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

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Accessed by AR - ARRB TRANSPORT RESEARCH on 04 Feb 2005 Austroads 2004 — 30 — Best Practices in Road Use Data Collection, Analysis and Reporting Plotting of AADT as ordinates on map of urban road network, against each segment as an abscissa. Axle pairs or Vehicle Counts Provide raw data on axle pairs and adjusted vehicle counts if a single axle sensor is used; Record the method of adjustment; Mention the level of accuracy. Seasonal Patterns and Trends of Traffic Monthly, weekly and daily variation patterns in traffic can be illustrated in graphical and tabular forms; Information on the variation about the average level of traffic can be drawn from the graphical data arranged in decreasing order. Turning Movements at Intersections A tabular method is used when classification by vehicle type is required to be present; Peak and daily hour turning movements can be illustrated graphically. Other issues that should be considered are: Reporting interval, What data are reported, Geographic referencing of the information, and Report presentation format. As a minimum, it is recommended that reporting should be at yearly intervals, providing AADT for each section of the road network, in terms of vehicles per section per time period. Each traffic counting station should be identified by geographic referencing using maps or coordinates. Minimum reporting format should include location, AADT by road section and vehicle class, details of homogeneous road sections, VKT (total, by vehicle class, by road type, by region), details of duration of counting and traffic growth over the previous year. An example of the data classes collected and stored for reporting in Queensland is detailed in Table 15. It is also good practice that statistical results be reported jointly in terms of percentage error and confidence interval. If measurements could be made over the totality of a target population rather than over just a sample then there would be no need to specify a confidence interval. Because usually only a sample is taken, there remains the possibility that this sample is unrepresentative of the population, so that the error is likewise unrepresentative. It is also good practice to specify a risk factor that the sample could be unrepresentative. For example, a risk of 1 in 20 chance (sample) is taken, which translates to the 95% confidence interval and this happens with the confidence limits at ±1.96 standard deviations from the mean. Similarly, with confidence limits at ±1 standard deviation from the mean, the confidence level is at 68 %. Risk should be specified as a percentage error for determining confidence limits.
Accessed by AR - ARRB TRANSPORT RESEARCH on 04 Feb 2005 Austroads 2004 — 31 — Best Practices in Road Use Data Collection, Analysis and Reporting Table 15 - Complete list of data classes collected/computed and stored in Queensland Class Description Class Description 0 Volume 33 Free Speed – Distribution – Low Range 1 Annual Average Daily Traffic 34 Free Speed – Distribution – Mid Range 2 Highest Hourly Volumes 35 Free Speed – Distribution – High Range 3 AM and PM Peaks 40 Gross Vehicle Mass – Mean 5 Exponential Growth 41 Gross Vehicle Mass – Standard Deviation 6 Set Factors 42 Gross Vehicle Mass - 95%< 10 Speed – Mean 43 Gross Vehicle Mass – Distribution 11 Speed – Standard Deviation 50 Axle Group Mass – Mean 12 Speed – 85%< 51 Axle Group Mass – Standard Deviation 13 Speed Distribution – Low Range 52 Axle Group Mass – 95%< 14 Speed Distribution – Mid Range 53 Axle Group Mass – Distribution 15 Speed Distribution – High Range 60 Unloaded 20 Percentage Following 61 Loaded 21 Gap Acceptance Overtaking 62 Overloaded Axle Group 22 Headway – Mean 63 Overloaded Vehicle – by Axle Group 23 Headway – Standard Deviation 64 Overloaded Vehicle – by Gross Vehicle Mass 24 Headway – 85%< 69 Mean Net Load – (Total Freight tonne) 25 Headway – Distribution 70 ESA – Unloaded 30 Free Speed – Mean 71 ESA – Loaded 31 Free Speed – Standard Deviation 72 ESA – Overloaded 32 Free Speed – 85%< 73 ESA – Total 80 Vehicle-Kilometre Travelled 4.4.2 Data Availability Reporting also entails making data available to a range of users at different levels of access. Such considerations include: Storage formats which should be clearly stated for easy unpacking and processing; Download formats which should included the most commonly used applications (pdf, spreadsheets, zipped, etc); Methods of access which should include traditional hard copies and more common electronic forms of access (Internet, dial up, help desk, etc); Limitations on sensitive and commercial information (if any); and Copyright and legal issues, regarding the on-sale and distribution of such information to third parties. The existence of Freedom of Information Acts in each RAs’ jurisdiction implies that road data should be available to the public. Indeed, this is already the experience of most RAs in dealing with an increasing amount of requests for such information. As requests can vary from simple queries to detailed investigations requiring further effort, processing or analysis of the data, it is reasonable that a user-pay policy applies.
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AP-G84/04 Best practice in road use data collection, analysis ... - WIM

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