Traffic Counts: 4 Traffic Statistics You Should Rethink

When conducting a traffic survey, it’s easy to forget about the latent value of your traffic data. Beyond the standard vehicle volume reports, you can analyze a wealth of information about road design, driver behaviour or road safety.

Traffic Counts or Traffic Data?

As a traffic engineer or road manager, you are aware that a number of variables influence infrastructure design and use. However, you might not have realised that additional KPI’s like the gap acceptance, real traveling speed, and vehicle classes,  are available in every MetroCount dataset. Don’t worry, you’re not the only one!

In the industry, we often refer to ‘traffic monitoring’ as ‘traffic counting’  with ‘traffic counters’. This nomenclature may be to blame for a limited perception of the scope of traffic data analysis. It might be time to rethink the data we consider for effective road analysis.

1. The 85th Percentile Speed

While the average driving speed is an obvious metric, the 85th percentile speed is really what you’re after. This value measures how the road usage, highlighting speed limits that don’t match road design.

The 85th percentile speed is the pace adopted by reasonable drivers on a particular road. Also called the ‘operating speed‘, this parameter is used as a benchmark for road design.

Calculating the 85th percentile speed is straightforward in MTE, but a headway filter is essential for representing the speed drivers choose to travel in free-flowing traffic. If a road experiences traffic congestion, motorists are unable to travel at their desired operating speed and a headway filter will remove speeds impacted by congestion.

To learn more about using MTE to determine the 85th percentile, check out this ebook or the video below.

2. Axle-based Vehicle Classification

Road managers should be as concerned about the types of vehicles traveling on a road, as they are about their volume. This will greatly influence the thickness and type of pavement, road capacity and safety. Considering the huge value of roads, effective management of repairs and upgrades is critical to ensure the community gets value for money.

While design guidelines differ from country to country, the common challenge of maximising pavement lifespan relies on understanding vehicle loads and axle configurations. MetroCount’s RoadPod VT and RoadPod VP systems, enable you to precisely identify the axle groups of each individual vehicle and produce accurate summaries of the relative load on a road. These tools are an invaluable asset for any road manager.

Left: Lecture on Pavement Design ( Right: MsDOT – Vehicle Classification for County Road Pavement Design (

3. Traffic Gap Analysis

A road user (ie. driver, rider or pedestrian) often needs to select a break in the traffic stream that will enable them to move safely. Determining a road’s gap acceptance is vital for designing intersections, pedestrian crossings, or timing traffic lights. Without establishing a safe break, roads can become dangerous and increase the risk of collisions.

MetroCount datasets can be manipulated to determine the available traffic gaps for crossing, entering and exiting a road. To learn more about how gap analysis is conducted in the MTE software, check out this ebook.

4. Hazard Ranking & Monetary Worth

It is very common for police officers to receive complaints about speeding cars. Unfortunately, the limited manpower makes it difficult to verify all complaints, so prioritising their importance is essential. The most efficient way to determine the true speed risk of a road is by employing traffic monitoring technology.

The RoadPod series of counters enable you not only to determine how many drivers are speeding but also what hours are most dangerous and the potential monetary value of speeding fines. Speed data can be grouped into bins and a weighting can be assigned to each bin. In other words, you can indicate a monetary value for each vehicle exceeding the speed limit, and this value will change according to its speed threshold.

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