Freight Performance Measurement - FPM

1. Freight Performance Measurement - FPM Talking Freight Crystal Jones FHWA Office of Freight Management and Operations 22 April 2010

2. FHWA - Office of Freight Management and Operations • Understand the magnitude and geography of freight moving on the nation’s transportation system, including international freight • Develop strategies, analytical tools, institutional arrangements, and professional capacities for all levels of government to address freight movement • Understand and promote the economic benefits of freight transportation • Encourage innovative freight technology & operations • Enforce commercial vehicle size and weight requirements

3. Themes GAO Identified inReauthorization Proposals Define a federal role in freight goods movement Incorporate performance & accountability Promote better management of existing assets Use multiple funding sources Link transportation policy & funding to environment and energy sectors

4. Public Sector Transportation Decisions Data are needed to answer these questions: Which key corridors and gateways should I make investment in to prepare for the future?What is the public benefit or good in in making an investment? Infrastructure Investment How does freight movement affect congestion? How does congestion, expected and unexpected delay, and cost affect freight movement? System Performance and Operations Policy & Regulation How should funding be allocated among a myriad of transportation goal areas and programs?

5. Freight Data Challenges • Difficulty having Harmonized definitions of freight transportation terms like: • Commodity Classifications • Mode Definitions • Often Available Data is used as a proxy for the Needed Data • Flow of trade used as a proxy for geographic flows • Value to Weight Ratios used for Export Weight • Lack of Authoritative Data Sources and Management Agencies • Compatible & quality data from many different transportation and trade systems

6. Public‐Private Data Partnerships • Information and data on freight movement mostly resides with the private sector • Public Sector Transportation Agencies and their Research partners need access to this data • Public‐Private data sharing partnerships offer an opportunity to gain access to information that accurately reflects geographical freight flows, commodity flows, and freight system performance

8. FHWA Goals System Performance National Leadership Corporate Capacity Program Delivery Leadership FHWA leads in developing and advocating solutions to national transportation needs. Federal Highway Programs are effectively and consistently delivered through successful partnerships, value-added stewardship, and risk-based oversight. The Nation’s highway system provides safe, reliable, effective, and sustainable mobility for all users. Organizational resources are optimally deployed to meet today’s and tomorrow’s missions. FHWA Strategic Plan

9. Improving System Performance: A Common Area of Interest • Increase capacity • Improve Operations • Work Zones • Incidents • Bottlenecks • Trucking Parking • Garner support for freight funding • Projects of National and Regional Significance • Coordinated Border Infrastructure Program

10. Freight Performance Measures (FPM) • Started in 2003 • Contractual Relationship Between FHWA and ATRI • ATRI Contractual Arrangements and Non Disclosure Agreements with Vendors/Data Providers

12. FPM Data Application – University Case Studies • Portland State • University of Minnesota • Texas Transportation Institute • Multimodal Freight Transportation Group • Texas Transportation Institute • Transportation Operations Group • University of Wisconsin

13. Portland State University Analysis of the Impacts of Congestion on Freight Movements in the Portland Metropolitan Area Prepared by: Nikki Wheeler and Miguel Andres Figliozzi Developed a methodology to analyze the impacts of recurring and non-recurring congestion on commercial vehicles traveling in and around the Portland metropolitan area Utilized GPS data from commercial trucks provided by FHWA/ATRI, corridor travel-time loop data from the Oregon DOT and archived incident data along I-5 Grouped commercial vehicles into two general categories for analysis: Through Trucks Local Trucks

14. Portland State University Through truck data were used for the analysis of both recurring and non-recurring congestion Recurring congestion Rush-hour related congestion Loop sensor data tend to underestimate the impact of congestion on trucks Non-recurring congestion From the analysis of a few incidents loop sensor data underestimated the impact of congestion on trucks Trucks making local network movements within vicinity of incident were shown to present a bias in truck speed data More through truck data will lead to improved freight specific performance measures

15. University of Minnesota Using Archived Truck GPS Data for Freight Performance Analysis on I-94/I-90 from the Twin Cities to Chicago Prepared by: Chen-Fu Liao Freight performance was analyzed to compare truck travel time with respect to duration, reliability and seasonal variation Utilized truck GPS data from FHWA/ATRI and general traffic data from state DOT Travel Time Index (TTI) - Used to measured the level of congestion Buffer Time Index (BTI) - Used to measure the travel time reliability Analyzed speed and volume variation by time of day and location Truck stop location, duration and destination inference

16. Texas Transportation Institute Travel Speed Estimation along I-35 from Laredo to San Marcos Texas Prepared by: Qing Miao and Bruce Wang • I-35 is a major freight corridor for both regional and international trade • FHWA/ATRI provided raw freight data for March 2009 • TTI removed records that: • Had time intervals greater than 15 minutes • Indicated long term parking • Indicated business operations (pickups and deliveries)

17. Texas Transportation Institute • The average speed was calculated for each of the 26 corridor segment • The lowest speeds occurred around the San Antonio metropolitan area • The highest speeds occurred on the interstate between the San Antonio and Laredo metropolitan areas

18. Texas Transportation Institute Analyzing the Feasibility of Integrating Truck GPS Data into the Border Crossing Information System (BCIS) Prepared by: Rajat Rajbhandari • Analyzed methods of integrating freight performance measures provided by FHWA and ATRI into the BCIS database • Utilized raw freight data for the El Paso and Laredo border crossing areas • Virtual geographic zones were created over roadways which allowed TTI to estimate travel times on segments in and out of the Mexico and US inspection stations

19. Texas Transportation Institute • Virtual zones over roadways leading to the World Trade Bridge • Only the two months with the highest number of truck positions were used in the analysis • Analysis was ultimately only conducted for the World Trade Bridge due to the higher number of truck positions • Daily average wait times were calculated; additional data would be needed to calculate wait times on an hourly basis

20. University of Wisconsin Freight Resiliency Performance Measures Prepared by: Teresa M. Adams, Edwin Toledo-Duran, and Ravi T. Pavuluri Resiliency is the capacity of a system to absorb disruption impacts and quickly recover Resiliency performance measures can be used to understand vulnerable points in transportation networks Two non-recurring weather related events were examined using data provided from FHWA/ATRI for the corridor between Hudson and Beloit, WI A severe winter storm in February 2008 A series of tornadoes followed by heavy rain in June 2008 Truck counts and average speed prior to, during and after each event were used to illustrate two resiliency measures Robustness – ability to withstand disasters without significant performance loss Rapidity – capacity to restore functionality

21. University of Wisconsin Example: Speed resiliency on the Janesville to Beloit section as affected by the February 2008 snow event (speeds before, during and after) The resiliency triangles show: How much loss the system had How much time the system took to reach its poorest performance How much time the system took to recover While travel speeds were affected in both directions, the westbound traffic saw a more significant decrease in speed (31 mph vs. 18 mph)

22. Lessons Learned The FHWA Experience

23. Getting Started • Knowledge of regulations that can restrict or facilitate access to data • Time and patience to identify and cultivate the right organizations/people • Careful think through procedures for handling data (collection, storage, processing analysis)

24. Why Private Sector May Say “No” • Afraid of being burned by bad publicity or regulation • Preparing the data will burden an already overworked staff • Worried about mishandling or improper release of the data • Source data is has to be modified to meet needs • Government –Big Brother

25. Compelling the Private Sector to Say “Yes” • Quid pro quo • Examples of how the partnership could produce benefits to freight transportation (not been harmed) • Assurance any burden will be on “you” not them • Peer pressure: other “Countries, states, … already have these partnerships in place..”

26. Industry Views on Freight Data Sensitivity • In Order… • Civil Litigation / Trial Lawyers • Subpoenas / Discovery • Competitive / Proprietary Access • Government Access • I

27. Freight Data Compendium

28. www.freightperformance.org Short Demo

29. Timeliness: up-to-date Accuracy Correct data definitions – unambiguous, clear, consistent Definitions are harmonized-international, national, state, local for planning, operations and other transportation functions Completeness – limit missing values Relevant Obtainable Format and presentation of data is appropriate, understandable & re-useable The End State-- Quality Freight Data

30. QUESTIONS??? CRYSTAL.JONES@DOT.GOV 202-366-2976