Traffic Studies Final Report

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

http://www.cts.cv.ic.ac.uk/documents/poster/poster00845.pdf



http://en.wikipedia.org/wiki/Imperial_College_London

http://www.ctre.iastate.edu/pubs/traffichandbook/3trafficcounts.pdf

https://blackboard.howard.edu/bbcswebdav/pid-1571822-dt-content-rid

https://blackboard.howard.edu/bbcswebdav/pid-1571822-dt-content-rid

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.


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.


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


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.


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.

https://blackboard.howard.edu/webapps/blackboard/content/listContent.jsp?course_id=_1037101_1&content_id=_1530770_1&mode=reset

https://blackboard.howard.edu/webapps/blackboard/content/listContent.jsp?course_id=_1037101_1&content_id=_1530770_1&mode=reset

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.


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.


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


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 (%

)


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 (%

)


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.


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


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.


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


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 AvenueFrom North

Greshem PlaceFrom East

Georgia AvenueFrom South

Greshem PlaceFrom West


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

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









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


PHF .719 .850 .500 .818 .839 .662 .000 .803 .633 .713 .500 .870 .841 .625 .819 .000 .000 .000 .533 .533 .840



Georgia Avenue

Gre

shem

Pla

ce G

resh

em

Pla

ce

Georgia Avenue

Right138

Thru170

Left6

Peds72


Rig

ht

45

Thru0

Left

122

Peds81

Out

Tota

lIn

10

248

258

Left138

Thru181

Right4

Peds70


Left0

Thru

0

Rig

ht0

Peds32

Tota

lO

ut

In276

32

308


Peak Hour Data

North









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


PHF .719 .850 .500 .818 .839 .662 .000 .803 .633 .713 .500 .870 .841 .625 .819 .000 .000 .000 .533 .533 .840



Georgia Avenue

Gre

shem

Pla

ce G

resh

em

Pla

ce

Georgia Avenue

Right138

Thru170

Left6

Peds72


Rig

ht

45

Thru0

Left

122

Peds81

Out

Tota

lIn

10

248

258

Left138

Thru181

Right4

Peds70


Left0

Thru

0

Rig

ht0

Peds32

Tota

lO

ut

In276

32

308


Peak Hour Data

North




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


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


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


North



Sherman AvenueFrom North

Barry PlaceFrom East

Sherman AvenueFrom South

Barry PlaceFrom West



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 Avenue

Barr

y P

lace

Barry P

lace

Sherman Avenue

Right13

Thru391

Left11

Peds7


Rig

ht

16

Thru2

7

Left31

Peds19

Out

Tota

lIn

73

93

166

Left45

Thru386

Right35

Peds7


Left12

Thru2

7

Rig

ht

54

Peds37

Tota

lO

ut

In85

130

215


Peak Hour Data

North




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


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


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


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


North




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


10th Street

U S

treet

U S

treet

Right

84 1

11 96

Left

29 2 0

31 Peds

134 0 0

134


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




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.


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


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


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.

https://blackboard.howard.edu/bbcswebdav/pid-1583208-dt-content-rid-2711760_1/courses/CIEG46501201408/Traffic-Engineering-Studies%20-%20Lecture%204.pdf

https://blackboard.howard.edu/bbcswebdav/pid-1583208-dt-content-rid-2711760_1/courses/CIEG46501201408/Traffic-Engineering-Studies%20-%20Lecture%204.pdf

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.


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.


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)


(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


(East bound & West Bound)


(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


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.


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


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.


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>.

Traffic Studies Final Report

Documents