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TRAFFIC LOADING

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4 classes of road, by % of 2-ax HV. Typical (default) axle-load distributions. Bosman 2004: ... the E80/HV is lower with higher law enforcement, and ... – PowerPoint PPT presentation

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Title: TRAFFIC LOADING


1
TRAFFIC LOADING ESTIMATED FROM COUNTS
M Slavik J Bosman
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  • Data

Collect
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Collect New Data
Organise
Make Accessible
Analyse
Apply
Retrieve
Knowledge
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  • 70 freight by road
  • 4 p.a. growth
  • Information on traffic loading
  • needed for
  • pavement design
  • road maintenance
  • law enforcement
  • statistics, patterns, trends

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  • SOURCES OF TRAFFIC LOADING
  • INFORMATION
  • Inductive-loop counters
  • Weigh-In-Motion (WIM)
  • Weighbridges

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  • ASPECTS OF TRAFFIC LOADING
  • Magnitude
  • Average Daily Traffic (ADT)
  • Average Daily Truck Traffic (ADTT)
  • Composition
  • LV, HV HV - short, medium, long,
  • buses, vehicle / axle configuration
  • Axle loads
  • Axle-load distribution
  • ESAL (E80)

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  • E80 FROM INDUCTIVE LOOPS
  • Bosman 1988
  • 4 classes of road, by of 2-ax HV
  • Typical (default) axle-load distributions
  • Bosman 2004
  • Simplified to 3 classes
  • Slavik Bosman in 2006
  • Parameters measurable by loops
  • HV - Short, Medium, Long, vs E80/HV
  • Influence of law enforcement
  • 3 steps

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  • STEP 1 RELATION WITH E80/HV
  • Loop measured attributes
  • heavy vehicles (HV)
  • short HV
  • mediun HV
  • long HV

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  • STEP 2 76 WIM STATIONS, 2005
  • Data validated
  • Reprocessed
  • Long trucks determined
  • E80/HV evaluated

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  • STEP 3 LAW ENFORCEMENT
  • INTENSITY
  • Strong permanent presence
  • Medium ad-hoc, blitzes
  • Weak occasional non-existent
  • STEPS 1 2 3 GRAPH FIG.1

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STEP 4 TRAFFIC LOADING MODELS Type LT class
Law Enf. 1 Below 35
Any 2 35 55 Weak 3 35
55 Strong 4 Over 55 Weak
5 Over 55 Strong
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STEP 5 FIVE MODEL STATIONS Type LT
LE Model 1 Below 35 Any
N12 Kliprivier 2 35 55 Weak
N2 Winkelspruit 3 35 55 Strong
N4 Komati 4 Over 55 Weak N3
Hidcote 5 Over 55 Strong N3
Heidelberg
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TABLE 2. Traffic and Sample Sizes at the Five
Traffic-loading Model Stations
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TABLE 3. Key Figures of the Five
Traffic-loading Types
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1 - N12 KLIPRIVIER
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2 - N2 WINKELSPRUIT
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3 - N4 KOMATIPOORT
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4 - N3 HIDCOTE
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5 - N3 HEIDELBERG
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  • WHY?
  • Weak relationship between LT and E80/HV
  • Imprecision of WIM due to
  • - Calibration problems
  • - Deteriorating pavement
  • - Hardware and software defects
  • No cheap substitute for good WIM measurements
  • NEXT?
  • Strict WIM quality control (European Standard)
  • Uniform data validation procedures
  • Uniform tender requirements
  • Re-appraise situation in 2-3 years time

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  • CONCLUSION
  • The relationship between the percentage of long
    trucks and E80/HV is not very good. R-square
    varies from 0,16 to 0,66.
  • The trend lines, however, indicate that
  • the E80/HV is lower with higher law
    enforcement, and
  • the E80/HV is higher with a higher percentage
    of long trucks.
  • It is thus recommended that, in the absence of
    better traffic loading data
  • the E80/HV values in Table 3 of the paper, and
  • the axle distributions in Appendix A of the
    paper
  • be used by designers and practitioners in the
    meantime.

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  • ACKNOWLEDGEMENTS
  • The authors wish to express their gratitude to
  • NTRV (Northern Toll Road Venture, the N1 Toll
    Road Concessionaire)
  • N3TC (N3 Toll Concession, the N3 Toll Road
    Concessionaire),
  • TRAC (Trans African Concessions, the N4 Toll
    Road Concessionaire),
  • Bakwena (the N4 Platinum Toll Road
    Concessionaire), and
  • SANRAL (South African National Roads Agency
    Limited)
  • for the traffic data and information made
    available.

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TRAFFIC LOADING ESTIMATED FROM COUNTS
M Slavik J Bosman
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  • FACTS
  • Bad news
  • Too dispersed - bottom of a birds cage
  • Good news
  • Red line above green line
  • All lines rising from left to right
  • Blue line joins green on left, red on right

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TABLE 1. Five Traffic-loading Model WIM
Stations
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