case study

Finding risky train level crossings.

A case study that analysed driver behaviour at Ben Bullen to determine infrastructure and driver safety levels at the local train level crossing.

With over a thousand near hits at train level crossings (TLC) in NSW every year, road safety at those locations is essential. Unfortunately, to be able to fix all the crossings at once is costly and may have logistical issues. To start this fix, it is best to understand which TLCs are the riskiest for drivers and then prioritise accordingly.

Street view of Ben Bullen's train level crossing.

By using connected vehicle data, the behaviour of drivers could be used to determine whether a crossing was risky or not. Ben Bullen’s Castlereagh Highway was one of the analysed TLCs. In that area, g-forces, speeds, and braking were analysed.

This graph indicates intense acceleration across all speeds and braking almost as intense.
There is harsh steering at this crossing even at low speeds.

The results showed that vehicles were not following the curve advisory speed and so when they reached the crossing, the drivers experienced high g-forces. Higher speeds also meant harsher steering when approaching the bend. These findings indicate a lack of awareness of the surroundings which is dangerous for drivers and so it is suggested changes be made to improve safety.

Use cases

How our customers are using Connected Vehicle data

Applications of vehicle-generated data for use cases across state-wide freight modelling, origin-destination studies, VMS signage effectiveness, road safety, and local area traffic management.

Urban road safety program

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Top view of the studied area in Osborne Park, Western Australia.

Identifying temporary road work

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Contraflow on the Hume Highway through the Road Intelligence Platform.

Conducting a speed study

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A heat map of speeding behaviour in the Inner West Council

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