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USE OF WIM IN SOUTHERN AFRICA USE OF WIM IN SOUTHERN AFRICA

USE OF WIM IN SOUTHERN AFRICA - PowerPoint Presentation

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Uploaded On 2020-08-06

USE OF WIM IN SOUTHERN AFRICA - PPT Presentation

Current Future 1 Louw Kannemeyer Contents Road Network Current WIM Use Future WIM Use 2 Authority Paved Gravel Total SANRAL 22 214 0 22 214 Provinces 9 46 548 226 273 272 821 ID: 799917

load wim calibration axle wim load axle calibration road sanral future data distribution total roads deviation overload random method

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Presentation Transcript

Slide1

USE OF WIM IN SOUTHERN AFRICACurrent / Future

1

Louw Kannemeyer

Slide2

Contents

Road Network

Current WIM Use

Future WIM Use

2

Slide3

Slide4

Authority

Paved

Gravel

Total

SANRAL

22 214

0

22 214Provinces - 946 548226 273272 821Metros - 851 68214 46166 143Municipalities 37 680219 223256 903Total158 124459 957618 081Un-Proclaimed (Estimate) 131 919131 919Estimated Total158 124591 876750 000

SA ROAD NETWORK - 2018

Un-Proclaimed

Roads = Public roads not formally gazetted by any Authority

Slide5

South Africa has the 10

th

longest total and 18

th

longest paved road network in the world

The National Development Plan states that roads represent one of the largest public infrastructure investments in most countries.

RSA road

replacement cost>R2 trillion

Slide6

Freight flow on road and rail (10

th

State of Logistics Survey 2014)

Also important to note that of the person trips recorded in

National Household Travel Survey

, 2013, by transport modes are as follow:

Minibus taxi’s (41.6%)

Private Vehicles (23.4%) Walking (18.5%) – Along road corridorsbusses (10.2%) Trains (4.4%)Other (1.9%)Roads account for 87.9% of Freight and 93.7% of Person TripsMode Choice FactorPercentageTravel time32.6Travel Cost26.1Flexibility9.2Other32.1SOUTH AFRICA ROAD USE

Slide7

Total Life Cycle Transportation Costs

Road User Cost is up to 90% of Total Life Cycle Transportation Cost

Very Good

Very Poor

Slide8

8

SANRAL Traffic Monitoring Stations

Accurate Traffic Data –

Most Important Data Item

Capacity Analysis / Pavement Design / Life Cycle Economics / Toll Income

Slide9

9

Traffic Monitoring Stations - WIM

Current Active WIM Stations

Slide10

Typical RSA WIM Station

Slide11

Main Problem - Systematic deviations in WIM observations due to quality/calibration of WIM installation.Available Calibration Methods

On-site calibration of WIM equipmentAutomatic self-calibrationPost-processing calibrationWhy post-processing calibration?Difficult to undertake full-scale on-site calibration (sample/weigh bridge)

WIM calibration tends to “drift” over time

Post-calibration method applied after load measurements. Can be reapplied to old data.

“Truck-Tractor” (TT) method - Calibration based on load observations of population sample of articulated trucks of a certain type and size Development of method – Dr Martin Slavik

/Mr Gerhard de Wet

WIM – Systematic Deviations

21.8 tons

Slide12

Poor WIM Installation

Slide13

13

Good WIM Installation

Slide14

WIM - Random Deviation

Axle load distribution

WIM Random errors and variation in dynamic loads result in:

Measured axle distribution wider than actual static load distribution

Particularly at higher end of distribution

Results in overestimation of percentage “overloaded” axles

Basic adjustment methodology

Observed axle load measurements is the sum ofStatic load of the axle plusWIM error and dynamic impactIf information on WIM error and dynamic impact is knownThen such impact can be “subtracted” from observed axle loadsTo provide the static load of the axleRandom Deviation Correction Important When Quantifying Overload Damage

Slide15

Expectation-Maximization-Smoothing” (EMS) algorithmApplies a numeric technique using so-called “deconvolution” methodWim errors basically “convolutes” or distorts the static loadDeconvolution removes this convolution from data

Central limit theorem is a special case

Numeric method does not require fitting of Log-Normal distributions

Can also be solved by means of Expectation-MaximizationProblem is that deconvolution is very sensitive to “noise” in dataCan only be used when data relatively free of noise

This problem is solved by incorporation of smoothing algorithm

Smoothing intended to remove noise from data

WIM - Random Deviation

Slide16

WIM - Random Deviation

Slide17

17

SANRAL OVERLOAD SOFTWARE

15 to 30 %

Vehicles Overloaded – Only

2%

loaded beyond Prosecution Grace

Statistics - Screened Sample versus Population

Slide18

18

SANRAL OVERLOAD SOFTWARE

Slide19

19

Committee of Transport Officials (COTO)

TMH Standards

Slide20

FUTURE WIM USE

Pavement Design/Maintenance

Old – Axle Load Histogram reduced to Equivalent Standard Axle Load per vehicle - E80

Future

SARDS Complete Axle Load Histograms used along with Tyre Contact Stress (How load is transferred to Pavement !!!)

20

20(Not to scale)n-shape:- Single Circularn-shape:- Single rectangularm-shape:- Triple rectangular

Slide21

FUTURE WIM USE

Overload Control

Old

– Screeners at Static Weigh Bridges

50 to 100 km impact radius

Construction/Operational Costs

Human Factor

Future – WIM-Enforcement Direct Weight Enforcement integrate with Average Speed over Distance (ASOD) – 250+ InstallationsBeen trialled over past 5 yearsAwaiting National Regulator Compulsory Standards Type Approval for ASOD and WIM-EEnd 2018Realtime Integration to SANRAL Central Operations CentreRealtime Tracking of Load Movements Country Wide (OD) Direct Enforcement (Speed/Load)Insurance FraudSecurity ApplicationsAbnormal Permits EnforcementIndustry Self Regulation Verification???2121(Not to scale)

Slide22

THANK YOU

Louw KannemeyerEngineering Executive SANRAL

louwk@nra.co.za

www.sanral.co.za

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