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Empirics of a  Generalized Empirics of a  Generalized

Empirics of a Generalized - PowerPoint Presentation

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Empirics of a Generalized - PPT Presentation

Macroscopic Fundamental Diagram for Urban Freeways Victor L Knoop Serge P Hoogendoorn Goal Describe traffic states and future traffic states An easy description of traffic ID: 780578

traffic production los accumulation production traffic accumulation los inhomogeneity power generalized fit mfd amp control empirical c3a2 formp density

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Slide1

Empirics of a Generalized Macroscopic Fundamental Diagram for Urban Freeways

Victor

L. Knoop, Serge P. Hoogendoorn

Slide2

GoalDescribe traffic states

and

future traffic statesAn easy description of traffic allows for large scale controlMFD: describe the flow (speed) as function of nr of vehiclesUse for control: routing, perimeter control

Slide3

Macroscopic Fundamental Diagram

Apparently

quite

good

, but

only with homogeneous networks

Main questions1) Can

produciton for inhomogeneous traffic conditions be

described by an MFD?2) How to quantify

the effect of

inhomogeneity

=>

Emperical

observations

Slide4

Empirical study – siteA10 freeway

21 km

10

months, daytimeMostly 3 lanes80-100 km/h speed limitDual loop detectors<500 meter sectionsSpeed, density=> accumulation & production

Slide5

Road impression

Slide6

Predicting production: methodology

Split data set

(

calibration/validation)Create MFDFor validation set:predict production based on accumulationusing

MFD

Slide7

Fit and predictive power

Moving

averageSevere errors in estimationof production near capacity

Slide8

Generalized MFDAccumulation =>

Inhomogeneity

=>

Production as function of accumulation and inhomogeneityInhomogeneity expressed as stdev of density

Production =>

Slide9

Generalized MFD

Accumulation

=>

Inhomogeneity =>Color = productionInterpolation as predictorMeasure accumulation &

inhomogeneity => predict production

Slide10

Quality of predictionPredicted by

interpolation

Slide11

Fitting a functional formP(A)=A*(c

1

+c

2A+c3A2)-c4sHomogeneous traffic situationInhomogeneous traffic situation

Slide12

Fitting a functional formP(A)=A*(c

1

+c

2A+c3A2)-c4s

Slide13

Empirical evidence

Accumulation

=>

Inhomogeneity =>

Slide14

Fit and predictive power (2)

Similar

to interpolationEasier to quantifyInterpretation of variables

Slide15

Quality of fit

R

2

MFDGMFDQuality of fit0.850.86A>18 veh/km0.00160.39

Slide16

Use in practiseBuffer traffic to

ensure

maximum

outflow to motorwayHold traffic further upstream, e.g.

Accumulation

A

c

.5 A

cAmax

LOS ALOS B

(Ac+Amax)/2LOS C

LOS D

Accumulation

Production

A

c

.5 A

c

(

Ac+A

max

)/2

A

max

Production

LOS A

LOS B

LOS C

LOS D

Slide17

ConclusionsTraffic flow can be

descibed

at a high (area-

wide) levelTwo explanatory variables: accumulation & inhomogeneityPredictive power much increased by adding inhomogeneity