EPA-450/3-74-003-C
September 1973
VEHICLE BEHAVIOR
IN AND AROUND
COMPLEX SOURCES
AND RELATED COMPLEX
SOURCE CHARACTERISTICS
VOLUME III - SPORTS STADIUMS
U.S. ENVIRONMENTAL PROTECTION AGENCY
Office of Air and Water Programs
Office of Air Quality Planning and Standards
Research Triangle Park, North Carolina 27711
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EPA-450/3-74-003-C
VEHICLE BEHAVIOR
IN AND AROUND
COMPLEX SOURCES
AND RELATED COMPLEX
SOURCE CHARACTERISTICS
VOLUME III - SPORTS STADIUMS
by
Scott D. Thayer and Kenneth Axetell, Jr.
Geomet, Inc.
50 Monroe Street
Rockville, Maryland 20850
Contract No. 68-02-1094
Task Order No. 3
EPA Project Officer: Edwin Meyer
Prepared for
ENVIRONMENTAL PROTECTION AGENCY
Office of Air and Water Programs
Office of Air Quality Planning and Standards
Research Triangle Park, N. C. 27711
September 1973
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This report is issued by the Environmental Protection Agency to report
technical data of interest to a limited number of readers. Copies are
available free of charge to Federal employees, current contractors
and grantees, and nonprofit organizations - as supplies permit - from
the Air Pollution Technical Information Center, Environmental Protection
Agency, Research Triangle Park, North Carolina 27711, or from the
National Technical Information Service, 5285 Port Royal Road, Springfield,
Virginia 22151.
This report was furnished to the Environmental Protection Agency
by Geomet, Inc. , 50 Monroe Street, Rockville, Maryland, in fulfillment
of Contract No. 68-02-1094. The contents of this report are reproduced
herein as received from Geomet, Inc. The opinions, findings, and
conclusions expressed are those of the author and not necessarily
those of the Environmental Protection Agency. Mention of company
or product names is not to be considered as an endorsement by the
Environmental Protection Agency.
Publication No. EPA-450/3-73-003-C
11
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ABSTRACT
The report presents a general methodology for interpreting parameters
which characterize a complex source into descriptions of traffic behavior
in and around the source. The methodology is implemented in quantitative
fashion for the third of seven types of complex source, sports complexes;
the information generated, relating sports complex parameters to the
associated traffic behavior, will now be used by the sponsor to generate
guidance for studying the impact of new sports complexes on air quality.
in
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CONTENTS
Page
Abstract iii
List of Figures v
List of Tables vi
Sections
I Conclusions 1
II Recommendations 2
III ' Introduction 3
IV Characteristics of Sports Complexes 7
V Parameters for Outdoor Stadiums 11
VI Traffic Parameterss Values and Derivations 16
VII Analysis 26
VIII Results 38
IX References 52
IV
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FIGURES
No. Page
1 Schematic Representation of Vehicle Operating Modes at 19
Stadiums
2 Queue Length as a Function of Time when Gate Capacity is 31
Exceeded
3 Generalized Methodology 39
4 Methodology Applied to Sports Complexes 40
5 Isopleths (m sec'l) of Autumn Wind Speed Averaged through 45
the Afternoon Mixing Layer
6 Isopleths (m sec"^) of Mean Winter Wind Speed Averaged 46
through the Afternoon Mixing Layer
7 Isopleths (m x 1£)2) of Mean Autumn Afternoon Mixing Heights 47
8 Isopleths (m x 102) of Mean Winter Afternoon Mixing Heights 48
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TABLES
No. Page
1 Recently Constructed Major U.S. Stadiums 9
2 Seating Capacities and Parking at Stauiums 12
3 Off-Street Parking Requirements for Stadiums and Arenas 14
4 Vehicle Exhaust Emissions at Idle in Grams Per Minute 17
5 Parameters for Estimation of Traffic Volumes 23
6 Area Consumption Per Parking Space 33
7 Waiting Times for Exit from Parking Stalls 34
8 Calculated and Observed Parking Lot Emptying Times 35
9 Key to Stability Categories (after Turner 1970) 44
VI
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SECTION I
CONCLUSIONS
1. A general methodology has been developed which relates parameters
of traffic behavior associated with complex sources to the available
descriptive characteristics of the complexes themselves. These relationships
are subsequently to be used by the sponsor to develop guidance for relating
the complex's characteristics to air quality.
2. The methodology has been successfully applied to the third (sports
complexes) of seven types of complexes, with quantitative results presented
in this task report. The methodology is considerably simplified for sports .
complexes because they can be analyzed on a well-defined single-event basis.
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SECTION II
RECOMMENDATIONS
It is recommended that, as planned, the project officer employ this
methodology to develop guidance for relating the traffic characteristics
of sports complexes to typical and peak air pollution concentrations.
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SECTION III
INTRODUCTION
OBJECTIVE AND SCOPE
The ability to estimate traffic characteristics for proposed developments
and the resulting effects on air quality is an important prerequisite for
promulgating State Implementation Plans which adequately address themselves
to the maintenance of NAAQS. Prior to estimating the impact of a develop-
ment (complex source) on air quality, it is necessary that traffic charac-
teristics associated with the source be identified and related to parameters
of the development which can be readily identified by the developer a priori.
The purpose of this study is to identify traffic craracteristics associated
with specified varieties of complex sources and to relate these character-
istics to readily identifiable parameters of the complexes. The end product
of this task will then be used to develop an Air Pollution Technical Docu-
ment which will provide guidance to enable control agencies to relate readily
identifiable characteristics of complex sources to air quality.
The work is being performed in seven sub-tasks. Each sub-task is devoted
to examining vehicle behavior and its relationship to readily obtainable
parameters associated with a different variety of complex source. The
seven categories of complex sources are:
1. Shopping centers
2. Sports complexes (stadiums)
3. Amusement parks
4. Major highways
5. Recreational areas (e.g., State and National Parks)
6. Parking lots (e.g., Municipal)
7. Airports
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This, the third, task report, describes the methodology developed, and
the analysis and results of its application to sports complexes.
APPROACH
Due to internal constraints, the sponsor has been forced to impose a tight
schedule on this project, permitting only two to three weeks for the analysis
and reporting of each sub-task. Accordingly, the employment of readily
available traffic design information for each type of complex has been
suggested as the general approach.
The approach was designed to permit the development of answers to the
following questions posed by the sponsor, using available traffic design
and behavior data, and available data on parameters of the complex:
1. How much area is allotted or occupied by a single motor vehicle?
2. How much or what percentage of the land occupied by the complex
source (and the source's parking facilities) can potentially be occupied
by vehicles? What is the usual percentage?
3. What portion of the vehicles within the complex are likely to be
running at any given time during a 1-hour period? During an 8-hour period?
We are interested in both peak and typical circumstances here.
4. What is the typical and worst case (slowest) vehicle speed over 1-hour
and 8-hour periods?
5. How are moving and parked vehicles distributed within the complex
property? (e.g., uniformly?).
6. What are the design parameters for each type of complex which are
likely to be known by the prospective developer beforehand?
7. Which ones of the design parameters in number 6 can be most successfully
related to traffic and emissions generated by the complex? What is the
best estimate for relationships between readily obtainable parameters and
emissions?
8. What are the relationships of parking "lot" design to parking densities
and vehicle circulation? What represents a typical design and/or a
design which has highest parking densities, lowest vehicle speeds, longest
vehicle operating times?
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9. What meteorological conditions (I.e., atmospheric dilutive capacity)
are likely to occur during periods of peak use? What use level is likely
to occur during periods of worst meteorology (I.e., atmospheric dilutive
capacity?).
The technical approach developed in this report consists of describing
automobile operating modes in and around complexes and the emission
significance of each mode. In our analysis, this leads to an important
emphasis of engine operating time, with only secondary significance attached
to operating speed and distance.
For the complex being studied, an analysis 1s made of the typical movements
of vehicles, and their movements under conditions of congestion, caused by
peak traffic loads or by awkward design elements of the complex, or both.
This highlights the traffic operational modes which have greatest effect
on running times, and assists 1n seeking out the elements or parameters of
the complex which influence these running times most.
The running times in critical modes are found to be dependent on the usage
rate of the complex as a percent of capacity, In addition, absolute values
of usage as a function of time are needed as a direct input for estimating
emissions. Therefore, data on usage patterns of the complex by season,
day of the week, and hour of the day are collected and related to capacity
parameters. The results are used 1n two important ways:
1. To develop quantitative relationships between running times and various
percent-usage parameters; and
2. To provide general usage patterns from which the usage pattern for
a complex of interest can be inferred, 1f no measured data are available.
This general methodology is simplified somewhat for sports complexes
because the traffic generated by them is not continuous, but instead is
related to well-defined (i.e., by attendance and starting and ending times),
isolated events. For this reason, the usage patterns need not be determined
as a function of time; usage and traffic patterns can both be related
directly to the time frame of each individual event.
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Total running times and number of vehicles running, the desired quantitative
descriptions of traffic behavior, can then be determined for each event
instead of for one- or eight-hour periods of maximum usage. Qualitative
guidelines which should provide further insight into factors related to
traffic congestion around sports complexes are also presented. These are
provided separately from the quantitative relationships.
Finally, the meteorological conditions associated with the occurrence of
the peak "(vehicle number) (running time)" values are defined; in addition
periods of the most adverse meteorological conditions are determined, and
the use rate data examined to determine associated use rates and running
times.
The methodology is considered to be completely general, and to apply to
all the complex sources of concern here, with the exception of "major
highway" cases cited in the section titled Objective and Scope. That
special case is recognized in the work statement as an unusual one requiring
different treatment in the context of the other six sources. In any
event, and in the words of that statement, "for highways it may simply be
necessary to tie existing guidelines into a concise package."
The remainder of the report describes the implementation of this methodology
for sports complexes, and the results obtained.
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SECTION IV
CHARACTERISTICS OF SPORTS COMPLEXES
Major spectator sporting events are held in two widely different and
easily distinguishable types of facilities -- outdoor stadiums and indoor
auditoriums. Highest attendances at outdoor stadium events, in descending
order, are for football, baseball, soccer, and field and track. The most
popular indoor sporting events are basketball and hockey. Stadiums built
in recent years generally have a seating capacity of about 70,000,1 whereas
new auditoriums designed primarily for sporting events seat 20,000 to
25,000.
In addition to stadiums and auditoriums, special facilities exist for
spectator sports such as horse or dog racing, auto racing, tennis, and
competition swimming. These facilities have characteristics which distinguish
them from the two "standard" facilities. For example, they may be used
much less frequently and therefore have more temporary provisions for
parking, seating, and traffic control. Also, these events usually attract
smaller numbers of spectators.
All sports facilities have one characteristic which separates them from
other complex sources: single-event orientation. Because of this char-
acteristic, the traffic analyses are simplified, to traffic per event
rather than complex variations of traffic with time, i.e., daily, weekly,
and seasonal,,
Sports facilities are further distinguished by their location. New stadiums
and auditoriums are about equally split between downtown and suburban
sites. Location affects traffic levels by influencing the modal split of
spectatorso
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OUTDOOR STADIUMS
Because of time constraints, only one type of sports complex, the outdoor
stadium, has been selected for more detailed analysis in this report.
Stadiums were choosen becasuse they are the sites of the most frequent
and highest-attended sporting events, and hence are the facilities of
greatest concern as complex sources. However, the methodologies developed
herein for relating characteristics of the complex to vehicle behavior in
and around the complex are equally applicable to auditoriums and other
sports facilities. Sites that are used very infrequently for large events,
such as the Indianapolis Motor Speedway, may show extreme capacity excesses
and more traffic congestion, but they are isolated occurrences and should
not form the basis for methodology development.
General information on most of the recently-built stadiums in the country
is presented in Table 1. This information was complied from published
data^>2 and from telephone surveys of stadium managers. Physical charac-
teristics and traffic parameters for these stadiums, obtained from the
same sources, are included in subsequent sections.
FUTURE STADIUMS
All of these relatively new stadiums except for the one in Kansas City
are termed "second generation" stadiums because they have been designed
specifically to accommodate both football and baseball, rahter than being
designed as baseball stadiums which later have been used for football
events. Since seating capacities, attendance patterns, and other parameters
vary for the two sports, a dual-purpose stadium should actual 1 be analyzed
separately for the different sports.
The Kansas City sports complex marks the advent of what may become the
third generation of stadiums -- single-purpose structures side-by-side,
sharing common parking and other auxiliary facilities. These stadiums
have the advantage of optimum configuration for each event and avoid
problems of shifting from one sport to the other. This design is not
as expensive as might initially be expected, since the single-purpose
stadiums can be kept simpler in design.
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Table 1. RECENTLY CONSTRUCTED MAJOR U.S. STADIUMS
Name
Atlanta Stadiums
(not yet completed)
Rich Stadium
Riverfront Stadium
Schaefer Stadium
Astrodome
Truman Sports Complex
Louisiana Superdome
Veteran's Stadium
3 Rivers Stadium
Busch Stadium
San Diego Stadium
Robt. F. Kennedy Stadium
City
Atlanta
Baltimore
Buffalo
Cincinnati
Foxboro, Mass.
Houston
Kansas City
New Orleans
Philadelphia
Pittsburgh
St. Louis
San Diego
Washington, D.C.
Area of
Stadium
Complex,
Acres
60
50
154
48
69
260
370
55
n.d.
80
85
166
60
Location
1 mile from CBD
Downtown
15 miles from CBD
Downtown
22 mi. from Boston CBD
6 miles from CBD
10 miles from CBD
Near French Quarter
2 miles from CBD
Downtown
Downtown
7 miles from CBD
4 miles from CBD
Metropolitan
Pop. (SMSA),
Millions
1.39
2.07
1.35
1.38
2.74
1.99
1.25
1.05
4.82
2.40
2.36
1.36
2.83
n.d. = no data
CBD = Central Business District
SMSA = Standard Metropolitan Statistical Area
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The side-by-side single-purpose stadium concept may be carried a step
further by locating other sports facilities adjacent to the stadium
nucleus, forming what is truly a sports "complex". Such a design is
presently nearing completion in New Jersey, where a football stadium
for the New York Giants, a baseball park, an indoor facility for basketball
and hockey, a race track, a hote'l , and an exposition hall are all located
at one site. In Philadelphia, Veteran's Stadium, John F. Kennedy Stadium,
and the Spectrum Sports Arena are on the same site.
While the stadium authority which manages a multiple-facility complex
would certainly attempt to prevent scheduling conflicts, unavoidable
overlapping is a possibility. The chances of a conflict between major
events increases with the number of facilities at the complex. If two
events coincide, the traffic: analysis would use the combined traffic volumes
for the two events.
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SECTION V
PARAMETERS FOR OUTDOOR STADIUMS
There are only a few measures of size and activity level which have been
widely used as descriptive parameters for stadiums. These measures are
part of the design criteria for the stadium, so they are known to the
developer as early as the planning stage.
Coincidently, these few available parameters, presented below, also are
important in estimating traffic volume and behavior at stadium events.
However, empirical traffic parameters discussed in Section VI are equally
important in the proposed methodology for estimating traffic patterns at
stadiums.
SIZE
The size of a stadium is almost always expressed in terms of seating capacity.
A dual-purpose stadium usually has a lower seating capacity for baseball
than for football, due to movable seats and the different field configurations.
Capacities of the newer stadiums are shown in Table 2.
For an individual sporting event (the basic unit for traffic analyses),
the size is measured in attendance, which is obviously limited at the
upper end by seating capacity plus the standing-room crowd. Attendance
is a function of the sporting event being held. For professional football,
average attendance for all teams over the past two seasons has been greater
than 95 percent of capacity,2 indicating that there is no significant
difference between typical and peak attendance. Both can be accurately
estimated by seating capacity.
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Table 2. SEATING CAPACITIES AND PARKING AT STADIUMS
Stadium
Atlanta Stadium
(not yet compieted)
Rich Stadium
Riverfront Stadium
Schaefer Stadium
Astrodome
Truman Sports Compex
Louisiana Superdome
Veteran's Stadium
3 Rivers Stadium
Busch Stadium
San Diego Stadium
Robt. F. Kennedy Stadium
City
Atlanta
Baltimore
Buffalo
Cincinnati
Boston '
Houston
Kansas City
.Mew- Orleans
Philadelphia
••* . - • *
Pittsburgh
St. Louis
San Diego
Washington, D.C.
Baseball
Seating
Capacity
!
51 ,400
55,000
-
52,000
-•
45,000
42,000
56,500
55,000
50,300
50,100
48,000
45,000
Football
Seating
Capacity
58,800
70,000
80,000
56,200
61 ,000
50,000
78,000
78,000
65,000
50,300
51,200
55,000
54,000
I
Parking I
At Stadium
4,400
6 ,500
15,000
4,600
16,200
30,000
16,000
5,100
6,800
4,400
5,200
16,200
11,500
Parking Lots
5,500
6,700
-
20,000
-
-
..
7,500
5,000
24,000
10,000
-
-
On-Street
*
900
300
*
-
-
-
-
*
*
500
-
1,000
Off-Street
Parking
Spaces
Per Seat
0.17
0.19
0.19
0.44
0.27
0.60
0.21
0.16
0.18
0.57
0.30
0.29
0.21
* Combined in value for parking lots
Source: Personal communications with Stadium Managers, September, 1973, and ref. 2. -
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In contrast, capacity crowds for baseball are rare and usually occur only
when the home team has a winning record or during post-season playoff
games. Since the long-range won-lost record of a team cannot be accurately
predicted, peak attendance should be assumed as the seating capacity of
the stadium for baseball, Average (typical) attendance values may be
obtained from market, surveys for a new team or from past attendance
records for an established team moving to a new stadium.
PARKING SPACES
The number of available parking spaces is a critical parameter for any
complex source, and sports facilities are no exception. For purposes
of analysis, total parking spaces should be obtained from three subtotals:
stadium parking, other public and private lots, and on-street parking.
The developer should have these three subtotal values.
The area allotted per vehicle in stadium parking lots may be slightly
lower than at lots serving other types of facilities, primarily because
parking is usually supervised and there is no turnover in the lot, making
three-, four-, or five-deep stall parking more common. The range of
gross areas (parking spaces plus access lanes) per vehicle is 170 to 260
sq. ft., with 200 sq, ft. a mean value.
Parking capacity is commonly evaluated in spaces per seat. Many cities
have regulatory requirements for the number of off-street parking spaces
serving public buildings. These requirements for stadiums and arenas
are summarized in Table 3.4 Corresponding values of off-street parking
per seat for the stadiums surveyed are shown in Table 2.
The maximum distance that parking spaces may be located from the stadium
is also a consideration. Observations by stadium officials have indicated
that spectators are willing to walk as far as 2400 feet to a baseball
game and 3000 feet to a football game.2 These radiuses should be used in
determining the parking available for each event.
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Table 3. OFF-STREET PARKING REQUIREMENTS FOR STADIUMS AND ARENAS
Spaces per Seat
Minimum
Maximum
Modal
Mean
Value Specified
in Regulation
0.05
0.33
0.25
0.20
Number of cities with
This basis = 91
With other basis = 53
With no requirement = 63
Ref.4
Zoning, Parking, and Traffic
David K. Witheford, Eno Foundation for Transportation,
Saugatuck, Conn. 1972.
The distribution of parking spaces is also important. If all of the spaces
are concentrated in a single stadium lot or a few parking garages, heavy
congestion at entrance/exits and on the streets within a few blocks of the
lot is inevitable. Even traffic distribution throughout the stadium area
can best be achieved by more dispersed parking.
TEMPORAL PARAMETERS
Two parameters that are related to the stadium or the sporting event which
are used in the traffic analysis are the stadium emptying time and the time
periods when events are scheduled. Stadium emptying time is the number of
minutes required after the game for the spectator seating area exitways,
and concourses to be vacated. It is a function of stadium size, attendance,
and configuration of the pedestrian system. Emptying time normally varies
from 10 minutes for a typical crowd to 20 or even 25 minutes for a capacity
crowd at a large stadium. It should be possible for the developer to
estimate emptying time from the stadium design.
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The schedule of events at a new stadium should be relatively fixed by league
policies. The important determination on game starting and ending times
is to check that they do not coincide with peak-hour traffic conditions
on the nearby arterial streets and highways. With this exception, neither
the timing nor duration of sporting events are factors in traffic analyses.
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SECTION VI
TRAFFIC PARAMETERS, VALUES AND DERIVATIONS
The methodology for describing traffic movement around this complex source,
as outlined in Section VII, requires estimates of the average running
time for the vehicles in the vicinity of the stadium and the volume of
such traffic. Traffic parameters which should be used to develop these
two values for a specific sporting event at a stadium are discussed in
this section.
PARAMETERS TO ESTABLISH RUNNING TIMES
Concept of Emissions per Unit Time
In the immediate vicinity of stadiums, maximum vehicle speeds rarely
exceed 10 or 15 mph, and average speeds are much lower. The usual procedure
for estimating motor vehicle emissions as a function of vehicle speed is
not very accurate at these low speeds due to:
a. Difficulty in estimating average operating speed; and
b. Variation in observed emission rates per mile with slight change
in average operating speed.
For sports complexes, analysis shows that traffic operations and their
related emissions are better considered in units of time (grams/minutes)
rather than units of distance (grams/mile), for the following reasons:
1. The variations in emission per unit time at different speeds are
relatively insignificant at the lowest speeds;* and
2. Traffic movement in the vicinity of a stadium can be described
more accurately and more easily in terms of minutes of running time
than in terms of average speed, particularly when engine idling can
predominate during congested periods.
* Less than 10 percent increase in CO and hydrocarbon emissions per minute
from idle to 15 mph.
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Values for automotive pollutant emissions for 1972 in grams/minute at idle
are available from A Study of Emissions from Light Duty Vehicles in Six
Cities.5 They are summarized in Table 4. These test data compare well
with emission factors calculated from the current edition of AP-42,6
when converted to grams/minute at various speeds and then extrapolated
to 2ero speed.
Table 4. VEHICLE EXHAUST EMISSIONS AT IDLE IN
GRAMS PER MINUTE*
Pollutant
Carbon monoxide
Hydrocarbons
Oxides of Nitrogen
Emissions, gm/min
16.19
1.34
0.11
* These values do not include emissions due to the cold start of engines
of to evaporation of gasoline at the end of a trip ("hot soak"). If
subsequent investigation of the relative magnitude of these emissions,
compared to the totals generated by the methodology of this report,
indicates that they are significant, appropriate values for each cold
start and hot soak can be inserted as the total emissions for the start
and stop modes, respectively. Since data for cold start and hot soak
emissions would be reported per occurrence, there is no need to deter-
mine an associated running time or emission period for the modes.
In applying the recommended procedure of emission estimation, total emissions
from the sports complex for any event would be the product of the number
of vehicles, times average vehicle running time, times the appropriate
emission factor from Table 4:
ETotal = (V) (RT) (EF)> where
V = Traffic volume during period of concern
RT = Average running time, minutes
EF = Emission factor, grams/minute.
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Operational Modes at Stadiums
For purposes of analysis, traffic movement in the vicinity of a stadium
has been divided into the same eight operational modes that were specified
for shopping centers and for airports. These are summarized below and
shown schematically in Figure 1 < Because vehicles parking at each of
the three types of parking facilities have distinctly different running
times in the operational modes> the modal analysis actually evolves
to an 8 x 3 factor analysis.
Approach {A) - The time or distance along streets leading to the stadium
in which total traffic movement is strongly affected by vehicles moving
toward stadium area parking. This area of influence has varied from
0.5 to 1.5 miles in previous traffic design studies for stadiums.2>?
Entrance (I) - Waiting time at the ticket gate to the parking facility.
(Negligible for on-street parking),
Movement in (MI) - Driving and waiting time within the parking facility.
(Negligible for on-street parking).
Stop (S) - Parking of the vehicle and shutoff of the engine.
Start (ST) - Starting of the engine and egress from the parking space
(No cold start because of short duration of parking).
Movement out (MO) - Driving time or distance from the parking space to
the preferred exitway. (Negligible for on-street parking).
Exit (E) - Movement through the exitway, including waiting time in a
queue. (Negligible for on-street parking).
Departure (D) - The time or distance along streets within the immediate
area of influence of the stadium.
The concept of a base running time for the eight modes is not usually
applicable in analyzing traffic for a sports complex, since it is characterized
by very high volume over a short period of time, and thus is either a peak
flow or nonexistent.
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I HSTADIUMB I
PRIVATE
PARKING
LOT
Figure 1. SCHEMATIC REPRESENTATION OF VEHICLE OPERATING MODES AT
STADIUMS
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Identification of Critical Modes at Stadiums
Examination of the eight operational modes that were identified indicates
that running times in some of the modes are relatively constant, out
that times in others may increase sharply under peak attendance/traffic
conditions. For stadiums, the five modes whose times are greatly affected
by traffic congestion, in order of decreasing impact, are:
1. Exit
2. Departure
3. Entrance
4. Approach
5. Movement out
Exit time for a vehicle in a parking lot is a function of the egress
capacity of the lot. Since all of the vehicles desire to leave the lot
within a few minutes' time span after the game, exit gate capacities
are almost immediately exceeded and the time in the exit mode becomes the
average waiting time in the resulting queue.
Departure time is a function of the street capacities of those arterial
streets and highways that carry the traffic away from the game. Again,
as a result of the almost simultaneous departure of all vehicles from
the stadium area, street carrying capacities may be exceeded with resulting
increases in running times.
Time in the entrance mode is affected by the collection of parking fees as
vehicles enter the parking lots. Queue lengths are moderated somewhat over
those for the exit mode by the arrival of vehicles over a longer period of
time.
Approach time, like departure time, is a function of the capacities of the
surrounding streets.
Normally, movement out of a parking space and into the exit line requires
such an insiginificant amount of time that it can be combined with the
time for exit mode with no loss of accuracy. However, if the parking
arrangement in the lot causes some of the vehicles to be blocked, long
average waiting times in the movement-out mode may result as early returnees
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must wait for later ones to move their cars. Estimation of running times
in this mode is further complicated by the observation that the waiting
motorists do not necessarily start their engines while they are waiting.
Spectator Arrival and Departure Patterns_
The spectators who travel by automobile arrive at the stadium area prior
to the game with some distribution over time. However, this pattern either
is not characteristic and set or it has not been investigated in detail,
uecause previous transportation planning studies for stadiums have simply
assumed that all the traffic for the game arrives at a uniform rate over
the one-hour period immediately prior to the start of the game.2'7 While
further investigation would undoubtedly show that significant variations
occur between different 10-minute intervals within this hour, the assumption
that essentially all of the stadium traffic: be assigned to the one-hour
period appears to be valid. The few vehicles that arrive more than one-
hour ahead of game time probably diminish the actual peak-hour traffic volume
by about the same amount that private vehicles which drop off spectators
within the peak hour but do not remain in the stadium area increase the
actual volume over the estimate.
Spectator departure patterns can be predicted much more closely. The
stadium emptying time, a value available from the developer, indicates
the time after game end by which all motorists have reached stadium
parking spaces. More remote private lots and on-street parking spaces
would require an additional 5 to 15 minute walking time. With the assump-
tions that spectators leave the stadium at a constant rate over the period
of the emptying time and start their autos immediately upon their return,
the number of vehicles starting from each type of parking facility can
be estimated for each minute following the end of the event. Design
criteria call for a maximum of one-hour time for egress of all stadium
traffic.
21
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Traffic Assignments
Traffic volumes on surrounding streets during pre- and post-game periods
are the sum of two components -- stadium and non-stadium traffic. Non-
stadium traffic estimates should be requested from the developer for the
specific pre- and past-game periods, since they are critical to the deter-
mination of adequate highway capacity for this particular complex source.
They can usually be obtained from the local highway department.
Stadium traffic volume estimation is discussed later in this section.
Its distribution is controlled by two primary factors, traffic origin and
capacities of streets leading to the stadium. Traffic origin by direction
may be approximated from the home addresses of season ticketholders, from
market surveys, or by other estimating procedures.
These directional movements must be superimposed over the street system
in the area of the stadium (0.5 to 1.5 mile radius) to determine the
probable travel routes. The street capacities are used at this point.
The assignment of traffic volume to the various approaching and departing
routes, when added to the non-stadium traffic, should not exceed the peak-
hour capacities of these streets.
PARAMETERS OF TRAFFIC AND PARKING
Spectator Transportation
The split of spectator transportation among autos, buses and other transit,
and walking affects traffic volumes at the stadium. Charter buses and
park-and-ride systems can account for significant portion of the total
attendance. Walk-ins are usually a factor only when the stadium is in
a downtown location.
The percent of spectators that normally arrive by auto at each of the
stadiums surveyed is shown in Table 5. The range in these values is
66 to 96 percent, and the mean is 83 percent. There does not appear to
be any correlation between these percentages and the downtown vs. suburban
location of the stadium. One reference states that designers usually assume
88 percent of the spectators will come by car.
22
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Table 5. PARAMETERS FOR ESTIMATION OF TRAFFIC VOLUMES
Stadium
Atlanta Stadium
Rich Stadium
Riverfront Stadium
Schaefer Stadium
Truman Sports Complex
Veteran's Stadium
3 Rivers Stadium
Busch Stadium
San Diego Stadium
Robt. F. Kennedy Stadium
Average
Accepted Design Value
City
Atlanta
Buffalo
Cincinnati
Boston
Kansas City
Philadelphia
Pittsburgh
St. Louis
San Diego
Washington, D.C.
Percent
Arriving
by Auto
87/66
88
90
96
71
94
70
n.a.
84
77
83
88
Av. Vehicle Occupancy
For Baseball
3.04
-
n.a.
-
n.a.
2.8
3.47
n.a.
n.a.
-
3.1
2.5
For Football
2.72
3.5
3.25
3.5
3.52
2.8
n.a.
3.0
3.1
3.4
3.2
3.5
n.a. = data not available
Source = Personal communications with Stadium Managers, September, 1973,
and ref. 2.
23
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The number of spectators that arrive by bus can be estimated from the
number of buses parked at the stadium. The developer should have a
capacity value for this parameter available, since special provision must
be made in design of the parking facility for bus parking. Occupancy for
a park-and-ride bus is assumed to be 30 and for a charter bus, 40.2
Average Vehicle Occupancy
After the number of spectators traveling by auto is determined, this
value can be converted to traffic volume for the event by dividing by
average vehicle occupancy. This parameter purportedly varies from foot-
ball to baseball and is directly proportional to crowd size,2 although this
variation is not shown in the surveyed values of average vehicle occupancy
presented in Table 5. The accepted design values for vehicle occupancy
are 2.5 for baseball and 3.5 for football.2'? The data in Table 5 does
not reveal any significant change in car occupancy rates between a down-
twon stadium location and a suburban one, either.
Parking Preferences
Parking capacity in the vicinity of a new stadium should very nearly approxi-
mate the maximum predicted traffic volume for a sporting event. The exception
to this rule is a stadium located in a downtown area where more parking spaces
are needed to handle workday parking requirements than for stadium events.
If excess spaces are available, car occupancy and bus ridership may initially
be low in response to anticipated ease of parking.
If parking capacity does exceed predicted traffic volume for a sell-out
event, it should be assumed that the stadium lot and on-street parking spaces
will be completely filled and that the remainder of the vehicles will use
private lots.
For analysis of non-capacity events, the distribution of parking among the
stadium lot, private lots, and on-street parking should also be known.
Observations by stadium managers reveal that the stadium parking facility
is often filled even for events with average attendance, indicating that
this is the preferential parking area. These observations obviously are
not for those stadiums where all or almost all of the parking spaces are
at the stadium. On-street parking is apparently the second preference,
24
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although it does not provide a substantial percent of total parking even
at non-capacity events. On-street parking is preferable for many spectators
because of its lower cost and a walking distance comparable with that of
a private lot.
A generalized procedure for the quantitative assignment of vehicles to the
alternate parking facilities for a typical-attendance event would be quite
complex. However, the developer should be able to provide a good estimate
of the split of vehicles among the three types of parking facilities for
a non-capacity event.
25
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SECTION VII
ANALYSIS
In this section., the relationships are developed for converting the
stadium parameters and traffic parameters into vehicle running times and
numbers of vehicles running. The final step of combining all these inter-
mediate results into a quantitative description of the stadium traffic
problem is then treated in Section VIII, RESULTS.
STADIUM TRAFFIC VOLUME
The very straightforward procedure for estimating stadium traffice volume
has been implied in the previous sections. In summary, the relationship
is as follows:
V = v + B , where
V = total stadium traffic volume, in vehicles
p - percent of spectators arriving by auto
A = attendance.
avo = average vehicle occupancy, in persons
B = buses at game
Seating capacity is input for attendance (A) to estimate peak traffic,
while average attendance is used to estimate typical traffic volume.
This procedure is commonly used in planning and design calculations for
stadiums.
The same number of vehicles, V, are moving in the stadium area in both
the pre-game and post-game traffic periods. Note that this traffic flow
is not tied to a specific time interval (i.e., vehicles/hour).
26
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The number of buses either may be estimated by a calculation analogous to
that for autos or may be requested by the developer. It is normally in the
range of 100 to 400 buses because of equipment availability limitations.
As a percentage of total traffic volume, this is quite small—less than
four percent—and thus not critical to the accuracy of the traffic analyses.
However, in the subsequent application of this data in estimating air pollutant
emissions, the percent of total vehicles that are buses may be an important
factor. Therefore, it is recommended that subtotals for automobile and
bus traffic volumes be carried through the traffic analyses for later use
in emission calculation.
APPROACH AND DEPARTURE TIMES
Running times for these two modes cannot be estimated by the methods used
for the other modes because of the complex network of alternate routes
involved and the interspersed traffic entry points. Other problems
associated with the prediction of running times on the public access
streets to the stadium are:
a. Determination of the distance from the stadium that is to be included
in the calculation of running time in the two modes (stadium traffic may
have some measurable effect on traffic conditions for many miles from the
stadium);
b. The possible consideration of non-stadium traffic in the analysis,
since it is slowed by the congestion and therefore produces more air
pollutant emissions per vehicle-mile;
c. Difficulty in obtaining traffic volumes for periods of less than
one hour's duration (traffic stalls of 5 or 10 minutes' length may go
unnoticed when traffic volumes are averaged over an hour);
d. Inability to predict the degree of route-changing that drivers will
undertake to minimize overloading of major access routes; and
e. Prediction and simulation of traffic controls, such as reverse-flow
street operations and temporary parking bans on access routes, that will
be employed to increase capacities and average speeds.
27
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While running times cannot be determined, some analysis can be done to
predict the potential for excessive congestion on the access routes during
approach and departure periods. These are called capacity analyses, and
are a comparison of estimated peak traffic flows to respective streets
capacities. If this ratio is greater than one, severe traffic problems
can be anticipated.
First, the origin and movement directions of the total stadium traffic
volume must be determined, as briefly discussed in Section VI. A one-hour
interval is proposed as the initial assumption for the duration of the pre-
game traffic movement.
Post-game traffic occurs over a period of 5 to 10 minutes longer than the
longest parking lot emptying time (see EXIT TIMES), provided that access
route capacities are adequate to remove the traffic from the stadium area.
If this time is longer than one hour, the post-game traffic flow rate
should be estimated by dividing the traffic volumes by the period over
which they occur.
These traffic flow rates are then assigned to specific access routes by
constructing an imaginary "screen line" enclosing the stadium at a distance
of 0.5 to 1.5 miles and placing the initial traffic flow estimates at
the intersections of the access roads and the screen line, based on percent
traffic movement in each direction to and from the stadium. The total
stadium traffic should be accounted for with these assignments.
Next, non-stadium traffic volumes for the hour periods of approach and
departure should be obtained for the streets with stadium traffic. The
two partial traffic flow rates should then be added to get total hourly
traffic flows at the several points around the screen line.
These initial flow estimates should be compared with street capacities
for the same points and, ideally, the ratio should be less than about 0.9
in all cases. If the ratio for one arterial exceeds 1.0, while another
in almost the same direction does not even approach capacity, the initial
stadium traffic assignments may be modified so that both are providing
the same level of service.
28
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Traffic controls that will be used to alleviate stadium traffic congestion
should be considered in specifying the street capacities.
The capacity analyses for the approach and departure modes for an event
should be almost identical when using a one-hour traffic averaging time,
since volumes and directions of origin would be the same. Potential differences
are in incoming/departure street capacities and pre- and post-game non-
stadium traffic flows.
This procedure for a capacity analysis is explained by use of example
data in "Transportation Planning Considerations for New Stadia".2
ENTRANCE TIMES
Time spent entering a parking lot is a function of the rate at which vehicles
are attempting to enter the lot, the number of entrance lines, and the
average time required to collect the parking fee (service time). The
average vehicle inflow rate is determined by the capacity of the parking
facility or the number of vehicles assigned to it divided by the one-hour
pre-game ingress period previously discussed. The number of entrance lanes
or gates to the lot should be determined by the developer or from design
drawings (if the facility is a parking garage).
Average service time per vehicle ranges from about 0.10 minutes, where
parking is free or the fee is collected after the vehicle has parked, to
0.25 minutes in cases where there are inadequate attendants or a poor
entrance' configuration. This value is difficult to predict from design
data, since it is much more closely related to operational features of
the parking facility. If no estimate can be obtained from available data,
an average service time of 0.18 minutes should be used for parking lots
and 0.20 minutes for parking garages.
The above input data are then used to calculate running time in the entrance
mode by use of a modified version of the equation for queue waiting time
that was used for shopping center entrance and exit gates:
29
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(*)•
RT = b (T^ , where
a = utilization factor
(vehicle inflow rate, veh/min) (b)
(no. of entrance lines)
b = average service time, min.
The utilization factor, a, in this equation cannot equal or exceed 1.0.
If the first calculation of "a" shows a value of one or greater, this
indicates that the entrances are operating at capacity for the entire pre-
game hour and still have a remaining queue at the end of the hour. Under
this condition, "a" should be set equal to one (complete gate utilization)
and the same equation should be used to solve for the time needed to completly
fill the lot. This time is the denominator of the vehicle inflow,rate in
vehicles per minute. Carrying the calculation further, the number of cars
in each queue at the end of the first hour can be determined by dividing
the inflow time greater than one hour by the average service time, b. This
step follows because no more cars are entering the queue after the first
hour in the proposed simulation, so the queue dissipates to zero at the
constant rate of the service time over the extra time period. Finally,
since the queue length builds and dissipates at approximately constant
rates with time before and after the end of the hour as shown in Figure 2,
the average queue length over the entire period can be estimated as one-
half the previously calculated maximum queue length. Running time for
a > 1 is then:
RT = (average queue length) (av. service time)
= jknaxA (b) , Wher6
M = queue length, in vehicles
'30
-------
.c
01
JC
-4->
CD
C
-------
Use of the queueing equation is illustrated in the following example. The
stadium lot at RFK Stadium in Washington, D.C. is filled to its capacity
of 11,500 cars. There are 28 entrance lanes, and an average service
time of 0.18 minute is assumed. Average running time for the entrance
mode would be:
3 "
28
•'1.23
Since a > 1 .solve for total ingress time;
0.18
i = \ i /
1 28
t = 74 minutes
^nax.
= 78 autos
Mau. ' T
- 39 autos
RT = (39) (.18)
=7.0 minutes
The basic queueing theory equation employed here assumes that vehicles
reach the entrances randomly over the specified time interval and distribute
themselves optimally among the alternate entrances. Errors resulting from
these assumptions are thought to be much lower than those involved in
quantifying the input data (vehicle inflow rate and service time).
This procedure should only be used for off-street parking areas. The
portion of the vehicles that utilize on-street parking have no entrance,
movement in, movement out, or exit modes. The stadium parking facility
and private lots should be analyzed separately, because of demonstrated
differences in spectator parking preferences between these two types of
facilities. However, the private lots may be grouped together for a
single analysis under the following conditions:
32
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a. Very small lots (less than 50 cars) are excluded from the analysis;
b. The total number of entrances lanes can be accurately determined;
c. No strong driver preferences are indicated among the private lots; and
d. A single lot does not account for more than 30 percent of the vehicles
using private lots.
MOVEMENT OUT TIMES
In conventional parking facilities, all parking spaces have free access to
traffic aisles and vehicles can therefore depart at the driver's convenience.
Some stadium lots, because of their relative infrequent usage, have been
modified for more compact parking arrangements in which cars are parked
2 to 5 deep and cannot leave until all cars blocking their access to the
nearest aisle have moved. Typical space savings from "stall" parking are
shown in Table 6.
Table 6. AREA CONSUMPTION PER PARKING SPACE3
No.
in
of Cars
Stall
1
2
3
4
5
6
7
Area per Parking
Space, sq. ft.
262
209
191
182
176
173
170
While the running time in the movement-out mode from the parking space to
the end of the exit queue is negligible for the conventional parking lot,
it can be significant if the car is running but unable to move from the
space. This situation has been investigated by Hauer and Templeton,3
who have developed a probability function to estimate the average waiting
times associated with stall parking, based on the average cars-per-stall
33
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and the stadium emptying time. This function has been solved for cars-per-
stall values of 2 through 7, and the resulting average waiting times have
been summarized in Table 7.
Table 7. WAITING TIMES FOR EXIT FROM PARKING STALLS
Average Cars
Per Stall
2
3
4
5
6
7
Average Waiting Time,
Minutes
.083 (s.e.t.)*
.138 (s.e.t.)
.179 (s.e.t.)
.210 (s.e.t.)
.235 (s.e.t.)
.255 (s.e.t.)
* s.e.t. = stadium emptying time in minutes
The above derivation was primarily for application to a stadium event or
other large public gathering characterized by a single termination time,
so it should be appropriate for use. Important assumptions in the derivation
are:
a. All passengers of each car are considered as a single spectator with
a single arrival time at the car;
b. The spectators reach their vehicles randomly over a total period of
time which may be approximated by the emptying time of the stadium; and
c. The order of arrival of the spectators is completely independent of
their vehicles order in the parking stalls.
As previously mentioned, waiting time is not necessarily equal to running
time in the movement out mode, because the motorists may not start their
engines until their exit path is cleared. Returning spectators are more
likely to start their engines immediately in very warm or very cold outside
temperatures. No quantitative relationship has been determined for estimat-
ing running time as a function of waiting time and temperature.
34
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EXIT TIMES
A simple model is proposed for estimating average running times in the
exit mode. First, the model hypothesizes that vehicles begin leaving the
parking lot almost immediately following the end of the event and that
the rate of exiting from the time of this initial outflow until the lot
is emptied is determined by exit gate capacities for the lot. While this
assumption may not be valid for the first few cars and last exiting cars,
it does not appear to alter the final predicted value of running time
substantially because it is correct for almost all of the vehicles. Based
on this assumption, the total emptying time for a lot is calculated as
the number of parked vehicles divided by the gate capacity (in vehicles
per minute).
Observed values of capacity exiting rates show them to be of the same
magnitude as average service times upon entry--0.13 to 0.22 minutes per
vehicle, or 8 to 13 vehicles per minute per exit lane. Values are held
within this range by required merging and turning movements in the exit
areas.
The estimated total emptying time for a parking lot is a parameter that
is easily checked by observation. Calculated values are compared with
observations of stadium managers in Table 8. The good correlation partially
verifies the applicability of the proposed model.
Table 8. CALCULATED AND OBSERVED PARKING LOT EMPTYING TIMES
Stadium Lot
RFK
Busch
R1 ch
San Diego
Parking,
Vehicles
11,500*
5,200*
3,500
15,000*
13,500
16,200*
Exit Lanes
36
13
13
30
30
32
Calculated
Emptying Time,
Minutes
32
40
27
50
45
51
Observed
Emptying Time,
Minutes
40 to 45
35 to 40
20
75
40
60
* Ceoacity
35
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If all the vehicles were started at the time of initial outflow, the average
running time per vehicle would be one-half of the lot's emptying time.
However, the returning spectators actually start their cars and enter the
exit queues randomly over a time period equal to the stadium emptying
time (this same hypothesis was used for the movement-out made). Therefore,
the average running time is reduced by a time equal to one-half the stadium
emptying time, and is estimated as follows:
DT _ Parking lot emptying time - stadium emptying time
Kl - - p
This simple relationship appears to be quite adequate as an estimating
tool for capacity (peak) events and, in most cases, also for typical atten-
dances. As the stadium emptying time (s.e.t.) approaches the parking lot
emptying time (p.l.e.t.) for low-attendance events, the equation obviously
becomes unsatisfactory. When the p.l.e.t. minus the s.e.t. is less than
one or negative, the condition of random arrival at the queue is met and
the queuei ng theory equation can be employed to estimate the average
running time in the exit queue:
RT = b T^— , where
i —a
a = utilization factor
(vehicle outflow rate, yen/mi n) (b)
(no. of exit lines)
b = average service time, min.
The procedure is illustrated in the following example. Stadium parking
garages at Busch Stadium in St. Louis have a capacity 5,200 vehicles and
13 exit lanes. For one event, 4,400 spaces are filled. Exit running
time is:
Estimated max. rate/lane = 10 vehicles/minute
Total exiting rate = 10 (13 exit lanes)
= 130 vehicles/minute
D i e t - 440°
p.l.e.t.
s.e.t. =15 minutes
DT - p.l.e.t. - s.e.t.
= 9.4 minutes
36
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Exit analyses become more complex if parking lot egress is impeded by
street congestion immediately at the exit. If this condition exists
or is anticipated, the longer resulting exit times should be attributed
to the departure mode and the vehicles considered to be displaced from
the exit for purposes of analysis.
37
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SECTION VIII
RESULTS
METHODOLOGY
In general terms, the methodology proceeds as described in the first para-
graph which follows. It should be emphasized that this description is of
the technique, shown schematically in Figure 3, in its most general form,
and as such will provide the starting for each of the complexes to be
studied in subsequent tasks. Differences in implementation are expected
to arise in the case of each complex, and particularly for sports complexes.
Starting from the physical, geographic, and demographic characteristics of
the complex, relationships are established for estimating typical and peak
traffic volumes. The concepts of operational traffic modes are used to
generate best estimates of associated running times for cars. The parameters
of the center which significantly and adversely impact traffic behavior
are also defined. The typical trip rates and base running times provide
the data for typical conditions for the required time periods. Quantitative
relationships are defined or estimated for the controlling center parameters
and affected traffic modes, and these in turn are superimposed on the base
running times to generate peak running times. The peak running times are
then associated with peak trip generation rates to create the peak infor-
mation for the required time periods. This generality is modified somewhat
for application to each type of complex.
In the case of sports complexes, as shown in Figure 4, the methodology
proceeds from basic information about a given sports complex (see Section
V), via traffic behavior data (see Section VI) and traffic volume projections
(see Section VII) to.generate estimates of peak and typical numbers of
vehicles and associated running times per event. The same procedure for
38
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Characteristic
Parameters
of Complex
/Peak
/ Trip
V Generation
X^ Values.
Cjxceedance^
Values
1
Exceedance
Depen-
dencies
^ »(
r> ~
/^TypicaT\
( Trip )
^Generation/
N^ Values^/
Peak
Running
Times
Peak Values
of Numbers of
^Cars Running, andj.
Running
TTTTIP ,
s*<
fot
: Basic
Running
Time
'eakValuesX
of Numbers of \
•JGars Running, and]
Peak Running
Times
fypical Values>.
of Numbers of \
\Cars Running, andj
Base Running J
TIIDP.S
Figure 3. GENERALIZED METHODOLOGY
39
-------
Characteristic Parametersj
s^ of Sports Complexes ^/
\
Parking
Lot Data
1
Seating
Capacity and
Attendance
Projections
Traffic
Assignments
to Roadway -
Serving
Stadium
i
Parking Lot
Analyses
^
^
traffic Volume
Analyses
Pafk and
typical
^
w
Street
Capacity
Analyses
Entrance» Exit
and Movement
Out Running
Times
Peak Traffic
Volumes and
Peak Running
times
lypical Traffic
Volumes and
Fypical Running
Times
Figure 4. METHODOLOGY APPLIED TO SPORTS COMPLEXES
40
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calculating running times is employed for both peak and typical traffic
conditions.
Two significant one-hour periods can be analyzed individually for each
event—the hour immediately preceding the event and the hour immediately
following the event. Post-game running times are generally longer than
pre-game times. Any eight-hour period of interest would include both
of these hours, plus any runovers of traffic movement into adjacent hours.
The Quantitative descriptions of traffic volumes and running times for
the one- and eight-hour periods are the required end products of the task.
The specifics of the procedure are presented below. First, the attnedance
associated with peak and typical events at the stadium are delineated.
These are converted into number of vehicles coming to the event by determin-
ing the percent of spectators traveling by car and the average occupancy
per vehicle. After the total number of vehicles has been estimated, this
number is divided among the three available types of parking facilities
according to capacities and parking preferences.
Running times in six of the operating modes are then determined.
Because of reasons outlined in Section VII, it is not possible to develop
accurate estimates for running times in the approach and departure modes.
Running times in the stop and the start modes are probably always very
low--the value of 0.1 minute used in the first task report is still
appropriate here. Because the parking lots at stadiums generally have
supervised parking, movement into a parking space becomes primarily a
function of the type and size of parking facility. The average running
time for this mode, which should be relatively independent of traffic
volume, can probably best be estimated from a diagram of the stadium
parking areas. Running times in the entrance, movement out, and exit
modes are estimated by the procedures presented in Section VII as functions
of the number of vehicles parked and physical characteristics of parking
lots.
41
-------
A schematic diagram similar to Figure 1 may be helpful in analyzing the
operating modes at the different parking areas around the stadium under
investigation. The average running times for the total stadium traffic
are simply the weighted averages of running times for all the segments
that are analyzed separately. On-street parking, for instance, does not
generate running times other than small times for movement in, stop, start,
and movement out. However, it does contribute to the traffic volume
considered in the street capacity analysis.
Finally, the street capacity analysis is performed to test the adequacy
of the access routes to and from the stadium (see Section VII). The results
of this analysis are not additive with those from the other modes;
rather, they indicate a potential problem and the need for further
traffic studies.
In summary, the main concerns for a sports complex are for adequate parking
capacity, adequate parking lot gate capacity, and adequate street capacity.
GEOGRAPHIC DISTRIBUTION
The sports complex is characterized by infrequent but extremely high volume
traffic and therefore is prone to capacity excesses and queueing problems.
Running times, and hence emissions, at a sports complex are usually
concentrated around entrances, exits, and points of constriction and merging
along the access routes.
Running times within the lots are relatively low because of supervised parking,
except in the case of exit queues extending throughout the parking facility.
A less common circumstance leading to high running times in the parking area
is the blocking of vehicles attempting.to exit from stall parking (cars
parked two or more deep).
Other isolated points of traffic congestion are passenger discharge/pickup
areas and pedestrian street crossings.
The procedure of estimating running time for each mode individually allows
some of these areas of high emission density to be evaluated quantitatively.
Emissions from a queue or an access street carrying its capacity can be
simulated as a continuously emitting line source.
42
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METEOROLOGICAL ASPECTS*
The meteorological characteristics which most importantly affect atmospheric
dilutive capacity are mixing height, wind speed and atmospheric stability.
A convenient summary of mixing height and wind speed characteristics which
affect air pollution potential is given in the Office of Air Programs
Publication No. AP-101 (Holzworth 1972). Atmospheric stability may be
determined in terms of cloud cover, solar radiation and wind speed by a
method proposed by Pasquill and shown in Table 9. For ground level sources,
such as automobiles in stadium parking lots, the ground level concentrations,
both in the vicinity and downwind of the sources will be inversely propor-
tional to wind speed and mixing height and directly proportional to atmospheric
stability (i.e., the more stable the atmosphere, the higher the concentration).
The season of peak use of stadiums is cited as late fall-early winter in
Section V titled "Parameters for Outdoor Stadiums", with the highest day
usually being a late fall Saturday or Sunday. The peak hour of use on any
given weekend is generally during departure, say, 5 to 6p.m. The peak
eight-hour period would encompass the entrance period (1 to 2p.m.) as
well as the exit period, and thus would run about, say, noon to 8p.m.
Since the period of concern occurs during the transition from autumn to
winter, the meteorological conditions which characterize the period of
use of stadiums should be estimated by interpolating between autumn and
winter means. Mean afternoon wind speeds and mixing heights for autumn
and winter, for locations in the contiguous United States, are shown in
Figures 5 through 8, taken from Holzworth, 1972. An occasional evening
secondary peak is discussed later. For most locations the diurnal variation
in mean wind speeds is small, and the values shown for afternoon means may
also be used for the rare evening peak use period. Also, since the transition
to a strong restraining nighttime mixing height has generally not occurred
by early evening hours, the afternoon mixing height can serve as a useful
estimate for any evening peak use period. For the weekend afternoon peak,
* This section was prepared by Mr. Robert C. Koch, Senior Research Scientist
of GEOMET, Incorporated.
43
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Table 9. KEY TO STABILITY CATEGORIES (after Turner 1970)
Surface Wind
Speed (at 10 m) ,
m sec"1
<2
2-3
3-5
5-6
Day
Incoming Solar Radi
ation
Strong Moderate Slight
A A-B
A-B B
B B-C
C C-D
>6 C C
B
C
C
D
D
Night
Thinly Overcast
or
>_ 4/8 Low Cloud
E
D
D
D
<3/8
Cloud
F
E
D
D
The neutral class, D, should be assumed for overcast conditions during day
or night.
NOTE: Class A is the most unstable, class F the most stable class. Night
refers to the period from 1 hour before sunset to 1 hour after sunrise.
Note that the neutral class, D, can be assumed for overcast conditions
during day or night, regardless of wind speed.
"Strong" incoming solar radiation corresponds to a solar altitude greater
than 60° with clear skies; "slight" insolation corresponds to a solar
altitude from 15° to 35° with clear skies. Table 170, Solar Altitude and
Azimuth, in the Smithsonian Meteorological Tables (List 1951) can be used
in determining the solar altitude. Cloudiness will decrease incoming
solar radiation and should be considered along with solar altitude in
determining solar radiation. Incoming radiation that would be strong
with clear skies can be expected to be reduced to moderate with broken
(5/8 to 7/8 cloud cover) middle clouds and to slight with broken low
clouds.
44
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Figure 5. ISOPLETHS (m sec'l) OF MEAN AUTUMN WIND SPEED AVERAGED THROUGH THE AFTERNOON MIXING LAYER
-------
ON
Figure 6. ISOPLETHS (m sec'l) OF MEAN WINTER WIND SPEED AVERAGED THROUGH THE AFTERNOON MIXING LAYER.
-------
10
12
14
Figure 7. ISOPLETHS (m x 102) OF MEAN AUTUMN AFTERNOON MIXING HEIGHTS
-------
t>
00
10
Figure 8. ISOPLETHS (m x 102) OF MEAN WINTER AFTERNOON MIXING HEIGHTS
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atmospheric stability classes B, C, and D may occur with classes C and
D being the most prevalent. During any evening hour peak, classes D
and E may occur. Atmospheric dispersion calculations reported by Turner
(1970) for stability classes D and E show that ground level concentrations
from ground level sources will generally be twice as high for class E as
for class D. Therefore, if an evening peak use period occurs, it will
probably be associated with more stable conditions, and may be the more
critical period for air quality considerations from the viewpoint of joint
consideration of peak use and adverse meteorology.
The period when meteorological conditions are least favorable for diluting
pollutants is the period when stadiums are essentially not in use.
This would be from very late evening until a few hours after sunrise. It
is most often during this period that mixing heights are lowest, wind
speeds are lowest, and atmospheric stability is greatest. For most parts
of the country, autumn is the season when the least favorable conditions
are most likely to occur.
If one now considers that there may be a fall or early winter evening
game occasionally, then, from a meteorological point of view, the single
hour least favorable for dispersing pollutants during that period would
be during departure, from say, from llp.m. to midnight, during the autumn
season. The least favorable eight-hour period would be from 4 to midnight.
QUALITATIVE GUIDELINES
In addition to the quantitative evaluation procedures developed above, the
review of sports complexes as complex emission sources should also include
the following considerations which are not presently reducible to quantitative
terms:
1. Conflicts between large numbers of pedestrians and traffic, both
concentrated in the same time frame and in the area of the stadium, can
cause substantial increases in running times. The interruption of traffic
flow can be minimized by extensive use of grade separations—bridges, ramps,
and underpasses--and by close-in curb frontage for high-volume discharge
and pickup of passengers.
49
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2. Temporary traffic controls, particularly reverse-flow one-way streets,
can be very effective for increasing access route capacities in the vicinity
of the stadium. These traffic controls are particularly important for
stadiums that are located in built-up downtown areas where lanes cannot be
added to existing streets.
3. The developer should provide plans for expected traffic circulation
patterns around the stadium. These should be checked for:
- no left turn movements across traffic
- right turns in and out for garage traffic
- maximum use of one-way and divided streets
- two-lane exits from parking lots onto streets.
4. Traffic information signs should be promimently displayed to improve
traffic movement.
THE NINE QUESTIONS
While the specific information called for by the task work statement has
been provided in Sections V through VIII, the nine questions spelled
out as part of the work statement warrant specific response. This is
given here, with the questions abbreviated.
1. Area allotted to or occupied by a single vehicle? See Table 6 and
accompanying text.
2. Percentage of land and parking spaces potentially occupied by
vehicles? The usual percentage? The stadium proper occupies about 15
acres. If streets are internal to the complex, they may account for
3 to 5 acres. The remainders of the gross stadium areas shown in Table 1
are devoted to parking. This averaged about 85 percent.
3. Typical and peak values (absolute or fractional) of vehicles running
for one- and eight-hour periods? All of the vehicles are running during
the typical and peak one-hour periods. All of the vehicles complete one
cycle of operating modes during the typical and .peak eight-hour periods.
4. Typical and worst case (slowest) vehicle speeds? In the context
of our approach, this question is only relevant to analysis of the "Major
Highway" complex source task. It will be dealt with in that task report.
50
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5. Vehicle distribution within the complex? See subheading entitled
Geographic Distribution in Section VIII.
6. Design parameters of the complex likely to be known beforehand?
See Section V, Parameters for Outdoor Stadiums.
7. Design parameters in question (6) which can be most successfully
related to traffic, and hence emissions? See Section VII, Analysis.
8. Relationships of parking lot design to parking densities and vehicle
circulation? What is typical design? Design with highest parking densities,
lowest vehicle speeds, longest vehicle operating times? To the extent
to which these questions are relevant to our methodology, they are answered
in the Sections VI and VII.
9. Meteorological conditions likely to occur during peak use? Use
level during periods of worst meteorology? See the subheading entitled
Meteorological Aspects in Section VIII.
51
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SECTION IX
REFERENCES
(l)The Stadium: All American Monument. Progressive Architecture. November 1971
(2)Ashwood, J.t. Transportation,Planning Considerations for New Stadia.
Traffic Engineering, Vol. 143, No. 10. July, 1973.
(3)Hauer, E. and J.G.C. Templeton. Queuing in Lanes. Traffic Quarterly.
(4) tJitherford, O.K. and G.E. Kanaan. Zoning, Parking and Traffic. The Eno
Foundation, Saugatuck, Corr. 1972. ,
(5)A Study of Emissions from Light Duty Vehicles in Six Cities. Automotive
Environmental Systems, Inc. Environmental Protection Agency Publication
No. APTD-1497. March, 1973.
(6) Compilation of Air Pollutant Emission Factors. Environmental Protection
Agency Publication No. AP-42, Second Edition. April, 1973.
(7) Proposed Roadway Improvements, Jackson County Sports Complex Area. Howard,
Needles, Tammen and Bergendoff, Kansas City, Missouri. February, 1969.
(8) Holzworth, G.C. 1972. Mixing Heights, Wind Speeds, and Potential for Urban
Air Pollution Throughout the Contiguous United States. U.S. Environmental
Protection Agency, Office of Air Programs, Research Triangle Park, N.C.
AP-101.
(9) Turner, D.B. 1970. Workbook of Atmospheric Dispersion Estimates.
U.S. Department of Health, Education, and Welfare, National Air Pollution
Control Administration, Cincinnati, Ohio. AP-26.
52
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TECHNICAL REPORT DATA
(Please read Instructions on the reverse before completing)
1. REPORT NO.
EPA-450/3-74-003-C
2.
3. RECIPIENT'S ACCESSION-NO.
4. TITLE AND SUBTITLE
Vehicle Behavior In and Around Complex Sources and
Related Cornel ex Source Characteristics
Volume III - Sports Stadiums
5. REPORT DATE
September, 1973 (Date of issue
6. PERFORMING ORGANIZATION CODE
7. AUTHOR(S)
Scott D. Thayer
Kenneth Axetell, Jr., Consultant
8. PERFORMING ORGANIZATION REPORT NO.
9. PERFORMING ORG MM IZ ATI ON NAME AND ADDRESS
Geomet, Inc.
50 Monroe Street
Rockville, MD 20850
10. PROGRAM ELEMENT NO.
11. CONTRACT/GRANT NO.
68-02-1094
12. SPONSORING AGENCY NAME AND ADDRESS
Office of Air Quality Planning and Standards
Environmental Protection Agency
Research Triangle Park, North Carolina 27711
13. TYPE OF REPORT AND PERIOD COVERED
Final
14. SPONSORING AGENCY CODE
15. SUPPLEMENTARY NOTES
16. ABSTRACT
A general methodology is presented for relating parametersof traffic behavior
at sports stadiums, including vehicle running time, traffic volume and vehicle
occupancy, to more readily available characteristics of stadiums, including seating
capacity, parking capacity and stadium emptying time. Such relationships are to be
used to relate staduim characteristics to air quality.
17.
KEY WORDS AND DOCUMENT ANALYSIS
DESCRIPTORS
b.lDENTIFIERS/OPEN ENDED TERMS
c. COSATl Field/Group
Air pollution, stadiums, urban planning,
traffic engineering, transportation manage-
ment, transportation models, land use,
regional planning, urban development, urban
transportation, vehicular traffic, highway
planning
Indirect sources
Indirect source review
13 B
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