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

Accessed by AR - ARRB TRANSPORT RESEARCH on 04 Feb 2005
8 CONCLUSIONS
Austroads 2004
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Best Practices in Road Use Data Collection, Analysis and Reporting
This report has successfully compiled and highlighted best practices in road use data collection,
analysis and reporting. Road use data is a complex topic and the materials in this report are the
findings of an Austroads Road Use Data Workshop held in October 2003 in Melbourne, and the
many feedback and suggestions from the Project Working Group members. A key finding of this
project is that RAs have been following similar principles in traffic count data collection and
analysis. Road authorities have refined their counting programs and in many ways have achieved
good practices.
The principles of best practices are enunciated in the report (Section 2). These principles include
accuracy, effectiveness, efficiency, reliability, accessibility, transparency, timeliness and relevance.
They also relate to the issue of data integrity (Section 6). The issue of transparency deserves
special attention because it is a key means at enhancing consistency in data collection, analysis
and reporting amongst RAs and facilitate accessibility of current and potential users of road use
data.
Another key data integrity issue is the method of managing missing data. It is recognised that
each RA has its own procedure in handling missing data, and that there is no standard way of
addressing the issue. This report provides the current procedures adopted in RTA NSW and Main
Roads WA as examples of good practices. In particular, the software developed by RTA-CSIRO
using the method of Hidden Markov Model could prove useful amongst RAs after the necessary
tests are completed.
The topics of vehicle detection and classification are also discussed. Most issues related to these
topics have been addressed over many years. It is generally accepted that the Austroads 12-bin
classification by axle configuration is stable and well-received since its inception in 1994. Minor
variations are recommended as follows:
Introduction of an error bin (bin 13) to account for the quality of classified counts;
Distribution of vehicles from the error bin into either bin 1 (the passenger-car bin) or across
all twelve bins depending on the error bin size, or using both methods making use of
knowledge of on-site traffic conditions;
Standardisation of classifying vehicles into four or five bins by vehicle lengths; and
Recognition of minor variations amongst RAs, but sub-classified counts by either axle
configurations or vehicle lengths must be capable of aggregating into the Austroads system
(13 bins by axles or 4 or 5 bins by lengths).
In the case of vehicle classification by lengths, there is no standard established system yet.
Indeed, it may be appropriate to adopt a 5-bin system to sub-classify combination vehicles so
manufacturers can design their equipment accordingly. The five bins can be aggregated into four
bins where necessary. Some field tests and calibration to determine the appropriate threshold
values of vehicle lengths for each bin are recommended.
The use of a single axle sensor for traffic count collection is quite common amongst RAs, even
though most have recognised the need for classified counts. It is recommended that traffic counts,
as a default, be reported in vehicle numbers. If the raw data is in the form of axles or axle-pairs,
then the count should be converted to vehicles with the conversion factor also reported if possible,
adopting the principle of transparency.