01043948

Component

The Lexington area is a medium sized community, located in the north central portion of Kentucky. Lexington has had its fair share of congestion scattered throughout the city. Until recent efforts, it has been difficult to qualify, quantify or give the extents of the problem-congested areas. Without this information, it has been difficult to rank projects for improvement. This report is part of a Congestion Management System (CMS). The following actions are identified as part of the CMS work plan: Formulation of performance measures applicable to all modes; Methods to monitor and evaluate conditions of the transportation system; Identification of alternative actions to address areas where congestion problems are most severe; Assessment and implementation of cost-effective traffic congestion mitigation strategies to relieve current or projected levels of congestion; and Evaluation of the impact of the congestion mitigation strategies implemented. To this end, a Global Positioning System (GPS) receiver was combined with a Data Storage Unit to capture positional data, store it, and plot it on a map to determine the location and severity of congestion along corridors in the MPO area. A number of MPO staff and volunteers were recruited to drive on the arterials leading into downtown Lexington. The equipment produced the following data: date, time, latitude, longitude and speed. When these points were plotted on a map, one could tell where they were relative to crossing streets. All of the data together made it possible to determine the location and length of delays. When the data from all ten morning and evening runs were combined and plotted against the cumulative distance, it was possible to calculate the average speed over quarter mile distances. It was also possible to identify areas of congestion. Congestion categories were based on average speeds ranked by three levels. This system can also provide information on intersection delay. For example, it can provide information on the probability of being stopped and the amount of time that one can expect to be delayed if stopped. This portion of the report also deals with the components of Run Time. Simply put: Run Time = Driving time + Intersection Delay + Other Delay. The relationship of Run Time to Driving Time can be expressed as Run Time divided by Driving Time, and is called the Travel Rate Index (TRI). The Texas Transportation Institute (TTI) developed this concept as a way to measure congestion. This measure was used as a way of comparing the amount of congestion.

01043941

English

13p

2004

9th National Conference on Transportation Planning for Small and Medium-Sized Communities

CD-ROM

Illustrations (1) ; Maps; Tables (6)

Alternatives analysis; Congestion management systems; Global Positioning System; Impacts; Intersections; Medium sized cities; Monitoring; Performance measurement; Stopped time delays; Strategic planning; Traffic congestion; Traffic delays; Traffic mitigation; Travel time

Lexington (Kentucky)

Highways; Planning and Forecasting; I72: Traffic and Transport Planning

TRIS, TRB

Mar 9 2007 1:16PM

• "What Do 3rd Graders and Volunteer Fire Chiefs Have in Common?": Public Outreach Experience on Planning Studies in Bowling Green, KY
• A Spatial Economic Model to Forecast External Trips in Small Communities
• Accomplishing Alternative Access on Major Transportation Corridors
• Addressing Rural Development Needs with Transportation Corridor Improvements
• Applications of TRIMM for Small and Medium Communities
• Congestion Mitigation Resources & Strategies for Arizona's State Highway System
• Crash Analyses of Raised Medians and Driveway Density: How Access Management Makes Communities Safer
• Duluth Urbanized Area Growth Impact Study
• Duluth-Superior Wayfinding Plan
• Economic Development Highways Initiative: Lessons Learned, and a Framework in the Sky
• Evaluating the Impacts of a New Bypass Segment Using a Travel Demand Model
• Evaluating the Impacts of Service Changes for a Mid-Size Transit System: Case Study of Columbia, South Carolina
• Four Decades of Travel Modeling and Forecasting in North Carolina--Lessons Learned
• Go for Health! Partnership-Supporting the Link Between Transportation Choices and Routine Physical Activity
• Integrating Multi-Modal Transportation into the Development Review Process
• Level of Service Analysis for Two-Lane Uninterrupted Flow Facilities in Developed Areas
• Linking Land Use and Transportation Planning in Aquidneck Island, RI: A Regional Perspective
• Linking Transportation & Economic Vitality; Kalamazoo, Ml
• New Digital Imaging Systems for Small and Mid-Sized Metropolitan Areas
• Regional Transportation Impact Fees as a Viable Financial Strategy in Growing Communities
• Roadway Project Prioritization for Ada County Highway District's Five-Year Work Program
• Safe Routes to School Through Safe Communities: Results of a Community Planning Grant Program in California
• Should Larger Time Penalties Be Applied for Modeling Internal-External Trips?
• Small and Medium-Sized Communities and the University Transportation Centers Program — Public/Academic Partnerships That Work!
• Small City Funding Partnerships: A Report from Washington State
• Small Urban Area Travel Demand Modeling in Oregon
• The 2002 Parkersburg West Virginia Household Travel Survey - What Went Right and What Went Wrong
• The Return of the Streetcar — An Experience from Middle America
• The Successful Implementation of a Quiet Rail Project
• TransCAD Tools for Managing Network Data
• Transportation Planning - Changes in North Carolina
• Transportation Utility Fees: The Oregon Experience
• Using the Principles of NEPA in Long-Range Planning to Improve Transportation Decision-Making
• Variations in Hispanic Travel Based on Urban Area Size