United States Air and Radiation EPA420-P-98-016
Environmental Protection June 1998
Agency
Office of Mobile Sources
v°/EPA Update of Fleet
Characterization Data for
Use In MOBILE6 - Final
Report
> Printed on Recycled Paper
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UPDATE OF FLEET
CHARACTERIZATION
DATA FOR USE IN
MOBILE6
Final Report
11 May 1998
PREPARED FOR
U.S. Environmental Protection
Agency
Motor Vehicle Emissions Laboratory
2565 Plymouth Road
Ann Arbor, Michigan 48105
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Update of Fleet
Characterization Data for
Use in MOBILE6
Final Report
Prepared for:
U.S. Environmental Protection Agency
Motor Vehicle Emissions Laboratory
2565 Plymouth Road
Ann Arbor, Michigan 48105
Prepared by:
Louis Browning, Michael Chan,
Doug Coleman, and Charlotte Pera
ARCADIS Geraghty & Miller, Inc.
555 Clyde Avenue
P.O. Box 7044
Mountain View
California 94039
Tel 650 961 5700
Fax 650 254 2496
Our Ref.:
SJ007260
Date:
11 May 1998
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This report and the information and data described herein have been funded by the USEPA under
Contract 68-C6-0068, Work Assignments #0-01 and 1-04. It is being released for information purposes
only. It may not reflect the views and positions of the USEPA on the topics and issues discussed, and
no official endorsement by USEPA of the report or its conclusions should be inferred.
This report has not been peer or administratively reviewed.
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SECTION 1
INTRODUCTION
The U.S. Environmental Protection Agency's (USEPA) highway emissions factor model,
MOBILE, is the primary model used by state and local agencies to simulate mobile source emissions
generated in their areas. In order to model emissions from motor vehicles, MOBILE must incorporate
data characterizing the fleet of vehicles in use in the United States. The vehicle population is
characterized by the total number of vehicles in operation within certain vehicle weight categories, the
age distribution and fuel type (gasoline or diesel) within each weight category, and the mileage
accumulation rates specific to vehicle age, fuel type, and weight category. The characterization for a
given calendar year is based on a July 1 "snapshot".
Due to changes in economic and demographic conditions in recent years, there have been
significant changes in the age distribution, vehicle-type distribution, and mileage accumulation rates
for the current national motor vehicle fleet since the last version of the model (MOBILESa) was
released in March 1993. As such, the fleet characterization data currently used in MOBILE must be
updated to reflect these changes.
This study utilized the latest available data to update the characterization of the national fleet
of vehicles used in the MOBILESa model. The results of this study may be used in MOBILE6,
currently under development. ARC ADIS Geraghty & Miller reviewed potential sources of information
and analyzed the most relevant and useful data sources. The results of this study, as well as a
description of the data and methodologies used to obtain the results, are presented in this document.
Table 1-1 lists the individual vehicle type categories included in the study. Registrations and
average annual mileage as functions of vehicle age were developed for each of these categories.
Registrations were also summed for the entire set of vehicles and certain subsets.
With respect to registrations, ARC ADIS Geraghty & Miller attempted to use 1996 as the base
year for the characterization. Transit bus registrations are the exception, for which the base year is
1994. Similarly, it was not possible to use 1996 as the base year for annual mileage accumulation rates,
since sources of these data were developed prior to 1996. The base year for each of these data sources
will be identified in the relevant subsections of Section 3.
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Table 1-1. Vehicle Types
Designation
Description
Gross Vehicle
Weight (Ib)
LDGV
LDDV
LDGT1
LDGT2
LDDT1
LDDT2
HDGV (classes 2B-3)
HDGV (classes 4-8)
HDDV (class 2B)
HDDV (class 3)
HDDV (classes 4-5)
HDDV (classes 6-7)
HDDV (class 8A)
HDDV (class 8B)
HDGB (school)
HDGB (transit)
HDDB (school)
HDDB (transit)
Light-duty gasoline vehicles
Light-duty diesel vehicles
Light-duty gasoline trucks
Light-duty gasoline trucks
Light-duty diesel trucks
Light-duty diesel trucks
Heavy-duty gasoline vehicles
Heavy-duty gasoline vehicles
Light heavy-duty diesel trucks
Light heavy-duty diesel trucks
Light heavy-duty diesel trucks
Medium heavy-duty diesel trucks
Heavy heavy-duty diesel trucks
Heavy heavy-duty diesel trucks
Heavy-duty gasoline school buses
Heavy-duty gasoline transit buses
Heavy-duty diesel school buses
Heavy-duty diesel transit buses
0 - 6,000
0 - 6,000
<6,000
6,001-8,500
<6,000
6,001-8,500
8,501-14,000
>14,000
8,501-10,000
10,001-14,000
14,001-19,500
19,501-33,000
33,001-60,000
>60,000
all
all
all
all
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SECTION 2
REVIEW OF DATA SOURCES
To develop a fleet characterization, ARCADIS Geraghty & Miller reviewed numerous data
sources for relevant and accurate content. In this section, both the data sets analyzed, and those that
were reviewed but not used (or used minimally), are described. A description of the data sources
reviewed but not used is found in Section 2.1. A description of the data sources used for this study is
found in Section 2.2. Analysis methodologies are described in Section 3. Results of the analysis are
found in Section 4.
2.1 SECONDARY DATA SOURCES
Most of the sources used minimally by ARCADIS Geraghty & Miller were tables and charts
listed in popular industry publications. In most cases, ARCADIS Geraghty & Miller found that either
pertinent data from these sources were missing or provided in a format that could not be translated into
the weight class/age/fuel type breakdowns required for this study. For example, often vehicles were
tabulated according to location instead of weight or age. In these cases, the total vehicle data from
these sources were used only to verify the final results obtained from other data sources. These sources
have been called "secondary data sources".
The Gallup Organization Final Report for the Motor Vehicle Manufacturers Association. 1993
The Gallop Organization study was conducted to determine private light-duty vehicle driving
patterns to help make estimations of emissions and fuel economy. It consisted of two samples, one
taken by telephone and the other by mail. The total number of respondents to both surveys was
approximately 8,300. The data recorded includes a number of different items such as driver profile,
vehicle make and model, cargo carried, the number and purpose of trips, and the type of road utilized.
Vehicle age and mileage were recorded, but the results were not published in a cross-correlated
fashion. In other words, it was not possible to associate the vehicle's age with the miles it drove.
Further, to define a vehicle's classification, Gallup used their own definitions that generally were not
consistent with the vehicle categories required for this study. For example, Gallup divided vehicles
into either passenger cars or vans/trucks, with no reference to weight. Finally, the resultant data was
not expanded to national levels, but instead reported in percentages of the overall sample. Given these
limitations, ARCADIS Geraghty & Miller felt that such data were not applicable for use in the present
study.
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1995 Motor Vehicles Facts & Figures (American Automobile Manufacturers Association)
The 7995 Motor Vehicles Facts & Figures by the American Automobile Manufacturers
Association (AAMA) is a compendium of tables and graphs sorted into several categories, such as
production, retail sales, registrations, ownership, travel trends, and automobile related fatalities. It has
a wealth of information pertaining to the motor vehicle industry, and was used by ARC ADIS Geraghty
& Miller as a point of departure for exploring other potential sources. It was not used for raw data itself
because it breaks vehicles out into categories that are different from those used in this study. One table
does categorize passenger cars by model year, but it does so only for LDVs, and only back to model
year 1979. The data on vehicle registrations presented in this publication was derived from data
maintained by R.L Polk & Company (which was used extensively in this study). ARC ADIS Geraghty
& Miller used the AAMA publication to verify total numbers of vehicles on the road.
Automotive Fleet 1994 Fact Book (Bobit Publication)
In this annual publication, a number of quantitative tables characterizing the various vehicle
fleets in the United States are presented. Information about truck market share, yearly model
registrations, operating costs, and fleet size is provided, but few data referring to fleet age or mileage
are included. ARCADIS Geraghty & Miller did not use information from this source.
School Bus Fleet 1997 Fact Book Issue (Bobit Publication)
The Fact Book Issue of the magazine School Bus Fleet presents statistical data regarding the
United States school bus fleet, including total registrations, annual mileage, students transported, and
fatalities. This issue was used for one important statistic: average school bus annual mileage. Since
annual mileage data by model year were unavailable from other sources, this value (9,939 miles per
year) was used as the mileage for every model year.
1996 Highway Statistics (Federal Highway Administration)
The 1996 Highway Statistics book is a compilation of statistics in several categories, with most
data items in the areas of highway finance and road characteristics. The Federal Highway
Administration (FHWA) records this information from various state and local administrative agencies
and publishes the Highway Statistics annually. While the document does contain some substantial
registration information according to vehicle type, registration data was not specified by vehicle age.
Further, the statistics contain no information regarding fuel type. Thus, in most cases, ARCADIS
Geraghty & Miller was not able to use these data for this study. However, information on total vehicle
miles traveled in the United States was used to verify the numbers generated using more detailed.
Also, certain statistics indicated that the number of government owned vehicles are insignificant
compared to the total number of vehicles on the road. This supported the application of private vehicle
annual mileage rates (provided in the NPTS database - see Section 2.2) to both public and private
vehicles as sufficiently accurate for this study.
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1995 Transit Passenger Vehicle Fleet Inventory (American Public Transit Association)
This American Public Transit Association (APTA) inventory categorizes and lists passenger
vehicles according to the fleet in which they are operated. It provides counts of vehicles in a variety
of categories, namely manufacturer, city of construction, specification, cost, ownership, and seating
capacity. The book also includes a section listing transit buses by age but not by fuel type. Since data
from the Federal Transit Administration (see Section 2.2) did contain both model year and fuel type,
it was chosen to provide data for this study over that presented in the APTA document. ARCADIS
Geraghty & Miller used thi s publication mainly to verify the regi strati on data obtained from the Federal
Transit Administration.
The 100-Year Almanac and 1996 Market Data Book (The Automotive News)
The 100-Year Almanac provides a historical representation of the automotive industry since
the turn of the century by highlighting key events and following manufacturer sales on a yearly basis.
The 1996 Market Data section of the magazine compiles statistics related to production, sales, and new
registrations for the year. The data contained in this source is extensive with respect to vehicle make,
model, and fuel type, but has very limited data categorizing vehicles by weight or model year.
Therefore, ARCADIS Geraghty & Miller was unable to incorporate this source of data into the study
results.
2.2 PRIMARY DATA SOURCES
The following data sources were used extensively in this study and are referred to as "primary
data sources." The data sources found most useful were contained in electronic databases from the R.L.
Polk & Company (Polk), the 1992 Truck Inventory and Use Survey (TIUS), the 1995 Nationwide
Personal Transportation Survey (NPTS), and in databases from the Federal Transit Administration
(FTA).
Primary data sources used for each vehicle type registration and annual mileage accumulation
are listed below in Table 2-1 and described below.
Table 2-1. Data Sources and Base Years
Vehicle Type
Light Duty Vehicle
Light & Heavy Duty Truck
School Buses
Transit Buses
Vehicle Registrations
Source
Polk
Polk
Polk
FTA
Base Year
1996
1996
1996
1994
Annual Mileage
Accumulation
Source
NPTS
TIUS
Bobit
FTA
Base Year
1995
1992
1996
1994
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R.L. Polk & Company
The only centralized source of nationwide vehicle registration data of the type needed for this
study is assembled by R.L. Polk & Company. Polk compiles Department of Motor Vehicle registration
information from each state into their database on a quarterly basis. These data include, for each
vehicle, information describing make, model year, fuel type, and gross vehicle weight.
Data from two databases at Polk were required for this study. The first database records light-
duty vehicles and truck registrations according to make, model year, fuel type, and gross vehicle
weight. Information was available from this database as of July 1, 1996.
The second database contains heavy-duty trucks and school buses, again recording make, model
year, fuel type, and gross vehicle weight. ARC ADIS Geraghty & Miller received two sets of heavy-duty
vehicle data from Polk: Oct 1, 1996 and Jan 1, 1997. In Section 3, the methodology used to convert
data from these dates to a July 1, 1996 snapshot is described.
For consistency, ARC ADIS Geraghty & Miller defined Age 1 vehicles to be model year 1996
for all Polk registrations. Mileage accumulation rates were not acquired from this source.
Truck Inventory and Use Survey
The Truck Inventory and Use Survey was conducted during the 1992-1993 time frame by the
U.S. Bureau of the Census. The database, which was supplied to ARC ADIS Geraghty & Miller on
CD-ROM, compiles a statistically significant sample of on-road light-duty and heavy-duty trucks.
Each record is the equivalent of one vehicle. Data for each record is extensive, and includes the
required attributes of age, gross vehicle weight, and fuel type. Most importantly, the database records
miles driven in calendar year 1992 by these vehicles. This data was used to determine mileage
accumulation for light-duty and heavy-duty trucks.
Model year 1992 was designated as Age 1 vehicles for the TIUS data.
Nationwide Personal Transportation Survey
Data recorded in the Nationwide Personal Transportation Survey was developed by a
consortium of Department of Transportation agencies to characterize the nature of personal travel (as
opposed to commercial and institutional travel). The 1995 survey, the fifth in the NPTS series, consists
of 42,033 individual telephone interviews. The survey asked interviewees about their travel habits,
including trip length, number and purpose of trips, and time of day. Also, information related to the
subj ects' personal background and vehicle characteristics was recorded during the study. Of relevance
to the ARC ADIS Geraghty & Miller study, the NPTS contains data regarding light-duty vehicle type,
age and annual mileage. Annual mileage was supplied both as a self-estimated value and one
determined by annualizing two odometer readings taken during the year. The second odometer reading
was taken from 2 to 6 months after the first. The NPTS data, however, does not contain data recording
fuel type or vehicle weight. Like the TIUS data, ARC ADIS Geraghty & Miller received the NPTS data
on CD-ROM.
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Age 1 vehicles in the NPTS data are defined as model year 1995 vehicles.
Federal Transportation Administration
The Federal Transit Administration supplied transit bus inventory data to ARCADIS Geraghty
& Miller in electronic form. The FTA helps fund transit districts across the nation; as part of this
program, funded agencies are required to submit revenue and vehicle inventory forms to the FTA on
a yearly basis. Included among the data recorded on these forms (Form 408) is the vehicle mileage
traveled during the previous year and the model year of the bus. This allowed calculation of transit bus
mileage by age in addition to total vehicle counts.
The latest available version of this data was recorded in 1994. Thus Age 1 is defined as model
year 1994 for this data set.
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SECTION 3
DATA ANALYSIS METHODOLOGIES
ARCADIS Geraghty & Miller performed an analysis of both vehicle registrations and annual
mileage data sources. The following subsections describe the methodologies used to determine the
values for these tasks. The data sources and methodologies used for registration purposes are described
in Section 3.1, those used to characterize annual mileage data are described in Section 3.2. Results of
these an analysis can be found in Section 4.
3.1 VEHICLE REGISTRATIONS
As required under Work Assignment Tasks 1, 2, and 3, ARCADIS Geraghty & Miller
determined total vehicle registrations and vehicle registrations as a function of age for all vehicle types
listed in Table 1-1. The primary source of this data was the Polk database, while information on transit
bus registrations was taken from the FTA database.
3.1.1 R.L. Polk & Company Database
Several manipulations were required to the data provided by Polk in tabular, electronic form
as an EXCEL spreadsheet.
First, ARCADIS Geraghty & Miller divided Class 8 heavy-duty diesel vehicle registrations in
the Polk database into Class 8A and Class 8B subclasses, since these breakdowns were not available
from Polk. Using registration data from the TIUS database, the percent of Class 8 vehicles below
60,000 pounds gross vehicle weight rating (GVWR) for each model year was calculated. These
percentages were then applied to the Polk data for Class 8 trucks to estimate total registrations of Class
8A and Class 8B vehicles. For model years not included in the TIUS data (1993 - 1996), ARCADIS
Geraghty & Miller assumed 26.5% of Class 8 vehicles are Class 8 A. This value represents the average
percentage of all vehicles in model years 1983 to 1992.
After splitting the data in this fashion, ARCADIS Geraghty & Miller translated the heavy-duty
vehicle October 1, 1996, and January 1, 1997 data to July 1, 1996. The two data sets allowed
calculation of attrition rates of registered vehicles between October 1, 1996 and January 1, 1997
specific to each model year, for all heavy trucks combined, but not for individual weight classes.
ARCADIS Geraghty & Miller used these attrition rates to "backcast" estimated registrations as of July
1, 1996, using linear extrapolation (Linear extrapolation of attrition rates is a reasonable
approximation considering the difficulty of obtaining and analyzing attrition data on monthly or shorter
periods, and is consistent with EPA's treatment and use of attrition information in MOBILESa and
earlier versions of the model). The same attrition rate calculated for all heavy trucks of each model year
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was applied to each weight class for that model year. Note that the number of model year 1995 and
1994 trucks registered increased in the fourth quarter of 1996. This, according to Polk personnel, is
not unusual and reflects stored inventory of one- and two-year old vehicles continuing to be sold
through 1996.
For model year 1996 heavy-duty vehicles, ARCADIS Geraghty & Miller performed a different
procedure to include new registrations. The values used for the July 1, 1996 snapshot for the 1996
model year are one-half of the values provided originally from Polk as of January 1, 1997. These are
the number of vehicles sold halfway through the year, assuming an even introduction throughout the
year (For the same reason as described in the previous paragraph regarding attrition rates, use of linear
extrapolation for sales data is appropriate in the MOBILE model series).
Internal USEPA review of the vehicle registration data reported by the R.L. Polk Company
identified apparent errors in some of the vehicle weight categories. Several USEPA reviewers noted
that the Folk-reported registration counts for light-duty diesel class 2 trucks (LDDT2) were far too
large. Discussions with several staff members at the R. L. Polk company revealed that Polk defines
light-duty class 2 trucks as having GVWRs of 6,001-10,000 Ibs. USEPA defines light-duty class 2
trucks as having GVWRs of 6,001 to 8,500 Ibs and heavy-duty class 2B trucks as having GVWRs of
8,501 to 10,000 Ibs. As a result, data reported by Polk for LDDT2 include data for both USEPA
LDDT2 and HDDV(2B). Thus a methodology to split the Folk-reported class 2 truck registrations into
USEPA LDDT2 and HDDV(2B) needed to be developed. To do this, USEPA staff consulted Polk
staff, several USEPA experts on truck populations, industry-published market data books, and the
Internet to determine the ratio of diesel-fueled light-duty class 2 trucks to diesel-fueled heavy-duty class
2B trucks. These investigations resulted in an estimate of 10% of the diesel-fueled vehicles with
GVWRs of 6,001-10,000 Ibs actually have GVWRs of 6,001-8,500 Ibs. This estimate was further
supported by discussions with staff at General Motors (which is the only manufacture currently selling
such trucks). Therefore, it was assumed that 10% of the Folk-reported registered trucks weighing
6,001-10,000 Ibs actually weighed 6,001-8,500 Ibs.
Further discussion with Polk staff indicated that these excess vehicles should not be added to
reported heavy-duty diesel class 2B category because this data was derived from a separate data source
which does separately define trucks 8,501-10,000 Ibs GVWR. Therefore, the excess 90% of the Folk-
reported class 2 trucks were discarded, and the reported heavy-duty class 2B registrations were
maintained.
Another reviewer of the preliminary data noted that registrations of heavy-duty gasoline trucks
class 2B-3 were under reported. This was verified by comparing the reported 1995 registration total
(which is assumed to be a close representation of the number of vehicle sold in that year, due to
expected low scrappage rates for trucks 6 months to 1.5 years old) to the actual sales of these trucks
(as reported in the 1997 American Automobile Manufacturers Association 'Motor Vehicle Facts and
Figures' report). Given reports from Polk that their reported light-duty gasoline class 2 includes trucks
that USEPA would define as heavy-duty gasoline class 2B trucks, is was noted that the light-duty
gasoline truck 2 category was being over estimated. Because sales of heavy-duty gasoline class 3
trucks are negligible, it was assumed that splitting the registrations that were being reported as LDGT2
by some ratio would more accurately represent LDGT2 and HDGV (class 2B-3) vehicles. USEPA
analysis of manufacturer-supplied sales data derived a ratio of 75:25 for these two categories.
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Once the manipulations of the data described above were completed, the resulting tabular data
was transferred to new spreadsheets and graphs were created. Where data was available from other
sources like MOBILESa, these data were plotted along side the Polk data for comparison purposes.
The results of these comparisons are described in Section 4.
3.1.2 Federal Transit Administration Database
Transit bus registration data for urban buses was obtained from the Federal Transit
Administration as an EXCEL spreadsheet. It was saved as a dB ASE file for processing. The structure
of the dBASE data file is shown in Table 3-1 below:
Table 3-1. BUSDATA.DBF Data Structure
Field Name
NUMVEH
TYPE
MY
NUMACTVEH
FUELTYPE
SEATING
ANNMILES
Description
Number of buses in fleet
Bus type code
Bus Model Year
Number of active buses in fleet
Bus fuel type
Seating capacity of the bus
Total Fleet annual mileage
Registration information for urban transit buses was determined from this data. Only vehicle
type codes listed in Table 3-2 were used in the analysis.
Table 3-2. Vehicle Type Codes Used in the Analysis
Code
AB
BA
BB
BC
DB
Bus Type
Articulated motor bus
Motor bus with > 35 seats
Motor bus with 25-35 seats
Motor bus with < 25 seats
Double-decker bus
Vehicle types codes other than those listed in Table 3-2 refer to non-bus transit vehicles, and
these records were eliminated from the database. As an urban bus is defined in the Code of Federal
Regulations (§86.093-2) as "a passenger carrying vehicle powered by a heavy heavy-duty diesel engine,
or of a type normally powered by a heavy heavy-duty diesel engine, with a load capacity of fifteen or
more passengers ...", records which indicated that a bus had less than a 15 seat capacity were
eliminated from the database. Buses designated as inactive in the FTA database were not included in
this calculation, even though they still exist within the inventory. (Inactive buses accounted for
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approximately 4% of the inventory.) Even though gasoline-powered buses are not technically
designated urban buses, the data set also contained a set of gasoline-powered buses that carried 15 or
more passengers. For consistency, gasoline-powered urban bus registrations were also documented in
this report. No attempt was made to translate the 1994 FTA data to the 1996 baseline.
The program BUSES.PRG, used to calculate bus registrations and mileage accumulation, is
listed in Appendix A. Bus registrations and comparisons to other data sets are discussed in Section 4.
Discussion of the calculation of mileage accumulation rates for transit buses can be found in Section
3.2.3.
3.2 ANNUAL MILEAGE ACCUMULATION
ARCADIS Geraghty & Miller acquired and analyzed information regarding the annual mileage
accumulation of all vehicle types by age as stated in Work Assignment Task 5. The methodologies
applied to each of these source are described in the subsections below.
3.2.1 Truck Inventory and Use Survey
To provide the best analysis of the TIUS data for the purposes needed by this work assignment,
ARCADIS Geraghty & Miller manipulated the TIUS data on a record-by-record basis. To do this,
pertinent data from the TIUS data file TI92MDF.DAT was converted into a comma-delimited file
using the C program TIUSCONV.C listed in the appendices. The comma-delimited file was then read
into a dBASE file following the structure presented in Table 3-3.
Two additional fields were added to TIUSDAT.DBF to further help in the manipulation of the
data for this work assignment. They are listed in Table 3-4.
Of the 247,282 records that comprised the original data set and were appended from
TI92MDF.DAT to TIUSDAT.DBF, 1,612 were deleted because they had no model year designation
and 3,694 records were deleted because they designated fuels other than gasoline or diesel (liquefied
gas or other). This left 241,976 records.
Each TIUS data record (representing one truck from the survey) had several different weight
and weight class fields. MAXWT represented the maximum gross weight at which the vehicle or
vehicle/trailer combination was operated. TIUGVW represented the gross vehicle weight (GVW) of
the vehicle based on the average weight and is receded to TIUS specifications. While this is based on
average weight, it is probably a good indication of the GVW of large trucks. PKGVW represents the
GVW class based upon the vehicle identification number (VIN) and is obtained from the manufacturer.
PKRWGT represents the gross vehicle registered weight which comes from state registration data. The
PKGVW and PKRWGT are the same values used by Polk to determine weight classes.
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Table 3-3. TIUSDAT.DBF Data Structure
Field Name
Description
EXPANF
MDLYR
ACQMON
ACQYR
OBTAIN
DISPOZ
DISMON
DISYR
HOWRID
BODTYP
MAXWT
ENGTYP
ANNMIL
TIUGVW
PKGVW
PKRWGT
VEHSZE
Expansion factor
Model year
Acquired month
Acquired year
How was vehicle obtained?
Was the vehicle disposed of?
Month the vehicle was disposed
Year the vehicle was disposed
How was the vehicle disposed?
Vehicle body type
Maximum gross weight
Fuel type
Annual mileage during 1992
TIUS gross vehicle weight class
Polk gross vehicle weight class
Polk registered weight
Vehicle size
Table 3-4. Additional Fields in TIUSDAT.DBF
Field Name
VEHTYPE
FUELTYPE
Description
Vehicle class description
Fuel type
In reviewing the data, inconsistencies between the various weight class designations and
weights were found. For example, a single record (1 truck) could list a registered weight (PKRWGT)
of 4,000 pounds GVWR but also list a gross vehicle weight class (PKGVW) of 8, indicating a
registered weight of 33,000 pounds or greater. Discussions with Census Bureau staff provided an
explanation for these inconsistencies. The two types of weights, PKGVW and PKRWGT, are based
on truck registrations, and are often entered into databases based on the VEST. Prior to 1983, VEST
coding was not uniform, and, as a result, incorrect interpretations of gross vehicle weight may have
occurred during data entry. Therefore, discrepancies between the PKRWGT and PKGVW data fields
should be more prevalent for trucks older than model year 1983. The recommendation of Census
Bureau staff was to use the PKRWGT and PKGVW for comparison to TIUGVW as a check for this
parameter's accuracy. TIUGVW gives an average gross weight value rather than the manufacturers
gross vehicle weight, but Census Bureau staff felt that the TIUGVW data was of high quality and, for
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large trucks especially, would be a good indication of the gross vehicle weight rating. While
ARCADIS Geraghty & Miller did not find that post-1983 data was necessarily more consistent than
pre-1983 data, the methodology recommended by the Census Bureau staff was applied to determine
which records were valid for use in this study. Only data records which met one of the following
criteria were retained:
Records where the Polk class (PKGVW) and weight (PKRWGT) were consistent
Records where the TIUS class (TIUGVW) and the Polk Weight (PKRWGT) were
consistent
Records where the TIUS class (TIUGVW) and Polk Class (PKGVW) were consistent
This resulted in 220,544 records for the analysis, approximately 90% of the original data set.
These records were used to characterize average annual mileage accumulation as a function of
vehicle age and weight class. The TIUS data was not used to characterize vehicle registrations; instead,
Polk data was used as was described in Section 3.1. TIUS data could not be used to characterize
registrations because records were for survey responses only. The database does incorporate an
"expansion factor" (EXPANF) which is used as a multiplier on the survey response records to expand
the data to be representative of the entire national truck fleet. However, the expansion factors are
specific only to each of five vehicle strata within each state: pickups, vans, single-unit light (26,000
pounds GVWR or less), single unit heavy, and truck tractor. Because the expansion factors are not
intended to, and the trucks surveyed were not selected to, correctly represent a model year- and weight
class-specific breakdown of the national truck fleet, the TIUS data could not be used to characterize
national truck registrations by model year and weight class. Census Bureau staff agreed that it would
be inappropriate to use the expansion factors in this way.
ARCADIS Geraghty & Miller calculated average annual mileage accumulations by averaging
the ANNMIL data for each weight class and model year. (The expansion factors were not applied to
the data records in the calculation of average annual mileage accumulation, since this calculation is also
specific by model year and weight class.)
To compensate for trucks used less than 12 months in the year due to acquisition or disposal
during 1992, months of operation for each record were determined. It was assumed that the acquisition
or disposal happened mid month. Thus a truck purchased in June of 1992 (ACQYR = 92 and
ACQMON = 6) was assumed to operate for 6.5 months in 1992, while a truck disposed of in June of
1992 (DISYR= 92 and DISMON = 6) was assumed to have operated for 5.5 months prior to disposal.
Months of operation were then averaged for each model year and class and the annual mileage
accumulation for that case was then extrapolated linearly to 12 months of operation.
The TIUS data model year designations are only given for vehicles with model years of 1983
or newer. Vehicles 11 years of age and older are categorized together as model year 11. To
characterize mileage accumulation for vehicles 11 years of age and older, records with model year 11
and OBTAIN = 1 (purchased new) were placed in a separate database (TIUS 11.DBF) with the same
structure as TIUSDAT.DBF. In those cases, model year was assumed to be the same as acquired year
3-6
-------
(ACQYR) and average mileage was determined for each of the classes for all acquired years 1982 and
earlier. Data records for trucks of model year 11 purchased as used vehicles could not be incorporated
into the analysis because there was no data to indicate the specific model year of the truck.
Curve fits were made through the first set of data (model years 1983 through 1992). Only
points in the second set (model years earlier than 1983) that did not change the shape of the curve
generated by the first set of data more than 5% were used to produce the final curve fits. Two different
curve fits were applied, exponential and 2nd order polynomial. The one that produced the highest
coefficient of determination (R2) was chosen.
No adjustments were made to translate the 1992 TIUS data to the 1996 baseline year for this
study. This is because total VMT calculated from the 1992 TIUS mileage estimates and the Polk 1996
registrations closely approximated other data sources (see Section 3.1).
The program TIUS.PRG, used to calculate mileage accumulation, is listed in the appendices.
Results of this analysis are given in Section 4.
In addition to the above analysis, the TIUS data was further analyzed to determine if mileage
accumulation of specific types of light-duty trucks were statistically significant from the aggregated
light-duty truck classes. Specifically, data for the LDGT1 class (0-6,000 Ibs GVWR) was divided into
sports utility vehicles (SUVs), minivans (MVs), pickup trucks (PUs) and other light-duty trucks (OTH).
A statistical t-test (difference between two means) was run for each of the four categories of light-duty
trucks compared against the aggregated LDGT1 class data. The test showed within a 95% confidence
interval that none of the four categories were statistically significant from the aggregated class. This
test was also run for the LDGT2, LDDT1 and LDDT2 vehicle classes and similar results were found.
Thus the light-duty truck class mileage accumulations were not disaggregated further beyond weight
class and fuel type. A chart showing curve-fit mileage accumulation for the four categories of LDGT 1
(SUVs, MVs, PUs, and OTH), plotted together with the aggregate LDGT1 curve fit mileage
accumulation, can be found in Appendix A. While the shape of some of the curves look different from
others, no one curve is statistically significant from the others.
3.2.2 Nationwide Personal Transportation Survey
The data on CD-ROM from the Nationwide Personal Transportation Survey was supplied in
dBASE format along with other formats that were not used in this study. The dBASE file structure for
the data file used in this study is shown in Table 3-5.
Two mileage estimates are listed in the 1995 version of the NPTS data base. The first is a self-
reported estimate of annual mileage accumulation reported by the interviewee. The second is an
annualized mileage calculated from two separate odometer readings taken by the interviewee on two
distinct days within the year. The two odometer readings are generally spaced from 2 to 6 months. Of
the 75,217 vehicles sampled, 47,874 relate to passenger cars and 22,864 relate to light trucks. The
remaining records relate to other vehicle types such as motorcycles, recreational vehicles and unknown.
Of the 70,738 passenger car and light truck samples, 70,486 had self-reported annual mileage, 47,677
for passenger cars and 22,809 for light-trucks. Only 31,252 of the vehicles sampled had valid
annualized odometer readings. Of those, 21,154 were for passenger cars and 10,098 were for light
3-7
-------
trucks. While the data set contained much fewer valid annualized odometer readings than self-reported
annual mileage readings, it was decided upon discussions with NPTS staff that the odometer readings
should be used for determining annual mileage accumulation.
Table 3-5. VEHICL95.DBF Data Structure
Field Name
Description
ANNMILES
MODLCODE
VEHTYPE
VEHYEAR
WTHHFIN
ANNUALZD
FLAGODO
FLAGOUT
Self-reported annualized mileage
Model code
Type of Vehicle
Model Year of vehicle
Registrations per record
Odometer based annualized mileage
Flag identifying missing ANNUALZD values
Flag identifying outlier ANNUALZD values
To better define the vehicle classes in the NPTS data, another field was added to the data base
which defined vehicle class (VEHCLASS). Using model codes, vehicle classes shown in Table 3-6
were defined. Vehicle model codes come from the National Accident Sampling System, a major
database of the National Highway Traffic Safety Administration.
Table 3-6. Vehicle Class Definitions
Vehicle Class
Passenger car (CAR)
Sports utility vehicle (SUV)
Minivan (MV)
Pick-up truck (PU)
Other light truck (OTH)
Model Codes
1 - 47, 398, 399
401, 402, 403, 404, 421
44 1} 442, 443
471, 472
431, 461, 470, 481, 482, 461, 470, 498, 499
In discussions with NPTS, it was decided that the mileage (ANNUALZD) should be averaged
using the expansion factor (WTHHFIN) for each vehicle class (VEHCLASS) and model year
(VEHYEAR). The expansion factor, which is specific to each record, is a multiplier applied to expand
the survey responses to represent the national fleet. The expansion factors are based on several
attributes of the survey respondent and help eliminate geographic bias in the data (since much more
data comes from some states than others). NPTS staff strongly recommended that the expansion
3-8
-------
factors be applied as part of the calculations. Since this data did not differentiate between gasoline and
diesel, the same mileage accumulation curve was generated for both1. The data was then curve fit
using the both a 2nd order polynomial and an exponential curve. The curve fit with the highest
coefficient of determination (R2) was chosen. This data was only used for determining mileage
accumulation for light-duty automobiles because the TIUS data, which includes light-duty trucks,
provided additional information on the type of fuel used and the gross vehicle weight of each vehicle.
The program LDVS.PRG to calculate mileage accumulation is listed in Appendix A. Results
of these an analysis are given in Section 4.
The NPTS data was also analyzed to determine if there was any statistically significant
difference between mileage accumulations of various light-duty truck types. Since the NPTS data was
3 years newer than the TIUS data, trends in SUVs might show up in this data set which might not show
up in the older TIUS data. A t-test was run for each light-duty truck type (SUVs, MVs, PUs and
others) listed in Table 3 -6 and compared against an aggregate NPTS light-duty truck category. As with
the TIUS data, within a 95% confidence interval, none of the various truck type mileage accumulation
data were statistically significant from the aggregated light-duty truck category.
3.2.3 Federal Transit Administration Database
Mileage accumulation data for urban buses was calculated using the program BUSES.PRG as
discussed in Section 3.1.2. For each fuel type and model year, annual fleet mileage was summed and
divided by the total number of buses. Buses designated as inactive in the FTA database were not
included in the denominator for this calculation. This results in a higher average annual miles per bus
than if both active and inactive buses were counted and used in the denominator.
The program BUSES.PRGto calculate mileage accumulation is listed in Appendix A. Results
from these calculations are given in Section 4.
1 According to USEPA, light-duty vehicles, whether gas or diesel, are generally used as personal
transportation and so are typically driven in patterns (annual mileage, trip frequencies, etc.) that are determined by
parameters other than fuel type.
3-9
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SECTION 4
RESULTS
Work Assignment Task 6 specifies that the results of this study be compared to the previous
data derived during development of MOBILESa. The results of this study are presented herein as
graphs and tables. In all cases, data from Polk and FTA are utilized for registration counts, and TIUS,
NPTS, FTA and Bobit data are used for mileage accumulation by age. Table 2-1 in Section 2.2
indicates which data source is used for each vehicle type. On some of the graphs at the end of this
section, additional data series from other sources are presented for comparative purposes only.
The Polk registration data presented in the following graphs does not perfectly coincide with
the previous characterization performed during the development of MOBILESa. Absolute values for
vehicle counts almost always differ by some discrete amount, as is to be expected when comparing data
sources developed with different methodologies. In most cases, it is extremely difficult to find
explanations that would account for the differences. In light of this, the following discussion attempts
to point out where the two (or more) data series either coincide or diverge in terms of relative trends
(peaks and valleys), rather than absolute difference. An attempt was made, however, to point out where
absolute values significantly differ and the possible reasons for these discrepancies.
The same attempt has been made with the annual mileage accumulation graphs. Here,
however, a curve fit was placed through the related data set. This has been done to smooth the results
generated from data sets that, especially within certain weight classes, do not contain enough data
points to avoid some dramatic model year variation in the averaged results. ARCADIS Geraghty &
Miller believes that while the graphs sometimes indicate highly erratic mileage differences from one
model year to the next (for the raw data), the curve fits are generally of the appropriate magnitude.
To compare results from this study to other sources, ARCADIS Geraghty & Miller multiplied
the vehicle registrations from each weight class and model year with the respective curve fit mileage,
and then summed the products to obtain the total vehicle miles traveled (VMT) for the entire U. S. fleet
in 1996 (see Table 4-1). This VMT figure (-2.130 trillion miles) was cross-checked with an
independent number generated by the 1996 Highway Statistics (-2.472 trillion miles). The 1996
Highway Statistics calculated total VMT and registrations from a number of independent sources
including state registration data, the 1995 NPTS report, and the 1992 TIUS report.
4-1
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Table 4-1. Total VMT, Registrations, and Annual Mileage
TOTAL VMT
LDVs and LDTs
HDVs
Buses
Total
US Highway Statistics 96
2,283,005,000,000
182,756,000,000
6,535,000,000
2,472,296,000,000
Current Study
1,894,165,618,859
230,289,095,076
5,804,509,986
2,130,259,223,921
% Difference
-17.03%
26.01%
-11.18%
-13.83%
REGISTRATIONS
LDVs and LDTs
HDVs
Buses
Total
US Highway Statistics 96
198,662,139
7,006,408
696,609
206,365,156
Current Study
176,385,176
11,428,172
469,689
188,283,036
% Difference
-11.21%
63.11%
-32.58%
-8.76%
ANNUAL MILEAGE
LDVs and LDTs
HDVs
Buses
Average
US Highway Statistics 96
1 1 ,492
26,084
9,381
11,980
Current Study
10,739
20,151
12,358
11,314
% Difference
-6.55%
-22.75%
31 .73%
-5.56%
Comparison of these two figures indicates that the current study proj ects 13.9% less total VMT
than the FHWA 1996 Highway Statistics study. This is most likely due to a number of factors. First,
the source of registration information differ. In the current study, registration data was supplied by R.L.
Polk Company for 1996. According the FHWA 1996 Highway Statistics report, vehicle registration
data was collected directly from the fifty states. A given state's reported vehicle registration data is
often incompatible with other states' data. For example, in some states a minivan, which by USEPA
regulations is defined as a light-duty truck, would be classified as a passenger car. Both FHWA and
Polk have addressed this problem, and both data sources are corrected for this. However, FHWA
reports that "in some states, it is also possible that contrary to the FHWA reporting instructions,
vehicles which have been registered twice in the same state may be reported as two vehicles." This
may account of some of the difference between the two studies' counts.
A second source of deviation between the two registration estimates arises from the adjustments
that were made to the Polk registration data to address comments made by various USEPA personnel
(see Section 3.1.1). This adjustment decreased light-duty truck registrations by approximately 6.1
million vehicles and increased heavy-duty truck registrations by approximately 2.5 million vehicles
resulting in a total decrease of approximately 3.6 million vehicles in the total U.S. vehicle fleet in this
study.
4-2
-------
A difference in vehicle weight category definition is the primary source of the variation in the
heavy-duty vehicle registration counts. FHWA defines light-duty trucks as having GVWRs up to
10,000 Ibs and heavy-duty trucks as having a GVWR greater than 10,000 Ibs. In accordance with
USEPA definitions, ARCADIS Geraghty & Miller defined light-duty trucks to include GVWRs only
up to 8,500 Ibs and heavy-duty trucks as having GVWRs greater than 8,500 Ibs.
Furthermore, the bus category in Table 4-1 considers only considers school and transit buses
for the current study whereas the 1996 Highway Statistics probably includes buses in addition to
school and transit buses. Buses other than school or transit buses were treated as heavy-duty trucks in
the current study. Polk school bus registration data used in the current study tracked quite well with
other sources, such as the 1997 SchoolBus F/ee^ Fact Book and transit bus registrations from FT A used
in the current study tracked very closely with information from the APTA 7995 Transit Passenger
Vehicle Fleet Inventory.
The average mileage accumulation rates derived in this study were higher than the 1996
Highway Statistics for buses and lower for all other classes. For LDVs, this study used annualized
odometer readings which were found to be approximately 10% lower than the self-estimated values
which were most likely used by FHWA. Also, the heavy-duty vehicles in this study included class 2B
vehicles (GVWR 8,500 - 10,000 Ibs) which have higher mileage accumlation rates than LDVs but
lower than heavy-duty trucks. Since Class 2B vehicles account for approximately 50% of the heavy-
duty vehicles in this study, much of the difference in mileage accumulation rates between this study
and the 1996 Highway Statistics for heavy-duty vehicles results from the addition in this study of a
significant number of vehicles with lower mileage accumulation rates in the heavy-duty class.
Bus mileage accumulations were significantly higher than those listed in the 1996 Highway
Statistics mostly due to inclusion of other bus types (other than transit and school) in the bus category
as defined by the 1996 Highway Statistics.
The differences between data obtained under this study and other sources for each weight class
are discussed below for both registrations and annual mileage accumulations.
4.1 REGISTRATIONS
4.1.1 LDVs
Light-duty registration data obtained from Polk (Figure 4-1) appear to follow the same trend
as the other sources of available registration data. In general, NPTS counts follow Polk data closely.
This further supports the suggestion mentioned above that the R.L. Polk data is probably more accurate
than the 1996Highway Statistics shown in Table 4-1. MOBILES a data indicates slightly higher counts
than Polk, however, MOBILESa data represents registrations as of July 1, 1992 and vehicle attrition
between 1992 and 1996 could account for the differences.
4.1.2 LDTs
Light-duty gasoline trucks (Figures 4-2 and 4-3) also appear to follow relatively similar
patterns. The major difference lies in model years 1976-1982, where peaks in the MOBILESa data
4-3
-------
either do not appear or do not coincide with the Polk data. Since LDDTs were not separated into
classes 1 and 2 during development of MOBILESa, discussion of this vehicle type is described below
under Aggregated Classes in subsection 4.1.5.
4.1.3 Heavy-Duty Trucks and School Buses
Comparison data could not be found in other sources for these vehicle classes (Figures 4-4 to
4-16). In the heavy duty classes, TIUS data was found to be inconclusive for purposes of registration
counts, as was discussed above. Also, MOBILESa contains no easily reproduced block data for the
heavy-duty truck fleet. Thus, only the Polk data is provided in the charts for these vehicles types.
4.1.4 Transit Buses
The data provided by the FT A (Figure 4-17) very closely follows the comparison APT A data.
This further supports the suggestion mentioned above that the apparent large discrepancy between bus
registrations in Table 4-1 is questionable.
4.1.5 Aggregated Classes
Certain aggregations of vehicle classes have been included here upon request of the USEPA.
Aggregated classes are: LDGTs (Figure 4-18) which include LDGT1 andLDGT2, LDDTs (Figure 4-
19) which include LDDT1 and LDDT2, LDTs (Figure 4-20) which include LDGT1, LDGT2, LDDT1
and LDDT2, HDGVs (Figure 4-21) which include HDGV1 and HDGV2, HDGB (Figure 4-22) which
includes gasoline transit and school buses, HDDVs(3-5) (Figure 4-23) which includes HDDV(3) and
HDD Vs(4-5), HDDVs(8) (Figure 4-24) which includes HDDV(8 A) and HDDV(8B), HDD Vs (Figure
4-25) which includes HDDV(2B), HDD V(3), HDD V(4-5), HDD V(6-7), HDDV(8 A) and HDDV(8B),
and HDDBs (Figure 4-26) which include diesel transit and school buses. The registration data
presented in these charts is simply the sum of the registrations in the classes indicated in the chart's
title. Of particular note is the comparison between data sources of LDDTs (Figure 4-19). As
mentioned above, MOBILESa did not discriminate between LDDTls and LDDT2s. For all LDDTs,
MOBILESa shows a peak in model year 1981, with registrations tapering off thereafter. The Polk data
shows significantly more LDDTs in the 1980s and 1990s, as well as a smaller peak in 1974. The reason
for the discrepancy between these two sources is unknown.
4.2 ANNUAL MILEAGE
4.2.1 LDVs
As shown in Figure 4-27, the annual mileage accumulation data provided from the NPTS
shows perhaps the most consistent data series of all the weight classes. Deviation of the data points
from the curve fit is generally small. The graph shows that mileage accumulation rates developed in
this study from 1995 NPTS data are higher than the rates incorporated into MOBILESa, which was
based on the 1983 NPTS study. This is consistent with recent trends indicating that people drive more
miles each year than they used to.
4-4
-------
4.2.2 LDTs
Light-duty truck mileage provided by the TIUS fairly closely tracks MOBILESa data (Figures
4-28 to 4-31). TIUS data for LDGTs indicates somewhat higher accumulation rates for the newer
vehicles and lower rates for older vehicles. For LDDTs, the data indicates that mileage accumulation
is somewhat higher than previously modeled for all vehicle ages, especially in the younger vehicles.
4.2.3 HDGVs
Heavy-duty gasoline trucks follow the same pattern as LDTs. However, the TIUS data
indicates that the older, heavier HDGV2s acquire fewer annual miles than MOBILESa indicates
(Figures 4-32 and 4-33)
4.2.4 HDGBs
ARCADIS Geraghty & Miller could not obtain suitable annual mileage rates for the gasoline
transit buses on an age basis. The 199 7 School Bus Fleet Fact Book Issue provides information placing
average school bus accumulation rates at 9,939 miles per year (for both gasoline and diesel school
buses).
4.2.5 HDDVs
For the lighter heavy-duty diesel classes (2B and 3), the TIUS data indicates the same trends
as both LDTs and HDGVs (Figures 4-36 and 4-37) However, the relative difference compared to
MOBILESa is greater for these vehicle classes than the others, up to as much as 50% greater than the
previously used value.
Classes 4 and 5 (Figure 4-38) show an altogether different pattern. Here, TIUS annual
accumulation rates are significantly greater than previous MOBILE values for all vehicle ages. This
is especially true at about Age 10, where there is about a 100% increase in mileage. One possible
reason may partly explain this occurrence. Note that the MOBILESa curve is the same for both Figures
4-37 and 4-38. This is because, in MOBILESa, mileage rates were accumulated for Classes 3 through
5 as an aggregate sum. Since there are nearly twice as many vehicles in Class 3 as there are in both 4
and 5 combined, the average mileage accumulation rate would tend to be lower, closer to the individual
Class 3 average. Thus the MOBILESa curve plotted here for Classes 4 and 5 is probably too low to
properly characterize these weight classes.
Classes 6 and 7 (Figure 4-39) indicate the opposite; TIUS mileage values are slightly less than
older MOBILESa values.
Classes 8A and 8B (Figures 4-40 and 4-41) mileage rates developed in this study are slightly
lower and higher, respectively, than MOBILESa. This is due partly to the same reason as explained
for Classes 4 and 5. MOBILESa only tracked Class 8 mileage accumulation rates. That curve, which
appears on both these figures, lies in between the two TIUS data sets, since it is the average
accumulation rate for all the vehicles in both sets (although weighted about 3 to 1 toward the 8B class,
since there are about 3 times as many 8B vehicles as there are 8A trucks.)
4-5
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4.2.6 HDDBs
Like gasoline school buses, diesel school buses have an average mileage accumulation for all
vehicles of 9,939 miles per year. Heavy-duty diesel transit bus mileages have been derived from an
analysis of the FTA Form 408 data set (Figure 4-42). Comparison data from other sources is not
available for this class.
4.3 TABLES
Additional information is provided in Tables 4-2 to 4-8 at the end of this report. Each is
categorized by weight class, fuel type and model year. Table 4-2 shows the total registrations received
from Polk and modified by ARCADIS Geraghty & Miller as described above. Table 4-3 shows the
raw annual mileage data available from the various sources listed above, while Table 4-4 is the annual
mileage curve fit for each weight class. Table 4-5 lists the mileage accumulation curve fit equations
used for each weight class. In Table 4-6, the percentage of vehicles in each model year as a fraction
of the total vehicles in the weight class is shown. Both total vehicles and percentages are also displayed
for aggregated weight classes in Tables 4-7 and 4-8. Finally, Table 4-9 is the gasoline/diesel sales
fraction of light-duty vehicles and trucks from 1985 to 1996, as requested in Work Assignment Task
4.
4-6
-------
g
+-
TO
Figure 4-1. Registration Comparison by Model Year
LDV
12,000,000
10,000,000 --
8,000,000 --
w 6,000,000
I
4,000,000
2,000,000
1995NPTS
1996 Polk
1992MOBILE5a
96 94 92 90
86 84 82 80 78 76 74 72 70 68 66
Model Year
(A
c
g
+-
TO
+j
(A
SP
Figure 4-2. Registration Comparison by Model Year
LDGT1
1996 Polk
1992MOBILE5a
96 94 92 90
86 84 82 80 78 76 74 72 70 68 66
Model Year
4-7
-------
(A
C
g
+-
TO
+j
(A
'Sf
a:
Figure 4-3. Registration Comparison by Model Year
LDGT2
1996 Polk
1992 MOBILESa
96 94 92 90 88 86 84 82 80 78 76 74 72 70 68 66
Model Year
c 40,000 --
o
'Sf
a:
Figure 4-4. Registration Comparison by Model Year
LDDT1
96 94 92 90
86 84 82 80 78 76 74 72 70 68 66
Model Year
4-8
-------
(A
O
+j
TO
1
8"
a:
Figure 4-5. Registration Comparison by Model Year
LDDT2
96 94 92 90
86 84 82 80 78 76 74 72 70 68 66
Model Year
600,000
Figure 4-6. Registrations by Model Year
HDGV(2B-3)
96 94 92 90 88 86 84 82 80 78 76
Model Year
74 72 70 68 66
4-9
-------
(A
C
g
+-
TO
4-*
(A
'ro
0)
a:
(A
C
g
^-t
TO
Figure 4-7. Registrations by Model Year
HDGV(4-8)
i.OOO
96 94 92 90 88 86 84 82 80 78 76 74 72 70 68 66
Model Year
Figure 4-8. Registrations by Model Year
HDGB School
96 94 92 90 88 86 84 82 80 78 76 74 72 70 68 66
Model Year
4-10
-------
(A
O
is
+j
to
SP
a:
140
120 --
100 --
80 --
60 --
40 --
20 --
Figure 4-9. Registrations by Model Year
HDGB Transit
96 94 92 90 88 86
84 82 80
Model Year
78 76 74 72 70 68 66
(A
C
g
+-
TO
4-*
(A
'O)
0)
180,000
Figure 4-10. Registrations by Model Year
HDDV(2B)
96 94 92 90 88 86 84 82 80 78 76
Model Year
74 72 70 68 66
4-11
-------
60,000
50,000 --
§ 40,000--
30,000
20,000
10,000 --
Figure 4-11. Registrations by Model Year
HDDV(3)
96 94 92 90
86 84 82 80 78 76 74 72 70 68 66
Model Year
I
50,000
Figure 4-12. Registrations by Model Year
HDDV(4-5)
96 94 92 90 88 86 84 82 80 78 76 74 72 70 68 66
Model Year
4-12
-------
g
+-
TO
O)
0)
120,000
0 -
Figure 4-13. Registrations by Model Year
HDDV(6-7)
96 94 92 90 88 86 84 82 80 78 76 74 72 70 68 66
Model Year
TO
i:
(A
60,000
50,000 --
w 40,000--
o
30,000
20,000
10,000 --
0 --
Figure 4-14. Registrations by Model Year
HDDV(8A)
96 94 92 90 88 86 84
82 80 78
Model Year
76 74 72 70 68 66
4-13
-------
(A
C
g
^-t
TO
1
SP
Figure 4-15. Registrations by Model Year
HDDV(8B)
96 94 92 90 88 86 84 82 80 78 76 74 72 70 68 66
Model Year
(A
.g
^-t
TO
i:
(A
,000
Figure 4-16. Registrations by Model Year
HDDB School
96 94 92 90 88 86 84 82 80 78 76 74 72 70 68 66
4-14
-------
(A
C
g
+-
TO
4-*
(A
'ro
0)
a:
1,000
Figure 4-17. Registrations by Model Year
HDDB Transit
96 94 92 90 88 86 84 82 80 78 76 74 72
Model Year
70 68 66
6,000,000
5,000,000 --
4,000,000
.2 3,000,000--
ff
£
2,000,000 --
1,000,000 --
Figure 4-18. Registrations by Model Year
Aggregated LDGT
96 94 92 90 88 86 84 82 80 78 76 74 72 70 68 66
Model Year
4-15
-------
(0
g
"S
^
+j
(0
(0
c
g
is
01
1,000
Figure 4-19. Registrations by Model Year
Aggregated LDDT
1996 Polk
1992MOBILE5a
96 94 92 90 88 86 84 82 80 78 76 74 72 70 68 66
Model Year
Figure 4-20. Registrations by Model Year
Aggregated LOT
i 1 1 1 1 1 1 1 1 1 1
96 94 92 90 88 86 84 82 80 78 76 74 72 70 68 66
Model Year
4-16
-------
600,000
500,000 --
Ğj 400,000
g
is
jjj 300,000--
ff
* 200,000--
100,000 --
Figure 4-21. Registrations by Model Year
Aggregated HDGV
96 94 92 90 88 86 84
82 80 78
Model Year
76 74 72 70 68 66
(0
g
+J
OJ
k.
4-1
to
,000
Figure 4-22. Registrations by Model Year
Aggregated HDGB
1996 Polk &1994 FTA
96 94 92 90 88 86 84 82 80 78 76 74 72 70 68 66
4-17
-------
120,000
Figure 4-23. Registrations by Model Year
Aggregated HDDV(3-5)
o -
96 94 92 90 88 86 84 82 80 78 76 74 72 70 68 66
Model Year
250,000 -r
200,000 --
o 150,000--
(0
'ff
01
100,000
50,000 --
Figure 4-24. Registrations by Model Year
Aggregated HDDV(8)
96 94 92 90 88 86 84 82 80 78 76 74 72 70
Model Year
68 66
4-18
-------
700,000
600,000 --
500,000 --
£ 400,000--
ns
g) 300,000
o:
200,000
100,000 --
Figure 4-25. Registrations by Model Year
Aggregated HDDV All
96 94 92 90 88 86 84 82 80 78 76 74 72 70 68 66
Model Year
Figure 4-26. Registrations by Model Year
Aggregated HDDB
40,000
35,000 --
30,000 --
£ 25,000--
g
| 20,000
tfi
$ 15,000
1996 Polk &1994 FTA
96 94 92 90 88 86 84 82 80 78 76 74 72 70 68
4-19
-------
25,000
20,000 --
2 15,000 --
= 10,000 --
5,000 --
Figure 4-27. Annual Miles by Age
LDV
-1995NPTS
-MOBILESa(LDGVonly)
-MOBILE5a(LDDVonly)
-Expon.(1995NPTS)
y= 15684e
-0.0506X
Age
Figure 4-28. Annual Miles by Age
LDGT1
-1992TIUS
-MOBILESa
-Poly. (1992 TIUS)
y = 17.472X2 -1163.7x + 20642
10
15
20
25
30
35
Age
4-20
-------
25,000
20,000 --
Ğ 15,000 --
ro
D
10,000 --
5,000 --
Figure 4-29. Annual Miles by Age
LDGT2
y = 22905e'
-0.0712X
-1992TIUS
-MOBILESa
-Expon.(1992TIUS)
10
15
20
Age
25
Figure 4-30. Annual Miles by Age
LDDT1
30
35
1992 TIUS
MOBILESa (all LDDT)
Expon. (1992 TIUS)
10
15
20
Age
25
30
35
4-21
-------
Figure 4-31. Annual Miles by Age
LDDT2
1992TIUS
MOBILESa (all LDDT)
Expon.(1992TIUS)
10
15
20
25
Age
30
35
25,000
20,000 --
Ğ 15,000 --
ro
D
10,000 --
5,000 --
Figure 4-32. Annual Miles by Age
HDGV(2B-3)
-1992TIUS
-MOBILESa (all HDGV)
-Expon.(1992TIUS)
y = 21250e
-0.0618x
10
15
20
Age
25
30
35
4-22
-------
25,000
20,000 --
Ğ 15,000 --
ro
D
10,000 --
5,000 --
Figure 4-33. Annual Miles by Age
HDGV(4-8)
-1992TIUS
-MOBILE5a(allHDGV)
-Expon.(1992TIUS)
y = 23243e
-0.0829X
10
15
20
25
30
35
Age
Figure 4-34. Annual Miles by Age
HDGB School
(A
i
"J5
3
C
C
14,000 -
12,000 -
10 000 -
8,000 -
6,000 -
4,000 -
2,000 -
0 -
(
1997 School Bus Fleet Fact Book
Average annual mileage for
all model years is 9,939
i i i i i i
i i i i i i
3 5 10 15 20 25 30 3
Age
4-23
-------
Figure 4-35. Annual Miles by Age
HDGB Transit
1994FTA
Expon.(1994FTA)
10
15
20
Age
25
30
35
Figure 4-36. Annual Miles by Age
HDDV(2B)
1992 TIUS
MOBILESa
Expon. (1992 TIUS)
10
15
Age
20
25
30
35
4-24
-------
Figure 4-37. Annual Miles by Age
HDDV(3)
y = 37008e
-0.1222X
-1992TIUS
-MOBILESa
-Expon.(1992TIUS)
Figure 4-38. Annual Miles by Age
HDDV(4-5)
1992TIUS
MOBILESa
Expon.(1992TIUS)
10
15
20
Age
25
30
35
4-25
-------
(A
0)
i 20,000 --
c
Figure 4-39. Annual Miles by Age
HDDV(6-7)
1992TIUS
MOBILESa
Expon.(1992TIUS)
10
15
20
25
30
35
Age
Figure 4-40. Annual Miles by Age
HDDV(8A)
1992 TIUS
MOBILESa (All Class 8)
Expon. (1992 TIUS)
10
15
20
25
30
35
Age
4-26
-------
Figure 4-41. Annual Miles by Age
HDDV(8B)
1992 TIUS
MOBILESa (All Class 8)
Expon. (1992 TIUS)
10
15
20
25
30
35
Age
Figure 4-42. Annual Miles by Age
HDDB School
s
ro
-I
c
c
14, DUD -
12,000 -
10 000 -
8,000 -
6,000 -
4,000 -
2,000 -
n -
- 1 997 School
Average annual mileage for
all model years is 9,939
Bus Fleet Fact Book
10
15
20
25
30
35
Age
4-27
-------
50,000
Figure 4-43. Annual Miles by Age
HDDB Transit
1994 FTA
Expon.(1994FTA)
10
15
20
25
30
35
Age
4-28
-------
Table 4-2. Vehicles in Operation as of July 1996
U.S. Levels
Model
Year
96
95
94
93
92
91
90
89
88
87
86
85
84
83
82
81
80
79
78
77
76
75
74
73
72
71
70
69
68
67
66
TOTAL
LDV
LDGV
5999331
9166694
7966182
8027524
7468105
7742072
7927068
8687143
8800821
8403556
8093892
7090963
5978688
3831635
2710825
2305351
1953647
2237823
1785913
1335445
824579
477882
532240
0
0
0
0
0
0
0
0
119347379
LDDV
5330
5425
630
2715
4432
9746
3280
3676
568
23000
26380
69659
98664
94461
145689
175194
79200
61862
20597
12593
11453
7505
3599
0
0
0
0
0
0
0
0
865658
LDGT
LDGT1
<6000
2475332
3723979
3636380
3338741
2716821
2893672
2517145
2922994
2961942
2666470
2600147
2040755
1670540
948999
739107
651163
446378
529703
384720
328772
389724
210964
335900
0
0
0
0
0
0
0
0
41130348
LDGT2
6001-8500
963616
1450819
1214578
855812
748099
570854
712943
833087
737315
576923
701241
661168
564080
388127
277091
251737
340398
820584
756833
587410
295581
181913
130161
0
0
0
0
0
0
0
0
14620369
LDDT
LDDT1
<6000
0
0
1
0
0
0
0
0
0
1937
8701
9754
20230
21601
51916
42762
20482
17283
10222
0
7408
24441
44505
0
0
0
0
0
0
0
0
281243
LDDT2
6001-8500
12298
16827
13634
12582
8703
7481
6943
6934
5338
4760
8808
9038
9680
8271
7279
329
217
917
93
21
12
8
7
0
0
0
0
0
0
0
0
140179
HDGV
2B-3
8501-14000
321205
483606
404859
285271
249366
190285
237648
277696
245772
192308
233747
220389
188027
129376
92364
83912
113466
273528
252278
195803
98527
60638
43387
0
0
0
0
0
0
0
0
4873456
4-8
>14000
16273
54732
47587
35154
36885
35345
47336
55083
70682
58113
51373
56147
55959
37983
37446
37952
45494
88619
69373
67918
67102
90069
94921
93372
72328
54597
57955
50761
39588
38887
34371
1699401
HDGB
S.BUS
ANYWGT.
516
4408
2926
2673
102
2368
4009
4342
6115
6980
8209
11009
11363
10931
9270
12053
10434
9290
8459
9547
6915
8715
0
0
0
0
0
0
0
0
0
150634
T.BUS
ANYWGT.
0
0
30
54
108
83
55
116
78
84
87
28
34
23
11
4
9
13
2
1
2
3
1
0
0
0
0
0
0
0
0
826
LDV Light duty vehicle
LDGV Light duty gasoline vehicle
LDDV Light duty diesel vehicle
LDGT Light duty gasoline truck
LDDT Light duty diesel truck
HDGV Heavy duty gasoline vehicle
HDGB Heavy duty gasoline bus
4-29
-------
Table 4-2. Vehicles in operation as of July 1996 (continued)
U.S. Levels
Model
Year
96
95
94
93
92
91
90
89
88
87
86
85
84
83
82
81
80
79
78
77
76
75
74
73
72
71
70
69
68
67
66
TOTAL
HDDV
2B
8501-10000
77760
162857
131869
133923
93290
77685
72117
69774
50752
45383
84934
80761
78286
51681
35845
1135
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1248050
3
10001-14000
20611
49894
46825
37278
31827
28002
40421
32708
22387
20704
25966
10736
6075
4005
2110
21
0
0
1
2
3
5
34
20
0
0
0
0
0
0
4
379639
4-5
14001-19500
15084
45619
29457
26359
20855
14467
18977
20834
13770
4064
2184
2066
1565
454
198
246
2
0
0
0
268
106
6
127
118
60
38
116
95
94
71
217303
6-7
19501-33000
36848
112777
69815
63675
55070
64578
80650
60814
68499
69454
60684
61696
56347
28033
29110
39861
27106
23784
14891
7938
4459
4534
3740
3497
2601
1905
4447
2618
2007
321
261
1062021
8A*
33001-60000
22858
55767
41561
35682
18191
25051
28786
29759
25953
29736
28204
30539
25970
13613
18921
23076
19685
28160
21616
14940
9327
15695
5779
5492
4445
3799
3386
850
655
186
277
587955
8B*
>60000
63398
154674
115272
98966
79092
71036
83175
98894
89567
74622
59103
69423
56621
26483
28273
33078
24454
36212
29266
23464
9767
10430
8590
7013
3650
1980
791
1205
605
946
298
1360346
HDDB
S.BUS
ANYWGT.
12592
34395
17088
19899
20696
24920
28698
15007
18602
19539
17097
11743
7120
5245
4488
4324
659
448
253
235
60
77
0
0
0
0
0
0
0
0
0
263185
T.BUS**
ANYWGT.
1186
2496
2278
3188
4682
3829
3167
3299
3330
3741
3206
3989
3017
3270
3811
1695
1182
760
510
682
338
393
247
211
73
106
78
90
189
55043
ALL
VEHICLES
TOTAL
10043049
15522473
13739879
12978803
11553918
11760833
11813932
13122690
13121329
12200932
12014086
10439615
8832456
5604910
4192960
3665466
3085441
4129922
3355700
2584847
1725698
1093667
1203209
109914
83389
62551
66691
55655
43028
40524
35470
188283036
HDDV Heavy duty diesel vehicle
HDDB Heavy duty diesel bus
* in MY 93-96, assumed 26.5% of Class 8 vehicles are Class 8A; for all other MY, percentage based upon
1992 TIUS data
** transit bus registrations are from FTA data
4-30
-------
Table 4-3. Annual Mileage Accumulation (Raw Data)
U.S. Levels
Vehicle
Age
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
LDV
LDGV
13386
13488
12496
12351
12059
11343
11067
10004
10718
8910
9046
10527
8268
8330
8337
7241
9015
6966
5479
4460
4940
4125
6531
5719
2357
6470
2921
LDDV
13386
13488
12496
12351
12059
11343
11067
10004
10718
8910
9046
10527
8268
8330
8337
7241
9015
6966
5479
4460
4940
4125
6531
5719
2357
6470
2921
LDGT
LDGT1
<6000
19698
16825
16770
16386
15677
15132
13883
12938
12522
12026
10008
7726
8940
6904
6238
6365
5278
5662
5704
4011
3127
2994
3465
2556
3616
2639
1382
1685
1622
LDGT2
6001-8500
21694
18416
17576
15141
16733
13229
14587
12677
13392
11527
14292
10784
7411
7026
7597
9852
9895
5365
5660
3239
7557
5500
4471
3124
LDDT
LDDT1
<6000
22653
25994
20482
17448
18890
19068
16500
14710
13016
10347
11272
5738
LDDT2
6001-8500
20882
24072
22784
22879
21633
22558
15628
11402
18014
13072
7357
9470
9000
HDGV
2B-3
8501-14000
18815
17574
18405
15697
14700
13281
12662
15497
13804
12067
9484
10058
11476
10011
9862
10138
7763
4234
5009
8798
6501
4122
4-8
>14000
23355
19328
16790
14549
14475
14502
15391
13001
12847
11745
9122
6287
7621
6662
6519
5997
6464
4397
3999
4412
4062
5736
5628
3356
2149
2091
1820
2714
2356
HDGB
S.BUS
ANYWGT.
(a)
T.BUS
ANYWGT.
(b)
28426
29869
26386
24000
22708
18205
23463
13141
16905
(b)
16882
12600
9000
5250
8583
(b)
(b)
(b)
(b)
6000
LDV Light duty vehicle
LDGV Light duty gasoline vehicle
LDDV Light duty diesel vehicle
LDGT Light duty gasoline truck
LDDT Light duty diesel truck
HDGV Heavy duty gasoline vehicle
HDGB Heavy duty gasoline bus
(a) Average school bus mileage for all ages = 9,939
(b) Indicates data point was removed as an abnormality
4-31
-------
Table 4-3. Annual Mileage Accumulation (Raw Data) (continued)
U.S. Levels
Vehicle
Age
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
HDDV
2B
8501-10000
22533
24591
21502
21973
22448
20624
18932
12949
16151
9320
15151
6750
7200
8000
9000
3
10001-14000
26616
27581
26920
27678
20526
22980
17816
17268
12186
6333
6000
10159
4-5
14001-19500
32471
23791
24800
19624
17776
23767
20066
21918
26337
29844
27830
13571
8341
8400
11000
6-7
19501-33000
39017
30011
27931
26190
25680
23481
23955
21071
23124
18216
13646
15412
11618
11487
9458
12977
6269
16296
14115
13844
5297
5000
1805
1053
7000
8A
33001-60000
85794
57498
59784
62189
55199
48350
39863
41742
36635
32963
25153
18800
21244
19149
19386
10912
13256
17975
18036
17712
7459
13934
8493
9452
14818
2088
5533
502
SB
>60000
113141
98673
95977
93147
84050
75736
68358
66294
60231
54245
39068
37879
30798
32119
28777
30416
32813
19820
22471
21928
25033
30084
22559
17363
13278
5538
19040
10417
1350
8443
HDDB
S.BUS
ANYWGT.
(a)
T.BUS
ANYWGT.
(b)
(b)
46791
41262
42206
39160
38266
36358
34935
33021
32540
32605
27722
28429
32140
28100
24626
23428
22575
23220
19588
22939
26413
23366
11259
23228
21515
25939
20117
17515
HDDV Heavy duty diesel vehicle
HDDB Heavy duty diesel bus
(a) Average school bus mileage for all ages = 9,939
(b) Indicates data point was removed as an abnormality
4-32
-------
Table 4-4. Annual Mileage Accumulation (Curve Fit Data)
U.S. Levels
Vehicle
Age
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
LDV
LDGV
14910
14174
13475
12810
12178
11577
11006
10463
9947
9456
8989
8546
8124
7723
7342
6980
6636
6308
5997
5701
5420
5152
4898
4656
4427
4208
4001
3803
3616
3437
LDDV
14910
14174
13475
12810
12178
11577
11006
10463
9947
9456
8989
8546
8124
7723
7342
6980
6636
6308
5997
5701
5420
5152
4898
4656
4427
4208
4001
3803
3616
3437
LDGT
LDGT1
<6000
19496
18384
17308
16267
15260
14289
13352
12451
11584
10752
9955
9194
8467
7775
7118
6496
5909
5356
4839
4357
3909
3497
3120
2777
2470
2197
1959
1756
1589
1456
LDGT2
6001-8500
21331
19865
18500
17228
16044
14942
13915
12959
12068
11239
10466
9747
9077
8453
7872
7331
6827
6358
5921
5514
5135
4782
4454
4148
3863
3597
3350
3120
2905
2706
LDDT
LDDT1
<6000
27059
24384
21973
19801
17843
16079
14490
13057
11766
10603
9555
8610
7759
6992
6301
5678
5116
4610
4155
3744
3374
3040
2740
2469
2225
2005
1807
1628
1467
1322
LDDT2
6001-8500
26040
24018
22154
20434
18848
17385
16036
14791
13643
12584
11607
10706
9875
9109
8402
7749
7148
6593
6081
5609
5174
4772
4402
4060
3745
3454
3186
2939
2711
2500
HDGV
2B-3
8501-14000
19977
18779
17654
16596
15601
14666
13787
12961
12184
11454
10768
10122
9516
8946
8409
7905
7432
6986
6568
6174
5804
5456
5129
4822
4533
4261
4006
3766
3540
3328
4-8
>14000
21394
19692
18125
16683
15356
14134
13010
11975
11022
10145
9338
8595
7911
7282
6703
6169
5679
5227
4811
4428
4076
3752
3453
3178
2926
2693
2479
2281
2100
1933
HDGB
S.BUS
ANYWGT.
(a)
T.BUS
ANYWGT.
35123
31914
28999
26350
23942
21755
19768
17962
16321
14830
13475
12244
11126
10109
9186
8347
7584
6891
6262
5690
5170
4698
4268
3879
3524
3202
2910
2644
2402
2183
LDV Light duty vehicle
LDGV Light duty gasoline vehicle
LDDV Light duty diesel vehicle
LDGT Light duty gasoline truck
LDDT Light duty diesel truck
HDGV Heavy duty gasoline vehicle
HDGB Heavy duty gasoline bus
(a)
Average school bus mileage for all ages = 9,939
4-33
-------
Table 4-4. Annual Mileage Accumulation (Curve Fit Data) (continued)
U.S. Levels
Vehicle
Age
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
HDDV
2B
8501-10000
27137
24831
22721
20791
19024
17407
15928
14575
13336
12203
11166
10217
9349
8555
7828
7163
6554
5997
5488
5021
4595
4204
3847
3520
3221
2947
2697
2468
2258
2066
3
10001-14000
32751
28984
25650
22699
20088
17778
15733
13923
12321
10904
9650
8540
7557
6688
5919
5238
4635
4102
3630
3213
2843
2516
2227
1971
1744
1543
1366
1209
1070
947
4-5
14001-19500
30563
28622
26805
25103
23509
22016
20618
19309
18083
16935
15860
14853
13910
13026
12199
11425
10699
10020
9384
8788
8230
7707
7218
6760
6331
5929
5552
5200
4869
4560
6-7
19501-33000
40681
36872
33420
30291
27455
24885
22555
20443
18529
16795
15222
13797
12505
11335
10273
9312
8440
7650
6933
6284
5696
5163
4679
4241
3844
3484
3158
2862
2594
2352
8A SB
33001-60000 >60000
87821 124208
78257 112590
69735 102060
62141 92514
55374 83861
49343 76017
43970 68907
39181 62462
34915 56620
31112 51324
27724 46523
24705 42172
22015 38228
19617 34652
17481 31411
15577 28473
13881 25810
12369 23396
11022 21208
9822 19224
8752 17426
7799 15796
6950 14319
6193 12979
5518 11765
4918 10665
4382 9667
3905 8763
3480 7944
3101 7201
HDDB
S.BUS
ANYWGT.
(a)
T.BUS
ANYWGT.
45171
43731
42337
40987
39681
38416
37191
36005
34857
33746
32670
31629
30620
29644
28699
27784
26898
26041
25211
24407
23629
22875
22146
21440
20757
20095
19454
18834
18234
17652
HDDV Heavy duty diesel vehicle
HDDB Heavy duty diesel bus
(a)
Average school bus mileage for all ages = 9,939
4-34
-------
Table 4-5. Annual mileage accumulation curve fit equations
Vehicle Class
LDGV
LDDV
LDGT1
LDGT2
LDDT1
LDDT2
HDGV (2B-3)
HDGV (4-8)
HDGSB
HDGTB
HDDV (2B)
HDDV (3)
HDDV (4-5)
HDDV (6-7)
HDDV (8A)
HDDV (8B)
HDDSB
HDDTB
Equation
y=15684e-°-0506x
y=15684e-°-0506x
y = 17.472x2 -1163.7x + 20642
y = 22905e-°0712x
y = 300280-°1041x
y = 28231 e-°-0808x
y = 21250e-°0618x
y = 23243e-°0829x
y = 9939
y = 386540-°0958x
y = 29657e-ao888x
y = 37008e-°1222x
y = 32635e-°0656x
y = 44883e-°0983x
y = 985540-°1153x
y= 1370240-°0982x
y = 9939
y = 46659e-°0324x
x = Model year -1900
y = Annual mileage (miles)
4-35
-------
Table 4-6. Vehicles in Operation as Percent of Class as of July 1996
U.S. Levels
Model
Year
96
95
94
93
92
91
90
89
88
87
86
85
84
83
82
81
80
79
78
77
76
75
74
73
72
71
70
69
68
67
66
TOTAL
LDV
LDGV
5.03%
7.68%
6.67%
6.73%
6.26%
6.49%
6.64%
7.28%
7.37%
7.04%
6.78%
5.94%
5.01%
3.21%
2.27%
1.93%
1.64%
1.88%
1.50%
1.12%
0.69%
0.40%
0.45%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
100%
LDDV
0.62%
0.63%
0.07%
0.31%
0.51%
1.13%
0.38%
0.42%
0.07%
2.66%
3.05%
8.05%
11.40%
10.91%
16.83%
20.24%
9.15%
7.15%
2.38%
1.45%
1.32%
0.87%
0.42%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
100%
LDGT
LDGT1
<6000
6.02%
9.05%
8.84%
8.12%
6.61%
7.04%
6.12%
7.11%
7.20%
6.48%
6.32%
4.96%
4.06%
2.31%
1.80%
1.58%
1.09%
1.29%
0.94%
0.80%
0.95%
0.51%
0.82%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
100%
LDGT2
6001-8500
6.59%
9.92%
8.31%
5.85%
5.12%
3.90%
4.88%
5.70%
5.04%
3.95%
4.80%
4.52%
3.86%
2.65%
1.90%
1.72%
2.33%
5.61%
5.18%
4.02%
2.02%
1 .24%
0.89%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
100%
LDDT
LDDT1
<6000
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.69%
3.09%
3.47%
7.19%
7.68%
18.46%
15.20%
7.28%
6.15%
3.63%
0.00%
2.63%
8.69%
15.82%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
100%
LDDT2
6001-8500
8.77%
12.00%
9.73%
8.98%
6.21%
5.34%
4.95%
4.95%
3.81%
3.40%
6.28%
6.45%
6.91%
5.90%
5.19%
0.23%
0.15%
0.65%
0.07%
0.02%
0.01%
0.01%
0.01%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
100%
HDGV
2B-3
8501-14000
6.59%
9.92%
8.31%
5.85%
5.12%
3.90%
4.88%
5.70%
5.04%
3.95%
4.80%
4.52%
3.86%
2.65%
1.90%
1.72%
2.33%
5.61%
5.18%
4.02%
2.02%
1 .24%
0.89%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
100%
4-8
>14000
0.96%
3.22%
2.80%
2.07%
2.17%
2.08%
2.79%
3.24%
4.16%
3.42%
3.02%
3.30%
3.29%
2.24%
2.20%
2.23%
2.68%
5.21%
4.08%
4.00%
3.95%
5.30%
5.59%
5.49%
4.26%
3.21%
3.41%
2.99%
2.33%
2.29%
2.02%
100%
HDGB
S.BUS
ANYWGT.
0.34%
2.93%
1.94%
1.77%
0.07%
1.57%
2.66%
2.88%
4.06%
4.63%
5.45%
7.31%
7.54%
7.26%
6.15%
8.00%
6.93%
6.17%
5.62%
6.34%
4.59%
5.79%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
100%
T.BUS
ANYWGT.
0.00%
0.00%
3.63%
6.54%
13.08%
10.05%
6.66%
14.04%
9.44%
10.17%
10.53%
3.39%
4.12%
2.78%
1.33%
0.48%
1.09%
1.57%
0.24%
0.12%
0.24%
0.36%
0.12%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
100%
LDV Light duty vehicle
LDGV Light duty gasoline vehicle
LDDV Light duty diesel vehicle
LDGT Light duty gasoline truck
LDDT Light duty diesel truck
HDGV Heavy duty gasoline vehicle
HDGB Heavy duty gasoline bus
4-36
-------
Table 4-6. Vehicles in Operation as Percent of Class as of July 1996 (continued)
U.S. Levels
Model
Year
96
95
94
93
92
91
90
89
88
87
86
85
84
83
82
81
80
79
78
77
76
75
74
73
72
71
70
69
68
67
66
TOTAL
HDDV
2B
8501-10000
6.23%
13.05%
10.57%
10.73%
7.47%
6.22%
5.78%
5.59%
4.07%
3.64%
6.81%
6.47%
6.27%
4.14%
2.87%
0.09%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
100%
3
10001-14000
5.43%
13.14%
12.33%
9.82%
8.38%
7.38%
10.65%
8.62%
5.90%
5.45%
6.84%
2.83%
1 .60%
1.06%
0.56%
0.01%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.01%
0.01%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
100%
4-5
14001-19500
6.94%
20.99%
13.56%
12.13%
9.60%
6.66%
8.73%
9.59%
6.34%
1.87%
1.01%
0.95%
0.72%
0.21%
0.09%
0.11%
0.00%
0.00%
0.00%
0.00%
0.12%
0.05%
0.00%
0.06%
0.05%
0.03%
0.02%
0.05%
0.04%
0.04%
0.03%
100%
6-7
19501-33000
3.47%
10.62%
6.57%
6.00%
5.19%
6.08%
7.59%
5.73%
6.45%
6.54%
5.71%
5.81%
5.31%
2.64%
2.74%
3.75%
2.55%
2.24%
1.40%
0.75%
0.42%
0.43%
0.35%
0.33%
0.24%
0.18%
0.42%
0.25%
0.19%
0.03%
0.02%
100%
8A*
33001-60000
3.89%
9.48%
7.07%
6.07%
3.09%
4.26%
4.90%
5.06%
4.41%
5.06%
4.80%
5.19%
4.42%
2.32%
3.22%
3.92%
3.35%
4.79%
3.68%
2.54%
1.59%
2.67%
0.98%
0.93%
0.76%
0.65%
0.58%
0.14%
0.11%
0.03%
0.05%
100%
8B*
>60000
4.66%
11.37%
8.47%
7.28%
5.81%
5.22%
6.11%
7.27%
6.58%
5.49%
4.34%
5.10%
4.16%
1.95%
2.08%
2.43%
1.80%
2.66%
2.15%
1.72%
0.72%
0.77%
0.63%
0.52%
0.27%
0.15%
0.06%
0.09%
0.04%
0.07%
0.02%
100%
HDDB
S.BUS
ANYWGT.
4.78%
13.07%
6.49%
7.56%
7.86%
9.47%
10.90%
5.70%
7.07%
7.42%
6.50%
4.46%
2.71%
1.99%
1.71%
1 .64%
0.25%
0.17%
0.10%
0.09%
0.02%
0.03%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
100%
T.BUS**
ANYWGT.
0.00%
0.00%
2.15%
4.53%
4.14%
5.79%
8.51%
6.96%
5.75%
5.99%
6.05%
6.80%
5.82%
7.25%
5.48%
5.94%
6.92%
3.08%
2.15%
1.38%
0.93%
1.24%
0.61%
0.71%
0.45%
0.38%
0.13%
0.19%
0.14%
0.16%
0.34%
100%
ALL
VEHICLES
TOTAL
5.33%
8.24%
7.30%
6.89%
6.14%
6.25%
6.27%
6.97%
6.97%
6.48%
6.38%
5.54%
4.69%
2.98%
2.23%
1.95%
1 .64%
2.19%
1.78%
1.37%
0.92%
0.58%
0.64%
0.06%
0.04%
0.03%
0.04%
0.03%
0.02%
0.02%
0.02%
100%
HDDV Heavy duty diesel vehicle
HDDB Heavy duty diesel bus
4-37
-------
Table 4-7. Vehicles in Operation as of July 1996
Aggregated Classes, U.S. Levels
Model
Year
96
95
94
93
92
91
90
89
88
87
86
85
84
83
82
81
80
79
78
77
76
75
74
73
72
71
70
69
68
67
66
TOTAL
LDV
all
6004661
9172119
7966812
8030239
7472537
7751818
7930348
8690819
8801389
8426556
8120272
7160622
6077352
3926096
2856514
2480545
2032847
2299685
1806510
1348038
836032
485387
535839
0
0
0
0
0
0
0
0
120213037
LDGT
all
<8500
3438948
5174798
4850958
4194553
3464920
3464526
3230088
3756081
3699257
3243393
3301388
2701923
2234620
1337126
1016198
902900
786776
1350287
1141553
916182
685305
392877
466061
0
0
0
0
0
0
0
0
55750717
LDDT
all
<8500
12298
16827
13635
12582
8703
7481
6943
6934
5338
6697
17509
18792
29910
29872
59195
43091
20699
18200
10315
21
7420
24449
44512
0
0
0
0
0
0
0
0
421422
LOT
all
<8500
3451246
5191624
4864593
4207136
3473623
3472007
3237031
3763014
3704595
3250090
3318897
2720715
2264530
1366998
1075393
945991
807475
1368487
1151869
916203
692725
417326
510573
0
0
0
0
0
0
0
0
56172139
HDGV
all
>8500
337478
538338
452446
320424
286251
225630
284983
332779
316453
250420
285120
276536
243986
167358
129809
121864
158960
362147
321650
263721
165629
150707
138308
93372
72328
54597
57955
50761
39588
38887
34371
6572857
HDGB
all
any
516
4408
2956
2727
210
2451
4064
4458
6193
7064
8296
11037
11397
10954
9281
12057
10443
9303
8461
9548
6917
8718
1
0
0
0
0
0
0
0
0
151460
HDDV
3 to 5
10001-19500
35695
95514
76282
63637
52681
42469
59398
53542
36157
24768
28150
12802
7640
4460
2308
267
2
0
1
2
272
111
40
147
118
60
38
116
95
94
75
596942
HDDV
8
>33000
86256
210440
156833
134648
97282
96087
111961
128653
115520
104358
87306
99962
82591
40096
47194
56154
44139
64371
50883
38403
19095
26125
14369
12504
8095
5778
4177
2054
1260
1132
575
1948301
HDDV
all
>8501
236558
581588
434799
395882
298324
280820
324127
312783
270929
243963
261075
255220
224864
124269
114457
97416
71247
88155
65775
46343
23825
30770
18149
16149
10814
7744
8663
4789
3362
1547
911
4855315
HDDB
all
any
12592
34395
18274
22395
22974
28108
33380
18836
21769
22838
20427
15484
10326
9234
7505
7594
4470
2143
1435
995
570
759
338
393
247
211
73
106
78
90
189
318228
LDV Light duty vehicle
LDGV Light duty gasoline vehicle
LDDV Light duty diesel vehicle
LDGT Light duty gasoline truck
LDDT Light duty diesel truck
HDGV Heavy duty gasoline vehicle
HDGB Heavy duty gasoline bus
HDDV Heavy duty diesel vehicle
HDDB Heavy duty diesel bus
Table 4-8. Vehicles in Operation as Percent of Class as of July 1996
4-38
-------
Aggregated Classes, U.S. Levels
Model
Year
96
95
94
93
92
91
90
89
88
87
86
85
84
83
82
81
80
79
78
77
76
75
74
73
72
71
70
69
68
67
66
TOTAL
LDV
all
5.00%
7.63%
6.63%
6.68%
6.22%
6.45%
6.60%
7.23%
7.32%
7.01%
6.75%
5.96%
5.06%
3.27%
2.38%
2.06%
1.69%
1.91%
1.50%
1.12%
0.70%
0.40%
0.45%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
100%
LDGT
all
<8500
6.17%
9.28%
8.70%
7.52%
6.22%
6.21%
5.79%
6.74%
6.64%
5.82%
5.92%
4.85%
4.01%
2.40%
1.82%
1 .62%
1.41%
2.42%
2.05%
1 .64%
1 .23%
0.70%
0.84%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
100%
LDDT
all
<8500
2.92%
3.99%
3.24%
2.99%
2.07%
1.78%
1 .65%
1 .65%
1 .27%
1.59%
4.15%
4.46%
7.10%
7.09%
14.05%
10.23%
4.91%
4.32%
2.45%
0.01%
1.76%
5.80%
10.56%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
100%
LOT
all
<8500
6.14%
9.24%
8.66%
7.49%
6.18%
6.18%
5.76%
6.70%
6.60%
5.79%
5.91%
4.84%
4.03%
2.43%
1.91%
1 .68%
1 .44%
2.44%
2.05%
1 .63%
1 .23%
0.74%
0.91%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
100%
HDGV
all
>8500
5.13%
8.19%
6.88%
4.87%
4.36%
3.43%
4.34%
5.06%
4.81%
3.81%
4.34%
4.21%
3.71%
2.55%
1.97%
1.85%
2.42%
5.51%
4.89%
4.01%
2.52%
2.29%
2.10%
1 .42%
1.10%
0.83%
0.88%
0.77%
0.60%
0.59%
0.52%
100%
HDGB
all
any
0.34%
2.91%
1.95%
1.80%
0.14%
1.62%
2.68%
2.94%
4.09%
4.66%
5.48%
7.29%
7.52%
7.23%
6.13%
7.96%
6.89%
6.14%
5.59%
6.30%
4.57%
5.76%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
100%
HDDV
3 to 5
10001-19500
5.98%
16.00%
12.78%
10.66%
8.83%
7.11%
9.95%
8.97%
6.06%
4.15%
4.72%
2.14%
1.28%
0.75%
0.39%
0.04%
0.00%
0.00%
0.00%
0.00%
0.05%
0.02%
0.01%
0.02%
0.02%
0.01%
0.01%
0.02%
0.02%
0.02%
0.01%
100%
HDDV
8
>33000
4.43%
10.80%
8.05%
6.91%
4.99%
4.93%
5.75%
6.60%
5.93%
5.36%
4.48%
5.13%
4.24%
2.06%
2.42%
2.88%
2.27%
3.30%
2.61%
1.97%
0.98%
1.34%
0.74%
0.64%
0.42%
0.30%
0.21%
0.11%
0.06%
0.06%
0.03%
100%
HDDV
all
>8501
4.87%
11.98%
8.96%
8.15%
6.14%
5.78%
6.68%
6.44%
5.58%
5.02%
5.38%
5.26%
4.63%
2.56%
2.36%
2.01%
1.47%
1.82%
1.35%
0.95%
0.49%
0.63%
0.37%
0.33%
0.22%
0.16%
0.18%
0.10%
0.07%
0.03%
0.02%
100%
HDDB
all
any
3.96%
10.81%
5.74%
7.04%
7.22%
8.83%
10.49%
5.92%
6.84%
7.18%
6.42%
4.87%
3.24%
2.90%
2.36%
2.39%
1 .40%
0.67%
0.45%
0.31%
0.18%
0.24%
0.11%
0.12%
0.08%
0.07%
0.02%
0.03%
0.02%
0.03%
0.06%
100%
LDV Light duty vehicle
LDGV Light duty gasoline vehicle
LDDV Light duty diesel vehicle
LDGT Light duty gasoline truck
LDDT Light duty diesel truck
HDGV Heavy duty gasoline vehicle
HDGB Heavy duty gasoline bus
HDDV Heavy duty diesel vehicle
HDDB Heavy duty diesel bus
4-39
-------
Table 4-9. Gasoline/Diesel Sales Faction*
Model
Year
96
95
94
93
92
91
90
89
88
87
86
85
LDV
LDGV
99.91%
99.94%
99.99%
99.97%
99.94%
99.87%
99.96%
99.96%
99.99%
99.73%
99.68%
99.03%
LDDV
0.09%
0.06%
0.01%
0.03%
0.06%
0.13%
0.04%
0.04%
0.01%
0.27%
0.32%
0.97%
LOT
LDGT
99.64%
99.68%
99.72%
99.70%
99.75%
99.78%
99.79%
99.82%
99.86%
99.79%
99.47%
99.31%
LDDT
0.36%
0.32%
0.28%
0.30%
0.25%
0.22%
0.21%
0.18%
0.14%
0.21%
0.53%
0.69%
* Assumes that scrappage rates are equivalent for diesel and gasoline vehicles
4-40
-------
APPENDIX A
A-l
-------
BUSES.PRG
* Determines total registrations and average annual mileage for transit buses
* using the FTA database
*
set talk off
use BUSDATA alias DATA
select 2
use BUSOUT alias OUT
index on FUEL+str(MY,4) to BUS
set index to BUS
select DATA
do while .not. eof()
select OUT
seek DATA->FUELTYPE+str(DATA->MY,4)
if .not. foundO
append blank
replace FUEL with DATA->FUELTYPE
replace MY with DATA->MY
end if
replace TOTALREGS with TOTALREGS + DATA->NUMVEH
replace AMREG with AMREG + DATA->NUMACTVEH
replace AMTOT with AMTOT + DATA->ANNMILES*1000
select DATA
skip
enddo
select OUT
go top
do while .not. eof()
if AMREG > 0
replace ACTMIL with AMTOT/AMREG
end if
if TOTALREGS > 0
replace AVEMIL with AMTOT/TOTALREGS
end if
skip
enddo
select 2
use
select 1
use
A-2
-------
TIUSCONV.C
/* TIUSCONV
Converts the TIUS dataset TI92MDF.DAT to a comma delimited file for
importing into dBASE file TIUSDAT
*/
#include
ttinclude
ttdefine comma 44
char buffer [625];
char bufout[70];
FILE *fin,*fout;
int count;
int idex,odex;
void main()
{
fin = fopen("E:TI92MDF.DAT","rb");
fout = fopen("C:TIRED.DAT","wb");
while (fgets(buffer,625,fin)) {
odex = 0;
idex = 14;
/* EXPANF 15-21 */
for (count=l; count <=7; count++) {
bufout[odex] = buffer[idex];
odex++;
idex++;
}
bufout[odex] = comma;
odex++;
idex = 23;
/* MDLYR 24-25 */
for (count=l; count <=2; count++) {
bufout[odex] = buffer[idex];
odex++;
idex++;
}
bufout[odex] = comma;
odex++;
/* ACQMON 26-27 */
for (count=l; count <=2; count++) {
bufout[odex] = buffer[idex];
odex++;
idex++;
}
bufout[odex] = comma;
odex++;
/* ACQYR 28-29 */
for (count=l; count <=2; count++) {
bufout[odex] = buffer[idex];
odex++;
idex++;
}
bufout[odex] = comma;
odex++;
/* OBTAIN 30 */
bufout[odex] = buffer[idex];
idex++;
odex++;
bufout[odex] = comma;
odex++;
/* DISPOZ 42 */
idex = 41;
A-3
-------
TIUSCONV.C
bufouttodex] = buffer[idex];
idex++;
odex++;
bufouttodex] = comma;
odex++;
/* DISMON 43-44 */
for (count=l; count <=2; count++) {
bufout[odex] = buffer[idex];
odex++;
idex++;
}
bufouttodex] = comma;
odex++;
/* DISYR 45-46 */
for (count=l; count <=2; count++) {
bufout[odex] = buffer[idex];
odex++;
idex++;
}
bufouttodex] = comma;
odex++;
/* HOWRID 47 */
bufouttodex] = buffer[idex];
odex++;
bufouttodex] = comma;
odex++;
/* BODTYP 58-59 */
idex = 57;
for (count=l; count <=2; count++) {
bufout[odex] = buffer[idex];
odex++;
idex++;
}
bufouttodex] = comma;
odex++;
/* MAXWT 105-110 */
idex = 104;
for (count=l; count <=6; count++) {
bufout[odex] = buffer[idex];
odex++;
idex++;
}
bufouttodex] = comma;
odex++;
/* EngTyp 112 */
idex = 111;
bufouttodex] = buffer[idex];
odex++;
bufouttodex] = comma;
odex++;
/* ANNMIL 155-160 */
idex = 154;
for (count=l; count <=6; count++) {
bufout[odex] = buffer[idex];
odex++;
idex++;
}
bufouttodex] = comma;
odex++;
/* TIUGVW 421-422 */
idex = 420;
for (count=l; count <=2; count++) {
A-4
-------
TIUSCONV.C
bufout[odex] = buffer[idex];
odex++;
idex++;
}
bufout[odex] = comma;
odex++;
/* PKGVW 423 */
bufout[odex] = buffer[idex];
odex++;
idex++;
bufout[odex] = comma;
odex++;
/* PKRWGT 424-429 */
for (count=l; count <=6; count++) {
bufout[odex] = buffer[idex];
odex++;
idex++;
}
bufout[odex] = comma;
odex++;
/* VehSze 430 */
bufout[odex] = buffer[idex] ;
odex++;
bufout[odex] = '\n';
odex++;
bufout[odex] = '\0';
fputs(bufout,fout);
}
fclose(fin);
fclose(fout);
puts("\nfile written");
A-5
-------
TIUS.PRG
* Determines average annual mileage accumulation rates for trucks using TIUSDAT
* created from the 1992 TIUS data set using TIUSCONV.C
*
set talk off
use TIUSDAT alias Data
select 2
use TIUSRES alias Res
ZAP
select Data
go top
V = Vehtype
MDY = 93 - Mdlyr
F = Fueltype
Recs = 0
Store 0.00 to Recs,Regs,MRec,AMARec,MTotRecs
do while .not. eof()
M = 93 - MDLYR
if M <> MDY .or. Fueltype <> F .or. Vehtype <> V
select Res
append blank
replace VEHTYPE with V
replace MY with MDY
replace Fueltype with F
replace TotalRecs with Recs
replace TotalRegs with Regs
replace MiRecs with MRec
replace Annmiles with AMARec*12/MtotRecs
select Data
V = Vehtype
MDY = M
F = Fueltype
Recs = 0
Store 0.00 to Recs,Regs,MRec,AMARec,MTotRecs
endif
Regs = Regs + Data->EXPANF
Recs = Recs + 1
if Data->ANNMIL <> SPACE(6)
MI = val(Data->ANNMIL)
MRec = MRec + 1
AMARec = AMARec + MI
if Data->ACQYR = 92 .AND. Data->ACQMON > 0;
.and. Data->ACQMON <= 12
MTotRecs = MTotRecs + 12.5-Data->ACQMON
else
if Data->DISYR = 92 .and. Data->DISMON > 0;
.and. Data->DISMON <= 12
MTotRecs = MTotRecs + Data->DISMON-0.5
else
MTotRecs = MTotRecs + 12
endif
endif
endif
select Data
skip
A-6
-------
TIUS.PRG
enddo
select Res
append blank
replace VEHTYPE with V
replace MY with MDY
replace Fueltype with F
replace TotalRecs with Recs
replace TotalRegs with Regs
replace MiRecs with MRec
replace Annmiles with AMARec*12/MtotRecs
Go Top
Select Data
Go Top
store 0.00 to N,var
Do While .not. eof()
M = 93 - MDLYR
if M <> Res->MY .or. Fueltype <> Res->FuelType .or. Vehtype <> Res->Vehtype
select Res
if N > 0.00
replace STDEV_ANMI with SQRT(Var/N)
endif
skip
select Data
endif
if Data->ANNMIL <> SPACE(6)
MI = val(Data->ANNMIL)
n = N + 1
if Data->ACQYR = 92 .AND. Data->ACQMON > 0;
.and. Data->ACQMON <= 12
Mons = 12.5-Data->ACQMON
else
if Data->DISYR = 92 .and. Data->DISMON > 0;
.and. Data->DISMON <= 12
Mons = Data->DISMON-0.5
else
Mons =12
endif
endif
Diff = MI*12/Mons - Res->AnnMiles
Var = Var + Diff*Diff
endif
skip
enddo
select Res
if N > 0.00
replace STDEV_ANMI with SQRT(Var/N)
endif
A-7
-------
Figure A-1. Segregated Light-Duty Truck Types
Annual Miles by Age for LDGT1
30,000
Aggregated Light-Duty Trucks
Mnivans
Other Light-Duty Trucks
Pick-Ups
Sport Utility Vehicles
HIII|IIII|IIII|IIII|IIII|IIIh
10
15
Age
20
25
30
A-8
-------
LDVS.PRG
* Calculates average annual mileage accumulation rates from the
* 1995 NPTS dataset VEHICL95
*
set talk off
use VEHICL95 alias LDVS
select 2
use NPTS alias ANS
ZAP
select LDVS
VC = VehClass
MY = VehYear
Store 0.0 to Regs,Recs,Reco,TotSE,SERegs,TotOD,ODRegs
do while .not. eof()
if VehClass <> VC .or. VehYear <> MY
select ANS
append blank
replace VehClass with VC
replace VehYear with MY
replace RECSE with Recs
replace RECOD with Reco
replace REGISTR with Regs
If SERegs > 0.00
replace AnnMiles with TotSE/SERegs
endif
if ODRegs > 0
replace ANNUALZD with TotOD/ODRegs
endif
select LDVs
VC = VehClass
MY = VehYear
Store 0.0 to Regs,Recs,Reco,TotSE,SERegs,TotOD,ODRegs,ODSE
endif
Regs = Regs + WTHHFIN
if ANNMILES > 0 .and. ANNMILES <= 115000
TotSE = TotSE + ANNMILES*WTHHFIN
SERegs = SERegs + WTHHFIN
Recs = Recs + 1
endif
if ANNUALZD > 0 .and. ANNUALZD <= 513292 .and. FLAGODO = "94" .and. FLAGOUT =
11 94 "
TotOD = TotOD + ANNUALZD*WTHHFIN
ODRegs = ODRegs + WTHHFIN
Reco = Reco + 1
endif
skip
enddo
select ANS
append blank
replace VehClass with VC
replace VehYear with MY
replace RECSE with Recs
replace RECOD with Reco
replace REGISTR with Regs
If SERegs > 0.00
A-9
-------
LDVS.PRG
replace AnnMiles with TotSE/SERegs
end if
if ODRegs > 0
replace ANNUALZD with TotOD/ODRegs
endif
select LDVS
go top
Select ANS
go top
Select LDVs
store 0.00 to SEREGs,ODOREGs,SEVAR,ODOVAR
do while .not. eof()
if VehClass <> ANS->VehClass .or. VehYear <> ANS->VehYear
Select ANS
If SERegs > 0.00
replace STDEV_SE with SQRT(SEVAR/SEREGs)
endif
If ODORegs > 0.00
replace STDEVJDDO with SQRT(ODOVAR/ODOREGs)
endif
store 0.00 to SEREGs,ODOREGs,SEVAR,ODOVAR
skip
Select LDVs
endif
if ANNMILES > 0 .and. ANNMILES <= 115000
SEVar = SEVar + (ANNMILES-ANS->ANNMILES)*(ANNMILES-ANS->ANNMILES)*WTHHFIN
SERegs = SERegs + WTHHFIN
endif
if ANNUALZD > 0 .and. ANNUALZD <= 513292 .and. FLAGODO = "94" .and. FLAGOUT =
.. 94..
ODOVar = ODOVar + (ANNUALZD-ANS->ANNUALZD)*(ANNUALZD-ANS->ANNUALZD)*WTHHFIN
ODORegs = ODORegs + WTHHFIN
endif
skip
enddo
Select ANS
If SERegs > 0.00
replace STDEV_SE with SQRT(SEVAR/SEREGs)
endif
If ODORegs > 0.00
replace STDEVJDDO with SQRT(ODOVAR/ODOREGs)
endif
A-10
------- |