1. USE OF WIM IN SOUTHERN AFRICA
Current / Future
Louw Kannemeyer

2. Contents
Road Network
Current WIM Use
Future WIM Use

4. SA ROAD NETWORK - 2018 Authority Paved Gravel Total 158 124 459 957
SANRAL
22 214
Provinces - 9
46 548
Metros - 8
51 682
14 461
66 143
Municipalities
37 680
Un-Proclaimed (Estimate)
Estimated Total
Un-Proclaimed Roads = Public roads not formally gazetted by any Authority

5. South Africa has the 10th longest total and 18th 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

6. Roads account for 87.9% of Freight and 93.7% of Person Trips
SOUTH AFRICA ROAD USE
Freight flow on road and rail (10th 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 corridors
busses (10.2%)
Trains (4.4%)
Other (1.9%)
Mode Choice Factor
Percentage
Travel time
32.6
Travel Cost
26.1
Flexibility
9.2
Other
32.1
Roads account for 87.9% of Freight and 93.7% of Person Trips

7. Road User Cost is up to 90% of Total Life Cycle Transportation Cost
Total Life Cycle Transportation Costs
Very Good
Very Poor
Road User Cost is up to 90% of Total Life Cycle Transportation Cost

8. Accurate Traffic Data – Most Important Data Item
SANRAL Traffic Monitoring Stations
Accurate Traffic Data – Most Important Data Item
Capacity Analysis / Pavement Design / Life Cycle Economics / Toll Income

9. Current Active WIM Stations
Traffic Monitoring Stations - WIM
Current Active WIM Stations

10. Typical RSA WIM Station

11. WIM – Systematic Deviations
Main Problem - Systematic deviations in WIM observations due to quality/calibration of WIM installation.
Available Calibration Methods
On-site calibration of WIM equipment
Automatic self-calibration
Post-processing calibration
Why 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
South African research has shown that significant errors can be found in Weigh-In-Motion observations due to calibration issues with WIM equipment.
Various calibration were investigated over many years in the country resulting in the development of the so-called Truck-Tractor method
The method has now been extensively tested in South Africa and has been found to be fairly accurate
It is a post-calibration method that can be used after load measurements have been undertaken. It therefore has the advantage that it can be applied to previous WIM measurements. SANRAL has been collected axle load data for nearly two decades and the method can therefore also be applied to such data, which is a major advantage of the method.
The calibration is based on the load observations of articulated trucks of a certain type and size typically found on South African roads.
10. CAPSA Traffic Modelling & Contact Stress-MDB.pptx
21.8 tons

12. Poor WIM Installation

13. Good WIM Installation

14. Random Deviation Correction Important When Quantifying Overload Damage
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 of
Static load of the axle plus
WIM error and dynamic impact
If information on WIM error and dynamic impact is known
Then such impact can be “subtracted” from observed axle loads
To provide the static load of the axle
Random Deviation Correction Important When Quantifying Overload Damage

15. WIM - Random Deviation
“Expectation-Maximization-Smoothing” (EMS) algorithm
Applies a numeric technique using so-called “deconvolution” method
Wim errors basically “convolutes” or distorts the static load
Deconvolution 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-Maximization
Problem is that deconvolution is very sensitive to “noise” in data
Can 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

16. WIM - Random Deviation

17. SANRAL OVERLOAD SOFTWARE
15 to 30 % Vehicles Overloaded – Only 2% loaded beyond Prosecution Grace
Statistics - Screened Sample versus Population

18. SANRAL OVERLOAD SOFTWARE

19. Committee of Transport Officials (COTO)
TMH Standards

20. 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 !!!)
m-shape:
- Triple rectangular
n-shape:
- Single rectangular
n-shape:
- Single Circular 20
(Not to scale)

21. FUTURE WIM USE Overload Control 21 (Not to scale)
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+ Installations
Been trialled over past 5 years
Awaiting National Regulator Compulsory Standards Type Approval for ASOD and WIM-E
End 2018
Realtime Integration to SANRAL Central Operations Centre
Realtime Tracking of Load Movements Country Wide (OD)
Direct Enforcement (Speed/Load)
Insurance Fraud
Security Applications
Abnormal Permits Enforcement
Industry Self Regulation Verification
??? 21
(Not to scale)

22. Engineering Executive SANRAL
THANK YOU
Louw Kannemeyer
Engineering Executive SANRAL 22