Spin, the San Francisco-based micromobility unit of Ford Motor Co. in Dearborn, has announced an exclusive partnership with Drover AI to incorporate its PathPilot technology into the next generation of Spin’s Insight e-scooter monitoring platform.
The platform is expected to be deployed to cities in the United States, across the United Kingdom, and in other regions around the world in 2021.
Spin Insight Level 2, powered by Drover AI’s computer vision and machine learning platform, equips Spin’s vehicles with a camera, an array of sensors, and on-board computing power. By leveraging artificial intelligence tools, Drover’s technology is adaptive and scalable to new environments, allowing an e-scooter to understand its surroundings in real time and assist riders in making safe riding decisions.
This week, Spin included Spin Insight Level 2 in a proposal for the first time as part of the e-scooter permit application for New York City. If Spin is awarded a permit in New York, the city will receive the first large-scale deployment of Spin’s sidewalk riding and improper parking solution starting in the spring.
“Spin is proud of its record of collaboration with cities to develop solutions that benefit their citizens,” says Derrick Ko, CEO of Spin. “We are excited to partner with Drover, which has proven to have the best-in-class micromobility AI technology, to power Spin Insight. This is Spin’s latest step in building trust in e-scooters among consumers and cities by enabling technology that creates a safer riding experience for riders and pedestrians.
“With nearly all municipalities prohibiting scooter use on sidewalks, Spin Insight data — in combination with Spin’s in-app mapping technology that enables riders to find routes that maximize bike lane use — can be used as a tool by cities to help enforce local regulations and promote safe riding behaviors in dense, urban environments like New York City.”
Additionally, the technology will enable Spin to share accurate insights with cities about the prevalence and location of sidewalk riding and bike lane riding, which can be used to identify potential congestion issues and road damage and highlight areas that may benefit from infrastructure improvements.