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2014
Ephrem Woldetsadik
Traffic Engineering
Traffic Reports
Table of Contents
CIEG 465: TRAFFIC ENGINEERING PROJECTS
PROJECT 1: Pedestrian Walking Speed Study Identify a crosswalk (preferably at one of your signalized intersections) or a sidewalk. Conduct a pedestrian walking speed study for 25 male and 25 female pedestrians and determine the average walking speeds for both gender and for all pedestrians sampled.
PROJECT 2: Traffic Flow Study Conduct a traffic flow study at a location on a selected corridor and compute the flow rate at the location.
PROJECT 3: Intersection Condition Diagrams Prepare intersection condition diagrams for the 4 intersections selected in Task 1. Use either AutoCAD or Microstation to prepare your diagrams.
PROJECT 4: Spot Speed Studies Conduct a spot speed study (off-peak period) at the location where Project 2 was conducted. The equipment for the field data collection will be provided. A minimum of 100 vehicles is required. Prepare a summary report for this study and provide the summary speed characteristics at the location.
PROJECT 5: Intersection Turning Movement Counts Conduct a 2-hour turning movement count (TMCs) at the 4 intersections selected for this class. The equipment for the TMCs will be provided. Prepare a summary report for this study and provide the peak hour volume and peak hour factors for the 4 intersections.
PROJECT 6: Parking Studies Conduct a 2-hour parking study at a selected location/block near one of your selected intersections. Prepare a summary report and provide the parking characteristics for the location.
PROJECT 7: Signal Timing and Phasing Study Conduct signal timing and phasing studies at the 2 selected signalized intersections. Prepare a report and summarize your findings.
PROJECT 8: Level of Service (LOS) Analysis Conduct LOS analyses at the 4 selected intersections using HCS and Synchro. Prepare a report and summarize your findings.
Fall 2014
Ephrem Woldetsadik
Traffic Engineering 1
Fall 2014
U and 10 Street Pedestrian Study
Pedestrian Data Collecting
Objectives:
The objective of the study is to determine the average walking speeds of pedestrians at a
selected crosswalk in Washington D.C.
Introduction/Background
Pedestrian studies focus on the
measurements, analysis, and
improvement of pedestrian traffic areas
in a given region. Until recently,
pedestrians were often overlooked in the
transportation system. A pedestrian
study typically addresses two major
issues; walk-ability and safety. Walk-
ability is the willingness of the
pedestrian to walk to their destination,
and is influenced by four major factors -
increasing vehicular traffic, travel
demand campaigns, mode/timing shifts
and destination distance from residential development. Pedestrian signals and pedestrian
pavement markings are major safety components. There are three common types of pedestrian
studies: pedestrian volume studies, pedestrian gap acceptance studies, and pedestrian walking
speed studies.
Pedestrian volume studies measure pedestrian demand and turning movements; they are
generally conducted during peak hours, which is important for the traffic flow. A pedestrian gap
acceptance study computes the approximate gap, or the time lag between two vehicles, needed
for pedestrians to cross. This information is useful when designing a crosswalk, especially at
mid-block locations. Pedestrian walking speed studies measure the speed of individual
pedestrians who cross in compliance with crossing signs and signals. This study may be used to
determine appropriate pedestrian signal timing at an intersection.
STREET VIEW OF 10TH AND U STREET NW
Pedestrian studies play a critical role when developing the infrastructure of a roadway.
Communities across the United States are implementing plans and strategies to integrate
pedestrian travel into the transportation system. According to the Intermodal Surface
Transportation Efficiency Act and Transportation Equity Act for the 21st Century, the Federal
Aid Highway Program funding for pedestrian facilities and programs increased from $17.1 in
million in 1991 to $422.7 million in 2003 (1).
Safety is the primary reason why pedestrian studies are conducted. Determining the
number of pedestrian related crashes that occur on a certain roadway or intersection can be
useful to identify safety discrepancies. With this information, recommendations can be made to
influence or improve the design of the roadway/intersection. This may be in the form of
increasing signal times, reducing the speed limit on a roadway, or widening crosswalks to
increase pedestrian capacity. Pedestrian studies are capable of pinpointing imperfections present
on a given corridor. Some corridors may need slight adjustments while others may need more.
Such adjustments can include median designs, nighttime lighting, countdown timers, and the
allowance of right turning movements during a red signal.
Pedestrian studies can also be used to determine the number of pedestrians in a certain
area during a given time frame. From this information building developments can be derived,
and the placement of certain stores, businesses, and restaurants can be determined. If a lack of
pedestrian presence is seen in the area, then steps can be taken to provide beautification measures
that will make the area more attractive and increase the pedestrian presence.
Most pedestrian studies, including pedestrian volume studies, pedestrian gap acceptance
studies, and pedestrian walking speed studies are conducted manually. Manual counting is
inexpensive and is typically used when automated equipment is deemed unnecessary. Manual
counts for pedestrian studies are typically executed using tally sheets. Tuesday, Wednesday, and
Thursday are typical days for collecting data as Monday morning and Friday evening peak hours
may exhibit unusually high volumes (2). Weather conditions such as cold and rainy weather may
also affect pedestrian counts. Depending on study purpose, items such as age, gender, and/or
handicap may be recorded for a certain number of pedestrians. Time intervals for data collection
may vary from study to study.
Pedestrian volume studies can be used to measure the amount of people passing a certain
point during a specified time period. Volumes can be recorded using the tally method. Using this
method, the number of pedestrians crossing at a certain approach may be recorded using tally
marks on a data sheet.
The purpose of a pedestrian gap acceptance or group size study is to determine adequate
gap time required for the 85th percentile group size of pedestrians to cross a street of specified
width at a given time (3). To complete a gap study, one must record the number of groups and
the number of rows within each group crossing. This information may be recorded using the
same tally method utilized in the pedestrian volume study. Using the data, the number of rows in
the predominant pedestrian group size, the length of a minimum adequate gap, the number and
size of gaps in the traffic stream, and the sufficiency of adequate gaps may be determined. (4)
Pedestrian walking speed studies, which are used to determine adequate signal timing,
may also be conducted manually. Pedestrian speeds, which are subject to several factors such as
age, gender, handicaps, and weather, may be timed using a stopwatch and recorded on a data
sheet. To decide if the signal timing is adequate for the pedestrians observed, the following
equation may be used when the crosswalk width is greater than 10 feet:
𝐺𝑝 = 3.2 + (𝐿𝑆𝑝
) + (2.7 ×𝑁𝑝𝑒𝑑𝑊𝐸
)
where L is the length of the crosswalk in feet, Sp is the walking speed of pedestrians, Nped is the
number of pedestrians crossing per phase in a single crosswalk, and 𝑊𝐸 is the width of the
crosswalk. When conducting a pedestrian study, it may also be necessary to compute the mean
walking speed and standard deviation for hypothesis testing. Statistical testing is completed
using data from a sample of the population. Upon completion of statistical testing one can infer
that the results apply to the population, assuming the sample is represents the population. The
mean walking speed is a measure of the average walking speed for compliant crossing
pedestrians. The average speed may be determined using the follow equation:
𝑀𝑒𝑎𝑛 𝑊𝑎𝑙𝑘𝑖𝑛𝑔 𝑆𝑝𝑒𝑒𝑑 = Σ 𝑑𝑡𝑖𝑛
AERIAL VIEW OF 10TH AND U STREET NW
where d is the distance traveled, t is the travel time, and n is the number of pedestrians. The
standard deviation is defined as the most common measure of spread of data around a central
value. Standard deviation is denoted by the following equation,
𝑠𝑡𝑎𝑛𝑑𝑎𝑟𝑑 𝑑𝑒𝑣𝑖𝑎𝑡𝑖𝑜𝑛 = �Σ(𝑥𝑖 − 𝑥)2
𝑁 − 1
where, x is the mean of the sample, N represents the number of sample and xi represents
individual data (3). The variance, which describes the amount of inconsistency around a mean,
can be found by squaring the standard deviation.
Scope:
The study location is at the
intersection of 10th and U Street NW
in Washington D.C. The location is
surrounded with local restaurants, U
metro station, CVS Pharmacy, bus
stop, night clubs, bicycle rentals,
houses, and a middle school. The
data that was collected included
factors that influenced the
pedestrian while completing the
crosswalk. These factors can vary
from age group, physical shape,
carrying bags, etc.
Methodology and Data Collection:
The northbound crosswalk at the intersection of 10th and U street NW was observed in
this study. Data was collected on Tuesday, September 2, 2014 from 6:45pm to 7:35 pm. The
weather at the study location was cloudy. Stated in the scope, the factors are considered while the
pedestrian are completing the crosswalk. The length of the crosswalk will determine how far and
fast will the pedestrian complete the crosswalk. In addition, the pedestrian countdown signal has
to be accounted whether it as a major factor on how fast the pedestrian
cross the sidewalk. A measuring wheel was used to measure the
crosswalk. The length of the crosswalk was determined to be 44 feet
from midpoint of one curve of the street to the other. A stop watch was
used to determine the length of time for a pedestrian to walk the
crosswalk successful without stopping in the middle of the crosswalk
for any reason. A raw data was collected for each pedestrian and it composed of each
individual’s time, physical shape, gender, and carrying bags. In addition, the raw data was
composed of 25 male and 25 female.
Analysis of Results:
As illustrated in the data table, the male pedestrian’s average time was 7.76 seconds to
complete the cross walk with the average walking speed of 5.96 feet per second. For the female
pedestrian’s average time it was 8.05 seconds with an average walking speed of 5.69 feet per
second. The overall average walking speed for pedestrians at the intersection is 5.82 feet per
second with the average time of 7.91 seconds.
Gender Average walking Speed (ft./s)
Male 5.96
Female 5.69
All 5.82
Conclusion/Recommendations:
The average walking speed for pedestrians at the northbound crosswalk at 10th and U
Street NW was 5.82 feet per second.
MEASURING WHEEL
References
1. Muhammad M. Ishaque; Robert B. Noland. "Making Roads Safe for Pedestrians or Keeping them Out of the Way? - an Historical Perspective on Pedestrian Policies in Britain" (PDF). Imperial College London Centre for Transport Studies. Retrieved 18 August 2009.
2. Traffic Volume Counts. http://www.ctre.iastate.edu/pubs/traffichandbook/3trafficcounts.pdf. Accessed Sept. 4, 2014.
3. "Pedestrian Group Size Study." Florida Department of Transportation. N.p., Jan.-Feb. 2000. Web. Sept. 2014. <http://www.dot.state.fl.us/trafficoperations/Operations/Studies/MUTS/Chapter10.pdf>.
4. "Traffic Engineering Studies - School Crossing Study." Iowa Department of Transportation. N.p., 2 Oct. 2006. Web. Sept.2014. <http://www.iowadot.gov/traffic/manuals/pdf/07f-01.pdf>.
5. Federal Highway Administration University Course on Bicycle and Pedestrian Transportation. Traffic Engineering 1. Dr.Arhin, Department of Transportation, Howard University, Washington D.C., https://blackboard.howard.edu/bbcswebdav/pid-1571822-dt-content-rid 2666632_1/courses/CIEG46501201408/Pedestrian%20and%20Bicycle%20Characteristics.pdf
Male (sec) Fps condation Female (sec) Fps condation Length of walkway (ft)5 8.8 bags 9 4.89 bags 448 5.5 7.3 6.03 couple 44
7.8 5.64 couple 8.27 5.32 bags 447.3 6.03 couple 8.47 5.19 fat 44
6.97 6.31 7.38 5.96 couple 4410.84 4.06 old 8.15 5.40 44
7.26 6.06 6.34 6.94 fat 449.41 4.68 old 7.87 5.59 44
7.8 5.64 8.27 5.32 448.55 5.15 6.75 6.52 young 447.49 5.87 carring bike 7.58 5.80 couple 447.58 5.80 couple 8.11 5.43 448.68 5.07 fat 8.57 5.13 couple 446.06 7.26 7.62 5.77 couple 448.37 5.26 6.77 6.50 447.86 5.60 7.93 5.55 446.57 6.70 9.26 4.75 dress 44
7.4 5.95 8.3 5.30 couple 445.86 7.51 bags 7.1 6.20 445.15 8.54 bike 5.05 8.71 bags 446.46 6.81 8.38 5.25 heels 44
10.52 4.18 old 8.49 5.18 couple 449.55 4.61 couple 9.12 4.82 449.45 4.66 11.73 3.75 old/bags 448.06 5.46 9.55 4.61 couple 44
mean (sec) 7.76 mean (sec) 8.05mean (fps) 5.96 mean (fps) 5.69All Gendermean(sec) 7.91mean(fps) 5.82
2014
Ephrem Woldetsadik
@02666435
9/16/2014
Georgia Ave NW Traffic Flow Study
Traffic Flow Study
Objectives:
The objective of this study is to conduct a traffic flow study at a location on a selected
corridor and compute the flow rate at the location for an hour.
Introduction/Background:
Traffic flow theory is expressed as numerical models that attempt to correlate
characteristics of traffic movement to each other and to essential traffic parameters. The science
behind traffic flow study was discovered by Bruce Greenshilds and the Yale Bureau of Highway
Traffic in the 1930s (1). The understanding of traffic characteristics has grown and became
beneficial for traffic engineers in developing roads, transportation plans, etc.
Traffic Flow is the study of the movement of individual drivers and vehicles between two
points and the interactions they make with one another. However, studying traffic flow is
difficult because driver behavior is something that cannot be predicted with one-hundred percent
certainty. Factors affecting traffic flow include geometric characteristics (length of the section,
free-flow speed, no. of lanes, lane width), traffic flow characteristics (volume, composition,
turning movements, driver behavior, etc.) and signal settings (cycle time, green times, phase
sequence, offsets) (2). Traffic flow characteristics consist of traffic speed, travel time, volume,
and density (1). These functions are the elements of planning, design and operation of roads and
highways and transport facilities. The relationship of flow, speed, and density help traffic
engineers in planning, designing and evaluating the efficiency of implementing traffic
engineering measures on a road or highway system. The basic for further analyses are data
collecting on several elements of traffic stream. One example of the use of traffic flow theory in
design is the determination of adequate lane lengths for storing left-turn vehicles on separate left-
turn lanes (1). The determination of average delay at intersections and freeway ramp merging
areas is another example of the application of traffic flow theory. Another important application
of traffic flow theory is simulation, where mathematical algorithms are used to study the
complex interrelationships that exist among the elements of a traffic stream or network to
estimate the effect of changes in traffic flow on factors such as accidents, travel time, air
pollution and fuel consumption (1).
Figure 1: Aerial View of Georgia Ave NW
Traffic conditions can range from almost free flow to highly congested conditions when
the roadways are jammed with slow moving vehicles. The basic variables that can describe the
existing conditions can be determined within a vehicles stream flow, concentration, and mean
speed. The fundamental relationship of these three elements can be used for several traffic
events. Consider the case of vehicles following each other on a long stretch of roadway.
Furthermore, assume that these vehicles are not required to interrupt their motion for reasons that
are external to the traffic stream, such as traffic lights, and transit stations. In this case of
uninterrupted flows the only interference that a single vehicle experiences is caused by other
vehicles on the roadway (1).
Scope:
The study was conducted on Georgia Ave NW between the intersecting roads of Howard
Pl NW and Barry Pl NW. This street is composed of 4 lanes, 2 northbound and 2 southbound.
The traffic flow study was performed on the 2 lanes southbound towards the intersection of
Barry Place NW and Georgia Ave NW. The location is surrounded with local restaurants, bus
stops, Howard University, college dorms, parking lots, Baseball Park, Banneker Recreation
Center, and 2 intersecting roads; Barry Place NW and Howard Place NW.
Methodology and Data Collection:
The flow rate data was collected on Georgia Ave NW
southbound towards the Barry Place NW for 30 minutes on
Thursday, September 4th from 8:30pm to 9:00pm. To
determine the flow rate, a tree was used as a reference point to
count the number of cars passing the tree within 30 minutes.
The tree location is shown on Figures 1and 2. Tally marks
were used to count the number of vehicles passing the tree
within the time frame. After 30 minutes, 262 vehicles passed
the reference point.
Reference point
Figure 2: Street View of Georgia Ave NW going Southbound
Reference point
Analysis of Result:
To calculate the traffic flow rate, the equation 𝑞 = 𝑛/𝑡, where q= traffic flow in vehicles
per unit time, n = number of vehicles passing some designated roadway point during time t, and
t= duration of time interval, was used (3). Theoretically, the flow rate can used to find the traffic
volume by multiplying the number of vehicles found in 30 minutes by 2 to determine the volume
for an hour.
Time (min) Vehicles(n) Traffic flow(q)
30 262 8.73
60 524 8.73
Conclusion/ Recommendations:
The traffic flow rate on southbound Georgia Ave NW between Barry Place NW and
Howard Place was computed to be 524 vehicles / hour.
References
1. McShane, William R., and Roger P. Roess. Traffic Engineering. 4th ed. Upper Saddle River
N.J.: Prentice-Hall, 2011. 107. Print. 2. Gartner, Nathan. "TRAFFIC FLOW CHARACTERISTICS IN COORDINATED SIGNAL
SYSTEMS." tft2010. Traffic Flow Theory and Characteristics Committee (AHB45) of the
Transportation Research Board, n.d. Web. 13 Oct 2014.
<http://www.tft2010.inrets.fr/papers/10-7-i4.pdf>. 3. McShane, William R., and Roger P. Roess. Traffic Engineering. 4th ed. Upper Saddle River
N.J.: Prentice-Hall, 2011. 107. Print. 4. Lecture 2- Traffic and Vehicle Characteristics, Dr. Stephen Arhin;
https://blackboard.howard.edu/bbcswebdav/pid-1579274-dt-content-rid-
2690357_1/courses/CIEG46501201408/Traffic%20and%20Vehicle%20Operating%20-
%20Chapter%202.pdf Accessed Sept. 13, 2014.
5. Valentin, Jan. "Traffic Flow Theory." Web. 15 Sept. 2014.
<http://d2051.fsv.cvut.cz/predmety/tren/trafficflow.pdf>.
2014
Ephrem Woldetsadik
@02666435
9/30/2014
Condition Diagram
Condition Diagram
Objectives:
The objective of this study is to develop condition diagram for 4 intersections.
Introduction/Background:
A site survey should be conducted to record relevant geometric and traffic control data.
These data include: number of lanes, lane widths, lane configurations, presence of turn bays,
length of turn bays, length of pedestrian crosswalks, and intersection widths for all approach
legs. An effective method for recording this information is with a condition diagram. A condition
diagram shows existing intersection layout including such features as roadway geometry,
channelization, grades, number and width of travel lanes, lane use, speed limit, parking
restrictions, driveways, bus stops and distance restrictions (1). The location of any land uses
including schools, parks, playground and other significant pedestrian generating facilities should
be indicated on the diagram. Other information that can have an impact on signal operations
include: approach grades, presence of on-street parking, presence of loading zones, presence of
transit stops, dips in approach profile near the intersection, and intersection skew angle (2).
Many of these factors may have an impact on the capacity of one or more movements at
the intersection; they may also influence intersection safety (2). The condition diagram should
provide engineers with details of field conditions and help study the need for changes to existing
traffic control devices and to do so a field evaluation should be conducted (2).
Scope:
There was a study of various intersections, accurate measurements, and detailed locations
of traffic control systems to create the condition diagram. Four intersection were chosen for the
site survey in Washington D.C.; 10 street NW & U Street NW (Figures 1 and 2), Sherman Ave
NW & Barry Pl NW (Figures 3 and 4), Sherman Ave NW & Girard Street NW (Figures 5 and
6), and Georgia Ave NW & Gresham Pl NW (Figures 7 and 8).
Figure 1: Aerial view of 10th street at U street NW Figure 2: Street view of 10th street at U street NW
Figure 3: Aerial view of Sherman Ave NW at Barry Pl NW
Figure 5: Aerial View of Sherman Ave NW at Girard Street NW Figure 6: Street view of Sherman Ave NW at Girard Street NW
Figure 4: Street view Aerial view of Sherman Ave NW at Barry Pl NW
s
Methodology and Data Collection:
The measurements at all 4 intersections were taken by a measuring wheel in feet. The
measurements included widths of travel lanes, bus stop lanes, driveways, on-street parking space,
and sidewalks. To collect the measurements, a sketch of the top view for each intersection was
drawn before going to each site on September 21, 2014. Since a drawing was available for all
sites, it was simple to write all the measurements from the top view for each intersection. After
gathering all the measurements and features for each intersection, AutoCAD was used to
illustrate the intersections with the measurements and features. AutoCAD is a 2-D and 3-D
computer-aided drafting software application used in architecture, construction and
manufacturing to assist in the preparation of blueprints and other engineering plans. All
intersection drawings with a legend are attached with the report.
Analysis of Result:
See attachment.
Conclusion/ Recommendations:
A condition diagram provides importation information when remodeling and improving
intersections. A recommendation would be to make sure all intersections for each state are up to
date and are available for engineers to look up on the web.
Figure 7: Aerial View of Georgia Ave NW at Gresham Pl NW Figure 8: Street view Aerial View of Georgia Ave NW at Gresham Pl NW
References
1. DeBenedictis, John. "Traffic Signal Operation Design Guidelines." Cityofboston. Boston
Department of Transportation, 4 Sept. 2004. Web. 28 Sept. 2014.
<https://www.cityofboston.gov/transportation/pdfs/traf_signal_oper_design_guide.pdf>. 2. "Traffic Signal Timing Manual." Office of Operation. U.S. Department of
Transportation, 1 Jan. 2004. Web. 28 Sept. 2014.
<http://ops.fhwa.dot.gov/publications/fhwahop08024/chapter7.htm>.
3. Condition Diagrams Information, Dr. Stephen
Arhin; https://blackboard.howard.edu/webapps/blackboard/content/listContent.jsp?course_id
=_1037101_1&content_id=_1530770_1&mode=reset Accessed Sept. 28, 2014.
2014
Ephrem Woldetsadik
@02666435
10/17/2014
Georgia Ave NW Spot Speed Study
Spot Speed Study
Objectives:
The objective of this study is to conduct a spot speed study (off-peak period) at a location
on a selected corridor and provide the summary speed characteristics at the location.
Introduction/Background:
Speed is an important measure of the quality of level and safety of road network. Speed
by definition is the rate of movement of vehicle in distance per unit time. Spot speed studies are
used to determine the speed distribution of a traffic stream at a specific location. The data
gathered in spot speed studies are used to determine vehicle speed percentiles, which are useful
in making many speed-related decisions (1). Spot speed data have a number of safety
applications, including the following (1):
1. Determining existing traffic operations and evaluation of traffic control devices a. Evaluating and determining proper speed limits b. Determining the 50th and 85th speed percentiles c. Evaluating and determining proper advisory speeds d. Establishing the limits of no-passing zones e. Determining the proper placements of traffic control signs and markings f. Setting appropriate traffic signal timing
2. Establishing roadway design elements a. Evaluating and determining proper intersection sight distance b. Evaluating and determining proper passing sight distance c. Evaluating and determining proper stopping sight distance
3. Assessing roadway safety questions a. Evaluating and verifying speeding problems b. Assessing speed as a contributor to vehicle crashes c. Investigating input from the public or other officials
4. Monitoring traffic speed trends by systematic ongoing speed studies 5. Measuring effectiveness of traffic control devices or traffic programs, including signs and
markings, traffic operational changes, and speed enforcement programs For a spot speed study at a selected location, a sample size of at least 50 and preferably
100 vehicles is usually obtained (2).Traffic counts during a Monday morning or a Friday peak
period may show very high volumes and are not normally used in the analysis; therefore, counts
are usually conducted on a Tuesday, Wednesday, and Thursday (2). Spot speed data are gathered
using one of three methods: stopwatch method, radar meter method, or pneumatic road tube
method.
Figure 1: Example of Frequency Distribution Table
Speed percentiles are tools used to determine effective and adequate speed limits. The
two speed percentiles most important to understand are the 50th and the 85th percentiles (2). The
50th percentile is the median speed of the vehicles and it represents the average speed of the
traffic stream. The 85th percentile is the speed at which 85% of the observed vehicles are
traveling at or below. This percentile is used in evaluating/recommending posted speed limits
based on the assumption that 85% of the drivers are traveling at a speed they perceive to be safe
(3). In other words, the 85th percentile of speed is normally assumed to be the highest safe speed
for a roadway section. Weather conditions like rain or snow may affect speed percentiles.
A frequency distribution table is
a suitable way to determine speed
percentiles as shown in figure 1. When
the sample size equals 100 vehicles, the
cumulative frequency and cumulative
percent are the same. A calculation is
completed using percentages and speeds
from the distribution table. Shown below
is the equation for calculating speed
percentiles (4):
𝑆𝑑 =𝑃𝑑 − 𝑃𝑚𝑖𝑛
𝑃𝑚𝑎𝑥 − 𝑃𝑚𝑖𝑛(𝑆𝑚𝑎𝑥 − 𝑆𝑚𝑖𝑛) + 𝑆𝑚𝑖𝑛
where 𝑆𝑑 = speed at 𝑃𝑑, 𝑃𝑑, = percentile desired, 𝑃𝑚𝑎𝑥= higher cumulative percent, 𝑃𝑚𝑖𝑛 =
lower cumulative percent, 𝑆𝑚𝑎𝑥 = higher speed, and 𝑆𝑚𝑖𝑛= lower speed.
After the study is completed and the data have been tabulated the following steps may be
considered as part of the typical data analysis (5).
1. Mean Speed: The average speed; calculated as the sum of all speeds divided by the number
of speed observations.
2. 85th Percentile Speed: The speed at or below which 85 percent of a sample of free flowing
vehicles is traveling.
Radar Meter Gun
3. Median (50th Percentile Speed): The speed that equally divides the distribution of spot
speeds; 50 percent of observed speeds are higher than the median; 50 percent of observed
speeds are lower than the median.
4. Mode: The number that occurs most frequently in a series of numbers.
5. Pace: A 10 mile-per-hour increment in speeds that encompasses the highest portion of
observed speeds; often is the mean speed plus/minus five miles per hour.
6. Standard Deviation: a measure of the spread of the individual speeds. It is estimated as
𝑆 = √∑(𝑢𝑗−𝑢�)2
𝑁−1
where S = standard deviation, u = arithmetic mean, 𝑢𝑗 = jth observation, and N = number of
observations.
Scope:
The study was conducted on Georgia Ave NW between the intersecting roads of Howard
Pl NW and Barry Pl NW. This street is composed of 4 lanes, 2 northbound and 2 southbound.
The spot speed study was performed on the 2 lanes southbound
towards the intersection of Barry Place NW and Georgia Ave
NW. A minimum of 100 vehicles is required for the study.
Using the data that was collected the mean, median, mode, 85th
percentile speed, standard deviation, and pace can be
determined. The location is surrounded with local restaurants,
bus stops, Howard University, college dorms, parking lots, Baseball Park, Banneker Recreation
Center, and 2 intersecting roads; Barry Place NW and Howard Place NW.
Methodology and Data Collection:
The spot speed data was collected on Georgia Ave NW southbound
towards the Barry Place NW for 27 minutes on Wednesday, October 8,
2014 from 3:00pm to 3:27pm. To determine the spot speed data, a radar
meter gun is used. The radar meter is used to measure the speed of a
moving vehicle and it’s operated by one person. A raw data is attached
illustrating each vehicles speed collected by the radar meter gun. To determine
Street View of Georgia Ave NW going Southbound
the key parameters: mean, median, mode, 85th percentile speed, standard devation, and pace,
Microsoft Excel is used.
Analysis of Result:
Using Microsoft Excel, the speed characteriastics: mean, median, mode, 85th percentile
speed, standard devation, and pace were determined as show in the table below. Along with
speed characteriastics, a Histogram of Observed Vehicles' Speeds, a Cumulative Distribution
graph, a Frequency Distibution graph was computed and illustrated.
see attachment.
Key Parameters
Mean 26.82 MPH
Median 27 MPH
Mode 27 MPH
85th percentile speed 30.5 MPH
Standard Deviation 3.93 MPH
Pace (22-32 mph) 83 Vehicles
Conclusion/ Recommendations:
The study shows the 50th percentile or median speed was 27 mph, and the 85th percentile
of speed was 30.5 mph.
References
1. Robertson, H. D. 1994. Spot Speed Studies. In Manual of Transportation Engineering
Studies, ed. H. D. Robertson, J. E. Hummer, D. C. Nelson. Englewood Cliffs, N.J.: Prentice
Hall, Inc., pp. 33–51.
2. Ewing, R. 1999. Traffic Calming Impacts. In Traffic Calming: State and Practice.
Washington, D.C.: Institute of Transportation Engineers, pp. 99–126.
3. Homburger, W. S., J. W. Hall, R. C. Loutzenheiser, and W. R. Reilly. 1996. Spot Speed
Studies. In Fundamentals of Traffic Engineering. Berkeley: Institute of Transportation
Studies, University of California, Berkeley, pp. 6.1–6.9.
4. "Spot Speed." .ctre.iastate.edu. Web. 16 Oct. 2014.
<http://www.ctre.iastate.edu/pubs/traffichandbook/2SpotSpeed.pdf>.
5. Roshandeh, Arash. "Evaluation of Traffic Characteristics: A Case
Study." Academypublisher. Academypublisher, 6 May 2009. Web. 16 Oct. 2014.
<http://www.academypublisher.com/ijrte/vol01/no06/ijrte0106062068.pdf>.
Car No. Speed (mi/hr) Car No. Speed (mi/hr)1 21 51 302 26 52 263 24 53 304 19 54 245 20 55 306 27 56 307 29 57 298 31 58 329 37 59 24
10 29 60 2611 28 61 3512 27 62 2913 25 63 2014 28 64 2415 30 65 2216 29 66 2817 24 67 2718 24 68 2819 20 69 3320 24 70 3221 24 71 2822 20 72 3523 20 73 2224 27 74 2725 28 75 2326 27 76 2727 26 77 2828 27 78 3329 23 79 3230 25 80 2831 29 81 3532 26 82 2233 22 83 2734 24 84 2335 31 85 2536 33 86 2737 30 87 2338 22 88 2739 29 89 3040 31 90 2941 29 91 2742 24 92 2343 25 93 2344 32 94 2145 27 95 3546 24 96 31
47 25 97 2648 27 98 2749 30 99 2250 27 100 21
Key Parameters Miles/HrMedian 27Mode 27Mean 26.82Standard Deviation 3.9385th percentile 30.5Pace (22-32 mph) 83 vehicles
Speed (mi/hr) Frequency of All Cumulative Frequency CumulativeAll Frequency CumulativeVehicles (f) Frequency Percent Percent
19 1 1 1% 1%20 5 6 5% 6%21 3 9 3% 9%22 6 15 6% 15%23 6 21 6% 21%24 11 32 11% 32%25 5 37 5% 37%26 6 43 6% 43%27 16 59 16% 59%28 8 67 8% 67%29 9 76 9% 76%30 8 84 8% 84%31 4 88 4% 88%32 4 92 4% 92%33 3 95 3% 95%35 4 99 4% 99%37 1 100 1% 100%
02468
1012141618
19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 35 37
Freq
uenc
y of
Veh
icle
(f)
Vehicle Speed (mi/h)
Histogram of Observed Vehicles' Speeds
0%2%4%6%8%
10%12%14%16%18%
15 20 25 30 35 40
Freq
uenc
y (%
)
Vehicle Speed (mi/h)
Frequency Distribution
0%10%20%30%40%50%60%70%80%90%
100%
15 20 25 30 35 40
Cum
ulat
ive
Freq
uenc
y (%
)
Vehicle Speed (mi/h)
Cumulative Distribution
2014
Ephrem Woldetsadik
@02666435
10/17/2014
Turning Movement Count
Turning Movement Count Study
Objectives:
The objective of this study is to conduct a 2 hour turning movement count (TMCs) and
provide the peak hour volume and peak hour factors for 4 intersections.
Introduction/Background:
Traffic volume studies are conducted to determine the number, movements, and
classifications of roadway vehicles at a given location. These data can help identify critical flow
time periods, determine the influence of large vehicles or pedestrians on vehicular traffic flow, or
document traffic volume trends (1). The length of the sampling period depends on the type of
count being taken and the intended use of the data recorded. For example, an intersection count
may be conducted during the peak flow period. If so, manual count with 15-minute intervals
could be used to obtain the traffic volume data (1). A traffic study is conducted to evaluate the
transportation system serving an area and to identify any improvements necessary to
accommodate existing or projected traffic volumes. The study consists of data collection,
including existing traffic volumes and turning movement counts, projected traffic volumes, and
the identification of required improvements such as traffic calming devices. Any identified
improvements may include a feasibility analysis, including identification of impacted properties,
impacted structures, alternate alignments, physical constraints and roadway design criteria to be
used.
Two methods are available for conducting traffic volume counts: manual and automatic.
Manual counts are typically used to gather data for determination of vehicle classification,
turning movements, direction of travel, pedestrian movements, or vehicle occupancy (1).
Automatic counts are typically used to gather data for determination of vehicle hourly patterns,
daily or seasonal variations and growth trends, or annual traffic estimates (1).
Precise traffic movement counts at intersections are needed in many situations. The
counts could be essential for advanced real-time traffic adaptive signal timing, dynamic traffic
assignment, and traffic demand estimation (2). It is desirable to obtain this information in real-
time and in a cost-effective way. Previous work estimates the turning movements using approach
and departure counts or directly identifies flows in exclusive turn lanes. An automated counting
process is extremely complicated for intersections having shared lanes. Machine detection of
turning movement counts can be extremely difficult. Eight independent equations for flow can be
written if one detector is placed on each set of inbound and outbound lanes of a four-leg
intersection, but 12 unknowns exist if all typical movements (left-turn, through and right-turn)
are allowed (2). An automated identification system for turning movements was developed by
Virkler and Kumar in 1998 (2). This system, which is described later in this paper in more detail,
requires the detection of vehicle departures from the intersection, the detection of right turns, and
concurrent information from the signal controller (2). It uses both the locations and the times of
actuations from a small number of detectors to classify movements from shared approach lanes.
Scope:
The study was to conduct a pedestrian and traffic movement analysis at the 4
intersections to create the TMC Data. Four intersection were chosen for the site survey in
Washington D.C.; 10th street NW & U Street NW (Figures 1 and 2), Sherman Ave NW & Barry
Pl NW (Figures 3 and 4), Sherman Ave NW & Girard Street NW (Figures 5 and 6), and Georgia
Ave NW & Gresham Pl NW (Figures 7 and 8).
Figure 1: Aerial view of 10th street at U street NW Figure 2: Street view of 10th street at U street NW
Figure 3: Aerial view of Sherman Ave NW at Barry Pl NW Figure 4: Street view Aerial view of Sherman Ave NW at Barry Pl NW
Methodology and Data Collection:
The pedestrian and traffic movement data for all 4 intersections were taken by TDC
(Traffic Data Collector) Ultra. The TDC Ultra is designed to make collecting turning movement
data easy and accurate. The buttons are arranged to simulate a standard intersection. There are 16
buttons, with 12 normally used for the left, through, and right movements from each of the four
approach directions. The additional four buttons are user-defined; they can be used for bicycles,
pedestrians, etc. While using TDC Ultra's ‘Bank’ buttons, trucks and other heavy vehicles can be
stored separate from passenger vehicles. Multiple studies can be stored in the TDC Ultra. For
Figure 5: Aerial View of Sherman Ave NW at Girard Street NW Figure 6: Street view of Sherman Ave NW at Girard Street NW
Figure 7: Aerial View of Georgia Ave NW at Gresham Pl NW Figure 8: Street view Aerial View of Georgia Ave NW at Gresham Pl NW
each study, the unit stores the date and time, the number of intervals
used, a site code, and the data. The data can be transferred to a
computer through a USB port and be decoded by PETRAPro software.
The software can reads, edit and store the data, as well as print them.
Analysis of Result:
See attachment.
Conclusion/ Recommendations:
The peak hour volume and peak hour factors for 4 intersections are provided below:
Intersections Peak hour volume Peak hour factors
10th street NW & U Street NW 987 .674
Sherman Ave NW & Barry Pl NW 1118 .977
Sherman Ave NW & Girard Street NW 833 .978
Georgia Ave NW & Gresham Pl NW 1059 .840
TDC Ultra
References
1. "Traffic Volume Count." .ctre.iastate.edu. Web. 16 Oct. 2014.
http://www.ctre.iastate.edu/pubs/traffichandbook/3TrafficCounts.pdf
2. Tian, Jialin. "Field Testing for Automated Identification of Turning Movements at
Signalized Intersection." Missouri.edu. University of Missouri-Columbia. Web. 16 Oct.
2014.
File Name : Georgia and GershimSite Code : 00000444Start Date : 9/10/2014Page No : 1
Groups Printed- All Vehicles - Heavy Vehicles - BicyclesGeorgia Avenue
From NorthGreshem Place
From EastGeorgia Avenue
From SouthGreshem Place
From West
Start Time Right Thru Left Peds App. Total Right Thru Left Peds App. Total Right Thru Left Peds App. Total Right Thru Left Peds App. Total Int. Total
08:45 PM 5 38 0 14 57 7 0 10 18 35 2 39 36 12 89 0 0 0 15 15 196Total 5 38 0 14 57 7 0 10 18 35 2 39 36 12 89 0 0 0 15 15 196
09:00 PM 48 42 3 22 115 10 0 36 26 72 0 51 41 28 120 0 0 0 8 8 31509:15 PM 45 40 2 21 108 17 0 38 32 87 0 52 38 24 114 0 0 0 4 4 31309:30 PM 40 50 1 15 106 11 0 38 5 54 2 39 23 6 70 0 0 0 5 5 23509:45 PM 28 52 3 5 88 11 0 18 3 32 3 44 9 2 58 0 0 0 4 4 182
Total 161 184 9 63 417 49 0 130 66 245 5 186 111 60 362 0 0 0 21 21 1045
10:00 PM 7 22 4 0 33 4 0 12 2 18 0 26 7 4 37 0 0 0 2 2 9010:15 PM 5 27 1 1 34 2 0 9 4 15 2 6 5 2 15 0 0 0 1 1 6510:30 PM 4 20 0 1 25 2 0 9 3 14 3 5 11 2 21 0 0 0 1 1 61
Grand Total 182 291 14 79 566 64 0 170 93 327 12 262 170 80 524 0 0 0 40 40 1457Apprch % 32.2 51.4 2.5 14 19.6 0 52 28.4 2.3 50 32.4 15.3 0 0 0 100
Total % 12.5 20 1 5.4 38.8 4.4 0 11.7 6.4 22.4 0.8 18 11.7 5.5 36 0 0 0 2.7 2.7All Vehicles 182 290 0 79 551 64 0 162 93 319 0 250 170 80 500 0 0 0 40 40 1410
% All Vehicles 100 99.7 0 100 97.3 100 0 95.3 100 97.6 0 95.4 100 100 95.4 0 0 0 100 100 96.8Heavy Vehicles 0 1 14 0 15 0 0 4 0 4 0 12 0 0 12 0 0 0 0 0 31% Heavy Vehicles 0 0.3 100 0 2.7 0 0 2.4 0 1.2 0 4.6 0 0 2.3 0 0 0 0 0 2.1
Bicycles 0 0 0 0 0 0 0 4 0 4 12 0 0 0 12 0 0 0 0 0 16% Bicycles 0 0 0 0 0 0 0 2.4 0 1.2 100 0 0 0 2.3 0 0 0 0 0 1.1
Georgia Avenue NW and Greshem Place NW
File Name : Georgia and GershimSite Code : 00000444Start Date : 9/10/2014Page No : 2
Georgia Avenue
Gre
shem
Pla
ce G
resh
em
Pla
ce
Georgia Avenue
Right
182 0 0
182 Thru
290 1 0
291 Left
0 14 0
14 Peds
79 0 0
79
InOut Total314 551 865 12 15 27 0 0 0
326 892 566
Rig
ht
64
0
0
64
Thru 0
0
0
0
Left
162
4
4
170
Peds 93
0
0
93
Out
Tota
lIn
0
319
319
14
4
18
12
4
16
26
353
327
Left170
0 0
170
Thru250 12 0
262
Right0 0
12 12
Peds80 0 0
80
Out TotalIn
452 500 952 5 12 17 4 12 16
461 985 524
Left
0
0
0
0
Thru
0
0
0
0
Rig
ht0
0
0
0
Peds40
0
0
40
Tota
lO
ut
In352
40
392
0
0
0
0
0
0
352
392
40
9/10/2014 08:45 PM9/10/2014 10:30 PM All VehiclesHeavy VehiclesBicycles
North
Georgia Avenue NW and Greshem Place NW
File Name : Georgia and GershimSite Code : 00000444Start Date : 9/10/2014Page No : 3
Georgia AvenueFrom North
Greshem PlaceFrom East
Georgia AvenueFrom South
Greshem PlaceFrom West
Start Time Right Thru Left Peds App. Total Right Thru Left Peds App. Total Right Thru Left Peds App. Total Right Thru Left Peds App. Total Int. Total
Peak Hour Analysis From 08:45 PM to 10:30 PM - Peak 1 of 1Peak Hour for Entire Intersection Begins at 08:45 PM
08:45 PM 5 38 0 14 57 7 0 10 18 35 2 39 36 12 89 0 0 0 15 15 19609:00 PM 48 42 3 22 115 10 0 36 26 72 0 51 41 28 120 0 0 0 8 8 315
09:15 PM 45 40 2 21 108 17 0 38 32 87 0 52 38 24 114 0 0 0 4 4 31309:30 PM 40 50 1 15 106 11 0 38 5 54 2 39 23 6 70 0 0 0 5 5 235
Total Volume 138 170 6 72 386 45 0 122 81 248 4 181 138 70 393 0 0 0 32 32 1059% App. Total 35.8 44 1.6 18.7 18.1 0 49.2 32.7 1 46.1 35.1 17.8 0 0 0 100
PHF .719 .850 .500 .818 .839 .662 .000 .803 .633 .713 .500 .870 .841 .625 .819 .000 .000 .000 .533 .533 .840
Georgia Avenue NW and Greshem Place NW
File Name : Georgia and GershimSite Code : 00000444Start Date : 9/10/2014Page No : 4
Georgia Avenue
Gre
shem
Pla
ce G
resh
em
Pla
ce
Georgia Avenue
Right138
Thru170
Left6
Peds72
InOut Total226 386 612
Rig
ht
45
Thru0
Left
122
Peds81
Out
Tota
lIn
10
248
258
Left138
Thru181
Right4
Peds70
Out TotalIn292 393 685
Left0
Thru
0
Rig
ht0
Peds32
Tota
lO
ut
In276
32
308
Peak Hour Begins at 08:45 PM All VehiclesHeavy VehiclesBicycles
Peak Hour Data
North
Georgia Avenue NW and Greshem Place NW
File Name : Georgia and GershimSite Code : 00000444Start Date : 9/10/2014Page No : 5
Georgia AvenueFrom North
Greshem PlaceFrom East
Georgia AvenueFrom South
Greshem PlaceFrom West
Start Time Right Thru Left Peds App. Total Right Thru Left Peds App. Total Right Thru Left Peds App. Total Right Thru Left Peds App. Total Int. Total
Peak Hour Analysis From 08:45 PM to 10:30 PM - Peak 1 of 1Peak Hour for Entire Intersection Begins at 08:45 PM
08:45 PM 5 38 0 14 57 7 0 10 18 35 2 39 36 12 89 0 0 0 15 15 19609:00 PM 48 42 3 22 115 10 0 36 26 72 0 51 41 28 120 0 0 0 8 8 315
09:15 PM 45 40 2 21 108 17 0 38 32 87 0 52 38 24 114 0 0 0 4 4 31309:30 PM 40 50 1 15 106 11 0 38 5 54 2 39 23 6 70 0 0 0 5 5 235
Total Volume 138 170 6 72 386 45 0 122 81 248 4 181 138 70 393 0 0 0 32 32 1059% App. Total 35.8 44 1.6 18.7 18.1 0 49.2 32.7 1 46.1 35.1 17.8 0 0 0 100
PHF .719 .850 .500 .818 .839 .662 .000 .803 .633 .713 .500 .870 .841 .625 .819 .000 .000 .000 .533 .533 .840
Georgia Avenue NW and Greshem Place NW
File Name : Georgia and GershimSite Code : 00000444Start Date : 9/10/2014Page No : 6
Georgia Avenue
Gre
shem
Pla
ce G
resh
em
Pla
ce
Georgia Avenue
Right138
Thru170
Left6
Peds72
InOut Total226 386 612
Rig
ht
45
Thru0
Left
122
Peds81
Out
Tota
lIn
10
248
258
Left138
Thru181
Right4
Peds70
Out TotalIn292 393 685
Left0
Thru
0
Rig
ht0
Peds32
Tota
lO
ut
In276
32
308
Peak Hour Begins at 08:45 PM All VehiclesHeavy VehiclesBicycles
Peak Hour Data
North
Georgia Avenue NW and Greshem Place NW
File Name : Georgia and GershimSite Code : 00000444Start Date : 9/10/2014Page No : 7
Georgia AvenueFrom North
Greshem PlaceFrom East
Georgia AvenueFrom South
Greshem PlaceFrom West
Start Time Right Thru Left Peds App. Total Right Thru Left Peds App. Total Right Thru Left Peds App. Total Right Thru Left Peds App. Total Int. Total
Peak Hour Analysis From 08:45 PM to 10:30 PM - Peak 1 of 1Peak Hour for Entire Intersection Begins at 08:45 PM
08:45 PM 5 38 0 14 57 7 0 10 18 35 2 39 36 12 89 0 0 0 15 15 19609:00 PM 48 42 3 22 115 10 0 36 26 72 0 51 41 28 120 0 0 0 8 8 315
09:15 PM 45 40 2 21 108 17 0 38 32 87 0 52 38 24 114 0 0 0 4 4 31309:30 PM 40 50 1 15 106 11 0 38 5 54 2 39 23 6 70 0 0 0 5 5 235
Total Volume 138 170 6 72 386 45 0 122 81 248 4 181 138 70 393 0 0 0 32 32 1059% App. Total 35.8 44 1.6 18.7 18.1 0 49.2 32.7 1 46.1 35.1 17.8 0 0 0 100
PHF .719 .850 .500 .818 .839 .662 .000 .803 .633 .713 .500 .870 .841 .625 .819 .000 .000 .000 .533 .533 .840
Georgia Avenue NW and Greshem Place NW
File Name : Georgia and GershimSite Code : 00000444Start Date : 9/10/2014Page No : 8
Georgia Avenue
Gre
shem
Pla
ce G
resh
em
Pla
ce
Georgia Avenue
Right138
Thru170
Left6
Peds72
InOut Total226 386 612
Rig
ht
45
Thru0
Left
122
Peds81
Out
Tota
lIn
10
248
258
Left138
Thru181
Right4
Peds70
Out TotalIn292 393 685
Left0
Thru
0
Rig
ht0
Peds32
Tota
lO
ut
In276
32
308
Peak Hour Begins at 08:45 PM All VehiclesHeavy VehiclesBicycles
Peak Hour Data
North
Georgia Avenue NW and Greshem Place NW
File Name : Georgia and GershimSite Code : 00000444Start Date : 9/10/2014Page No : 9
Georgia Avenue NW and Greshem Place NW
File Name : Barry and ShermanSite Code : 00000222Start Date : 9/17/2014Page No : 1
Groups Printed- All Vehicles - Heavy Vehicles - BicyclesSherman Avenue
From NorthBarry PlaceFrom East
Sherman AvenueFrom South
Barry PlaceFrom West
Start Time Right Thru Left Peds App. Total Right Thru Left Peds App. Total Right Thru Left Peds App. Total Right Thru Left Peds App. Total Int. Total
03:00 PM 3 80 2 4 89 4 4 5 3 16 8 86 18 1 113 12 7 1 8 28 24603:15 PM 1 99 3 1 104 4 6 9 0 19 7 92 9 2 110 12 4 3 11 30 26303:30 PM 4 90 3 4 101 4 7 8 5 24 8 91 9 0 108 10 9 2 14 35 26803:45 PM 6 96 1 1 104 4 5 9 4 22 9 100 13 1 123 19 6 2 4 31 280
Total 14 365 9 10 398 16 22 31 12 81 32 369 49 4 454 53 26 8 37 124 1057
04:00 PM 2 102 5 0 109 4 6 10 5 25 6 98 8 2 114 17 4 7 10 38 28604:15 PM 1 103 2 2 108 4 9 4 5 22 12 97 15 4 128 8 8 1 9 26 28404:30 PM 3 89 5 4 101 1 4 10 3 18 13 80 11 2 106 18 7 1 5 31 25604:45 PM 1 66 0 0 67 2 9 10 0 21 17 72 6 0 95 12 10 4 0 26 209
Total 7 360 12 6 385 11 28 34 13 86 48 347 40 8 443 55 29 13 24 121 1035
Grand Total 21 725 21 16 783 27 50 65 25 167 80 716 89 12 897 108 55 21 61 245 2092Apprch % 2.7 92.6 2.7 2 16.2 29.9 38.9 15 8.9 79.8 9.9 1.3 44.1 22.4 8.6 24.9
Total % 1 34.7 1 0.8 37.4 1.3 2.4 3.1 1.2 8 3.8 34.2 4.3 0.6 42.9 5.2 2.6 1 2.9 11.7All Vehicles 14 699 21 16 750 27 46 61 25 159 77 696 84 12 869 102 47 14 61 224 2002
% All Vehicles 66.7 96.4 100 100 95.8 100 92 93.8 100 95.2 96.2 97.2 94.4 100 96.9 94.4 85.5 66.7 100 91.4 95.7Heavy Vehicles 7 23 0 0 30 0 3 4 0 7 3 16 2 0 21 6 8 7 0 21 79% Heavy Vehicles 33.3 3.2 0 0 3.8 0 6 6.2 0 4.2 3.8 2.2 2.2 0 2.3 5.6 14.5 33.3 0 8.6 3.8
Bicycles 0 3 0 0 3 0 1 0 0 1 0 4 3 0 7 0 0 0 0 0 11% Bicycles 0 0.4 0 0 0.4 0 2 0 0 0.6 0 0.6 3.4 0 0.8 0 0 0 0 0 0.5
Sherman Ave NW and Barry Pl NW Intersection
File Name : Barry and ShermanSite Code : 00000222Start Date : 9/17/2014Page No : 2
Sherman Avenue
Barr
y P
lace
Barry P
lace
Sherman Avenue
Right
14 7 0
21 Thru
699 23 3
725 Left
21 0 0
21 Peds
16 0 0
16
InOut Total737 750 1487 23 30 53 4 3 7
764 1547 783
Rig
ht
27
0
0
27
Thru 4
6
3
1
50
Left 61
4
0
65
Peds 25
0
0
25
Out
Tota
lIn
145
159
304
11
7
18
0
1
1
156
323
167
Left84 2 3
89
Thru696 16 4
716
Right77 3 0
80
Peds12 0 0
12
Out TotalIn
862 869 1731 33 21 54 3 7 10
898 1795 897
Left14
7
0
21
Thru4
7
8
0
55
Rig
ht
102
6
0
108
Peds61
0
0
61
Tota
lO
ut
In144
224
368
12
21
33
4
0
4
160
405
245
9/17/2014 03:00 PM9/17/2014 04:45 PM All VehiclesHeavy VehiclesBicycles
North
Sherman Ave NW and Barry Pl NW Intersection
File Name : Barry and ShermanSite Code : 00000222Start Date : 9/17/2014Page No : 3
Sherman AvenueFrom North
Barry PlaceFrom East
Sherman AvenueFrom South
Barry PlaceFrom West
Start Time Right Thru Left Peds App. Total Right Thru Left Peds App. Total Right Thru Left Peds App. Total Right Thru Left Peds App. Total Int. Total
Peak Hour Analysis From 03:00 PM to 04:45 PM - Peak 1 of 1Peak Hour for Entire Intersection Begins at 03:30 PM
03:30 PM 4 90 3 4 101 4 7 8 5 24 8 91 9 0 108 10 9 2 14 35 26803:45 PM 6 96 1 1 104 4 5 9 4 22 9 100 13 1 123 19 6 2 4 31 28004:00 PM 2 102 5 0 109 4 6 10 5 25 6 98 8 2 114 17 4 7 10 38 28604:15 PM 1 103 2 2 108 4 9 4 5 22 12 97 15 4 128 8 8 1 9 26 284
Total Volume 13 391 11 7 422 16 27 31 19 93 35 386 45 7 473 54 27 12 37 130 1118% App. Total 3.1 92.7 2.6 1.7 17.2 29 33.3 20.4 7.4 81.6 9.5 1.5 41.5 20.8 9.2 28.5
PHF .542 .949 .550 .438 .968 1.00 .750 .775 .950 .930 .729 .965 .750 .438 .924 .711 .750 .429 .661 .855 .977
Sherman Ave NW and Barry Pl NW Intersection
File Name : Barry and ShermanSite Code : 00000222Start Date : 9/17/2014Page No : 4
Sherman Avenue
Barr
y P
lace
Barry P
lace
Sherman Avenue
Right13
Thru391
Left11
Peds7
InOut Total414 422 836
Rig
ht
16
Thru2
7
Left31
Peds19
Out
Tota
lIn
73
93
166
Left45
Thru386
Right35
Peds7
Out TotalIn476 473 949
Left12
Thru2
7
Rig
ht
54
Peds37
Tota
lO
ut
In85
130
215
Peak Hour Begins at 03:30 PM All VehiclesHeavy VehiclesBicycles
Peak Hour Data
North
Sherman Ave NW and Barry Pl NW Intersection
File Name : Barry and ShermanSite Code : 00000222Start Date : 9/17/2014Page No : 5
Sherman Ave NW and Barry Pl NW Intersection
File Name : Girard and GeorgiaSite Code : 00000333Start Date : 10/9/2014Page No : 1
Groups Printed- All Vehicles - Heavy Vehicles - BicyclesSherman Avenue NW
From NorthGirard StreetFrom East
Sherman Avenue NWFrom South
Girard StreetFrom West
Start Time Right Thru Left Peds App. Total Right Thru Left Peds App. Total Right Thru Left Peds App. Total Right Thru Left Peds App. Total Int. Total
06:30 PM 2 62 0 4 68 7 8 5 5 25 0 78 3 5 86 2 1 3 3 9 18806:45 PM 4 82 1 5 92 6 5 6 1 18 0 81 2 4 87 1 0 2 0 3 200
Total 6 144 1 9 160 13 13 11 6 43 0 159 5 9 173 3 1 5 3 12 388
07:00 PM 4 92 0 8 104 2 6 5 4 17 0 80 3 2 85 2 1 3 1 7 21307:15 PM 1 76 2 1 80 5 6 5 5 21 0 93 1 7 101 3 0 3 1 7 20907:30 PM 4 98 0 5 107 1 6 4 2 13 0 80 2 0 82 2 1 4 2 9 21107:45 PM 1 72 0 2 75 4 5 4 3 16 0 72 3 4 79 1 1 3 2 7 177
Total 10 338 2 16 366 12 23 18 14 67 0 325 9 13 347 8 3 13 6 30 810
08:00 PM 2 68 0 2 72 5 5 6 0 16 0 63 1 1 65 3 3 3 1 10 16308:15 PM 7 65 0 5 77 9 9 4 1 23 0 62 2 0 64 3 0 0 2 5 169
Grand Total 25 615 3 32 675 39 50 39 21 149 0 609 17 23 649 17 7 21 12 57 1530Apprch % 3.7 91.1 0.4 4.7 26.2 33.6 26.2 14.1 0 93.8 2.6 3.5 29.8 12.3 36.8 21.1
Total % 1.6 40.2 0.2 2.1 44.1 2.5 3.3 2.5 1.4 9.7 0 39.8 1.1 1.5 42.4 1.1 0.5 1.4 0.8 3.7All Vehicles 25 615 3 32 675 39 50 39 21 149 0 609 17 23 649 17 7 21 12 57 1530
% All Vehicles 100 100 100 100 100 100 100 100 100 100 0 100 100 100 100 100 100 100 100 100 100Heavy Vehicles 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0% Heavy Vehicles 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
Bicycles 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0% Bicycles 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
Sherman Ave NW and Girard Street NW
File Name : Girard and GeorgiaSite Code : 00000333Start Date : 10/9/2014Page No : 2
Sherman Avenue NW
Girard
Str
eet
Gira
rd S
treet
Sherman Avenue NW
Right
25 0 0
25 Thru
615 0 0
615 Left
3 0 0 3
Peds
32 0 0
32
InOut Total669 675 1344
0 0 0 0 0 0
669 1344 675
Rig
ht
39
0
0
39
Thru 5
0
0
0
50
Left 39
0
0
39
Peds 21
0
0
21
Out
Tota
lIn
10
149
159
0
0
0
0
0
0
10
159
149
Left17 0 0
17
Thru609
0 0
609
Right0 0 0 0
Peds23 0 0
23
Out TotalIn
671 649 1320 0 0 0 0 0 0
671 1320 649
Left21
0
0
21
Thru
7
0
0
7
Rig
ht
17
0
0
17
Peds12
0
0
12
Tota
lO
ut
In92
57
149
0
0
0
0
0
0
92
149
57
10/9/2014 06:30 PM10/9/2014 08:15 PM All VehiclesHeavy VehiclesBicycles
North
Sherman Ave NW and Girard Street NW
File Name : Girard and GeorgiaSite Code : 00000333Start Date : 10/9/2014Page No : 3
Sherman Ave NW and Girard Street NW
File Name : U Street and 10th StreetSite Code : 00000111Start Date : 9/18/2014Page No : 1
Groups Printed- All Vehicles - Bicycles - Heavy Vehicles10th StreetFrom North
U StreetFrom East
U StreetFrom West
Start Time Right Left Peds App. Total Right Thru Peds App. Total Thru Left Peds App. Total Int. Total07:00 PM 10 2 4 16 10 11 7 28 19 1 14 34 7807:15 PM 14 4 22 40 8 17 24 49 23 3 32 58 14707:30 PM 12 6 22 40 30 44 46 120 53 3 26 82 24207:45 PM 24 5 45 74 36 69 96 201 49 2 40 91 366
Total 60 17 93 170 84 141 173 398 144 9 112 265 833
08:00 PM 12 8 20 40 29 55 59 143 19 5 25 49 23208:15 PM 7 1 12 20 6 30 20 56 26 4 12 42 11808:30 PM 10 1 5 16 4 22 5 31 17 2 5 24 7108:45 PM 7 4 4 15 2 21 9 32 15 3 4 22 69
Total 36 14 41 91 41 128 93 262 77 14 46 137 490
Grand Total 96 31 134 261 125 269 266 660 221 23 158 402 1323Apprch % 36.8 11.9 51.3 18.9 40.8 40.3 55 5.7 39.3
Total % 7.3 2.3 10.1 19.7 9.4 20.3 20.1 49.9 16.7 1.7 11.9 30.4All Vehicles 84 29 134 247 125 234 266 625 184 23 158 365 1237
% All Vehicles 87.5 93.5 100 94.6 100 87 100 94.7 83.3 100 100 90.8 93.5Bicycles 1 2 0 3 0 8 0 8 7 0 0 7 18
% Bicycles 1 6.5 0 1.1 0 3 0 1.2 3.2 0 0 1.7 1.4Heavy Vehicles 11 0 0 11 0 27 0 27 30 0 0 30 68
% Heavy Vehicles 11.5 0 0 4.2 0 10 0 4.1 13.6 0 0 7.5 5.1
U street and 10th street Intersection
File Name : U Street and 10th StreetSite Code : 00000111Start Date : 9/18/2014Page No : 2
10th Street
U S
treet
U S
treet
Right
84 1
11 96
Left
29 2 0
31 Peds
134 0 0
134
InOut Total148 247 395
0 3 3 0 11 11
148 409 261
Rig
ht
125
0
0
125
Thru
234
8
27
269
Peds
266
0
0
266
Out
Tota
lIn
213
625
838
9
8
17
30
27
57
252
912
660
Left23
0
0
23
Thru184
7
30
221
Peds
158
0
0
158
Tota
lO
ut
In318
365
683
9
7
16
38
30
68
365
767
402
9/18/2014 07:00 PM9/18/2014 08:45 PM All VehiclesBicyclesHeavy Vehicles
North
U street and 10th street Intersection
File Name : U Street and 10th StreetSite Code : 00000111Start Date : 9/18/2014Page No : 3
U street and 10th street Intersection
2014
Ephrem Woldetsadik
@02666435
10/17/2014
Parking Study
Parking Study
Objectives:
The objective of this study is to conduct a 2-hour parking study and provide the parking
characteristics at a selected location/block near an intersection.
Introduction/Background:
Parking studies must be conducted to collect the required information about the capacity
and use of existing parking facilities. In addition, information about the demand for parking is
needed. Parking studies may be restricted to a particular traffic producer or attractor, such as a
store, or they may encompass an entire region, such as a central business district (1).Before
parking studies can be initiated, the study area must be defined. A cordon line is illustrated to
outline the study area. It should include traffic generators and a periphery, including all points
within an appropriate walking distance (1). The boundary should be drawn to facilitate cordon
counts by minimizing the number of entrance and exit points.
Once the study area has been defined, there are several different types of parking studies
that may be required. These study types are listed below (1):
• Inventory of Parking Facilities
• Accumulation Counts
• Duration and Turnover Surveys
• User Information Surveys
• Land Use Method of Determining Demand
Inventory of Parking Facilities:
Information is collected on the current condition of parking facilities. This includes (1):
• The location, condition, type, and number of parking spaces.
• Parking rates if appropriate. These are often related to trip generation or other land use
considerations.
• Time limits, hours of availability and any other restrictions.
• Layout of spaces: geometry and other features such as crosswalks and city services.
• Ownership of the off-street facilities.
Accumulation Counts:
These are conducted to obtain data on the number of vehicles parked in a study area
during a specific period of time (1). First, the number of vehicles already in that area are counted
or estimated. Then the number of vehicles entering and exiting during that specified period are
noted, and added or subtracted from the accumulated number of vehicles (1). Accumulation data
are normally summarized by time period for the entire study area. The occupancy can be
calculated by taking accumulation/total spaces (1). Peaking characteristics can be determined by
graphing the accumulation data by time of day (1). The accumulation graph usually includes
cumulative arrival and cumulative departure graphs as well.
Duration and Turnover Surveys:
The accumulation study does not provide information on parking duration, turnover or
parking violations. This information requires a license plate survey, which is often very
expensive. Instead, modifications are often made to the field data collection protocols (1). In
planning a license plate survey, assume that each patrolling observer can check about four spaces
per minute (1). The first observer will be slower, because all the license plate numbers will have
to be recorded, but subsequent observers will be able to work much faster (1).
Parking turnover is the rate of use of a facility. It is determined by dividing the number of
available parking spaces into the number of vehicles parked in those spaces in a stated time
period (1).
User Information Surveys:
Individual users can provide valuable information that is not attainable with license plate
surveys. The two major methods for collecting these data are parking interviews and postcard
studies. For the parking interviews, drivers are interviewed right in the parking lot. The
interviews can gather information about origin and destination, trip purpose, and trip frequency.
The postage paid postcard surveys requests the same information as in the parking interview.
Return rates average about 35%, and may include bias. The bias can take two forms. Drivers will
sometimes overestimate their parking needs in order to encourage the surveyors to recommend
additional parking. Or, they may file false reports that they feel are more socially acceptable.
Land Use Method of Determining Demand:
Parking generation rates can be used to estimate the demand for parking (1):
• Tabulate the type and intensity of land uses throughout the study area.
• Based on reported parking generation rates, estimate the number of parking spaces
needed for each unit of land use.
• Determine the demand for parking from questionnaires. A rule of thumb is to
overestimate the demand for parking by about 10 %. If the analysis suggests that the
parking demand for a particular facility will be 500 spaces, then the design should be for
550 spaces.
Scope:
The parking study was conducted on westbound and eastbound block of Barry Pl NW
near the intersection of Sherman Ave NW & Barry Pl NW (Figures 1 and 2). The study
composed of parking: accumulation, duration, and turnover. The location is surrounded with bus
stops, Howard University, college dorms, and private parking lots. The eastbound block of Barry
Pl NW permits on-street parking to the public except Tuesday from 7am to 7pm March 1 through
October 31 but permitted on holidays (figures 1 and 3). The westbound block of Barry Pl NW
permits on-street parking to the public except Tuesday from 9:30am to 11:30am March 1 through
October 31 but permitted on holidays. In addition, there’s no parking/standing between 4pm to
10pm Monday thru Friday (figures 2 and 4).
Figure 1: Street View of Barry Place NW going Eastbound Figure 2: Street View of Barry Place NW going Westbound
Methodology and Data Collection:
The parking study data was collected on westbound and eastbound block of Barry Pl NW
near the intersection of Sherman Ave NW & Barry Pl NW for 2 hours on Thursday, October 16,
2014 from 1pm to 3pm. Observation was required for both on-street parking blocks. There were
two vehicles parked on the westbound on-street parking and five vehicles for the eastbound on-
street parking. Within the 2 hour frame window, the vehicles parked remained the same position
and no new vehicles occupied the westbound parking spaces. Since all the parking spaces for the
eastbound were occupied, the westbound parking still had five vacant spaces during the 2 hour
parking study.
Figure 3: Barry Place NW Eastbound parking sign Figure 4: Barry Place NW Westbound parking sign
Results:
Using Microsoft Excel, the parking characteristics: accumulation, turnover, and duration are provided below:
Intersections Vehicles parked Total Parking
Space
Turnover Accumulation
1pm C 12 0.58 7
2pm C 12 0.58 7
3pm B 12 0.58 7
Car No. Duration
(hr)
1 2
2 2
3 2
4 2
5 2
6 2
7 2
Conclusion/ Recommendations:
During the 2- hour parking study, no changes occurred with vehicles arriving or leaving
the parking spaces. A recommendation for this study would be have a longer time frame of
collecting parking data. It will provide a better result of actually parking studies, demands, etc.
References
1. Parking Studies." Parking Studies. Web. 17 Oct. 2014.
<http://www.webpages.uidaho.edu/niatt_labmanual/Chapters/parkinglotdesign/theoryandconcepts/Parki
ngStudies.htm>. 2. Lecture 3: Traffic Engineering Studies, Dr. Stephen
Arhin; https://blackboard.howard.edu/bbcswebdav/pid-1583208-dt-content-rid-
2711760_1/courses/CIEG46501201408/Traffic-Engineering-Studies%20-%20Lecture%204.pdf
Accessed Oct.16, 2014.
2014
Ephrem Woldetsadik
@02666435
12/9/2014
Signal Timing and Phasing Study
Signal Timing and Phasing Study
Objectives:
The objective of this study is to conduct signal timing and phasing studies at 2 signalized
intersections.
Introduction/Background:
Traffic signal timing is one of the important factors in traffic signal. The goal of signal
timing is to maintain a safe and efficient transfer of right-of- way between complementary and
competing traffic demands at intersections (1). Signal timing is typically designed, implemented
and maintained by the agency with operational authority over the intersection (1). Traffic signal
controllers are designed to maintain a safe and constant flow of traffic at intersections by issuing
a proper green time from for each intersection approach. Traffic signals can be traced back to
London as early as 1868 (2). United States first developed a traffic signal to prevent accidents by
alternatively assigning right of way but now it has significantly and there are over 272,000 traffic
signals (2). Traffic signals are a major role in today’s transportation network and are a source for
traveling throughout in a safely and organized way. Traffic signals provide the following
benefits (2):
1. Provide for the orderly and efficient movement of people.
2. Effectively maximize the volume movements served at the intersection.
3. Reduce the frequency and severity of certain types of crashes.
4. Provide appropriate levels of accessibility for pedestrians and side street traffic.
An unreliably designed signal timing plan may make the intersection less efficient, less
safe, or both. Signal timing will go through a phase, ring, and cycle length. A phase is when
vehicles in a certain approach are allotted time to a movement. A ring is a sequence of phases
that a signal light goes through; green phase, red phase, yellow phase, and all-red phase. A cycle
length is the time from one major green phase to the next green phase in the same signal and it is
determined by the equation C= G+ R+Y+AR. The cycle time is typically 45-180s.
Figure 1: Street View Intersection of 10th Street NW & U Street NW
Scope:
The study was to conduct signal timing and phase study at the 2 signalized intersections,
10th Street NW & U Street NW (Figure 1), and Sherman Ave NW & Barry Pl NW (Figure 2).
The study composed of gathering the time for each phase a signalized intersection goes through a
cycle. During the cycle, the time for each light, Green, Yellow, Red, and All Red, are collected
and used to determine the cycle length for each approach phase. The phase study is gathered by
illustrating the direction that a vehicle can travel given by the signal lights and this will
determine whether the direction the vehicle can travel will be permissive or protected during the
phase. The intersection 10th Street NW & U Street NW is surrounded by local restaurants, bus
stops, CVS store, U Metro Station, and a middle school. The intersection Sherman Ave NW &
Barry Pl NW is surrounded by bus stops, Howard University, and college dorms.
Methodology and Data Collection:
The signal timing and phase studies for both signalized intersections were conducted on
November 20, 2014 from 7:30pm to 8:15pm. To determine the phase studies for both
intersections, the approach directions must be determined initially. Then, observe the
intersections through each phase to determine whether the phases contained a permissive phase,
protected phase, or pedestrian phase. To collect the signal timing data, a stopwatch is needed. An
observation of the cycle length for each intersection is completed to determine the length of time
Figure 2: Street View Intersection of Sherman Ave NW & Barry Pl NW
for each light during its phases. This process is repeated 5 times for each phase to collect a more
accurate time data for each light. Once the times for each light (Green, Yellow, Red, All Red) is
collected, the cycle length for each phases of the intersections can be concluded by taking the
average time of the green light, yellow light, and red light of each phases and insert them into the
cycle length equation. See raw data attachment.
Analysis of Result:
To calculate the cycle length time, the equation = + + + , where C= total
time in seconds from a green phase to a green phase on an approach, G= average green light time
for a phase, R = average red light time for a phase, Y= average yellow light time for a phase, and
AR= all red light time for the signalized intersection, was used.
Sherman Ave NW & Barry
Pl NW
Phase 1 Average Time
(North bound & South bound)
Phase 2 Average Time
(East bound & West bound)
Green light (sec) 40.26 28.73
Yellow light (sec) 3.97 3.63
Red light (sec) 35.94 47.3
All Red (sec) 2 2
Cycle length (sec) 82.17 81.66
10th Street NW & U Street
NW
Phase 1 Average Time
(East bound & West Bound)
Phase 2 Average Time
(South bound)
Green light (sec) 47.87 22.39
Yellow light (sec) 3.59 3.67
Red light (sec) 27.79 48.64
All Red (sec) 2 2
Cycle length (sec) 81.25 76.7
Conclusion/ Recommendations:
The signal timing cycle length of Sherman Ave NW & Barry Pl NW for north bound and
south bound is 82.17 seconds and for east bound and west bound was 81.66 seconds. Also, the
cycle length of 10th street NW & U street NW for east bound and west bound is 81.25 and for
south bound was 76.7. The phase study for each signalized intersection is illustrated on the raw
data attachment.
References
1. "Traffic Signal Timing & Operations Strategies." Federal Highway Administration. Federal
Highway Administration, 1 Jan. 2014. Web. 9 Dec. 2014.
<http://ops.fhwa.dot.gov/arterial_mgmt/tst_ops.htm>.
2. “TRAFFIC SIGNAL TIMING MANUAL." Federal Highway Administration. Federal
Highway Administration, 1 June 2008. Web. 9 Dec. 2014.
<http://www.signaltiming.com/The_Signal_Timing_Manual_08082008.pdf>.
2014
Ephrem Woldetsadik
@02666435
12/9/2014
LEVEL OF SERVICE
Level of Service (LOS)
Objectives:
The objective of this study is to conduct a Level of Service (LOS) at the 4 intersections
using HCS and Synchro.
Introduction/Background:
Level of Service (LOS) measures the average delay time of all the movements at an
intersection. LOS can be used to roughly estimate a driver’s discomfort, frustration, and lost
travel time. LOS is used to design or to analyze an intersection, and is typically completed using
the guidelines specified in the Highway Capacity Manual (HCM). A LOS grade represents the
quality of the traffic operational conditions experienced by the user of the facility. The Highway
Capacity Manual (HCM) defines LOS for freeways and multilane highways in 6 different
categories:
• LOS A: free-flow conditions where individual drivers are unaffected by the presence of
other vehicle in the traffic stream. The freedom to select desired speeds and maneuver is very
high with excellent comfort and convenience degree for the user.
• LOS B: allows speeds near to LOS A but presence of other users in the traffic stream will
be noticeable. Desired speed is unaffected but maneuver is slightly affected.
• LOS C: speed neat to free-flow speed. Maneuver is noticeably restricted and incident like
disablement may cause in significant backed up delay however causing minor delay.
• LOS D: speed begins to decline with increasing flow. Comfort level declines
significantly with restricted maneuvers. Incidents can be a lengthy stretch in traffic delay.
• LOS E: Operating to the roadway’s capacity. Minor disruptions will cause long delays.
Maneuvering is extremely limited with discomfort experience.
• LOS F: A total breakdown of the traffic flow. Queues form quickly and delay times are
very long. Complete stops and long queues are more likely (1).
The Level of Service (LOS) is a measure used by traffic engineers to determine the
effectiveness of transportation infrastructures. It can be applied to highways, intersections,
transit, portable water, sanitary sewer service, solid waste removal, drainage, and public open
space and recreation facilities. Level of service is given on a scale from A-F with A being the
highest and F being the lowest. Level of service is often used at signalized intersections. For
example, an intersection in which traffic movements produce conflicting turns might yield a
level of service of D or E. The level of service here approaches an unstable flow and fluctuations
in volume and temporary restrictions cause a substantial drop in the operating speed.
Level of service was first developed for highways in an era that experienced rapid
expansion in the use and availability of the private motor car. The primary concern was
congestion, and it was commonly held that only the rapid expansion of the freeway network
would mitigate congestion. Since this time, levels of service have been modified to take into
account public transportation as well. Most urban areas will receive a level of service of F
because stoppages occur for short or long periods of time due to downstream congestion.
However, these locations are typically still operational due to improved pedestrian, bicycle, or
transit alternatives. Most level of service standards call for roads to be widened to help improve
LOS grades; however, this may not always be feasible. Because of this some planners
recommend increasing population density in towns, narrowing streets, managing car use in some
areas, providing sidewalks and safe pedestrian and bicycle facilities, and increased beautification
of the area (2).
Scope:
The LOS study was conducted for the 4 intersections in Washington D.C.; 10th street
NW & U Street NW (Figures 1), Sherman Ave NW & Barry Pl NW (Figures 2), Sherman Ave
NW & Girard Street NW (Figures 3), and Georgia Ave NW & Gresham Pl NW (Figures 4).
Figure 1: Street view of 10th street at U street NWFigure 2: Street view of Sherman Ave NW at Barry Pl NW
Methodology and Data Collection:
The LOS data for all 4 intersections were obtained by HCS and Synchro on December 5,
2014. Highway Capacity Software (HCS) implements the procedures defined in the Highway
Capacity Manual for analyzing capacity and determining level of service for Signalized
Intersections, Unsignalized Intersections, Urban Streets, Freeways, Weaving Areas, Ramp
Junctions, Multilane Highways, Two-Lane Highways and Transit (3). Synchro is a software
application for optimizing traffic signal timing and performing capacity analysis (4). The
software improves splits, offsets, and cycle lengths for individual intersections, an arterial, or a
complete network and it also provides detailed time space diagrams that can show vehicle paths
or bandwidths (4). To use Synchro, pervious data from all 4 intersections must be provided for
the software. They are Turning Movement Count data and the Condition Diagram measurements.
Synchro can now provide the data that can be transferred to HCS and HCS will provide the LOS
data automatically.
Figure 3: Street view of Sherman Ave NW at Girard Street NWFigure 4: Street view Aerial View of Georgia Ave NW at Gresham Pl NW
Synchro simulation view of Georgia Ave NW at Gresham Pl NW
Synchro simulation view of Sherman Ave NW at Barry Pl NW
Synchro simulation view of U Street NW at 10 Street NW
Synchro simulation view of Sherman Ave NW and Girard Street
Analysis of Result:
See attachments.
Conclusion/ Recommendations:
All Level of Service for the 4 intersections are provided in the HCS and Synchro report
attachments.
References
1. https://engineering.purdue.edu/~flm/CE%20361_files/chapter6_notes_.pdf. Accessed
date 11/04/2014
2. Scorsone, T. Florida Deparment of Transporataiton, (2009). 2009
quality/level of service handbook . Retrieved from website:
http://www.dot.state.fl.us/planning/systems/sm/los/
3. Mctran. University of Flordia, 1 Jan. 2014. Web. 9 Dec. 2014.
<http://mctrans.ce.ufl.edu/hcs/hcs2000/>.
4. "Product Overview." Trafficware. Trafficware, 1 Jan. 2003. Web. 9 Dec. 2014.
<http://trafficware.infopop.cc/synchro.htm>.