Congestion management is the use of strategies to optimize operations of a transportation system through management of the existing system. As such, a congestion management process (CMP) is a systematic approach coordinated regionally that provides current performance measures detailing the system performance and evaluates strategies that meet the local objectives.

CONGESTION MANAGEMENT PROCESS (CMP)
REPORT
Final Report
2015
Prepared for:
Northwest Arkansas
Regional Planning
Commission
1311 Clayton Street
Springdale, AR 72632
Prepared by:
Co-PLAN
5508 Sandalwood Drive
McKinney, Texas 75070
Highway 265 Access Management Plan – AHTD, NWARPC, and the City of Fayetteville
In Association with:
Texas A&M
Transportation Institute
May 22, 2015
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CoPLAN
ACKNOWLEDGEMENTS
Northwest Arkansas Regional Planning Commission
Agency Representative
Avoca Jordan W. Sullivan
Beaver Water District Alan Fortenberry
Bella Vista Peter Christie
Benton County Bob Clinard
Benton County John Sudduth
Bentonville Bob McCaslin
Bentonville Shelli Kerr
Bentonville Troy Galloway
Bethel Heights Cynthia J. Black
Cave Springs Travis Lee
Centerton Bill Edwards
Decatur Bob Tharp
Elkins Bruce Ledford
Elm Springs Harold D. Douthit
Farmington Ernie Penn
Fayetteville Lioneld Jordan
Fayetteville Matthew Petty
Fayetteville Jeremy Pate
Garfield Gary L. Blackburn
Gateway Frank Hackler
Gentry Kevin Johnston
Goshen Joe Benson
Gravette Kurt Maddox
Greenland Bill Groom
Highfill Cassie Elliott
Hindsville X Dotson
Huntsville Kevin Hatfield
Johnson Chris Keeney
Lincoln Rob Hulse
Little Flock Buddy Blue
Lowell Eldon Long
Pea Ridge Jackie Crabtree
Prairie Grove Sonny Hudson
Rogers Greg Hines
Rogers Bob Crafton
Rogers Steve Glass
Siloam Springs John Turner
Siloam Springs Ben Rhoads
Springdale Doug Sprouse
Springdale Patsy Christie
Springdale Jim Ulmer
Springtown Preston Barrett
Sulphur Springs Greg Barber
Tontitown Paul Colvin, Jr.
Washington County Marilyn Edwards
Washington County Juliet Richey
Washington County Dan Short
West Fork Charlie Rossetti
Razorback Transit Gary Smith
Ozark Regional Transit ORT Board Chair
University of Arkansas Mike Johnson
AHTD – Districts Chad Adams
AHTD – Planning Jessie Jones
MODOT Laurel McKean
McDonald County, MO Keith Lindquist
Pineville, MO Greg Sweeten
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The contents of this report reflect the views of the preparers who are responsible for the
opinions, findings, and conclusions herein. The contents do not necessarily reflect the
views or policies of the Federal Highway Administration, Federal Transit Administration,
Missouri Department of Transportation, or the Arkansas State Highway and
Transportation Department.
NORTHWEST ARKANSAS REGIONAL PLANNING COMMISSION NOTICE OF
NONDISCRIMINATION
The Northwest Arkansas Regional Planning Commission (NWARPC) complies with
all civil rights provisions of federal statues and related authorities that prohibit
discrimination in programs and activities receiving federal financial assistance.
Therefore, the NWARPC does not discriminate on the basis of race, sex, color, age,
national origin, religion or disability, in the admission, access to and treatment in
NWARPC’s programs and activities, as well as the NWARPC’s hiring or
employment practices. Complaints of alleged discrimination and inquiries
regarding the NWARPC’s nondiscrimination policies may be directed to Celia
Scott-Silkwood, AICP, Regional Planner – EEO/DBE (ADA/504/TitleVI Coordinator),
1311 Clayton, Springdale, AR 72762, (479) 751-7125, (Voice/TTY 7-1-1 or 1-800-285-
1131) or the following email address: cscott-silkwood@nwarpc.org. This notice is
available from the ADA/504/Title VI Coordinator in large print, on audiotape and in
Braille. If information is needed in another language, contact Celia Scott-Silkwood.
Si necesita informacion en otro idioma, comuniqese Celia Scott-Silkwood, cscott-
silkwood@nwarpc.org.
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Table of Contents
Page No.
EXECUTIVE SUMMARY ……………………………………………………………………………………………… 1
INTRODUCTION ………………………………………………………………………………………………………… 7
HISTORY OF THE CONGESTION MANAGEMENT PROCESS …………………………………………. 7
WHAT IS THE CONGESTION MANAGEMENT PROCESS? ……………………………………………… 7
1.0 Action 1 – Develop Regional Objective for Congestion Management …………………………… 8
2.0 Action 2 – Define CMP Network …………………………………………………………………………….. 9
3.0 Action 3 – Develop Multimodal Performance Measures……………………………………………. 13
3.1 Traffic Flow ……………………………………………………………………………………………….. 13
3.2 Congestion Index (CI) and Volume Delay per Mile ………………………………………….. 13
4.0 Action 4 – Collect Data / Monitor System Performance ……………………………………………. 15
5.0 Action 5 – Analyze Congestion Problems and Needs ………………………………………………. 23
5.1 Roadway Segment Definition ………………………………………………………………………. 23
5.2 Data Reduction………………………………………………………………………………………….. 23
5.3 Data Formatting …………………………………………………………………………………………. 23
5.4 Multimodal Analysis ……………………………………………………………………………………. 24
6.0 Action 6 – Identify and Assess CMP Strategies ………………………………………………………. 27
6.1 Congestion Results ……………………………………………………………………………………. 27
6.2 Recommendations …………………………………………………………………………………….. 30
7.0 Action 7 – Program and Implement CMP Strategies ………………………………………………… 34
8.0 Action 8 – Evaluate Strategy Effectiveness ……………………………………………………………. 34
CONCLUSION ………………………………………………………………………………………………………….. 36
Appendix A Detailed Conflation and Traffic Volume Estimation Procedures
Appendix B 2013 Intersection Segment Results
Appendix C Congested Segments Ranked by Functional Class (Top 15%)
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List of Tables
Page No.
Table E-1 – Top 20 Congested Segments ………………………………………………………………………. 4
Table 1 – Top 20 Congested Segments ………………………………………………………………………… 29
List of Figures
Page No.
Figure E-1 – NWARPC Metropolitan Planning Area (MPA) ………………………………………………… 2
Figure E-2 – Top 20 Congested Segments ……………………………………………………………………… 5
Figure E-3 – Highway 265 Access Management Plan ……………………………………………………….. 6
Figure 1 – 2015 CMP Network …………………………………………………………………………………….. 11
Figure 2 – 2015 CMP Segments ………………………………………………………………………………….. 12
Figure 3 – Preserved Segments …………………………………………………………………………………… 13
Figure 4 – INRIX Data Collection Process ……………………………………………………………………… 17
Figure 5 – Subset of 2013 INRIX XD Dataset Coverage ………………………………………………….. 19
Figure 6 – Speed Limits ……………………………………………………………………………………………… 21
Figure 7 – School Zones …………………………………………………………………………………………….. 22
Figure 8 – Intersection Control …………………………………………………………………………………….. 23
Figure 9 – Peak Period Congestion Results …………………………………………………………………… 26
Figure 10 – Congested Segments by Functional Class ……………………………………………………. 27
Figure 11 – Top 20 Congested Segments ……………………………………………………………………… 30
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EXECUTIVE SUMMARY
Congestion management is the use of strategies to optimize operations of a
transportation system through management of the existing system. As such, a
congestion management process (CMP) is a systematic approach coordinated regionally
that provides current performance measures detailing the system performance and
evaluates strategies that meet the local objectives.
By definition, the CMP is not to be a
stand-alone study and is to be an
integral component of the metropolitan
transportation planning process. Once
an MPO exceeds a population of
200,000, the Moving Ahead for
Progress in the 21 st Century Act (Map-
21) requires a CMP, while not strictly
stating the methodology or approach
that is to be followed.
The flexibility is intentional within the
regulations to allow the MPO to
develop a living methodology that
evolves with the local objectives and
needs.
NWARPC is the designated
Metropolitan Planning Organization
(MPO) for the region. In 2012, the
region was designated as a
Transportation Management Area
(TMA) based on the 2010 U.S. Census
urbanized area exceeding 200,000 in
population. The NWARPC Metropolitan Planning Area (MPA) includes all of Washington
and Benton County in Arkansas and a portion of McDonald County/City of Pineville in
Missouri. The Current MPA boundary is shown in Figure E-1 (Page 4).
By responding to congestion through a process that involves developing congestion
management objectives, developing performance measures to support these objectives,
collecting data, analyzing problems, identifying solutions, and evaluating the
effectiveness of implemented strategies, the CMP provides a structure for responding to
congestion in a consistent, coordinated fashion.
The CMP, as defined in the federal
register, is intended to serve as a
systematic process that provides for
safe and effective integrated
management and operation of the
multimodal transportation system. The
process includes:
 Development of congestion
management objectives
 Establishment of measures of
multimodal transportation
system performance
 Collection of data and system
performance monitoring to
define the extent and duration of
congestion and determine the
causes of congestion
 Identification of congestion
management strategies
 Implementation activities,
including identification of an
implementation schedule and
possible funding sources for
each strategy
 Evaluation of the effectiveness of
implemented strategies
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McDonald Co., MO
Benton County, AR
Washington County, AR
Figure E-1 – NWARPC Metropolitan Planning Area (MPA)
The Northwest Arkansas Regional Planning Commission (NWARPC) is developing its’
inaugural congestion management process (CMP) to monitor the transportation network
in the Metropolitan Planning Area. The study area includes Benton and Washington
Counties in Arkansas and a portion of McDonald County/City of Pineville in Missouri.
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The goal of the monitoring system is to ensure optimal performance of the transportation
system by identifying congested areas and related transportation deficiencies.
The primary purpose of the 2015 Congestion Management Process is to evaluate the
transportation system and prepare a report as part of the Congestion Management
Process (CMP) in compliance with the MAP-21, the Moving Ahead for Progress in the
21st Century Act. The secondary purpose of the study was to identify trends in
congestion and travel time in order to identify problem locations for possible
improvements.
Being the inaugural study, the MPO is establishing the baseline of existing congestion
for comparison in future years. To help establish the CMP network, the MPO staff
invited representatives of local agencies and units of government to a kick-off meeting in
June 12, 2014. The primary goal of the meeting was to have a CMP workshop to
provide an overview of the CMP objectives. This discussion was very helpful to those in
attendance to help guide the local approach for the inaugural CMP. The study network
includes 224.5 centerline miles of roadway spread over 13 different roadways divided
into 234 directional links bound by a traffic signal, stop sign, or major cross street. For
added functionality, each segment was assigned a jurisdiction (City / County) depending
on its location within the MPA boundaries. This attribute will allow the MPO and its
members to query data within the database for each respective jurisdiction.
The CMP is intended to use an objectives-driven, performance-based approach to
planning for the management of congestion. Through the use of congestion
management objectives and performance measures, the CMP provides a mechanism for
ensuring that investment decisions are made with a clear focus on desired outcomes.
The purpose of this study was to identify and quantify problem areas using private sector
data. The results of this study are used as factors in prioritizing needed improvements.
Through the use of private sector travel speed data, various performance measures are
calculated. This data provides the needed reference material to prepare
recommendations that are focused on the true cause of the congestion.
Private sector travel speed data was procured for the region which covered the vast
majority of the identified network. The CMP network roadways included arterials and
freeways. Segment delay for vehicles was recorded within the defined segmentation
and compared with criteria in the Highway Capacity Manual (HCM). In order to
differentiate between congested roadways and roadways with low speed limits, various
performance measures for illustrating the data were introduced. The preferred
performance measure as determined by the CMP Committee, made of member of the
Technical Advisory Committee (TAC) is composed of two parts. The first element is
delay as compared to the posted speed limit. The second element begins with the link
daily volumes as provided by AHTD. By applying the vehicle volumes to the measured
delays on the links, the volume delay was determined. The CMP segments vary in
length across the board between those on arterials and freeways. In order to
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standardize the results and allow direct comparison across the network, the volume-
delay results were divided by the length. This provides a result with the units, vehicle-
hours of delay per road mile, thus allowing a more direct comparison among segments.
As a result, the preferred performance measure was determined and used to identify the
operating results of each link of the CMP network.
Of the 242 directional miles studied in the morning peak and afternoon peak periods, it
was determined to classify the top 15% of the segments as congested including both the
results of the AM and PM periods. In discussions with the Committee, the AM period
was defined as 7-9 AM. while the PM. period was described as 4:30-6:30 PM. Table E-
1 and Figure E-2 below shows the Top 20 congested segments in this study based on
the volume-delay per mile performance measure for both the AM and PM peak period.
This results in some segments being classified as “congested” for both periods.
One of the biggest benefits of the CMP is a structured, transparent process for effective
allocation of limited transportation funding among operations and capital projects and
programs. It also highlights travel demand management and operations strategies that
historically may not have been a focus of metropolitan transportation planning. Through
an integrated congestion monitoring system, decision-makers are provided with system
performance and the effectiveness of potential solutions as well as the results of
implemented strategies.
Table E-1-Top 20 Congested Segments
Top 20
Rank
(Art/Fwy) SegmentId Route Segment Name
Time
Period
Func
Class City
Length
(mi)
Weighted
Avg Speed
Limit
Congestion
Index
Volume
Delay per
Mile
1 9E Hwy 71 – SB Mercy Way to Riorden Rd AM Art Bella Vista 1.61 45.0 0.51 194.2
2 9C Hwy 71 – SB Peach Orchard Rd to Mercy Way AM Art Bella Vista 1.34 45.0 0.49 168.1
3 2E North St – EB Oakland Ave to Hwy 45 PM Art Fayetteville 1.37 26.4 0.38 155.0
4 5389030 I-49 – SB South of Fullbright PM Fwy Fayetteville 0.27 60.0 0.68 123.3
5 2E North St – EB Oakland Ave to Hwy 45 AM Art Fayetteville 1.37 26.4 0.45 106.4
6 5369443 I-49 SB Short segment at on-ramp from Walnut PM Fwy Rogers 0.21 70.0 0.44 103.4
7 10M Hwy 71B – EB I-49 to Rainbow Rd PM Art Bentonville 1.34 45.0 0.46 79.2
8 5369443 I-49 SB Short segment at on-ramp from Walnut AM Fwy Rogers 0.21 70.0 0.48 73.1
9 2C Hwy 16 – EB Rupple Rd to Futtrall PM Art Fayetteville 1.07 43.9 0.48 70.1
10 2C Hwy 16 – WB Rupple Rd to Futtrall PM Art Fayetteville 1.07 43.9 0.48 69.7
11 5389031 I-49 – SB West of Hwy 112 PM Fwy Fayetteville 0.25 60.0 0.65 67.2
12 5369409 I-49 – NB South of Walton on-ramp PM Fwy Bentonville 0.34 54.4 0.47 66.6
13 10M Hwy 71B – Walton Blvd – WB I-49 to Rainbow Rd PM Art Bentonville 1.34 45.0 0.50 65.7
14 9C Hwy 71 – NB Peach Orchard Rd to Mercy Way PM Art Bella Vista 1.34 45.0 0.71 60.9
15 5402368 Hwy 71 – SB North CMP limits PM Art Missouri 0.06 45.0 0.40 58.5
16 10F Hwy 71B – NB Shiloh to Tyson Pkwy PM Art Springdale 1.70 43.3 0.55 55.4
17 5389276 I-49 – NB North of Hwy 412 AM Fwy Springdale 0.54 70.0 0.67 53.6
18 5402369 Hwy 71 – NB North CMP limits PM Art Missouri 0.06 45.0 0.42 52.7
19 5389139 Fullbright – WB Within I-49 interchange PM Fwy Fayetteville 0.61 60.0 0.71 51.6
20 5389081 I-49 – NB South of Fullbright interchange AM Fwy Fayetteville 0.43 63.5 0.73 51.0
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Figure E-2 – Top 20 Congested Segments
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Managing demand and implementing operations strategies are more cost-effective in the
short-term than larger capacity adding projects. At a minimum, operations should not be
forgotten when performing capacity projects in order to enhance their effectiveness.
History has shown, that widening a corridor without attention to optimizing the signal
system leads to little reduction in delays. Other MPOs have created funding set-asides
to be used to address smaller scale projects that can be quickly addressed without the
need for lengthy ROW or environmental process.
In the NWA region, many corridors could benefit from the application of access
management techniques (See Figure E-3) to its developed and currently undeveloped
corridors. The Federal Highway Administration defines access management as “the
process that provides access to land development while simultaneously preserving the
flow of traffic on the surrounding system in terms of safety, capacity, and speed.” It is
accomplished by controlling the design of access points, the location of access points,
and the number of access points allowed within a given distance. Access management
provides benefits related to safety, mobility, the environment, and fuel consumption.
While it is possible to retrofit already developed corridors for access management,
common problems include lack of right-of-way and landowner opposition. It is less
expensive to apply access management techniques to undeveloped corridors as they
develop. Consideration should be given to developing an access management program
that would define land patterns and traffic flow, program goals, policies, implementation
and financial strategies.
2013 2015
Figure E-3 – Highway 265 Access Management Plan 3-lane Undivided
to 4-lane Divided Median Boulevard, Bike Lanes, and Sidewalks
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HISTORY OF THE CONGESTION MANAGEMENT PROCESS
The NWARPC has initiated the Congestion Management Process (CMP) to monitor the
transportation network in the region. The goal of the monitoring system is to ensure optimal
performance of the transportation system by identifying congested areas and related
transportation deficiencies. This information will then be used in the transportation planning
process to develop strategic improvement projects that will improve and maintain the
performance of roadways at a system level.
The 2013 study was conducted using a full year dataset for 2013. The primary tasks completed
as part of this study include:
o Geo-coding the routes included in the CMP network
o Conflation of private sector data to the coded network
o Conflation of the AHTD volumes to the coded network
o Calculations of performance measures
o Congestion mitigation recommendations
WHAT IS THE CONGESTION MANAGEMENT PROCESS?
Guidance provided by FHWA includes eight (8) “actions” that comprise a well-developed CMP.
The elements are referred to as actions to indicate that the process is not to be thought of as a
linear methodology to step through, but may include variations and at times one may need to
revisit previous steps as a result of another. The actions below taken directly from the 2011
FHWA published “Congestion Management Process: A Guidebook” were used as the basis for
the structure for this report, as well as the MPO’s inaugural CMP itself.
1. Develop Regional Objectives for Congestion Management – First, it is important to
consider,―What is the desired outcome? ―What do we want to achieve? It may not be feasible
or desirable to try to eliminate all congestion, and so it is important to define objectives for
congestion management that achieve the desired outcome.
2. Define CMP Network – This action involves answering the question, ―What components of
the transportation system are the focus…and involves defining both the geographic scope and
system elements (e.g., freeways, major arterials, transit routes) that will be analyzed in the
CMP.
3. Develop Multimodal Performance Measures – The CMP should address, ―How do we
define and measure congestion? This action involves developing performance measures that
will be used to measure congestion on both a regional and local scale. These performance
measures should relate to, and support, regional objectives.
4. Collect Data/Monitor System Performance – After performance measures are defined,
data should be collected and analyzed to determine, ―How does the transportation system
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perform? Data collection may be on-going and involve a wide range of data sources and
partners.
5. Analyze Congestion Problems and Needs – Using data and analysis techniques, the CMP
should address the questions, ―What congestion problems are present in the region, or are
anticipated? ―What are the sources of unacceptable congestion?
6. Identify and Assess Strategies – Working together with partners, the CMP should address
the question, ―What strategies are appropriate to mitigate congestion? This action involves
both identifying and assessing potential strategies, and may include efforts conducted as part of
the MTP, corridor studies, or project studies.
7. Program and Implement Strategies – This action involves answering the question…How
and when will solutions be implemented? It typically involves including strategies in the MTP,
determining funding sources, prioritizing strategies, allocating funding in the TIP, and ultimately,
implementing these strategies.
8. Evaluate Strategy Effectiveness – Finally, efforts should be undertaken to assess, ―What
have we learned about implemented strategies? This action may be tied closely to monitoring
system performance under Action 4, and is designed to inform future decision making about the
effectiveness of transportation strategies.
1.0 Action 1 – Develop Regional Objective for Congestion Management
The starting point for the CMP is to develop regional objectives for congestion
management. These objectives draw from the regional vision and goals that are
articulated in the MTP. The goal of the CMP is not to eliminate congestion, but rather to
manage this congestion while balancing community livability, access, and pedestrian
safety.
Objective One: Develop procedures for evaluating the relative congestion of facilities.
NWARPC utilized 2013 Inrix XD Speed Data and 2013 AHTD AADT
and conflated the CMP Network for Congestion Analysis;
Objective Two: Develop procedures to determine if congestion mitigation strategies
should be implemented for a particular facility. Performance measures
were calculated to determine congested corridors within the region
along with a “tool box” of potential mitigation strategies;
Objective Three: Develop a procedure or procedures for evaluating the effectiveness of
congestion mitigation strategies implemented. NWARPC intends to
evaluate the deployed access management strategies,
intersection/interchange improvements, roadway widening, safety
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improvements, and signal timing projects in the next phase of the
CMP.
Therefore, the objective is to manage congestion and identify those roadway segments
with “unacceptable” congestion and establish objectives for congestion management in
line with regional goals. The MPO will work to promote projects and policies that support
the stated vison, goals, and objectives as part of the metropolitan planning process.
Stakeholders and participants in this study were part of the Technical Advisory
Committee. The CMP Committee included representatives of the following governments
units or agencies:
 Lowell
 Bentonville
 Fayetteville
 Rogers
 Springdale
 AHTD
2.0 Action 2 – Define CMP Network
To help establish the CMP network, the MPO staff invited representatives of local
agencies and units of government to a kick-off meeting in June 2014. The primary goal
of the meeting was to provide an overview of the CMP objectives.
The 2015 CMP network included a large portion of the roadway network functionally
classified as arterial and freeway. This will allow a baseline to be established of the
existing delay for the MPO to compare with future updates.
The study network included 224.5 centerline miles of roadway over 13 different
roadways divided into 234 directional links bound by a traffic signal, stop sign, or major
cross street. Figure 1 shows the city limits and CMP network, while a few of the
roadways extend outside the city limits and state. Figure 2 reflects the CMP Segments
whereby the performance measures are summarized within. The Interstate 49
segments are not labeled individually due to length of the segments. The individual
segments are delineated on the map and described in Table 1 (Page 29) and in
Appendices B and C.
All of the CMP network roadways were evaluated during the AM and PM peak periods
between the hours of 7:00 AM-9:00 AM and 4:30 PM-6:30 PM (Monday through Friday)
respectively. The total directional and centerline miles during each study period are
shown in Table 1.
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The CMP Committee identified a subset of roadway segments as “preserved” or
sometimes referred to as “multimodal corridors”. By associating this identification with
the segments, the Committee wants to maintain the character and speeds of the corridor
for various reasons and is not interested in reducing congestion, delays or increasing
speeds. This applies to areas with high density of pedestrians, on-street parking,
minimum ROW, etc. These segments, as highlighted in Figure 3 (Page 13), were
evaluated, but will not be included in the congestion analysis or mitigation
considerations.
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Figure 1 – 2015 CMP Network
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Figure 2 – 2015 CMP Segments
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Figure 3 – Preserved Segments
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3.0 Action 3 – Develop Multimodal Performance Measures
Performance measures are a critical component of the CMP. According to Federal
regulation, the CMP must include “appropriate performance measures to assess the
extent of congestion and support the evaluation of the effectiveness of congestion
reduction and mobility enhancement strategies for the movement of people and goods.
Since levels of acceptable system performance may vary among local communities,
performance measures should be tailored to the specific needs of the area and
established cooperatively by the State(s), affected MPO(s), and local officials in
consultation with the operators of major modes of transportation in the coverage area
(23 CFR 450.320 (c) 2).
3.1 Traffic Flow
The Highway Capacity Manual 2010 defines capacity as “…the maximum hourly rate at
which persons or vehicles reasonably can be expected to traverse a point or a uniform
section of a lane or roadway during a given time period under prevailing roadway, traffic,
and control conditions.”
The capacity of a roadway, and its operational characteristics, is a function of a number
of elements including: the number of lanes and lane widths, shoulder widths, roadway
alignment, access, traffic signals, grades, and vehicle mix. Generally, roadways with
wider travel lanes, fewer traffic control devices, straight alignments, etc. allow faster
travel speeds.
3.2 Congestion Index (CI) and Volume Delay per Mile
Federal guidance recommends that CMPs include performance measures that are
clearly understood and relatable to the public, decision makers, and technical
practitioners. The MPO has introduced the use of congestion index (CI) as one element
of performance in the CMP. This performance measure allows easy comparison of the
efficiency of roadways as a ratio of average travel speed to the posted speed limit. The
second measure is volume delay per mile. This performance measure calculates the
delay or amount of time drivers wait as compared to traveling at the posted speed. Also,
by multiplying it by the link volume, the overall impact of the delay can be measured. CI
is purely a measure of delay time, but does not relate the number of cars in the delay. In
many cases the minor or secondary roads are high on the CI ranking but rank lower on
the volume delay because fewer vehicles and people are affected on these secondary
roads. The CMP segments vary in length across the board between those on arterials
and freeways. In order to standardize the results and allow direct comparison across the
network, the volume-delay results were divided by the length. This provides a result with
the units of vehicle hours of delay per mile, thus allowing a more direct comparison
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between segments. As a result, the preferred performance measure was determined
and used to identify the operating results of each link of the CMP network.
 CI = Actual Average Speed / Weighted Average Posted Speed Limit
CI = Congestion Index
Actual Average Speed = Average speed of all INRIX data on the segment
Weighted Average Posted Speed Limit = Average of all posted speed limits on
the segment weighted by length
 Volume Delay (VD/mile) = (Delay X Segment Volume from Travel Demand
Model) / Segment Length
Based on the local conditions in the region, attention was focused on the peak periods.
The duration of congestion and other performance measures were not as much of a
concern with the short peaking of congestion within the region. This also is applicable in
most areas of the region to performance measures based on volume. There are a few
areas within the region where capacity is an issue, but most delay occurs at the node
level and is not a link problem. Because volume is measured mid-block and does not
consider the operations of the nodes (intersections), attention is being focused at the
location where the MPO can get the most benefit.
The MPO’s primary performance measure, as selected by the CMP Committee, is
volume delay per mile. The MPO CMP Committee evaluated thresholds to define what
would be used as “unacceptable” congestion. In order to narrow the focus on those
roadway segments that need attention and commonly have recurring delay, the results
were tabulated and the highest 15% of the network was categorized as congested. Over
time, with future updates, the committee will be able to revisit these thresholds and
adjust as desired. FHWA encourages the MPO to be flexible with the process and
customize the methodology and performance measures to respond to the local and
regional objectives.
The MPO can also consider adding other performance measures in future updates that
are multi-modal based that reflect the accessibility of transit, bike, and pedestrian
facilities. This can be as direct on the regional level as the % of jobs or households
within ¼ mile of transit. This will serve as an indicator of the accessibility to transit and
should have some correlation to the ridership.
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4.0 Action 4 – Collect Data / Monitor System Performance
It is necessary for MPO to maintain an accurate, up to date regional transportation
model in order to conform to State and Federal regulations for transportation planning.
The MPO maintains the regional model using current information on the roadway
network, area development, and other relevant characteristics. The MPO will collect
data as necessary to support the CMP and planning process.
For this 2015 study, the base conditions of the selected corridors were collected
including: roadway characteristics, travel time, and travel speed data. The primary
purpose of this year’s 2015 CMP is to establish the MPO’s initial CMP base.
Mapping of the roadway attributes and collection of travel speeds were collected for
arterials and freeways included in the CMP Network. The routes that were studied in
2013 are shown in Figure 1 (Page 29). In future years, the MPO may consider a more
detailed analysis of a subset of the overall network based on the results of this year’s
baseline analysis. That way, the MPO can maximize the detail collected on a smaller
roadway set, while not collecting data just for the sake of treating the entire network the
same. FHWA favors using professional judgment on defining the network with
consideration given for a systematic data collection plan that may include cyclical
analysis of certain roadways based on historic results or known changes since the last
update.
INRIX is one of the leading providers of real-time, historical and predictive traffic
information. As illustrated in Figure 4, it works by combining anonymous, real-time GPS
probe data from more than 1,000,000 commercial fleet, delivery, taxi vehicles, and smart
phone users across the U.S. with market-specific criteria that affect traffic such as
construction and road closures, real-time incidents, sporting and entertainment events,
weather forecasts and school schedules.
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Figure 4 – INRIX Data Collection Process
INRIX also recently introduced the INRIX Total Fusion service that combines real-time
predictive and historical traffic information for over 800,000 miles of roadways across the
U.S. The segmentation of INRIX data is based on Traffic Messaging Channel (TMC)
background and TeleAtlas map network. TMC location codes were established as a
standardized way (independent of map vendor) to report traffic incidents on major
roadways. TMC codes were originally conceived of as points on the road network,
typically assigned at significant decision points, interchanges or intersections, for the
purpose of describing locations of traffic incidents (accidents, construction, traffic
slowdowns, etc.) in an unambiguous, vendor independent format. It is possible to report
traffic flow data – as INRIX does – by considering the road segments implied by the
distance between consecutive TMC codes. These road segments are also referred to as
“TMC Paths”. In North America, a consortium of Tele Atlas and NAVTEQ, the nation’s
leading suppliers of commercial map databases, created and maintain a U.S./Canada
TMC location code table that adheres to the international standard on location
referencing (ISO 14819-3:2004 ). Initially published in fall 2003, the North American
Location Code Alliance owns, maintains and expands the location tables. The version
that is currently utilized by INRIX contains in excess of 218,000 location codes spanning
the U.S. and Canada, and allowing TMC paths to be created for roughly 400,000
centerline miles of roads. Updated versions of the location tables that further sub-divide
the TMC network, referred to as the XD network, were released in 2013 in order to
expand road coverage. Note that the TMC standard mandates that the tables remain
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backwards compatible as new versions are introduced. Although coverage area and
granularity will change, older codes will continue to map to the correct spatial location.
INRIX historical data product provides historical traffic flow information in major metro
areas in U.S. by deriving historic flow from traffic sensors, probe vehicles and Smart
Dust Network which combines data from various sources with a patented inference
engine. The inference engine calculates the speed of each road segment to a measured
degree of accuracy. The historical traffic flow data is provided for all major roads and
most local arterials in the U.S., with arterials being a more recent addition to the product.
The depth of historic information is greater on freeways compared to arterials.
The reported statistics for each segment include:
 The link identifier like LinkID or TMC Code
 Calculated average speed for each time interval
 Percentage of time spent under speeds of 30 mph, 50 mph and 60 mph
 Percentile speeds for each time interval like 10 th percentile, 15 th percentile, 25 th ,
50 th , and 85 th percentile if sufficient data is available to make this calculation.
While the dominant source of data is obtained from fleet systems that use GPS to
monitor vehicle location, speed, and trajectory, other data sources such as sensors may
also be used. The INRIX system fuses data from various sources to present a
comprehensive picture of traffic flow. This is being considered as an innovative data
source for both highway performance monitoring and regional planning. The archived
data is a valuable source for congestion monitoring and evaluation for the Congestion
Management Process (CMP), as well as for validation of the regional travel forecasting
model.
Traffic speeds and volumes are the two basic building blocks for most congestion
measures. It was decided by the CMP Committee to use a 2013 annual dataset after
taking into account the initiation of the vast majority of construction along I-49. This
allowed the analysis to reflect the “before” conditions and not be influenced by the on-
going construction and possible diversion of traffic to alternative routes due to
construction activities. In this effort, the 2013 traffic speed data licensed from INRIX was
referenced to different roadway segments than the segments for which Arkansas State
Highway and Transportation Department (AHTD) reports traffic volumes. Additionally,
NWARPC defined CMP-specific segments that did not match exactly either the INRIX
XD speed segments or the AHTD traffic volume segments. Therefore, the project team
had to conflate (or combine) the INRIX XD speed segments and the AHTD traffic volume
segments to the NWARPC-defined CMP segments. The sole sources of performance
data for this inaugural study include the INRIX XD data and AHTD volumes. The
saturation and coverage of data from INRIX continues to grow dramatically each year.
As shown in Figure 5 (Page 19), the 2013 dataset used for this CMP did not have
coverage along Wagon Wheel (Corridor 11A and 11B); therefore, no results will be
reported along that
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Figure 5 – Subset of 2013 INRIX XD Dataset Coverage
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route within this report. Alternative data sources will need to be used in the future if it is
desired to include this route with future updates to the CMP.
The project team obtained AHTD’s traffic volume network as part of the defined GIS
network provided in the previous step. The GIS file contained multiple years of traffic
data, and we used traffic volumes for the most recent year available, which was 2013.
The project team performed the conflation process within the ESRI ArcView GIS
software, using a mostly automated process that has been described in Appendix A.
The automated network conflation results were reviewed and manual
corrections/adjustments were made by a GIS analyst.
Through the integrated datasets assembled in GIS and the additional data assembled
below, the data collected in this study has a variety of additional uses outside the CMP.
Because the information is all housed in a GIS, queries can group data by area for use
in individual planning processes. Within the GIS, the MPO will have access to the
following datasets:
 CMP Routes
 Speed Limits (Figure 6)
 School Zones (Figure 7)
 Intersection Control (Figure 8)
 Jurisdiction
 Average Speed
 Congestion Index (% posted speed)
 Peak Period Travel Time
 Segment Delay
 Segment Volume
 Volume Delay per Mile North Street, Fayetteville
Studies like a CMP are data intensive and typically require a large amount of resources
and time to assemble. Other data sources may include transit operations, ridership, and
incidents.
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Figure 6 – Speed Limits
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Figure 7 – School Zones
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Figure 8 – Intersection Control
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5.0 Action 5 – Analyze Congestion Problems and Needs
Given the data collected and dataset assembled, the primary performance measure for
the CMP is volume-delay per mile. This performance measure calculates the delay or
amount of time drivers wait as compared to traveling at the posted speed. Also, by
multiplying it by the link volume, the overall impact of the delay can be measured. The
CMP segments vary in length across the board between those on arterials and
freeways. In order to standardize the results and allow direct comparison across the
network, the volume-delay results were divided by the length. This provides a result with
the units in vehicle hours of delay per mile, thus allowing a more direct comparison
between segments. As a result, the preferred performance measure was determined
and used to identify the operating results of each link of the CMP network.
According to the MPO thresholds developed by the CMP Committee, the top 15% of the
performance measure were identified as being congested.
5.1 Roadway Segment Definition
Utilizing the roadway attributes, the CMP corridors were divided into segments with the
endpoint or nodes being represented by controlled intersections or major cross-streets.
The roadway segment endpoints are defined at each traffic signal or stop sign. This
allowed the segments to be evaluated on a detailed level and then combined, as
appropriate, to make corridor recommendations. In addition, for the approximately 224.5
miles of roadways including 13 different roads, the network was further divided into 234
directional links for detailed evaluation. These segments either had a traffic signal, stop
sign, or a major cross street in rural areas with limited controlled intersections, as the
end points.
5.2 Data Reduction
The method of recording roadway information and the use of an annual private sector
dataset create large amounts of data that require manipulation into a useable format.
City limits were added directly into the database using the most current boundary files in
the MPO’s system. Each roadway was defined as a “route” in both directions and
beginning and ending points were determined in order to calculate travel time and
average speed for the segment.
5.3 Data Formatting
The travel time information and associated performance measures were formatted into
tables, graphs, and in ArcGIS. ArcGIS is a geographic information system (GIS)
software that allows the user a quick, easy-to-understand graphical reference. ArcGIS
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reads the study data files, stored in geo-databases, and presents the information
graphically. ArcGIS allows the user to group and summarize data for specific purposes.
When congestion occurs during only one time period, the user can study the detailed
information to determine the cause of the delay. Thus, improvements can be better
focused to ensure the most appropriate use of funds.
ArcGIS can be used to view the information provided in this study for reference and for
future projects. Maps and figures can be made for presentations. Information such as
speed limits along specific roadways, location and number of traffic signals, the location
and number of stop signs, and the location and length of school zones can be
summarized and viewed. The information can be summarized for the entire region or
broken down and summarized by city, and can be used to identify future improvements.
Figure 9 (Page 26) illustrates the congested segments (lowest performing 15%
segments) based on volume delay per mile results for the CMP network. Figure 10
(Page 29) further differentiates between the congested segments by functional class.
More detailed results can be seen within the tabular summaries included in the
Appendix.
5.4 Multimodal Analysis
This year’s network also reflects the existence of the transit network. Specific details on
the transit operations are not currently included in the analysis, but the MPO will need to
continue building on the system created so the CMP can truly be multi-modal not only
with transit but bike and pedestrian accessibility also. The CMP can and should reflect
various performance measures to evaluate the components of an integrated multimodal
transportation system.
Several “preserved” or “multimodal corridors” were designated in this initial effort as
locations where lower speeds and higher levels of auto congestion would be accepted to
aid in encouraging alternative transportation (transit, biking, and walking).
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Figure 9 – Peak Period Congestion Results
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Figure 10 – Congested Segments by Functional Class
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6.0 Action 6 – Identify and Assess CMP Strategies
6.1 Congestion Results
Congested Segments. The travel speeds on congested segments are slower than
drivers typically want to drive, and there may be less opportunity for lane changing and
maneuvering.
Stable Flow Segments. Stable-flow sections are accommodating volumes less than
capacity. Travel speeds are somewhat slower than the speed limit, but generally
acceptable to drivers. Lane changing and maneuvering is less difficult than in congested
segments.
Free Flow Segments. Free-flow sections are operating well below capacity. Travel
speeds equal or exceed the speed limit and traffic can maneuver without interference.
Appendix B lists each roadway segment and the performance measure results for the
travel time runs. Of the directional miles studied in AM and PM, the CMP Committee
determined to classify the top 15% of the segments as congested including both the
results of the AM and PM periods.
The 20 most congested segments based on the Volume-Delay per Mile are summarized
in Table 1 and illustrated in Figure 11. This table was developed by ranking segments
by volume delay per mile. For the Top 20, the average CI, was found to be 0.53 or an
average of 53% of the posted speed limit. For further study and analysis, Appendix C
includes those segments found to be congested ranked by functional class.
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Table 1 – Top 20 Congested Segments
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Figure 11 – Top 20 Congested Segments
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6.2 Recommendations
Private sector data as used in this study bring with it many advantages, but also a few
disadvantages. The primary advantage includes a large dataset that opens the door to
various performance measures and applications from 5 minute results for any day of the
week to annualized results for a full year at a reasonable cost. The downside of such
link based datasets is the limitation in evaluating detailed intersection level results.
Within the context of the CMP, link level results limit the details available to determine
appropriate mitigation for those segments identified as being congested; therefore,
specific segment or link recommendations to address congestion on CMP segments are
not possible given the dataset used for the CMP. The recommendations will be limited
to a “tool box” of recommendations that are typically seen with other CMPs. To address
this issue, it is recommended that the MPO consider taking a “hybrid” approach for the
next CMP update. That would include the use of a private sector dataset initially as a
regional review of the network. The analysis would then continue for those found to be
congested with more detailed data collection either using local sources, such as traffic
counts or data from traffic controllers (available), or collection of travel time runs on a
limited level to evaluate the performance of the corridor. These datasets would assist in
better pinpointing the location of delays within a segment, rather than just knowing the
average speed within a segment was low between the start and end nodes.
This is a very timely research topic within the industry given the growing use of private
sector data in regional operational assessments and CMP. Purdue University is actively
performing research on limitations and supplemental sources of data of large datasets,
including private sector data.
Typically, an arterial network plays a large role in circulation of traffic within a region.
Over the years, approximately 70% of signalized corridors show signs of poor signal
coordination, thus creating avoidable delays on the surface streets. This leads to not
only delays, but increased emissions and incidents. The following tools should be
considered on a regional level to address delays along local corridors and those that are
more regionally significant. Improvements include signal timing optimization / traffic
signal progression, access management, incident management, additional capacity, and
adding signals in place of stop signs. Benefits of these improvements are described
below. Additionally, the use of alternative modes such as public transit, bicycling, and
walking to the extent possible should be encouraged.
Signal Timing
Typically, many of the recommendations include signal timing improvements. Signal
timing improvements are a relatively inexpensive way to make significant improvements
on a transportation network. Improved signal timing can decrease delay by
appropriately allocating green time among competing phases. This allows more traffic to
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pass through the signal with less delay. By adjusting cycle lengths and offsets, drivers
can travel longer distances along a corridor before having to stop for a red light. This
decreases travel time and improves air quality. Both signal timing optimization and
traffic signal progression are low cost improvements to make the best use of existing
capacity and optimize allocation of funding. The cost for a signal timing improvement
project varies depending on the number of traffic signals, the controller capabilities, the
location of the traffic signals and adjacent signals, the number of timing plans required,
and implementation and fine-tuning needs. Adaptive signal control as has been
implemented along US 71B in Springdale and Rogers and US 62 in Rogers, will be
much more expensive per intersection than just occasional signal optimization, but
depending on the application, may be cost effective in the long run.
The U.S. Department of Transportation’s Federal Highway Administration (FHWA) has
produced a video showing that retiming traffic signals is one of the more cost-effective
techniques available to state and local agencies in their efforts to manage congestion
and growing travel demand. The video, “It’s About Time, Traffic Signal Management:
Cost-Effective Street Capacity and Safety,” demonstrates how signal timing on roads
can improve air quality while reducing fuel consumption, decreasing traffic congestion,
and saving time for commercial and emergency vehicles. Two-thirds of all highway
miles in the United States are roads with traffic signals. According to the Institute of
Transportation Engineers, the United States has about 300,000 traffic signals. The
performance of about 75 percent of them could be improved easily and inexpensively by
updating equipment or by simply adjusting the timing.
Signal timing is an area that deserves attention within the region to allow maximum
efficiency of the existing system before costly widening to add capacity. The results will
be very evident as has been demonstrated previously with localized projects. A regional
perspective would produce consistent travel time runs even when crossing from one
city/agency to another.
As transportation funding continues to be limited, operations are being highlighted by
many MPOs across the country. It has been clearly proven locally and nationally that
operational improvements provide the highest benefit/cost ratio and on a regional scale
as compared to local capacity projects that benefit a smaller portion of the area.
Data collection, development of a model for each desired timing plan, signal timing
optimization, and implementation can be accomplished along a corridor for around
$3,000 per intersection (not including any necessary hardware in the signal cabinet).
The methods will vary as to how to accomplish the desired results depending on the
signal hardware currently in place and the expansion capabilities. It can be as simple as
installing a GPS clock at each intersection ($500) to synchronize the controller clocks to
more advanced systems where each intersection needs vehicle detection ($15,000) and
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wireless communications ($2,500) between signals. Either way, the benefit/cost ratio of
this type of work is unmatched in today’s funding environment.
Until a time when the system is fine-tuned to operate efficiently within the existing
roadway cross-section, it is difficult to identify those areas that may need more attention
including local geometric improvements, access management, or finally added capacity.
Access Management
The Federal Highway Administration defines access management as “the process that
provides access to land development while simultaneously preserving the flow of traffic
on the surrounding system in terms of safety, capacity, and speed.”
Access management is accomplished in a variety of ways such as managing the design
of access points, the location of access points, the number of access points allowed
within a given distance (access density), and the roadway median treatment. Generally,
the number of access points is minimized and regularly spaced from each other so that
conflict points are separated.
Access management can provide a number of benefits to the public agency and to the
traveling public. Capacity is preserved and safety (motorized and non-motorized) is
improved by minimizing conflict points and minimizing speed differentials between
through traffic and slow moving turning traffic. Safety for turning movements is also
improved by providing adequate turning (auxiliary) lanes or by prohibiting turns in key
locations using a raised median. In addition to safety and efficiency improvements,
access management also provides environmental and financial benefits with reduced
vehicle emissions and improved fuel economy by maintaining the flow of traffic.
On new roadways, or on undeveloped corridors, access management can be used to
minimize operational traffic problems, due to unmanaged development, before they
occur. In these cases, it is inexpensive and fairly easy to accomplish. The traveling
public benefits from a safe and efficient corridor. Property owners benefit from safe
access. The agency benefits from a low cost management plan from the onset rather
than costly highway improvement projects once problems occur. Once corridors are
developed, it is more difficult, expensive, and time consuming to retrofit managed
access. Whenever possible, access management should be given high priority on
undeveloped corridors.
Access management can be very challenging on existing ‘built-up’ urban roadways.
Common issues include limited right-of-way and opposition by land owners. Still,
retrofitting a corridor with access management can provide benefits. Possible retrofitting
improvements include: consolidating and closing driveways, constructing raised
medians, constructing auxiliary lanes, providing regularly spaced traffic signals to
encourage use of a major cross-street or driveway, and providing alternative routes such
as internal access roads.
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Intersection Control
Adding signals or roundabounts, when warranted, may be an improvement at all-way
stop intersections or intersections with heavy major-street and cross-street traffic. This
reduces delay for previously stop-controlled movements but may increase delay for
movements that were not controlled. As traffic volumes increase, traffic signals or other
types of intersection design such as roundabouts or continuous flow intersections should
be considered to efficiently move traffic. Local intersection improvements also can result
in big reductions in delays through bottleneck mitigation. Local improvements include
geometric changes related to increased queue storage to channelized right turns and
overlapping signal phases.
2010 2015
Fulbright Expy – Northhills Blvd – Futrall Dr. Roundabout
2010 2015
Fayetteville Flyover/Fulbright Expressway
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Incident Management
Incident management plays a large roll in reducing delays and secondary incidents. By
identifying incidents early and having quick responses from tow trucks available in close
proximity that may be stationed or roving, clearing of incidents helps traffic return to
normal operations as quick as possible.
Safety Projects (Roadway Departures, Bicycle and Pedestrian Crossings)
Safety projects reduce crash rates and the severity of crashes. Non-reoccurring
congestion based on traffic incidents (crashes) can account for up to 25% as the source
of congestion. The region should continue to deploy rumble strips as needed, cable
median barriers, enhanced signing at curves and high friction pavements to reduce
crash rates on the CMP network.
2010 2015
I-49 Cable Median Barrier Project, Springdale, AR
2010 2015
MLK Blvd – Razorback Regional Greenway Pedestrian and Bicycle Underpass
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Added Capacity
Roadway widening is necessary where traffic signal timing and access management are
unable to provide enough capacity for heavy traffic volumes. Some segments may
improve in the short term with optimized signal timing, but may ultimately warrant
additional capacity through widening. Widening could include adding a through lane for
a long section of road, or providing turn lanes at intersections. Adding capacity through
roadway widening is generally expensive.
2010 2015
Don Tyson Parkway Interchange/I-49
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7.0 Action 7 – Program and Implement CMP Strategies
A fully integrated CMP not only evaluates the current congestion conditions and
recommends mitigation, but prioritizes the improvements and incorporates them into the
planning process. Those improvements can be viewed as local improvements, corridor
strategies, or regional programs/initiatives.
Regions are expected to manage their system to get as much capacity out of the
existing system prior to capital projects to widen the roadways. Ideally, every effort
should be exhausted and documented before getting to the end of the line and adding
capacity.
This study serves as the initial element of the CMP and should not be viewed as a
complete CMP. The CMP is a living process that is part of the planning process. This
initial study is documenting the current conditions, ranking the magnitude of observed
congestion, recommending possible mitigation, and prioritizing those improvements.
The MPO will apply these findings and integrate them into the planning process.
One option that many MPOs have used is in the form of a “set aside” funding category
for localized bottleneck and operational projects. These projects are “quick fixes” and do
not need the sometime lengthy process required for capital projects. Also, the
prioritization of operational projects compared to the larger capital projects at times is
tough to compare. By having a separate category for operational projects makes the
time to market much shorter and the community can benefit much sooner.
8.0 Action 8 – Evaluate Strategy Effectiveness
This 2015 CMP is the first effort toward development of a full CMP. Therefore, the MPO
is not able to evaluate the benefits of implemented strategy this time around; however, in
the future the MPO’s CMP will go full circle to identify the conditions, recommend
mitigation, prioritize the improvements, plan the schedule and funding, and evaluate the
benefits.
MPO member agencies have implemented various projects over the last few years. In
the future, projects like those shown below will be evaluated using before/after datasets.
The assessments of historic projects are not only intended to validate the benefits of
specific projects, but to evaluate general strategies effectiveness.
Recent projects include:
Adaptive Signal Control
City of Rogers:
 Highway 71B/Walnut Street – From I-49 to Highway 71B (Walnut) – Completed
December 2011
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 Highway 71B/South 8 th Street – From Olive Street to New Hope Road –
Completed December 2011
 I-49 / New Hope Road – interchange signals
City of Springdale:
 Highway 71B/Thompson – From Don Tyson Blvd. to Randall Wobbe –
Completed April 2010
Highway 265 Access Management Plan
 This plan was part of an agreement between the city of Fayetteville, the
Arkansas State Highway and Transportation Department and the Northwest
Arkansas Regional Planning Commission to protect the capacity of the roadway,
improve safety for drivers, bicyclists and pedestrians. The agreement was
executed in 2009.
Congestion Analysis and Performance Measures for Northwest Arkansas
The Interstate 49 Improvements Study prepared by Parsons Transportation Group in
2006 considered the needed Interstate widening and focused on an analysis of nineteen
interchanges in order to recommend short-term, interim and long-term improvements.
The study developed the following:
 2024 travel demand forecast for I-49
 Identified congestion segments
 Calculated 2006 and 2024 Level of Service
 Recommended interstate widening
 Analyzed nineteen interchanges on I-49
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The Northwest Arkansas Eastern North-South Corridor Study
Completed in 2011, the project analyzed the need for improvements to an eastern north-
south corridor in order to alleviate the traffic congestion on the existing north-south
routes, especially Highway 71B. The study extended from Highway 16 East in
Fayetteville to Highway 62 in Rogers, with a potential extension to Bentonville.
Highway 112 (Razorback Road and Maple Street) Improvement Study
Completed in 2010 by the Arkansas State Highway and Transportation Department, the
study was conducted to determine the appropriate cross-section for improvements to
Highway 112 along Razorback Road and Maple Street between Highway 180 (Martin
Luther King Blvd.) and Garland Ave. through the University of Arkansas campus in
Fayetteville.
CONCLUSION
The Congestion Management Process (CMP) plays an essential role within the transportation
planning and programming process by providing decision-makers at MPOs, local governments,
and state agencies a clear analytical understanding of congestion in the region. The CMP must
be an integral element in a well-organized, objectives-driven, performance-based planning
approach.
The flexibility of the regulations and guidelines has allowed the MPO to customize the CMP in
various ways to reflect both regional needs and priorities. MPOs around the country have
developed unique methods of implementing the CMP. The NWARPC looks forward to continue
working with the members of the CMP Committee to build on the momentum begun through the
development of this component of the overall CMP by using the performance measures
identified here within, by aligning the CMP closely with the Metropolitan Transportation Plan and
Transportation Improvement Program, and using the CMP performance measures to directly
influence project prioritization and funding.
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Appendix A
Detailed Conflation and Traffic Volume Estimation Procedures
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Detailed Conflation and Traffic Volume Estimation Procedures
The following steps were used to conflate the traffic speed and traffic volume networks, which
are then used to calculate the congestion performance measures for each CMP-defined road
segment.
1. Identify/obtain AHTD traffic volume data by road section
2. Match the AHTD road network sections with the traffic speed dataset road sections
3. Estimate traffic volumes for each 15-minute time interval from the daily volume data
4. Calculate congestion measures based on integrated 15-minute speeds and volumes
Step 1. Identify/Obtain Traffic Volume Data
An AHTD dataset provided the source for traffic volume data, although the geographic
segmentation in the AHTD dataset are not identical to the private sector speed data. The daily
traffic volume data must be divided into the same time interval as the traffic speed data (hour
intervals). While there are some detailed traffic counts on major roads, the most widespread
and consistent traffic counts available are average daily traffic (ADT) counts. The hourly traffic
volumes for each section; therefore, were estimated from these ADT counts using typical time-
of-day traffic volume profiles developed from continuous count locations or other data sources.
The section “Estimation of Hourly Traffic Volumes” shows the average hourly volume profiles
used in the measure calculations.
Volume estimates for each day of the week (to match the speed database) were created from
the average volume data using the factors in Exhibit A-1. Automated traffic recorders from
around the country were reviewed and the factors in Exhibit A-1 are a “best-fit” average for both
freeways and major streets. Creating an hourly volume to be used with the traffic speed values,
then, is a process of multiplying the annual average by the daily factor and by the hourly factor.
Exhibit A-1. Day of Week Volume Conversion Factors
Day of Week
Adjustment Factor
(to convert average annual volume
into day of week volume)
Monday to Thursday +5%
Friday +10%
Saturday -10%
Sunday -20%
Step 2. Combine the Road Networks for Traffic Volume and Speed Data
The second step was to combine the road networks for the traffic volume and speed data
sources, such that an estimate of traffic speed and traffic volume was available for each
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roadway segment in each urban area. The combination (also known as conflation) of the traffic
volume and traffic speed networks was accomplished using Geographic Information Systems
(GIS) tools. The INRIX speed network was combined with an ADT count from the AHTD
volume network, and then integrated onto the CMP-defined roadway segments. The traffic
count and speed data for each roadway segment were then used to calculate congestion
measures.
Step 3. Estimate Traffic Volumes for Shorter Time Intervals
The third step was to estimate traffic volumes for one-hour time intervals for each day of the
week.
Typical time-of-day traffic distribution profiles are needed to estimate hourly traffic flows from
average daily traffic volumes. Previous analytical efforts 1,2 have developed typical traffic profiles
at the hourly level (the roadway traffic and inventory databases are used for a variety of traffic
and economic studies). These traffic distribution profiles were developed for the following
different scenarios (resulting in 16 unique profiles):
 Functional class: freeway and non-freeway
 Day type: weekday and weekend
 Traffic congestion level: percentage reduction in speed from free-flow (varies for
freeways and streets)
 Directionality: peak traffic in the morning (AM), peak traffic in the evening (PM),
approximately equal traffic in each peak
The 16 traffic distribution profiles shown in Exhibits A-2 through A-6 are considered to be very
comprehensive, as they were developed based upon 713 continuous traffic monitoring locations
in urban areas of 37 states.
1 Roadway Usage Patterns: Urban Case Studies. Prepared for Volpe National Transportation Systems Center and
Federal Highway Administration, July 22, 1994.
2 Development of Diurnal Traffic Distribution and Daily, Peak and Off-peak Vehicle Speed Estimation Procedures for
Air Quality Planning. Final Report, Work Order B-94-06, Prepared for Federal Highway Administration, April 1996.
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Exhibit A-2. Weekday Traffic Distribution Profile for No to Low Congestion
Exhibit A-3. Weekday Traffic Distribution Profile for Moderate Congestion
0%
2%
4%
6%
8%
10%
12%
0:00 2:00 4:00 6:00 8:00 10:00 12:00 14:00 16:00 18:00 20:00 22:00
Percent of Daily Volume
Hour of Day
AM Peak, Freeway Weekday PM Peak, Freeway Weekday
AM Peak, Non-Freeway Weekday PM Peak, Non-Freeway Weekday
0%
2%
4%
6%
8%
10%
12%
0:00 2:00 4:00 6:00 8:00 10:00 12:00 14:00 16:00 18:00 20:00 22:00
Percent of Daily Volume
Hour of Day
AM Peak, Freeway Weekday PM Peak, Freeway Weekday
AM Peak, Non-Freeway Weekday PM Peak, Non-Freeway Weekday
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Exhibit A-4. Weekday Traffic Distribution Profile for Severe Congestion
0%
2%
4%
6%
8%
10%
12%
0:00 2:00 4:00 6:00 8:00 10:00 12:00 14:00 16:00 18:00 20:00 22:00
Hour of Day
AM Peak, Freeway Weekday PM Peak, Freeway Weekday
AM Peak, Non-Freeway Weekday
Percent of Daily Volume
PM Peak, Non-Freeway Weekday
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Exhibit A-5. Weekend Traffic Distribution Profile
0%
2%
4%
6%
8%
10%
12%
0:00 2:00 4:00 6:00 8:00 10:00 12:00 14:00 16:00 18:00 20:00 22:00
Hour of Day
Exhibit A-6. Weekday Traffic Distribution Profile for Severe Congestion and
Similar Speeds in Each Peak Period
Freeway Non-Freeway
Percent of Daily Volume
0%
2%
4%
6%
8%
10%
12%
0:00 2:00 4:00 6:00 8:00 10:00 12:00 14:00 16:00 18:00 20:00 22:00
Percent of Daily Volume
Hour of Day
Freeway Weekend Non-Freeway Weekend
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The next step in the traffic flow assignment process is to determine which of the 16 traffic
distribution profiles should be assigned to each Traffic Message Channel (TMC) path (the
“geography” used by the private sector data providers), such that the hourly traffic flows can be
calculated from traffic count data supplied by AHTD. The assignment should be as follows:
 Functional class: assign based on AHTD functional road class
o Freeway – access-controlled highways
o Non-freeway – all other major roads and streets
 Day type: assign volume profile based on each day
o Weekday (Monday through Friday)
o Weekend (Saturday and Sunday)
 Traffic congestion level: assign based on the peak period speed reduction percentage
calculated from the private sector speed data. The peak period speed reduction is
calculated as follows:
1) Calculate a simple average peak period speed (add up all the morning and evening
peak period speeds and divide the total by the 8 periods in the eight peak hours) for
each TMC path using speed data from 7 a.m. to 9 a.m. (morning peak period) and 4:30
p.m. to 6:30 p.m. (evening peak period).
2) Calculate a free-flow speed during the light traffic hours (e.g., 10 p.m. to 5 a.m.) to be
used as the baseline for congestion calculations.
3) Calculate the peak period speed reduction by dividing the average combined peak
period speed by the free-flow speed.
For Freeways:
o speed reduction factor ranging from 90% to 100% (no to low congestion)
o speed reduction factor ranging from 75% to 90% (moderate congestion)
o speed reduction factor less than 75% (severe congestion)
For Non-Freeways:
o speed reduction factor ranging from 80% to 100% (no to low congestion)
o speed reduction factor ranging from 65% to 80% (moderate congestion)
o speed reduction factor less than 65% (severe congestion)
 Directionality: Assign this factor based on peak period speed differentials in the private
sector speed dataset. The peak period speed differential is calculated as follows:
1) Calculate the average morning peak period speed (7 a.m. to 9 a.m.) and the average
evening peak period speed (4:30 p.m. to 6:30 p.m.)
2) Assign the peak period volume curve based on the speed differential. The lowest
speed determines the peak direction. Any section where the difference in the morning
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and evening peak period speeds is 6 mph or less will be assigned the even volume
distribution.
Step 4. Calculate Congestion Performance Measures
At this point in the process, we now have a traffic speed value and traffic volume estimate for
every 15 minutes of an average weekday for each of the CMP-defined roadway segments. The
total size of this integrated volume and speed database is 143,136 rows/records, which can be
imported into an Excel spreadsheet or Access database table for specific congestion measure
calculations. In this effort, the project team used Microsoft Excel for final performance measure
calculations.
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Appendix B
2013 Intersection Segment Results
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Appendix C
Congested Segments Ranked by Functional Class