HomeMy WebLinkAboutSP201500023 Study 2012-02-01 Research Findings for Drive-Through Windows
- Orient town alley, driveway,or interior parking areas and not to a street.
- Do not locate within 20 feet of a street and not oriented to a street corner. Walk up only tellers
and kiosks may be oriented to a street or placed adjacent to a street corner.
- No more than one drive-through shall be permitted for a distance of 400 hundred linear feet
along the same block face (same side of the street).
- Drive-through lanes shall be separated from the sidewalk by a planting strip at least 5 feet in
width.
- Drive-through lanes shall not restrict pedestrian access between the sidewalk and on-site
buildings. Where pedestrian routes cross drive through lanes a crosswalk that is raised or
features a change in texture and/or other treatment must be utilized to enhance the safety and
visual appearance of the pedestrian crossing.
- Drive-through lanes visible from internal access roads and customer parking lots shall provide a
planting strip at least 5 feet in width between the drive-through lane and any sidewalk or other
vehicular access route.
- Drive-through lanes shall not be located in the area between a building and a public street and
the drive-through window shall not face a public street.
- A 100 foot separation distance from all parts of the drive-through facility, including stacking
lanes,to the edge of the lot line of any residential use or zone where residential uses are
permitted.
- Locate building close to or at the street to define and support the street edge and align new
buildings with the front facades of existing buildings.
- Drive-through sites and buildings should be designed to:
o Locate the main entrance door directly off the public sidewalk.
o Locate the main entrance doo at the corner or on the more major street, on a corner
lot.
o Locate uses that support the street along the public sidewalk(outdoor seating).
o Make walls along the street face and visible from the street,transparent with windows,
door and other forms of transparent building materials to maximize views in and out of
the building and the relationship between interior and exterior to support and animate
the public street and sidewalk.
- Do not locate stacking lanes or driveways between the building and the street.
- Locate stacking lanes and driveways out of view of the public street and/or sidewalk, at the rear
and/or flank of the building.
- Provide a minimum of 10 stacking spaces on site for restaurant and food sales.
- Provide a minimum of 4 stacking spaces on site for banking, pharmacies and similar non-food
related uses.
- Provide stacking spaces which are 11.5 feet in width and 21 feet in length.
- Multiple windows servicing a single stacking lane should be considered to reduce idling.
- Multiple stacking lanes for a single user are discouraged.
- Provide sufficient signage where necessary to indicate direction of vehicular travel,stop signs
and no entrance areas.
Provide vehicular site access from the side or less major street.
- Do not locate parking or vehicular site exits or entrances between the building and the street.
- Provide parking adjacent to the secondary entrance doors to the facility such that it is not
necessary for pedestrians who arrive by car to cross driveways or stacking lanes to enter the
interior of the building.
- Provide and clearly demarcate separate,safe pedestrian circulation routes in conjunction with
vehicular circulation for the drive-through facility and larger site using techniques such as raised
pedestrian crossings,change in paving, bollards and landscaping to separate them from stacking
lanes and driveways.
- Provide pedestrian circulation routes that are a minimum of 5 feet wide and barrier free.
- Provide continuous soft landscaped areas no less than 8 feet in width,to define stacking lanes.
- Maintain site lines from stacked cars to pedestrian crossings by providing low soft landscaping in
such areas.
- Stacking lanes should be located away from residential properties.
- Site layout shall provide clear and distinct separation of vehicular and pedestrian traffic.
- Mid-block sites are preferred for drive-through facilities.
- Located at mid-block locations within larger developments away from corners and intersections.
- Windows shall be located at side and/or rear facing the internal area of larger developments.
- Where a drive-through facility abuts a residential use,the intercom order station should be
located as far away as possible from the residential property line. Order station speakers shall
be shielded and directed away from residential areas.
- Intercom order stations should be located away from the main site entrance and initial turning
movements.
- Drive-through menu boards and other information displays shall be located near the intercom
order stations.
- Order stations should be situated well into the stacking lanes where possible.
- Entrances and exists for vehicles shall be located as far from corner intersections as possible to
minimize disruption of street traffic flow.
- Where two drive-through facilities are located on the same site or adjacent to each other,
stacking lanes shall be separated.
- Stacking lanes and their circulation could include escapee lanes at logical and functional
locations.
- Stacking lanes shall not conflict with access to parking areas, driveways,service or loading areas.
The use of soft and hard landscaping,decorative pavement, painted lines,strips or low walls not
higher than 3.5 feet to delineate and separate stacking lanes from these areas is encouraged.
- Locate the start point to the stacking lane at the rear of the site so that queued vehicles do not
block traffic along the public streets or the movement of other vehicles on site.
- Do not locate stacking lane between the building and the public street.
- Separate stacking lanes from parking areas and driveways using 5 foot wide landscaped islands.
- Provide views and clear sightlines between the site and surrounding uses to ensure sufficient
safety and comfort levels.
- Drive-through lanes shall be a minimum of 12 feet in width. The lane shall be independent of
any onsite parking, parking maneuvering areas, public streets, alleys or traffic ways.
- Drive-through aisles shall have a minimum width of 10 feet and 12 feet at curves.
- Each drive-through entrance/exit shall be at least fifty feet from any intersection of public
streets measured at the closest intersecting curbs, and at least 25 feet from entrances on
adjacent property.
- When located within 100 feet of any residential property line hours of operation shall be limited
from 7:00 a.m to 10:00 p.m. daily.
- Stacking lanes shall not enter or exist directly onto a public street.
Design Sketches
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Issues not addressed
- Speakers
- Security
- Stacking lanes cannot block parking.
- Direction of travel in stacking lane should be same as any adjacent travelway.
- Noise
- Space after window.
Recommended#of stacking spaces;
Bank—5-8 or 150-160 feet
Car Wash—3-6 or 140 feet
Coffee Shop—10-13 or 260 feet
Fast Food—8-12 or 240 feet
Pharmacy—2-4 or 100 feet
Dry Cleaner—50 feet
General Standards for Drive-Throughs
Proposed Conditions
(1) Buffer. Any drive-through located within 30 feet of a resicten'tial zoning district shall
provide a landscape buffer and/or screening as approvd the Albemarle County
Planning Director or agent.
(2) Stacking Lanes.
a. Design. Stacking lanes shall be provided for any use having a drive-through
establishment and shall comply with the following standards:
i. Drive-through stacking lanes and bypass lanes (where provided) shall
have a minimum width of 10 feet.
ii. When stacking lanes are separated from other stacking lanes, from bypass
lanes, or from other site areas, the separation shall be by means of a raised
concrete median, concrete curb, or landscape area.
b. Stacking.
i. The number of required stacking spaces shall be as provided for in this
section.
ii. Specific Uses.
Banks 160 feet (8 vehicles)
Car Washes 140 feet (7 vehicles)
Coffee Shops 140 feet (7 vehicles)
Fast Food Restaurants 140 feet(7 vehicles)
Pharmacies 100 feet (5 vehicles)
iii. ITE and other professional studies may be submitted to allow for alternate
stacking requirements.
iv. Stacking includes the car being serviced at the drive-through window.
v. In the event that multiple lanes are provided for one (1) use, the total
stacking provided shall be the accumulative number of vehicles provided
in all of the lanes.
(3) Circulation.
a. Traffic Control Devices. Installation and maintenance of traffic control devices,
including but not limited to signage and pavement markings, shall be provided to
promote safe circulation of automobiles, bikes and pedestrians.
b. Pedestrian Crossing. Pedestrian crossings shall be provided on-site to allow for
the safe passage of pedestrians to the establishment.
c. Circulation shall be designed to minimize the conflicts between vehicles and
pedestrians.
d. Bypass lanes are desirable for each establishment, but they are not required.
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Drive-Through Queue Generation,
1st Edition
Mike Spack, P.E.— CountingCars.com
Nate Hood—CountingCars.corn
Max Moreland—Counting Cars.com
Lindsay de Leeuw—CountingCars.com
wa r-o0s` ' a a o x s
Businesses with drive-through lanes are commonplace in the United States. Yet, up-to-date queue-generation
data is not available. The most recent ITE article published on the topic was in 1995 (ITE Technical Council
Committee 5D-10) using data collected between the late 1960s and early 1990s.
Things have changed in the past 17 years, and we felt it was necessary to create an up-to-date report that
provided accurate queuing data for businesses with drive-through lanes to aid engineers and site designers.
The data was modeled similar to that of the Institute of Transportation Engineers' Trip Generation and Park-
ing Generation reports and a presentation by Mark Stuecheli at the 2009 ITE Annual Meeting that concen-
trated on bank and coffee shop drive-through lanes.
Of course, this type data collection effort is daunting using staff in the field to count cars. This issue was
solved by developing new hardware and software systems. For this project, portable COUNTcams were
used to collect 1,220 hours of drive-through video footage for up to five straight days at a minimum of six lo-
cations for each land use. Videos were collected throughout Minneapolis and several suburbs between 2010
and 2012 at banks, car washes, coffee shops, fast food restaurants and pharmacies.
The 1,220 hours of videos were watched in 120 labor hours at high speeds using PC-TAS counting software
and maximum queues throughout the day were recorded. The COUNTcam video system made it possible to
observe the drive-through lanes 24 hours a day and the PC-TAS software made the data reduction practical.
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(1-494 and 34th Avenue S Diverging Diamond Interchange continued from page 10)
Once the maximum queue length for each day at each location was determined, the data was compiled and
statistics for each land use were calculated. The average maximum queue, standard deviation, coefficient of
variation, range, 85th percentile and 33`d percentile were calculated (see Table 1).
Designers can choose whether the average maximum queue or the 85th percentile maximum should be de-
signed to. As conservative engineers, we lean towards the 85th percentile maximum. Based on the findings,
the following design queues are recommended (assuming each vehicle occupies 20 feet in the queue, which
matches our observations):
• Banks: 160 feet (eight vehicles)
• Car washes: 140 feet (seven vehicles)
• Coffee shops: 260 feet (13 vehicles)
• Fast food restaurants: 240 feet (12 vehicles)
• Pharmacies: 100 feet (five vehicles)
Table 1: Queue Statistics
Fast Food Coffee Shops Banks Pharmacies Car Washes
Number of Data Points 14 26 21 12 12
Average Maximum Queue(vehicles) 8.50 10.23 5.76 2.92 4.42
Standard Deviation(vehicles) 2.68 2.76 2.21 1.16 2.31
Coefficient of Variation 32% 27% 38% 40% 52%
Range(vehicles) 5 to 13 3 to 16 1 to 10 1 to 5 1 to 10
85th Percentile(vehicles) 12.00 13.00 8.00 4.05 6.20
33rd Percentile(vehicles) 7.90 9.91 5.00 2.00 3.00
Fast food restaurants and coffee shops have the longest maximum queues of the five land uses observed.
Coffee shops have a maximum 85th percentile queue of 13 vehicles and fast food restaurants have a maxi-
mum 85th percentile queue of 12 vehicles. Coffee shops have a tendency for the morning queues to build up
so long that they spill out onto the street, though, as is expected, their afternoon and evening queues are
minimal. Fast food restaurants typically have sizeable queues, but they tended to have enough dedicated
space that stacking did not go beyond the designated queuing area. Bank and pharmacy drive-through lanes
seem to be significantly over-designed for today's use. Car washes also seem to be significantly overd-
esigned, but they can have significant peaks in Minnesota based on weather conditions. Extreme peak con-
ditions may not have been observed.
To read the full study, including data from each site observed, please visit MikeonTraffic.com.
coursnriNGcors
,q®n
Drive-Through Queue Generation
Mike Spack, PE, PTOE, Max Moreland, EIT, Lindsay de Leeuw, Nate Hood
1.0 Introduction
This report provides queuing data for businesses with drive-through services. It is intended to
be an aid for site designers and reviewers, similar to the Institute of Transportation Engineers'
Trip Generation and Parking Generation reports. The data presentation is modeled on the
Parking Generation report and data is provided based on at least six sites, similar to data sets
marked as statistically significant in Trip Generation.
Businesses with drive-through lanes are very common in the United States and having data that
gives usage information for drive-through lanes will assist designers as well as cities in
determining the appropriate amount of storage needed for proposed drive-through businesses.
Data for drive-through queues was published by the ITE Technical Council Committee 5D-10 in
1995 based on information collected between the late 1960's and the 1990's. A paper was also
published in 2009 by Mark Stuecheli, PTP giving updated information for bank and coffee shop
drive-through lanes. The results from the 2009 study are incorporated into this paper (thank
you Mark for your assistance).
2.0 Data Collection
Data was collected using COUNTcam video recording systems at a total of 30 drive-through
locations in Minneapolis, MN and several surrounding suburbs between 2010 and 2012 (26 of
the 30 videos were recorded in February of 2012, which should represent peak usage in the
cold Minnesota winter). Videos of drive-through lanes were collected at banks, car washes,
coffee shops, fast food restaurants and pharmacies. A total of six locations were selected for
each of the five different land uses. Each location was recorded for between one and five days
where the majority of locations were recorded for two consecutive days. The days of the week
that each video was recorded on varies.
The 24-hour videos were watched at high speeds with the PC-TAS counting software and
maximum queues throughout the day were noted. Most of the COUNTcams were set up such
that the entire queue lane could be seen, but at a few locations the drive-through lanes
wrapped around the building in a way that the entire queue length would not be able to be
seen. For these situations, the COUNTcams were set up so that the ordering window and back
of the queue could be seen and it was noted how many vehicles could fit between the ordering
window and the front of the queue. For drive-through locations with multiple lanes, the
number of lanes was noted but the maximum queue is defined as the sum of the queues at
each lane for any given point in time, not the queue per lane. This approach provides overall
demand, which may assist designers in determining how many drive through lanes are
appropriate in addition to determining how long they should be.
Drive-Through Queue Generation 1 February 2012
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Once the maximum queue for each day at each location was determined, the data was
compiled and statistics for each land use were calculated. The average maximum queue,
standard deviation, coefficient of variation, range, 85th percentile and 33rd percentile were
calculated for each land use.
Data for drive-through coffee shops and banks from the Kansas City, Kansas metropolitan area
was published in the 2009 paper New Drive-Through Stacking Information for Banks and Coffee
Shops by Mark Stuecheli. This data is included in the analysis.
3.0 Data Analysis
Based on the peak queue lengths, it is apparent that each land use will require a different
minimum drive through stacking distance. The results for each land use can be found below.
The peak queue lengths for each location, broken down by land use and day of the week, can
be found in the Appendix.
3.1 Banks
Data collection was done at six banks with drive-through services (including one credit union) in
August 2011 and February 2012. Twelve days of data were collected. The banks were located
in the cities of Minneapolis, Robbinsdale and St. Louis Park, MN.
All of the locations had a lane with a drive-through ATM and at least two other lanes. Though
service times may differ for ATM lanes compared to the regular lanes, the maximum queues
were counted together. This is because based upon what was observed, vehicles would
occasionally switch the lane they were in. For example,a vehicle waiting in the ATM line with a
queue of three vehicles may move over to a regular line with a queue of only one vehicle.
Much of what can be done at the bank's drive-through lane can also be accomplished at that
bank's ATM and vice versa. Vehicles being served were counted as being in the queue.
Nine days of data from the Kansas City, Kansas area is also included. This data does not factor
in vehicles in ATM lanes.
Table 3.1—Drive-Through Bank Maximum Queue Statistics
Minnesota Data Minnesota+Kansas Data
Number of Data Points 12 21
Average Maximum Queue(Vehicles) 5.83 5.76
Standard Deviation(Vehicles) 1.85 2.21
Coefficient of Variation 32% 38%
Range(Vehicles) 3 to 8 1 to 10
85th Percentile(Vehicles) 8.00 8.00
33rd Percentile(Vehicles) 5.00 5.00
Drive-Through Queue Generation 2 February 2012
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Figure 3.1.1—Drive-Through Bank Maximum Queue Frequency—Minnesota Data
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Figure 3.1.2—Drive-Through Bank Maximum Queue Frequency—Minnesota + Kansas Data
Drive-Through Queue Generation 3 February 2012
COUNTINGCCWS,COM
The data for Kansas banks was collected between 4:30pm and 6:00pm. While many of the
maximum queues for the data collected in Minnesota were between these times, maximum
queues occurred between 8:30am and 5:30pm so it is possible that some of the Kansas data
does not capture the actual maximum queues for the day.
The number of available lanes at banks, not including the ATM lane, ranged from two to seven
lanes (though the most open at one time was five lanes). Even though plenty of lanes were
available, cars often stacked at the lane closest to the building, thus additional lanes may not
result in shorter queues. With an 85th percentile maximum queue of eight vehicles, the data
suggests that banks with drive-through lanes should be able to accommodate 160 feet of
vehicle stacking.
3.2 Car Washes
Data collection was done at six car washes with drive-through services (including one full-
service car wash) in February 2012. Twelve days of data were collected. The car washes were
located in the cities of Falcon Heights, Hopkins, Minneapolis, Roseville and St. Louis Park, MN.
Five of the six car washes (excluding the full-service car wash) were located at gas stations.
Only the vehicles waiting in line were counted; vehicles being washed were not added to the
queue.
Table 3.2—Drive-Through Car Wash Maximum Queue Statistics
Number of Data Points 12
Average Maximum Queue(Vehicles) 4.42
Standard Deviation(Vehicles) 2.31
Coefficient of Variation 52%
Range(Vehicles) 1 to 10
85th Percentile(Vehicles) 6.20
33rd Percentile(Vehicles) 3.00
Drive-Through Queue Generation 4 February 2012
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Figure 3.2—Drive-Through Car Wash Maximum Queue Frequency
Two of the car washes had two lanes while the other four were one lane car washes. The full-
service car wash had two lanes and also produced the highest maximum queue of 10 vehicles.
The maximum queues for car washes were spread throughout the afternoon from 12:30pm to
8:30pm. With an 85th percentile maximum queue of more than six vehicles, the data suggests
that car washes with drive-through lanes should be able to accommodate 140 feet of vehicle
stacking throughout the day.
3.3 Coffee Shops
Data collection was done at six coffee shops with drive-through services in November 2010,
August 2011 and February 2012. Fourteen days of data were collected. The coffee shops were
located in the cities of Edina, Hopkins, Minneapolis, Roseville and St. Louis Park, MN. Vehicles
being served were counted as being in the queue. Twelve days of data from the Kansas City,
Kansas area is also included.
Table 3.3—Drive-Through Coffee Shop Maximum Queue Statistics
Minnesota Data Minnesota+Kansas Data
Number of Data Points 14 26
Average Maximum Queue(Vehicles) 11.00 10.23
Standard Deviation(Vehicles) 2.25 2.76
Coefficient of Variation 20% 27%
Range(Vehicles) 7 to 16 3 to 16
85th Percentile(Vehicles) 13.50 13.00
33rd Percentile(Vehicles) 10.00 9.91
Drive-Through Queue Generation 5 February 2012
COUNTINQCOrS
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Maximum Queue Length(Vehicles)
Figure 3.3.1—Drive-Through Coffee Shop Maximum Queue Frequency—Minnesota Data
6
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Maximum Queue Length(Vehicles)
Figure 3.3.2—Drive-Through Coffee Shop Maximum Queue Frequency-MN + KS Data
Drive-Through Queue Generation 6 February 2012
COUNTINGCarS.COM
Coffee shops produced the longest maximum queues of any of the land uses in this study with
all of the maximum queues occurring in the morning. In four of the six cases, the queues spilled
out of the parking lot and into the street. These spillovers would typically only happen once or
twice a day and last only a few minutes, however, one location had stacking into the street for
about 15 minutes in addition to multiple periods of several minutes where cars would queue in
the street.
With an 85th percentile maximum queue of 13 vehicles, the data suggests that coffee shops
with drive-through lanes should be able to accommodate at least 260 feet of vehicle stacking
during morning hours.
3.4 Fast Food Restaurants
Data collection was done at six fast food restaurants with drive-through services in August 2011
and February 2012. Fourteen days of data were collected. The restaurants were located in the
cities of Golden Valley, Hopkins, Minneapolis and St. Louis Park, MN. Vehicles being served
were counted as being in the queue.
Table 3.4—Drive-Through Fast Food Restaurant Maximum Queue Statistics
Number of Data Points 14
Average Maximum Queue(Vehicles) 8.50
Standard Deviation(Vehicles) 2.68
Coefficient of Variation 32%
Range(Vehicles) 5-13
85th Percentile(Vehicles) 12.00
33rd Percentile(Vehicles) 7.90
Drive-Through Queue Generation 7 February 2012
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Maximum Queue Length(Vehicles)
Figure 3.4—Drive-Through Fast Food Restaurant Maximum Queue Frequency
The maximum queues for fast food restaurants were spread throughout the day from 8:00am
to 10:00pm. With an 85th percentile maximum queue of 12 vehicles, the data suggests that fast
food restaurants with drive-through lanes should be able to accommodate 240 feet of vehicle
stacking throughout the day.
3.5 Pharmacies
Data collection was done at six pharmacies with drive-through services in February 2012.
Twelve days of data were collected. The pharmacies were located in the cities of Hopkins,
Minneapolis, New Hope and Robbinsdale, MN. Vehicles being served were counted as being in
the queue.
Table 3.5—Drive-Through Pharmacy Maximum Queue Statistics
Number of Data Points 12
Average Maximum Queue(Vehicles) 2.92
Standard Deviation(Vehicles) 1.16
Coefficient of Variation 40%
Range(Vehicles) 1-5
85th Percentile(Vehicles) 4.05
33rd Percentile(Vehicles) 2.00
Drive-Through Queue Generation 8 February 2012
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Figure 3.5—Drive-Through Pharmacy Maximum Queue Frequency
The maximum queues for pharmacies were spread throughout the day from 8:00am to
10:00pm. With an 85th percentile maximum queue of more than 4 vehicles, the data suggests
that pharmacies with drive-through lanes should be able to accommodate 100 feet of vehicle
stacking throughout the day.
4.0 Conclusions
The 85th percentile maximum queue lengths for each land use are: 160 feet for banks (eight
vehicles), 140 feet for car washes (seven vehicles), 260 feet for coffee shops (13 vehicles), 240
feet for fast food restaurants (12 vehicles) and 100 feet for pharmacies (five vehicles).
While some of the locations observed have an excess of space dedicated to drive-through lanes
(i.e. some banks and pharmacies), others could occasionally use additional space for drive-
through lanes (i.e. coffee shops in the morning).
Fast food restaurants and coffee shops have the longest maximum queues of the five land uses
observed. Coffee shops have a tendency for the morning queues to build so long that they spill
out onto the street,though, as is expected, their afternoon and evening queues are minimal.
Fast food restaurants also have large queues, but they tended to have enough dedicated space
that stacking did not go beyond the designated queuing area.
Drive-Through Queue Generation 9 February 2012
�- r
COLINTINGCCIraCOM
The data collected for this paper along with the data from the papers by Mark Stuecheli and the
ITE Technical Committee 5D-10 (see Appendix for both of these) will hopefully provide useful
data for traffic engineers and others trying to analyze drive-through queuing storage areas.
5.0 Labor Savings of the COUNTkit
Deploying people in the field to perform this data collection would not have been feasible.
Using the COUNTcam video system made it possible to observe the drive through lanes 24
hours a day and the PC-TAS software made the data reduction practical. One location was
recorded in November 2010 for 6 hours,three locations were recorded in August 2011 for a
total of 202 hours and 26 locations were recorded in February 2012 for a total of 1012 hours.
These 1220 hours of video were counted with a total of 120 hours of labor, meaning the videos
were watched at approximately 10x speed. Installation of a COUNTcam takes approximately 10
minutes and retrieval takes approximately 5 minutes. This whole project was completed in
approximately 3 weeks.
6.0 References
1. Stuecheli, M. (2009). New Drive-Through Stacking Information for Banks and Coffee
Shops. ITE 2009 Annual Meeting and Exhibit. Print.
2. ITE Technical Committee 5D-10. "Queuing Areas for Drive-Thru Facilities." ITE Journal
(May 1995): 38-42. Print.
3. Institute of Transportation Engineers. Parking Generation. 4th ed. Washington, DC:
Institute of Transportation Engineers, 2010. Print.
4. Institute of Transportation Engineers. Trip Generation. 8th ed. Washington, DC:
Institute of Transportation Engineers, 2008. Print.
7.0 Appendix
A—Day of Week Maximum Queues
B—New Drive-Through Stacking Information for Banks and Coffee Shops
C—ITE Technical Committee 5D-10: Queuing Areas for Drive-Thru Facilities
D—Drive-Through Data Forms
Drive-Through Queue Generation 10 February 2012
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Appendix B
New Drive-Through Stacking Information for Banks and
Coffee Shops
Mark Stuecheli, PTP
Abstract
This paper provides updated queuing information for drive-in banks and new queuing
data for coffee shops with drive-through lanes. The data is presented in a format similar
to that used in the report for ITE Technical Council Committee 5D-10, originally
published in 1995.
Significant changes have occurred in the way that bank patrons conduct business with
their banks. In recognition of those changes, ITE has adjusted the trip generation
information included in the Eighth Edition of Trip Generation, an ITE Informational
Report to include only data collected since 2000, and the revised trip generation totals
are significantly lower than in previous editions. Clearly, the reduced trip generation
figures indicate a reduction in bank drive-through business. This report summarizes
queuing information included in counts taken in the Kansas City metropolitan area.
In the last few years coffee shops with drive-through lanes have become prevalent
throughout the country. Because those businesses were uncommon when the 1995
report was prepared, no data was gathered for those operations. This paper contains
information on counts taken at those establishments, once again in the Kansas City
metropolitan area.
Based on the count data, recommendations are included for the minimum amount of
stacking distance to require for the two types of drive-through businesses that were
studied.
Background
ITE Technical Council Committee 5D-10 was formed in 1987 to produce a database
of queuing information for various types of drive-through lanes. The report of the
findings of the Committee, published in the May 1995 ITE Journal, included information
on the characteristics of drive-through lane stacking for fast-food restaurants, drive-in
banks, car washes, day care centers and dry cleaners. The counts that were included
in the Committee report were conducted from the late 1960s through the late 1980s in a
limited number of mid-western, southern and eastern states.
As a former member of that Committee, and having submitted drive-through counts for
the effort, I am in a position to make some observations about the change in drive-
through usage.
Drive-Through Queue Generation B1 February 2012
Appendix B
This paper analyzes two types of drive-through operations — one that is greatly modified
and another that is new since the original report was published. First, significant
changes have occurred in the ways that bank patrons conduct business with their
financial institutions. On-line banking, direct deposit and the wide usage of ATMs have
resulted in greatly reduced trip generation totals for drive-in banks. In recognition of that
fact, ITE adjusted the trip generation information for drive-in banks in the Eighth Edition
of Trip Generation, an ITE Informational Report, to include only data collected since
2000. The trip generation rates during the p.m. peak hour for the newer data are about
44% lower than rates in the Seventh Edition.
The amount of stacking provided for bank drive-through lanes often has a critical impact
on the potential site design alternatives for proposed bank properties. If the information
included in the 1995 Report were to be used as the basis for establishing stacking
requirements, a large area would need to be allocated to the drive-through lanes. On
tight sites, that limitation could preclude developing an acceptable layout.
Clearly, the major drop in trip generation rates indicates that fewer customers are using
drive-through lanes. That reduction in drive-through usage has an impact on queue
lengths and other operational characteristics observed at those facilities. This paper
includes updated information on queuing in bank drive-through lanes based on counts
taken in the City of Overland Park, Kansas, a suburban community of 171,000 residents
in the Kansas City metropolitan area.
The second area of analysis in this paper pertains to observed queuing characteristics
for coffee shops with drive-through lanes. In the last few years, drive-through coffee
shops have become common throughout the country. Because those businesses were
an insignificant factor when the report for ITE Technical Council Committee 5D-10
was completed, no counts were conducted for that land use category. This paper
contains data on queuing for coffee shops with drive-through lanes, based on counts
conducted predominantly in the Kansas suburbs of the Kansas City metropolitan area.
As is the case for drive-in banks, the length of stacking required for a site has a major
impact on potential site layouts. If a relatively short stacking distance is permitted, the
lanes can be fit into very restricted sites or be more easily retrofitted to work with
existing buildings. But if more queuing occurs than is provided for in a dedicated lane,
the flow of traffic within a parking lot can be seriously restricted by that excess queue.
In the worst case, if the drive-through stacking is located close to a public street and the
excess queue extends into or near the street, the operation of the adjoining public street
may be negatively impacted.
Drive-Through Queue Generation B2 February 2012
Appendix B
Drive-In Banks
Counts were conducted at ten suburban drive-in banks located throughout Overland
Park in the fall of 2008 and the spring of 2009. Both established locations and sites that
were relatively new were counted, although all banks had been open for business for at
least one year. All but one location had drive-through ATMs. Based on the results of
counts taken at a single bank location during a mid-week lunch hour, a mid-week p.m.
peak hour, a Friday lunch hour, and a Friday p.m. peak hour; the maximum queue
lengths occurred during the Friday p.m. peak hour. Therefore, all counts used in the
study were conducted during the Friday p.m. peak hour time period.
The counting process involved noting the maximum per lane and total queues for the
drive-through lanes at each location in fifteen minute increments, along with collecting
information on the stacking of any drive-through ATM. In all cases the vehicles in the
service positions were included in the counts. Where possible, the volumes of vehicles
entering and exiting the parking lot also were tabulated. As a way to evaluate the
frequency of various maximum queue lengths, the total queue lengths were noted at
five minute intervals.
The queuing data was analyzed in ways similar to the methods used in the 1995
Report. Table 1 lists the observed frequency of maximum queue lengths per lane.
Figure 1 plots the per lane maximum queue lengths using both the 2009 data and the
data that was presented in 1995 (please note that the 1995 data involved fifteen counts,
compared to the ten counts in the 2009 data). Figure 2 plots the probability that the
queue lengths per lane will not exceed a given maximum queue length, once again
presenting both 2009 and 1995 data.
Table 1 — Drive-In Bank 2009 Maximum Queue Length Per Lane
Queue Length Frequency Cumulative Frequency P(g5N)
0 0 0 0.00
1 1 1 .10
2 4 5 .50
3 4 9 .90
4 1 10 1.00
Note: P(q<_N) indicates probability, based on sample, of queue length of"q" not
exceeding length "N"
Drive-Through Queue Generation B3 February 2012
Appendix B
Figure 1 — Drive-In Bank 1995 And 2009 Maximum Queue Length
Per Lane Data Plot
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Maximum Number of Vehicles in Queue
Figure 2 — Drive-In Bank 1995 And 2009 Cumulative Maximum
Queue Length Per Lane Data Plot
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The differences between the 1995 Report data (as noted earlier, actually based on
counts conducted from the late 1960s to the late 1980s) and the 2009 counts are
dramatic. The maximum per-lane queue lengths in the current counts were half what
they were in the 1995 data.
Drive-Through Queue Generation B4 February 2012
Appendix B
An attempt was made to determine if such factors as adjoining major street traffic
volumes or the size of the building could predict the queuing results, but no correlation
was found.
Observations
Some banks, especially those that have been in operation for several years, have a
surplus of drive-through lanes and stacking area. That is because those sites were
designed to accommodate the much higher demands that existed many years ago.
Consequently, they often open only a portion of the available lanes.
In one case, for a main office bank location where it was possible to make a direct
comparison between a count conducted in 1988 and a new count in 2008 (actually
taken almost precisely 20 years apart), the difference was dramatic. The p.m. peak
hour drive-through volumes for the 2008 count were 65% lower than the 1988 count, a
much greater drop than would have been indicated by the reduced ITE trip generation
figures discussed earlier. The maximum total number of vehicles queued and the
maximum queue lengths per lane were correspondingly lower, dropping from 29 to 8
and 7 to 3, respectively. The demographics and development characteristics of the
surrounding area have changed little since 1988 and the bank has continued as a stable
operation. Considering all of those factors, it is reasonable to assume that the
differences are associated with changes in customers' banking habits.
The one incidence of a four car per lane maximum stack was a single occurrence that
lasted for only a few minutes. Based on that information, it is reasonable to consider
the practical maximum required queue length to be three vehicles.
The maximum queue lengths for ATMS ranged from two to five vehicles. Only one
location experienced the longer queue lengths and only for a short time period. All
other locations had maximum queue lengths of three vehicles or less.
Coffee Shops With Drive-Through Lanes
Counts were conducted in the fall of 2008 and the spring of 2009 at twelve coffee shops
located in the Kansas suburbs of Merriam, Olathe and Overland Park in the Kansas City
metropolitan area and also in suburban Kansas City, Missouri. All but two of the
establishments were situated in free-standing buildings, and several were located within
shopping centers. Three were drive-through-only operations and the remaining nine
were full-service locations that included both drive-through lanes and inside seating
facilities. Because this type of use is busiest in the morning peak hour, all counts were
completed during that time period.
Similar to the process used for drive-in banks, the counting process involved noting the
maximum number of vehicles queued in the drive-through lane at each location for
fifteen minute increments. As was done for the drive-in bank counts, the vehicle in the
Drive-Through Queue Generation B5 February 2012
Appendix B
service position was included in the counts. Information on the number of vehicles
entering and leaving the parking lot was collected for full-service operations (drive-
through-only locations did not have any parking activity). The queuing information was
tabulated for both the total length of queue and for the number of vehicles behind the
menu board. The observed queue length was noted at five minute intervals as a way
to evaluate the frequency of various queue lengths.
Once again, the queuing data was analyzed in ways similar to the methods used in the
1995 Report. Table 2 lists the observed frequency of maximum queue lengths. Figure
3 plots the per-lane maximum queue lengths and Figure 4 plots the probability that the
queue will not exceed a given maximum queue length.
Table 2—Coffee Shop With Drive-Through Maximum Queue Length
Queue Length Frequency Cumulative Frequency P(q<_N)
0 0 0 0.00
1 0 0 0.00
2 0 0 0.00
3 1 1 .08
4 0 1 .08
5 0 1 .08
6 1 2 .17
7 1 3 .25
8 2 5 .42
9 1 6 .50
10 1 7 .58
11 2 9 .75
12 0 9 .75
13 3 12 1.00
Note: P(q<_N) indicates probability, based on sample, of queue length of"q" not
exceeding length "N"
Drive-Through Queue Generation B6 February 2012
Appendix B
Figure 3 –Coffee Shop With Drive-Through Maximum Queue
Length Data Plot
3 . . .. L.........
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Q
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1 _
Z I i
0 1 2 3 4 5 6 7 8 9 10 11 12 13
Maximum Number of Vehicles in Queue
Figure 4–Coffee Shop With Drive-Through Cumulative Maximum
Queue Length Data Plot
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Drive-Through Queue Generation B7 February 2012
Appendix B
The total trip generation figures were compared to the a.m. peak hour ITE rates for
Land Use Code 937, Coffee/Donut Shop with Drive-Through Window, and Land Use
Code 938, Coffee/Donut Shop with Drive-Through Window and No Indoor Seating. The
observed counts generally fell within the range of counts included in those categories,
although two of the rates for the No Indoor Seating category exceeded the published
range. No correlation was found between the adjoining major street traffic volumes or
the size of the building and either the queuing or the trip generation results.
Observations
Several of the drive-through lanes were under-designed for the usage that was
observed and queues spilled-out into parking lot circulation areas. In most cases the
excess stacking did not result in disruptions of the operations of surrounding uses, since
most other businesses were not open in the early morning. But for those sites where
the end of the drive-through lane extended into the coffee shop parking lot, the excess
queue often disrupted the movements of drivers who were trying to enter or exit parking
spaces or the site itself.
One interesting facet of the data is that the three lowest observed maximum queue
lengths were for the drive-through-only locations. The highest observed queue length
for those operations was seven vehicles, which occurred only once at one location and
only for a very short period of time. A six vehicle maximum stack was a more common
occurrence.
The data shows that the volume of drive-through traffic and, therefore, the required
stacking distance, is higher for full-service coffee shops than for drive-through-only
operations. When total trip generation (both drive-through business and customers who
park and walk in) is factored in, the full-service coffee shops did, on average, about two
and one-half times the business of drive-through-only facilities. Since all of the full-
service operations were Starbucks locations, it may be possible to apply the results of
those counts to other proposed suburban Starbucks locations elsewhere in the country.
Total vehicular stacking available for a drive-through lane is an important consideration,
but the location of the menu board relative to the pick-up window also impacts the
efficiency of a drive-through lane operation. If the spacing is too short, stacking behind
the pick-up window will extend into the menu board area, delaying ordering for those
farther back in the line. In the counts conducted for this study, the pick-up window to
menu board available stacking distances ranged from two to five vehicles.
The operation with the two car stack between the pick-up window and menu board
regularly resulted in delays for drivers waiting to order at the menu board. The location
with a five car stack rarely experienced delays for those ordering. Based on field
observations, if an unlimited amount of stacking were available at a proposed site, the
five car spacing would be ideal. Realizing that space for stacking nearly always is
limited, an acceptable alternative would be the four car spacing.
Drive-Through Queue Generation B8 February 2012
Appendix B
Conclusions
Drive-in bank usage has dropped dramatically, as illustrated in the data provided in this
report. Consequently, a reduced amount of stacking is required. That reduced area for
drive-through stacking can provide more flexibility in the design of bank sites, allowing
for development on smaller sites or the provision of increased landscaped areas.
Based on the data that was gathered, the City of Overland Park has reduced its
previous requirement for a minimum five car stack per lane to a three car stack (a
distance of 60 feet per lane, assuming average vehicle spacing to be 20 feet). That
design should be sufficient to accommodate virtually all situations. Vehicular stacking
requirements for ATMs have been established, also at a minimum of three car lengths.
Coffee shop drive-through lanes are most heavily used during the morning peak period,
and therefore it is important to design sites to accommodate that peak demand. The
following recommended minimum stacking lengths should be appropriate in most cases.
The only exceptions would be situations in which excess queuing could impact a nearby
street or major drive, in which case a more conservative approach should be taken.
Based on the data that was gathered for drive-through-only operations, it appears
reasonable to require that a dedicated drive-through lane be provided with a stack of
120 feet — enough to handle six vehicles. That should be sufficient to accommodate
nearly all vehicles that are likely to arrive during the morning peak hour time period.
For full service establishments, a 220-foot long drive-through lane, providing eleven
cars of total storage, should be adequate to handle the vast majority of the drive-
through lane volumes that might be encountered. In those cases where more than
eleven vehicles were counted, the duration of the extreme queue lasted for only a few
minutes. For the most efficient operation, the distance between the pick-up window and
menu board should be at least 80 feet to accommodate four vehicles.
References
1. Gattis, J. L., Chair of ITE Technical Council Committee 5D-10. "Queuing Areas for
Drive-Thru Facilities, by ITE Technical Council Committee 5D-10." ITE Journal(May
1995): 38-42.
Author Information
Mark Stuecheli, PTP
Senior Transportation Planner
City of Overland Park
Overland Park, KS 66212
Phone: 913-895-6026
Fax: 913-895-5016
E-Mail: mark.stuecheliaopkansas.orq
Drive-Through Queue Generation B9 February 2012
Appendix C
QueuingAreas
For Drive-Thru Facilities
BY ITE TECHNICAL COUNCIL COMMITTEE 5D-10
TE Technical Council Committee Many types of businesses (such as operations occur(such as parents pick-
151)-10 was formed to collect and ana- fast-food restaurants, banks and clean- ing up schoolchildren). These drive-
lyze basic information that may be used ers) utilize drive-thru systems. A simi- thru systems arc comprised of a server
to estimate and evaluate lengths of lar form of drive-thru operation can be position (often at a service "window"),
automobile queues at drive-thru facili- found at sites where passenger pick-up and vehicle queuing space in advance
ties. In addition to fulfilling this objec-
tive, this Informational Report consti-
tutes a starting point for compiling a
QUEUING DATA SHEET
database for drive-thru facility queue
length information.
Introduction
1. Type of Service Provided
When faced with the need to evalu-
ate the future impacts of a planned 2. Day(s) of Week Sun Mon Tue Wed Thu Fri Sat
development, the transportation engi- 3. Time(s) of Day _
neer often employs some form of anal-
ogy, estimating the future impacts of 4. Type of Area can Surburban Rural
as-yet unbuilt development by using El 0 ❑
the attributes of existing land uses hav- Competition in Area High Medium Low
(For Same Services) I...] ❑
ing a similar nature. For instance, the
engineer may refer to published trip 6. Service Rate Measured Vehicles/Time
generation rates,derived from observa- (Per Window or Aisle or Lane)
tions made at existing developments,to 7. Arrival Rate Measured Avg Max Vehicles/Time
obtain a figure by which to estimate (Per Window or Aisle or Lane)
volumes that will occur at the proposed 8. Uniformity Rating (1 - 10)
development. 9. Capacity of Queue Storage Area (Vehicles)
10. Measured Average Queue (Vehicles)
11. Measured Maximum Queue (Vehicles)
12. Excess Demand Volume (Vehicles)
13. Excess Demand Frequency
P J. L. Gattis,
14. Size Sample or Length-�f Countbata
., was Chair of ---
' �'' 15. Narrative Description of Service
., Technical Council
Committee 51)-IU.
yo„
He is an Assistant
—
_
Professor in the
Department of
Civil Engineering at the University of
-
Arkansas in Fayetteville, Ark. lie is a
Member of ITE. Figure 1.Data gathering form used in survey.
38•ITE JOURNAL*MAY 1995
Drive-Through Queue Generation C1 February 2012
P\ppas e cl ix C
of the service position, for waiting in Table 1, nes of Food Queue Lengths by Food Type
line as those ahead are served first.
When attempting to project lengths Maximum Average
of automobile queues at proposed Queue Range Maximum Queue
drive thru facilities,the municipal or Food Type 0 in system) 0 in system) Studies
private consulting engineers may not Donuts 4 4 2
find available data by which a projec- Steak 4 4 2
lion can be made. While such data Chicken 2-9 5 5
may be known by larger business Fish 5 5 1
chains that have drive-thru operations, Sandwiches 5 5 1
the data do not seem to be generally Mexican 7 7 1
available to the average traffic engi- Roast Beef 6-8 7 2
neer trying to size or evaluate automo- Hamburgers 4-13 7 27
bile queue storage area. True, some
publications present results of queuing Table 2.Fast Food Queue Lengths
studies or equations for estimating
queue lengths based on known system Maximum Queue Length Cumulative
arrival and service rates,'-"Rut the pro- ( in system) Frequency Frequency P(a<N)
posed-site arrival and service rates 1 0 0 0.00
may be unknown, and the proposed
system may not possess attributes 2 2 2 0.05
3 0 2 0.05
(such as negative exponential service 4 6 8 0.18
time rates) needed for certain equa- 5 4 12 0.27
tions to properly predict queue 6 7 19 0.43
lengths. 7 10 29 0.66
Drive-thru facilities are perceived 8 7 36 0.82
as time-savers;as a convenience to the 9 5 41 0.93
physically challenged, elderly and par- 10 1 42 0.95
tints with young children; and as a way 11 0 42 0.95
to avoid going out into inclement 12 1 43 0.98
weather. Due to vehicle idling while in 13 1 44 1.00
line, drive-thru facilities may also be Note:P(q_<N)Indicates probability,based on sample,of queue length"q"not exceeding length
viewed as causing unnecessary fuel N ;
consumption and air pollution. The
popularity of drive-thru services cre- queues would not exceed an absolute the 1990s, at sites in Florida, Kansas,
ates a need to evaluate the queuing maximum were calculated and shown Illinois, Minnesota, Montana, New
capacities of the varied drive-thru facil- graphically. Jersey, Oklahoma, Pennsylvania and
ities. This report provides some basic Texas. All fast-food facilities observed
drive-thru facility queue length infor- for this study had a single-window
mation. It is hoped that the database Findings drive-thru system. The industry is
will continue to grow,so that a com- Within this report, data have been changing,with double-and even triple-
prehensive analytical tool may he compiled for banks, car washes, day window systems being utilized. Further
available for the transportation profes- care facilities, dry cleaners and fast- information will be needed on queuing
sional• food restaurants. characteristics of these facilities.
The average observed service rate
Fast Food was 54 vehiclesper hour (vph); the
Methods ( P )�
This category includes restaurants maximum rate was 108 vph.The maxi-
The queue length data gathering characterized by food being prepared mum observed queue lengths (number
form shown in Figure 1 was distributed in advance of,or shortly after,ordering; of vehicles in line, including vehicle at
to committee members in November by high turnover for eat-in customers; service position)ranged from two to 13
1987. The form was accompanied by and by long business hours. The ITE vehicles(see Table 1).Where there was
specific user-instructions to ensure uni- land-use codes(Lt1Cs)for this use are a menu-order board followed by a ser-
formity of procedures and compatibility LUC 834(Trip Generation, 1991) and vice window, the combined total of
of results. 836(Parking Generation,1987). vehicles in both sequential lines was
Completed forms were returned to Forty-four fast-food restaurants reported.
the committee chair and data were cat- were observed for this study. They The restaurants featuring hamburg-
aloged by land-use type.The maximum ranged from those serving chicken to ers had maximum queues in the upper
observed queue lengths and the maxi- the hamburger chains. All sites were part of the range. Table 2 shows the
mum observed queue length frequen- suburban locations. Queuing was frequencies of the observed maximum
cies were compiled. Cumulative fre- observed mainly during the weekday queue lengths,as well as a probability
quencies and the probability that mid-day peak from the 1970s through of a queue of less than a given number
ITE JOURNAL•MAY 1995*39
Drive-Through Queue Generation C2 February 2012
Appendix C
• ,a I
ac ) i m ;
o I I 1 1 ) r w t i
:
W , I 1 i I f #....._......_. W OS r....----...__ . �.._._-.........j._-
q4:'._ I I 0 i � 1! I 1..._._
l
k
-; yX j 1I
I
CC 1
I
I j ico
m t f._.. }...
Z• 0 , 3 57 8 i', 13 O 0 -ammo
MAXIMUM NUMBER OF VEHICLES IN QUEUE a NUMBER OF VEHICLES IN QUEUE�= L ,s
Figure 2.Maximum queue lengths at fast-food. Figure 3.Maximum queue length probability al fast-food.
of vehicles. Figure 2 plots maximum biped) ranged from five to 29 vehicles, observed. On the basis of the studies
queue length against the observed fre- At two sites, it was observed that a received, there is a 100 percent proba-
quency of occurrence. Figure 3 depicts queue length exceeding eight vehicles bility that the queue length at a bank
the probability that at any fast-food per lane was not tolerated by cus- drive-thru facility will not exceed eight
site, the queue will not exceed a given Comers.When the queue length became vehicles per lane,as Figure 5 shows.
maximum queue length. From Table 2 excessive, customers would park and Table 4 presents the maximum num-
or Figure 3, it can he seen that there use walk-in facilities rather than the ber of vehicles in an entire drive-thru
was a 95 percent probability that the drive-thru. Thus the collected data system (all lanes combined) by ranges,
maximum queue at a site would be no reflect a maximum queue per lane of along with the frequency of occurrence.
more than 10 vehicles. eight vehicles. This table shows that the most common
The maximum queues were evaluat- Table 3 shows the observed frequen- maximum number-in-the-system at a
ed against days of the week and were cy of occurrence of maximum queue bank drive-thru facility fell between six
found to have no statistical relation- lengths per lane, Figure 4 plots the and 10 vehicles,as most observed facili-
ship. Likewise,when evaluated against maximum number of vehicles per lane ties consisted of two lanes.Table 4 also
different levels of competition within
the area and against service rates,there Table 3.Bank Queue Lengths
was no statistical relationship. Maximum Queue Per Lane
Bank Queue Length Frequency Cumulative Frequency P(q_<N)
This category includes savings-and- 0 0
loans with or without automatic teller 0 0.00
machines (ATMs) and commercial 1 0 0 0.00
banks with or without ATMs.Although 2 1 1 0:07
3 4 5 0.33
there were historical differences 4 2 7 0.47
between banks and savings-and-loans, 5 4 11 0.73
they are now often indistinguishable to 6 1 12 0,80
the public.The ITE land-use codes for 7 2 14 0.93
this use are LUC 912 and 914 (Trip 8 1 15 1.00
Generation, 1991) and LUC 912 Note:P(q<N)indicates probability,based on sample,of queue length"q"not exceeding length
(Parking Generation,1987).
The studies analyzed were conduct-
ed from the late 1960s through the late Table 4.Maximum Number of Vehicles In Bank System(All Lanes)
1980s; many were in Illinois,
Minnesota,New Jersey and Texas.The o in Cumulative
size of the bank drive-thru facilities system Frequency Frequency P(gsN)
ranged from a minimum of one lane
with one teller-window up to an institu- 0- 5 2 2 0.13
lion with 10 lanes and four tellers. 6-10 6 8 0.53
Observed service rates for these 11-15 3 13 0.87
16-20 2 13 0.87
institutions went up to a maximum of 21-25 1 14 0.93
35 vehicles per lane-hour. Maximum 26-30 1 15 1.00
observed queues per lane ranged from
two to eight vehicles. The maximum Note P(gsN)indicates probability,based on sample,of queue length"q"not exceeding length
system queue lengths (all lanes con-
40•ITE JOURNAL.MAY 1995
Drive-Through Queue Generation C3 February 2012
Appendix C
J
ws r f u 1 --
0 I
W
a)m i v 0 8 :....................... i._. _...
i I W i
i
I
iTiI i i t3 t 7 ' I
0 2-
Q I I
LI-1 02 L....... a_ _.
m i I m
z o L s O 0
CC 1 3 5 7
MAXIMUM NUMBER OF VEHICLES IN QUEUE NUMBER OF VEHICLES IN QUEUE = L
Figure 4.Maximum queue length per lane at bank. Figure 5.Maximum per lane queue length probability at bank.
gives the probability,based on the stud- Studies at the full-service car washes queues per bay or total maximum
ies received, that the number of vehi- were made during winter or early queues(per entire operation).
des in the system will not exceed a cer- spring months. Both full-service car
taro range. washes consisted of a single tunnel. Day Care
It should be noted that queuing Observed service rates were 35 vph This category includes facilities that
lengths may be affected by time-of-day (maximum queue of nine vehicles) and provide a place for children during the
banking habits. There may be differ- 27 vph (maximum queue of 26 vehi- day, often while parents are at work.
ences between the central city and a des). At the site with a 26-vehicle After-school care may also he provid-
suburb. An area with a large propor- queue,the queue extended off the site ed. The ITE land-use code is LUC 565
tion of retired persons may experience and onto an adjacent private street with (Trip Generation, 1991).This land use
unique banking-time behaviors. In light traffic volumes. was not included in the 1987 Parking
addition,the effects of banks incorpo- The self-service car wash studies Generation report.
rating ATMs into drive-thru aisles may were conducted on Saturday and Data were submitted for one day-
also need to be investigated in future Thursday. during late spring and/or care facility in Texas, during the
queuing studies. summer months. Service rates at self- evening peak hour. The facility had 99
service car washes ranged from 4.1 children enrolled and 94 present the
Car Wash vehicles per bay-hour to 5.4 vehicles day the study was conducted.The day-
This category includes full-service per bay-hour.The average service rate care facility handled children age 2
car washes (offering vacuuming and was 4.77 vehicles per bay-hour. The through first grade. The facility was
towel-drying services),exterior tunnel maximum queue observed at two study operated in a manner that required the
operation (vacuuming and towel dry- sites was three vehicles,and at a third parents to park their cars and go inside
ing not a part of the "in-line" opera- study site the maximum observed was to get their children.
lion, but may be offered at separate one vehicle.No distinction was made as The hour service rate was 46 vehi-
stations to the side), and self-service to whether these were maximum des, A maximum of eight vehicles in
car washes (where customers pull into
a wash bay,insert coins into a box,and
proceed to wash). The ITE land-use This is an Informational Report of the Institute of Transportation
code for these uses is LUC 847 (Trip Engineers prepared by Technical Council Committee SD-i0.The information
Generation, 1991). This land use was in this report has been obtained from experiences of transportation engineer-
not included in the 1987 Parking ing professionals and research. ITE Informational Reports are prepared for
Generation report. informational purposes only and do not include Institute recommendations on
The studies analyzed were conduct- which is the best course of action or the preferred application of the data.
ed from the late 1960s through the late Members of Technical Council Committee 5D-10 were J. L. Gattis, P.E.
1980s in Kansas, illinois.Montana, (M).Chair;Grant A.Bacchus,P.Eng.(F);Benedict G.Barkan(F);Robert R.
New Jersey and Texas. They included Marvin, P.E. (M);Dale B. McKinney, P.E. (F); Robert A. Nelson, P.E. (F);
seven full service ear washes,two exte- Seyed M.Safavian (M);James M.Schoen(A);David K. Sorenson,P.E.(A);
nor tunnel car washes, and nine self- Mark J.Stuecheli(M);and Jack Wierzenski(A).
service car washes.The number of self- Members of the Technical Council Department 5 Standing Committee at
service bays ranged from six to 14 per the time of approval of this report were Dennis O'Malley(F),Chair;Carol H.
site.The self-service car washes typical- Walters,P.E.(M).Assistant Chair;Robert D.McMillen,P.E.(FL);Wamandri
ly had one or more parallel wash bays; W. Williams (A); and Donald J. Galloway, P.E. (F). Brian S, Bochner, P.E.
the full-service car wash operations (F),was the Chair of Technical Council,and John M.Mason,P.E.(F),was the
tended to have a single tunnel to serve Assistant Chair.
customers.
ITE JOURNAL.MAY 1995•41
Drive-Through Queue Generation C4 February 2012
Appendix C
Table 5.Summary of Observed Queue Distances at Appendix
Facilities that could be studied include those at
credit unions, funeral homes, gas sta-
Near-maximum number Lane Length needed tions(either gas only, full-service,self-
of queued vehicles observed to store near-maximum service, or a combination with conve-
in system(does not include queue(does not include) nience stores or car washes), libraries,
vehicle at service position) vehicle at service position)
liquor stores, movie theater ticket
Fast-Food(Hamburger) 10-1=9 60 m(198 feet) booths,parking lots and garages(either
Bank 8-1=7 47 m(154 feet) pick-up ticket or pay, or key, tag, or
Car Wash(self-service) 3-1=2 13 m(44 feet) card), post offices, pre-schools, baby-
Day Care 10-1 =9 can store in parallel sitting or school combinations, lower
Dry Cleaner 3-1 =2 13 m(44 feet) grade schools, stadium ticket sales
machines, truck stops and places of
5 minutes(if sustained,equivalent to 96 Due to a change of committee per- worship.
vph) were observed; a 20-minute peri- sonnet during the course of the data- References
od had 28 vehicles (84 per hour). The gathering effort,some of the original
maximum number of waiting vehicles forms submitted by committee mem- 1• Ballard,J. L.,J. G. Goble,and Pat T.
was 10 vehicles. hers are not available.There are some McCoy. "Another Look at the Storage
VanWinkle and Kinton reported the apparent errors in the tables: For Requirements for Bank Drive-in
Facilities." Transportation Research
results of 29 field studies at day-care instance, the number of studies tallied Record 971. Washington. D.C.:
establishments in Tennessee. 'Their in Table 1 is 41, while the number in 'Transportation Research Board(1984):
findings are in the July 1994 ITE Table 2 is 44. It is not known whether 130-132.
Journal? three studies were not included in 2. W. Gordon Derr,Thomas E. Mulinaizi,
Table 1, or whether there was double and Bob L.Smith."Queuing at Drive-up
Dry Cleaners counting in Table 2. The unavailability Windows." Transportation Research
This category includes facilities that of the original data forms makes it Record 901. Washington, D.C.:
clean clothing and other fabrics that impossible to recheck the numbers. Transportation Research Board (1983):
should not be laundered.Often a walk- The size of this drive-thru facility 38-42.
up window is present. No information queuing characteristic database was 3. Frisker,Jon D. and H.S.Tray. "Drive-
Up Windows,Energy,and Air Quality."
is provide for this land use in either the limited.There is a need to accumulate Transportation Research Record 1092.
l'FE 1991 Trip Generation report or the and analyze more drive-thru queuing Washington, D.C.: Transportation
ITE1987 Parking Generation report. system data, so transportation engi- Research Board(1975):22-25.
One study was conducted at a dry neers and site planners can be better 4. Gattis,J. L.. N. Zaman.G. W.Tauxe,
cleaner with drive-thru facilities in informed. Additional observations of and R, S. Marshmcnt. "Analyzing Fast-
Montana during a weekday p.m. peak service rates are also needed in order to Food Drive-Up Window Site Impacts."
period. An average service rate of determine relationships between ser- Site impact Traffic Assessment. New
41 vph was measured at the single win- vice rates and queue lengths, and to York: American Society of Civil
dow. The observed maximum queue evaluate long-term trends in service Engineers(1992):16-20,
was three vehicles long. Forty-five per- rates. Finally,investigations of the 5 Gerlough,D.L.and M.J. .Traffic
Flow Theory: 7'R13 Speciall Report 165.
cent of the customers used the drive- amount of space occupied per vehicle Washington, D.C.; Transportation
thru facility. within a queue are needed so that engi- Research Board,1975.
neers will have the ability to project not 6. May, Adolf D. Traffic Flow
Conclusionsonly the number of vehicles that will be Fundamentals. Englewood Cliffs, N..I.:
in the maximum queue for a given site, Prentice Hall,1990.
Table 5 summarizes the observed but also the queue storage length 7. Stover,Virgil G. and Frank J. Kocpke.
maximum or near-maximum observed required for a site. Transportation and Land Development.
queue lengths, and also lists the stack- When collecting queuing data,the Washington. D.C.: Institute of
ing distance needed to accommodate recorder should clearly indicate Transportation Engineers;1987.
8. VanWinkle, John W. and S. Colin
these observed queues,based on a whether the number of vehicles record- Kinton. "Parking and 'Trip Generation
front bumper-to-front bumper space ed includes or excludes the vehicle(s)in Characteristics for Day-Care Facilities."
occupied length of 22 feet(ft)per vehi- the service position (that is,at the win- ITE Journal(July 1994):24-28.
cle. This 22 ft may not be the exact dow). The data record must indicate 9. Woods,Donald L.and Carroll J.Messer.
space that vehicles occupy,but a value which numbers are for a single queuing "Design Criteria for Drive-In Banking
ranging from 20 ft to 25 ft seems appro- line and which totals are for the entire Facilities." Traffic Engineering
priate for many situations. Because system of multiple queuing lines, An (December 1970):30-37.
only one day-care facility was observed, observer should also note instances of If
and because parents picking up chil arriving vehicles balking or refusing to
dren may park in parallel or in a lot enter a queue due to excessive length,
instead of in a single-file line,no stack- and how many vehicles were in the
ing length was calculated for this land queue when the next arrival balked.
use. Other types of drive-thru operations
42•ITE JOURNAL*MAY 1995
Drive-Through Queue Generation C5 February 2012
Appendix D
Drive-Through Queuing Data Form
ITE Land Use Code: 912
Land Use/Building Type*: Drive-in Bank
Name of Business: Citizens Independent Bank
Address: 3700 W Broadway Ave
City: Robbinsdale
State: MN
Zip Code: 55422
Date(s) February 7-8, 2012(Tuesday-Wednesday)
Weather Conditions High 32 °F and Clear
CBD
Urban (non-CBD) Competition Within High
Location Within Area Suburban (non-CBD) X Medium X
Area
(select one): Suburban CBD Low
(select one):
Rural
Not Given
Drive-Through Description 4 Lanes+ 1 ATM Lane
IGross Floor Area (estimated) 6300
Maximum Queue Time Max Queue Occurred
Sunday
Monday
Tuesday 5 3:36pm
Wednesday 5 2:37pm
Thursday
Friday
Saturday
Drive-Through Queue Generation D1 February 2012
Appendix D
Drive-Through Queuing Data Form
ITE Land Use Code: 912
Land Use/Building Type: Drive-in Bank
Name of Business: SharePoint Credit Union
Address: 3670 Aquila Ave S
City: St. Louis Park
State: MN
Zip Code: 55426
Date(s) February 1-2, 2012 (Wednesday-Thursday)
Weather Conditions High 32-36°F and Fog
CBD
Urban (non-CBD) Competition Within High
Location Within Area Suburban (non-CBD) X Medium X
Area
(select one): Suburban CBD (select one):
Low
Rural
Not Given
Drive-Through Description : 2 Lanes+ 1 ATM Lane
IGross Floor Area (estimated) 7,850 sq.ft
Maximum Queue Time Max Queue Occurred
Sunday
Monday
Tuesday
Wednesday 3 3:28pm
Thursday 3 8:51am, 10:37am
Friday
Saturday
Drive-Through Queue Generation D2 February 2012
Appendix D
Drive-Through Queuing Data Form
ITE Land Use Code: 912
Land Use/Building Type: Drive-in Bank
Name of Business: TCF Bank
Address: 8020 Highway 7
City: St. Louis Park
State: MN
Zip Code: 55426
Date(s) August 5-7, 2011 (Friday-Sunday)
Weather Conditions High 84-88°F and Clear
CBD
Urban (non-CBD) Competition Within High
Location Within Area Suburban (non-CBD) X Medium X
(select one): Suburban CBD Area Low
Rural (select one):
Not Given
Drive-Through Description : 5 Lanes+ 1 ATM Lane
IGross Floor Area (estimated) 6,000 sq.ft
Maximum Queue Time Max Queue Occurred
Sunday 4 5:18pm
Monday
Tuesday
Wednesday
Thursday
Friday 8 12:20pm,2:20pm
Saturday 8 11:40am
Drive-Through Queue Generation D3 February 2012
Appendix D
Drive-Through Queuing Data Form
ITE Land Use Code: 912
Land Use/Building Type: Drive-in Bank
Name of Business: US Bank
Address: 4000 W Broadway Ave
City: Robbinsdale
State: MN
Zip Code: 55422
Date(s) February 7-8, 2012 (Tuesday-Wednesday)
Weather Conditions High 32°F and Clear
CBD
Urban (non-CBD) Competition Within High
Location Within Area Suburban (non-CBD) X Medium X
Area
(select one): Suburban CBD Low
Rural (select one):
Not Given
Drive-Through Description : 3 Lanes+ 1 ATM Lane
Gross Floor Area (estimated) 21,550 sq.ft.
Maximum Queue Time Max Queue Occurred
Sunday
Monday
Tuesday 7 4:47pm,5:04pm
Wednesday 7 3:00pm,5:26pm
Thursday
Friday
Saturday
Drive-Through Queue Generation D4 February 2012
Appendix D
Drive-Through Queuing Data Form
ITE Land Use Code: 912
Land Use/Building Type: Drive-in Bank
Name of Business: Wells Fargo
Address: 425 E Hennepin Ave
City: Minneapolis
State: MN
Zip Code: 55414
Date(s) February 7, 2012 (Tuesday)
Weather Conditions High 32°F and Clear
CBD
Urban (non-CBD) X Competition Within High
Location Within Area Suburban (non-CBD) Medium X
Area
(select one): Suburban CBD (select one): Low
Rural
Not Given
Drive-Through Description : 4 Lanes+ 1 ATM Lane
I Gross Floor Area (estimated) 12,000 sq.ft.
Maximum Queue Time Max Queue Occurred
Sunday
Monday
Tuesday 6 1:18pm
Wednesday
Thursday
Friday
Saturday
Drive-Through Queue Generation D5 February 2012
Appendix D
Drive-Through Queuing Data Form
ITE Land Use Code: 912
Land Use/Building Type: Drive-in Bank
Name of Business: Wells Fargo
Address: 2329 Central Ave NE
City: Minneapolis
State: MN
Zip Code: 55418
Date(s) February 7-8, 2012 (Tuesday-Wednesday)
Weather Conditions High 32°F and Clear
CBD
Urban (non-CBD) X Competition Within High
Location Within Area Suburban (non-CBD) Medium X
Area
(select one): Suburban CBD Low
(select one):
Rural
Not Given
Drive-Through Description : 7 Lanes(4-5 Lanes were open at various points)+ 1 ATM Lane
Gross Floor Area (estimated) 20,125 sq.ft.
Maximum Queue Time Max Queue Occurred
Sunday
Monday
Tuesday 8 4:41pm
Wednesday 6 11:27am, 1:48pm,2:23pm,4:32pm,5:25pm
Thursday
Friday
Saturday
Drive-Through Queue Generation D6 February 2012
Appendix D
Drive-Through Queuing Data Form
ITE Land Use Code: 948
Land Use/Building Type: Automated Car Wash
Name of Business: BP
Address: 3012 Excelsior Blvd
City: Minneapolis
State: MN
Zip Code: 55416
Date(s) February 1-2, 2012, (Wednesday-Thursday)
Weather Conditions High 32-36°F and Fog
CBD
Urban (non-CBD) X Competition Within High
Location Within Area Suburban (non-CBD) Medium
(select one): Suburban CBD Area Low X
(select one):
Rural
Not Given
Drive-Through Description :
1 Lane. Only counted the vehicles waiting in line, not the vehicles
currently being washed.
Gross Floor Area (estimated) 3,375 sq.ft
Maximum Queue Time Max Queue Occurred
Sunday
Monday
Tuesday
Wednesday 6 3:08pm
Thursday 6 3:07pm
Friday
Saturday
Drive-Through Queue Generation D7 February 2012
Appendix D
Drive-Through Queuing Data Form
ITE Land Use Code: 948
Land Use/Building Type: Automated Car Wash
Name of Business: BP
Address: 2441 Fariview Ave N
City: Roseville
State: MN
Zip Code: 55113
Date(s) February 7-8,2012(Tuesday-Wednesday)
Weather Conditions High 32°F and Clear
CBD
Urban (non-CBD) Competition Within High
Location Within Area Suburban (non-CBD) X Medium
(select one): Suburban CBD Area Low
Rural X
(select one):
Not Given
1 Lane. Only counted the vehicles waiting in line, not the vehicles
Drive-Through Description : currently being washed.
Gross Floor Area (estimated) 3,150 sq.ft
Maximum Queue Time Max Queue Occurred
Sunday
Monday
Tuesday 1 12:58pm
Wednesday 3 2:53pm
Thursday
Friday
Saturday
Drive-Through Queue Generation D8 February 2012
Appendix D
Drive-Through Queuing Data Form
ITE Land Use Code: 948
Land Use/Building Type: Automated Car Wash
Name of Business: BP
Address: 1691 Snelling Ave N
City: Falcon Heights
State: MN
Zip Code: 55113
Date(s) February 7-8, 2012 (Tuesday-Wednesday)
Weather Conditions High 32 °F and Clear
CBD
Urban (non-CBD) Competition Within High
Location Within Area Suburban (non-CBD) X Medium
Area
(select one): Suburban CBD (select one): Low X
Rural
Not Given
1 Lane. Only counted the vehicles waiting in line, not the vehicles
Drive-Through Description : currently being washed.
IGross Floor Area (estimated) 1,500 sq.ft.
Maximum Queue Time Max Queue Occurred
Sunday
Monday
Tuesday 4 1:48pm
Wednesday 3 4:29pm
Thursday
Friday
Saturday
Drive-Through Queue Generation D9 February 2012
Appendix D
Drive-Through Queuing Data Form
ITE Land Use Code: 948
Land Use/Building Type: Automated Car Wash
Name of Business: Holiday Gas Station Carwash
Address: 5430 Minnetonka Blvd
City: St. Louis Park
State: MN
Zip Code: 55416
Date(s) February 1-2, 2012 (Wednesday-Thursday)
Weather Conditions High 32-36°F and Fog
CBD
Urban (non-CBD) Competition Within High
Location Within Area Suburban (non-CBD) X Medium
Area
(select one): Suburban CBD Low X
Rural (select one):
Not Given
1 Lane. Only counted the vehicles waiting in line, not the vehicles
Drive-Through Description : currently being washed.
Gross Floor Area (estimated) 3,000 sq.ft
Maximum Queue Time Max Queue Occurred
Sunday
Monday
Tuesday
Wednesday 3 12:37pm, 1:50pm,3:43pm,4:41pm,5:10pm,7:04pm,
7:30pm
Thursday 4 2:38pm,4:20pm
Friday
Saturday
Drive-Through Queue Generation D10 February 2012
Appendix D
Drive-Through Queuing Data Form
ITE Land Use Code: 948
Land Use/Building Type: Automated Car Wash
Name of Business: Mister Car Wash
Address: 8650 Highway 7
City: St. Louis Park
State: MN
Zip Code: 55426
Date(s) February 1-2, 2011 (Wednesday-Thursday)
Weather Conditions High 32-36°F and Fog
CBD
Urban(non-CBD) Competition Within High
Location Within Area Suburban (non-CBD) X Medium
(select one): Suburban CBD Area Low X
Rural (select one):
Not Given
Drive-Through Description :
2 Lanes, Full Service Wash,only vehicles in line were counted, not
the vehicles being washed.
Gross Floor Area (estimated) 8,250 sq.ft
Maximum Queue Time Max Queue Occurred
Sunday
Monday
Tuesday
Wednesday 10 1:03pm
Thursday 6 4:02pm
Friday
Saturday
Drive-Through Queue Generation D11 February 2012
Appendix D
Drive-Through Queuing Data Form
ITE Land Use Code: 948
Land Use/Building Type: Automated Car Wash
Name of Business: Mobil Car Wash
Address: 3864 Hopkins Crossroad
City: Minnetonka
State: MN
Zip Code: 55305
Date(s) February 1-2, 2012(Wednesday-Thursday)
Weather Conditions High 32-36°F and Fog
CBD
Urban (non CBD) Competition Within High
Location Within Area Suburban (non-CBD) X Medium
(select one): Suburban CBD Area Low X
(select one):
Rural
Not Given
2 lanes. Only vehicles in line were counted, not vehicles being
Drive-Through Description :
washed.
Gross Floor Area (estimated) 1,225 sq.ft
Maximum Queue Time Max Queue Occurred
Sunday
Monday
Tuesday
Wednesday 4 6:03pm
Thursday 3 4:37pm,6:28pm,7:39pm,7:51pm,8:04pm,8:23pm
Friday
Saturday
Drive-Through Queue Generation D12 February 2012
Appendix D
Drive-Through Queuing Data Form
ITE Land Use Code: 937
Land Use/Building Type: Coffee/Donut Shop w/Drive Thru
Name of Business: Caribou Coffee
Address: 4745 Cedar Ave S
City: Minneapolis
State: MN
Zip Code: 55407
Date(s) February 1-2, 2012(Wednesday-Thursday)
Weather Conditions High 32-36°F and Fog
CBD
Urban (non-CBD) X Competition Within High
Location Within Area Suburban (non-CBD) Medium X
Area
(select one): Suburban CBD Low
Rural (select one):
Not Given
Drive-Through Description : 1 Lane
Gross Floor Area (estimated) 1,950 sq.ft.
Maximum Queue Time Max Queue Occurred
Sunday
Monday
Tuesday
Wednesday 11 8:50am
Thursday 10 7:57am
Friday
Saturday
Drive-Through Queue Generation D13 February 2012
Appendix D
Drive-Through Queuing Data Form
ITE Land Use Code: 937
Land Use/Building Type: Coffee/Donut Shop w/Drive Thru
Name of Business: Caribou Coffee
Address: 5330 Cedar Lake Rd
City: St. Louis Park
State: MN
Zip Code: 55416
Date(s) August 5-9, 2011 (Friday-Tuesday)
Weather Conditions High 82-88°F and Clear
CBD
Urban (non-CBD) Competition Within High
Location Within Area Suburban (non-CBD) X Medium X
Area
(select one): Suburban CBD Low
Rural (select one):
Not Given
Drive-Through Description : 1 Lane
I Gross Floor Area (estimated) I 3,600 sq.ft
Maximum Queue Time Max Queue Occurred
Sunday 7 9:39am,9:41am
Monday 10 8:39am
Tuesday 12 9:26am
Wednesday
Thursday
Friday 12 8:12am
Saturday 8 8:52am, 10:24am
Drive-Through Queue Generation D14 February 2012
Appendix D
Drive-Through Queuing Data Form
ITE Land Use Code: 937
Land Use/Building Type: Coffee/Donut Shop w/Drive Thru
Name of Business: Starbucks
Address: 5121 Gus Young Lane
City: Edina
State: MN
Zip Code: 55436
Date(s) February 7-8, 2012(Tuesday-Wednesday)
Weather Conditions High 32 °F and Clear
CBD
Urban (non-CBD) Competition Within High
Location Within Area Suburban (non-CBD) X Area Medium
(select one): Suburban CBD (select one): Low X
Rural
Not Given
Drive-Through Description : 1 Lane
Gross Floor Area (estimated) 3,000 sq.ft
Maximum Queue Time Max Queue Occurred
Sunday
Monday
Tuesday
Wednesday 14 7:22am,7:49am
Thursday 16 8:56am
Friday
Saturday
Drive-Through Queue Generation D15 February 2012
Appendix D
Drive-Through Queuing Data Form
ITE Land Use Code: 937
Land Use/Building Type: Coffee/Donut Shop w/ Drive Thru
Name of Business: Starbucks
Address: 1505 Highway 7
City: Hopkins
State: MN
Zip Code: 55305
Date(s) February 1-2, 2012(Wednesday-Thursday)
Weather Conditions High 32-36°F and Fog
CBD
Urban(non-CBD) Competition Within High
Location Within Area Suburban (non-CBD) X Medium X
Area
(select one): Suburban CBD Low
(select one):
Rural
Not Given
Drive-Through Description : 1 Lane,Queuing Went Out Onto the Street
IGross Floor Area (estimated) 1,800 sq.ft
Maximum Queue Time Max Queue Occurred
Sunday
Monday
Tuesday
Wednesday 10 7:42am,8:41am,8:59am
Thursday 11 7:33am
Friday
Saturday
Drive-Through Queue Generation D16 February 2012
Appendix D
Drive-Through Queuing Data Form
ITE Land Use Code: 937
Land Use/Building Type: Coffee/Donut Shop w/Drive Thru
Name of Business: Starbucks
Address: 4201 Minnetonka Blvd
City: St. Louis Park
State: MN
Zip Code: 55416
Date(s) November 3, 2010(Wednesday)
Weather Conditions High 56°F and Clear
CBD
Urban (non-CBD) Competition Within High
Location Within Area Suburban (non-CBD) X Medium X
(select one): Suburban CBD Area Low
(select one):
Rural
Not Given
Drive-Through Description : 1 Lane,Queue Lengths Recorded at 5 min Intervals
Gross Floor Area (estimated) 2,550 sq.ft.
Maximum Queue Time Max Queue Occurred
Sunday
Monday
Tuesday
Wednesday 11 8:45am
Thursday
Friday
Saturday
Drive-Through Queue Generation D17 February 2012
Appendix D
Drive-Through Queuing Data Form
ITE Land Use Code: 937
Land Use/Building Type: Coffee/Donut Shop w/ Drive Thru
Name of Business: Starbucks
Address: 2305 Fairview Ave
City: Roseville
State: MN
Zip Code: 55113
Date(s) February 7-8,2012(Tuesday-Wednesday)
Weather Conditions High 32°F and Clear
CBD
Urban (non-CBD) High
Competition Within
Location Within Area Suburban (non-CBD) X Medium X
(select one): Suburban CBD Area Low
(select one):
Rural
Not Given
Drive-Through Description : 1 Lane
IGross Floor Area (estimated) 1,500 sq.ft
Maximum Queue Time Max Queue Occurred
Sunday
Monday
Tuesday 10 8:09am
Wednesday 12 7:57am
Thursday
Friday
Saturday
Drive-Through Queue Generation D18 February 2012
Appendix D
Drive-Through Queuing Data Form
ITE Land Use Code: 934
Land Use/Building Type: Fast Food with Drive Thru
Name of Business: Arby's
Address: 1116 W Lake St
City: Minneapolis
State: MN
Zip Code: 55408
Date(s) February 1-2, 2012 (Wednesday-Thursday)
Weather Conditions High 32-36°F and Fog
CBD
Urban (non-CBD) X Competition Within High
Location Within Area Suburban (non-CBD) Medium X
Area
(select one): Suburban CBD Low
(select one):
Rural
Not Given
Drive-Through Description : 1 Lane
Gross Floor Area (estimated) 3,000 sq.ft
Maximum Queue Time Max Queue Occurred
Sunday
Monday
Tuesday
Wednesday 5 6:04pm
Thursday 5 6:55pm
Friday
Saturday
Drive-Through Queue Generation D19 February 2012
Appendix D
Drive-Through Queuing Data Form
ITE Land Use Code: 934
Land Use/Building Type: Fast Food with Drive Thru
Name of Business: Burger King
Address: 6660 Wayzata Blvd
City: Golden Valley
State: Minnesota
Zip Code: 55426
Date(s) August 5-8, 2011
Weather Conditions High 82-88°F and Clear
CBD
Urban (non-CBD) Competition Within High
Location Within Area Suburban (non-CBD) X Medium X
Area
(select one): Suburban CBD Low
(select one):
Rural
Not Given
Drive-Through Description : 1 Lane
Gross Floor Area (estimated) 3,300 sq.ft
Maximum Queue Time Max Queue Occurred
Sunday 6 4:30pm
Monday 12 12:10pm
Tuesday
Wednesday
Thursday
Friday 10 12:12pm
Saturday 8 9:38pm
Drive-Through Queue Generation D20 February 2012
Appendix D
Drive-Through Queuing Data Form
ITE Land Use Code: 934
Land Use/Building Type: Fast Food with Drive Thru
Name of Business: McDonald's
Address: 5200 Excelsior Blvd
City: St. Louis Park
State: MN
Zip Code: 55416
Date(s) February 1-2, 2012 (Wednesday-Thursday)
Weather Conditions High 32-36°F and Fog
CBD
Urban (non-CBD) Competition Within High
Location Within Area Suburban (non-CBD) X Medium X
Area
(select one): Suburban CBD (select one): Low
Rural
Not Given
Drive-Through Description : 2 Order Stations
IGross Floor Area (estimated) 3,600 sq.ft
Maximum Queue Time Max Queue Occurred
Sunday
Monday
Tuesday
Wednesday 12 11:46am
Thursday 13 12:23pm
Friday
Saturday
Drive-Through Queue Generation D21 February 2012
Appendix D
Drive-Through Queuing Data Form
ITE Land Use Code: 934
Land Use/Building Type: Fast Food with Drive Thru
Name of Business: McDonald's
Address: 2929 Hennepin Ave S
City: Minneapolis
State: MN
Zip Code: 55408
Date(s) February 1-2, 2012 (Wednesday-Thursday)
Weather Conditions High 32-36°F and Fog
CBD
Urban (non CBD) X Competition Within High
Location Within Area Suburban (non-CBD) Medium X
Area
(select one): Suburban CBD Low
(select one):
Rural
Not Given
Drive-Through Description : 1 Lane
Gross Floor Area (estimated) 3,825 sq. ft.
Maximum Queue Time Max Queue Occurred
Sunday
Monday
Tuesday
Wednesday 9 8:48am
Thursday 8 8:54am
Friday
Saturday
Drive-Through Queue Generation D22 February 2012
Appendix D
Drive-Through Queuing Data Form
ITE Land Use Code: 934
Land Use/Building Type: Fast Food with Drive Thru
Name of Business: Taco Bell
Address: 819 Cambridge St
City: Hopkins
State: MN
Zip Code: 55343
Date(s) February 1-2, 2012 (Wednesday-Thursday)
Weather Conditions High 32-36°F and Fog
CBD
Urban (non-CBD) Competition Within High
Location Within Area Suburban (non-CBD) X Medium X
Area
(select one): Suburban CBD Low
Rural (select one):
Not Given
Drive-Through Description : 1 Lane
Gross Floor Area (estimated) 2,500 sq.ft
Maximum Queue Time Max Queue Occurred
Sunday
Monday
Tuesday
Wednesday 10 12:26pm
Thursday 8 12:17pm,6:57pm
Friday
Saturday
Drive-Through Queue Generation D23 February 2012
Appendix D
Drive-Through Queuing Data Form
ITE Land Use Code: 934
Land Use/Building Type: Fast Food with Drive Thru
Name of Business: White Castle
Address: 1111 Cambridge St
City: Hopkins
State: MN
Zip Code: 55343
Date(s) February 1-2, 2012 (Wednesday-Thursday)
Weather Conditions High 32-36°F and Fog
CBD
Urban (non-CBD) High
Competition Within
Location Within Area Suburban (non-CBD) X Medium X
Area
(select one): Suburban CBD Low
(select one):
Rural
Not Given
Drive-Through Description : 1 Lane
Gross Floor Area (estimated) 1,750 sq.ft
Maximum Queue Time Max Queue Occurred
Sunday
Monday
Tuesday
Wednesday 8 5:26pm
Thursday 5 8:13am, 12:10pm, 1:25pm,3:22pm,8:54pm
Friday
Saturday
Drive-Through Queue Generation D24 February 2012
Appendix D
Drive-Through Queuing Data Form
ITE Land Use Code: 881
Land Use/Building Type: Pharmacy/Drugstore w/Drive-Thru
Name of Business: CVS Pharmacy
Address: Medicine Lake Rd &Winnetka Ave
City: New Hope
State: MN
Zip Code: 55427
Date(s) February 7-8,2012 (Tuesday-Wednesday)
Weather Conditions High 32 °F and Clear
CBD
Urban (non-CBD)
CompetitionWithin High X
Location Within Area Suburban (non-CBD) X Area Medium
(select one): Suburban CBD Low
(select one):
Rural
Not Given
Drive-Through Description : 2 Lanes
' Gross Floor Area (estimated) 18,700 sq.ft.
Maximum Queue Time Max Queue Occurred
Sunday
Monday
Tuesday 1 13 times
Wednesday 2 5:55pm
Thursday
Friday
Saturday
Drive-Through Queue Generation D25 February 2012
Appendix D
Drive-Through Queuing Data Form
ITE Land Use Code: 881
Land Use/Building Type: Pharmacy/Drugstore w/Drive-Thru
Name of Business: CVS
Address: 2426 W Broadway Ave
City: Minneapolis
State: MN
Zip Code: 55411
Date(s) February 7-8, 2012 (Tuesday-Wednesday)
Weather Conditions High 32 °F and Clear
CBD
Urban (non-CBD) High
Competition Within
Location Within Area Suburban (non-CBD) X Medium X
Area
(select one): Suburban CBD (select one): Low
Rural
Not Given
Drive-Through Description : 2 Lanes
Gross Floor Area (estimated) 14,200 sq.ft
Maximum Queue Time(s)Max Queue Occurred
Sunday
Monday
Tuesday 4 5:28pm
Wednesday 4 6:38pm
Thursday
Friday
Saturday
Drive-Through Queue Generation D26 February 2012
Appendix D
Drive-Through Queuing Data Form
ITE Land Use Code: 881
Land Use/Building Type: Pharmacy/Drugstore w/Drive-Thru
Name of Business: CVS
Address: 3655 Central Ave NE
City: Minneapolis
State: MN
Zip Code: 55418
Date(s) February 7-8, 2012(Tuesday-Wednesday)
Weather Conditions High 32°F and Clear
CBD
Urban (non-CBD) X Competition Within High
Location Within Area Suburban (non-CBD) Medium X
Area
(select one): Suburban CBD Low
(select one):
Rural
Not Given
Drive-Through Description : 2 Lanes
Gross Floor Area (estimated) 14,200 sq.ft
Maximum Queue Time(s) Max Queue Occurred
Sunday
Monday
Tuesday 2 1:57pm,3:35pm,5:48pm,6:07pm,7:10pm
Wednesday 2 3:03pm,3:52pm,4:07pm,4:46pm,5:12pm,5:20pm,
6:43pm
Thursday
Friday
Saturday
Drive-Through Queue Generation D27 February 2012
Appendix D
Drive-Through Queuing Data Form
ITE Land Use Code: 881
Land Use/Building Type: Pharmacy/Drugstore w/Drive-Thru
Name of Business: Walgreens
Address: 540 Blake Rd N
City: Hopkins
State: MN
Zip Code: 55343
Date(s) February 1-2, 2012 (Wednesday-Thursday)
Weather Conditions High 32-36°F and Fog
CBD
Urban (non-CBD) Competition Within High
Location Within Area Suburban (non-CBD) X Area Medium X
(select one): Suburban CBD Low
(select one):
Rural
Not Given
Drive-Through Description : 2 Lanes
IGross Floor Area (estimated) 14,375 sq.ft
Maximum Queue Time(s) Max Queue Occurred
Sunday
Monday
Tuesday
Wednesday 4 2:33pm,3:31pm,4:46pm,4:57pm,5:28pm,6:26pm,
6:38pm,8:20pm,9:20pm
Thursday 5 4:30pm,4:52pm, 5:56pm,6:00pm
Friday
Saturday
Drive-Through Queue Generation D28 February 2012
Appendix D
Drive-Through Queuing Data Form
ITE Land Use Code: 881
Land Use/Building Type: Pharmacy/Drugstore w/Drive-Thru
Name of Business: Walgreens
Address: 4200 Winnetka Ave N
City: New Hope
State: MN
Zip Code: 55428
Date(s) February 7-8, 2012 (Tuesday-Wednesday)
Weather Conditions High 32 °F and Clear
CBD
Urban (non-CBD) Competition Within High X
Location Within Area Suburban (non-CBD) X Area Medium
(select one): Suburban CBD Low
(select one):
Rural
Not Given
Drive-Through Description : 2 Lanes
Gross Floor Area (estimated) 16675 sq.ft.
Maximum Queue Time(s) Max Queue Occurred
Sunday
Monday
Tuesday 3 4:03pm
Wednesday 3 8:34am,4:04pm,4:51pm
Thursday
Friday
Saturday
Drive-Through Queue Generation D29 February 2012
Appendix D
Drive-Through Queuing Data Form
ITE Land Use Code: 881
Land Use/Building Type: Pharmacy/Drugstore w/Drive-Thru
Name of Business: Walgreens
Address: 4100 W Broadway Ave
City: Robbinsdale
State: MN
Zip Code: 55422
Date(s) February 7-8,2012(Tuesday-Wednesday)
Weather Conditions High 32 °F and Clear
CBD
Urban (non-CBD) Competition Within High X
Location Within Area Suburban (non-CBD) X Medium
Area
(select one): Suburban CBD (select one): Low
Rural
Not Given
Drive-Through Description : 1 Lane
I Gross Floor Area (estimated) 14,400 sq.ft.
�` "'Maximum Queue Time(s) Max Queue Occurred
Sunday
Monday
Tuesday3 4:49pm
WednestlaiV ' '' 2 12:49pm
Thursday't°fir
Friday
Saturday
Drive-Through Queue Generation D30 February 2012