Peer Exchange Workshop on the "Perfect World of Measuring Congestion"
Workshop Summary Report

PERFECT WORLD FOR MEASURING CONGESTION

The morning session of December 17th focused on attendee perspectives regarding what the perfect world of congestion measurement might look like. The Operations Performance Management Capability Maturity Model (OPMCMM) (presented in white paper #1 (see Appendix C)) was used to facilitate the discussion.

Five prevalent themes emerged that workshop attendees would like to see in a “perfect world” of measuring congestion for operations:

1. Flexible Decision-Making Framework: Public-agency transportation staff are often inundated with questions from varied stakeholders who have specific needs or decisions to make. The perfect world will have a flexible decision-making framework that is suitable for communicating to several audiences – travelers, operators, planners, and political/decision-makers.
2. Automated Monitoring at all Geographic Levels: The perfect world will have monitoring everywhere for system needs, but allows for filtering out specific/local transportation project/program improvements. This continuous multimodal monitoring would provide benefit-cost information for specific projects (rural or urban), and allow automated report creation.
3. Data Consistency: There is a need for consistency in data set formats within and across agencies. The perfect world will have consistency in data formats to improve understanding of the data.
4. Measures and Methods Consensus: In some urban areas and states, there is a difference of opinion on performance measures, thresholds (to define congestion), appropriate targets for the measures, calculation procedures and assumptions used. The perfect world will have consensus on the measures and calculation methods.
5. Fusion of Mode-Specific Datasets: Thorough transportation decision-making requires mode-specific data. The perfect world will have a fusion and redundancy of mode-specific data sets across roadway facilities for decision-making in a multimodal and multi-agency environment.