Ramp Meters on Trial: Evidence from the Twin Cities Ramp Meters Shut-off

1. Lake Arrowhead Symposium October 20-22, 2002 Ramp Meters on Trial: Evidence from the Twin Cities Ramp Meters Shut-off David Levinson Department of Civil Engineering University of Minnesota

2. Lei Zhang Shantanu Das Atif Sheikh Kasia Winiarczyk Pavithra Parthasarathi Minnesota Department of Transportation Center for Transportation Studies Intelligent Transportation Systems Institute California PATH University of Minnesota Department of Civil Engineering Acknowledgements

3. Background • 443 Ramp Meters in the Twin Cities metro area; • Zonal control; • Long delays at some ramps; • Meters shut off for 8 weeks from Oct. to Dec., 2000.

4. Theory of Metering • Metering Keeps Traffic Flowing at Freeflow Speed and at Near Maximum Flow • Slightly Below Maximum (Risk Averse) • By Maximizing Total Output Flow, Meters Should Maximize Flow On Other Facilities As Well.

5. Other Aims of Metering • Break up platoons entering freeway • Improve safety • reduce merging incidents, • reduce stop and start conditions on freeway • Manage Incident Conditions

6. Minnesota Algorithm Objective - Meet target flow for each zone Adjust inflow to meet targeted outflow: Where: • A upstream mainline volume (measured variable); • U sum of unmetered entrance ramp volumes (measured variable); • M sum of metered local access ramp volumes (controlled variable); • F sum of metered freeway to freeway access ramp volumes (controlled variable); • X sum of exit ramp volumes (measured variables); • B downstream bottleneck volume at capacity (constant); • S space available within the zone (volume based on a measured variable).

7. Why Equity? • Welfare comprises efficiency and equity. • Efficiency is concerned with net benefits, not their distribution. • Transportation projects and policies create both winners and losers from mobility, accessibility, environmental, and economic standpoints. • Identifying (and perhaps remedying) those inequities is necessary to implement projects from a political perspective. -- An unbuilt project (or removed ramp meters) will not enhance efficiency.

8. Data and Study Locations • PM peak 30 sec averages of flow and occupancy on TH169, I94, I494 and TH62 with/without ramp meters; • On-ramp queue length 5 min interval video camera counts on TH169 and I94; • Other data e.g. hourly weather conditions, average vehicle length, freeway geometry.

9. More Equitable Results (TH169): Mobility and Equity

10. TH 169 Spatial Equity Less Equitable More Equitable More Efficient Less Efficient Mobility and Equity (cont.) Mn Control Algorithm vs. No Control on TH169 NB

11. Mobility and Equity (cont.) Travel Speed (km/hour) Travel Delay (sec/km) With Meters Mobility Measure 62 68 Gini Coefficient 0.28 0.68 W/O Meters Mobility Measure 37 82 Gini Coefficient 0.23 0.28 Gini = 0: Perfect Equity Gini = 1: Perfect Inequity

12. Summary • On TH169 - Measures of Effectiveness Agree, Ramp Meters outperform No Meters from efficiency point-of-view, but not from equity point-of-view. • On other routes (I-94), efficiency results more ambiguous.

13. Demand responses to Metering - Theory

14. Demand Methodology • Total Trips: Total trips entering a specific freeway in each time interval. ∑ Q • Total Vehicle Kilometers Traveled: VKT on a specific freeway in each time interval. ∑VKT • Average Trip Length = ∑VKT / ∑Q • Afternoon Nonwork = afternoon peak nouthbound (or sorthbound) - morning peak southbound (or northbound).

18. Travel Time Reliability • Reliability may be just as important a factor as average travel time … • It doesn’t matter how long it takes, as long as you know in advance. Does ramp metering improve reliability?

19. Inter-day Travel Time Variation: TH169 Northbound

20. Intra-day Travel Time Variation: TH169 Northbound

21. Results: Reliability Inter-day Travel Time Variation Voff - Von > 0, statistically significant at 99% confidence level for 103/124 OD Pairs: 26/45 for OD Pairs <= 3 miles, 77/82 for OD Pairs > 3 miles Inter-day travel time variation is reduced by 1.5 min per trip: Long trips (> 5 km) 1.91 min Short trips (< 5 km) 0.17 min Intra-day Travel Time Variation Intra-day travel time variation is also reduced: Long trips (> 5 km) 3.33 min Short trips (< 5 km) 0.01 min

22. Benefit Estimate On average, meters reduce variability by 1.82 minutes per trip Small et al. (1999) estimate $0.21 per minute of travel time standard deviation Monetized benefits of improved travel time reliability: $0.38 per trip 1,000,000 trips per PM peak per day in the Twin Cities ~100 million dollars per year, savings during PM peak only

23. Conclusions • Freeway speeds and flows are consistently higher with ramp metering than without (while the waits at ramps are longer); • Metering benefits long trips at the expense of short. Whether reserving the freeways for long trips is still an appropriate objective is an important public policy debate - do meters encourage sprawl?; • A limit on individual delay, even at the expense of overall freeway efficiency, may be necessary for ramp meters to satisfy equity considerations; • Undertaking research into the value of time under different traffic conditions is important to have a system that is both efficient and equitable; • Additional data collection systems to measure on-ramp queue lengths in real time are required; • Ramp meters, by their very nature only work within a narrow range, and can not be expected to compensate for traffic growth.