In a paper due to be presented in Germany next week, the Glasgow team of human-computer interaction specialists describe how they studied the many ways drivers and cyclists directly and indirectly communicate with each other on the road. For autonomous vehicles (AVs) to work safely in human traffic, they must first understand these often-subtle human interactions, and then be able to act appropriately according to the situation.
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“Cars and bikes share the same spaces on the roads, which can be dangerous – between 2015 and 2020, 84 per cent of fatal bike accidents involved a motor vehicle, and there were more than 11,000 collisions,” said research lead Professor Stephen Brewster, from the Glasgow University’s School of Computing Science. “There has been a lot of research in recent years on building safety features into autonomous vehicles to help keep pedestrians safe, but comparatively little on how AVs can safely share the road with cyclists.
“That’s a cause for concern as AVs become more commonplace on the roads. While pedestrians tend to meet AVs in highly controlled situations like road crossings, cyclists ride alongside cars for prolonged periods and rely on two-way interactions with drivers to determine each other’s intentions. It’s a much more complicated set of behaviours, which makes it a big challenge for future generations of AVs to tackle.”
According to Brewster, self-driving cars currently offer little or no feedback to cyclists about when it’s safe to overtake or switch lanes, information that is vital to rider safety. One suggestion from the study is traffic-light-like coloured LEDs around the perimeter of AVs, which would indicate things like when it is safe to pass or when the car intends to give way. Another technology proposed by the Glasgow team is smart glasses that AVs could communicate with directly, displaying information as well as giving haptic warnings if a situation could lead to danger.
“Just like spoken languages, communication between cyclists and drivers varies from country to country,” said co-author Ammar Al-Taie, also from Glasgow’s School of Computing Science. “We’re very conscious that this paper focuses specifically on UK roads – any future developments will need to take into account the differences in drivers’ and cyclists’ interactions across the world.
“However, we hope that this research will be a valuable resource for AV designers to consider new ways that self-driving cars can work safely alongside cyclists by speaking their language, wherever they may be.”
The paper, titled ‘Keep it Real: Investigating Driver-Cyclist Interaction in Real-World Traffic’, will be published in Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems. The research was supported by funding from Glasgow University and the Royal Society of Edinburgh.
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