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 — 4 — Best Practices in Road Use Data Collection, Analysis and Reporting With the prevalent use of single axle sensor for traffic counts, it is important that the number of axle pairs obtained be corrected for vehicles with more than two axles. The correction factor is dependent on traffic composition and site conditions and should be calibrated on-site. Some guidelines on the correction factor are given in GTEP Part 3. For example, if heavy vehicles account for 12% of the total traffic on an urban highway, the number of axle-pairs obtained should be reduced by about 6%, i.e. the correction factor is 0.94 ±0.15 at the 95 % confidence limits. There are no standard practices amongst RAs regarding when axle pair counts are collected rather than classified counts. At the Austroads Road Use Data Workshop, there was general agreement that classified counts be collected wherever possible. As mentioned earlier, a pair of axle sensors is essential for classified counts in spite of higher installation and maintenance costs. An axle sensor pair is also more appropriate than a single axle sensor in obtaining bi-directional counts as traffic volume increases. Table 1 recommends what could be used under different axle arrangements and AADT values. In Table 1, the threshold AADT values correspond to different Levels of Service (LoS) for two-lane rural roads and arterial roads (GTEP Part 2, Austroads 1988b; TRB 2000). At a LoS of E, a road facility is operating at capacity. Usually a facility is designed for a LoS of C. Delay is frequently experienced at LoS of D and E. The values in Table 1 are for a peak-hour to daily factor of 0.15. Road environment Combined direction (e.g. two-lane two-way rural roads) Separate direction (e.g. multi-lane carriageway at 80 km/h speed limit) Table 1 - Use of axle sensors under different AADT values Indicative maximum AADT (veh) One axle Two axles 9,000 (two lanes) (Level of Service = D) 8,500 per lane (Level of Service = C) 15,000 (two lanes) (Level of Service = E or at capacity) 11,000 per lane (Level of Service = D) On multi-lane highways, temporary surface mounted pneumatic tube sensors may not be suitable under heavy traffic conditions, poor pavement surface or OH&S problems for field staff. The count accuracy also decreases with increase in traffic flow and the number of lanes that an axle sensor (or an axle pair) has to cover. In these situations, it could be better to use in-ground loop sensors described in Section 3.2. The development of piezo-cables for axle detection continues to progress (Luk and Brown 1987; ARRB TR 2003). The cost is higher than pneumatic tubes but should be able to offer a working life similar to that of an in-ground inductive loop - four to five years depending on traffic volume, its composition and pavement type and condition. Piezo-cables can be installed lane-by-lane so lanebased counts are possible. The piezo-sensor needs to cover only half to three-quarters of a lane width to reduce cost and possibly improve accuracy with ‘cleaner’ axle actuations. Axle sensors give more distinct axle actuation times and therefore better accuracy than loops in speed measurement and vehicle classification. Figure 2 shows the four timing pulses for speed calculation and hence vehicle classification. For very slow or stationary traffic, it is difficult to separate vehicles using the axle actuation times T1 to T4 and determine speeds and classify vehicles, especially if a vehicle straddles over both axle sensors for a long period of time. Inductive loops and the related electronic circuitry are designed to monitor loop occupancy (i.e. the time that a vehicle is on top of a loop) and are more suitable for slow traffic, e.g. urban traffic in peak hours.
Accessed by AR - ARRB TRANSPORT RESEARCH on 04 Feb 2005 Austroads 2004 — 5 — Best Practices in Road Use Data Collection, Analysis and Reporting The ability to detect gaps between adjacent vehicles and obtain a valid vehicle count is dependent on the length of the inductive loop in the direction of travel along a lane. Undercounting will occur when the loop detection zone is too long. Mendigorin et al. (2003) described studies in Sydney on using axle sensors for classified counts in urban traffic. Their results suggested that a separation of 4 m between two axle sensors provide good accuracy and these results are consistent with those obtained in Luk and Besley (1985) using different counting equipment. The optimal separation is a balance between equipment accuracy and fluctuations of vehicle speeds between the two axle sensors. It is dependent on the type of equipment and the associated software used in a study. T 1 T 3 T 2 T 4 Pair of axle sensors Vehicle actuation pulses T 1 Figure 2 – Four positions of a two-axle vehicle passing over two axle sensors In summary, a pair of axle sensors should be considered where possible to give better accuracy, better distinction by direction, and the ability to produce classified counts through axle configurations. If a single axle is used, it is a recommended practice to correct for traffic composition and convert axle-pairs into vehicle counts for reporting purposes. 3.2 Inductive Loop Sensor and Vehicle Counts The operation of a loop sensor requires an alternating current passing through the inductive loop. When a mass of metal such as a vehicle chassis and an engine passes through the electromagnetic field of the loop, the inductance of the loop reduces. These reductions are used to indicate the passage or presence of a vehicle. Figure 3 shows the typical response of a loop detector when crossed by a passenger car. The reduction in loop inductance depends on the size and metallic content of the vehicle. For example, a passenger car generates a change of about five per cent for the loops typically used in traffic counting. The inductive loop detector is used extensively for automatic traffic counting, traffic surveillance and traffic signal control. The analysis of inductive loop profiles can also be used for vehicle classification but is seldom used amongst RAs. − T 13 T 3 − T 2 − T 34 T 4 − Time
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AP-G84/04 Best practice in road use data collection, analysis ... - WIM

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