As summer approaches, more people are opting to enjoy the sunshine by riding their bikes. Josh Andres, an IBM Researcher who regularly rides his bike, was inspired by the frustration experienced by bike riders when getting stuck at a red traffic light. This problem aligned well with his research and that of his collaborators at the RMIT Exertion Games Lab, which looks to study how humans can partner with intelligent like systems. Their collaboration resulted in the development of ‘Ari’, a Smart e-Bike which can extend the rider’s physical and cognitive abilities to catch traffic lights on the green.
Partners in riding
Ari used artificial intelligence (AI) and the Internet of Things to assist the rider to regulate the speed and cross-traffic lights on green. Using traffic data and green wave modelling provided by Victoria’s road and traffic authority, VicRoads, we trialled the e-bike in real traffic conditions on Melbourne’s streets.
To achieve this, we calculated the optimum speed required to have the greatest chance of crossing all lights on green at the test location — which happens to be 22km per hour. We then programmed Ari to assist the rider to meet this reference speed. The e-bike assisted the rider physically by increasing engine support to accelerate, and cognitively by whispering “slow down a little” via bone-conducting headphones, which left the rider’s ears uncovered in order to navigate the environment safely.
The project is an example of how advances in AI and the Internet of Things in everyday objects could have implications in many aspects of our day-to-day lives.
Through this research, we can begin to explore what it means for humans to partner with AI systems. And how we can design these systems to support user interaction by being trustworthy, explainable, and, ultimately, explore futures that could make a societal contribution.
This research is also important as it explores a new type of interaction between human and computer (and machine), where the computer does not replace the user’s exertion (i.e. it is not a motorbike that replaces pedalling), but instead it can physically and cognitively support the rider, offering opportunities for partnership.
Computer says, coach
Real-world applications of the e-bike technology could depend on per-country traffic light data access. Currently, there are no plans for exploration. However, what we can do now with the learnings from this experiment is inform the design of the user and AI system partnership, specifically in contexts where screens like smartphones are not needed, as they can be an obstruction to the user while moving.
We believe the development of reliable and explainable AI could open opportunities where this type of systems can serve as human “coaches” by complementing physical effort and offering extra cognitive abilities.
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