The partnership will see Luna's high-accuracy algorithmic solutions deployed across both Segway's new open platform and its new retrofit camera-based solution.
Founded in 2020, Luna's Computer Vision solutions enable micromobility operators such as escooter vendors to tackle core challenges such as sidewalk riding, collisions and disorderly parking.
To date, Luna has provided its own camera-based retrofit solutions, as well as IoT integration on customer vehicles.
Computer Vision has grown in priority in the micromobility space, with cities increasingly requesting its integration as part of their licensing terms with escooter and ebike vendors.
Luna's cloud back-end platform enables operators and cities to understand better how riders engage with shared e-scooters as they move through cities. Actionable data and visual confirmation enables operators to confidently communicate with riders about cases of errant riding, increasing their safety performance in a controlled and highly measurable way.
Cities can also use this data to heatmap errant riding to understand key infrastructure pain points in cities contributing to the problem.
Tracking each rider, Luna detects the speed at which riders travel, their exact location and, importantly, the number of pedestrians in the path of their vehicle, providing a complete picture of the risk profile of each ride and the causative factors behind them.
Andrew Fleury, CEO & Co-Founder of Luna Systems, believes that shared micromobility remains a tangible means to reduce car usage. He shared:
"We set off in 2020 with the mission of making these schemes more scalable. Core to this were safety issues such as sidewalk riding and collisions. This partnership will make a significant impact so that schemes can realise their full potential."
Fleury sees the partnership as solid confirmation of the demand for Computer Vision, sharing:
"For Luna, errant riding behaviour is not just whether a vehicle is on the sidewalk or not — it's a far more nuanced picture.
One of our core differentiators is being able to provide this complete context. Location, speed, the number of pedestrians in the path of the scooter and more are vital elements of that picture.
Armed with this data, as well as visual confirmation of an infringement, our customers are enabled to confidently engage with riders about their behaviour - without the concern of customer friction."