AP-G84/04 Best practice in road use data collection, analysis ... - WIM

Accessed by AR - ARRB TRANSPORT RESEARCH on 04 Feb 2005
Austroads 2004
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Best Practices in Road Use Data Collection, Analysis and Reporting
Some examples of using Table 9 are as follows:
(a) If the short-term day count on a Wednesday on a rural urban fringe site is 10,000 vehicles
per 24 hour, then the estimated AADT is 1.10 × 10,000 = 11,000 vehicles.
(b) If the short-term part-day (7 a.m. – 9 a.m.) count on a Wednesday at the same rural urban
fringe site is 1,300 vehicle per 2 hour, then the estimated AADT is 8.61 × 1300 = 11,193
vehicles.
In general, counts of very short durations of a few hours or even 12 hours are not reliable for traffic
forecasting. With automatic counting equipment now commonly deployed, the extra cost of
collecting data on more days should be minimal. The best way to ensure consistency amongst RAs
is for each RA to collect robust data sets – collecting data over a consecutive period of, say, seven
days.
Based on some NSW count data, Botterill and Luk (1998) reported that regression analysis is
suitable for determining an adjustment factor to convert a sample count to an estimated AADT and
estimating the relevant accuracy. Regression analysis could be preferable to cluster analysis for
some users because the statistics from regression are well-known. The NSW data were separated
into monthly counts and regression equations were derived relating AADT to road type, count type
(axle counts or classified counts), and AADT strata. It was found that AADT strata had minimal
effect and a recommended regression equation is as follows (without using the constant term):
AADT = β × Vol + ε
where AADT is the count for each Permanent Station,
β is the seasonal adjustment factor to be estimated,
Vol is the daily volume for each nominal period (either a three-day or a six-day week) in the four weeks
in any month for each permanent stations,
ε is the error term representing the deviation from the regression line.
Botterill and Luk (1998) further provided a systematic view of the tasks involved in a traffic counting
program and the calculation of VKTs (Figure 8). The framework highlights the following issues:
Need for a strategic view in implementing a counting program (funding issues and on-going
maintenance);
Appropriate analysis techniques (cluster or regression for pattern recognition, seasonal
adjustments, etc.);
Reliability check over many years and between years;
Clear operational producers.
Some of the issues have been mentioned earlier in Section 2 and are addressed further below.