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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 Fayettevilles 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.

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

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    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.

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

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    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 Citys 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.

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    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

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