App developed to turn traffic lights green as cyclists approach

Academics at a university in the United States have developed an app for cyclists that turns traffic lights green as they approach, which they say could ultimately help trigger a “green wave” that enables people to ride along busy bike corridors quickly and efficiently.

The app, called Bike Connect, was developed for $200 using off-the-shelf hardware and software by two professors at the University of Oregon. One, Stephen Fickas, specialises in computer and information science, the other, Marc Schlossberg, in city and regional planning.

The pair obtained a $67,000 grant to test the app, which has its origins in an ‘Internet of Things’ class taught by Fickas.  

10 cyclists tried it out over nine months in partnership with the university’s home city of Eugene, which installed a device to communicate with the app at a traffic signal on Alder Street, a popular cycling route to and from campus.

“We wanted to find a way to make it more convenient and easier for people on bikes to get through a transportation system built for and optimised for motor vehicle traffic,” said Schlossberg.

Here’s how it works. As a cyclist approaches the traffic light, an indicator on the app turns from grey to yellow to notify them that it had been alerted of their presence and speed.

Once the traffic light turned green, so too would the indicator, or the phone could be set to vibrate to inform the cyclist of that.

Speaking of his experience of using the app, Schlossberg said: “It was awesome.”

According to Fickas, who pointed out that the sample size was small, during the trial the app worked 80 per cent of the time – when it didn’t, that was usually because a motor vehicle or another cyclist were already at the junction waiting for a green light.

He pointed out that many cyclists would be unaware of the existing, buried loop detectors that trigger traffic lights when a vehicle passes over them, meaning instead they may push a pedestrian crossing button or take the risk of riding through a red light.

The academics also said their app aims to highlight the profile – and legitimacy – of cyclists in urban transport systems of the future, where autonomous cars will be able to communicate directly with traffic signals and other infrastructure.

They are now looking for funding to take the concept further, perhaps through developing a small device that could be mounted on a bike’s handlebars and indicate to the cyclist whether they should speed up, slow down, or maintain their pace as they approach a traffic light, thereby harnessing that sought-after green wave.