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Beyond Gee-Whiz Statistics:

Beyond Gee-Whiz Statistics:. Guiding Transportation Investments with Transportation System Performance Measures. presented by Richard Margiotta, Principal Cambridge Systematics, Inc. November 6, 2003. Presentation Overview. Why Bother With Performance Measures? Where We’ve Been

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Beyond Gee-Whiz Statistics:

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  1. Beyond Gee-Whiz Statistics: Guiding Transportation Investments with Transportation System Performance Measures • presented by • Richard Margiotta, Principal • Cambridge Systematics, Inc. • November 6, 2003

  2. Presentation Overview • Why Bother With Performance Measures? • Where We’ve Been • Advances in Metrics and Data • Opportunities for Performance Measures to Guide Investment -- Focus on Operations investments

  3. Congestion Performance: Why Bother? • Sound Business Practice • Private sector has embraced performance measures as a way to: • Better serve customers • Assess return on investment • “Know where you are before you decide where to go” • Use of Performance Measures Becoming More Widespread and Accepted as Best Practice • Well established in pavement and bridge management • Service-oriented measures increasingly being used in State and MPO Long Range Plans

  4. Why Bother? (cont.) • Accountability • Broader customer base for performance measures • Decision-makers and public becoming increasingly more interested in “how are we doing?” • Becoming easier to do with new technologies • Challenges: • How to apply concepts worked out in private sector and transportation planning to real-time Operations • Moving beyond simple reporting of trends

  5. Where We’ve Been • Performance measures have always been used to some degree in transportation planning, but at a simplified scale… • V/C, travel time/delay studies • … But suffer from data problems • Indirect measurement (traffic volumes as a surrogate) • Travel demand forecasting models • Small samples, infrequent surveys

  6. ADVANCES IN DATA AND METRICS

  7. What Are We Measuring? • Congestion • What happens on facilities • Mobility • What happens to users -- how they experience the transportation system (trips) • Accessibility • Interaction of transportation system and activities (opportunities) • Congestion and Mobility can use similar metrics

  8. Metrics for Performance Monitoring • System performance tracked at the level of the user (trip) and facility (corridor) • Understandable to professionals and public • Multiple metrics to capture full range • Existing data and methods, preferably through continuous monitoring • Integration with other transportation functions

  9. Indirect Measurement/Modeling Direct Measurement Continuous Special Studies Continuous Special Studies probe vehicles instrumented cars ITS roadway equipment short-term traffic counts forecasting models spot speeds volumes Post-processors (IDAS) transformation models Travel Time (route segments or trips) roadway characteristics ideal travel conditions volumes Performance Measures average travel speed (mph) travel time (min) travel rate (min/mile) • indices • travel rate index • traffic temperature • congestion severity • delay (min) • per vehicle • per person • per VMT • per driver absolute measures relative measures

  10. Performance Measures Should Encompass Multiple Dimensions TIME Late Night P.M. Peak Daily Mid-Day A.M. Peak Early A.M. Segment Incidents Trip DISTANCE Work Zone Corridor Bottleneck SOURCE Weather Detection Daily Histories Demand Areawide Special Events TCD’s Trends

  11. Recommended Measures: Basic • Travel Rate Index (TRI) ratio of: travel rate in peak ideal travel rate • Delay per Driver • Percent of Congested Travel • %VMT where speeds < 45 mph (fwy)

  12. Travel Time Reliability: Definition • Measured by how travel time of a trip varies from one time period to another • In other words, reliability is measured as the variability of travel times • “How long will my trip take today compared to the same trip at the same time on any average day?” OR • Ability of travelers to predict travel time for a trip and to arrive at destination within an “on-time window” • Variability caused by the “Seven Sources” of congestion

  13. Categories of Reliability Measures There are three categories of reliability measures • Statistical • Buffer time • “Tardy arrival”

  14. Mean Travel Time Frequency Tardy Trips Buffer Time On-Time Performance Travel Time Distribution and Reliability Measures Statistical Measures

  15. 95th % Travel Rate Average Travel Rate Average Travel Rate Buffer Index • Weighted average of . . . • The extra time needed to arrive on time • Seems to resonate with practitioners

  16. Measuring Reliability • Field measurement • Requires many samples or, ideally, continuous measurement • Roadway performance versus trip performance • Different technologies and measurement scale • Hard to separate out “root causes” due to complex interactions • Requires combination of travel time and “event” data • Modeling methods • Tend to regress to average conditions • May be useful in decomposing reliability into sources

  17. Intermediate or Surrogate Performance Metrics • Examples: • Incident duration and “timeline” • Clearance time for snowy roads • Easier to develop • More understandable to profession BUT • Don’t get to the bottom-line as effectively as travel time measures

  18. The “Family Tree” of Performance Measures Total Delay Reliability (Variability) UserImpacts “Recurring” Delay(Bottleneck) “Nonrecurring” Delay Incident Work Zone Weather TotalDuration Total Duration Throughput Total Duration AgencyResponse orEvent-Related During Peak Response Clearance Detection Response

  19. Data Issues Associated With Detailed Performance Measures • Secondary Use of Operations a tremendous data source, BUT… • Limited primarily to freeways in major urban areas • Archiving and data quality are problematic • Measurement limited to facility performance or “corridor-trips” • Comparability of measures calculated from continuous Operations data vs. “traditional” or “synthetic” methods

  20. OPPORTUNITIES TO GUIDE INVESTMENT

  21. Performance Measures Can Be Applied At Several Levels of Interest • Real-Time Operations • What is happening now; expected to happen shortly • How do we respond to travel/system conditions; what strategies do we implement? • Incident response, traveler information (esp. advanced guidance) • Operations Planning • What we expect to happen next week/next month • How can we adjust our strategies to be more responsive • New coordination plans, pre-deployment, routing plans

  22. Performance Measures Can Be Applied At Several Levels of Interest • Short-Term Planning and Programming - 1-5 years (TIP, ITS Deployment Plans and Architectures) • Long-Term Planning - 5-20 years (Long-Range Plans) Expected impacts on the “family” of performance measures can help in deciding priorities and trade-offs • Models need to be sensitive to performance measures, especially reliability and the “Seven Sources”

  23. Measuring Reliability (continued)Atlanta, GeorgiaTrTI/Buffer Index by Time-of-Day Index Value or Congested Travel (1.0=100%) Travel Time Index 1.40 Buffer Index 1.20 1.00 0.80 0.60 0.40 0.20 0.00 0:00 2:00 4:00 6:00 8:00 10:00 12:00 14:00 16:00 18:00 20:00 22:00 0:00 Time of Day (Average Weekdays Only)

  24. SUMMARY • Metrics • Numerous travel-time based metrics are available • Local conditions will indicate which ones are best, but multiple metrics should be used to meet a variety of needs • Summary metrics good for “report card” • Decomposing metrics by at least 3 dimensions is very useful for investment decisions • Time/Space/Source • Reliability becoming increasingly important • “Family Tree” of metrics, with output measures at the bottom feeding into user-based measures should be developed

  25. SUMMARY (cont.) • Data to Support Metrics • Operations sources can provide the data to support this level of detail, but barriers exist • Data quality, coverage, consistency • Models do not now provide emerging performance metrics, especially Reliability • Investment Decisions • Currently, short-range decisions most easily supported • Profession needs to evolve toward a broader framework using the full range of performance measures for all levels of investment, from the “here and now” to long-range planning

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