SN 96148.020
ENERGY CONSERVATION/ALLOCATION
MEASURE IMPACT ON
LIGHT DUTY VEHICLE MILES TRAVELED
FOR
AIR QUALITY PLANNING
TASK ORDER NO. 2
CONTRACT NO. 68-02-1385
FEBRUARY 25, 1974
Prepared For
ENVIRONMENTAL PROTECTION AGENCY
RESEARCH TRIANGLE PARK
NORTH CAROLINA 27711
Prepared By
TRW!
TRANSPORTATION &
ENVIRONMENTAL
OPERATIONS
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SN 96148.020
ENERGY CONSERVATION/ALLOCATION
MEASURE IMPACT ON
LIGHT DUTY VEHICLE MILES TRAVELED
FOR
AIR QUALITY PLANNING
TASK ORDER NO. 2
CONTRACT NO. 68-02-1385
FEBRUARY 25, 1974
Prepared For
ENVIRONMENTAL PROTECTION AGENCY
RESEARCH TRIANGLE PARK
NORTH CAROLINA 27711
Prepared By
/ transportatioi
M n&wgmj / ENVIRONMENTAL
B M ^ WW / OPERATIONS
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This report was furnished to the Environmental Protection Agency by
TRW Transportation and Environmental Operations in fulfillment of Contract
Number 68-02-1385. The contents of this report are reproduced herein as
received from the contractor. The opinions, findings, and conclusions
are those of TRW and not necessarily those of the Environmental Protection
Agency. Mention of company or product names does not constitute endorse-
ment by the Environmental Protection Agency.
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TABLE OF CONTENTS
Page
1.0 INTRODUCTION I
2.0 SUMMARY 4
3.0 TECHNICAL APPROACH 8
3.2 SCALE OF ANALYSIS UNITS 13
3.3 AIR QUALITY PLANNING REGIONS 13
3.4 TRANSPORTATION ANALYSIS ZONES 15
3.5 HOUSEHOLD PANEL 16
3.6 MAJOR ACTIVITY CENTERS 16
3.7 PROJECT-SPECIFIC STUDY AREAS 17
3.8 MULTIPLE REGIONS APPROACH 17
3.9 DATA REQUIREMENTS AND SOURCES 18
APPENDIX A A-l
APPENDIX B B-l
APPENDIX C C-l
APPENDIX D ' D-l
APPENDIX E E-l
APPENDIX F F-l
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1.0 INTRODUCTION
The "energy crisis" has resulted in a broad spectrum of effects to the
lifestyles in the United States. Unfortunately, most of the impacts were
unanticipated during the development of the EPA Transportation Control Stra-
gegies to achieve the National Ambient Air Quality Standards in numerous AQCR's
in accord with the requirements of the Clean Air Act of 1970.
As a result of shortages in petroleum supplies, constraints have been
introduced to reduce the use of gasoline for travel purposes. These con-
straints have included,
o gasoline prices rising by 3 - 5 percent per month;
• closing of automobile service stations on Sundays and reduced hours
on other weekdays;
• restrictions on gasoline sales due to limited supplies;
• car pooling incentives including preferred parking, use of exclusive
traffic lanes, pool locator services, and other measures;
• reduced speed limits on freeways and major highways.
In addition, other measures to reduce fuel consumption for travel are being
proposed:
• shifts in work hours
6 gasoline rationing e.g. standby coupon system, Oregon's 'even-odd'
programs
« bus use incentives.
The conservation, distribution, allocation, and other aspects affecting
the production and consumption of motor fuel for passenger cars has brought
about changes in total vehicle miles traveled throughout the country. How-
ever, because of the various travel alternatives available in different loca-
tions, i.e. demand for VMT, the regional differences in pricing, and motor
fuel distributions, the impact of the energy conservation and allocation
measures is not uniformly distributed geographically.
1
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Because of the significant changes now anticipated in projected air
quality levels associated with transportation related pollutants due to
the energy related VMT changes, it becomes imperative to understand the
specifics of these changes and how they relate to or may be applied as
transportation control measures from an air quality point-of-view.(See Figure 1)
To summarize, it is recommended that the EPA immediately embark on a pro-
gram to monitor travel impacts of fuel shortage conditions to:
9 understand modal shifts and trip making rate changes resulting from
reduced gasoline availability;
• update regional transportation strategies on basis of the changing
VMT levels throughout the country.
2
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Figure 1. Travel Impacts of Fuel Shortages
Reported by Washington Newspapers
Year.
x WASHING tu:I4( 0 C f TUESDAY, FEBPAWRY 12, 1974 PAGES
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'he Vi;, ;\m P'-p.u ni:jnt
A:, f ihhv r nihiiii;: i'0,iiicrn
ante 10 scu if u, loo, suj«s a
F.PA's announced poal v.ns to reduce
rj c.i during the inoi ru:;; tujh hoai s
h\ VI pcrtcnt, and H ^: 11 c y w'icvls tins
Jcvcl may be reached as more people
thuo:^ to ride buses or cm pools
Thi- Metropolitan W.ishu.jion Council of
Gu\ c»rnicnts. which inoni'^ri: t ir quahty
ri 'hi5; aria, intends Io 'in* 1 y < nno \cn:y
tlic tr< uic ieduction and its on over-
p! 1 \chick- crru^sion^, .iCLinoi,r: to Per'-ts
D.'itcs dliccior of COv.«'> h.'r.Uh and cnvi-
ropni^ntal protection seciion
KATKS SAID COG must look not only nt
lh<: roduclion in the nmribi-r of vehicle
t-:'W-:oiine Skor
' ' - ' " > C vl ; t ;/d L- -_V
SLj
73
Wnh hw
\\ .T-h P'.'tC'T)
c,vji « 'i\ J n • - ] rm r i
line ^.Tuir.-T M'.'ii'iiui
< (,)'.< i j\i i > 1 (5 8 ;ic
lif-t V (•<•!; ( Il «'d i
s.nr.f f,('•> in
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Widnv
Rv Jj'cl: 1 i^'n
u H<-hi ,i' n f'i «i 5m, : w
i ichii^ in i)ic
m-;i ,in;iai rni! <
Si.-n|iio .said tJicio wos nn pvc-
hm cMimale o-tho rUiiril-f'i of
'• r'11 ,i i 'S^spn^n s c a: i • t-c!
If Mn ro s i .i-1 ; ui. t v,n\, c:-
iirn.ii.ny foj mula ltm.iir1- .'.f
trir.'i. it apiicaiS Hi.-' ih<-
73 .i u dii-ti u t'ek's jiHoiiional fPi^ < ¦ IK *¦-
i opo" ted > i s iin.i^ wnkild lcpicsmi rif,oui
ppiwi5 o\>^> \hc
>Uaih" K> )iplp i he Mt't \ o 1 ] i\ o c,i\ pn mil 'lh,n uon'ci l^c
hus '•'.'um .'I'd oint': uai^it t'bciji 14 0C"» nun r p:^- or .ihr.tit h.ilf-
n\ui uiMcficus c-au^-il Oi.u 7,0UD, duru^^
pnilK h\ a ncefl |i> mk i ctj " c i*.u li rndinui^ and evening'
scn'C rnn < t,sioria! ropioi- » u>h hour 1
res r:icod Kit" ' '""^u tda\ otij 'Ihe^iiMe Motronus usirm !
icvi*-io:"« m pf't-clm i lcp^la oiui.nn i!\ collects a»4t"nj-1 i'itc sales i:i the \\,i-hir: on
|;inn ncrc ltjt'ictcd lo ni'i'i-j
This rompate^ wnh ^'.('(i, n.iu- rla\s. hn«ed upon niotoi
nnilioti in fis* Ml Kl75, ' f which iisjs' luvnse ta^ tuimbei c
$]4G miltcm v.-ouM ro jni j >e\ere crnwdinf, hren
11 ancit in 1'ie \\ asln.i.'io , | \ e->ubuibiin bvis iouKS
ti anr.poi tauon [»arkr.»p ,in, «ndmarily there arc
pi".1' d lost w> )» b\ i'1 cvid( nt i (Kil*. ie|p'iveiv fr*\\ slander's
Ni. n'i jSt.u.dins lf'ads ha\e lonj breu
The PmshI?iU ha5 threat uminion on the- shotted iity
encd to \eu» «mh le?irl?tion'lunies
as th n ntit .'d to Jn\ b\ , •] |,-> new national Iccisln'ion
the- < onfr-i iV4, li^nder' b\ >.nn ' niri.o^s a foim'ila 101 (huii-
Haui'on \ Vvi'liatn*- «lr <,1 Um icm of U\e U:ui«aaid
\.J j aiui itr>p Ci A j mi- momy Kach teuton vouldtiet
ish iH\ l) llie confeicr"'• o. < 'on-i cv;, wi:h ¦ cent on Die nutthe' of \chu-le
the U'-.iici- ar I in" l 1"=! • «:i«los ol service oppi'."HOil and
J'al ScslH'v Moiin's as< si•,?^ ]»ei cent on the number of
an; scr-i e!ai y 11 rrj, s.uri' or ."•enters
lerionnl »n'» In-' (ol'eetions - ['lie V\nn admmivirmion's
hi'iv hi't uua'rd pioposal ti» based fiilnely on
miles trau'lcd, but also at whether dn\ers
arc makihi! fewei tt ips
He said rt>u{:lily half the n*» .inus '"'iris
sion of automobiles ocelli s in the : ¦"st
three minutes after the enij..:c is siar-jd.
another attnrter when the cr.r is pai vd
anJ the engine cooling off, and the other 25
percent in between
Both Lhies and David JJ:Julio. lOG'5-
Air Qir.liiv Fioj:iani man. o:, b -h •
that if na:fic levels dccreace and tre air
qi:alny ponis set by KI'A ai e obtained vol
untanly, then COCJ's an quality pl.T.rinj"
con;inittee and the COG borud probcol>
would request EPA to drop its Washn-gtor
ai ea plan
,0 J1 Mi an ii.ii e,nce /if
G3J ri\oi je\^nu-<«. diii;nn, ino
secoir! full »M^»k of I'^bnia.v
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p«il>ul.it um
I hit*? under the \i\op ap- [
piomh \\a"hin-ion unuld'"'!
? 10 pei rent nt ihf iKM-"nal
nyMic.' and New Y<-il. which
ha*« about half of ib" raiion'c1
t i a us ¦' tulejs woi.ld 1 I'/i
]u r t en» Viulcr the coi^i es
' ion;il % crMnii \\ ;i«.Iup " '•n
wiM'ic1 vii'l 2 H.T pei cent niKJ
N• u V<.rk 2'i 53 pnr rent
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2.0 SUMMARY
The objective of this study was to determine:
(1) What can or cannot be accomplished to correlate specific energy
related measures with light duty vehicle miles traveled;
(2) What models or methodology exist to quantify the relationship in
(1) above;
(3) What types of data are required to evaluate the VMT/energy measure
relationship;
(4) Establish the availability of such data from Federal, state, and
local agencies.
The approach was to examine the VMT/energy problem in two different ways.
The initial attempt was to take the area of interest as one specific Air
Quality Control Region (AQCR), standard metropolitan statistical area (SMSA),
or single city to satisfy the study objective, i.e. a single sample area
consideration. The other, which evolved as an extension of the preceding
method was to consider a multiple area approach such that a number of regions
be considered simultaneously for examining the cause/effect relationship between
energy measures and VMT. This was not a planned alternative to the focus on
a single sample area approach, but evolved in course of attempting to identify
or categorize specific data for a correlation type model.
The approach to developing methods of quantifying and correlating the
energy related measures to light duty VMT is to use standard statistical
methods to establish linear or expotential relationships for single or mul-
tiple correlation analysis. This recommended methodology is included in the
Technical Approach of this report.
The findings, of this study indicate that the objective to develop a
method to quantify and correlate the effects of motor fuel shortages and con-
servation measures on light duty vehicle miles traveled is a formidable
undertaking for a specific single sample region or city. The reason for this
is that the necessary empirical data base to relate a given measure to a
related change in VMT is not available and must be acquired by a very compre-
hensive experimental information gathering program. Traditionally, the type
4
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of detailed information required, i.e. historical areawide VMT, auto occu-
pancy, transit ridership, origin distribution information, is nonexistent
to the level of detail such study demands. That is, to model travel choices/
decisions (in any given region) requires very detailed, comprehensive infor-
mation not normally collected.
The problem may be approached by considering VMT as having consumer demand
and supply characteristics. As with the case of all products or services con-
sumed, as the supply of available VMT declined with an attendant increase in
price, the consumer public reaction would be expected to (1) become more ju-
dicious in the consumption of VMT, for example, plan a number of trip types
together or carpool; (2) substitute available alternatives i.e. mass transit,
while (3) the supply side attempts to overcome the shortage, i.e. more trip
alternatives like park and ride, more small automobiles, etc.
The cause-effect relationship of a specific energy related measure and
a resultant VMT reduction requires an accurate model of the behavioral response
characteristics of the VMT consuming public. This can best be accomplished
by in-depth household surveys. However, it should be noted that the outcome
of the elasticity of VMT demand is unique for a given SMSA, city or AQCR
depending on such regional characteristics as public transit, degree of
urbanization or urban density and land use characteristics. It follows that
those areas of the country that have relatively good or adequate alternatives
to the private passenger car will respond totally differently than those that
do not. Therefore, it is concluded that change in VMT as a function of energy
related measures is so dependent on regional characteristics that even a
good VMT model has but limited application to areas other than the specific
region of original calibration. The above observations'in addition to a con-
sideration of the EPA objective to apply the results of a VMT/energy measure
relationship in numerous regions where the National Ambient Air Quality
Standards have been exceeded led to a somewhat different approach than the
single study area concept.
Rather than embark on a microscopic consideration of a single region
with the recognized need to collect substantial behavioral characteristics
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regarding trip and modal choice patterns, it was concluded that by considering
a number of areas, perhaps ten or more, the differences and similarities in
regional features will make it possible to understand and quantify the VMT/
energy measure relationship based on existing available data. This approach
can best be conceptualized by considering, for example, the geographical
variability of price and supply that has existed. The demand elasticity
of VMT with price can be assessed based on the level of available transit
service. A "good transit" city would be expected to demonstrate a greater
elasticity to price than a region with a "fair transit" system. By standard
statistical multiple correlation, these relationships are quantifiable.
Additionally, the non-availability of data in a given region can be offset
by the judicious selection of the number and kind of study areas to offset
these data gaps and therefore yield statistical significance.
Therefore, the study findings are:
(1) Current regional data bases are not adequate, i.e. not disaggregated
to the level of detail necessary to deal with the VMT/energy measure
impact relationship for a single SMSA, AQCR, or municipality study area.
Significant supplemental data acquisition/organization is reauired,
e.g. comprehensive survey "to ascertain behavior and decision
patterns regarding private car trip choices including odometer re-
cords. Additionally, most VMT measurements and transit ridership
data is incomplete to develop a reliable correlation model. The
EPA/DOT interagency sponsored project to.develop.a disaggregate be-
havioral model of urban travel demand (Charles River Model) is an
approach to such a detailed modeling project, however, the results
of this project will not be forthcoming for some time.
(2) The majority of data collected regarding the production, distribution,
consumption, and allocation of motor fuels is aggregated on a state,
regional, or Petroleum Administration for Defense (PAD) District
level. The difficulty acquiring this data was illustrated in the
hearings of Senator Jackson's sub-committee with the seven major oil
companies on the oil shortage question. The most successful approach
to getting this type of data for a sample city appears to be a survey
of a given region's service stations. However, the historical data
on fuel sales for the past several years is expected to be difficult
to acquire without cooperation of the principal motor fuel distributors.
(3) The shortcoming of modeling a sample city, AQCR, or SMSA appears to
be that once the model is calibrated and demonstrates reasonable
correlations of VMT/energy related measures, this relationship is
uniquely tied to the characteristics of that area. For example, a
good transit city like New Orleans would exhibit totally different
VMT demand elasticity than the often cited, auto dependent examDle.
of Los Angeles.
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(4) No single agency exists as a data base source or focal point of the
type of information necessary to assess the effects of energy-related
measures on light duty vehicle VMT. Experience during the period of
this study has shown that federal, state, local, and the private
sectors all have interest in and collect certain energy measure/VMT
related data. However, the type of data necessary to satisfy the
objective of such a program crosses several agencies' structures
both horizonally and vertically. The Department of Transportation
(DOT) and the Washington D.C. Council of Governments (COG) are
typical examples.
(5; There are considerable spin-off benefits for the EPA to acquire the
capability of assessing the energy measure/VMT relationship In
addition to evaluating energy conservation and allocation alterna-
tives for potential implementation as air quality improvement measures,
the data base of existing aggregated VMT/transit/fuel supply and
consumption will support such EPA activities as: (a) assessment of
the effectiveness of other transportation control measures and (b)
provide a basis for response to questions of policy i.e. to Federal
Energy Offical or Federal Department of Transportation.
Based on the findings of this study, it is recommended that EPA proceed
with a regional aggregated'approach (i.e. similar to the level of detail for
which the EPA transportation control measures have been applied.) for several
select cities or AOCR's with and without EPA promulgated transportation control
strategies. This project would consist of (a) assembling all existing available
data as identified by this study and expanded to include specific data types
and sources in ten or more candidate areas. (It should be noted that much of
the data was employed in developing the existing transportation control stra-
tegies and the activity becomes more of an organizing function than a gathering
or collecting effort); (b) utilizing EPA regional offices as the fundamental
source of the VMT/energy measure data. The region office activities would
involve the compilation of data for input to an EPA centralized facility and
participate in related local support activities. This approach fits well
into the regional office concept and is well suited to the performance of
such a data acquisition program.
7
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3.0 TECHNICAL APPROACH
The approach used in the performance of this study is to inventory and
categorize the data necessary to ascertain the relationship(s) between fuel
shortage and fuel conservation measures, and reductions in vehicle miles
traveled (VMT) as it impacts ambient air quality affected by transportation
related pollutants. The tasks can be summarized as:
(1) categorize data
(2) identify methods for quantification and correlation
(3) identify agency
(4) access data
(5) define additional data requirements and
(6) sample city selection.
The development of a model to quantify and correlate the changes in VMT
associated with all motor fuel conservation and allocation related measure
may be approached as follows. One method, as initially conceived, is to
concentrate on a given region or city and all related cause/effect inter-
actions that bare on light duty vehicle VMT within the study area envelope
plus certain external influences or exogenous valuables. The initial activ-
ity of this study pursued this concept in depth, the results of which will
be initially described. Subsequently, the multiple region method will be
considered. It should be noted that the multiple region approach evolved
as a rational solution to overcome the identified shortcoming in the single
area methods. This tack or line of thinking will be further developed.
3.1 DATA CATEGORIZATION AND- AVAILABILITY
In organizing a study for characterization of the types of information
necessary to evaluate the relationship(s) between those measures or conditions
which are attributable to the motor fuel availability or supply situation and
the resultant change in light duty vehicle VMT, it becomes readily apparent
that numerous, interrelated actions are simultaneously taking place and
8
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changing with time. This makes a very complex function between what is ob-
served as the dependent variable of change in VMT and the independent or
forcing variables.
A matrix of the data categories with sources necessary to perform cor-
relation analysis based on about 10 or more sample areas is presented in
Table 1. The supplemental data requirements are expected to be minimized by
selecting those sample areas that are best represented by existing data bases.
The specific supplemental data requirements are contigent upon an in-depth
examination of several candidate areas.
During the course of this study, a number of Federal agencies were con-
tacted for the purposes of acquiring the types of information that would be
available at the Federal level:
• Federal Energy Office
Energy Data and Analysis
Fuel Allocation Office
e Department of Transportation
\
Federal Highway Administration
Office of Energy Planning
Urban Mass Transportation Administration
« Bureau of Mines
Office of Mineral Information
0 Department of Labor
Cost of Living Council
• Internal Revenue Service
For example, the Office of Energy Data and Analysis of the Federal Energy
Office was questioned as to the availability of data for studies such as
this for the Environmental Protection Agency. It was discovered that the
specific type of data of interest to the Office of Energy Data and Analysis
was for the purposes of predicting short-falls of motor fuels at a national
level on a month-by-month basis. It was also pointed out that the objective
or mission of the Data Group in the Office of Energy Data and Analysis was
9
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Table 1 - ^ta Requi
rements and Sources
D ft T A
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not specifically addressed to distributing data, as such. Further inquiries
at the regional office level of the Federal Energy Office indicate that data
is available relating to allocation amounts for specific reference periods
from February 1972 through February 1974. However, it should be pointed out
that this information is generally available on a "need-to-know" basis and
that the most successful way of acquiring this information is through Environ-
mental Protection Agency's regional offices. This proved successful in ob-
taining this type of information on a state wide basis for energy related
work that is currently being performed for the EPA Region VI Office in
Dallas, Texas.
It should also be pointed out that because of the relative infancy of
the Federal Energy Office, information that would perhaps be forthcoming
in the near future was not readily available as input type information for
the purposes of study. Similarly, the Office of Mineral Information of
the Bureau of Mines supplied the type of information from their petroleum
specialists which suggests that specific types of data available in this
federal organization are demand and consumption figures on an annual basis
by PAD District. These are significantly larger than the areas of interest
considered applicable for this study. The Allocation Office of the Federal
Energy Office was also interviewed with regard to the types and kinds of
information that may be available regarding the fuel allocation measures
currently being implemented and it was noted that the Allocation Office
is primarily concerned with assisting those people or corporations who are
having difficulty acquiring necessary fuel supplies.
The Federal Highway Administration of the U.S. Department of Transpor-
tation, was querried regarding any additional work concerning their study
entitled Nationwide Personal Transportation Study dated April, 1972 to, in
fact, see if there was not any update to that planned for the future that
may be useable with regard to types of information used for the study. The
Department of Transportation is very interested in additional work in this
area but at the present time does not have the necessary funding and has made
statements to the fact that they would be interested in trying to acquire
some funding supDort from agencies like the Environmental Protection Agency.
11
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In addition, information was obtained from the Department of Transportation
regarding current research programs to expand capabilities of the Charles
Rivers Associates disaggregate travel demand model (joint project with the
Environmental Protection Agency), and to develop incentives and locator
services for carpooling. Discussions with the Cost of Living Council and
the Internal Revenue Service yielded no productive information that could
be used in this study. Since these agencies are generally regulatory and
only perform regulatory functions, there was no usable information relating
to the objectives of the study.
The American Automobile Association was very cooperative in supplying
gasoline availability information that is valuable on a regional basis;
that is, regions similar to the EPA region areas. Lundberg Surveys Inc.
was also contacted regarding the availability of their fuel price and supply
survey statistics. At a local level, inquiries were made at the District
of Columbia Department of Highways and Traffic regarding traffic count data,
the Metropolitan Washington Council of Governments, and the Washington
Metropolitan Area Transit Authority.
It can be concluded that the information required to perform a multiple
regional study approach is available. However, when such a program is ini-
tiated, part of the effort should be devoted to firming up some of the in-
formation channels that have been identified at this time. It is also con-
cluded that the most effective and productive way to access information from
other Federal agencies, either regional office or otherwise, is through the
formal requests of the Environmental Protection Agency since this approach
minimizes any difficulties of transmitting what might be publicly sensitive
information regarding fuel distribution/allocation activities and other
items reflecting Federal policies.
12
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3.2 SCALE OF ANALYSIS UNITS
It became clear during the course of our study that it would be possible
to measure VMT impacts of current fuel shortage conditions in several ways
depending upon the scale of the analysis unit chosen. Possible analysis units
identified were:
• Air Quality Planning Regions generally corresponding to urban area
or Standard Metropolitan Statistical Area (SMSA) boundaries;
• transportation analysis zones generally employed by regional planning
agencies for urban area analysis and corresponding to census tracts
or small multiples of tracts;
o individual households;
e major activity centers such as large employers, shopping centers, and
principal traffic generators;
« project-specific analysis areas adapted for on-going or recently com-
pleted transportation demonstration projects.
In each case, travel and trip making changes due to measured fuel supply
shortages and price increases would be estimated and subjected to various cor-
relation analysis for quantification of observed relationships. However,
review of alternative approaches has revealed significant differences in data
collection requirements and overlap with existing programs, as well as, we
believe, potential payoffs to the Environmental Protection Agency for proce-
dure development and air quality control plan updating. A synopsis of the
data requirements and analysis procedures for each approach is presented in
Table 2.
3.3 AIR QUALITY PLANNING REGIONS
As was outlined in the introductory sections, it is recommended that the
Environmental Protection Agency undertake fuel shortage impacts monitoring
at this analysis unit level. Most data input needs may be obtained from
available sources, although special counts may be required to assess car
pooling and vehicle mix changes. Additionally, as with previous research
analysis involving multiple cities, it may be difficult to characterize
inherent land use and socioeconomic differences among cities although failure
13
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TABLE 2
SUMMARY OF
TRAVEL IMPACT ANALYSES APPROACHES
!
ANALYSIS UNIT
AGENCY DATA INPUTS
ADDITIONAL DATA INPUTS
ANALYSIS
APPLICATION
I Ai r Qua I i ty
PIanning
Regi ons
•
•
•
•
Selected traffic counts
Average daily transit
ridership and supply
Historical VMT, popula-
tion, and related urban
development statistics
from 70 Census and
ongoing comprehensive
pianni ng
Fuel supply
•
Possible auto occupancy and
vehicle mix county at selected
screenlines
•
•
Relate areawide travel
characteristics, estimates
to regional fuel availability
and price data. Correlate
for urban areas throughout
nation.
Relate observed relationship
to household data.
•
0
Regional air quallty
plan development
Intermediate range
energy policy planning,
e.g., adequacy of current
bus fleet to absorb extra
ri ders.
II Transportation
Analysis Zones
•
«
•
•
•
Screenline traffic
count data
District trip matrices
by mode and purpose
(census, COG, WMATA)
Screenline or route
transit ridership
data
Transi t service data
expressed for planning
di stricts
Regional fuel supply
data
•
•
•
Screenline auto occupancy
counts
Possible special surveys of
gasoline pricing and
avai1abi1lty
Possible use of regional
information system, e.g.,
FHWA demonstration project
in Albuquerque, Fairfax
Co. (Washington, D. C. area)
•
•
•
Scale trip matrices to most
likely estimate of current
travel using screenline data.
Estimate trip generation,
trip length, etc. from trip
matrices and correlate changes
with fuel supply and transpor-
tation system variables.
Relate observed changes with
household data.
•
•
Establishes methodology
for continuing travel
monitoring for regional
planning (transportation,
air quality, energy]_
Regional air quality
plan development
III Household Panels
•
Selection and interview of
selected households for data
on:
VMT by auto
trip generation
atti tudes
changes in travel patterns
socioeconomic profile
•
•
Relate travel characteristics
with fuel supply and system
statistics
Verify relationships with
areawide data.
•
Same as II
IV Major
Activi ty
Centers
e
Traffic counts including
occupancy, bus use, etc., at
selected major employers,
shopping centers, residential
areas (Reston).
•
Correlate travel pattern
changes with attributes of
activity center.
•
•
0
Same as II
Complex source regulation
and control
Success of car pooling
programs
V Special
Studies
•
Coordinate with ongoing
demonstration programs
by others, e.g., Shirley
busway, Haddonfield
'dial-a-ride'
14
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to fully account for all differences in a statistical sense does not invali-
data the basic monitoring objective of the proposed program. Procedures
developed would be especially applicable for air quality control planning
purposes and useful for updating areawide strategies to account for current
VMT estimates and better understanding of modal diversion potentials.
3.4 TRANSPORTATION ANALYSIS-ZONES
Most urban areas have been subdivided into small analysis zones (corre-
sponding to census tracts or small combinations of tracts) for transportation
planning purposes in accordance with requirements of the Federal Highway Admin-
istration. Generally, extensive planning data bases are compiled and main-
tained for the zone reference system. The principal difficulty encountered
in every situation is the extensive data collection effort needed to maintain
current information on population, transportation system, and travel character-
istics at the zone level of detail. In fact, the initial data surveys in many
urban areas took 2-3 years or more to conduct, validate, and prepare for anal-
ysis. The requirements for an urban transportation planning data base have
been considered many times over the past 10-15 years. Two recent research
studies, one as part of the National Cooperative Highway Research Program
and the other for the Federal Highway Administration , thoroughly summarize
these requirements and provide a starting point for further specification.
The Urban Mass Transportation Administration is commencing major research to
develop computer software components for data base management application.
A major portion of the multi-million dollar BART Impact Study currently be-
ginning in the San Francisco Bay area will involve data base development and
updating for assessment of the regional travel impacts of BART. Primarily
in recognition of the scale of required data collection efforts needed to
15
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embark on a monitoring and analysis program for a single urban area, and
coupled with our view of the direct applicability of more aggregate regional
approach spanning varying conditions throughout the nation, it is recommended
that proceeding in this direction for fuel shortage impact monitoring be
dropped from further consideration at this time.
3.5 HOUSEHOLD PANEL
Transportation modeling in recent years has turned to disaggregate
approaches requiring travel pattern observations for relatively few households
as input for model calibration purposes, thereby avoiding extensive travel
surveys. Such an approach would be applicable in this case even though a
detailed population and transportation system characteristics data base would
still be required. Unfortunately, most urban areas have not developed dis-
aggregate travel models, and those that have been developed generally are
undergoing refinement and research. One such model for simulating urban area
travel patterns developed by Charles River Assoicates of Cambridge, Mass.
has been applied and tested using data from the San Francisco, Boston, and
Pittsburgh areas. Further research and development of the model is currently
being undertaken in a project jointly sponsored by the Federal Highway Admin-
istration and the Environmental Protection Agency aimed at identifying input
data requirements more fully and at introducing specific policy-sensitive
variables into the model structure. Hence, while approaching fuel shortage
impact monitoring through the development of household panels would provide
extensive information on trip making and auto ownership characteristics, it
appears that further research is needed to advance required analytical tech-
niques to operational status.
3.6 MAJOR ACTIVITY CENTERS
Measuring travel characteristics at major activity centers within metro-
politan areas would provide valuable information for detailed air quality
and traffic analyses of major traffic generators. It would be a meaningful
16
-------
approach in a context for treatment of complex source conditions, and addi-
tionally, applicable for areawide analyses to the extent that regional air
quality problems are often focused on specific locations within regions.
3.7 PROJECT-SPECIFIC STUDY AREAS
Many transportation demonstration projects are currently underway
throughout the United States with Department of Transportation funding. In
many instances, these projects involve extensive data collection and travel
monitoring aspects. Examples of on-going demonstration projects which might
be candidates under the scope of this study include the Shirley Busway pro-
ject in the Northern Virginia1 suburbs of Washington, D.C. and the Haddonfield,
New Jersey 'dial-a-ride' development program.
At this point in our study, the following conclusions were developed as
to the best course of action for EPA to undertake:
o a program to monitor travel characteristics in air quality planning
regions for fuel shortage impacts measurement as well as continuing
planning purposes would offer analysis potential with minimum special
data assembly and interpretations;
0 coordination with on-going projects to develop transportation planning
data base management and analysis capabilities centered on transpor-
tation analysis zones or individual households;
o development and refinement of air quality analysis procedures relating
to major activity centers;
o coordination with results of major transportation demonstration pro-
jects.
3.8 MULTIPLE REGIONS APPROACH
Our review of possible approaches to estimation of travel and air quality
impacts of current fuel shortages indicates that EPA should proceed immediately
to implement a program for monitoring data on a monthly basis from selected
or all air quality planning regions. This 'multiple regions' approach would
require compilation of aggregate areawide statistics, most of which can be
obtained easily although time lags may be experienced in certain instances.
Furthermore, by establishing such a program through the existing EPA regional
17
-------
office structure, the monitoring program would be a useful basis for con-
tinuing air quality plan updating and strategy refinement after the 'energy
crisis' has passed. For example, the President recently has proposed legis-
lation to provide major operating subsidy support.for transit operations which
appears likely to gain congressional support. If such a program were imple-
mented, it is likely that transit service would be enhanced in many urban
areas resulting in diversions from automobile usage and generating additional
air quality maintenance area (AQMA) plan requirements.
The remainder of this report section elaborates on the proposed multiple
districts approach considering:
e data requirements and sources
e analysis procedures
o implementation for continuing planning.
3.9 DATA REQUIREMENTS AND SOURCES
The following types of information would be obtained for each Air Quality
Planning Region (AQPR):
Automobile traffic volumes
Fuel availability
Fuel price
Transit availability and use
Highway system characteristics
Vehicle occupancy
Vehicle mix
Air quality
Land use and demographic characteristics
Transportation policy
Community attitudes
A summary of specific information items and their source is included in Table 3,
and will be further illustrated using the Washington, D.C. area as a case
example of data sources and availability.
1. Automobile Traffic Volumes. In the Washington area, the Metropolitan
Washington Council of Governments (MWCOG) maintains current regional
VMT estimates derived from their 1968 home interview travel survey and
updated on the basis of traffic count trends across selected cordon
18
-------
Table 3.
/un qmiTY planni.^g district monitoring system
1
1 Type of Information
I
Variables
Source
Remarks
Automobile Traffic
Volumes
Screenline traffic counts
State Highway or Transportation Dept.
County & Municipal Traffic or
Public Works Offices
Federal Highway Administration
Correlate VMT with permanent count
station traffic volumes
Fuel Availability
Gallons/barrels of gasoline
Average weekly gas station hours
American Petroleum Institute
Federal Energy Office
American Automobile Association
Gasoline sales tax information
Gasoline allocation statistics may
only be available by national
regi ons
Fuel Price
Trans11 Aval 1abi1ity
and Use
Cents per gal 1 on
Daily transit miles operated
Daily ridership
Average fares
Service area or route miles
Bureau of Labor Statistics
Cost of Living Council
Lundberg Survey Inc.
American Transit Association
Operating Properties
DOT 1972-74 National Transportation
Study
UMTA Transit Management
Division (/-ARE Project)
More detailed ridership or operating
statistics may be available in
selected areas.
Highway System
Characterise cs
Miles of Freeway
Miles of Arterial, etc.
Average parking cost (CBD &
non-CBD)
Regional Planning Agencies
FWHA Office of Urban Planning
DOT 1972-74 National Transportation
Study
Vehicle Occupancy
Vehicle Mix
Average auto occupancy at
selected locations
Distribution of vehicle types
and sizes
Field counts along major CBD corridors
or at selected major activity centers
Federal Highway Administration
Field counts
County & Municipal Traffic or Public
Works Offices
Vehicle registrations or sales data
Should be possible to monitor car pool
program activity.
Available data varies by area.
Air Quali ty
Pollutant levels at permanent
field stations
Regional Air Quality Control Agencies
Land Use &
Demographi c
Characteristics
Average journey-to-work time
Population
Percent reqional employment incBD
Census of Population
Regional Planning Agencies
GM Research Laboratories
Many variables could be introduced to
distinguish demographic & land development
characteristics of various urban areas.
Transportation
Policy
Capital grant assistance from
UMTA for transit development
(do!1ars per year)
Percent transit cost subsidized
Urban Mass Transportation
Administration
American Transit Association
Community Attitudes
Various
National Opinion Research Center
19
-------
Fi gure 2
SCREENLINE LOCATIONS
Washington, D. C. Area
-------
lines and screenlines throughout the area. Figure 2 shows the screen-
line locations used for VMT analysis purposes by MWCOG. Traffic
volume measurements would provide a reasonable basis for assessing
changes in regional VMT. Each of the jurisdictions in the Washington
area responsible for streets and highways makes, periodic or regular
traffic count checks at selected locations. For example, the D.C.
Department of Highways and Traffic maintains 51 permanent counting
stations throughout the District of Columbia (See Appendix A). Other
agencies with traffic count programs indludes the states of Virginia
and Maryland; Montgomery, Prince Georges', Fairfax, and Arlington
counties; and the cities of Alexandria, Falls Church, Rockville, and
Fairfax.
2. Fuel Availability. Information on gasoline supplies has been kept
for other reasons on a limited basis in the past. In California and
Texas, gasoline sales tax revenues are compiled by county for reim-
bursement purposes, and may be used to estimate actual supplies.
The American Petroleum Institute has maintained statistics on national
fuel supplies according to Petroleum Allocation Districts (PAD), seven
of which are defined to cover the continental Unites States (see
Figure 3). More recently, the Federal Energy Office has compiled
gasoline suddIv data on a state-by-state basis for allocation and
redistribution purposes. Another source of fuel availability sta-
tistics is the American Automobile Association's Fuel Gauge reports
(see Appendix B). These weekly reports summarize telephone inter-
views with service stations from all states regarding hours and
days of operation for the previous week as well as regional price
trends and economic conditions. For example, during the first week
in February, an estimated 24 percent of service stations located in
the District of Columbia were reported to be out of gasoline while
approximately eight percent of California stations had no gasoline.
3. Fuel Price. The Federal Labor Departments Bureau of Labor Statistics
conducts monthly 'cost of living' surveys for the Cost of Living Council
including service station surveys in 56 cities to estimate gasoline
prices. In addition, a Southern California organization, Lundberg
Surveys Inc., conducts gasoline price surveys in selected major urban
areas with results available by subscription (See Appendix C).
4. Transit Availability and Use. The principal single source for data
on both transit ridership and transit service levels is the American
Transit Association (ATA), located in Washington, D.C. Most of the
major transit properties in the United States, as well as large num-
bers of smaller ones, are ATA members and report operating conditions
to ATA on a regular basis. ATA provides the following information
services -- monthly ridership totals for member systems published
in Monthly Transit Traffic (see Appendix D); annual Transit Operating
Report summarizing annua! operating statistics for member systems;
and a weekly newspaper Passenger Transport providing descriptive
21
-------
PADS"
PAD V
PAD 2.
ro
ro
PAD ±
.r
1
Figure 3 National Petroleum
Allocation Districts
-------
information on recent federal capital grants, equipment replacement
and increases, fare changes, major service extensions, etc. In the
course of this study, contact was made with the Washington Metropol-
itan Transit Authority (WMATA), the agency responsible for bus oper-
ations in the Washington, D.C. area, to determine what Information
they might provide. WMATA supplied estimates of total ridership by
operating division based on revenue data as well as corresponding
statistics on number of buses in service and daily miles operated.
WMATA also makes periodic 'peak load point1 ridership counts on
selected lines which for points checked on a regular basis would be
an additional basis for assessing patronage trends. Similar data
would be available from other operating agencies and properties as
required to supplement ATA reports.
5. Highway System Characteristics. This information expressed as miles
of freeway, miles of arterial, etc. or in terms of average travel
speeds or trip lengths, if available or easily computed, is expected
to distinguish varying responses to fuel shortage conditions among
different urban areas possibly due to varying levels of auto dependency
and committment. In the Washington area, MWCOG can provide all re-
quired data items considered. Highway mileage information is also
available from the Federal Highway Administration, and 'journey to
work1 trip lengths may be estimated from 1970 Census tabulations.
Highway fatalities information as shown in Table 4 might also be
a data element for analysis and comparison. Interestingly, fuel
shortages and reduced speed limits have resulted in lower highway
accident rates.
6. Vehicle Occupancy. It will be necessary to conduct special counts
to establish changes which may be occuring due to car pooling and
vehicle sharing. Small sample counts along major commute corridors
and at selected major traffic generators will be adequate to identify
current patterns on a monthly basis. The difficulty in interpreting
vehicle occupancy trends will arise from the lack of pre-'energy
crisis' data, since 1970 Census 'journey to work' summaries providing
areawide occupancy averages for work trips is the only uniform source
for this data item. It may be possible to obtain some statistics
relating to increased activity in organized car pooling programs
which would provide some basis for developing historical patterns,
although the quality and availability of such data would vary con-
siderably from city to city.
7. Vehicle Mix. Information on new automobile sales as well as existing
fleet characteristics is compiled on a state and county level by
R.L. Polk and Company, and available for purchase directly from the
Chicago-based firm. In addition, vehicle mix counts should be taken
in conjunction with the occupancy checks described above, or possibly
made at selected parking areas in downtown and adjacent to major ac-
tivity centers.
23
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Table 4
HIGHWAY FATALITIES DECEMBER: 1972, 1973
Year States with
Lowered
Speed Limits
1972 1635
1973 1225
Other Total
States
3072 4707
2689 3914
% Change -25.1% -12.5% -16.8%
No. of States 18 32 50
ESTIMATED
TRAFFIC FATALITIES FOR
STATES ENFORCING LOWER SPEED LIMITS
State
December 1973
December 1972
Percent
Change
Alaska
5
4
+25.0%
Connecti cut
35
33
+ 6.0
Del aware
6
9
-33.3
Flordia
199
247
-19.4
Maryland
55
62
-11.3
Massachusetts
77
96
-19.8
New Hampshire
14
11
+27.3
New Jersey
102
120
-15.0
New York
154
285
-46.0
North Carolina
147
188
-21.8
North Dakota
5
15
-66.7
Oregon
41
45
- 8.9
Pennsylvania
203
281
-27.8
Rhode Island
6
12
-50.0
Vermont
10
10
0
Virginia
88
115
-23.5
Washington
53
61
-13.1
West Virginia
25
41
-39.0
Total
1,225
1,635
-25.17%
24
SOURCE: U. S, Department of Transportation,, _
National Highway Traffic Safety Administration
-------
8. Air Quality. A major element of the project analysis will involve
relating measured travel impacts to observed air quality levels.
Readings from air quality monitoring stations in urban areas are
readily available from local environmental agencies.
9. Land Use and Demographic Characteristics. Selected variables to
describe area wide land use and demographic characteristics would
be introduced to isolate fuel shortage response patterns in AOCR's
being monitored. Many variables would be candidates for use, and
most may be easily derived from 1970 Census summaries or data files
maintained by regional planning agencies. It should be noted that
it may not be possible to separate all localized land use and demo-
graphic influences from an analysis of fuel shortage impacts on
travel characteristics through use of generalized areawide variables,
such as those suggested. The development of exact statistical rela-
tionships devoid of these influences is not required for the success
of the project, and the decision to proceed with an AQPR monitoring
system should not be based on the prospects of developing such re-
lationships. The identification of conditions and/or areas which
do not fit generalized statistical patterns will be valuable output
of an implemented monitoring program as outlined in this report.
10. Transportation Policy. The development and promotion of alternative
travel modes depends to a large degree on local support and commit-
ment in this direction. It is proposed that information on local
transit subsidy levels, federal capital and demonstration grant
assistance amounts for transit system improvements and car pooling
programs, and similar policy-related data items be compiled and
incorporated into analysis as a determinant of modal shift sensitivities.
11- Community Attitudes. Appendix E includes excerpts from community
attitude survey tabulations prepared by the National Opinion Research
Center at the University of Chicago from their Continuing National
Survey. As shown, survey results have been developed by PAD allowing
comparison with general fuel allocation levels. A total of about
700 interviews are obtained every four weeks via carefully controlled
sampling procedures.
25
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Analysis Procedures
The proposed 'multiple regionsh approach to measuring travel impacts
of fuel shortages would involve analyzing monthly data from individual
air quality planning regions throughout the United States. Data items
as summarized in Table 3 and reviewed in detail in the preceeding section
would be required to:
o develop statistical relationships between regional VMT, and fuel
availability and price for different price and availability con-
ditions experienced in various parts of the country.
o correlate reductions in VMT with reductions in trip making and
diversion to other modes. It is expected that use of other modes
will depend on their relative availability.
o account for concurrent changes in transit fare and service policies,
parking rates, etc. as well as inherent differences in urban develop-
ment patterns among cities.
o relate air quality monitoring trends to measured VMT and associated
travel pattern changes for plan updating purposes.
The analysis and development of relationships for planning applications is
envisioned to encompass three steps as follows:
o plots and graphical tabulations — Figure 4 shows traffic count
data for selected major interstate routes compiled by the Federal
Highway Administration for January, 1974. Simple data tabulations
of this type will demonstrate where strong correlations may be found
for further detailed analysis.
o statistical correlation analysis — various hypotheses will be tested
to determine relative travel impacts of fuel shortage conditions for
varying transportation system characteristics and modal options. A
number of statistical processing routines for simple or time multi-
variate series applications, factor analysis, etc. are available for
use.
q calibration and application of TRANS model — this model developed
by the U. S. Department of Transportation, Office of the Secretary,
is designed for analyzing nationwide, multiregional transportation
policy impacts and would be particularly well-suited as means for
extrapolating observed fuel shortage impacts to related conditions
for air quality plan updating. A brief description of TRANS 1s
included as Appendix F.
After the appropriate data sources are identified and basic information
collected, a number of preliminary steps are needed to prepare the data for
analysis. A significant effort is required to place all the data sources
26
-------
into a common frame. For historical data, the same time periods,
frequency of data collection, and validity of data need to be ensured.
In areas where programs need to be established to collect data, careful
design of data collection procedures are required to maintain overall
compatability with other data sources.
Preliminary analysis of the data can be accomplished by simple
data tabulations and plots to identify obvious correlations of the data.
Here, one would identify if the changes in VWT regionally were correlated
to increases in auto occupancy or decreases in gasoline consumption, etc.
Implicit in this preliminary analysis is the assumption that simple cause
and effort relationships do exist and that the variables under study are
independent. In reality, any analysis of complex social systems exhibit
a high degree of interaction between variables.
The results of the preliminary regression analysis are intended
to indicate the appropriateness of pursuing additional statistical
analysis of the data. Multiple regression techniques allow estimation of a
dependent variable based on values for several independent variables.
Unique problems are encountered when using time-series data in multiple-
regression analysis, and special methods of analysis have been developed
to handle these problems. For example, in economic analyses, population,
income, overall economic activity, and many other social trends vary together,
especially when viewed over a considerable time period. In the present
situation, one would similarly expect that gasoline sales, auto owner-ship
changes, and transit ridership trends might vary together as well. Time -
series techniques treat this problem by separating the trend effects,
cyclical effects, and random effects, and treating each component separately.
A variety of computer programs have been specifically designed for performing
time-series multiple-regression analysis. Typically, these programs may be
used to generate ordinary least squares regressions of both levels and first
derivatives with respect to time.
Implementation for Continuing Planning
In order to best facilitate the implementation of such a plan as proposed
to meet the EPA study objective of inventory and characterizing data that will
27
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be required to ascertain the relationships between energy measures
(fuel shortages and fuel conservation measures) and subsequent reductions
in vehicle miles traveled, the following programatic outline is presented.
Because the EPA regional offices serve as the agency's principal representa-
tives in each region in contacts and relationships with federal, state, and
local agencies industry, academic institutions and other public and private
groups, it appears that the program described and presented herein can best
be implemented by using the regional office organization. The energy related
measures/VMT impact will be similar to the concept of the EPA regional office
activity concerning the transportation control strategies as well as the planned
air quality maintenance area programs and State Implementation Plan related
actions.
As a point of departure, the regional offices which have AQCR's that
require transportation control strategies should be initially involved in
the program i.e. the ten regional organizations of EPA. The fact that the
Federal Energy Office (FEO) is also organized on a regional basis that co-
incides exactly with Environmental Protection Agencies regions. In addition,
data being collected by such agencies as the American Automobile Association
(AAA) is collected on the same geographical boundaries as the EPA regional
offices supports the proposed program recommendation. In addition, to the
obvious benefit of the existing organizational relationships, the fact to
embark on such a program without using the regional office as an intergral
part, would entail a considerable expenditure of resources on the part of
the Environmental Protection Agency. The way the program is currently
envisioned as it would require only contractor assistance to the level of
planning and initiating the program based on a sample city in each regional
office which includes regional indoctrination into the program, objective
and benefits, the types and kinds of data for a sample city, in other words,
setting up a single sample city concept in each of the ten regional offices
to get the program underway. Actual maintenance and such continuation of
the energy related measure/VMT program would require a minimum of contractor
involvement. That is, selected cities would be the subject of this program
such that additional cities in the air quality control region could be very well
28
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handled by the regional office staff. For example, the transportation
control officer of each regional office.
In addition to the above considerations it should be also noted
that the EPA transportation control strategy planning process is a
continuing function is presented in Figure 5. That 1s to say that
urban change process is dynamic and must be under constant review and,
in addition, subject to national priorities which both impact a revision
of the EPA transportation control strategy and maintenance process. This
figure is to more or less demonstrate the dynamics of the situation.
Figure 6 summarizes the concept of regional office involvement as
well as the overall concept of the EPA transportation control strategy
data coordination effort that works through the EPA regional offices and is a
direct interaction with state, local, and other Federal agencies to bring
to bear EPA policy and transportation strategy positions.
In conclusion, the benefits and losses attributable to implementation
of particular transportation controls measures as related tq motor vehicles
fuel supply, distribution and demand, must be identified. The process must
recognize that social, community, environmental, and other external impacts
may be as significant as the transportation control measure impacts. The
planning process needs to identify the distribution of these impacts across
areas and interest groups so that public discussion and public information
may include consideration of impacts of alternative evergy related transportation
control measure actions. This can best be accomplished by using the current
EPA organization framework and the generation of EPA guideline procedures for
a program to begin to understand the complex relationships of control measure/
VMT changes.
29
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Figure 4
AVERAGE PERCENT CHANGE IN TRAFFIC VOLUMES FROM
SAME WEEKEND IH THE PREVIOUS YEAR
Weekend
Friday
Saturday
Sundav
Sat. & Sun.
1st Dec. 73/72
+3.5'
- 1.0
-18.2
-10.9
2nd Dec. 73/72
+1.8
+ 1.1
-18.2
-11.8
3rd Dec. 73/72
N/A
- 8.3
-28.8
-20.1
1st Jan. 74/73
-5.9
- 7.7
-26.2
-17.9
3rd Jan. 74/73
-6.2
-17.0
-23.4
-20.6
NOTE: These are updated data and supersede the first January survey.
10
PER CENT
INCREASE
0
10
PER CENT
DECREASE
2Q.
FRI
SAT
L
i§
y
/I
K.
4c
SUN
s + s
t= ^
• '//
V
f
\vc ^
\ !
IPf
L>-
N
Si/
Source: U. S. Department of Transportation, Federal Highway
Administration
30
-------
Figure 5
CONTINUING EPA TRANSPORTATION CONTROL MEASURE
PLANNING PROCESS
31
-------
-------
fiPPEKDIX A
DAYTIME TRAFFIC FLOW
AX
PERMANENT COUNTING STATIONS
Source: District of Columbia
Department of Highways
and Traffic
A-1
-------
TABLE 1. VEHICLE CLASSIFICATIONS AT PERMANENT COUNTING STATIONS, WASHINGTON, D. C.
DURING A 10-HOUR PERIOD BETWEEN 7:00 AM & 6:00 PM, WEEK-DAY, 1968
MAP
LOCATION
T C T A I
T OTAI VEHICLES
M».
PASS.
NO.
C AOS
susss
TRUCKS
1 iweouNO
OUTBOUNO
TOTAl
1 ,
t
Wisconsin Ave., N.W.
18,388
419
1,530
9,639
10,698
20,337
4
Bladensburg Road, N.E.
9,942
320
2,612
6; 587
6,287
12,874
11
Conn. Ave., N.W.
19,498
522
1,169
11,115
10,074
21,189
12
16th Street, N.W.
19,092
547
1,091
13,016
7,714
20,730
13
Rhode Island Ave., N.W.
17,673
453
1 2,422
i 10,766
9,782
20,548
14
13th Street, N.W.
11,439
814
878
7,439
5,692
13,131
15
"k" Street, N.W.
15,389
1,235
1,343
8,240
9,727
17,967
17
Penn. Ave., S.E.
18,939
828
1,795
11,672
9,890
21,562
19
Canal Road, N.W.
23,740
117
1,542
13,764
11,635
25,399
20
Mass. Ave., N.W.
25,261
594
1,209
14,656
12,408
27,064
21
13th Street, N.W.
14,562
67
875
8,517
6,987
15,504
22
Sherman Ave., N.W.
11,936
780
1,318
8,025
6,009
14,034
25
Washington-Baltimore Pkwy.
46,689
464
6,428
29,131
24,450
53,581
26
Kenilworth Ave., N.E.
36,870
166
5,477
21,850
20,663
42,513
30
Southwest,Freeway, S.W.
50,529
323
4,286
24,089
31,049
55,138
32
Anacostia Freeway, S.E.
27,123
98
4,028
15,380
15,869
31,249
34
North Capitol St., N.W.
14,530
44
1,576
'7,841
8,309
16,150
35
Wisconsin Ave., N.W.
20,266
555
1,929
10,904
11,846
22,750
36
Nebraska Ave., N.W.
15,779
207
959
8,856
8,089
16,945
37
Mass. Ave., N.W.
10,356
194
499
5,978
5,071
11,049
38
Conn. Ave., N.W.
19,509
198
1,067
12,307 :
8,467
20,774
39
Military Road, N.W.
18,266
221
2,163
10,223
10,427
20,650
40
Georgia Ave., N.W.
17,808
611
1,796
11,264 |
8,951
20,215
41
New Hampshire Ave., N.E.
12,295
288
988
7,353 i
6,218
13,571
42
Riggs Road, N.E.
18,229
107
2,585
10,267
10,654
20,921
43
Florida Ave., N.W.
12,484
278
2,450
8,659
6,553
15,212
44
Rhode Island Ave., N.E.
' 8,199
172
1,769
5,387
4,753
10,140
45"
Anacostia Freeway, S.W,
23,730
30
4,664
13,985
14,439
28,424
46
Alabama Ave., S.E.
9,727
239
827
5,068
5,725
10,793
47
Finey Branch Road,N.W.
9,389
25
644
5,019
5,039
10,058
48
Reno Road, N.W.
14,664
220
604
8,035
7,45?.
15,488
49
Rock Creek Pkwy., N.W.
20,202
13
44-
9,826
10,43.-!
20,259
50
16th Street, N.W.
18,131
244
1,220
10,478
9,u:'
19,595
51
East Capitol St., N.E.
5,007
117
385
' 2,980
2,52S1
5,509
52
"K" Street, N.E.
9,434
7
1,468
4,721
6,18£1
10,909
53
Kansas Ave., N.W.
6,362
89
716
3,787
3,38C1
7,167
54
Maryland Ave., N.E.
4,632
224
823
2,973
2,7061
5,679
55
Mass. Ave., N.E.
10,067
205
902
6,842
4,332
11,174
56
Michigan Ave., N.E.
18,560
611
1,676
11,034
9,813
20,847
IOTA I
684,696
12,646
69,757
397,673 !
t
36$, *2-
To"7,099
A-2
-------
Figure 1. Percentage Distribution of Vehicles by Type at Permanent Counting Stations and in
Geographic Sectors, Washington, Dv C., 1968
-------
TABLE 2. WERCZNTAGE DISTRIBUTION OF VEHICLES BY TYPE 7:T FEFJ4IUJENT COUNTING STATIONS, WASHIHSTOB, D. C. , Q. B.
DURING ft 10-HOl'R PERIOD BETWEEN 7:00 Ail K 6:00 PN ON A TYPICAL WEEK-DAY, 1968
MAP
PASS. CARS
BUSES
T
a u c
K S
BEF.
LOCATION
LIGHT
HE AW
*
COK0tWA?fr,3 j| TCVai TSUCIJ
NO.
IN
out
TOTAl
IN
OUT
TOTAL
IN
OUT
TOTAl
1 N
OUT
TOTAl
1 N
[ OUT
1
1 ^OIAl
X
?.
X
X
2
y.
*
%
X
1
*
*
I
1 ¦
Wisconsin Ave., N.W.
90.0
90.8
90.4
2.2
1.9
2.1
4.9
4.6
4.7
2.5
2.1
2.2
0.4
0.6
0.6
70
7.3
7.5
11
Connecticut Ave., N.W.
93.0
90.9
92.0
2.3
2.6
2.5
3.2
3.6
3.4
1.3
2.6
1.9
0.2
0.3
0.2
4.7
6.5
5.5
12
16th street, N.W.
93.4
90.0
92.1
2.2
. 3.3
2.6
3.2
4.5
3.7
1.2
2.0
1.5
0.2
0. 1
4.4
6.7
5.3
13
Rhode Island Ave., N.W.
86.4
85.6
86.0
1.8
2.7
2.2
5.9
6.3
6.6
4.1
4.5
4.3
0.8
0.9
0.9
5.1.8
u.e
U.8
14
13th Street, N.W.
88.7
85.0
87.1
5.2
7.5
6.2
4.2
4.5
4.4
1.7
2.6
2.1
0.2
0.4
0.2
6.1
7.5
6.7
IS
"K" Street, N.W.
85.1
86.1
85.6
7.1
6.7
6.9
4.7
4.1
4.4
2.4
2.4
2.4
0.7
0.7
0.7
7.8
7.2
7.5
19
Canal Road
95.1
91.6
93.4
0.5
0.4
0.4
2.3
3.9
3.1
1.7
. 1.9
1.8
0.4
2.2
1.3
4.4
0.0
6.2
20
Massachusetts Ave., N.W.
93.6
93.0
93.3
2.3
2.1
2.2
2.9
2.7
2.8
1.0
1.5
1.2
0.2
0.7
0.5
4.1
4.9
4.5
21
13th Street N.W.
94.4
93.4
93.9
0.5
0.3
0.4
3.2
4.7
3.9
1.8
1.5
1.7
0.1
0.1
0.1
5.1
6.2
5.7
22
Sherman Ave., N.W.
86.0
83.9
85.0
5.2
6.0
5.6
6.3
7.5
6.9
2.2
2.4
2.3
0.3
0.2
0.2
1 8.8
10.1
9.4
34
North Capitol St.. N.W.
90.6
89.4
90.0
0.4
0.2
0.3
4.6
5.4
5.0
>.»
4.3
3.9
0.9
0.7
0.8
9.0
10.4
9.7
35
Wisconsin Ave., N.W.
89.8
88.4
89.1
2.6
2.3
2.4
4.8
5.7
5.3
,S
2.5
2.2
1.0
1.1
1.0
7.6
9.3
e.5
36$
Nebraska Ave., N.W.
93.4
92.8
93.1
1.3
1.1
1.2
3.7
4.3
4.0
1.5
1.7
1.6
0.1
0.1
0.1
5.3
6.1
i-7 I
37
Massachusetts Ave., N.W.
94.3
93.0
93.7
1.6
1.9
1.8
2.8
3.1
2.9
1.1
1.8
1.4
0.2
0.2
0.2
4.1
5.1
4.5 j
38
Connacticut Ava., N.W.
94.7
92.8
93.9
0.9
1.0
1.0
3.1
4.4
3.6
1.1
1.6
1.3
0.2
0.2
0.2
4.4
».l 1
39fl
40
Military Road, n.«.
Georgia Ave., N.W.
U.)
89.2
68.T
86.7'
85.5
88.1
1.1
2.B
1.0
3.3
I-1
3.0
6.9
4.2
6.0
5.2
6.4
4.7
1.2
3.0
3-T.
3.9
-J"4
1.4
0.6
0.8
0.6
0.8
o.e
o.a
UB.t
a.o
10. J
9.0
8.9
43
Florida Ave., N.W.
B1.6
82.7
82.1
2.0
1.6
1.8
8.9
7.3
8.2
6.2
7.1
6.6
1.3
1.3
1.3
16.4
15.7
6.1
47
Piney Brcicli Road, N.W.
93.0
93.6
93.3
0.1
0.4
0.3
5.4
4.5
4.9
1.4
1.4
1.4
0.1
0.1
0.1
6.9
6.0
6.3
48$
Reno Road
95.3
94.1
94.7
1.3
1.6
1.4
2.5
3.3
2.9
0.8
1.0
0.9
0.1
0.1
3.4
4.3
3.9
4^
Rock Creek Pkwy.
99.7
99.7
99.7
0.1
0.1
0.1
0.1
0.1
0.1
0.1
0.1
0.1
0.2
0.2
0.2
50
16th Street, N.W.
92.0
93.0
92.5
1.3
1.3
1.3
4.8
3.6
4.2
1.6
1.8
1.7 .
0.3
0.3
0.3
6.7
5.7
6.2
53
Kansas Ave., N.W.
89.4
88.1
88.8
1.3
1.2
i.2
6.4
7.4
2.6
3.0
2.8
0.3
0.)
0.3
».)
10.7
0.0
TOTAl AVIRA9I !
91.2
90.5
90.6'
2.0
2.1
2.1
4.3
4.6
4.5
2.1
2.4
2.3
0.4
0.4
O.S
e.e
y.i
7.3
3 "Stations on Feieral-Aid Secondary foutes. F - Stations on Park System. All others are on Federal-Aid Prlaary Ron tee.
-------
TABLE 3. PERCENTAGE DISTRIBUTION OF VEHICLES BY TYPE AT PERMANENT COUNTING STATIONS, WASHINGTON, D. C., N. E.
DURING A 10-HOUR PERIOD BETWEEN 7:00 AM & 6:00 PM ON A TYPICAL WEEK-BAY, 1968
MAP
REF.
NO.
LOCATION
PASS. CARS
BUSES
T
IUC
K S
IN
OUT
TOTAL
IN
OUT
TOTAL
LIGHT
HEAVY
COMBINATION
TOTAl TRUCKS
IN
OUT
TOTAL
IN
Ou i
TOTAL
1 N
OUT
TOTAL
1 N
OUT
TOTAL
X
X
X
X
z
X
X
X
7.
X
y.
7.
X
V
X
X
X
4
Bladensburg Road, N.E.
77.0
77.5
77.2
1.9
3.1
2.5
10.5
10.2
10.4
8.4
7.3
7.8
2.2
1.9
2.1
21.1
19.4
20.3
25
Washington-Baltimore Pkwy.
88.6
85.4
87.1
0.7
1.1
0.9
4.7
5.9
5.2
3.6
4.6
4.1
2.4
3.0
2.7
10.7
13.5
12.0
26
Kenilworth Ave., N.E.
86.1
87.3
86.7
0.5
0.3
0.4
6.3
5.9
6.1
4.5
4.1
4.3
2.6
2.4
2.5
13.4
12.4
12.9
41
New Hampshire Ave., N.E.
91.0
90.1
90.6
2.1
2.1
2.1
' 4.6
4.4
4.5
1.8
3.1
2.4
0.5
0.3
0.4
6.9
7.8
7.3
42
Riggs Road, N.E.
87.7
86.6
87.1
0.4
0.6
0.5
6.1
7.1
6.6
4.7
4.2
4.5
1.1
1.5
1.3
11.9
12.8
12.4
44
Rhode Island Ave., N.E.
81.9
79.7
80.8
1.7
1.7
1.7
9.6
10.9
10.2
5.4
6.0
5.7
1.4
1.7
1.6
16.4
18.6
17.5
51
East Capitol St., N.E.
90.4
91.5
90.9
3.2
0.8
2.1
3.4
4.6
4.0
2.9
2.6
2.7
0.1
0.5
0.3
6.4
7.7
7.0
52
"K" Street, N.E.
84.5
88.0
86.5
0.1
0.1
0.1
8.1
6.8
7.4
6.5
4.4
5.3
0.8
0.7
0.7
15.4
11.9
13.4
54
Maryland Ave., N.E.
82.9
80.1
81.6
2.7
5.3
3.9
5.0
4.4
4.7
3.3
3.3
3.3
6.1
6.9
6.5
14.4
14.6
14.5
55
Massachusetts Ave., N.E.
92.2
86.8
90.1
1.5
2.5
1.8
4.0
6.0
4.9
2.1
2.1
2.1
0.2
2.6
X.l
6.3
10.7
..X
56
Michigan Ave., N.E.
89.1
89.0
89.1
3.0
2.8
2.9
4.5
5.3
4.9
3.0
2.7
2.8
0.4
0.2
0.3
7.9
8.2
8.0
TOTAl AVIRAOC
86.5
85.6
86.1
1.6
1.9
1.7
6.1
6.5
6.3
4.2
4.0
4.1
1.6
2.0
1.8
11.9
12.5
12.2
Count Locations on 1) Federal Aid Primary Routes t 4 - 25 - 26 - 41 - 44 - 51 - 52 - 54 - 55 - 56
2) Federal Aid Secondary Routes ¦ 42
-------
TABLE 4. PERCENTAGE DUSTRIBUTION OF VEHICLES BY TYPE AT PERMANENT COUNTING STATIONS, WASHINGTON, D. C. , 3. W-
DURING A 10—HOUR PERIOD BETWEEN 7:00 AM & 6:00 PM ON A TYPICAL WEEK-DAY, 1968
MAP
PASS. CARS
BUSES
T
R U
C K S
REF.
LOCATION
LIGHT
H E AVY
COMBINATION
TOTAL TRUCKS
NO.
IN
OU T
TOTAl
IN
OUT
TOTAL
IN
OUT
TOTAl
1 N
OUT
TOTAL
1 N
OUT
TOTAL
IN
OUT
TOTAL
7
X
7.
X
X
X
%
X
y.
X
X
X
X
X
X
X
X
X
30
Southwest Freeway
93.0
90.6
91.6
0.3
0.8
0.6
3.0
3.5
3.3
2.8
3.7
3.3
0.9
1.4
1.2
6.7
8.6
7.8
45
Anacostia Freeway
83.6
83.4
83.5
0.1
0.1
0.1
6.4
6.6
6.5
6.9
7.1
7.0
3.0
2.8
2.9
16.3
16.5
L6.4
TOTAL AVERAGE
88.3
87.0
87.6
0.2
0.5
0.3
4.7
5.0
4.9
4.8
5.4
5.2
2.0
2.1
2.0
11.5
12.5
L2.1
Count Locations on 1) Federal Aid Primary Routes : 45
2) Federal Aid Secondary Routes : 30
-------
TABLE 5. PERCENTAGE DISTRIBUTION OF VEHICLES BY TYPE AT PERMANENT COUNTING STATIONS, WASHINGTON, D. C., S. E.
DURING A 10-HOUR PERIOD BETWEEN 7:00 AM & 6:00 PM ON A TYPICAL WEEK-DAY, 1968
MAP
PASS. CARS
BUSES
T
R U
C K S
REF.
LOCATION
IIGHT
HEAVY
combination
TOTAL TRUCKS
NO.
IN
OUT
TOTAl
IN
OUT
TOTAL
IN
OUT
TOTAl
IN
OUT
TOTAL
IN
OUT
TOTAL
IN
OUT
TOTAL
X
X
X
X
X
X
X
7.
X
X
%
X
X
X
X
X
X
*/
17
Pennsylvania Ave., S.E.
89.0
86.5
87.8
3.8
3.9
3.8
4.4
5.6
5.0
1.9
2.7
2.3
0.9
1.3
1.1
7.2
9.6
8.4
32
Anacostia Freeway
84.3
89.1
86.7
0.2
0.4
0.3
5.4
4.8
5.1
6.7
2.7
4.7
3.4
3.0
3.2
15.5
10.5
13.0
46
.
Alabama Ave., S.E.
90.4
90.0
90.2
2.3
2.1
2.2
4.6
4.2
4.4
2.5
3.3
2.9
0.2
0.4
0.3
7-3
7.9
7.6
1
TOTAL AVERAGE
87.9
88.5
88.3
2.1
2.1
2.1
4.8
4.9
4.8
3.7
2.9
3.3
1.5
1.6
1.5
10.0
9.4
9.6
Count Locations on 1) Federal Aid Primary Routes : 17-32
2) Federal Aid Secondary Routes : 46
-------
TABLE 6.
PERCENTAGE DISTRIELTTIGN OF VEHICLES BY TYPE AT ALL PERMANENT OO'JiJTIViG STATIONS, WASHIWGTC^, D. C.
DURING A 10-HOUR PERIOD BETWEEN 7:00 AM & 6:00 PM ON A TYPICAL WEEK-DAY, 1968
Note: Potomac and Anacostia Bridges not included.
-------
2
A.M. P.M.
TIME
Eigure 2. Hourly Variation of Vehicles by Type at.Permanent
Counting Stations, Washington, D. C., 1968
A-9
-------
45.0
3»
i
V)
ut
s
3
o
>
u
u.
u.
<
at
3
0
X
1
o
u
ex
in
a.
35.0
25.0
150
5.0
TIME
Figure 3. Comparison of Hourly Variation of Truck-with Total Traffic at
Permanent Counting Stations, Washington, D. C., 1968
-------
APPENDIX B
American Automobile Association
Fuel Gauge Report
B-l
-------
AMERICAN AUTOMOBILE ASSOCIATION
8111 Gatehouse Road • Falls Church, Virginia 22042
703/AAA-6332
For Immediate Release
AAA Fuel Gauge Report II - No. 6
For Information: Call 703-AAA-6332
NORTHEAST, NORTHWEST, MID-ATLANTIC
AREAS 'WORST' FOR GAS, AAA REPORTS
WASHINGTON, D. C. , Feb„ 20 -- The Northeast, Northwest and Mid-
Atlantic areas of the country again appear to be most disrupted by gasoline
shortages, the American Automobile Association's sixth nationwide FUEL
GAUGE REPORT indicates.
This week's AAA spot check of 5,325 stations in all states but Alaska
showed that fuel conditions deteriorated slightly more in those three areas
than did the nation as a whole.
Increasing numbers of service stations are operating on self-imposed
daily gallonage quotas, closing pumps when quotas are met, or are staggering
pumping hours between early morning and late afternoon shifts.
Such practices are common in New England, New York, Illinois, Hawaii,
Louisiana, Oregon and the Washington, D. C. metro area.
(More)
-------
areas "worstM/2/2/2/2
In general, difficulties in finding gasoline available are more pronounced
in metropolitan areas than along major travel routes in outlying rural locations,
the AAA survey shows.
The national scene at a glance:
-- 28% of stations contacted are pumping fuel after 7 p.m. weekdays,
compared with 31% last report.
-- 14% pumping after 9 p.m. weekdays, 15% did last week.
-- On Saturdays, 26% pump fuel after 7 p. m. , down from 28% last week,
and 10 pump after 9 p.m. , compared with 11% last report.
-- 11% open Sunday, down from 12% last week.
-- 10% out of fuel when contacted, no change from last report,
-- 29% limiting purchases to motorists, compared with 28% last report,
mainly by 10 gallon or $2-$5 amounts,
There is some hope, however, that the situation may improve as the
Federal Energy Office announced yesterday additional increased February
allotments for hard-hit states. Virginia and New Jersey will receive a 3%
increase over the original 2% increase announced Feb. 9.
Alabama, Arizona, Georgia, Nevada, New Hampshire, Oregon, Vermont
and West Virginia will receive 5% increases.
Connecticut, Florida, Indiana, Massachusetts, Missouri, New York,
Pennsylvania and Rhode Island will receive 2% more fuel.
B-3
(More)
-------
areas "worst"/3/3/3/3
Meanwhile, more states reportedly have adopted or will shortly adopt
modifications of the Oregon odd-even license tag gasoline distribution plan. The
plans are in effect voluntarily in the District of Columbia, Pennsylvania,
Massachusetts, New York, Washington, North Carolina, South Carolina, New
Hampshire, some counties of Florida including Sarasota, Dade, Broward and
Palm Beach, as well as Oregon.
In Maryland, Virginia, New Jersey and Hawaii (rationing is in effect in
Hawaii County), the distribution odd-even system is mandatory. The New
Jersey plan is mandatory for out-of-state travelers as well as residents;
Virginia's is mandatory for drivers in areas of other states contiguous
Virginia and the Maryland plan is mandatory for motorists in other jurisdictions
having reciprocal agreements with the state -- primarily Washington, D. C. and
Northern Virginia. Although New Hampshire's plan is voluntary, it also applies
to out-of-state motorists.
Five turnpikes also have adopted variations of the Oregon plan. New
Jersey Turnpike made this policy mandatory for New Jersey and New York
State residents, however, motorists from any other state can purchase $1
worth of gas on any day. Garden State Parkway's policy is mandatory for all
motorists whose state is affected by the odd-even plan. J. F. K. Memorial
Highway's policy is mandatory for local traffic, but out-of-state motorists
can purchase $2 worth of gas on any day. New York State Thruway and
Pennsylvania Turnpike policies are in effect for all cars, but it is voluntary
at this time.
B-4 (Mo
-------
areas "wor st"/4/4/4/4
Most dealers along virtually all major turnpikes contacted are limiting
purchases from a low of a single $1 to a high of 10 gallons. Toll tickets are
marked on the New Jersey Turnpike so motorists can get gas at one station
only. New Jersey Turnpike authorities warned under state law that it is illegal
in New Jersey to carry gasoline in automobiles anywhere except in the gas tanks.
Violators are subject to fine and imprisonment.
Only the Ohio Turnpike reports no limits on gas purchases.
New Jersey, Oklahoma and Florida Turnpikes report stations operating
24 hours a day, seven days a week.
The Delaware Turnpike reports only one station is open over the week-
end and it is limiting purchases to $1.
Pumps on Pennsylvania, New York State, Ohio, Indiana Toll Road,
Kansas, Garden State Parkway and J. F. K. Memorial Highway are closed
from 9 p.m. Saturday to at least midnight Sunday.
Pumps on the Illinois Tollway are closed from 9 p.m. Saturday to
midnight Sunday and during the rush hours, 6:30-9:30 a. m. and 3:30-7:30 p. m. ,
Monday through Friday.
Vermont and Mississippi reported the highest average price for regular
fuel -- 53 cents -- and both states reported the highest average price for premium
grade --57 cents. Rhode Island had the lowest average price for regular gas,
46 cents, and Texas again reported the lowest price for premium, 50 cents.
A regional breakout of fuel availability conditions by state and region
follows:
B-5
2/74
-------
Date: February 20, 1974
REGION_l_
Total
Stations
Called
Major
Ind.
Open
Mon.-Fri.
after 7 pm
Open
Saturday
after 7 pm
Open
Sunday
Limiting
Purchases
Out
of
Fuel
Conn.
51
46
5
_ _
1
35
7
Me.
39
36
3
11
11
1
21
4
Mass.
50
36
14
1
1
—
23
4
N.H.
58
53
5
3
1
3
31
6
R.I.
43
41
2
„ _
1
36
7
Vt.
37
32
5
3
20
3
TOTAL:
278
244
34
15
13
9
166
31
REGION 1 OUTLOOK: ^ stations contacted pump fuel after 7 pm weekdays compared
with 10% last week. 4% sell after 9 pm weekdays, little change. On Saturdays, 5%
sell after 7 pm, little change, and 1% sell after 9 pm, down from last week's 4%.
3% pump fuel on Sundays, no change. 11% out of fuel when contacted, a drop from
last report's 14%. 60% limiting purchases compared with 71% last report, mainly to
10 gallons or $2-$5. Average price for regular, 49.8premium, 54.4£. Supplies low
in Mass., Conn., and R.I. The Mass. odd-even plan lets tourists with out-of-state
plates buy daily. Purchase limits standard practice throughout New England. Most
stations pumping gas mornings until daily quota reached. Others stagger hours.
REGI0N_2
Total
Stations
Called
Ma jor
Ind.
Open
Mon. - Fri.
after 7 pm
Open
Saturday
a f te r 7 pm
Open
Sunday
Lim i tinu
rchaops
Out
n I
I'uel
N.J.
78
75
3
2
2
1
45
17
N. Y.
175
167
8
30
18
4
76
29
TOTAL:
253
242
11
32
20
5
121
46
REGION 2 OUTLOOK:
13% of stations contacted pump fuel after 7 pm weekdays, little
change from last week. 4% sell after 9 pm weekdays, no change. On Saturdays,- 8%
are selling after 7 pm, little change, and 3% sell after 9 pm, little change. 2%
pump fuel on Sundays, compared with last week's 4%. 18% out of fuel when contacted,
an improvement over last report's 21%. 48% limiting purchases compared with 51%
last report, mainly to 10 gallons or $2-$5. Average price for regular, 50$; premium,
54£. Lines in New Jersey have decreased due to odd-even plan. In New York,13% of
stations operating on daily quotas, and 37% report situation "bad."
B-6
-------
Date: February 20, 1974
REGI0N_3_
Total
Stations
Called
Major
Ind.
Open
Mon.-Fri.
after 7 prr
Open
Saturday
after 7 prr
Open
Sunday
Limiting
Purchases
Out
of
Fuel
Del.
47
41
6
6
3
1
30
4
D. e.
77
77
8
2
28
8
Md.
27
23
4
5
2
--
8
4
Pa.
250
216
34
84
80
19
100
96
Va.
104
91
13
12
13
5
52
17
W. Va.
77
64
13
12
10
3
19
15
TOTAL:
582
512
70
127
108
30
237
144
REGION 5 OUTLOOK. 22% of stations contacted pump fuel after 7 pm weekdays compared
with 28% last week. 9% sell after 9 pm weekdays, decrease from last week's 11%. On
:aturdays, 19% sell after 7 pm, (23% last report) and 6% after 9 pm, little change.
% pump fuel on Sundays, little change. 25% out of fuel when contacted, 5% more than
last week. 41% limiting purchases compared with 32% last report, mainly to $2-5. Average
"irice for regular, 49£ ; premium, 53$. Region shows slight worsening; exception is Pa.
'ith better outlook; in D.C., 43% stations closed Saturdays, most close by noon weekdays.
„dd-even plan voluntary in D.C., Pa.; mandatory in Md., Va.
REGI0N_4_
Total
Stations
Called"
Ma jor
Ind.
Open
Mon.-Fr L.
after 7 pm
Open
Saturdav
after 7 pm
Open
Sunday
L i m iti nn
Pure hasps
Out
of
Pup 1
Ala.
7
5
2
--
1
4
Fla.
285
227
58
57
41
20
84
46
Ga.
148
120
28
67
61
24
27
7
Ky.
111
104
7
63
63
38
29
2
Miss.
40
35
5
15
15
4
8
1
N. C.
212
181
31
5
4
3
134
41
S. c.
70
63
7
6
3
1
36
10
Tenn.
83
74
9
37
35
8
28
10
TOTAL:
956
809
147
250
222
98
347
121
REGION 4 OUTLOOK: 26% of stations contacted pump fuel after 7 pm weekdays compared
ith 30% last week. 14% sell fuel after 9 pm weekdays, little change. On Saturdays,
23% sell after 7 pm; last week 27%, and 10% after 9 pm, no change. 10% pump on Sundays,
nittle change. 13% out of fuel when contacted; 15% last week. 36% limiting purchases
ompared with 31% last report, mainly to 10 gallons and $2-5. Average price for regular,
,9£; premium, 53$. Odd-even plan improved situation in major Fla. cities, but supply
nroblems exist along lower east coast. Conditions fair in Orlando, Miami, West Palm Beach
nd Ft. Lauderdale. N.C. situation tight.
B-7
-------
Date: February 20, 1974
REGION_5
Total
Stations
Called
Major
Ind.
Open
Mon.-Fri.
after 7 pm
Open
Saturday
after 7 pm
Open
Sunday
Limiting
Purchase::
Out
o f
I'unl
111.
80
74
6
--
--
2
62
8
Ind.
129
90
39
81
80
43
3
1
M i ch.
171
148
23
76
74
2
36
14
Minn.
57
48
9
36
29
5
8
--
Ohio
198
151
47
114
106
27
18
4
Wis.
75
61
14
27
21
8
27
2
TOTAL:
710
572
138
334
310
87
154
29
REGION S OUTLOOK: 47^ q{. stations contacted pump fuel after 7 pm weekdays compared
with 54% last week. 22% sell after 9 pm weekdays, 14%less than last report. On Sat-
urdays, 44% sell after 7 pm compared with 55% last report, and 15% sell after 9 pm-
down from last week's 19%. 12% pump fuel on Sundays; 14% last week. 4% out of fuel
when contacted; last report, 6%. 22% limiting purchases compared with 15% last report,
mainly to $2-$5 amounts. Average price for regular, 50; premium, 53$. In 111., 78%
of stations report limiting sales and none contacted open after 7 pm Mondays through
Saturdays. Long lines becoming more common in region Friday nights through Sunday.
Stations reducing pumping hours, increasing prices. Supply outlook fair to good.
REGI0N_6_
Total
Stations
Called
Major
Ind.
Open
Mon.-Fri.
after 7 pm
Open
Saturday
after 7 pm
Open
Sundav
L irn i ting
Purchases
Out
o f
Fuel
Ark.
22
19
3
3
4
1
4
l
La.
62
44
18
19
20
9
5
6
N.M.
40
32
8
15
15
6
2
3
Okla.
53
46
7
20
21
" "12
16
6
Tex.
319
251
68
71
68
17
76
53
TOTAL:
496
392
104
128
128
45
103
69
REGION 6 OUTLOOK: 9^ 0f stations contacted pump fuel after 7 pm weekdays compared
with 22% last week. 11% sell after 9 pm weekdays, little change. On Saturdays, 26%
sell after 7 pm compared with 29% last report, and 7% sell after 9 pm, little change.
9% pump on Sundays, little change. 14% out of fuel when contacted, an increase over
last report's 5%. 21% limiting purchases compared with 19% last report, mainly to 10
gallons or $2-$5. Average price for regular, 48.1C; premium, 51.4£. Virtually no
changes except La. where stations sell daily quotas, then close for rest of day.
More stations out of gas in Texas and Sunday closings up 10%.
B-8
-------
Date: February 20, 1974
REGI0N_7_
Total
Stations
Called
Ma ior
Ind.
Open
Mon.-Fri.
a f te r 7 pm
Open
Saturday
a 1 tor 7 pm
Opon
Sunday
1. inti t i no
l\j rchasr:'
(Hit
^1
Fuel
Iowa
49
44
5
32
35
14
5
--
Kans.
45
28
17
15
11
4
13
Mo.
45
40
5
24
23
15
1
--
Neb.
50
42
8
23
22
11
2
--
TOTAL:
189
154
35
94
91
44
21
--
REGION 7 OUTLOOK: crvV , . . . . , , , .
50% of stations contacted pump fuel after 7 pm weekdays, compared
¦ith 52% last week. 24% are pumping after 9 pm weekdays; no change from last week. On
'aturdays, 48% sell gas after 7 pm compared with 51% last report, and 17% sell after
9 pm; little change. 23% pump fuel Sundays, compared with last week's 19%. None out of
uel when contacted; 2% last report. 11% limiting purchases; little change, mainly to
.0 gallons and $2-$5. Average price for regular, 49<:; premium, 53£. 85% of stations
contacted report fair to good supply outlook, 13% report poor.
REGI0N_8
Total
Stations
Called
Major
Ind.
Open
Mon.-Fri.
after 7 pm
Open
Saturday
after 7 pm
Opon
Sunday
r. i rn i t i nq
Purchaser.
Out
0 1
1 uo 1
fnl o.
40
28
12
17
15
23
3
Mont.
59
43
16
42
41
12
N. D.
117
64
53
91
86
16
2
2'
S. D.
56
45
11
26
26
17
6
1
Utah
58
45
13
45
44
15
3
Wyo.
27
25
2
23
21
13
--
TOTAL:
357
250
107
244
233
... 96
14
3
REGION 8 OUTLOOK: 0f stations contacted pump fuel after 7 pm weekdays, no change.
38% sell after 9 pm weekdays, decreased from last week's 42%. On Saturdays, 65% sell
after 7 pm, little change, and 29% sell after 9 pm, down from last week's 32%. 27% pump
fuel on Sundays, compared with last week's 21%. 1% out of fuel when contacted, little
change. 4% limit purchases; little change, mainly to $2-$5. Average price regular, 49$;
premium,53<£. All states report fair to good outlook. Wyo. again appears in best shape,
S. Dak. worst. Some stations report able to pump because business is slow, but still
expect to run out before end of month. Possible trend of stations in remote resort areas
rotating so at least one is open each Sunday.
B-9
-------
Date: February 20, 1974
REGI0N_9
Total
Stations
Called
Major
Ind.
Open
Mon.-Fri.
after 7 pm
Open
Saturday
after 7 pm
Open
Sunday
Limiting
Purchases
Out
of
Fuel
Ariz.
105
82
23
19
9
9
46
6
cai.
857
799
58
210
177
124
207
39
Hawaii
16
16
. _
_ _
¦» -
Nev.
20
18
2
7
8
6
1
__ _
TOTAL:
998
915
83
236
194
139
254
45
REGION 9 OUTLOOK: 0/)0/ c ^
24% of stations contacted pump fuel after 7 pm weekdays compared
to 19% last week. 11% sell after 9 pm weekdays, an increase from last week's 6%. On
!aturdays, 19% sell after 7 pm — 16% last report. 10% sell after 9 pm; 7% last week,
^4% sell on Sundays; 21% last week. 5% out of fuel when contacted, little change. 25%
limiting purchases compared with 29% last report, mainly to 10 gallons or $2-$5. Average
irice regular, 50$; premium, 54£. Fair to good conditions in Cal. and Nev., but more
tations closing Sundays. S. Cal. generally better shape than N. Cal. Ariz, conditions
poor to fair. Hawaii's odd-even plan resulting in some shorter lines, stations sell
.n early a.m. hours, no weekend sales.
REGION_10
Total
Stations
Called
Major
Ind.
Open
Mon.-Fri.
af to r 7 pm
Open
Saturday
a f te r 7 pm
Oppn
Sunday
Limiti nq
Purchases
Out
(J (
lur-l
Ida.
59
48
,11
19
20
13
--
--
Ore.
296
271
25
18
12
17
87
27
Wash.
151
133
18
13
14
9
52
13
TOTAL:
506
452
54
50
46
"39
139
40
REGION 10 OUTLOOK: stations contacted pump fuel after 7 pm weekdays; little
change. 5% sell after 9 pm weekdays, little change. On Saturdays, 9% sell after 7 pm;
little change, and 4% sell after 9 pm, little change. 8% sell on Sundays, little change.
8% out of fuel when contacted , no change. 27% limiting purchases; no change--mainly to
10 gallons or $2-$5. Average price regular, 51<:; premium, 53$. Of 128 stations contacted
Dn 1-97, 1-26, and Highway 101, only 2% open after 7 pm weekdays and Saturdays, none
after 9 pm. All these stations report poor outlook, 51% limiting purchases. In Portland,
5% of stations contacted out of fuel but 75% sell between 8 am and 12 noon weekdays.
Elsewhere within "the state 36% of stations are open between 6 am and 10 am weekdays,
31% closed Saturday.
B-10
-------
APPENDIX C
Selected Reports Prepared by Lundberg Surveys Inc.
C-l
-------
D
¦ E
R
G. In-J'i'. iy i: -J..:ioii
Ti.L'-D:r i>. Inc.
1 2'j :) -jrn I
U. Hr '.i-- C,\ 'jrj'j5
(213) J jl II
Account
bv,;; 00g
Da:.o December 28, 1973
Publir.iwcl Fridays
RETAIL PRICE OF PREMIUM GRADE GASOLINE. 12/21/73
DIFFERENTIAL
Numb*f of
SfQllQ'H-
Suevtyf d
MAJORS
frieon Prico
pnr Gallon
cents
Cheng* from
Lost Reading
conli
.
Numtxr of
Stations
Surveyed
NOEPENDENTS
Mean Price Cbongo from
per Gallon Lotl Rtoding
Ctnit ctnli
Bttwttn Major* d lnd«pand«nta
Chongo trom
C«nf» Lot( Riding
p«f Gollon c,nU
ins ANGfcLES
3,487
4f.ft7
~
.31
334
45.63
~
.58
7.74
-
.27
LANCASTER
78
48. 87
~
• IS
12
45.63
-
.25
3.24
~
.40
E SCONDion
75
4 7.96
~
.26
9
44.56
+
.47
3.40
-
.'t
SAN 1)1 F00
<.*">5
48.19
~
.n
41
45.06
~
.29
3. 1 V
-
.16
SANTA BARBARA
I SB
50* 1 *3
.28
28
46.28
.01
3.91
-
.63
THOUSAND OAKS
6S
47. 53
~
.10
3
46.40
~
.67
1.13
-
.79
SACRAMENTO
302
4R.64
~
.09
69
45. 74
~
.60
2.90
-
.51
STOCKTON
19S
49. 34
~
.20
53
46. 6B
~
.76
2.66
-
.56
NAPA
4"i
48.00
.OS
10
44.81
~
.57
3.19
-
• 6 7
SAN JOAQUIN
4?9
49.00
~
.31
93
46.25
~
.72
2. 75
-
.41
SAN FRANCISCO
I, 546
49. 52
~
.33
173
45.78
*
. 70
3. 74
-
.37
MORCAN HILL
90
49. B3
4
.19
10
46.32
*
.40
3.51
-
. ?1
PAL P SPRINGS
16
SO. 73
+
.52
1
43.90
*
.00
6. «3
~
.57
California
6,939
40.50
+
.29
836
45.79
*
.6?
2. Tl
—
.33
PHOENIX
419
46. 31
-
.08
29
44.28
*
.82
7.03
-
.90 .
TUCSON
167
46.26
.24
17
44.91
~
.64
1.35
-
.40
NEVADA
ho
49 . 7 6
~
.32
30
46.42
~
.47
3. 34
-
.15
SF AT Tl. E
<331
47.87
4-
.13
96
45.58
*
.23
2.29
-
.10
PO^T L ANO
666
4A.0L
f
.30
113
45.55
t
.44
2.46
-
. 14
SPOKANE
Ifl 1
47.60
4-
.52
53
46.8?
~
.98
.78
-
. 46
SALEM
139
48. 39
~
.52
29
44.79
~
.20
3.60
~
. 3?
B01SF
11K
49.60
V
1.18
26
47.55
~
V .61
2.0*
-
.43
YAKIMA
73
50.85
4-
.14
14
50.41
1,00
.44
-
.86
SALT LAKE CMY
4 215
47.14
~
1.28
85
44.78
~
V.84
-
•56
WASHINGTON, OC
M 699
4fl. 93
~
1.7S
37
46.95
2.03
1.98
-
.?«
MlLWAUKtt
M '92
47.09
~
) . 78
72
43.90
~
1.4V
3. I'l
~
. 71
ATLANT A
M 316
48.
•f
1 .55
73
45.36
~
1.90
2.89
-
. 35
NtW YORK
M lr>?
49. 14
~
2.0*
13
.47.71
~
2.78
1.43
-
. 74
HAHYL ON
M 529
46*04
~
2.14
44
47.86
*
2.39
. 9ft
-
. 25
NEW ORLEANS
M »75
46.55
~
1 .46
28
42.47
~
1.82
4.0*1
-
. 36
"Last KoadinK"
Service stations ore surveyed twice monthly,
exce)>t cities marked M, which are surveyed
moil t li 1 >-.
C-2
Ki i>' i'i.' c, I Ol', *vt>ui tl Milim'» u'tn'n i!M(V>
Al 11» i wM ,<•«!' | v,i i r. > iiicn nwh, ,n y < m *(tor. by ?">
,» •' i i Ovtut " <•' I»* Mu'iu'w of put ill Ji»m «. Ivy K ,«<•' r Irrul.u l. ,it». »\.
• 11 <• r •. » M Mil f'« I I »• Mill' ' I .<>> I »t HM\ hv lh«J Mll'i 11 1, .M «' t»»t f ¦ Ml I («•>).
r.fi'.iV J ««» Clii'.lt.iK I uii.liiMiJ, I'.r I III t(i'"t k.'iin»'tl) |i, Co<, I lo.f'i. iinri I'l.'u (.ni'iim, Lnaioi An.ily.r Joroimt !.> Iiu<.hliir, PHP L'litor. Hereon
i*i »ii • ,.lr j I >••• 11» H 1 <' 11 • i
R n k ' JjCk k»
-------
sfaspka! vap i atiri'i IN r.A>oi imp r,.M i nn^,? Mini..
A'.
I 7
C h
r i
' r>
_LL_
1 f
* ?
v Y
I «.
v' L/
uc
" T
vri
i";
u r
VS
kc
MD
i;W
S'.l
N'-t
M7
my
r »
g.\
» I
SC
SO
T\
T y
TTT"
vt
v ^
TT5~
MI
uv
WY
PFRCfiNT OF YEAR'S SALES IN EACH MONTH, BAStO ON 1967-1972 DATA
¦ !.VI
' ¦'¦ A 3
7.17
7.t.i
¦» . i '¦
7. M
7. 7/,
7.0'-
6.60
7. -'0
9.11
7. ! 3
7.9',
f . 5 ">
7.2 3
7. 36
6.64
1. '.S
i.
6. 2 7
7 ¦ 7 7.
7. ?2
7.3 7
7. 31
7
7 . 5->
7.AT
7.12
6. = 3
7. 36
7.23
1 0
14
OA
no_
c5
31
55
7.29
7.01
JLuZ3_
7.61
7.'-6
6. f-9
7.f'2
rirr
7. -34
7. 04
7.39
*.oa
7. 4 5
6. 93
7.
7._l;L
i
6.2 7
h. i i
7. ,'V,
6 . *
6. -17
6.84
7. ?P
7.10
7.7 0
6 • h 7
7. 1 5
6. 95
£.88
6. '•o
^« 71.
6. 4 I
7. 12
5. 52
6. 79
7.11
6. 90
6.53
-L.-U-
~7T 2?J
6. 92
A. 90
7.02,
• 7.15
6. RO
5.94
6. 76
6 . 0Q
3 H
3 .'^7
8.48
7. 79
Q-.I5_
o . o
R . OS
" . CO
7.63
7. 8i
_7J^7
7.or
8.37
7. 36
rr?r
T7KT
7.06
6796
6.66
7. 06
5.41
7.95
8.26
6. 30
7.81
APR
"W
7.67
1.38
-rtvr^
7.58
7.64
6.31
7.28
0. 3 4
. o L_
R . 0 3
8.09
7.50
7 . Q8
8.05
S. 23
8. 19
>;. i. q
H ."0 9
8.77
7 . 6 6
JUG.2-
8 . 2 4
8.3 2
8. 54
7.(15
a.24
7.08
_LJ?JL
7.6 7
8.20
R. 14
0.19
8.57
7.87
_7_^oa_
7. 4
7 .76
7.59
6". 04
a.u
7.80
8.03
8.25
7.4V
3. A 3
8T7"«~
"7. y r
7. 34
8.10
"STmT
7.51
e.i5
6.62
MAY
8.13
¦-1.7?
n # & o
";V<)4
P .6 I
JL.J-L.
8.26
° . 73
3.23
f1 5_
. '"W
9. '.6
n . 58
8. 6 3_
9.05
8.91
8.8 3
J.H
9.63
8.63
8. 1 A
8.99
8.75
8.59
8.51
8.57
0.71
8 - 0 . 7^:
a.53
8.A8
8.A6
TTTTu"
8 .26
8.58
ir.7r5"~
8.77
8.90
T.«7
m
9.72
8.73
__9.1i_
e. 6 »
8.69
o. 30
H 3
8.70
¦8.33
l'. 5 3_
fl . 'i \
9.18
9 . ',5
0.*.7 G_
8.8 8
8.OP
9.11
_e t6 3_
9.^,7
0.85
9.10
_a^.o.
8.90
8.98
0. 7 1
9.«_7Q_
9.05
8.84
9.'.6
_JU.8-Z_
ft. 7 7
9. J 6
9. 4 7
—3.^75-
0.S9
9.13
9.20
_fl . CtJ_
(!. 7 3
8.97
9.98
8 . 36
nV'to
^tps
9.59
9.03
iT76r^
9.39
9.10
1 0.60
i 0.42
3 . 6?
3 ,/?2_
.1 .
8.^0
8 1
.44
i.23
fl.41
Q 01
id '•* 'i ~
9 .00
10.26
JS^IL
8.61
9.09
9 . 75
__8.,27_
8.64
S.72
10.74
9 .58
9.02
O.10
10.16
8.83
10.16
_L D.^SL.
8.<15
9.5 8
10.05
9.. 13_
0 .68
8.22
9. 52
P . R2__
a. 84
9.17
11.14
8.90
'ill TT
9.53
9_jJ 6
~~9.20"
9.50
8.61
.12 ,68 ,
-A1KL
10. 04
9.14
3 ,_26_
a.')r:
n«•"* ?
i o; i b
8. l-
8.53
Q.6 9
S . 5 5
3CL
Q . <;-)
>' . 7 (>
10.86
?
9.0 1
9. 2°
9.16
9. 1 3_
9. 26
0.07
10.98
_9.-2.S_
9.68
9. 16
8. 76
JLU„95_
9. 50
8. 86
12.63
_1.D«33_
9 . 2 t
9 . 8 0
10. 24
9^1 H_
0. 79
9.24
10. 1 1
_c'^25_
9.04
9.20
11.17
8 . 89_
l> - i'S
Ttrrai
10. 30
8*87
9. 82
9. 54
_13 • lil_
<;fp
10. 21
0 . 24
_a. 29.
S. 18
8.33
8. 73
A.3 5_
8.24
3 4
7.99
p • ?2
h.""'} ')
8 . .'9
9.0V
8.24
8. 57
8 . ?4
__.a,.06_
8 . 3 4
8 . i 4
8. 74
8. 73
8.24
8.6R
903_
8.35
8. 36
•10. 03
8. ?6
U. 54
8.90
8.43
8.48
8.90
0.,3-L
8.47
7.99
8.64
8. 81
-av/r
8.60
_9-tZiL
8.49
8.41
8.65
.9.52-
..Of.I.
MOV
8.15
8. 50
_9.08_.
8.3 5
8.3 9
8. S4
,_52_
S. 4h
a.37
8.18
8 . 4 -
B. 52
8.24
7.91
L_
8.3 3
8.36
7. 8 4
8.44
-jcor
8. 1 8
8^3L_
8. t6
8.34
8.39
ft.81
.JlEI
7, '.9
C.4T
8. 5 4
8.25
a, *>
A. 7<-""
P. 35
P.. ° 1
7_
u . .,
7 . 1
7.42
n .
8 o"4 d
8.10
3.3-3
_£. 6 a_
8 . 6 r)
8 . 4 2
fl.o:
8.30
9.24
_J . ? 7_
7.'. 3
c. 5
7 . 0-#
I. • > 7
«.' 0
7 . "i 5
^ L_
ti . t- i
c. w
7.3 9
_f . * l_
o • 'J c
e.59
7.23
ft . 6 I)
h.'ll
8.05
8 , 4 5_
"¥. 2 I
8.20
8.09
. ca
-------
CMl FOKNlA
CHEVRON
EXXON
GULF
^C?I L
PHILLIPS
SHELL
TEXACO
'JfJ! ON
MAJORS
MINORS
TOTAL
DFALCR BUYING PRICE REPORT - REGULAR GRADE
TOTAL
PR ICE
READINGS
873
1,091
<~55
425
780
263
1,072
840
886
6,828
822
7,650
OBSERVED
PE TAIL
AVERAGE
PRICE
L44. 9 5
?44. 76
L43.91
L44.20
L44.68
L45.65
L45.80
~45-87
?44. 18
44.77
L41.95
44.46
ACTUAL
UBP
23. 00
22.40
21.40
21.85
22.40
24. 00
23.57
24.60
20.40
22.60
19.80
22.31
ACTUAL
DE ALER
MARGIN
8. 80
9.20
9.40
9.25
9. 10
8.40
9.03
8.10
10.70
9.00
9. 10
8.99
CALIFORNIA 12/21/73
RETAIL LEVEL .
{TOLERANCE OF ~ OR - .2 CENTS! "
% AT
8.5
14.0
12.3
2. I
2.2
20.2
13.3
8.0
8.9
11.2
9.5
11.0
X ABOVE
81.1
81.9
78.5
94.4
77.9
71.9
eo. i
60.0
88.7
77.9
80.3
78.2
* BELOW
10.4
4 . 1
9.2
3.5
19.9
e.o
6.5
32.0
2.4
10.9
10.2
10. 8
O
l
-P»
* LOW LEAO
L - LEAOED
~ - COMPANY MARKETS BOTH LOW-LEAD AND LEADEO REGULAR IN DIFFERENT MARKETS
t - THESE PERCENTAGES DEMONSTRATE THE INCIDENCES OF DEALERS AT, ABOVE, OR BELOW, THE COMPANY-OPERATED-STATION
RETAIL. PRICES Or THEIR SUPPLIERS' OWN OUTLETS.
-------
Prices are ex-taxes FOB THE RACK. (0.55(i is ususl local haul)
LAST WEEK THIS WEEK
CHANGE
GREATER LOS ANGELES
regular
premium
19.119
21.182
19.450
21.527
+00.331
+00.34 5
SAN FRANC I SCO/BAY
regular
premium
18.093
20.953
20 .402
21.900
+01.50 9
+ 00 . 9-17
SACRAMENTO
regular
premium
19.086
21.055
20.900
22.400
+01.814
+01.345
SAN DIEGO
regular
premium
19 .444
21.514
19 .722
21.801
+00.278
+ 00 . 2G7
FRESNO
regular
premium
20.001
22.061
20.987
22.998
+00.9SG
+00.937
BAKERSFIELD
regular
premium
20.270
22.163
20.865
22.718
+00.595
+00.555
PORTLAND
regular
premium
21.051
22.526
21.051
22.526
+00.000
+00.000
SEATTLE
regular
premium
21.051
22.526
21.051
22.526
+00.000
+00.000
PHOENIX
regular
premium
21.623
23.346
21.985
23.606
+00.3G2
+00.260
BOISE
RENO
regular
premium
regular
premium
22.025
24.268
22.883
22.980
22.025
24.268
22.883
22.980
+00.000
+00.000
+00.000
+ 00 .000
LAS VEGAS
legular
premium
22.016
24.007
22.016
24.007
+00.000
+oo.ouo
C-5
-------
G,"- 5 5 > r> r*
v > kj i £ i * v.' i » w ; < ^
Weekly Ocm^iic Roviu.:/v V:o:''jr/,i-:..i nr.;! Inventories, 1073 and 1074
PAD DISTRICT I
GALLONS
Millions I
REFiMEi-'iY PRODUCTION
WEEK OF JANUARY II
300
200
100
1973
1974
/
I I07c
0 *
-10
-eo
Ja« P«b Mar
.J I I I I ,1 1 1 l-LU-
Aor. Moy June
i t i t i i j j__i .i.i.,,j
Jill* Ac? Sep
J Li. i t \ i i it I I
Oct Nov. 040
I ,i l J—t t »lt< tt
Porccnt Chancie: 1973 to 1974
T"
INVENTORYa! Ryfinarigs, O-jik Terminals SiinPbolincs
Billions
+107,
0
-10
-20
K — —
1973
1974' '
7
1 Jor» r«b. Wor
Apr Voy Juno
July Aug Sip
Oct. Hoy, P»o-
i Pe i
cent Chango
: 1973 to 197'
*
3
WEEKS SUPPLY Ratio of inventory to Product/on
10
v\
wv
^1974 ^
j\i 973
/if
V
V
Ml
^ V
A ;
-------
APPENDIX D
American Transit Association
Monthly Transit Traffic Report
D-l
-------
VOLUME 50
American Transit Association (CATA
JANUARY 28, 1974
TRANSIT INDUSTRY TRAFFIC
CURRENT MONTHLY TRENDS - REVENUE PASSENGERS (ESTIMATED)
1973 1972
465 L'Enfant Plaza West. S.W
Washington. D.C. 20024
Robert Sloan, Executive Vice-President
NUMBER 1
DECEMBER (FINAL)
NOVEMBER (FINAL)
446,932,000
¥+8,029,000
444,842,000
444,l8l,000
CALENDAR COMPARISONS (NUMBER OF DAYS)
0.1+7$ INCREASE
0.86% INCREASE
DECEMBER
NOVEMBER
i?T3
1972
1972
1972
WEEKDAYS (MON. - FRI.)
* 15
20
21
21
SATURDAYS
* 5
5
1+
4
SUNDAYS
* 5
5
4
1+
HOLIDAYS
* 3 (MON.
1 (MON.)
1 (THURS.
) 1 '
* SEE ATTACHED
& TUES.
)
REVENUE PASSENGERS CARRIED ON TRANSIT
SYSTEMS OF THE
UNITED STATES IN ]
DISTRIBUTED BY POPULATION GROUPS DURING THE 12 MONTHS
ENDING DECEMBER ;
PORJLATION GROUPS -
(1970 CENSUS)
DECEMBER
12 MONTHS ENDING 12/31/73
1973
(THOUS)
% CHANGE
FROM 1972
1973
(THOUS)
% CHANGE
FROM 1972
CITIES OVER 500,000 (TOTAL)
325,365
+ 0.31
3,809,702
" 0.99
RAPID TRANSIT LINES
138,995
- 1.11
1,423,685
- 2.60
SURFACE LINES
186,370
+ 1.39
2,386,017
- 0.01
250,000 - 500,000
53,632
- 0.64
682,039
+ 4.44
100,000 - 250,000
21,453
+ 4.33
228,836
+ 0.60
50,000 - 100,000
15,196
+ 0.62
174,852
- 2.36
LESS THAN 50,000
8,939
+ 13.81
103,937
+ 2.72
TOTAL ALL CITIES
424,585
+ 0.64
4,999,366
- 0.18
SUBURBAN
22,347
- 2.74
294,329
- 2.85
GRAND TOTAL
446,932
+ 0.47
5,293,695
- 0.33
D-2
FOR EXCLUSIVE USE OF AMERICAN TRANSIT ASSOCIATION MEMBERS
-------
Note: TYils chart reflects changes In the Transit Traffic Index and not the actual
month-to-month percentage changes reported In "Current Monthly Trends" shown on
page 1. The Index corrects for seasonal variations and the number of working days
in the month. The average level of revenue passenger traffic In the years 1964 -
1968 is taken as 100 and the Index figures reflect the change from that base period.
CITIES OVER
600.000
UNITED STATES
100,000 - 500,000
LESS THAN
100,000
D-3
-------
CURRENT MONTHLY REVENUE PASSENGER TRAFFIC - INDIVIDUAL TRANSIT SYSTEMS
DECEMBER AND NOVEMBER 1973 AND 1972
(INCLUDING REPORTS RECEIVED UP TO MORNING OF JANUARY 28, 197*0
NOTE: (1) ALL REPORTS ARE LISTED ALPHABETICALLY BY CITY.
(2) % CHANGE IS BASED UPON COMPLETE FIGURES.
THE FIGURES SHOWING % CHANGE FROM PREVIOUS YEAR MAY BE AFFECTED TO SOME EXTENT
BY CALENDAR CONDITIONS. SEE "CALENDAR COMPARISONS" ON PAGE ONE.
DECEMBER 1973
NOVEMBER 1973
CALENDAR
YEAR 1973
REVENUE
-------
CITY AND SYSTEM
DECEMBER 1973
NOVEMBER 1973
CALENDAR
YEAR 1973
REVENUE
PASSGRS
(THOUS)
<% CHANCE
FROM
1972
REVENUE
PASSGRS
(THOUS)
% CHANGE
FROM
1972
REVENUE
PASSGRS
(THOUS)
% CHANGE
FROM
1972
~CHICAGO (ILL.) TRANSIT AUTHORITY
SURFACE LINES
22,11*3
- 2.U
22,871
- 0.1
272,937
- 0.3
RAPID TRANSIT LINES
7,815
- 2.6
8,033
- 0.1
95,383
- 3.5
CHICAGO, ILL. - OTHER SYSTEMS
SOUTH SUBURBAN SAFEWAY LINES, INC
S*CINCINNATI, 0. - QUEEN CITY METRO (e)
1,563
+ 19.1
1,995
+ 1+6.7
19,217
+ 11.6
~CLEVELAND (0.) TRANSIT SYSTEM - TOTAL
6,788
- 12.1
7,050
- 11.3
85,297
- 10.1+
CLEVELAND, 0. - OTHER SYSTEMS
SHAKER HEIGHTS (0.) CITY OF, D. 0. T
306
- 3.8
308
- 1+.5
3,668
- 5.8
COLORADO SPRINGS (COLO.) COACH COMPANY
COLUMBIA, S.C. - SOUTH CAROLINA ELECTRIC
AND GAS COMPANY
3 b6
- 6.7
361+
+ 2.1
U,352
- 2.3
S*COLUMBUS (0.) TRANSIT COMPANY (f)
820
- 33
CORPUS CHRISTI (TEX.) TRANSIT SYSTEM
15U
+ 1.2
17I+
+ 1.6
1,961
- 1+.1+
DALLAS (TEX.) TRANSIT SYSTEM
1,969
+ 3.6
2,232
+ U.5
25,696
- 1.9
DAVENPORT (IA.) CITY LINES, INC
DAYTON, 0. - MIAMI VALLEY REG. TRANS. AUTH.
651
- 1+.8
672
+ 7.5
7,391
- 5.2
DECATUR (ILL.) CITY LINES, INC
S DENVER (COLO.) METRO TRANSIT
1,705
+ 11.2
1,661+
+ 2.9
18,628
+ 10.8
*DES MOINES, IA. - IOWA REG. TRANSIT CORP...
309
- 15.3
DES PLAINES, ILL. - UNITED MOTOR COACH 00..
26U
+ 6.7
*DETROIT, MICH. - SOUTHEASTERN MICHIGAN
TRANSPN. AUTH. - LAKE SHORE DIVISION.. (G)
lll+
- 7.1
10l+
- U.l
1,^55
- 6.8
S DULUTH (MINN.) TRANSIT AUTHORITY
291
319
- H+.6
3,368
- 15.U
DURHAM, N.C. - DUKE POWER COMPANY
226
- 7.6
251
- 7.3
3,01*6
- 5.1
EAU CLAIRE (WISC.) TRANSPN. COMPANY
EDMONTON (ALTA.) TRANSIT SYSTEM
EL PASO (TEX.) CITY LINES, INC... (H)
ERIE (PA.) METROPOLITAN TRANSIT AUTH (A)
1+06
+ 11.1
1+10
+ 8.2
l+,2l+9
+ 6.0
EUGENE, ORE. - LANE TRANSIT DISTRICT (i)
195
+ J+9.7
171+
+ 59.2
1,580
+ 86.6
S EVANSTON (ILL.) BUS COMPANY (j)
EVERETT (WASH.) TRANSIT SYSTEM (k)
35
- 31.2
FITCHBURG (MASS.)&LEOMINSTER ST. RWY. CO..
81+
- 7 2-
100
+ 0.2
1,023
- 1+.6
FORT WORTH, TEX. - "CITRAN" CITY TRANS. SER
358
- 2.7
372
- 3.h
b,033
- 9-2
GALVESTON (TEX.) TRANSIT COMPANY
GRAND RAPIDS (MICH.) TRANSIT AUTHORITY
131
- 1.6
136
- 0.7
1,52U
- 5.2
GREENSBORO, N.C. - DUKE POWER COMPANY
163
- 6.8
168
- 5.6 ¦
2,01+2
- 5.3
GREENVILLE (S.C.) CITY COACH LINES, INC....
151+
- 21.3
165
- 11*.5
2,091
- 13-3
GRETNA, LA. - WESTSIDE TRANSIT LINES, INC..
~HALIFAX (NOVA SCOTIA) TRANSIT CORP
91+1
+ 6.8
HAMILTON (ONT.) STREET RAILWAYS
2,308
+ 1.6
2,1+31
+ U.l
25,953
+ 6.3
HAMMOND, IND. - CHICAGO & CALUMET DISTRICT
TRANSIT COMPANY, INC
-------
DECEMB1
2R 1973
NOVEMB]
SR 1973
CALENDAR
YEAR 1973
REVENUE
% CHANGE
REVENUE
% CHANGE
REVENUE
-------
DECEMBER 1973
NOVEMEER 1973
CALENDAR YEAR 1973
REVENUE
% CHANGE
REVENUE
% CHANGE
REVENUE
"jo CHANGE
CITY AND SYSTEM
PASSGRS
FROM
PASSGRS
FROM
PASSGRS
FROM
(THOUS)
1972
(THOUS)
1972
(THOUS)
1972
NEW ORLEANS (LA.) PUBLIC SERVICE, INC,
5,639
- 5-5
5,801
. - 1.8
69,318
- C.4
NEW YORK CITY (N.Y. ) TRANSIT AUTH- - TOTAL.
121,911
- 3-5
124,539
- 3.1
1,471,842
- 4.2
SURFACE LINES
31,929
- 0.8
32,742
- 0.7
382,036
- 2.2
RAPID TRANSIT LINES
89,981
- 4.4
91,797
- 3.9
1,106,130
- 3.0
NEW YORK CITY, N.Y. - OTHER SYSTEMS
MANHATTAN & BRONX SURFACE TRANS. OP. AUTH
28,316
- 0.7
S*FORT AUTHORITY TRANS-HUDSON CORPORATION..
2,936
- 8.2
2,986
- 8.0
30,031
- 25.5
NORFOLK, VA. - TIDEWATER METRO TRANSIT..(p)
1,566
+ 6.4
OAKLAND, CALIF. - AC TRANSIT (q)
4,459
+ 4.0
OMAHA, NEB. - METRO AREA TRANSIT
ORANGE COUNTY (CALIF.) TRANSIT DISTRICT.(?)
224
+283.2
219
+282.7
1,601
+216.5
*ORANGE COUNTY, CALIF. - LA HABRA
DIAL -A -RIDE
10
10
94
*OTTAWA (ONT.) CARLETON REG. TRANS. COMM
3,900
+ 9.6
3,933
+ 15.3
4l,8o8
+ 11.4
PHILADELPHIA, PA. - SOUTHEASTERN PENNSYL-
VANIA TRANSPORTATION AUTHORITY - TOTAL(A)
20,564
+ 4.4
24,881
+ 0.5
SURFACE LINES
15,327
+ 5.2
18,581
+ 0.3
RAPID TRANSIT LINES ..
5,237
+ 2.1
6,301
+ 1.0
PHILADELPHIA, PA. - OTHER SYSTEMS
PORT AUTH. TRANS. CORP. OF PA.& N.J.-RT
PHOENIX (ARIZ.) TRANSIT CORPORATION
S PITTSBURGH, PA. - PORT AUTH. OF ALLEGHENY
COUNTY . . (S )
5,672
- 25.9
8,271
+ 5.5
90,5^1
+ 0.8
PORTLAND, ME. - GREATER PORTLAND TRANS. DIS
PORTLAND, ORE. - TRI-COUNTY METROPOLITAN
TRANSPORTATION DISTRICT OF OREGON, (T^
1,582
+ 3-7
1,540
+ 3-3
18,356
+ 6.4
PROVIDENCE, R.I. - RHODE ISLAND
PUBLIC TRANSPORTATION AUTHORITY.
1,371
- 5.1
1,414
+ 0.2
15,994
+ 1.0
PUEBLO (COLO.) TRANSPORTATION COMPANY
QUEBEC (QUE.) URBAN COMMUNITY TRANSIT COMM.
2,2b2
- 2.1
2,1+98
+ 0.1
RALEIGH (N.C.) CITY COACH LINES, INC
181
- 3.1
226
+ 0.1
2,467
+ 1-5
-^RICHMOND, VA.' - GREATER RICHMOND TRANS. CO.
ROANOKE, VA. - ROANOKE CITY LINES, INC
ROCHESTER, N.Y. - REGIONAL TRANSIT SERVICE.
ROCKFORD (ILL.) MASS TRANSIT DISTRICT
202
+ 15.6
195
+ 5.3
2,054
+ 6.0
ROCK ISLAND - MOLINE (ILL.) CITY LINES
SACRAMENTO (CALIF.) TRANSIT AUTHORITY
SALT LAKE CITY, UTAH - UTAH TRANSIT AUTH...
339
+ 12.8
324
+ 9.1
3,590
+ 10.1
S SAN ANTONIO (TEX.) TRANSIT SYSTEM (u)
1,569
- 1.3
1,308
- 19.1
19,583
- 3.2
*SAN DIEGO (CALIF.) TRANSIT CORPORATION
1,950
+ 30.0
1,988
+ 23.3
21,647
+ 45.9
SAN FRANCISCO (CALIF.) MUNICIPAL RAILWAY...
SAN FRANCISCO, CALIF. - BAY AREA RAPID
TRANSIT DISTRICT - RAPID TRANSIT (Q.)
1.466
1,424 -
-------
- 7 -
DECEMBER 1973
NOVEMBER 1973
CALENDAR
YEAR 1973
CITY AND SYSTEM
REVENUE
% CHANGE
REVENUE
% CHANGE
REVENUE
% CHANGE
PASSGRS
FROM
PASSGRS
FROM
PASSGRS
FROM
(THOUS)
1972
(THOUS)
1972
(THOUS)
1972
SM JOSE (CALIF.) CITY LINES, INC
S SAN JUAN, P.R. - METROPOLITAN BUS AUTH
3,615
+ 0.2
SANTA ROSA (CALIF.) MUNICIPAL TRANSIT...(V)
22
+ 40.8
19
+ 11.3
229
+ 22.5
SAN RAFAEL, CALIF. - GOLDEN GATE TRANSIT...
*SAVANNAH (GA.) TRANSIT AUTHORITY
448
- 1.3
496
+ 12.3
5,599
- 0.6
SCHENECTADY, N.Y. - CAPITOL DIS. TRANS. SYS
183
- 0.2
180
- 2.2
SEATTLE, WASH. - METRO TRANSIT '
2,750
+ 13.6
2,821
+ 19.5
32,235
+ 10.5
SOUTH BEND (IND.) PUBLIC TRANSPN. CORP
SPARTANBURG, S.C. - DUKE POWER COMPANY
101
- 4.9
102
- 2.7
1,232
- 2.0
SPOKANE (WASH.) TRANSIT SYSTEM
483
+ 19.5
462
+ 20.9
4,591
+ 5-3
SPRINGFIELD (ILL.) MASS TRANSIT DISTRICT.'..-
221
+ 1.7
SPRINGFIELD (MO.) CITY UTILITIF"
STOCKTON (CALIF.) METRO. TRANSIT DISTRICT...
15U
+ 15.8
163
- 1.8
1,847
- 1.2
ST. JOSEPH (MO.) LIGHT & POWER" COMPANY
117
- 3.0
84
- 2.3
1,131
- 4.8
SYRACUSE, N.Y. - CNY CENTRO, -INC
883
+ 0.3
874
- 0.5
10,118
+ 2.6
TACOMA (WASH.) TRANSIT SYSTEM
522
- 0.9
580
+ 1.8
6,097
- 0.3
0 TAMPA (FLA.) BUS LINES
210
- 6.0
229
+ 2.7
2,691
+ 0.4
TOLEDO (0.) AREA REG. TRANSIT AUTHORITY
1,081
+ 1.8
1,271
+ 0.7
TORONTO (ONT.) TRANSIT COMM. - TOTAL (W)
27,820
+ 11.4
30.404
+ 11.8
330,986
+ 2.5
SURFACE LINES
16,663
- 9.2
20,312
+ 10.4
223,084
- 0.6
RAPID TRANSIT LINES
9,472
+ 13.8
10,092
+ 14.8
106,217
+ 5.9
VANCOUVER, B.C. - B.C. HYDRO & POWER AUTH...
6,443
+ 13.4
6,746
+ 17.9
73,735
+ 9.5
VICTORIA, B.C. - B.C. HYDRO & POWER AUTH
7 48
+ 12.0
775
+ 21.1
8,640
+ 13.7
WACO (TEX.) TRANSIT CORPORATION ./v)
66
+ 50.6
61
+ 19.5
660
+ 1.5
WALTHAM, MASS. - MIDDLESEX & BOSTON
STREET RAILWAY COMPANY "
WASHINGTON, D.C. - METROBUS
WICHITA FALLS, TEX. - WICHITA' CITY LINES...
WICHITA (KAN.) METROPOLITAN TRANSIT AUTHO')
152
+ 5-9
WILKES-BARRE (PA.) TRANSIT CORPORATION. -
WILMINGTON, N.C. - SAFEWAY TRANSIT CO
WILMINGTON, DEL. - DEL. AUTH. FOR REG. TRANS.
392
- 20.6
372
- 4.2
5,215
+ 0.2
WINNIPEG (MAN.) TRANSIT SYSTEM
4,966
+ 1.0
5,366
+ 1.9
58,022
- 0.5
WINSTON-SALEM (N.C.) TRANSIT AUTHORITY
143
+ 59.0
151
YONKERS (N.Y.) TRANSIT CORPORATION
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* FARE. CHANGE IN BASIC ADULT RATES DURING PAST 12 MONTHS # PRELIMINARY
S STRIKE WITHIN LAST 12 MONTHS R REVISED - CORRECTED
(A) FREE FARE FOR SENIOR CITIZENS 7/1/73.
(B) SENIOR CITIZENS FARE REDUCED ll/73-
(C) SERVICE EXTENDED TO FIVE AREAS 11/73-
(D) INCLUDES STUDENT PASSENGERS CARRIED UNDER CONTRACT.
(E) BASIC ADULT FARE CHANGE FROM 550 TO 250 EFFECTIVE U/73; STRIKE 12/8-12/73-
(F) AS OF 1/1/73 DISCONTINUED OPERATING ON SUNDAYS AND HOLIDAYS; STRIKE ll/ll-l8/73.
(G) SUNDAY SERVICE RESTORED; SENIOR CITIZENS FARES REDUCED; 11/72 REVISED DUE TO
HIGHER AVERAGE FARE.
(H) STREETCAR OPERATIONS DISCONTINUED 7/30/73; PREVIOUSLY CARRIED hOO,000 - 1+50,000
PASSENGERS PER MONTH.
(I) SERVICE IMPROVEMENTS IMPLEMENTED 10/15/72; BEGAN EVENING SERVICE 9/17/73-
(J) STRIKE BEGINNING k/2k/73-
(K) FREE FARE EFFECTIVE 11/22/73; NO PASSENGER COUNT FROM THAT DATE.
(L) SERVICE REDUCED FOR ONE WEEK DUE TO FUEL SHORTAGE 11/73-
(M) IMPLEMENTED NEW ROUTES; ADDITION OF NEW BUSES.
(N) FARE REDUCTION 7/l/73; 10/73 - 53,SU8 FREE PASSENGERS FROM FREE FARE DAY.
(0) SATURDAY AND CROSSTOWN SERVICE CUT 10/735 CUT IN SERVICE DUE TO FUEL SHORTAGE 12/73-
(P) FIGURES REVISED FOR 1972.
(Q) BAY AREA RAPID TRANSIT DISTRICT BEGAN OPERATING ON 9/ll/72.
(R) FIGURES DO NOT INCLUDE DIAL-A-RIDE DEMONSTRATION PROJECT.
(S) FIGURES REPRESENT TOTAL PASSENGERS INCLUDING TRANSFERS; FREE FARE FOR SENIOR CITI-
ZENS 7/1/73; STRIKE 12/3-9/73-
(T) REVISED FORMULA FOR ALLOCATING PASSENGERS EFFECTIVE 10/72; NEW SENIOR CITIZENS
FARE 10/73-
(U) STRIKE 11/11+-19/73-
(V) ROUTE CHANGES EFFECTIVE u/li/73; ADDITION OF TWO JITNEY SERVICES 9/73.
(W) TWO-ZONE FARE SYSTEM ELIMINATED; FIGURES FOR 1972 REVISED TO SHOW CHANGES.
(X) ZONE FARE ELIMINATED 8/27/73, SENICk CITIZENS FARE REDUCED 11/73-
(Y) PASSENGER COUNTING METHOD REVISED 1972 - 1973-
(Z) ALL FARES 154 EFFECTIVE 7/13/73-
D-9
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APPENDIX E
Tabulation of Selected Energy-Related Survey Results
by National Opinion Research Center University of Chicago
E-l
-------
-2-
Preference for Gasoline Allocation Mechanism
(Question 140)
A B
C
D
A) Pay $1.00 per gallon
X
B) 7 gallons ration and
$1.30 per gallon over that
27% JXC
C) Ration 10 gallons per week
14% 43%
X
D) Free market price
53%
58%
73%
Entries are per cent of respondents choosing column
option over row option. Thus 27 % prefer
option A over B. (Week 1, Cycle 8 results)
Average estimated price per gallon in one month
if free market = $1.05/gatlon
E-2
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6 - XoLY 1<\ \<\*13
kc;T
JO (vtic.wfA_ y\ f\L-^
|s). O' R.' C*
BtMke?. <5? (Lasss - 1
100. In the past month, have you or anyone in your family had any trouble getting
gas?
7/) \ (479)
Yes , , • , l('^7
No . (SKIP TO Q. 103). 2 (.6*})
k 6K=.1Q
101. Which of the problems on this card have you had? CODE ALL THAT APPLY.
f
~ £^Ga's "station wasn't open as much as it used to be l^alOfy (480)
/ f\ Q"Oas station went out of business , <.03} (481)
station didn:t have cne grade of gas f i
I wanted 3v^J 3/(482)
(,»2S^pas station wouldn't give me as many gallons" / I/^\
as I wanted 4 >.*' ^(433)
{»%r$^3.s station didn't have any gas at all r . . . 5(.07)(„„
(455)
|.C>£>0ther (SPECIFY)
8k= -*7
E-3
-------
Suppose we knew that there wasn't going to be enough gas, oil, and electricity
in this country for everyone who needed it, and the federal government was
-trying to decide what uses were most important. I will read you a list of
i^ssiblc uses. For each one, please tell x.e how important you think it is
to guarantee an adequate amount of fuel or enfcrgy for that use. (First, for
hcatinr ho~es)--how important is it that there be gas, oil, or electricity
for that—is it... (READ CATEGORIES)? ASK FOR EACH ITEM, A-I.
Absolutely
essential
Extremely
important
Moderately
important
Slightly
important
Not
at al 1
important
A.
Heating homes
('U)
fhi) (3ttf)
rV)
,0 (487)/12
( O)
B.
Commercial freight
transportation
/.Va
(H
f.ci)
'
,0 . (488)/13
(.43)
c.
Pleasure driving
by private
citizens
V "
(:°2)
(:&l)
(. 2Z)
(.
0 (489)/14
P.
Other recreation
uses
t.o\)
^ y
C 0 3)
?.n)
()m f)
\ *
E.
Farming' operations
•
C-'t
'S ¦
<1
ton)
0 (A 91) /16
<
F.
Air conditioning
(to?)
(f.oO
l\$
l.Zl)
0 v(492)/17
(.HO)
G.
Public passenger
transportation
like buses, trains
and' airlines
' (. Z1)
(.31)
2-
f. ?-?-)
(-^)
. Si ¦» 1
0 (493)/I8
(,o£\
H.
Factory'operations
}¦o)
— T. f
\.CM)
v. y
0 <494)/19
f.Ol)
I.
Business driving by
private citizens
f.ll)
¦ v 1
h*
v — ¦
(¦
\
^.13^
P \(495)/20
E-4
-------
l_i »JW j-o - ,
van-.cd Co do something to cue Che n:r.ounC of fuel used for transports ion by
private individuals, which of the things on this card would you most like Co
see then do? W'nac would be your next choice after that? And what would your
third choice be? CODE ONE ONLY IN EACH COLUMN.
«a:;o
A.
B.
C.
CM u>
First
Second
Third
K
Choice
Choice
Cheice
Impose a maximum speed limit of 60 miles per hour
on all open highways
Impose a maximum speed limit of 50 miles per hour
on all open highways
Ration gasoline -
Increase gas taxes
Put a commuter tax on all-day downtown parking
Restrict cars in the central business and
shopping area
Encourage the use of urban public transportation
by improving the service or lowering the cost .
Encourage the use of car pools by making them
cheaper or easier than driving alone
01
(.IV)
.01,
03 ^
C-ol)
04 v
^OZ)
05
c°o
06
(.oi)
07
(;2'0
08
Impose a tax cn new cars above a minimum weight
and horse power
(¦os)
/°9
G°2)
Restrict the weight and horse power of new cars . . 10
0*1)
11 V
C-O'l)
Do nothing ¦ 12
Relax or eliminate the standards for anti-pollution
device on cars
Other (SPECIFY)
i.O))
,13 \
01
02
Uo)
" 03 v
C
04
05
oo
06
(j07)>
07
Cis")
08
(.2?)
09
(.OH)
10
11
C,f)
S-oO
,13 V
(496)/ (457)/ (498)/
21 22 23
01
(.•<0
02
(.06)
03 v
(
-------
-32-
Nov suppose the government was c°inC to ration motor fuel. Here is a list of
vpes of vehicles. Which one of these should get fuel firct? Which one should
it second? And which one shouldxget it third? CODE 0I5E ONLY IN EACH COLUMN.
A.
First
Private cars 01
(.iz)
Taxis 02
(.•»0
Urban public transportation vehicles .
Buses for between-city trips ..... 04
C-03)
Passenger trains for between-city trips 05
Railroad freight trains 06 .
• (.¦&)
Trucks ....... 07
(;0^
Commercial airlines' 08
L-°2)
Private or company-owned airplanes » . 09
foz]
Farm work vehicles ....• 10
Construction vehicles .
-------
Per cent choosing:
"Absolutely-essential" = A
"!¦ xtr ,'nely. rroderafely
or slightly important" = B
"Not at nl1 important" = C
NO]':': July 1 v73 results were:
A (> '\"l.; l\r> 7,; C-0
-------
PADS"
a-S3.z7c{
C= O
/V-~/3
PAD
A =
ft* _
c ~ o
^6
PAD 2.
L
6r
/v-
i
00
Table # 89
2)How important is having fuel available for
commercial, freight transportation (Q.97)?
Per cent choosing:
"Absolutely essential" = A
"Extremely, moderately
or slightly important" = B
"Not at all iimportant" = C
NOTE: July 1973 r.;iliun;il results were:
A-3 3/. ; 1JC=37.
-------
I
KO
PAD j5~
G- O
r>^)2>
PAD V
/9r /00%
6* O
O 0
N' 6
Table # 92
3) How important is having fuel available for
faming operations (Q. 97)?
Per cent choosing:
"Absolutely essential" = A
" ^L rc 1 y, t.-.o t! c r o t e ] y
or slightly ii.iportant" = B
"Not t a LI important" = C
KOT_K: July 197J li/ition.1! results were:
A- 'i 7 'i 3/.; O-O
¥1.1%
.5" o.
-------
Table # 94
4)How important is having fuel available for
public transportation (Q. 97)?
Per cent choosing:
"Absolutely essential" = A
"L:-:t re :c ly , -moderately
or sliriitly i :.:,ior tant" = B
''Not .it /j L i important" = C
NOTjJ; Jul/ 1-./7J national results were:
; ; c--=5L/0
-------
PADS"
^ o
//-y3
Table #95
5) How important is having fuel available
factory operations (Q. 97)?
Per cent choosing:
"Absolutely essential" = A
"i;::Cr; .ioly, -.noderato ly
or slightly important" = B
"Not i.t all important" = C
N0T1- : Ju]y 1S73 national results were
A-A.V/,; C = l%
^o,*%
- 0
¦S?
PAD 3
fi Z S0%
& • S0%
o - o
n- /a
PAP ±
c = o
-------
Tabic #96
6) How inportant is having fuel available for
business driving by private citizens (Q.97)?
Per cent choosing: \
"Absolutely essential" = A
" !•; ::L ri_i:v lv liiode f.-il c; ly
vj: lightly important" = B
"Not dt ;>1 1 ir.ipoi. t .ml" = C
NOTK : .July I'") 7 3 national results were:
A- -1 \>'i ; i'.-'/jl; C-6%
PAD 3
n--
is =¦ so %
c = %
{J: )A
-------
-------
-------
energy
-------
Ap[>rXinTV P
-------
YES
ALL MIXES N0
TESTED
?
FREEWAYS
SOCIOECONOMIC
FACTORS
\
INVESTMENT
LEVEL
ARTERIALS BUS
RAPID
TRANSIT
EXISTING
SYSTEM
TARGET YEAR
ALTERNATIVE
/
tiWr
FUTURE
TRAVEL
BY MODE
SYSTEM
PERFORMANCE
USER COSTS
DIRECT
CAPITAL
COST
NON-CAPITAL
COST
ECONOMIC
ANALYSIS
INDIRECT/
EXTERNAL
COSTS
EVALUATION
NO
SOLUTION ?
I yes
OPTIMAL
ALTERNATIVE
LOGIC FLOW DIAGRAM OF TRANS
F-2
-------
dollars of user costs via statistically compiled relationships.
A breakdown of user costs is given below:
private vehicle: . travel time costs
. vehicle running costs
. accident costs
. parking costs
. gas tax
public transportation: . travel time costs
. fare
. accident costs
Other transportation costs such as direct capital costs,
non-capital costs and indirect/external costs are estimated
directly from the system supply. An enumeration of these
costs follows:
Direct Capital Costs:
. highway - new construction of freeway/arterials
- reconstruction of freeway/arterials
. transit - rolling stock (bus, rapid vehicles)
- guideway for rapid system
- stations and terminals for rapid
systems
- yards and shops
Non-Capital Costs:
. operating costs
. maintenance costs
Indirect/External Costs:
. fatalities
. land consumption
. dislocation of households and businesses
. air pollution by pollutant
. energy consumption
It is recognized that certain cost itfems, especially in the
last category, are noncostable, i.e., nonquantifiable in terms
of dollars.
F-3
-------
Fourth, and finally, an economic analysis and an evaluation
are performed based upon the costs obtained from the last step.
An economic efficiency concept is used. A total value indicator
is defined to represent the sum of the prices which all travelers
are willing to pay. Total transportation cost is computed by
summing up capital, operating and user costs. The difference
between total value indicator and total transportation cost
constitutes the net value indicator, which is a measure of
"consumer surplus" benefit. Noncostable impacts are formulated
as constraints in the evaluation procedure. Unless an invest-
ment alternative satisfj.es the constraints, (e.g., maximum number
of facilities), it is rejected irrespective of its economic
viability.
APPLICATIONS
TRANS is designed as a sketch planning,fast turnaround,
tool for analyzing nationwide, mul t.iregional policies. Toward
this end, three different "standard'1 sets of curves have been
calibrated in' the highway version -- one for the urban area with
over 50,000 population; another for small urban areas grouped by
states, with 5,000 to 50,000 population; and, the final one is
for "rural" regions which analyzes a whole state or a large
portion of a state. These three versions of the model are
respectively labelled: (i) TRANS - urban; (ii) TRANS - small
urban; and (iii), TRAMS - rural. In the current multi-modal
version, only TRANS-urban is available.
TRANS has been used in a number of studies within DOT.
It was used in an analysis of urban highway public transportation
facility needs, documented as a report of the Secretary of
Transportation to the U.S. Congress. The analysis indicated
that busways, special fringe parking facilities and operational
improvements can substantially improve public transportation
service. The investment fundings needed to achieve these
improvements were given. The analysis examined 6 5 urbanized
areas.
TRANS was again used by F1IWA to look into the effects of
varying policies and assumptions on national highway require-
ments. A wide range of alternatives ranging from building
nothing to extensive highway construction are analyzed under
varying patterns of population, mode choice, economic assump-
tions and impact valuations.
Finally, TRANS was used for the "1972 National Transporta-
tion Report" performed by the Office of the Assistant Secretary
for Policy and International Affairs. The effects of three
F-4
-------
prog mm funding levels, with four allocation of funds among
highways and public transportation for each program, were
analyzed. The study examined G3 urbanized areas that will
have a 19^0 population of 500,000 or greater.
TRANS is coded in FORTRAN IV. The uniinodal version has
been implemented on an IBM 360 machine, requiring about 125K
bytes of core. The multimodal version, under the final stages
of development, is reported to occupy 220K. A run-time of
about 4 0 minutes on the model 6 5 is needed to process the 2 61
individual urban regions, 150 small urban groupings, and 80
rural areas evaluating about 75 transportation alternatives in
each. Computer costs are therefore in the range of 1 cent per
alternative analyzed.
Developed as an in-housc analysis tool, TRANS is not
distributed openly in the public domain. However, TRANS has
been made available outside the in-house staff for a number
of studies, especially when the study has some significance
in national policy making. Additionally, a version is currently
under development for application by urban transportation
studies which will treat individual communities within the area
as analysis units.
CONCLUSIONS
TRANS is an aggregate model designed to provide fast turn-
around answers to national policy type questions. The useful-
ness of such- a model in FIIV.'A or OST has been deomontrated by the
various studies cited .in this review. However, because of the
aggvegate nature of the model, its analysis is not currently
designed to pertain to ind.ivi.dual cities. While supply data
are inputted by city, many of the functional relationships
have been calibrated using nation-wide data by population group
for urban, small-urban and rural-areas. As such, TRANS does
not completely distinguish between City A vs. City B as long as
they fall into the same population categorization. TRANS is
a sketch policy planning tool and should not be therefore
regarded as a substitution for the more detailed micro planning
models. Rather, the macro and micro models should be applied
in conjunction to supplement each other.
F-5
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Gentle 11, D.S., II. KassofC, and T.J. Hillegass, "The Effects of
Varying Policies and Assumptions on National Highway
Peiju.irmecnts" , IJRB r)2nd Annual Meeting, January 197 3.
GendelJ , b.S., 11. Kan soft' and T. Mil legass, "TRANS Technical
Not"os - Description of TRANS Analysis Procedures", FHWA
internal document, .'June 1971,
Kassoff, H. and D.S. Gendell, "An Approach to Multi-Reg ional
Urban Transportation Policy Planning", KRR Wo. 340 , 1971.
We.incr , E . , II. Kassoff and D.S. Gendell, "A i1u 1 ti -- Mod a ].
National Urban Transportation Policy Planning Model", HRB
5 2 nd Annual Meeting, January 1973.
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