or mechanical failure); water level and rate of flow regulation; and lock equipment malfunction.

Source:

SLSDC gathers the data from internal Lock Operations records.

Limitations:

As the agency responsible for the operation and maintenance of the U.S. portion of the St. Lawrence Seaway, SLSDC’s lock operations unit gathers primary data for all vessel transits through the U.S. Seaway sectors and locks, including any downtime in operations.  Data is collected on site, at the U.S. locks, as vessels are transiting or as operations are suspended.  This information measuring the System’s reliability is compiled and delivered to SLSDC senior staff each month.  In addition, SLSDC compiles annual System availability data for comparison purposes.  Since SLSDC gathers data directly from observation, there are no limitations.

Statistical Issues:

None.

Verification & Validation:

SLSDC verifies and validates the accuracy of the data through review of 24-hour vessel traffic control computer records, radio communication between the two Seaway entities and vessel operators; and video and audiotapes of vessel incidents.

Comment:

SLSDC influences the measure primarily through capital planning, and consistent facilities maintenance and investment.

Measure:

1.      Percentage of bus fleets that are Americans with Disabilities Act (ADA) compliant. (CY)

2.      Percentage of key rail stations that are ADA compliant. (CY)

Scope:

Accessibility for bus fleet means that vehicles are lift or wheel chair ramp equipped.   Accessibility for key rail facilities is determined by standards for ADA compliance.

Source:

Data on bus accessibility is collected in the National Transit Database (NTD), with information gathered from transit operators.  Data on rail accessibility is reported to FTA by the transit authorities.

Limitations:

Measure does not capture ADA compliance (or transportation accessibility) for modes other than transit.

Statistical Issues:

None.

Verification & Validation:

For bus accessibility, an independent auditor and the transit agency’s CEO certify that data reported to the NTD are accurate.  Data are also compared with fleet data reported in previous years, and crosschecked with other related operating/financial data in the report.  Fleet inventory is reviewed as a part of FTA’s Triennial Review, and a visual inspection is made at that time.  FTA’s Office of Civil Rights conducts oversight reviews in order to verify the information on key rail station accessibility which has been self-reported by the transit authorities.

Comment:

FTA will primarily influence the goal through Federal transit infrastructure investment, which speeds the rate at which transit operators can transition to ADA-compliant facilities and equipment.

Measure:

Number of employment sites that are made accessible by Job Access and Reverse Commute transportation services. (FY)

Scope:

This measure assesses one part of the Job Access and Reverse Commute program – the number of employment sites made accessible that were not previously accessible.  An employment site is considered accessible if located within 1/4 mile of services provided by the grantee.  Employment sites must offer jobs that require a high school diploma or less.  Services that make an employment site accessible may include, but are not limited to, carpools, vanpools, and demand-responsive services as well as traditional bus and rail public transit.  The measure cannot account for those Job Access and Reverse Commute activities that encourage riders to use already existing sources of public transit. 

Source:

Data are provided to FTA by grantees of the Job Access and Reverse Commute program in their quarterly progress reports.

Limitations:

This measure includes the “goal” of the commute and the job, but it does not include the “starting line” of the commute, the rider’s home.  Although jobs may be made more accessible to transportation services, these services may not provide access to potential workers’ communities.  This measure also cannot account for improved accessibility due to lower fares or shorter commute times – it only addresses the gap in service delivery.  FTA requires a greater level of precision from larger, urban grantees than rural grantees that may have fewer resources at their disposal.

Statistical Issues:

FTA estimates performance based on usable information reported by grantees, but FTA has had difficulty in getting complete information from its grantees.  Currently FTA has received usable information from approximately 40% of its grantees.

Verification & Validation:

FTA will use an oversight contractor to verify reported information on a sample basis.

Comment:

None.

Measure:

Number of passengers (in millions) in international markets with open skies aviation agreements. (FY)

Scope:

These data are collected by DOT for all flight segments to/from a U.S. point. The data for this measure include all passengers on U.S. and foreign carrier flights to and from 47 “open-skies” countries and Canada.  This indicator reflects (barring significant, unrelated macroeconomic and political influences) the extent to which the competitive environment promoted by DOT increases travel opportunities.

Source:

U.S. air carriers file domestic and foreign data in the T-100 system.  Foreign carrier data are from the T-100F database.  Foreign air carriers file data for all nonstop flight segments involving a U.S. point. 

Limitations:

These data are considered a reliable measure of airline passenger traffic between the U.S. and foreign nations.  The annual increase in air traffic, however, is affected by economic strength as well as market liberalization in bilateral aviation trade agreements.  Furthermore, only part of the growth rate in open skies markets can be attributed to new traffic – some of the increase may reflect diversion of traffic from less competitive routes with higher taxes and/or inferior service options.

Statistical Issues:

Like other counts of aviation-related activities, there are no major sources of systematic error in these data that have been quantified.  However, random variation in the number and distribution of airline passengers, as well as the changes in the number of "open-skies" agreements, results in variation in the measure over time.

Verification & Validation:

Airlines are required to certify that these data are accurate.  Also, these data are a 100% enumeration of traffic and capacity and can be verified for reasonableness against other databases, such as flight schedules.

Comment:

U.S. policy has favored the linking of networks.  Networks allow improved service and marketing in many thousands of small city-pair markets.  All of this traffic flows over flights captured by the T-100 and T-100F reports for international flights.

Measure:

On a program-wide basis, acres of wetlands replaced for every acre affected by Federal-aid Highway projects (where impacts are unavoidable). (FY)

Scope:

Measure includes wetlands associated with all Federal-aid highway projects each fiscal year.  To be included, wetland replacement (or investment in a wetland bank) must have begun.

Source:

State DOTs input Federal-aid related wetland degradation and replacement data into either locally developed wetland mitigation databases or the FHWA Wetlands Management Database.  FHWA compiles the final data. 

Limitations:

Data only exists on Federal-aid related wetland replacement.  Also, uniformity of the data is not guaranteed, as it is subject to interpretation by the reporting State DOTs.  In particular, there is no uniform understanding of what should be reported as mitigation acreage.  The FHWA has provided guidance on mitigation activities to report and will soon issue the Wetlands Management Database that should reduce the current variations in data received from the States.  Data on wetland replacement is available for the past five fiscal years (FY 1996 - FY 2000).

Statistical Issues:

The non-uniformity of the data is problematic.  Definitional ambiguity also makes formal statements of statistical uncertainty problematic.

Verification & Validation:

Data are gathered from established mitigation amounts required by section 404 (Clean Water Act) permits that states must acquire for their projects.  In addition, FHWA provides guidance to help states consistently report mitigation data.  This process will be further improved through a standard mitigation database under development for the states.  At present, there is no external audit of state data.

Comment:

All Federal agencies (including FHWA and other modes) must comply with National Environmental Policy Act (NEPA) and the Clean Water Act (specifically section 404(b)(1) of the CWA) regarding disruption of wetlands. These laws require agencies to identify project alternatives that would avoid or minimize impacts to wetlands as a first consideration.  These alternatives are subjected to analysis under both NEPA and the Clean Water Act.  Under the law, these alternatives must be chosen unless the project sponsors clearly demonstrate that they are not viable because they do not meet the project purpose and need, or will lead to other more significant environmental impacts.  If, in compliance with the law, wetland disruption is unavoidable, FHWA then works to achieve this goal of wetland replacement.

Measure:

Percentage of DOT facilities categorized as No Further Remedial Action Planned (NFRAP) under the Superfund Amendments and Reauthorization Act (SARA). (FY)

Scope:

EPA maintains a Federal Facility Hazardous Waste docket (docket), which contains information regarding Federal facilities that manage hazardous wastes or from which hazardous substances have been or may be released.  DOT facilities listed on the docket are discussed in the Annual SARA report sent to Congress each year.  EPA regional offices make the determination to change facility status to NFRAPs on the docket.

Source:

Annual SARA Report to Congress.

Limitations:

The number of DOT facilities listed on the docket can and has fluctuated over the years.  Several of the DOT facilities listed have more than one site requiring cleanup and a facility is not removed from the list until all of the sites have no further remedial action planned.  Some facilities are listed erroneously and it may take several years to remove them from the docket.  NFRAP decisions may be reversed by EPA if future information reveals that additional remedial actions are warranted.

Statistical Issues:

None

Verification & Validation:

The data used in measuring this performance is based on restoration activities at field locations for FAA, FHWA, and FRA.  These field sites report their activities to their respective headquarters management who verifies the data by periodic follow-up reviews.  The data is then reported yearly to the Office of the Secretary, who crosschecks it against data received from EPA and the states. 

Comment:

The primary criterion for NFRAP is a determination that the facility does not pose a significant threat to the public health or environment.  NFRAP decisions may be reversed if future information reveals that additional remedial actions are warranted. The Operating Administrations’ activities are controlled, to a degree, by interaction and decisions made by EPA Regional personnel.

Verification & Validation:

Vessels removed from the NDRF sites are tracked by MARAD.  MARAD has oversight authority for the vessels that it has contracted to be scrapped and continually monitors the operation of the contract holders to make sure that the ships are scrapped in a safe and environmentally sound manner.  Additionally, the Environmental Protection Agency and State and local environmental agencies are made aware of ships being scrapped or recycled, and they also monitor progress.  MARAD requires written certification from respective entities that all recycled activities are completed in accordance with Federal, State and local laws.

Comment:

None

Measure:

12 month moving average number of area transportation emissions conformity lapses. (FY)

Scope:

The transportation conformity process is intended to ensure that transportation plans, programs, and projects will not create new violations of the National Ambient Air Quality Standards (NAAQS), increase the frequency or severity of existing NAAQS violations, or delay the attainment of the NAAQS in designated non-attainment (or maintenance) areas.  The publication, Transportation Conformity: A Basic Guide for State and Local Officials contains the basic provisions of the conformity process.

Source:

FHWA and FTA jointly make conformity determinations within air quality non-attainment and maintenance areas to ensure that Federal actions conform to the purpose of State Implementation Plans (SIPs).  With DOT concurrence, the EPA has issued regulations pertaining to the criteria and procedures for transportation conformity, which were revised based on stakeholder comment.

Limitations:

Conformity determinations are required by law to be updated once every three years.  One reason for an area to be in a conformity lapse is due to the fact that it missed the deadlines for making a conformity determination on the transportation plan and program.  Under this scenario, the conformity lapse is not a result of the emissions problem in that area. 

In addition, certain State Implementation Plan (SIP)-related deficiency findings by EPA (such as a disapproval of a submitted SIP without a protective finding) may also put an area in a conformity lapse.  This may take a long time before the SIP-related issue(s) are addressed through the complex and time-consuming SIP revision process.  In this situation, FHWA/FTA will have little control over the duration of the conformity lapse.

Statistical Issues:

None.

Verification & Validation:

The MPO and U.S. DOT (FHWA/FTA) have a responsibility to ensure that transportation plans and programs within metropolitan boundaries conform to the SIP. In metropolitan areas, the governing board of each MPO must formally make a conformity determination on its transportation plan/TIP prior to submitting them to the U.S. DOT (FHWA/FTA) for review and approval. Conformity determinations for projects outside of these boundaries are the responsibility of the U.S. DOT (FHWA/FTA) and the project sponsor, which usually is the State DOT.  In addition, the National Memorandum of Understanding issued on April 19, 2001, provides the EPA and DOT with a framework for coordinating and working through issues in the conformity and SIP processes. Specifically, the MOU's provisions ensure that:

1. EPA and DOT consult on conformity determinations before DOT's approval process;

2. the conformity rule's provisions are appropriately applied with regard to conformity determinations; and

3. adequate interagency consultation persists through the planning and conformity processes to identify and resolve issues prior to a conformity lapse or freeze.

Comment:

If conformity cannot be determined within certain time frames after amending the SIP, or if three years has passed since the last conformity determination, a conformity lapse is deemed to exist and no new non-exempt projects may advance until a new determination for the plan and TIP can be made. This affects transit as well as highway projects.  During a conformity lapse, FHWA and FTA can only make approvals or grants for: projects that are exempt from the conformity process (pursuant to '93.126 and '93.127 of the conformity rule) such as safety projects, and transportation control measures (TCMs) that are included in approved SIP. Only those project phases that have received approval of the project agreement, and transit projects that have received a full funding grant agreement (FFGA), or equivalent approvals, prior to the conformity lapse may proceed during a conformity lapse.

Measure:

Tons of hazardous liquid materials spilled per million ton-miles shipped by pipelines. (CY)

Scope:

Hazardous liquid pipeline incidents are those that result in a fatality or injury resulting in hospital treatment or hospitalization, property damage equal to or greater than $50,000, or more than 50 barrels spilled.  (A rulemaking proposes to lower the reporting threshold for spill amount from 50 barrels to five gallons.)  This measure tracks only releases from hazardous liquid pipelines to the environment.  Natural gas pipeline releases vaporize into the atmosphere and do not have long-term significant impact on the environment, and thus are not included in this measure.

Source:

Pipeline operators report to RSPA on form 7000-1, Hazardous Liquid Accident Report.  RSPA records the data in RSPA’s Hazardous Materials Information System.

Limitations:

Because of the magnitude and frequency of fluctuations in the historical data for this measure, a short-term goal will be of limited use in tracking program performance.  RSPA does not collect volume shipped data but uses the Association of Oil Pipelines annual Fact Sheet as source for this part of the measure.

Statistical Issues:

These spill incidents are rare and probably not independent events.  The performance measure is a ratio, so uncertainty in the denominator can have a large effect on the overall uncertainty. 

Verification & Validation:

RSPA reviews the data for accuracy.  Supplemental reports are requested where obvious reporting shortcomings are indicated.  Additionally, the ASME B31.4 liquid pipeline data review subcommittee performs an annual examination of the hazardous liquid incident reports.  Known problems with under-reporting property damages and spill quantities are being addressed by a rulemaking to revise accident reporting requirements to implement a new “open and closed” status to insure that operators continue to file supplemental reports until the spill consequence is fully reported.  A new industry data improvement effort piloted in 1999 will provide better precursor data and more extensive data about impacts to the environment of hazardous liquid pipeline spills.  The American Petroleum Institute is housing the voluntary data repository, which will collect information on spills down to five gallons (down to one gallon in water) for all pipeline spills, including those currently not jurisdictional to RSPA.

Comment:

The data for this measure fluctuate year to year.  RSPA is studying the spill data to determine the nature of this fluctuation and improve this measure.

Measure:

Number of people in the U.S. (in thousands) who are exposed to significant noise levels (65 decibels or more). (FY)

Scope:

Residential population exposed to aircraft noise above Day-Night Sound Level of 65 decibels around U.S. airports with the greatest number of commercial jet take-offs and landings.

Source:

A statistical modeling technique (the MAGENTA model) is applied using U.S. population data from the Department of Commerce, locally developed traffic distribution (route and runway utilization), and aircraft distributions developed using the Official Airline Guide and current aircraft registration databases. The local traffic utilization data is available for the busiest U.S. airports in the form of studies developed for the FAA’s Integrated Noise Model (INM). For smaller airports, a generic statistical procedure was employed.

Limitations:

No actual count is made of the number of people exposed to aircraft noise.  No military or general aviation aircraft are included in the FAA’s model.  Aircraft type and event level are current.  However, the majority of the databases used to establish route and runway utilization were developed from 1990 to 1997, with many of them now over seven years old. Changes in airport layout including expansions may not be reflected. The benefits of federally funded mitigation, such as sound insulation or buyout, are not accounted at present. Future development of the methodology will attempt to quantify the gains (reduction in people exposed) due to these actions.

Statistical Issues:

This measure is derived from model estimates that are subject to errors in model specification.  The estimates of population data will be revised once the new U.S. Census data for 2000 is released and the model software is updated accordingly.

Verification & Validation:

The Integrated Noise Model has been validated with actual acoustic measurements at both airports and other environments such as areas under aircraft at altitude.  External forecasts data are from primary sources. The MAGENTA population exposure methodology has been thoroughly reviewed by an ICAO task group and was validated for several airport specific cases.

Comment:

FY 2000 was the first year measuring using the MAGENTA model.

Measure:

Percentage of DOD-required shipping capacity complete with crews available within mobilization timelines (FY)

Scope:

As of March 2002, this measure is based on the material availability of 76 ships in the Maritime Administration’s Ready Reserve Force (RRF) and 115 ships enrolled in the Voluntary Intermodal Sealift Agreement (VISA) program, which includes 47 ships enrolled in the Maritime Security Program (MSP).  A second factor pertinent to this measure is the availability of sufficient licensed and unlicensed mariners to operate the available ships.  The performance measure represents the number of available ships (compared to the total number of ships in the RRF and VISA) that can be fully crewed within the established readiness timelines.  While other Government (primarily Military Sealift Command) owned or controlled sealift type vessels are not included in this measure, they draw their crews from the same pool of mariners.  Accordingly, the availability measure is adjusted to reflect expected requirements during the early stages of a military crisis.

Source:

Material availability of ships: MARAD records (and reports to DOD) on the readiness/availability status of each RRF ship each month.  Typical reasons why a ship is not materially available include: the ship is in drydock, the ship is undergoing a scheduled major overhaul, or the ship is undergoing an unscheduled repair.  MARAD and DOD also maintain records of the sealift ships enrolled in the MSP and VISA and their crew requirements. Availability of mariners: Information on the available supply of licensed and unlicensed mariners is extrapolated from data received from the U.S. Coast Guard’s Merchant Mariner Licensing and Documentation (MMLD) system.

Limitations:

The information on the available supply of licensed and unlicensed mariners is an estimate. Because the MMLD also does not contain all of the information on individual mariners contained in their paper records, and provides no information on the availability and willingness of individuals to accept a sealift position in an emergency, it does not provide sufficient assurance of mariner availability.

Statistical Issues:

None

Verification & Validation:

The MARAD Regional Offices (and contracted ship managers) monitor the condition and overall readiness of each assigned RRF ship to meet its DOD mission.  When a ship is determined not capable of meeting its activation timeframe (mission), it is given one of several vessel condition ratings that are reported to DOD.  The monthly report contains an explanation of the deficiency and an estimated date when the ship will become fully capable of meeting its mission.  MSP contract performance is monitored throughout the year in order to assure proper payment of the MSP payment to the ship operators.  Recently, MARAD attempted to validate mariner availability estimates by conducting a survey of the mariner population.  A second survey is expected to commence in April 2002 to refine and improve the information needed to determine availability.  Because the decision to serve is a matter of individual choice and is subject to change, MARAD intends to develop a plan for maintaining current information on mariner availability based on the results of the 2002 mariner survey.

Comment:

None.

Measure:

Percentage of DOD-designated commercial strategic ports for military use that are available for military use within DOD established readiness timelines.

Scope:

The measure consists of the total number of DOD-designated commercial strategic ports for military use that are assessed as able to meet DOD-readiness requirements on 48-hour notice, expressed as a percentage of the total number of DOD-designated commercial strategic ports.  Presently there are 14 DOD-designated commercial strategic ports.  Port readiness is based on monthly reports submitted by the ports and semi-annual port readiness assessments by MARAD in cooperation with other NPRN partners.  The MARAD/DOD semi-annual port assessments provide data or other information on a variety of factors, including the following: the capabilities of channels, anchorages, berths, and pilots/tugboats to handle larger ships; rail access, rail restrictions, rail ramp offloading areas, and rail storage capacities; the availability of trained labor gangs and bosses; number and capabilities of available cranes; long-term leases and contracts for the port facility; distances from ports to key military installations; intermodal capabilities for handling containers; highway and rail access; number of port entry gates; available lighting for night operations; and number and capacity of covered storage areas and marshalling areas off the port.

Source:

MARAD data are derived from monthly reports submitted by the commercial strategic ports and from MARAD/DOD semi-annual port assessments.

Limitations:

Port readiness assessments were not made prior to 1995; therefore, data are available only for 1995 and later years.  MARAD conducts a monthly survey of all strategic facilities to determine whether they meet the DOD availability requirement.  This information is provided to MARAD as a self-assessment by the port agency that owns the facility.  There is some degree of subjectivity in determining the availability of the port facilities.  As part of the overall planning process, MARAD and DOD conduct semiannual visits to independently verify and reassess port capability and availability.  The indicator is by definition a point-in-time judgment.  The results of the monthly and semi-annual reports used to measure port readiness can vary in accordance with the intensity of commercial activity at a given port at the time of the assessment.  Also, the monthly reports do not include the same level of detail as the semi-annual assessments, although MARAD is in continuous contact with port officials to minimize response error.

Statistical Issues:

The measurement of port readiness is an overall measure derived from MTMC comments, monthly readiness reports, and semi-annual assessments.  As such, it is a subjective measure.

Verification & Validation:

The MARAD/DOD semi-annual port visits independently verify and reassess not only the DOD-designated facilities, but also the total capability of the commercial strategic port.

Comment:

None.

Measure:

Percentage of DOT major system acquisition cost and schedule baselines that are met. (FY)

Scope:

This performance measure encompasses acquisition management data for all of DOT’s major systems acquisition contracts, primarily in the FAA, but from any office procuring a major system as defined in OMB Circular A-11, and DOT’s Capital Programming and Investment Control order.

Source:

Acquisition program management data from each DOT organization procuring major systems.

Limitations:

None.

Statistical Issues:

None.

Verification & Validation:

Each DOT organization maintains its own quality control checks for cost, schedule, and performance data of each major systems acquisition in accordance with OMB Circulars A-11, A-109, and A-130, Federal Acquisition Regulations, and Departmental orders implementing those directives and regulations.

Comment:

None.

Measure:

1.  Percent share of the total dollar value of DOT direct contracts that are awarded to women-owned businesses. (FY)

2.  Percent share of the total dollar value of DOT direct contracts that are awarded to small disadvantaged businesses. (FY)

Scope:

Includes contracts awarded by DOT contracting activities (except FAA) through direct procurement (i.e., not including contracts issued by grantees).

Source:

All DOT contracting activities except the FAA report data to the Contract Information System (CIS).  This data is reported to the Federal Procurement Data Center (FPDC) by the CIS.

Limitations:

Contracting data is reported by procurement offices directly into the CIS. Data can still be entered into CIS and reported to FPDC after performance measurement results are submitted so small variations in prior year performance data may result.

Statistical Issues:

There is no major error present in the subject data.  However, random variation in the number of DOT contracts as well as the number of women-owned and small-disadvantaged businesses each year results in some random variation in these measures from year to year.

Verification & Validation:

DOT conducts comparison checks of CIS data with FPDC data to reconcile discrepancies.  On occasion, GSA audits the accuracy of DOT contracting data.

Comment:

None.

Measure:

Percentage of major Federally funded infrastructure projects that meet cost estimates in project agreements or contracts, or miss them by lest than 10%. (FY)

Percentage of major Federally funded infrastructure projects that meet schedule milestones in project agreements or contracts, or miss them by lest than 10%. (FY)

Scope:

Active FTA New Starts projects with Full Funding Grant Agreements larger than $1 billion; FHWA projects with a total cost of $1 billion or more, and FAA runway projects with a total cost of $1 billion or more.

Source:

FTA:  measures are calculated monthly by an FTA Headquarters Engineer, checked by the Team Leader and re-checked by the Office Director.  FTA uses independent reviews and third party assessments such as the Corps of Engineers and other oversight contractors to validate the accuracy of project budgets and schedules before grantees’ are awarded Full Funding Grant Agreements.  FHWA:  uses essentially the same process as FTA.  FAA enters into a project agreement with airport sponsors, and closely manages the project in a fashion similar to managing a direct FAA contract

Limitations:

None.

Statistical Issues:

None.

Verification & Validation:

DOT operating administrations work closely with their State and local government counterparts in designing and adhering to project cost and schedule baselines. 

Comment:

None.

Measure:

Percentage of transit grants obligated within 60 days after submission of a completed application.

Scope:

FTA grants obligated during a fiscal year period for major programs: Urbanized area, non-Urbanized area, and Elderly and Persons with Disabilities formula grants; Capital grants; Job Access and Reverse Commute grants; Over-The-Road Bus grants; and Planning grants.

Source:

FTA TEAM database.

Limitations:

Several factors that contribute to grant delays are beyond FTA’s ability to control. These factors include the processing of flexible funds from FHWA through the Treasury, and the Congressional grant release process.

Statistical Issues:

Processing time is calculated from submission date to obligation date. $0 dollar non-funding grant amendments are excluded from analysis.

Verification & Validation:

TEAM output file is crosschecked against other system generated files for consistency; inconsistencies are investigated and corrected prior to reporting. Grants with missing or out-of-sequence dates are excluded for calculating averages.

Comment:

An FTA task force meeting was held in February 2002 to identify causes for grant processing delays. The resulting action plan is now being circulated for final review and approval. Implementation of the plan will follow.

Measure:

Percent of environmental justice cases that remain unresolved after one year. (FY)

Scope:

Data covers complaints filed with DOT under Title VI of the Civil Rights Act of 1964 and which have had environmental justice elements, such as allegations of substantially adverse environmental or health impact on a minority or low-income community by a transportation project.  Case resolutions are actions that end or administratively close out complaints.  These include such actions as determinations of no jurisdiction, withdrawals by complainants, resolutions achieved through alternative dispute resolution, findings of no violation, and negotiated settlements after discrimination findings under Title VI.

Source:

DOT will collect this data through the External Complaint Tracking System (XTRAK).

Limitations:

This measure is an initial indicator of how well DOT processes EJ complaints.  Variables that will not necessarily be assessed include such factors as magnitude of injury, number of beneficiaries adversely affected, pervasiveness, and time constraints before irreparable damage occurs. Other statutory requirements exist for NEPA concerns.

Statistical Issues:

None.

Verification & Validation:

Data will cover the entire universe of external complaints received by DOT, and will be entered into the system by operating administrations and DOT Office of Civil Rights staff.

Comment:

This indicator does not measure the impact of DOT’s efforts to prevent the conditions that give rise to complaints.  It does provide an initial measure of response timeliness, which is important to the public.  The measure was expanded in 2000 to include the percent of cases that remain unresolved after one year as a further indicator of the timeliness of resolution.  All environmental justice cases by definition relate to the concerns of a community of low income and/or minority people.  In addition, the number of cases indicates the pervasiveness of community perception of significantly adverse environmental and health concerns.