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 Table 3 – Vehicle classification systems currently in use Austroads 2004 — 8 — Best Practices in Road Use Data Collection, Analysis and Reporting Methodology Urban traffic Rural traffic By axle configuration using two axle sensors By vehicle length using two inductive loops By manual observation, loop inductance profiling or video imaging Not suitable for congested roads, turning traffic, vehicles changing lanes 3- or 4-bin systems Austroads 12-bin system (Table 2) Suitable for sites where loops can be embedded into a sealed carriageway; requires good pavement surface 2-bin system (light and heavy vehicles; Table 2) and various vehicle classification schemes 3.3.1 Current Austroads Vehicle Classification System As already mentioned, the Austroads vehicle classification system currently in use is based on classifying axle configurations. Bins 1 and 2 are classified as light vehicles (two axle vehicles with or without towing a caravan, trailer, etc.) and bins 3 to 12 are called heavy vehicles. This two-bin system is suitable for manual classified counts but now used mainly for intersection movement counts. The 12-bin system has been found valuable since its inception and has provided useful data for all RAs. The system has provided consistency across jurisdictions and the data can also be analysed over time. There have been requests for changes that include: Different jurisdictions require variations to cater for their own needs; sub-classifications within a bin would be a solution. Examples are motor cycles in bin 1 and sand trucks in bin 9. These sub-classes can be easily aggregated to provide the standard 12-bin system for consistent reporting and trend analysis. New vehicle-axle configurations such as the performance-based standard (PBS) vehicles are being developed. These vehicles aim to carry heavier loads with better safety capability and more user-friendly suspension. It is expected that PBS vehicles would still fit into the 12-bin system but their development needs to be monitored. It is anticipated that the migration of the current heavy vehicle fleet to a PBS regime will take some time. There are requests to create additional classification bins within Austroads bins 11 and 12 (Type 1 and Type 2 road trains respectively; Roper et al. 2002). It is therefore recommended that the current Austroads vehicle classification be maintained but allowing sub-classes as variations of the basic system. This was also endorsed at the Austroads Road Use Data Workshop held in Melbourne. It may be appropriate to introduce a new notation to designate different jurisdictional versions, e.g. the Austroads (Vic) for the Victoria version. The issue of introducing a separate bin to collect errors in classified counts is discussed below. 3.3.2 The Error Bin It is good practice to always check where the errors come from, e.g. poor installation, malfunctioning of sensors, etc. Different ways are currently used to treat an error or ‘nonclassifiable’ vehicle count. Error counts can be lumped into a separate error bin (say, bin 13) that also acts as a quality check of the classified data. Methods for managing the error counts include the following possible actions:
Accessed by AR - ARRB TRANSPORT RESEARCH on 04 Feb 2005 Put them into bin 1 (passenger-car bin); Austroads 2004 — 9 — Best Practices in Road Use Data Collection, Analysis and Reporting Distribute across the 12 bins in proportion to the measured vehicle numbers in each bin (i.e. new bin j vehicles = old bin j vehicles × sum of bins 1 to 13 / sum of bins 1 to 12); and Discard them. Each of these methods has its own inadequacy. The last method in discarding the error counts would underestimate the true traffic demand in a road network. The second method of proportional distribution across all bins may significantly distort the true distribution if the sum of vehicles in bins 1 to 12 is small relative to the vehicles in the error bin. The first method of loading error counts into the passenger-car bin (bin 1) would not significantly affect the true count in bin 1 only if there are relatively large numbers of vehicles in this bin. It is thus recommended that: (a) An error bin (no. 13) be introduced into the Austroads system as good practice to indicate the quality of the classified counts; (b) The inclusion of error counts in bin 13 in the total counts requires some judgement. If the number of error counts is high relative to the total counts, it is necessary to identify the reasons for such a situation before error counts are included; (c) If it is deemed appropriate to distribute bin 13 vehicles, the two distribution methods mentioned previously can be considered, or both methods are used and guided by relevant local knowledge. (d) The number of error counts should be monitored and, if these remain high relative to the traffic stream, the reasons for these errors should be identified and the problem rectified. 3.3.3 Vehicle Classification in Urban Traffic As indicated in Table 3, loop sensors are more suitable for collecting vehicle classified counts on congested multi-lane highways. These sensors are usually located mid-block on arterial roads and data retrieved remotely using modems. Another source of classified counts is the freeway management systems now in place in capital cities. Loop sensors or virtual loops using imaging technologies are installed at regular intervals (e.g. 500 m) to monitor traffic flow and identify incidents. These loop pairs calculate the spot speed and classify vehicles by length. Both 3-bin and 4-bin systems have been employed in various jurisdictions. VicRoads, Main Roads Queensland and Transit New Zealand have reported using a 4-bin system. Transit New Zealand and RTA NSW also use three bins to classify vehicles by lengths. Table 4 shows the threshold values of these systems. Vehicle class Main Roads Queensland Table 4 – Vehicle classification systems by lengths Vehicle lengths (m) VicRoads Transit New Zealand RTA NSW Bin 1 (short) < 5.8 < 6.0 < 5.5 11.5 Bin 4 (combination) > 21.2 > 17.5 > 17.0 -
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AP-G84/04 Best practice in road use data collection, analysis ... - WIM

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