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# Mobility Division

Texas A&M Transportation Institute

## Sitemaps

- [XML Sitemap](https://mobility.tamu.edu/sitemap.xml): Contains all public & indexable URLs for this website.

## Posts

- [What we are saying about the transportation effects of COVID-19](https://mobility.tamu.edu/what-we-are-saying-about-the-transportation-effects-of-covid-19/) - On March 11, 2020, the World Health Organization (WHO) declared the outbreak of COVID-19 a pandemic. Many cities and states had already announced closures and altered operating regulations, but the pace of change accelerated after the WHO announcement. It is an unsettling time for all of us, and the impacts of this pandemic will likely

## Pages

- [Home](https://mobility.tamu.edu/)
- [Urban Congestion Reports](https://mobility.tamu.edu/ucr/) - Also includes: Summary of procedures used to analyze detailed traffic data from transportation management centers. Contains the most recent trends from 52 selected cities with readily-available freeway data. For More Information Pete Koeneman (979) 317-2479 p-koeneman@tti.tamu.edu or Shawn Turner (979) 317-2481 s-turner@tti.tamu.edu
- [TESTING Texas Bicycle and Pedestrian Count Exchange (BP|CX)](https://mobility.tamu.edu/testing-texas-bicycle-and-pedestrian-count-exchange-bpcx/) - The Texas Department of Transportation teamed with TTI to create a system that allows anyone in the state collecting bicycle or pedestrian counts to import, manage, quality review, factor, and share their data with others. The Texas Bicycle and Pedestrian Count Exchange (BP|CX) completes this vision. Use the data visualization below to explore where bicycle
- [Texas Bicycle and Pedestrian Count Exchange (BP|CX)](https://mobility.tamu.edu/bikepeddata/) - The Texas Department of Transportation teamed with TTI to create a system that allows anyone in the state collecting bicycle or pedestrian counts to import, manage, quality review, factor, and share their data with others. The Texas Bicycle and Pedestrian Count Exchange (BP|CX) completes this vision. Use the data visualization below to explore where bicycle
- [Texas’ Top 100 Congested Road Segments](https://mobility.tamu.edu/texas-most-congested-roadways/) - For more information Ibrahima Tembely,Texas Department of Transportationibrahima.tembely@txdot.govph. (512) 416-4627 David Schrank,Texas A&M Transportation Instituted-schrank@tti.tamu.eduph. (979) 317-2464 Print Instructions To print any current view from the above visualization: Select "PDF" found in the EXPORT area of the right toolbar. Under "Include," select either "This View" or “Specific sheets from this dashboard," choose the options you As Texas continues to experience rapid population and economic growth and more vehicles on the road, targeted congestion-relief transportation investments are helping drivers spend less time stuck in traffic and saving Texans millions of dollars each year.
- [Archive - Urban Mobility Reports: 1999-2023](https://mobility.tamu.edu/umr/archive/) - CAUTION: Do not compare data or performance measures from different reports to identify trends. Reports by Year: 2023 2021 2019 2015 2012 2011 2010 2009 2007 2005 2004 2003 2002 2001 1999 The methodology used for the Urban Mobility Reports and the data obtained from the Federal Highway Administration and the state Departments of Transportation
- [Press Release](https://mobility.tamu.edu/umr/media-information/press-release/) - Traffic Hits Record High as Commuters Rewrite the Rush Hour The 2025 Urban Mobility Report finds traffic’s return is changing how, when and where we travel For immediate release: October 22, 2025 For more information: Jack Wenzel, (979) 317-2392, media@tti.tamu.edu Americans lost an average of 63 hours sitting in traffic in 2024 — the highest
- [Data and Trends](https://mobility.tamu.edu/umr/data-and-trends/) - In addition to using the data visualization map, you may also access the data and related trends in the forms below. Base Statistics The congestion data Excel spreadsheet (2.0MB) contains the base statistics for the 101 urban areas from 1982 to 2024. The spreadsheet also includes individual 2017 to 2024 congestion statistics for 393 other
- [Urban Areas in the Study](https://mobility.tamu.edu/umr/data-and-trends/urban-areas-in-the-study/) - In addition to the initial 101 cities covered in the Urban Mobility Report, you may also find limited data for 393 more urban areas. Open the congestion data Excel spreadsheet (2.0MB) to see your city. New this year are data for observed destination access for all urban areas. Open the destination access area Excel spreadsheet
- [2025 Urban Mobility Report and Appendices](https://mobility.tamu.edu/umr/report/) - Report 2025 Urban Mobility Report (5.1MB) Appendices Learn how we got the numbers and more in the appendices. Appendix A – Methodology (1.2MB) Appendix B – Change in Vehicle Occupancy Used in Mobility Monitoring Efforts (330KB) Appendix C – Value of Delay Time for Use in Mobility Monitoring Efforts (353KB) Appendix D – Observed Access
- [Urban Mobility Report](https://mobility.tamu.edu/umr/) - Americans lost an average of 63 hours sitting in traffic in 2024 — the highest level ever measured — according to the 2025 Urban Mobility Report. While the volume of traffic has returned, researchers found travel patterns have shifted. Delays are no longer confined to the traditional weekday rush hours.
- [Congestion Data for Your City](https://mobility.tamu.edu/umr/congestion-data/) - Interactive dashboard enabling you to explore congestion and access patterns across U.S. cities. Discover how your city compares in delay, reliability and congestion cost.
- [Answers to Many of Your Questions](https://mobility.tamu.edu/umr/media-information/answers-to-many-of-your-questions/) - Can I download the report from the internet? Yes. Link to: https://mobility.tamu.edu/umr/report/. What does “cost of congestion” mean? Value of extra travel time (which we call delay) and the extra fuel consumed by vehicles traveling at slower speeds. Travel time has a value of $24.01 per person-hour and $80.16 per truck-hour in 2024. Fuel cost
- [Glossary of Mobility-Related Terms](https://mobility.tamu.edu/umr/media-information/glossary/) - Annual Delay per Auto Commuter A yearly sum of all the per-trip delays for those persons who travel in the peak period (6 to 10 a.m. and 3 to 7 p.m.). This measure illustrates the effect of the per-mile congestion as well as the length of each trip. Commuter Stress Index Same as the Travel
- [Media Information](https://mobility.tamu.edu/umr/media-information/) - Press Release Answers to Many of Your Questions Glossary of Mobility-Related Terms
- [Directory](https://mobility.tamu.edu/directory/) - Access a list of people associated with the Mobility Analysis and Transit Mobility programs. David Schrank, Ph.D. Texas A&M Transportation Institute 1111 RELLIS Parkway Bryan, TX 77807 (979) 317-2464 D-Schrank@tti.tamu.edu Mobility Analysis Transit Mobility
- [FHWA Visualization Review](https://mobility.tamu.edu/review/fhwa/) - In cooperation with FHWA, TTI maintains data visualization information for: FHWA Freight Mobility Trends (FMT) Tool FAF VIUS Contact Phil Lasley, TTI, with questions on how to access the information.
- [Review](https://mobility.tamu.edu/review/) - TTI offers assistance in ... Learn more...
- [How We Got the Numbers](https://mobility.tamu.edu/resources/corridors/methodology/) - 2011 Congested Corridors Report: Methodology Appendix B - Detailed Methodology (1.6MB) TTI-INRIX Partnership Learn more about the TTI-INRIX partnership. TTI Press Release January 11, 2010 INRIX Press Release January 11, 2010
- [Monitoring Congested Corridors Report](https://mobility.tamu.edu/resources/corridors/) - 2011 Congested Corridors Report The inaugural 2011 Congested Corridors Report is the first nationwide effort to identify reliability problems at specific stretches of highway responsible for significant traffic congestion at different times and different days. Analyses are performed along 328 specific (directional) freeway corridors in the United States. These corridors include many of the worst
- [Colorado’s Most Congested Roadways](https://mobility.tamu.edu/colorados-most-congested-roadways/) - Print Instructions To print any current view from the above visualization: Select "Download" found in the bottom right-hand corner, then select PDF. Under Content, select "Sheets in Dashboard," choose the options you wish to have printed, and select "Export" (Note that the default is that all are selected, so clicking on an option deselects the
- [Contact the COMPAT Team](https://mobility.tamu.edu/contact-compat-team/)
- [The Keys to Estimating Mobility in Urban Areas](https://mobility.tamu.edu/resources/estimating-mobility/) - There are several keys to developing and applying mobility measures that are technically useful and generally understandable. Travel time measures are relatively easy to comprehend, but they have not always been used because of data concerns, mandated reporting practices, and other issues. Travel time and speed measures can serve many different uses, communicate to many
- [Mobility Monitoring Program](https://mobility.tamu.edu/mmp/) - The Mobility Monitoring Program is no longer an active program. If you are not automatically taken to our related section "FHWA Urban Congestion Reports," please select the link below. http://mobility.tamu.edu/project/urban-congestion-reports/
- [Congestion Data for Your Corridor](https://mobility.tamu.edu/resources/corridors/congestion-data/) - The map has dots linking to PDF files that contain the Congested Corridors Statistics—Buffer Index, Planning Time Index, Travel Time Index, Delay per Mile, Congestion Cost. If an individual urban area is listed, it has at least 5 corridors included in the study. If a state is listed, it has corridors from urban areas within
- [Summary Tables – Tables of Rankings](https://mobility.tamu.edu/resources/corridors/summary-tables/) - Tables 1 through 8 contain the “Top 40” for each category. Appendix A tables, A-1 and A-2, contain the ranking of all 328 corridors for Table 1 and Table 2. The tables are available in PDF format. Table 1. Reliably Unreliable (Top 40) Table 2. Congestion Leaders (Top 40) Table 3. 3-Cup Mornings (Top 40)
- [2011 Congested Corridors Report and Appendices](https://mobility.tamu.edu/resources/corridors/report/) - You may view the 2011 Congested Corridors Report (1.6MB), including appendices, online. What are the purposes of this report? We show congestion levels along specific corridors — the level where transportation improvements are determined. The very detailed hour-by-hour data shows when and where congestion occurs. We can suggest how much extra “buffer” time to allow.
- [Answers to Many of Your Questions](https://mobility.tamu.edu/resources/corridors/media-information/faq/) - What is the take away message? This is the first report about travel time reliability performance measures at a national level. The report describes congestion problems in 328 seriously congested corridors in the US over a variety of times – all day, morning and evening peaks, midday, weekends. This report shows that much of our
- [Media Information](https://mobility.tamu.edu/resources/corridors/media-information/) - Press Release Answers to Many of Your Questions
- [Press Release](https://mobility.tamu.edu/resources/corridors/media-information/press-release/) - Researchers identify the nation’s most congested corridors in first nationwide effort to quantify travel reliability problems For release: 12:01 a.m. CST, Tuesday, November 15, 2011 For more information: Bill Eisele Research Engineer Texas Transportation Institute (979) 845-8550 David Schrank Associate Research Scientist Texas Transportation Institute (979) 845-7323 Holiday travelers will have a better idea of
- [Monitoring Urban Freeways in 2003: Current Conditions and Trends from Archived Operations Data](https://mobility.tamu.edu/resources/fhwa-hop-05-018/) - December 2004 Report Number: FHWA-HOP-05-018 Prepared for:U.S. Department of TransportationFederal Highway AdministrationOffice of Operations Prepared by:Texas Transportation InstituteandCambridge Systematics, Inc. Under contract to:Battelle505 King AvenueColumbus, Ohio 43201 Annual Summary Report The annual summary report is available in PDF format. The report is also available in HTML format by clicking on the individual report chapters to
- [Resources](https://mobility.tamu.edu/resources/)
- [5. Recommendations](https://mobility.tamu.edu/resources/fhwa-hop-05-018/recommendations/) - Promote Local Use of Archived Operations Data and Performance Measures In the long run — especially as many more cities deploy TMCs and coverage for existing systems expand — a national performance measurement program will benefit from increased local involvement in archiving and use of operations data. As more local applications are developed, there will
- [Detailed Information for each City](https://mobility.tamu.edu/resources/fhwa-hop-05-018/appendices/) - Individual appendices to the report, available in PDF format, include more detailed performance information for each city. Albany, NY Atlanta, GA Austin, TX Baltimore, MD Charlotte, NC Cincinnati, OH/KY Dallas, TX Detroit, MI El Paso, TX Houston, TX Los Angeles, CA Louisville, KY Milwaukee, WI Minneapolis-St. Paul, MN Orange County, CA Philadelphia, PA Phoenix, AZ
- [4. Major Findings and Conclusions](https://mobility.tamu.edu/resources/fhwa-hop-05-018/findings/) - This chapter summarizes the major findings and conclusions from the fourth year of the Mobility Monitoring Program. To date, this Program has gathered and analyzed archived traffic detector data from 2000 through 2003. However, this fourth year provided the first opportunity to analyze more than two years of annual trends for more than 20 cities.
- [3. Data, Analysis Methods, and Performance Measures](https://mobility.tamu.edu/resources/fhwa-hop-05-018/data/) - This chapter provides documentation on the archived traffic detector data as well as the analysis methods used to process and summarize the data. The definition and calculation procedures for the performance measures reported in the Mobility Monitoring Program are also included. The chapter is organized as follows: Participating cities and their archived data — presents
- [2. Background](https://mobility.tamu.edu/resources/fhwa-hop-05-018/background/) - This chapter contains background information on the Mobility Monitoring Program, and compares and contrasts this Program with other national performance monitoring programs. This chapter also highlights several examples of state and local performance monitoring programs. National Performance Monitoring Programs There are three programs at a national scale that attempt to measure city-level traffic congestion, and
- [1. Introduction](https://mobility.tamu.edu/resources/fhwa-hop-05-018/introduction/) - Objectives of the Mobility Monitoring Program The Mobility Monitoring Program is an effort by the Federal Highway Administration (FHWA) to track and report traffic congestion and travel reliability on a national scale. The program has two primary objectives: Monitor traffic congestion levels and travel reliability trends using archived traffic detector data; and Provide "proof of
- [Summary](https://mobility.tamu.edu/resources/fhwa-hop-05-018/summary/) - What is the Mobility Monitoring Program? The Mobility Monitoring Program is an effort by the Federal Highway Administration (FHWA) to track and report traffic congestion and travel reliability on a national scale. The program has two primary objectives: Monitor traffic congestion levels and travel reliability trends using archived traffic detector data; and Provide "proof of
- [Acknowledgements](https://mobility.tamu.edu/resources/fhwa-hop-05-018/acknowledgements/) - In addition to the primary sponsorship of the Federal Highway Administration (FHWA), the authors gratefully acknowledge the following agencies that participated in the fourth year of the Mobility Monitoring Program by providing archived traffic detector data: Albany: New York State Department of Transportation (DOT) Atlanta: Georgia DOT Austin: Texas DOT Baltimore: University of Maryland in
- [Table of Contents](https://mobility.tamu.edu/resources/fhwa-hop-05-018/table-of-contents/) - Acknowledgements Summary What is the Mobility Monitoring Program? What performance measures are used? What data are used? Introduction Objectives of the Mobility Monitoring Program Report Overview New Report Elements Additional Information and City Reports Background National Performance Monitoring Programs Mobility Monitoring Program Urban Congestion Reporting Program Urban Mobility Study Comparison of Programs Other Related National

## Soliloquy Sliders

- [home](https://mobility.tamu.edu/?post_type=soliloquy&p=18)
- [team](https://mobility.tamu.edu/?post_type=soliloquy&p=52)

## Projects

- [Mobility Analysis & System Transportation Efficiency Research](https://mobility.tamu.edu/project/mobility-analysis-and-system-transportation-efficiency-research/) - Over the last 25+ years, mobility analysis has changed dramatically and TTI has consistently been at the leading edge, working with sponsor states to improve the practice. Topics of the MASTER study have included evaluating data and data sources, developing new performance measures, refining calculation procedures, conducting sensitivity analyses, exploring target-setting, communicating and visualizing performance
- [Texas' 2030 Committee](https://mobility.tamu.edu/project/texas-2030-committee/) - The 2030 Committee was originally formed in May 2008 by Texas Transportation Commission Chair Deirdre Delisi, at the request of Texas Governor Rick Perry. This volunteer committee of experienced and respected business leaders was initially charged with providing an independent, authoritative assessment of the state's transportation infrastructure and mobility needs from 2009 to 2030. The
- [Mobility Improvement Strategies](https://mobility.tamu.edu/project/mobility-improvement-strategies/) - The tool does two different things: helps narrow down a long list of strategies to a more manageable size while making them more relevant to the area or problem trying to be solved. Then, the tool shows how each strategy is related or interconnected with the others.
- [Kyle Field Gameday Transportation Plan](https://mobility.tamu.edu/project/kyle-field-gameday-transportation-plan/)
- [Freight Mobility](https://mobility.tamu.edu/project/freight-mobility/) - Metropolitan Freight Transportation Tools to Facilitate Implementation of Effective Metropolitan Freight Transportation Strategies Publication: Transportation Research Board's National Cooperative Highway Research Program (NCHRP) Research Report 897 Authors: Bill Eisele, Mario Monsreal, Shuang Guo, Seckin Ozkul, Behzad Karimi Varzardoliya, Kristine Williams, Fatemeh Ranaiefar, Michael Kao, and Susan Atherton Published: 2018 Provides transportation practitioners and decision makers
- [Bush / Wellborn Interchange Planning](https://mobility.tamu.edu/project/bush-wellborn-interchange-planning/) - The existing George Bush Drive / Wellborn Road intersection in College Station, Texas, which has not been improved in more than 20 years, is no longer able to efficiently handle the growing number of travelers. Congestion and long queues develop every week day over several hours during peak travel periods and Texas A&M University class-change
- [Big Data and Machine Learning Analytics](https://mobility.tamu.edu/project/big-data-and-machine-learning-analytics/) - TTI’s Travel Survey and Passive Data research team are leaders in the integration of passive data from GPS connected vehicle data and Location Based Services (LBS) data with transportation planning practices. The team’s efforts focus on data fusion of these data sets with traditional survey and aggregate data sources. Increasingly machine learning methods are implemented
- [Traffic Congestion & Reliability](https://mobility.tamu.edu/project/traffic-congestion-and-reliability-trends-and-advanced-strategies-for-congestion-mitigation/) - Mitigating congestion is a high priority for the Federal Highway Administration, which has established congestion mitigation as a key focus area. This report supports this effort by providing a review of congestion issues and solutions in the United States. The emphasis of the report is on measuring trends in travel time reliability and making travel
- [Mobility/Reliability Research](https://mobility.tamu.edu/project/mobility-reliability-research/) - Travel Time Reliability Estimating Freeway Route Travel Time Reliability from Data on Component Links and Associated Cost Implications Estimating Freeway Route Travel Time Reliability from Data on Component Links and Associated Cost Implications - Online Article Publication: International Journal of Urban Sciences Author: Kartikeya Jha, John P. Wikander, William L. Eisele, Mark W. Burris, and
- [Smart Growth Trip Generation](https://mobility.tamu.edu/project/smart-growth-trip-generation/) - TTI was contracted to produce a validated and improved estimation method and a user-friendly tool to more accurately estimate trip generation for use in determining proper transportation improvements for smart growth developments in California and beyond. To improve the accuracy of the trip generation estimation model previously developed, this project collected trip generation data at
- [Port Fluidity Performance Measurement](https://mobility.tamu.edu/project/port-fluidity-performance-measurement/) - Journal Article Developing and Implementing a Port Fluidity Performance Measurement Methodology using Automatic Identification System Data Publication: Transportation Research Record: Journal of the Transportation Research Board Authors: C. James Kruse, Kenneth N. Mitchell, Patricia K. DiJoseph, Dong Hun Kang, David L. Schrank, and William L. Eisele Published: September 2018 This paper covers AIS data inputs,
- [Traffic Signal Performance Measures Using Crowd-Sourced Data](https://mobility.tamu.edu/project/evaluating-regional-traffic-signal-performance-measures-using-crowd-sourced-data-in-2021-urban-mobility-report/) - Traffic signal performance measures have historically been more difficult to quantify than other mobility measures, but new datasets obtained from crowdsourced data have improved the ability of users to quantify traffic signal performance measures at statewide, urban area, and corridor levels without the installation and maintenance costs of detection and enhanced signal system equipment beyond
- [Texas Freight Fluidity](https://mobility.tamu.edu/project/texas-freight-fluidity/) - Authors: Nicole Katsikides, Bill Eisele, Mario Monsreal, Jason Wallis, and William HwangPublished: July 2021 This guidebook is for transportation planners, policymakers, and system operators to help in understanding what freight fluidity is and illustrate the importance of the information freight fluidity provides. This guidebook aims to compel practitioners to want to know about freight fluidity
- [Urban Mobility Report](https://mobility.tamu.edu/project/urban-mobility-report/) - TTI’s 2025 edition uses crowdsourced data from INRIX on urban streets and highways, along with highway inventory data from a Federal Highway Administration database. The report was sponsored by the Texas Department of Transportation. For a nationwide interactive map of congestion conditions: Urban Mobility Report Website.For dozens of ways to address roadway gridlock: How to
- [Texas’ Top 100 Congested Road Segments](https://mobility.tamu.edu/project/texas-most-congested-roadways/)
- [Pedestrian and Bicyclist Research](https://mobility.tamu.edu/project/pedestrian-and-bicyclist-research/) - TxDOT Pedestrian and Bicyclist Count Data Program TTI has worked with the Texas Department of Transportation (TxDOT) since 2016 to improve the availability and quantity of pedestrian and bicyclist count data in Texas. The most visible product of this work has been a statewide database called the Texas Bicycle and Pedestrian Count Exchange, which is
- [WSDOT Creating Interactive Reports](https://mobility.tamu.edu/project/wsdot-creating-interactive-reports/)
- [Transportation System Management and Operations for Freight](https://mobility.tamu.edu/project/transportation-system-management-and-operations-tsmo-for-freight/) - With the emergence of connected and automated vehicle (CAV) telecommunications, TSMO strategies fit right in by making the best use of opportunities to coordinate freight movement and modal infrastructure in highly efficient ways. Some of TTI’s state-of- the-art research capabilities include: CAV Technology Leading CAV technology efforts with the Texas Department of Transportation (TxDOT) as
- [National Performance Management Research Data Set](https://mobility.tamu.edu/project/national-performance-management-research-data-set-npmrds/) - The FHWA has acquired a national data set (called NPMRDS) of average travel times on the National Highway System for use in its performance measures and management activities. TTI is a part of the NPMRDS project team and provides geospatial data integration (i.e., GIS conflation) services. In particular, TTI conflates selected HPMS attributes onto the
- [Emerging Data and Methods](https://mobility.tamu.edu/project/emerging-data-and-methods-in-transportation-planning-survey-applications/) - Understanding Bias Emerging big data sources unlike traditional surveys come with their own biases, which could be distinct across space, time and socio-demographics. This is because, these data sources are more of a convenience sample heavily influenced by the purpose of software application generating it, from which it is derived. Thus, it makes them more
- [Bicycle and Pedestrian Count Exchange](https://mobility.tamu.edu/project/texas-bicycle-and-pedestrian-count-exchange/)
- [Visualizing Travel Patterns Using Passive Data](https://mobility.tamu.edu/project/visualizing-travel-patterns-using-passive-data/) - Using data analysis and interactive reporting/presentation techniques in R, Python, and Jupyter Notebooks, the team is able to relay results from analyses quickly as projects progress. The team has also developed a number of skills for visualizing origin-destination characteristics and travel patterns from passive data and roadway networks, including interactive graphics (MAG External Travel Study)
- [Mobility Analysis Visualization Tools](https://mobility.tamu.edu/project/mobility-analysis-visualization-tools/) - Congestion Management Process Analysis Tool The Congestion Management Process Analysis Tool (COMPAT) is a web-based product that allows the user access to annual traffic congestion statistics on the majority of roads in an individual Texas metropolitan area. COMPAT is designed to help local agencies such as metropolitan planning organizations monitor traffic congestion on area roadways
- [Mobility Investment Priorities](https://mobility.tamu.edu/project/mobility-investment-priorities/) - Traffic congestion in Texas is choking our highways and choking our economy, making it harder to buy what we need and harder to keep or find a job. Congestion in cities not only costs Texans billions in lost time and wasted fuel, but also robs us of time we would rather spend with our family
- [Colorado's Most Congested Roadways](https://mobility.tamu.edu/project/colorados-most-congested-roadways/) - Print InstructionsTo print any current view from the above visualization: Select "Download" found in the bottom right-hand corner, then select PDF. Under Content, select "Sheets in Dashboard," choose the options you wish to have printed, and select "Export" (Note that the default is that all are selected, so clicking on an option deselects the item).
- [Performance Based Planning and Programming](https://mobility.tamu.edu/project/performance-based-planning-and-programming/) - The Mobility Division develops and delivers Performance Based Planning and Programming training and workshops to MPOs and state DOTs to assist them in addressing federal requirements. The training and workshops include creating appropriate goals, objectives, performance measures, and performance targets that provide accountability and transparency in the transportation planning and programming processes. The training and
- [Urban Congestion Reports](https://mobility.tamu.edu/project/urban-congestion-reports/) - Also includes: Summary of procedures used to analyze detailed traffic data from transportation management centers. Contains the most recent trends from 52 selected cities with readily-available freeway data. For More Information Pete Koeneman (979) 317-2479 p-koeneman@tti.tamu.edu or Shawn Turner (979) 317-2481 s-turner@tti.tamu.edu
- [Mobility Monitoring in Small to Medium-Sized Communities](https://mobility.tamu.edu/project/mobility-monitoring-in-small-to-medium-sized-communities/)
- [Congested Corridors Report](https://mobility.tamu.edu/project/congested-corridors-report/) - The 2011 Congested Corridors Report is the first nationwide effort to identify reliability problems at specific stretches of highway responsible for significant traffic congestion at different times and different days. Analyses are performed along 328 specific (directional) freeway corridors in the United States. These corridors include many of the worst places for congestion in the
- [Truck Drivers’ Routing Decisions](https://mobility.tamu.edu/project/truck-drivers-routing-decisions/) - Evaluating the Impact of Real-Time Mobility and Travel Time Reliability Information on Truck Drivers’ Routing Decisions Publication: Transportation Research Record: Journal of the Transportation Research Board Authors: Xiaoqiang Kong, William L. Eisele, Yunlong Zhang, and Daren B. H. Cline Abstract The research analyzed 14,538 global positioning system devices recording trips on the I-495 crossing through

## Categories

- [Uncategorized](https://mobility.tamu.edu/category/uncategorized/)
- [Moving People](https://mobility.tamu.edu/category/moving-people/)
- [Moving Freight](https://mobility.tamu.edu/category/moving-freight/)
- [Transportation Data](https://mobility.tamu.edu/category/transportation-data/)
- [Reporting & Visualization](https://mobility.tamu.edu/category/reporting-and-visualization/)
- [Metro State Planning](https://mobility.tamu.edu/category/metro-state-planning/)