Dynamic ramp metering strategies designed to actively counter developing bottlenecks can reduce vehicle delay up to 48 percent.
Experience using real-time traffic data to improve ramp metering and mainline performance on Highway-100 in Minneapolis, Minnesota.
Made Public Date
04/20/2017

837

Hwy100NB
Minneapolis
Minnesota
United States
Identifier
2017-01136
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Development of Active Traffic Management Strategies for Minnesota Freeway Corridors

Summary Information

A new metering strategy was implemented on Highway-100 Northbound (100NB) in Minneapolis, Minnesota. The strategy activated metering controls for each ramp depending on mainline conditions and the current traffic demand at a given ramp.

To assess system impacts, traffic performance on the mainline and ramp were analyzed before and after the system was implemented. Traffic data were collected during weekday afternoon peak periods (Tuesdays, Wednesdays, and Thursdays). To account for seasonal variations in traffic demand, the performance of the new metering strategy was compared with that of the old strategy during the same months of the previous year.

FINDINGS

Results of the field test indicated substantial improvements in both mainline and ramp traffic performance as compared to the old strategy that used a stratified algorithm. By dynamically configuring the bottleneck-based zone structure to be controlled in real-time, the new strategy did not require pre-specified associations between ramps and potential bottlenecks, thus increasing its flexibility in dealing with incidents or unexpected events. Further, the turn-on/off times of each ramp meter were automatically determined with consideration given to the mainline traffic states. The results below were excerpted from the source report.

Impacts on Travel Delay

Before/After Comparison of Total Delayed Vehicle Hours Traveled
October-November (2011-Before vs 2012-After)

 

Before

After

Change

Average

432.3359

224.5156

-48.1%

Variance

46174.83

20186.8

-56.3%

Stddev

214.8833

142.0802

-33.9%

Before/After Comparison of Total Delayed Vehicle Hours Traveled
April-May (2012-Before vs 2013-After)

 

Before

After

Change

Average

457.6556

377.9004

-17.4%

Variance

23668.66

37924.77

60.2%

Stddev

153.8462

194.7428

26.6%

Before/After Comparison of Total Delayed Vehicle Hours/Total Entered Vehicles
October-November (2011-Before vs 2012-After)

 

Before

After

Change

Average

0.017575

0.008942

-49.1%

Variance

8.03E-05

3.55E-05

-55.7%

Stddev

0.00896

0.005961

-33.5%

Development of Active Traffic Management Strategies for Minnesota Freeway Corridors

Development of Active Traffic Management Strategies for Minnesota Freeway Corridors
Publication Sort Date
06/01/2015
Author
Kwon, Eil and Chongmyung Park
Publisher
Minnesota DOT
Other Reference Number
Report No. MN/RC 2015-26

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