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Bad Weather Data Sets Could Aid Autonomous Vehicles on the Road

David Paul


Bad Weather Data
Collected data in bad weather conditions could help self-driving cars to ‘see’ and operate more safely.

A new Heriot-Watt University project could use data to help autonomous vehicles better operate on the road in adverse weather conditions.

Sensors that work in rain, snow and fog on Scottish roads are providing data that could help autonomous vehicles see and work safely.

The Radiate project has published a new dataset that includes three hours of radar images and 200,000 tagged road actors including other vehicles and pedestrians.

Professor Andrew Wallace and Dr Sen Wang tested the tech by driving around Edinburgh and the Scottish Highlands and used LiDAR technology to capture urban and rural roads at all times of day and night, purposefully chasing bad weather.

Commenting on the journey, Dr Sen Wang said: “We labelled over 200,000 road objects in our dataset – bicycles, cars, pedestrians, traffic signs and other road actors. We could use this data to help autonomous vehicles predict the future and navigate safely.

“When a car pulls out in front of you, you try to predict what it will do – will it swerve, will it take off? That’s what autonomous vehicles will have to do, and now we have a database that can put them on that path, even in bad weather.”

A problem that has been facing manufacturers and researchers of autonomous vehicles can now potentially be saved by this new data.

Until now, almost all the available labelled data has been based on sunny, clear days meaning there was no public information available to help develop autonomous vehicles that can operate safely in bad weather.

Data collection in the past has also been reliant on optical sensors, which, much like human vision, don’t work as well during bad weather.

Professor Wallace said: “Datasets are essential for developing and benchmarking perception systems for autonomous vehicles.

“We’re many years from driverless cars being on the streets, but autonomous vehicles are already being used in controlled circumstances or piloting areas.

“We’ve shown that radar can help autonomous vehicles to navigate, map and interpret their environment in bad weather when vision and LiDAR can fail. ”


The team says by labelling all the objects their system spotted on the roads they’ve provided another step forward for researchers and manufacturers.

Wallace added: “We need to improve the resolution of the radar, which is naturally fuzzy. If we can combine hi-res optical images with the weather-penetrating capability of enhanced radar that takes us closer to autonomous vehicles being able to see and map better, and ultimately navigate more safely.”

The team is based at Heriot-Watt’s Institute of Sensors, Signals and Systems, which has already developed classical and deep learning approaches to interpreting sensory data. They say their ultimate goal is to “improve perception capability”.

David Paul

Staff Writer, DIGIT

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