Vehicle loading

Vehicle loading, or axle load, surveys are conducted using either static/low speed equipment or high-speed weigh-in-motion (WIM) equipment. TRL (1978) gives a good discussion of how to conduct static/low speed surveys.

The success of the survey, and the ease that it can be carried out, depends largely on the choice of site. The site must be selected so that the traffic can be sampled easily and safely. It should ideally be on a clear stretch of road with good visibility as it is important to give traffic ample times to slow down and stop. It is often useful to survey at the crest of a hill where vehicles will be travelling slowly due to the gradient. If both directions are being sampled, it is not necessary that the measurements be made exactly opposite to each other.

The site should allow for vehicles to be safely weighed off the carriageway, and queue if necessary. An ideal site is one where there are slip roads, although it is more common to use the shoulders or a level area adjacent to the road.

The general area must be level and firm, with no high spots or risk of subsidence during the survey. Depending upon the length of the survey and the type of equipment, a concrete pit may be used for holding the scales. Alternatively, ramps may be used to ensure a smooth transition of the vehicle onto the scales. Care should also be taken to ensure that vehicles inadvertently driving over them couldn’t damage the cables. It is useful to have the approach to the scales clearly defined using flags or rocks to guide the vehicles to the scales. If only measuring on a single side of the vehicle it is best to position the scale on the driver’s side as this facilitates positioning the vehicle.

Before the survey commences the scales should be calibrated using the manufacturer’s recommended procedure. It is important to ensure that there are spare batteries, cables, etc.

available so that the survey will not be interrupted.

Experience has shown that it is best to monitor both sides of a road, as there are usually differences in the axle loading. The sampling of vehicles should be made on a systematic basis as opposed to random basis. Thus, every n^th vehicle is weighed as opposed to selecting vehicles when the scales are free (that is, a random approach). Since the heaviest vehicles tend to travel the slowest, they have a higher likelihood of being sampled with a random approach, thereby overestimating the axle loads. The sampling rate should be based upon the traffic volume, assuming a measurement rate of 60 to 90 veh/h. The achievable measurement rate is dependent upon both the equipment and the experience of the crew.

For each vehicle both the axle configuration and the axle loads should be recorded, as these are required for calculating the vehicle damage factor (see Section 6.3.1). It is also useful at the same time to collect additional data from the driver, such as the commodity carried, as these data can be used in determining the road user effects.

With the advent of relatively inexpensive WIM technology, this is becoming more widely used for collecting vehicle weight data. With most WIM technology, particularly portable equipment, there is a trade-off between accuracy and sampling; one samples the entire traffic stream but with less accuracy than one gets by weighing individual vehicles from the traffic stream using static techniques. This reduction in accuracy arises because of the effects of vehicle dynamics.

As with all measurements, WIM equipment is subject to random and systematic errors.

Slavik (1998) notes that calibration will limit the systematic errors, however, most procedures will not always eliminate the random error. On-site calibration, which involves stopping and statically weighing trucks and comparing their static loads to the dynamic loads, will consider both systematic and random errors. But there has often been uncertainty as to how many

vehicles one needs to weigh to achieve suitable confidence in the data from the WIM scale.

Slavik (1998) addresses this issue and shows that the sample size is much smaller for

estimating the average load as opposed to the number of equivalent standard axles. Figure E.4 gives the 90% confidence intervals for both of these based on a sample of 218 axles (Slavik, 1998).

The Slavik (1998) approach takes into consideration the properties of the WIM equipment used, the condition of the road surface, the composition and loading of truck traffic which makes the procedure site specific. The raw axle loads are multiplied by a correction factor to convert them to adjusted axle loads:

i i k r

a = …(E.14)

where:

ai is the adjusted axle load I ri is the raw axle load I k is the correction factor

0 10 20 30 40 50 60 70 80

50 100 150 200

Number of Axles Used in Calibration

90% confidence inteval, % of mean

ESA

Load

Figure E.4 90% confidence intervals for WIM equipment This suppresses the systematic error but affects the distribution of axle loads. The

distribution is therefore corrected by converting the adjusted axle loads into corrected axle loads using the equation:

(

)

i

i a fai a

c = + − …(E.15)

where:

ai is the mean adjusted axle load f is a correction factor

The values for k and f are established from the on-site calibration data using the following equations. Their derivation is described in Slavik (1998).















 +

+

−

=

i i i

i i i

a n s s

a n s s

0.5 k

σ σ

…(E.16)

i i / Va Ve 1

f = − …(E.17)

where:

si is the mean static axle load

σsi is the sample standard deviation of the static axle load

n is the sample size

Vai is the variance of the adjusted axle loads

Vei is the variance of the difference between the adjusted and static axle loads