United States

Environmental Protection

Agency

Air and Radiation EPA420-P-98-016

June 1998

Update of Fleet

Characterization Data for

Use In MOBILE6 - Final

Report

 Printed on Recycled Paper

Office of Mobile Sources
11 May 1998

P R E P A R E D F O R

U.S. Environmental Protection

Agency

Motor Vehicle Emissions Laboratory

2565 Plymouth Road

Ann Arbor, Michigan 48105

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

Update of Fleet

Characterization Data for

Use in MOBILE6

Final Report
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.
1-1

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 (MOBILE5a) 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 MOBILE5a model. The results of this study may be used in MOBILE6,

currently under development. ARCADIS 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, ARCADIS 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.
1-2

Table 1-1. Vehicle Types

Designation Description

Gross Vehicle

Weight (lb)

LDGV Light-duty gasoline vehicles 0 - 6,000

LDDV Light-duty diesel vehicles 0 - 6,000

LDGT1 Light-duty gasoline trucks <6,000

LDGT2 Light-duty gasoline trucks 6,001-8,500

LDDT1 Light-duty diesel trucks <6,000

LDDT2 Light-duty diesel trucks 6,001-8,500

HDGV (classes 2B-3) Heavy-duty gasoline vehicles 8,501-14,000

HDGV (classes 4-8) Heavy-duty gasoline vehicles >14,000

HDDV (class 2B) Light heavy-duty diesel trucks 8,501-10,000

HDDV (class 3) Light heavy-duty diesel trucks 10,001-14,000

HDDV (classes 4-5) Light heavy-duty diesel trucks 14,001-19,500

HDDV (classes 6-7) Medium heavy-duty diesel trucks 19,501-33,000

HDDV (class 8A) Heavy heavy-duty diesel trucks 33,001-60,000

HDDV (class 8B) Heavy heavy-duty diesel trucks >60,000

HDGB (school) Heavy-duty gasoline school buses all

HDGB (transit) Heavy-duty gasoline transit buses all

HDDB (school) Heavy-duty diesel school buses all

HDDB (transit) Heavy-duty diesel transit buses all
2-1

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 vehicles age with the miles it drove.

Further, to define a vehicles 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.
2-2

1995 Motor Vehicles Facts & Figures (American Automobile Manufacturers Association)

The 1995 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 ARCADIS 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). ARCADIS 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.
2-3

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 this publication mainly to verify the registration 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

Vehicle Registrations

Annual Mileage

Accumulation

Source Base Year Source Base Year

Light Duty Vehicle Polk 1996 NPTS 1995

Light & Heavy Duty Truck Polk 1996 TIUS 1992

School Buses Polk 1996 Bobit 1996

Transit Buses FTA 1994 FTA 1994
2-4

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 lightduty 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. ARCADIS 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, ARCADIS 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 ARCADIS 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

subjects personal background and vehicle characteristics was recorded during the study. Of relevance

to the ARCADIS 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, ARCADIS Geraghty & Miller received the NPTS data

on CD-ROM.
2-5

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.
3-1

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 8A. 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 EPAs treatment and use of attrition information in MOBILE5a and

earlier versions of the model). The same attrition rate calculated for all heavy trucks of each model year
3-2

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 Polk-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 lbs. USEPA defines light-duty class 2

trucks as having GVWRs of 6,001 to 8,500 lbs and heavy-duty class 2B trucks as having GVWRs of

8,501 to 10,000 lbs. As a result, data reported by Polk for LDDT2 include data for both USEPA

LDDT2 and HDDV(2B). Thus a methodology to split the Polk-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 lbs actually have GVWRs of 6,001-8,500 lbs. 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 Polk-reported registered trucks weighing

6,001-10,000 lbs actually weighed 6,001-8,500 lbs. 

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 lbs GVWR. Therefore, the excess 90% of the Polkreported 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. 
3-3

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 MOBILE5a, 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 dBASE 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 Description

NUMVEH Number of buses in fleet

TYPE Bus type code

MY Bus Model Year

NUMACTVEH Number of active buses in fleet

FUELTYPE Bus fuel type

SEATING Seating capacity of the bus

ANNMILES 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 Bus Type

AB Articulated motor bus

BA Motor bus with > 35 seats

BB Motor bus with 25-35 seats

BC Motor bus with < 25 seats

DB 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
3-4

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 recoded 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.
3-5

Table 3-3. TIUSDAT.DBF Data Structure

Field Name Description

EXPANF Expansion factor

MDLYR Model year

ACQMON Acquired month

ACQYR Acquired year

OBTAIN How was vehicle obtained?

DISPOZ Was the vehicle disposed of?

DISMON Month the vehicle was disposed

DISYR Year the vehicle was disposed

HOWRID How was the vehicle disposed?

BODTYP Vehicle body type

MAXWT Maximum gross weight 

ENGTYP Fuel type

ANNMIL Annual mileage during 1992

TIUGVW TIUS gross vehicle weight class

PKGVW Polk gross vehicle weight class

PKRWGT Polk registered weight

VEHSZE Vehicle size

Table 3-4. Additional Fields in TIUSDAT.DBF

Field Name Description

VEHTYPE Vehicle class description

FUELTYPE 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 VIN. Prior to 1983, VIN

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

parameters 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
3-6

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 (TIUS11.DBF) with the same

structure as TIUSDAT.DBF. In those cases, model year was assumed to be the same as acquired year
3-7

(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 lbs 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 LDGT1

(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 selfreported 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
3-8

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 Self-reported annualized mileage

MODLCODE Model code

VEHTYPE Type of Vehicle

VEHYEAR Model Year of vehicle

WTHHFIN Registrations per record

ANNUALZD Odometer based annualized mileage

FLAGODO Flag identifying missing ANNUALZD values

FLAGOUT 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 Model Codes

Passenger car (CAR) 1 - 47, 398, 399

Sports utility vehicle (SUV) 401, 402, 403, 404, 421

Minivan (MV) 441, 442, 443

Pick-up truck (PU) 471, 472

Other light truck (OTH) 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
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

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.PRG to calculate mileage accumulation is listed in Appendix A. Results

from these calculations are given in Section 4.
4-1

SECTION 4

RESULTS

Work Assignment Task 6 specifies that the results of this study be compared to the previous

data derived during development of MOBILE5a. 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 MOBILE5a. 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.
4-2

Table 4-1. Total VMT, Registrations, and Annual Mileage

 TOTAL VMT 

 US Highway Statistics 96 Current Study % Difference

 LDVs and LDTs 2,283,005,000,000 1,894,165,618,859 -17.03%

 HDVs 182,756,000,000 230,289,095,076 26.01%

 Buses 6,535,000,000 5,804,509,986 -11.18%

 Total 2,472,296,000,000 2,130,259,223,921 -13.83%

 REGISTRATIONS 

 US Highway Statistics 96 Current Study % Difference

 LDVs and LDTs 198,662,139 176,385,176 -11.21%

 HDVs 7,006,408 11,428,172 63.11%

 Buses 696,609 469,689 -32.58%

 Total 206,365,156 188,283,036 -8.76%

 ANNUAL MILEAGE 

 US Highway Statistics 96 Current Study % Difference

 LDVs and LDTs 

11,492 

 10,739 -6.55%

 HDVs 

26,084 

 20,151 -22.75%

 Buses 9,381 12,358 31.73%

 Average 11,980 11,314 -5.56%

Comparison of these two figures indicates that the current study projects 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.
4-3

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 lbs and heavy-duty trucks as having a GVWR greater than 10,000 lbs. In accordance with

USEPA definitions, ARCADIS Geraghty & Miller defined light-duty trucks to include GVWRs only

up to 8,500 lbs and heavy-duty trucks as having GVWRs greater than 8,500 lbs.

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 School Bus Fleet Fact Book and transit bus registrations from FTA used

in the current study tracked very closely with information from the APTA 1995 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 lbs) which have higher mileage accumlation rates than LDVs but

lower than heavy-duty trucks. Since Class 2B vehicles account for approximately 50% of the heavyduty 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 1996 Highway Statistics shown in Table 4-1. MOBILE5a data indicates slightly higher counts

than Polk, however, MOBILE5a 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 MOBILE5a data
4-4

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 MOBILE5a, 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, MOBILE5a 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 FTA (Figure 4-17) very closely follows the comparison APTA 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 and LDGT2, 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

HDDVs(4-5), HDDVs(8) (Figure 4-24) which includes HDDV(8A) and HDDV(8B), HDDVs (Figure

4-25) which includes HDDV(2B), HDDV(3), HDDV(4-5), HDDV(6-7), HDDV(8A) 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 charts

title. Of particular note is the comparison between data sources of LDDTs (Figure 4-19). As

mentioned above, MOBILE5a did not discriminate between LDDT1s and LDDT2s. For all LDDTs,

MOBILE5a 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 MOBILE5a, 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.
4-5

4.2.2 LDTs

Light-duty truck mileage provided by the TIUS fairly closely tracks MOBILE5a 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 MOBILE5a 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 1997 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

MOBILE5a 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 MOBILE5a curve is the same for both Figures

4-37 and 4-38. This is because, in MOBILE5a, 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 MOBILE5a 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 MOBILE5a values.

Classes 8A and 8B (Figures 4-40 and 4-41) mileage rates developed in this study are slightly

lower and higher, respectively, than MOBILE5a. This is due partly to the same reason as explained

for Classes 4 and 5. MOBILE5a 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.)
4-6

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.
4-7

Figure 4-1. Registration Comparison by Model Year

LDV

0

2,000,000

4,000,000

6,000,000

8,000,000

10,000,000

12,000,000

66687072747678808284868890929496

Model Year

Registrations

1995 NPTS 

1996 Polk 

1992 MOBILE5a 

Figure 4-2. Registration Comparison by Model Year

LDGT1

0

500,000

1,000,000

1,500,000

2,000,000

2,500,000

3,000,000

3,500,000

4,000,000

66687072747678808284868890929496

Model Year

Registrations

1996 Polk

1992 MOBILE5a
4-8

Figure 4-3. Registration Comparison by Model Year

LDGT2

0

200,000

400,000

600,000

800,000

1,000,000

1,200,000

1,400,000

1,600,000

66687072747678808284868890929496

Model Year

Registrations

1996 Polk

1992 MOBILE5a

Figure 4-4. Registration Comparison by Model Year

LDDT1

0

10,000

20,000

30,000

40,000

50,000

60,000

66687072747678808284868890929496

Model Year

Registrations

1996 Polk
4-9

Figure 4-5. Registration Comparison by Model Year

LDDT2

0

2,000

4,000

6,000

8,000

10,000

12,000

14,000

16,000

18,000

66687072747678808284868890929496

Model Year

Registrations

1996 Polk

Figure 4-6. Registrations by Model Year

HDGV(2B-3)

0

100,000

200,000

300,000

400,000

500,000

600,000

66687072747678808284868890929496

Model Year

Registrations

1996 Polk
4-10

Figure 4-7. Registrations by Model Year

HDGV(4-8)

0

10,000

20,000

30,000

40,000

50,000

60,000

70,000

80,000

90,000

100,000

66687072747678808284868890929496

Model Year

Registrations

1996 Polk

Figure 4-8. Registrations by Model Year

HDGB School

0

2,000

4,000

6,000

8,000

10,000

12,000

14,000

66687072747678808284868890929496

Model Year

Registrations

1996 Polk
4-11

Figure 4-9. Registrations by Model Year

HDGB Transit

0

20

40

60

80

100

120

140

66687072747678808284868890929496

Model Year

Registrations

FTA

Figure 4-10. Registrations by Model Year

HDDV(2B)

0

20,000

40,000

60,000

80,000

100,000

120,000

140,000

160,000

180,000

66687072747678808284868890929496

Model Year

Registrations

1996 Polk
4-12

Figure 4-11. Registrations by Model Year

HDDV(3)

0

10,000

20,000

30,000

40,000

50,000

60,000

66687072747678808284868890929496

Model Year

Registrations

1996 Polk

Figure 4-12. Registrations by Model Year

HDDV(4-5)

0

5,000

10,000

15,000

20,000

25,000

30,000

35,000

40,000

45,000

50,000

66687072747678808284868890929496

Model Year

Registrations

1996 Polk
4-13

Figure 4-13. Registrations by Model Year

HDDV(6-7)

0

20,000

40,000

60,000

80,000

100,000

120,000

66687072747678808284868890929496

Model Year

Registrations

1996 Polk

Figure 4-14. Registrations by Model Year

HDDV(8A)

0

10,000

20,000

30,000

40,000

50,000

60,000

66687072747678808284868890929496

Model Year

Registrations

1996 Polk
4-14

Figure 4-15. Registrations by Model Year

HDDV(8B)

0

20,000

40,000

60,000

80,000

100,000

120,000

140,000

160,000

180,000

66687072747678808284868890929496

Model Year

Registrations

1996 Polk

Figure 4-16. Registrations by Model Year

HDDB School

0

5,000

10,000

15,000

20,000

25,000

30,000

35,000

40,000

66687072747678808284868890929496

Model Year

Registrations

1996 Polk
4-15

Figure 4-17. Registrations by Model Year

HDDB Transit

0

500

1,000

1,500

2,000

2,500

3,000

3,500

4,000

4,500

5,000

66687072747678808284868890929496

Model Year

Registrations

1994 FTA

1994 APTA

Figure 4-18. Registrations by Model Year

Aggregated LDGT

0

1,000,000

2,000,000

3,000,000

4,000,000

5,000,000

6,000,000

66687072747678808284868890929496

Model Year

Registrations

1996 Polk
4-16

Figure 4-19. Registrations by Model Year

Aggregated LDDT

0

20,000

40,000

60,000

80,000

100,000

120,000

140,000

160,000

180,000

66687072747678808284868890929496

Model Year

Registrations

1996 Polk

1992 MOBILE5a

Figure 4-20. Registrations by Model Year

Aggregated LDT

0

1,000,000

2,000,000

3,000,000

4,000,000

5,000,000

6,000,000

66687072747678808284868890929496

Model Year

Registrations

1996 Polk
4-17

Figure 4-21. Registrations by Model Year

Aggregated HDGV

0

100,000

200,000

300,000

400,000

500,000

600,000

66687072747678808284868890929496

Model Year

Registrations

1996 Polk

Figure 4-22. Registrations by Model Year

Aggregated HDGB

0

2,000

4,000

6,000

8,000

10,000

12,000

14,000

66687072747678808284868890929496

Model Year

Registrations

1996 Polk & 1994 FTA
4-18

Figure 4-23. Registrations by Model Year

Aggregated HDDV(3-5)

0

20,000

40,000

60,000

80,000

100,000

120,000

66687072747678808284868890929496

Model Year

Registrations

1996 Polk

Figure 4-24. Registrations by Model Year

Aggregated HDDV(8)

0

50,000

100,000

150,000

200,000

250,000

66687072747678808284868890929496

Model Year

Registrations

1996 Polk
4-19

Figure 4-25. Registrations by Model Year

Aggregated HDDV All

0

100,000

200,000

300,000

400,000

500,000

600,000

700,000

66687072747678808284868890929496

Model Year

Registrations

1996 Polk

Figure 4-26. Registrations by Model Year

Aggregated HDDB

0

5,000

10,000

15,000

20,000

25,000

30,000

35,000

40,000

66687072747678808284868890929496

Model Year

Registrations

1996 Polk & 1994 FTA
4-20

Figure 4-27. Annual Miles by Age

LDV

y = 15684e-0.0506x

0

2,000

4,000

6,000

8,000

10,000

12,000

14,000

16,000

18,000

20,000

0 5 10 15 20 25 30 35

Age

Annual Miles

1995 NPTS

MOBILE5a (LDGV only)

MOBILE5a (LDDV only)

Expon. (1995 NPTS)

Figure 4-28. Annual Miles by Age

LDGT1

y = 17.472x2

 - 1163.7x + 20642

0

5,000

10,000

15,000

20,000

25,000

0 5 10 15 20 25 30 35

Age

Annual Miles

1992 TIUS

MOBILE5a

Poly. (1992 TIUS)
4-21

Figure 4-29. Annual Miles by Age

LDGT2

y = 22905e-0.0712x

0

5,000

10,000

15,000

20,000

25,000

0 5 10 15 20 25 30 35

Age

Annual Miles

1992 TIUS

MOBILE5a

Expon. (1992 TIUS)

Figure 4-30. Annual Miles by Age

LDDT1

y = 30028e-0.1041x

0

5,000

10,000

15,000

20,000

25,000

30,000

0 5 10 15 20 25 30 35

Age

Annual Miles

1992 TIUS

MOBILE5a (all LDDT)

Expon. (1992 TIUS)
4-22

Figure 4-31. Annual Miles by Age

LDDT2

y = 28231e-0.0808x

0

5,000

10,000

15,000

20,000

25,000

30,000

0 5 10 15 20 25 30 35

Age

Annual Miles

1992 TIUS

MOBILE5a (all LDDT)

Expon. (1992 TIUS)

Figure 4-32. Annual Miles by Age

HDGV(2B-3)

y = 21250e-0.0618x

0

5,000

10,000

15,000

20,000

25,000

0 5 10 15 20 25 30 35

Age

Annual Miles

1992 TIUS

MOBILE5a (all HDGV)

Expon. (1992 TIUS)
4-23

Figure 4-33. Annual Miles by Age

HDGV(4-8)

y = 23243e-0.0829x

0

5,000

10,000

15,000

20,000

25,000

0 5 10 15 20 25 30 35

Age

Annual Miles

1992 TIUS

MOBILE5a (all HDGV)

Expon. (1992 TIUS)

Figure 4-34. Annual Miles by Age

HDGB School

0

2,000

4,000

6,000

8,000

10,000

12,000

14,000

0 5 10 15 20 25 30 35

Age

Annual Miles

1997 School Bus Fleet Fact Book

Average annual mileage for

all model years is 9,939
4-24

Figure 4-35. Annual Miles by Age

HDGB Transit

y = 38654e-0.0958x

0

5,000

10,000

15,000

20,000

25,000

30,000

35,000

40,000

0 5 10 15 20 25 30 35

Age

Annual Miles

1994 FTA

Expon. (1994 FTA)

Figure 4-36. Annual Miles by Age

HDDV(2B)

y = 29657e-0.0888x

0

5,000

10,000

15,000

20,000

25,000

30,000

0 5 10 15 20 25 30 35

Age

Annual Miles

1992 TIUS

MOBILE5a

Expon. (1992 TIUS)
4-25

Figure 4-37. Annual Miles by Age

HDDV(3)

y = 37008e-0.1222x

0

5,000

10,000

15,000

20,000

25,000

30,000

35,000

0 5 10 15 20 25 30 35

Age

Annual Miles

1992 TIUS

MOBILE5a

Expon. (1992 TIUS)

Figure 4-38. Annual Miles by Age

HDDV(4-5)

y = 32635e-0.0656x

0

5,000

10,000

15,000

20,000

25,000

30,000

35,000

0 5 10 15 20 25 30 35

Age

Annual Miles

1992 TIUS

MOBILE5a

Expon. (1992 TIUS)
4-26

Figure 4-39. Annual Miles by Age

HDDV(6-7)

y = 44883e-0.0983x

0

5,000

10,000

15,000

20,000

25,000

30,000

35,000

40,000

45,000

0 5 10 15 20 25 30 35

Age

Annual Miles

1992 TIUS

MOBILE5a

Expon. (1992 TIUS)

Figure 4-40. Annual Miles by Age

HDDV(8A)

y = 98554e-0.1153x

0

10,000

20,000

30,000

40,000

50,000

60,000

70,000

80,000

90,000

100,000

0 5 10 15 20 25 30 35

Age

Annual Miles

1992 TIUS

MOBILE5a (All Class 8)

Expon. (1992 TIUS)
4-27

Figure 4-41. Annual Miles by Age

HDDV(8B)

y = 137024e-0.0982x

0

20,000

40,000

60,000

80,000

100,000

120,000

140,000

0 5 10 15 20 25 30 35

Age

Annual Miles

1992 TIUS

MOBILE5a (All Class 8)

Expon. (1992 TIUS)

Figure 4-42. Annual Miles by Age

HDDB School

0

2,000

4,000

6,000

8,000

10,000

12,000

14,000

0 5 10 15 20 25 30 35

Age

Annual Miles

1997 School Bus Fleet Fact Book

Average annual mileage for

all model years is 9,939
4-28

Figure 4-43. Annual Miles by Age

HDDB Transit

y = 46659e-0.0324x

0

5,000

10,000

15,000

20,000

25,000

30,000

35,000

40,000

45,000

50,000

0 5 10 15 20 25 30 35

Age

Annual Miles

1994 FTA

Expon. (1994 FTA)
4-29

Table 4-2. Vehicles in Operation as of July 1996

U.S. Levels

LDV LDGT LDDT HDGV HDGB

Model LDGV LDDV LDGT1 LDGT2 LDDT1 LDDT2 2B-3 4-8 S.BUS T.BUS

Year <6000 6001-8500 <6000 6001-8500 8501-14000 >14000 ANY WGT. ANY WGT.

96 5999331 5330 2475332 963616 0 12298 321205 16273 516 0

95 9166694 5425 3723979 1450819 0 16827 483606 54732 4408 0

94 7966182 630 3636380 1214578 1 13634 404859 47587 2926 30

93 8027524 2715 3338741 855812 0 12582 285271 35154 2673 54

92 7468105 4432 2716821 748099 0 8703 249366 36885 102 108

91 7742072 9746 2893672 570854 0 7481 190285 35345 2368 83

90 7927068 3280 2517145 712943 0 6943 237648 47336 4009 55

89 8687143 3676 2922994 833087 0 6934 277696 55083 4342 116

88 8800821 568 2961942 737315 0 5338 245772 70682 6115 78

87 8403556 23000 2666470 576923 1937 4760 192308 58113 6980 84

86 8093892 26380 2600147 701241 8701 8808 233747 51373 8209 87

85 7090963 69659 2040755 661168 9754 9038 220389 56147 11009 28

84 5978688 98664 1670540 564080 20230 9680 188027 55959 11363 34

83 3831635 94461 948999 388127 21601 8271 129376 37983 10931 23

82 2710825 145689 739107 277091 51916 7279 92364 37446 9270 11

81 2305351 175194 651163 251737 42762 329 83912 37952 12053 4

80 1953647 79200 446378 340398 20482 217 113466 45494 10434 9

79 2237823 61862 529703 820584 17283 917 273528 88619 9290 13

78 1785913 20597 384720 756833 10222 93 252278 69373 8459 2

77 1335445 12593 328772 587410 0 21 195803 67918 9547 1

76 824579 11453 389724 295581 7408 12 98527 67102 6915 2

75 477882 7505 210964 181913 24441 8 60638 90069 8715 3

74 532240 3599 335900 130161 44505 7 43387 94921 0 1

73 0 0 0 0 0 0 0 93372 0 0

72 0 0 0 0 0 0 0 72328 0 0

71 0 0 0 0 0 0 0 54597 0 0

70 0 0 0 0 0 0 0 57955 0 0

69 0 0 0 0 0 0 0 50761 0 0

68 0 0 0 0 0 0 0 39588 0 0

67 0 0 0 0 0 0 0 38887 0 0

66 0 0 0 0 0 0 0 34371 0 0

TOTAL 119347379 865658 41130348 14620369 281243 140179 4873456 1699401 150634 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
4-30

Table 4-2. Vehicles in operation as of July 1996 (continued)

U.S. Levels

HDDV HDDB ALL

Model 2B 3 4-5 6-7 8A* 8B* S.BUS T.BUS** VEHICLES

Year 8501-10000 10001-14000 14001-19500 19501-33000 33001-60000 >60000 ANY WGT. ANY WGT. TOTAL

96 77760 20611 15084 36848 22858 63398 12592 10043049

95 162857 49894 45619 112777 55767 154674 34395 15522473

94 131869 46825 29457 69815 41561 115272 17088 1186 13739879

93 133923 37278 26359 63675 35682 98966 19899 2496 12978803

92 93290 31827 20855 55070 18191 79092 20696 2278 11553918

91 77685 28002 14467 64578 25051 71036 24920 3188 11760833

90 72117 40421 18977 80650 28786 83175 28698 4682 11813932

89 69774 32708 20834 60814 29759 98894 15007 3829 13122690

88 50752 22387 13770 68499 25953 89567 18602 3167 13121329

87 45383 20704 4064 69454 29736 74622 19539 3299 12200932

86 84934 25966 2184 60684 28204 59103 17097 3330 12014086

85 80761 10736 2066 61696 30539 69423 11743 3741 10439615

84 78286 6075 1565 56347 25970 56621 7120 3206 8832456

83 51681 4005 454 28033 13613 26483 5245 3989 5604910

82 35845 2110 198 29110 18921 28273 4488 3017 4192960

81 1135 21 246 39861 23076 33078 4324 3270 3665466

80 0 0 2 27106 19685 24454 659 3811 3085441

79 0 0 0 23784 28160 36212 448 1695 4129922

78 0 1 0 14891 21616 29266 253 1182 3355700

77 0 2 0 7938 14940 23464 235 760 2584847

76 0 3 268 4459 9327 9767 60 510 1725698

75 0 5 106 4534 15695 10430 77 682 1093667

74 0 34 6 3740 5779 8590 0 338 1203209

73 0 20 127 3497 5492 7013 0 393 109914

72 0 0 118 2601 4445 3650 0 247 83389

71 0 0 60 1905 3799 1980 0 211 62551

70 0 0 38 4447 3386 791 0 73 66691

69 0 0 116 2618 850 1205 0 106 55655

68 0 0 95 2007 655 605 0 78 43028

67 0 0 94 321 186 946 0 90 40524

66 0 4 71 261 277 298 0 189 35470

TOTAL 1248050 379639 217303 1062021 587955 1360346 263185 55043 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
4-31

Table 4-3. Annual Mileage Accumulation (Raw Data)

U.S. Levels

Vehicle

Age

LDV LDGT LDDT HDGV HDGB

LDGV LDDV LDGT1 LDGT2 LDDT1 LDDT2 2B-3 4-8 S.BUS T.BUS

<6000 6001-8500 <6000 6001-8500 8501-14000 >14000 ANY WGT. ANY WGT.

1 13386 13386 19698 21694 22653 20882 18815 23355 (a) (b)

2 13488 13488 16825 18416 25994 24072 17574 19328 28426

3 12496 12496 16770 17576 20482 22784 18405 16790 29869

4 12351 12351 16386 15141 17448 22879 15697 14549 26386

5 12059 12059 15677 16733 18890 21633 14700 14475 24000

6 11343 11343 15132 13229 19068 22558 13281 14502 22708

7 11067 11067 13883 14587 16500 15628 12662 15391 18205

8 10004 10004 12938 12677 14710 11402 15497 13001 23463

9 10718 10718 12522 13392 13016 18014 13804 12847 13141

10 8910 8910 12026 11527 10347 13072 12067 11745 16905

11 9046 9046 10008 14292 11272 7357 9484 9122 (b)

12 10527 10527 7726 10784 5738 10058 6287 16882

13 8268 8268 8940 7411 9470 11476 7621 12600

14 8330 8330 6904 7026 10011 6662 9000

15 8337 8337 6238 7597 9862 6519 5250

16 7241 7241 6365 9852 9000 10138 5997 8583

17 9015 9015 5278 9895 7763 6464 (b)

18 6966 6966 5662 5365 4234 4397 (b)

19 5479 5479 5704 5660 5009 3999 (b)

20 4460 4460 4011 3239 8798 4412 (b)

21 4940 4940 3127 7557 6501 4062 6000

22 4125 4125 2994 5500 4122 5736

23 6531 6531 3465 4471 5628

24 5719 5719 2556 3124 3356

25 2357 2357 3616 2149

26 6470 6470 2639 2091

27 1382 1820

28 1685 2714

29 2921 2921 2356

30 1622

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
4-32

Table 4-3. Annual Mileage Accumulation (Raw Data) (continued)

U.S. Levels

HDDV HDDB

Vehicle 2B 3 4-5 6-7 8A 8B S.BUS T.BUS

Age 8501-10000 10001-14000 14001-19500 19501-33000 33001-60000 >60000 ANY WGT. ANY WGT.

1 22533 26616 32471 39017 85794 113141 (a) (b)

2 24591 27581 23791 30011 57498 98673 (b)

3 21502 26920 24800 27931 59784 95977 46791

4 21973 27678 19624 26190 62189 93147 41262

5 22448 20526 17776 25680 55199 84050 42206

6 20624 22980 23767 23481 48350 75736 39160

7 18932 17816 20066 23955 39863 68358 38266

8 12949 17268 21918 21071 41742 66294 36358

9 16151 12186 26337 23124 36635 60231 34935

10 9320 6333 29844 18216 32963 54245 33021

11 15151 6000 27830 13646 25153 39068 32540

12 6750 13571 15412 18800 37879 32605

13 7200 11618 21244 30798 27722

14 10159 8341 11487 19149 32119 28429

15 8000 8400 9458 19386 28777 32140

16 9000 11000 12977 10912 30416 28100

17 6269 13256 32813 24626

18 16296 17975 19820 23428

19 14115 18036 22471 22575

20 13844 17712 21928 23220

21 5297 7459 25033 19588

22 5000 13934 30084 22939

23 1805 8493 22559 26413

24 1053 9452 17363 23366

25 7000 14818 13278 11259

26 5538 23228

27 2088 19040 21515

28 5533 10417 25939

29 502 1350 20117

30 8443 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
4-33

Table 4-4. Annual Mileage Accumulation (Curve Fit Data)

U.S. Levels

Vehicle

Age

LDV LDGT LDDT HDGV HDGB

LDGV LDDV LDGT1 LDGT2 LDDT1 LDDT2 2B-3 4-8 S.BUS T.BUS

<6000 6001-8500 <6000 6001-8500 8501-14000 >14000 ANY WGT. ANY WGT.

1 14910 14910 19496 21331 27059 26040 19977 21394 (a) 35123

2 14174 14174 18384 19865 24384 24018 18779 19692 31914

3 13475 13475 17308 18500 21973 22154 17654 18125 28999

4 12810 12810 16267 17228 19801 20434 16596 16683 26350

5 12178 12178 15260 16044 17843 18848 15601 15356 23942

6 11577 11577 14289 14942 16079 17385 14666 14134 21755

7 11006 11006 13352 13915 14490 16036 13787 13010 19768

8 10463 10463 12451 12959 13057 14791 12961 11975 17962

9 9947 9947 11584 12068 11766 13643 12184 11022 16321

10 9456 9456 10752 11239 10603 12584 11454 10145 14830

11 8989 8989 9955 10466 9555 11607 10768 9338 13475

12 8546 8546 9194 9747 8610 10706 10122 8595 12244

13 8124 8124 8467 9077 7759 9875 9516 7911 11126

14 7723 7723 7775 8453 6992 9109 8946 7282 10109

15 7342 7342 7118 7872 6301 8402 8409 6703 9186

16 6980 6980 6496 7331 5678 7749 7905 6169 8347

17 6636 6636 5909 6827 5116 7148 7432 5679 7584

18 6308 6308 5356 6358 4610 6593 6986 5227 6891

19 5997 5997 4839 5921 4155 6081 6568 4811 6262

20 5701 5701 4357 5514 3744 5609 6174 4428 5690

21 5420 5420 3909 5135 3374 5174 5804 4076 5170

22 5152 5152 3497 4782 3040 4772 5456 3752 4698

23 4898 4898 3120 4454 2740 4402 5129 3453 4268

24 4656 4656 2777 4148 2469 4060 4822 3178 3879

25 4427 4427 2470 3863 2225 3745 4533 2926 3524

26 4208 4208 2197 3597 2005 3454 4261 2693 3202

27 4001 4001 1959 3350 1807 3186 4006 2479 2910

28 3803 3803 1756 3120 1628 2939 3766 2281 2644

29 3616 3616 1589 2905 1467 2711 3540 2100 2402

30 3437 3437 1456 2706 1322 2500 3328 1933 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
4-34

Table 4-4. Annual Mileage Accumulation (Curve Fit Data) (continued)

U.S. Levels

Vehicle

Age

HDDV HDDB

2B 3 4-5 6-7 8A 8B S.BUS T.BUS

8501-10000 10001-14000 14001-19500 19501-33000 33001-60000 >60000 ANY WGT. ANY WGT.

1 27137 32751 30563 40681 87821 124208 (a) 45171

2 24831 28984 28622 36872 78257 112590 43731

3 22721 25650 26805 33420 69735 102060 42337

4 20791 22699 25103 30291 62141 92514 40987

5 19024 20088 23509 27455 55374 83861 39681

6 17407 17778 22016 24885 49343 76017 38416

7 15928 15733 20618 22555 43970 68907 37191

8 14575 13923 19309 20443 39181 62462 36005

9 13336 12321 18083 18529 34915 56620 34857

10 12203 10904 16935 16795 31112 51324 33746

11 11166 9650 15860 15222 27724 46523 32670

12 10217 8540 14853 13797 24705 42172 31629

13 9349 7557 13910 12505 22015 38228 30620

14 8555 6688 13026 11335 19617 34652 29644

15 7828 5919 12199 10273 17481 31411 28699

16 7163 5238 11425 9312 15577 28473 27784

17 6554 4635 10699 8440 13881 25810 26898

18 5997 4102 10020 7650 12369 23396 26041

19 5488 3630 9384 6933 11022 21208 25211

20 5021 3213 8788 6284 9822 19224 24407

21 4595 2843 8230 5696 8752 17426 23629

22 4204 2516 7707 5163 7799 15796 22875

23 3847 2227 7218 4679 6950 14319 22146

24 3520 1971 6760 4241 6193 12979 21440

25 3221 1744 6331 3844 5518 11765 20757

26 2947 1543 5929 3484 4918 10665 20095

27 2697 1366 5552 3158 4382 9667 19454

28 2468 1209 5200 2862 3905 8763 18834

29 2258 1070 4869 2594 3480 7944 18234

30 2066 947 4560 2352 3101 7201 17652

HDDV Heavy duty diesel vehicle

HDDB Heavy duty diesel bus

(a) Average school bus mileage for all ages = 9,939
4-35

Table 4-5. Annual mileage accumulation curve fit equations

Vehicle Class Equation

LDGV y = 15684e-0.0506x

LDDV y = 15684e-0.0506x

LDGT1 y = 17.472x2 - 1163.7x + 20642

LDGT2 y = 22905e-0.0712x

LDDT1 y = 30028e-0.1041x

LDDT2 y = 28231e-0.0808x

HDGV (2B-3) y = 21250e-0.0618x

HDGV (4-8) y = 23243e-0.0829x

HDGSB y = 9939

HDGTB y = 38654e-0.0958x

HDDV (2B) y = 29657e-0.0888x

HDDV (3) y = 37008e-0.1222x

HDDV (4-5) y = 32635e-0.0656x

HDDV (6-7) y = 44883e-0.0983x

HDDV (8A) y = 98554e-0.1153x

HDDV (8B) y = 137024e-0.0982x

HDDSB y = 9939

HDDTB y = 46659e-0.0324x

x = Model year - 1900

y = Annual mileage (miles)
4-36

Table 4-6. Vehicles in Operation as Percent of Class as of July 1996

U.S. Levels

Model

Year

LDV LDGT LDDT HDGV HDGB

LDGV LDDV LDGT1 LDGT2 LDDT1 LDDT2 2B-3 4-8 S.BUS T.BUS

<6000 6001-8500 <6000 6001-8500 8501-14000 >14000 ANY WGT. ANY WGT.

96 5.03% 0.62% 6.02% 6.59% 0.00% 8.77% 6.59% 0.96% 0.34% 0.00%

95 7.68% 0.63% 9.05% 9.92% 0.00% 12.00% 9.92% 3.22% 2.93% 0.00%

94 6.67% 0.07% 8.84% 8.31% 0.00% 9.73% 8.31% 2.80% 1.94% 3.63%

93 6.73% 0.31% 8.12% 5.85% 0.00% 8.98% 5.85% 2.07% 1.77% 6.54%

92 6.26% 0.51% 6.61% 5.12% 0.00% 6.21% 5.12% 2.17% 0.07% 13.08%

91 6.49% 1.13% 7.04% 3.90% 0.00% 5.34% 3.90% 2.08% 1.57% 10.05%

90 6.64% 0.38% 6.12% 4.88% 0.00% 4.95% 4.88% 2.79% 2.66% 6.66%

89 7.28% 0.42% 7.11% 5.70% 0.00% 4.95% 5.70% 3.24% 2.88% 14.04%

88 7.37% 0.07% 7.20% 5.04% 0.00% 3.81% 5.04% 4.16% 4.06% 9.44%

87 7.04% 2.66% 6.48% 3.95% 0.69% 3.40% 3.95% 3.42% 4.63% 10.17%

86 6.78% 3.05% 6.32% 4.80% 3.09% 6.28% 4.80% 3.02% 5.45% 10.53%

85 5.94% 8.05% 4.96% 4.52% 3.47% 6.45% 4.52% 3.30% 7.31% 3.39%

84 5.01% 11.40% 4.06% 3.86% 7.19% 6.91% 3.86% 3.29% 7.54% 4.12%

83 3.21% 10.91% 2.31% 2.65% 7.68% 5.90% 2.65% 2.24% 7.26% 2.78%

82 2.27% 16.83% 1.80% 1.90% 18.46% 5.19% 1.90% 2.20% 6.15% 1.33%

81 1.93% 20.24% 1.58% 1.72% 15.20% 0.23% 1.72% 2.23% 8.00% 0.48%

80 1.64% 9.15% 1.09% 2.33% 7.28% 0.15% 2.33% 2.68% 6.93% 1.09%

79 1.88% 7.15% 1.29% 5.61% 6.15% 0.65% 5.61% 5.21% 6.17% 1.57%

78 1.50% 2.38% 0.94% 5.18% 3.63% 0.07% 5.18% 4.08% 5.62% 0.24%

77 1.12% 1.45% 0.80% 4.02% 0.00% 0.02% 4.02% 4.00% 6.34% 0.12%

76 0.69% 1.32% 0.95% 2.02% 2.63% 0.01% 2.02% 3.95% 4.59% 0.24%

75 0.40% 0.87% 0.51% 1.24% 8.69% 0.01% 1.24% 5.30% 5.79% 0.36%

74 0.45% 0.42% 0.82% 0.89% 15.82% 0.01% 0.89% 5.59% 0.00% 0.12%

73 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 5.49% 0.00% 0.00%

72 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 4.26% 0.00% 0.00%

71 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 3.21% 0.00% 0.00%

70 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 3.41% 0.00% 0.00%

69 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 2.99% 0.00% 0.00%

68 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 2.33% 0.00% 0.00%

67 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 2.29% 0.00% 0.00%

66 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 2.02% 0.00% 0.00%

TOTAL 100% 100% 100% 100% 100% 100% 100% 100% 100% 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
4-37

Table 4-6. Vehicles in Operation as Percent of Class as of July 1996 (continued)

U.S. Levels

Model

Year

HDDV HDDB ALL

VEHICLES

TOTAL

2B 3 4-5 6-7 8A* 8B* S.BUS T.BUS**

8501-10000 10001-14000 14001-19500 19501-33000 33001-60000 >60000 ANY WGT. ANY WGT.

96 6.23% 5.43% 6.94% 3.47% 3.89% 4.66% 4.78% 0.00% 5.33%

95 13.05% 13.14% 20.99% 10.62% 9.48% 11.37% 13.07% 0.00% 8.24%

94 10.57% 12.33% 13.56% 6.57% 7.07% 8.47% 6.49% 2.15% 7.30%

93 10.73% 9.82% 12.13% 6.00% 6.07% 7.28% 7.56% 4.53% 6.89%

92 7.47% 8.38% 9.60% 5.19% 3.09% 5.81% 7.86% 4.14% 6.14%

91 6.22% 7.38% 6.66% 6.08% 4.26% 5.22% 9.47% 5.79% 6.25%

90 5.78% 10.65% 8.73% 7.59% 4.90% 6.11% 10.90% 8.51% 6.27%

89 5.59% 8.62% 9.59% 5.73% 5.06% 7.27% 5.70% 6.96% 6.97%

88 4.07% 5.90% 6.34% 6.45% 4.41% 6.58% 7.07% 5.75% 6.97%

87 3.64% 5.45% 1.87% 6.54% 5.06% 5.49% 7.42% 5.99% 6.48%

86 6.81% 6.84% 1.01% 5.71% 4.80% 4.34% 6.50% 6.05% 6.38%

85 6.47% 2.83% 0.95% 5.81% 5.19% 5.10% 4.46% 6.80% 5.54%

84 6.27% 1.60% 0.72% 5.31% 4.42% 4.16% 2.71% 5.82% 4.69%

83 4.14% 1.06% 0.21% 2.64% 2.32% 1.95% 1.99% 7.25% 2.98%

82 2.87% 0.56% 0.09% 2.74% 3.22% 2.08% 1.71% 5.48% 2.23%

81 0.09% 0.01% 0.11% 3.75% 3.92% 2.43% 1.64% 5.94% 1.95%

80 0.00% 0.00% 0.00% 2.55% 3.35% 1.80% 0.25% 6.92% 1.64%

79 0.00% 0.00% 0.00% 2.24% 4.79% 2.66% 0.17% 3.08% 2.19%

78 0.00% 0.00% 0.00% 1.40% 3.68% 2.15% 0.10% 2.15% 1.78%

77 0.00% 0.00% 0.00% 0.75% 2.54% 1.72% 0.09% 1.38% 1.37%

76 0.00% 0.00% 0.12% 0.42% 1.59% 0.72% 0.02% 0.93% 0.92%

75 0.00% 0.00% 0.05% 0.43% 2.67% 0.77% 0.03% 1.24% 0.58%

74 0.00% 0.01% 0.00% 0.35% 0.98% 0.63% 0.00% 0.61% 0.64%

73 0.00% 0.01% 0.06% 0.33% 0.93% 0.52% 0.00% 0.71% 0.06%

72 0.00% 0.00% 0.05% 0.24% 0.76% 0.27% 0.00% 0.45% 0.04%

71 0.00% 0.00% 0.03% 0.18% 0.65% 0.15% 0.00% 0.38% 0.03%

70 0.00% 0.00% 0.02% 0.42% 0.58% 0.06% 0.00% 0.13% 0.04%

69 0.00% 0.00% 0.05% 0.25% 0.14% 0.09% 0.00% 0.19% 0.03%

68 0.00% 0.00% 0.04% 0.19% 0.11% 0.04% 0.00% 0.14% 0.02%

67 0.00% 0.00% 0.04% 0.03% 0.03% 0.07% 0.00% 0.16% 0.02%

66 0.00% 0.00% 0.03% 0.02% 0.05% 0.02% 0.00% 0.34% 0.02%

TOTAL 100% 100% 100% 100% 100% 100% 100% 100% 100%

HDDV Heavy duty diesel vehicle

HDDB Heavy duty diesel bus
4-38

Table 4-7. Vehicles in Operation as of July 1996

Aggregated Classes, U.S. Levels

Model

Year

LDV

all

LDGT

all

<8500

LDDT

all

<8500

LDT

all

<8500

HDGV

all

>8500

HDGB

all

any

HDDV

3 to 5

10001-19500

HDDV

8

>33000

HDDV

all

>8501

HDDB

all

any

96 6004661 3438948 12298 3451246 337478 516 35695 86256 236558 12592

95 9172119 5174798 16827 5191624 538338 4408 95514 210440 581588 34395

94 7966812 4850958 13635 4864593 452446 2956 76282 156833 434799 18274

93 8030239 4194553 12582 4207136 320424 2727 63637 134648 395882 22395

92 7472537 3464920 8703 3473623 286251 210 52681 97282 298324 22974

91 7751818 3464526 7481 3472007 225630 2451 42469 96087 280820 28108

90 7930348 3230088 6943 3237031 284983 4064 59398 111961 324127 33380

89 8690819 3756081 6934 3763014 332779 4458 53542 128653 312783 18836

88 8801389 3699257 5338 3704595 316453 6193 36157 115520 270929 21769

87 8426556 3243393 6697 3250090 250420 7064 24768 104358 243963 22838

86 8120272 3301388 17509 3318897 285120 8296 28150 87306 261075 20427

85 7160622 2701923 18792 2720715 276536 11037 12802 99962 255220 15484

84 6077352 2234620 29910 2264530 243986 11397 7640 82591 224864 10326

83 3926096 1337126 29872 1366998 167358 10954 4460 40096 124269 9234

82 2856514 1016198 59195 1075393 129809 9281 2308 47194 114457 7505

81 2480545 902900 43091 945991 121864 12057 267 56154 97416 7594

80 2032847 786776 20699 807475 158960 10443 2 44139 71247 4470

79 2299685 1350287 18200 1368487 362147 9303 0 64371 88155 2143

78 1806510 1141553 10315 1151869 321650 8461 1 50883 65775 1435

77 1348038 916182 21 916203 263721 9548 2 38403 46343 995

76 836032 685305 7420 692725 165629 6917 272 19095 23825 570

75 485387 392877 24449 417326 150707 8718 111 26125 30770 759

74 535839 466061 44512 510573 138308 1 40 14369 18149 338

73 0 0 0 0 93372 0 147 12504 16149 393

72 0 0 0 0 72328 0 118 8095 10814 247

71 0 0 0 0 54597 0 60 5778 7744 211

70 0 0 0 0 57955 0 38 4177 8663 73

69 0 0 0 0 50761 0 116 2054 4789 106

68 0 0 0 0 39588 0 95 1260 3362 78

67 0 0 0 0 38887 0 94 1132 1547 90

66 0 0 0 0 34371 0 75 575 911 189

TOTAL 120213037 55750717 421422 56172139 6572857 151460 596942 1948301 4855315 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
4-39

Aggregated Classes, U.S. Levels

Model

Year

LDV

all

LDGT

all

<8500

LDDT

all

<8500

LDT

all

<8500

HDGV

all

>8500

HDGB

all

any

HDDV

3 to 5

10001-19500

HDDV

8

>33000

HDDV

all

>8501

HDDB

all

any

96 5.00% 6.17% 2.92% 6.14% 5.13% 0.34% 5.98% 4.43% 4.87% 3.96%

95 7.63% 9.28% 3.99% 9.24% 8.19% 2.91% 16.00% 10.80% 11.98% 10.81%

94 6.63% 8.70% 3.24% 8.66% 6.88% 1.95% 12.78% 8.05% 8.96% 5.74%

93 6.68% 7.52% 2.99% 7.49% 4.87% 1.80% 10.66% 6.91% 8.15% 7.04%

92 6.22% 6.22% 2.07% 6.18% 4.36% 0.14% 8.83% 4.99% 6.14% 7.22%

91 6.45% 6.21% 1.78% 6.18% 3.43% 1.62% 7.11% 4.93% 5.78% 8.83%

90 6.60% 5.79% 1.65% 5.76% 4.34% 2.68% 9.95% 5.75% 6.68% 10.49%

89 7.23% 6.74% 1.65% 6.70% 5.06% 2.94% 8.97% 6.60% 6.44% 5.92%

88 7.32% 6.64% 1.27% 6.60% 4.81% 4.09% 6.06% 5.93% 5.58% 6.84%

87 7.01% 5.82% 1.59% 5.79% 3.81% 4.66% 4.15% 5.36% 5.02% 7.18%

86 6.75% 5.92% 4.15% 5.91% 4.34% 5.48% 4.72% 4.48% 5.38% 6.42%

85 5.96% 4.85% 4.46% 4.84% 4.21% 7.29% 2.14% 5.13% 5.26% 4.87%

84 5.06% 4.01% 7.10% 4.03% 3.71% 7.52% 1.28% 4.24% 4.63% 3.24%

83 3.27% 2.40% 7.09% 2.43% 2.55% 7.23% 0.75% 2.06% 2.56% 2.90%

82 2.38% 1.82% 14.05% 1.91% 1.97% 6.13% 0.39% 2.42% 2.36% 2.36%

81 2.06% 1.62% 10.23% 1.68% 1.85% 7.96% 0.04% 2.88% 2.01% 2.39%

80 1.69% 1.41% 4.91% 1.44% 2.42% 6.89% 0.00% 2.27% 1.47% 1.40%

79 1.91% 2.42% 4.32% 2.44% 5.51% 6.14% 0.00% 3.30% 1.82% 0.67%

78 1.50% 2.05% 2.45% 2.05% 4.89% 5.59% 0.00% 2.61% 1.35% 0.45%

77 1.12% 1.64% 0.01% 1.63% 4.01% 6.30% 0.00% 1.97% 0.95% 0.31%

76 0.70% 1.23% 1.76% 1.23% 2.52% 4.57% 0.05% 0.98% 0.49% 0.18%

75 0.40% 0.70% 5.80% 0.74% 2.29% 5.76% 0.02% 1.34% 0.63% 0.24%

74 0.45% 0.84% 10.56% 0.91% 2.10% 0.00% 0.01% 0.74% 0.37% 0.11%

73 0.00% 0.00% 0.00% 0.00% 1.42% 0.00% 0.02% 0.64% 0.33% 0.12%

72 0.00% 0.00% 0.00% 0.00% 1.10% 0.00% 0.02% 0.42% 0.22% 0.08%

71 0.00% 0.00% 0.00% 0.00% 0.83% 0.00% 0.01% 0.30% 0.16% 0.07%

70 0.00% 0.00% 0.00% 0.00% 0.88% 0.00% 0.01% 0.21% 0.18% 0.02%

69 0.00% 0.00% 0.00% 0.00% 0.77% 0.00% 0.02% 0.11% 0.10% 0.03%

68 0.00% 0.00% 0.00% 0.00% 0.60% 0.00% 0.02% 0.06% 0.07% 0.02%

67 0.00% 0.00% 0.00% 0.00% 0.59% 0.00% 0.02% 0.06% 0.03% 0.03%

66 0.00% 0.00% 0.00% 0.00% 0.52% 0.00% 0.01% 0.03% 0.02% 0.06%

TOTAL 100% 100% 100% 100% 100% 100% 100% 100% 100% 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
4-40

Table 4-9. Gasoline/Diesel Sales Faction*

Model

Year

LDV LDT

LDGV LDDV LDGT LDDT

96 99.91% 0.09% 99.64% 0.36%

95 99.94% 0.06% 99.68% 0.32%

94 99.99% 0.01% 99.72% 0.28%

93 99.97% 0.03% 99.70% 0.30%

92 99.94% 0.06% 99.75% 0.25%

91 99.87% 0.13% 99.78% 0.22%

90 99.96% 0.04% 99.79% 0.21%

89 99.96% 0.04% 99.82% 0.18%

88 99.99% 0.01% 99.86% 0.14%

87 99.73% 0.27% 99.79% 0.21%

86 99.68% 0.32% 99.47% 0.53%

85 99.03% 0.97% 99.31% 0.69%

* Assumes that scrappage rates are equivalent for diesel and gasoline vehicles
A-1

APPENDIX A
BUSES.PRG

A-2

*

* 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. found()

 append blank

 replace FUEL with DATA->FUELTYPE

 replace MY with DATA->MY

 endif

 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

 endif

 if TOTALREGS > 0

 replace AVEMIL with AMTOT/TOTALREGS

 endif

 skip

enddo

select 2

use

select 1

use
TIUSCONV.C

A-3

/* TIUSCONV 

 Converts the TIUS dataset TI92MDF.DAT to a comma delimited file for

 importing into dBASE file TIUSDAT

*/

#include <stdio.h>

#include <ctype.h>

#define 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=1; count <=7; count++) {

 bufout[odex] = buffer[idex];

 odex++;

 idex++;

 }

 bufout[odex] = comma;

 odex++;

 idex = 23;

 /* MDLYR 24-25 */

 for (count=1; count <=2; count++) {

 bufout[odex] = buffer[idex];

 odex++;

 idex++;

 }

 bufout[odex] = comma;

 odex++;

 /* ACQMON 26-27 */

 for (count=1; count <=2; count++) {

 bufout[odex] = buffer[idex];

 odex++;

 idex++;

 }

 bufout[odex] = comma;

 odex++;

 /* ACQYR 28-29 */

 for (count=1; 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;
TIUSCONV.C

A-4

 bufout[odex] = buffer[idex];

 idex++;

 odex++;

 bufout[odex] = comma;

 odex++;

 /* DISMON 43-44 */

 for (count=1; count <=2; count++) {

 bufout[odex] = buffer[idex];

 odex++;

 idex++;

 }

 bufout[odex] = comma;

 odex++;

 /* DISYR 45-46 */

 for (count=1; count <=2; count++) {

 bufout[odex] = buffer[idex];

 odex++;

 idex++;

 }

 bufout[odex] = comma;

 odex++;

 /* HOWRID 47 */

 bufout[odex] = buffer[idex];

 odex++;

 bufout[odex] = comma;

 odex++;

 /* BODTYP 58-59 */

 idex = 57;

 for (count=1; count <=2; count++) {

 bufout[odex] = buffer[idex];

 odex++;

 idex++;

 }

 bufout[odex] = comma;

 odex++;

 /* MAXWT 105-110 */

 idex = 104;

 for (count=1; count <=6; count++) {

 bufout[odex] = buffer[idex];

 odex++;

 idex++;

 }

 bufout[odex] = comma;

 odex++;

 /* EngTyp 112 */

 idex = 111;

 bufout[odex] = buffer[idex];

 odex++;

 bufout[odex] = comma;

 odex++;

 /* ANNMIL 155-160 */

 idex = 154;

 for (count=1; count <=6; count++) {

 bufout[odex] = buffer[idex];

 odex++;

 idex++;

 }

 bufout[odex] = comma;

 odex++;

 /* TIUGVW 421-422 */

 idex = 420;

 for (count=1; count <=2; count++) {
TIUSCONV.C

A-5

 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=1; 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");

}
TIUS.PRG

A-6

*

* 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
TIUS.PRG

A-7

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-8

Figure A-1. Segregated Light-Duty Truck Types

Annual Miles by Age for LDGT1

0

5,000

10,000

15,000

20,000

25,000

30,000

0 5 10 15 20 25 30

Age

Annual Miles

Aggregated Light-Duty Trucks

Minivans

Other Light-Duty Trucks

Pick-Ups

Sport Utility Vehicles
LDVS.PRG

A-9

*

* 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 =

"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
LDVS.PRG

A-10

 replace AnnMiles with TotSE/SERegs

endif

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 STDEV_ODO 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 STDEV_ODO with SQRT(ODOVAR/ODOREGs)

endif