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For the 3 rd ICTTS, Guilin, P.R.China, 07/24/02. Estimation of Demand Responses to Ramp Meters by Lei Zhang and David Levinson. Problem Statement.  Previous research has assumed fixed demand  How different types of trips respond to ramp meters (work vs. non-work; short vs. long)

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Presentation Transcript
slide1

For the 3rd ICTTS, Guilin, P.R.China, 07/24/02

Estimation of Demand Responses to Ramp Meters

by

Lei Zhang and

David Levinson

problem statement
Problem Statement

 Previous research has assumed fixed demand

 How different types of trips respond to ramp meters (work vs. non-work; short vs. long)

 A bill was passed to shut off ramp meters to study effectiveness in the Twin Cities in Spring 2000

 The shut-off experiment provides data not previously available (Oct. 16 ~ Dec. 8, 2000)

slide3

Research Objectives

 Develop a methodology to estimate freeway demand shifts from loop detector data

 Apply the methodology to determine from the empirical data how travelers respond to ramp meters.

slide5
Data

 30-sec flow counts, a measure of the number of vehicles that have passed over a detector, collected during the shut-off period (in 2000) and the corresponding weeks in 1999.

 Freeway geometry

 Hourly precipitation data

 Control for other factors:

Seasonal Demand Fluctuation, Weather, Crashes

methodology
Methodology

 Total Trips =

 Total VKT=

 Average trip length

methodology cont
Methodology (cont.)

 Non-work trips (discretionary trips)

QAM (morning peak flow)

QPM (afternoon peak flow)

Eastbound Non-work Trip = QPM - QAM

results
Results

 Peak Spreading

%Changes of total trips

results cont
Results (cont.)

 Peak Spreading (cont.)

%Changes in total VKT

results cont 2
Results (cont. 2)

 Afternoon peak non-work trips

results cont 3
Results (cont. 3)

 Long non-work trips are rescheduled to…

Changes in total VKT

conclusions
Conclusions

 Evidence of rescheduling trips, switching routes and/or destinations after the shut-off

 Long non-work trips are losers and short non- work trips are winners

 Freeways handle more trips but fewer vehicle kilometers

 If used in combination with an OD prediction technique, the methodology developed herein is capable to estimate the actual freeway supply/demand curve.

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