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City of Fayetteville, Arkansas Traffic and Transportation Study Chapter 3 – Traffic Analysis

Bucher, Willis & Ratliff Corporation 21 M:\2002-359\doc\Report\10-05-03 Final Report.doc

3. TRAFFIC ANALYSIS

Key Findings:

This chapter of the report discusses the impacts of existing and future traffic demand on Fayetteville’s major street system, as well as recommendations for mitigating traffic impacts.

• County population and employment are projected to grow by 45 percent in the next 20 years contributing to increased traffic congestion.

• Approximately 10 percent of the major intersections in the City suffer traffic congestion.

• Approximately 25 percent of the major intersections in the City will suffer traffic congestion in 20 years.

• In the next 20 years, traffic demand will exceed roadway capacity on more than 20 miles of major streets in the City.

• 35 short range traffic improvement projects and 22 long range traffic improvement projects have been identified for construction over the next 20 years.

INTRODUCTION

During the initial project interactive workshop, one of the key issues of public concern was traffic congestion within the community. This issue has been studied through a comprehensive traffic data collection and analysis effort. The traffic analysis included all the signalized intersections within the City and all the arterial streets. In addition, several non signalized intersections and several collector streets were also identified for traffic analysis. The data collection involved compiling:

Morning and afternoon peak hour traffic counts for major intersections.

Daily traffic volumes.

A windshield survey of the arterial streets, identifying road geometry.

Travel time and delay surveys in a test car, on all arterial streets.

Traffic signal timings.

The analysis of the traffic data included the following elements:

Preparation of 20 year traffic forecasts.

Development of a traffic simulation model.

Intersection capacity analysis.

Intersection queuing analysis.

Arterial level of service analysis.

Traffic volume/capacity comparison for arterial streets.

Traffic congestion mitigation recommendations.



PEAK HOUR TRAFFIC COUNTS

Traffic congestion generally occurs most severely during the commuter peak periods. Because traffic congestion in a community is generally the worst on a daily basis during the morning and afternoon commuter periods, traffic congestion analysis is typically performed for traffic volumes during those periods. The analysis methodology established by the Transportation Research Board in their publication, the Highway Capacity Manual, is based on the evaluation of one hour of traffic flow during the heaviest traffic periods of the day. Traffic volumes for major intersections in the City were provided by the City staff. These traffic counts were derived from vehicle detection units at signalized intersections. Those counts provided tallies of left turn traffic and through/right turn traffic on each approach. The traffic detection equipment did not make a distinction between through traffic and right turn traffic, so right turn traffic percentages were estimated.

In addition to the 66 intersection locations where counts were supplied by the City the project data collection included obtaining manual peak hour turning movement counts at 41 locations, ten of which were included in the 66 locations supplied by the City. These ten locations were considered by the City to be locations where actual right turn counts were desirable rather than estimates only. Both the manual counts and the automatic sensor counts were compiled for the periods 7:00 to 8:00 a.m., and 5:00 to 6:00 p.m. on typical weekdays. Traffic counts were conducted in the fall of 2002 while the university was in session. The detailed traffic count summaries along with the date and time of counts have been compiled in a technical appendix.

DAILY TRAFFIC VOLUMES

The AHTD maintains an annual traffic counting program on major streets. Historical maps of daily traffic counts were supplied by the City for completion of this study. The major street analysis compared daily traffic volumes for the year 2000 with forecast traffic volumes for the year 2023 to evaluate the staging for major street improvements.

WINDSHIELD SURVEYS

The data collection effort included conducting a windshield survey of all the designated arterial streets in the City. The survey included:

Noting posted speed limits.

Preparing sketches of the number of through and auxiliary lanes at each major intersection.

Taking photographs of each approach at each major intersection.

This information was compiled in technical appendices and used as a basis for the traffic analysis.



TRAVEL TIME AND DELAY SURVEYS

The travel speeds experienced along all the arterial streets in the City during the commuter peak hours were surveyed as a part of the data collection effort. The speed surveys were conducted by driving a test car along the major street and recording the overall travel time between each major intersection, as well as the period of time the vehicle was delayed at each signalized intersection. Three runs were performed in each direction during the commuter peak hours to provide average travel and delay times. This information was foundational for grading the quality of traffic operation on the City’s arterial street network.

TRAFFIC SIGNAL TIMINGS

Traffic signal timings were supplied by the City for all signalized intersections. The signal timings were an essential element of data for the traffic analysis.

TRAFFIC FORECASTS

Fayetteville Model Development

To support the Fayetteville traffic study and operations analysis, 2023 traffic forecasts were developed for the major streets in Fayetteville. These traffic forecasts were based on projected changes in employment and population. Since historical background traffic growth rates are not sensitive to shifting distributions of population and employment, the only valid method for considering changes in future travel patterns is a travel demand-forecasting model. A model requires subdividing the entire area into traffic analysis zones, and then population and employment are allocated to these zones. This zonal allocation produces traffic volume forecasts on roadway segments and at intersections.

Methodology

The Fayetteville Model was developed using the TransCAD (version 4.5) travel demand forecasting system. This software can directly access Census TigerLine files as well as Census geography. This feature allowed the Fayetteville model to be constructed quickly and efficiently.

The Fayetteville Model covers all of Washington County. To begin model development, Census TigerLine files, and Census geographic boundary files were downloaded from Census and GIS web pages. The boundary files downloaded are:

County Boundary File for Washington and Benton County

Census Tract Boundary File for Washington County

Census Block Group Boundary File for Washington County

Census SF1 Block Group Data File for Washington County.



In addition to these Census data, additional data sources for this model included:

An older Tranplan model for Washington and Benton Counties.

Employment data purchased from InfoUSA.

Land use and other GIS data from the Fayetteville web site.

In addition, proprietary TransCAD GISDK user interface software was used to run the model and develop forecast year traffic.

Network Development

The Census TigerLine files were used as the basis for the model network. The TigerLine files were first imported into TransCAD. Then these files were reviewed and modified to convert them from simple line configurations into a network suitable for use in a traffic forecasting model. TigerLine data does not have travel direction information. Consequently a road such as I-540 is shown as parallel lines with no travel direction. Also, TigerLine data does not have grade data, consequently any grade separation (bridge) is shown as an intersection. From a line attribute perspective, the TigerLine data does not have many of the attributes typically used in models such as:

Number of lanes

Posted speed

Roadway functional classification.

However, the benefit of the TigerLine data is that it is geographically correct and aligns perfectly with Census geography. The TigerLine data also has street address and zip codes that can be used for address matching.

The first major work activity was to convert the TigerLine data into a model network. This conversion was achieved by fixing all the grade separations, particularly along I-540. Northbound/southbound or eastbound/westbound directions on the limited access roads were also properly coded. All ramps had to be checked and set with the proper travel direction. Test paths were then built through the network to check for erroneous line gaps.

Following this initial cut, the existing Tranplan network was then geo-rectified and used as an under-layer to the TigerLine network. This underlying process allowed attributes from the Tranplan model to be attached to the TigerLine network. Using this attaching “tagging” process, one-way roads in the Tranplan model were readily identified and this feature was carried into the TigerLine network file. Similarly, the TigerLine roads were also tagged with the functional classification, posted speed, roadway capacity, and number of travel lanes from the Tranplan model.

Next, the TigerLine network was electronically overlaid atop an aerial photo downloaded from the Fayetteville web page. Then a detailed manual process was conducted to check the lane attributes and roadway configurations in the model against the aerial photography.



The TigerLine data shows a line for every road in the County. However, only major roads are represented in the travel demand-forecasting model. Since TransCAD is a geographic information system (GIS), it develops a travel demand forecasting model network by building a network from the GIS layer. This allows the user to create a selection set of roads in the GIS that can be used as the roadway network for the model. As a starting point, all of the roads included in the Tranplan model were selected for inclusion in this model. In addition, the project team compiled intersection turning movements at the major intersections in Fayetteville. These intersections were used as a guide to select additional roads for inclusion in the model. Basically, all the roadway approaches to counted intersection were included in the model. A final review of the network selection set was then conducted by another examination of the aerial photography. The purpose of this review was to identify local roads that appeared to be logical connections/crossroads that would provide network connectivity.

As final network preparation steps, speeds, capacities, and observed counts were coded into the model. The capacities and speeds initially came from the TranPlan model and were compared against speed/capacity lookup tables developed for other projects. This capacity analysis was used to estimate hourly and daily directional roadway capacity. Newly collected traffic counts were then coded into the model for later use in the model calibration process. When completed, the highway network consisted of 869 centerline miles of road (note limited access roads were computed with centerline miles in each direction).

Traffic Analysis Zone Development

Traffic analysis zones (TAZs) were developed based on 2000 Census block group geography. This geography and demographic data can be readily downloaded on the web and TransCAD has built-in functions to import this data for model use. The demographic data came from the SF1 block group file for the County.

The TAZ employment data came from InfoUSA. This website based company sells County level employment data. The data contains all reported employers, the business address of the employer, the number of employees, the employer name, and the standard industrial code (SIC) of the employer. There are many other data fields in the InfoUSA data, but those fields were not used. TransCAD was then used to “tag” each employer with a block group (TAZ) ID. A proprietary in-house program was used to aggregate the data by traffic zone and by employment type. The employment types used in the model were:

Retail

Service

Education (K-12)

Education (college)

Health

Entertainment

Manufacturing

Agriculture

Wholesale

Government



Other.

The InfoUSA data represented the last quarter of 2002, and the Census data represented2000. The Census data was inflated to an estimated 2002 based on historic demographic trends.

As a final step in the employment compilation process, the employment data was reviewed against the aerial photography. Some cleaning of the InfoUSA data was needed.

Traffic zones were then attached (creating zone connectors) to the highway network using an automated TransCAD process. These zone connectors were then reviewed using the aerial photography and many were adjusted.

At the external boundaries of the County, external traffic zones were developed. These external zones were placed where model network roads crossed the County line. At each external zone, the average daily traffic (ADT) was coded along with a likely share of the ADT trips that are external-external (these trips travel through the County without stopping). The external-external percentages were based on roadway functional classification, the total population in the County, and Transportation Research Board Report #365 (TRB Report 365). TRB Report 365 provides guidance regarding external-external percentages and it is an industry standard for providing general guidance toward the development of regional travel demand forecasting models. This report is based on the compilation of hundreds of surveys conducted nationwide.

When completed, the TAZ structure for the County consisted of 364 zones, including 336 internal zones and 28 external zones.

Trip Generation

The trip generation process generally follows TRB Report 365. For internal traffic analysis zones a cross-classification process based on area type (urban, suburban, CBD), total households, household size, and auto availability was used. The model has 5 trip purposes as follow:

Home Based Work Trips

Home Based Non-Work Trips

Non-Home Based Trips

Trips which have one end of the trip outside the County (external-internal trip)

Trips which have both ends of the trip outside the County, but which pass through the County (external-external).

The trip generation equations generally follow TRB Report 365, with some modifications based on previous work from the Missouri Statewide Travel Demand Forecasting Model.

Trip Distribution

A gravity model was used to perform the trip distribution step. The gravity model is an industry standard and is discussed in detail in TRB Report 365. Gravity model parameters and settings used for this Fayetteville project were taken from TRB Report 365. The output of the gravity model is a daily person trip origin/destination table for each of the trip purposes discussed above.



Trip Assignment

The trip assignment process used is known as an equilibrium assignment. This process considers speeds and capacities when assigning trips to particular travel route. The process is sensitive to congestion and will recalculate routes as corridor congestion increases. The assignment was conducted separately for each time period (daily, AM peak hour, and PM peak hour). The assignment product was traffic volumes on all roads included in the model, and intersection turning movements at intersections.

Model Calibration

The model was calibrated to guidelines establish by the Federal Highway Administration (FHWA). Typically to achieve calibration, each step in the modeling process is reviewed with some adjustments made.

Population and Employment Projections

Demographic and employment projections were based on projections made by Fayetteville and posted in recent reports. The projections were allocated to TAZs based on Fayetteville’s future land use plan. The projections were made for a 2023 forecast year. Table 3-1 below shows a summary of the base and future year demographics and employment.

Table 3-1 Population and Employment Projections

Variable Base Year 2002 Future Year 2023

County Population 158,117 230,327

County Employment 99,293 144,482

These demographic and employment characteristics translated to 688,000 daily person trips in 2002, and 1, 003,000 daily person trips in 2023.

The model zones and network and the input and output files are included in a technical appendix.

The daily traffic volume forecasts for the year 2023 were used to establish 20 year growth factors for each of the arterial streets in the City. Those growth factors were then applied to the existing intersection peak hour traffic counts to develop 20 year forecast intersection peak hour traffic volumes.



SIMTRAFFIC MODEL

SimTraffic is a micro simulation traffic model used to present an animation of traffic movements through a street system. Just as a model is a replica of a real item, a traffic simulation model is intended to replicate traffic movements on a street. A micro simulation traffic model is intended to provide detailed information about traffic movements at one or more intersections. SimTraffic provides a graphic animation of how the vehicles would look from an aerial view as they pass through intersections and along a street system. The SimTraffic software works with another software package Synchro, to provide measures of effectiveness for intersection operation. These measures include vehicle delay, and a resulting level of service for each intersection. Level of service is a grade A, B, C, D, E, or F, of the quality of traffic operation, depending on the average delay that motorists can expect during peak traffic periods.

The SimTraffic model was set up for the City only as a byproduct of the Synchro analysis of the major intersections. The SimTraffic network reflects only those major intersections where traffic volumes were obtained and a level of service calculated. Inputs for the model included only those parameters necessary for the Synchro level of service and vehicle queuing analysis, which were lane geometry, traffic signal timings, and peak hour traffic volumes. The SimTraffic model includes other parameters which can be adjusted to refine the model. It was the intent of this project to prepare the model for future City use, and not to refine the model for any particular application in this project.

Figure 3-1 depicts a screen capture from the SimTraffic model.

Figure 3-1 SIMTRAFFIC Model Sample Screen Capture



CAPACITY ANALYSIS

The methodology used to compute level of service for an intersection is known as capacity analysis. This methodology is described in the Highway Capacity Manual 2000 (HCM 2000), published by the Transportation Research Board. Table 3-2 summarizes the delay parameters resulting from intersection capacity analysis corresponding to the six levels of service grades for both signalized and non-signalized intersections.

Table 3-2 Level-Of-Service Criteria Non-signalized Intersections

Signalized Intersections LOS

Approach Delay (Seconds/vehicle)e

Approach Delay (Seconds/vehicle)

A ≤ 10 ≤ 10

B > 10 and ≤ 15 > 10 and ≤ 20

C > 15 and ≤ 25 > 20 and ≤ 35

D > 25 and ≤ 35 > 35 and ≤ 55

E > 35 and ≤ 50 > 44 and ≤ 80

F >50 > 80

Capacity analysis was performed for all the signalized intersections in the City for the a.m. and p.m. peak periods, for both the current and the 2023 forecast traffic conditions, and for select non-signalized intersections. The capacity analysis worksheets have been included in the technical appendix. The resulting level of service for current traffic volumes are depicted graphically on Figures 3-2 and 3-3 while the 20 year forecast level of service are depicted on Figures 3-4 and 3-5. Level of service C or better is considered desirable. Level of service D, while less than desirable, is nevertheless generally considered acceptable in urban conditions. Locations indicating a level of service E or F were investigated for improvement strategies. The results of this analysis were used to identify locations where intersection capacity improvements may be warranted. These improvements generally consisted of the construction of additional lanes, where feasible, or change in traffic control, such as from stop sign control to roundabout or signal control.

Table 3-3 summarizes the slate of short and long term congestion mitigation projects for intersections identified as being congested under current or projected year 2023 conditions. Table 3-4 summarizes the levels of service corresponding to those intersections for both congested and mitigated conditions.



Table 3-3 Mitigation Strategies for Congested Intersections Intersection Short Range Improvement *Long Range Improvement

Shiloh and 6th Street Realigned and Installed Single Point InterchangeEB and WB widened to 6 lanes plus median, Added EB Right Turn Lane

Hollywood (Futrall St) and 6th Street Realigned and Installed Single Point Interchange, Install Traffic Signal Control

EB and WB widened to 6 lanes plus median

Garland and 6th Street No short range improvement EB and WB widened to 6 lanes plus median

Happy Hollow Rd. and 6th Street Install Traffic Signal Control EB and WB widened to 4 lanes plus median

College and Rock Street Closure No long range improvement

Maple and West Install Traffic Signal Control No long range improvement

Maple and Garland No short range improvement, Optimized Signal Timings Divert Traffic With Realignment

Wedington and Rupple No short range improvement Install Traffic Signal Control

North and Gregg Added EB, WB and SB Thru Lanes, Added SB Right Turn Lane

EB and WB widened to 4 lanes plus median

Mission and Old Wire Rd. Install Roundabout Control EB and WB widened to 4 lanes plus median

Crossover and Citizen NB and SB widened to 5 lanes No long range improvement

Crossover and Joyce NB and SB widened to 5 lanes, Added EB Right Turn Lane, Added WB Left Turn Lane, Added 2nd EB and NB Left Turn Lanes

Added NB and SB Right Turn Lane

Maple and Mission Install Traffic Signal Control No long range improvement

Rolling Hills Dr. and Old Missouri Rd. No short range improvement Install Traffic Signal Control/Roundabout

College and Rolling Hills Dr. Added NB and SB Right Turn Lanes No long range improvement

Drake and Gregg NB and SB widened to 5 lanes Extend Drake, Install Traffic Signal Control

College and Longview Added EB Right Turn Lane Install Traffic Signal Control

College and Harold St. Added WB Right Turn Lane Install Traffic Signal Control

College and Poplar St. No short range improvement Install Traffic Signal Control

Poplar and Gregg Install Traffic Signal Control No long range improvement

Sycamore and Garland Added WB Right Turn Lane Install Traffic Signal Control

Joyce and Mall Ave Added 2nd SB and WB lLeft Turn Lanes

Old Missouri and Zion Install Multiway Stop Control/Roundabout

Joyce and Private Drive Install Traffic Signal Control

Deane St. and Garland Install Traffic Signal Control

Crossover and Cliffs Install Traffic Signal Control

15th Street and Morningside Install Traffic Signal Control

Wedington Dr and Double Springs Rd. No long range improvement

School and Cato Springs Rd. No long range improvement

School and Willoughby Rd. Install Traffic Signal Control

6th Street and Finger EB and WB widened to 6 lanes plus median

6th Street and Razorback EB and WB widened to 6 lanes plus median

6th Street and School EB widened to 6 lanes plus median, WB widened to 4 lanes plus median

College and Dickson Added EB, NB and SB Right Turn Lanes, Added 2nd EB and NB Left Turn Lanes

College and Lafayette Added NB and SB Right Turn Lanes

College and Township Added SB Right Turn Lane

Maple and Leverette Added SB Right Turn Lane

North and College EB and WB widened to 4 lanes plus median

Wedington and Shiloh Added SB and EB Right Turn Lanes, Added SB Left Turn Lane

Crossover and Mission EB widened to 4 lanes plus median

Township and Crossover Added NB and SB Right Turn Lanes No long range improvement

Old Missouri and Old Wire Rd. Install Multiway Stop Control/Roundabout No long range improvement

Note: Not all intersections that received improvement were identified, rather only those intersections that exemplified a LOS of unacceptable condition prior to improvement are included in the table.

* In addition to any short range improvements



Table 3-4 Level of Service Summary for Congested Intersections

AM PM AM PM

AM Mitigated PM Mitigated AM Mitigated PM Mitigated

Existing Existing Existing Existing 2023 2023 2023 2023

LOS LOS LOS LOS LOS LOS LOS LOS

Shiloh and 6th Street D A E B F B F B

Futrall and 6th Street E A B C F A E D

Hollywood and 6th Street D A E C F A F D

Garland and 6th Street F F F F C F E F

Happy Hollow Rd. and 6th Street F A F B F B F B

College and Rock F NA A NA F NA A NA

Maple and West B A F A C A F B

Maple and Garland E E C B F NA D NA

Wedington and Rupple D D E E F A F A

North and Gregg F B E B F B F D

Mission and Old Wire Rd. E B F B E D F E

Crossover and Citizen D C F C F E F F

Crossover and Joyce F C D B F E F D

Rolling Hills Dr. and Old Missouri Rd. C C B B F B/B F B/C

College and Rolling Hills Dr. C B E C C C E D

Drake and Gregg C B F D E A F A

College and Longview E E F F F A F A

College and Harold St. C C F F C A F A

College and Poplar St. D D F F F A F A

Poplar and Gregg C A F A C A F A

Sycamore and Garland C C F E E A F A

Joyce and Mall Ave A - C - B B E D

Old Missouri and Zion B - C - C B/B F C/B

Joyce and Private Drive C - F - F A F B

Deane St. and Garland D - F - F A F A

Crossover and Cliffs C - C - F A F A

15th Street and Morningside C - D - E A E A

Wedington Dr and Double Springs Rd. D - D - F F F F

School and Cato Springs Rd. B - C - C C E E

School and Willoughby Rd. D - C - F A D A

6th Street and Finger A - C - C A F D

6th Street and Razorback C - D - C C E C

6th Street and School C - C - E C E C

College and Dickson C - D - D C F D

College and Lafayette B - C - B B E D

College and Township B - D - B B E E

Maple and Leverette A - B - B A F B

North and College C - C - C C F C

Wedington and Shiloh B - D - B A F D

Crossover and Mission B - C - B B E D

Township and Crossover D - B - F D E B

Old Missouri and Old Wire Rd. D F/B F C/B F F/B F F/C

Mission and Maple D A E A E A F A

Note: A "-" denotes no mitigation recommended

Note: Not all intersections that received improvement were identified, rather only those intersections that exemplified a LOS of unacceptable condition prior to improvement are included in the table.

Intersection



QUEUING ANALYSIS

Where vehicles are required to stop for cross traffic or opposing traffic, the possibility exists for several vehicles to form a queue, or stack behind each other. Intersection geometry should provide sufficient turn bay storage space so that queued turning vehicles will not spill back into the through lane, and block through traffic. Likewise, the turn bay ideally should be long enough so that if through vehicles are queued back from a traffic signal, a vehicle approaching the end of the queue would be able to get into the turn bay. Sometimes, this may not be practical at locations where a large volume of through vehicles could form extensive queues.

A queuing analysis was performed for all the signalized intersection approaches in the City for the a.m. and p.m. peak hours for the existing and forecast 2023 traffic conditions, and for select non-signalized intersections. A summary of the comparison of vehicle queue lengths with existing turn bay lengths for the a.m. and p.m. peak hour traffic volumes for existing and for 2023 traffic demand has been included in the technical appendix. This information will be of use to City staff as they establish the parameters for specific capital improvement projects.

City of Fayetteville, Arkansas Traffic and Transportation Study

Figure 3-2 Existing Peak Hour Intersection LOS

Chapter 3 - Traffic Analysis

Intersectioncapacity1.ppt

SignalizedLocationUnsignalized Location

PM Level of Service

Legend

B(A)AM Level of Service

33

A(A)

A(A)

C(D)A(C)

A(A)

A(A)

B(B)

F(D)

B(B)

C(E)

A(B)

A(B)

B(D)

A(A)A(B)

C(C)D(B)

A(A) B(D) B(B)

A(A)B(B)

B(C)

F(E) C(C)

B(A)

A(A)

B(B)

D(C)B(C)

E(F)

C(F)B(C)

A(A)

A(B)

C(B)

C(F)

C(F)

A(B)D(F)

C(F)

D(E)

B(A) E(F)

D(F)

D(F)

C(B)C(A)

B(C)

D(F)

B(B)C(B)

B(B)


FIGURE 3-3 Existing Peak Hour Intersection LOS


Intersectioncapacity2.ppt

Signalized LocationUnsignalized Location

PM Level of Service

Legend


34

B(B)

B(C)

C(D)

A(A)

A(B)E(C)

A(B)

A(A)

A(A)

A(A)C(C)

B(B) A(A)

C(D)

E(B)D(E)

A(C)

A(A)

D(E)

B(B)

F(F)

B(B) C(D)

B(C)

D(C)

F(F)A(B)

C(C)

A(A)

F(A)

D(E)B(F)

A(C)

A(A)

A(A)


FIGURE 3-4 2023 Peak Hour Intersection LOS


2023Intersectioncapacity1.ppt


PM Level of Service

Legend


35

A(B)

A(A)

B(D)B(E)

A(D)

F(F)

B(C)

F(F)

B(B)

C(E)

A(C)

A(B)

B(E)

A(A)A(B)

D(D)F(E)

B(A) B(F) B(B)

B(B)D(D) B(C)

F(F) C(F)

B(A)

B(A)

A(B)

B(C)C(F)

F(F)

C(F)B(C)

B(C)

A(B)

D(D)

E(F)

C(F)

A(B)F(F)

E(F)

F(F)F(F)

F(F)

F(F)

F(F)D(B)

F(F)

B(B)C(C)

B(A)

B(E)

B(C)


FIGURE 3-5 2023 Peak Hour Intersection LOS


2023Intersectioncapacity2.ppt


PM Level of Service

Legend


36

B(C)

B(E)

D(F)

A(A)

B(F)F(D)

A(B)

B(A)

B(A)

A(A)E(E)

B(B) B(B)

C(E)

F(E)F(F)

C(F)

A(A)

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C(C)

F(F)

C(C) E(E)

C(E)

F(D)

F(F)A(C)

F(F)

A(A)

F(A)

E(F)C(F)

A(A)

A(A)

A(A)



ARTERIAL LEVEL OF SERVICE

The travel time and delay surveys conducted on the arterial streets and on several select collector streets served as the primary basis for determining the level of service for each segment of arterial street corridors. The Highway Capacity Manual 2000 methodology for assigning level of service for arterial streets is based on travel speed on the arterial. The travel speed requirements to achieve an adequate level of service depend on the class of the arterial. The class of an arterial street is defined by Tables 3-5 and 3-6.

Based on the combination of these characteristics, the arterial street is assigned a class of I, II, III, or IV. Table 3-7 correlates arterial level of service with class and average travel speed.

Table 3-5 Functional and Design Categories

Functional Category Criterion

Principal Arterial Minor Arterial

Mobility function Very important Important

Access function Very minor Substantial

Points connected Freeways, important activity centers, major traffic generators

Principal arterials

Predominant trips served Relatively long trips between major points and through-trips entering, leaving, and passing through the city

Trips of moderate length within relatively small geographical areas

Design Category Criterion

High-Speed Suburban Intermediate Urban

Driveway/access density Very low density Low density Moderate density

High density

Arterial type Multilane divided; undivided or two-lane with shoulders

Multilane divided; undivided or two-lane with shoulders

Multilane divided or undivided; one way, two-lane

Undivided one-way, two-way, two or more lanes

Parking No No Some Significant

Separate left-turn lanes Yes Yes Usually Some

Signals/mi 0.5-2 1-5 4-10 6-12

Speed limit 45-55 mi/h 40-45 mi/h 30-40 mi/h 25-35 mi/h

Pedestrian activity Very little Little Some Usually

Roadside development Low density Low to medium density

Medium to moderate density

High density



Table 3-6 Urban Street Class Based on Functional and Design Categories

Functional Category Design Category

Principal Arterial Minor Arterial

High-Speed I N/A

Suburban II II

Intermediate II III or IV

Urban III OR IV IV

Table 3-7 Arterial Street Level-Of-Service Criteria

Class I II III IV

LOS Average Travel Speed (mi/hr)

A >42 >35 >30 >25

B >34-42 >38-35 >24-30 >19-25

C >27-34 >22-28 >18-24 >13-19

D >21-27 >17-22 >14-18 >9-13

E >16-21 >13-17 >10-14 >7-9

F <16 <13 <10 <7

Figures 3-6 and 3-7 depict the arterial level of service for the existing a.m. and p.m. peak periods.


Chapter 3 – Traffic Analysis

FIGURE 3-6 Existing Peak Hour Arterial LOS

Class of Major Streets

II

Legend

IIIIV

Level of ServiceAM (PM)

39

A(A)

B(C)

A(A)

B(B)

A(B)

A(A)

B(B)

A(A)

B(B)

F(B)

A(A)

C(A)

C(A)

A(A)

C(A)

A(C)

A(A)

A(A)

B(A) A(B)

B(C) A(F)

E(C) A(D)B(D)

B(A)

E(E)

B(B) A(B)

B(D)B(A)

B(C)

A(A)

C(C)

A(B)B(C)

B(A) A(A)

A(A)

A(B)

A(C)

A(B) B(B)

A(E)

A(A)

A(C)

D(F)

E(A)

B(C)

A(A)A(A)

C(C)A(D)

B(B) A(B)

A(A)C(C)

A(B)

B(C)

C(C)

A(C)A(A)

D(B) A(B)E(D)A(A)

A(D) A(B)A(B)

A(A)

A(A)

B(C)

C(C)

C(E)

B(B)D(E)A(B)

D(E)E(D)

C(D)D(F)

D(E)

E(E)

A(D) A(A)

A(A)A(B) C(C)

B(E)

C(C)

B(D) A(A)

A(A)

M:\2002-359\ppt\los1.ppt

Class of Major Streets

II

Legend

IIIIV

Level of ServiceAM (PM)



FIGURE 3-7 Existing Peak Hour Arterial LOS 40

E(E)

C(C)

F(F)

B(C)D(D)

A(A) A(A)

A(B)C(B)

E(D)

B(C)

C(C)

A(A)C(C)

C(B) E(E)

E(D)B(B) D(E)B(C)

B(B)

B(B)

A(A)A(A)

B(A)

C(C)

C(D)

C(C) C(C)

B(B) B(B)

B(E) D(F)

F(D) B(C)

D(C) A(B)

B(A) A(A)

A(A)

B(B)

A(A)

A(A)

A(A)

B(A)

C(B) C(B)

C(B)C(D)

B(B)B(B) B(B)

C(C)A(A)

A(A)A(A)

A(A) A(A)

E(D)

C(C)

D(A)B(B)

B(B) B(A)

A(A)

A(A)

B(B)

B(B)

A(B)C(C)

C(C)

M:\2002-359\ppt\los2.ppt



TRAFFIC VOLUME/STREET CAPACITY

The Highway Capacity Manual 2000 provides traffic service volumes that can be accommodated on arterial streets, depending on the number of lanes, and based on assumptions of traffic signal timings and free flow traffic speeds. The arterial streets in Fayetteville have been assigned a daily capacity to carry traffic as derived from the HCM service volumes. Figures 3-8 and 3-9 depict those streets in the Master Street Plan proposed to be arterial streets, plus the collector streets Maple, Lafayette, and Old Wire, along with their daily traffic capacity, the year 2000 daily traffic volumes, and the year 2023 daily projected traffic volumes. This comparison of traffic volumes to street capacity has provided the basis for major street widening recommendations. The expected average daily service volumes based on the number of through lanes has been correlated with level of service in Table 3-8. Level of service E is generally considered the full capacity of a street or intersection, and consequently represents severe congestion. Level of service C or better is desirable. In urban locations, level of service D is considered less than desirable, but still acceptable.

Table 3-8 Service Volumes and Level-Of-Service

Service Volume (vehicles per day) Lanes in Each Direction L.O.S. C L.O.S. D L.O.S. E

1 10,000 16,000 17,000

2 20,000 32,000 34,000

3 30,000 48,000 51,000

TRAFFIC IMPROVEMENTS

The comparison of the traffic volume to street capacity provided a basis for identifying arterial streets that will need improvement now. In addition to those arterials, other major streets have been identified as key to completing system continuity or providing infrastructure for Priority Growth Areas. The results of the intersection capacity analysis served as the basis for identifying intersections that will benefit from improvements now. Other intersections were identified by City Staff as having potential safety concerns or non conventional intersection geometry that needed to be addressed. These short range improvement locations are identified in Figures 3-10 and 3-11.

Those improvements that will be needed within the course of the next 20 years are identified in Figures 3-12 and 3-13 as long range improvements.

17,000

Legend

1(2)2023 Average Daily Traffic

2000 Average Daily Traffic

Capacity

34,00051,000



FIGURE 3-8 Traffic Volumes & Street Capacity 42

3200(8200)

4600(8600)

7000(14,700)

34,000(42,300)

18,000(26,700) 14,000

(18,700)

1500(5700)

15,000(21,100)

15,000(16,400)

17,000(22,600)

5500(7500)

9200(14,800)10,000

(10,700)11,000

(17,600)

14,000(19,700)

12,000(16,000)

27,000(28,900)

5900(12,400)

540010,0007800

(13,500)26,000(33,700)

11,000(15,400)

16,000(18,100)

13,000(23,000)

15,000(35,000)

6200(14,200)

15,000(19,700)

10,000(15,000)

14,000(21,100)

9000(11,500) 20,000

(25,500)

17,000(23,900)

6100(14,600)

8200(18,400)

16,400(36,000)

13,000(33,000)

14,000(14,000)

27,000(35,000)

12,000(18,300)

ArterialMap1.ppt

6200(9200)

8900(13,200)

900(2300)

5300

17,000

Legend

1(2)2023 Average Daily Traffic

2000 Average Daily Traffic

Capacity

34,00051,000



FIGURE 3-9 Traffic Volumes & Street Capacity 43

5500(8000) 12,900

(14,000)

5300(6700)

7000(8200)

12,000(16,400)

21,000(33,500)

15,000(24,000)

19,000(28,000)

14,000(22,500)

26,000(42,700)

6000(9800)

3200(6400)

19,000(47,800)

29,000(58,000)

6400(14,900)

24,000(52,800)

5600(8200)

5800(9800)

7800(11,800)

7100(9500)

13,000(19,700)

10,000(14,800)

11,000(13,700)

8700(18,800)

8400(11,700)

12,000(28,700)

15,000(28,000)

11,000(18,500)

4600(7600)

11,000(25,200)

10,000(24,200) 7700

(21,900)

12,000(20,300)

ArterialMap2.ppt

7000(2800)



FIGURE 3-10 Short Range Traffic Improvements

Legend

Widen to 5 Lanes Plus Trails

Widen to 3 Lanes Plus Bike Lanes

2 Lanes Street3 Lanes Street

Widen to 4 Lanes plus Median & Trails

2 Lanes in Principal Arterial R/W

Legend

Widen to 5 Lanes Plus TrailsWiden to 5 Lanes Plus Trails

Widen to 3 Lanes Plus Bike LanesWiden to 3 Lanes Plus Bike Lanes

2 Lanes Street2 Lanes Street3 Lanes Street3 Lanes Street

Widen to 4 Lanes plus Median & TrailsWiden to 4 Lanes plus Median & Trails


44Short2 10-9-03.ppt

Multiway Stop orRoundabout

Add NB & SBRight Turn Lanes

Add WB Right Turn Lane

Signal

Add WBLeft Turn Lane

Add EB Right Turn LaneAdd WB Left Turn LaneAdd 2nd EB & NB Left Turn Lane

Add EBRight Turn Lane

Realign Add NB & SBRight Turn Lanes

Add EB, WB, & SBThru LanesAdd SBRight Turn Lane

Signal or Roundabout

Add EB Right Turn Lanes

Signal andU Turn



FIGURE 3-11 Short Range Traffic Improvements

Legend






Legend






45

Add EB & WB Right Turn Lanes2nd EB, SB & NB Left Turn Lanes

Single PointInterchange

Signal

Short1.ppt

Realign

Realign

Realign

Signal Signal

Close StreetConnection

New Street

Signal

Signal



FIGURE 3-12 Long Range (2023) Traffic Improvements 46Long2.ppt

Add WB Left Turn LaneSB & NB Right Turn Lane2nd EB, NB & SB LeftTurn Lanes

Add SB & EB Right Turn LanesSB Left Turn Lane

Add SBRight Turn Lanes

Extend & Signalize

Add 2nd SB & WBLeft Turn Lanes

Roundabout, Signalor Multiway Stop

Signal

Signal

Signal

Signal

Signal

Roundabout or Signal

Legend






Legend






Realign

Close



FIGURE 3-13 Long Range (2023) Traffic Improvements

Legend






Legend






47

Add EB, NB & SB Right Turn Lanes2nd EB Left Turn Lane

Signal

Long1.ppt

Signal

Add WB & SBRight Turn Lanes

Add NB & SBRight Turn Lanes

Signal

Add EB Right Turn Lane

Add EB, NB, SB Right Turn LanesAdd 2nd EB Left Turn Lane

3. traffic analysis - nwarpcnwarpc.org/pdf/congestion management/chapter 3 - traffic...

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