Transport for New South Wales and Microsoft have partnered to develop a proof of concept that uses data and machine learning to flag potentially dangerous intersections and reduce road accidents.
As part of the proof of concept, Transport for NSW ran a trial in Wollongong to uncover five potentially risky intersections. It involved 50 vehicles generating more than a billion rows of data over a 10-month period, before Databricks and Azure were used to curate, ingest, and interpret the data.
The telematics data was used to identify speed, harsh braking, harsh acceleration, and lateral movement just before the intersection. It was then compared to patterns of existing crash investigation data.
“We had a circle of interest around the intersection … when the vehicle is actually approaching the intersection, how does it behave at 50 metres, how does it behave at 25 metres, and how does it behave going through the