Bird Vehicles Can Now Detect Sidewalk Riding  

Bird, a shared micro-mobility operator, is getting on the ADAS bandwagon. The company has launched new technology, after three years of research, to detect when a rider is scooting on the sidewalk. Once detected the tech can bring them to a halt.  

Currently, the tech is being piloted in scooters in San Diego and Milwaukee. It is expected to reach Madrid and other cities by next year.   

Scott Rushforth, chief vehicle officer at Bird, said new vehicles will be built with sidewalk-detection-equipped vehicles to come off the assembly line. The feature aims to address the concern of cities everywhere about shared micro-mobility.   

The new tech is made possible through a partnership with u-blox, a Swiss wireless semiconductor producing company. Together, they co-developed a unique version of u-blox’s ZED-F9R module. The tech is specifically tailored to meet the needs of the micro-mobility industry.  

“It takes input from the GPS sensors, and it uses a dual-band GPS sensor, which is the best of the best in terms of GPS,” Rushforth told TechCrunch.   

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“What we’ve added on top of that is a system called RTK, which stands for real-time kinematics. And then we’ve added on top of that a system that uses sensor fusion that takes all this data together as well as data from the vehicle itself, like how far the wheel has gone or the angle the scooter is leaning and infuses it with the GPS location so that it gets an extremely accurate view of where the vehicle is, even in times where the GPS signal does not work very well.”  

Riders will receive alerts when they enter the sidewalk of their transgressions via a new 16-bit color display and the mobile application. After that, the scooter will auto-remove its throttle and brings itself to a halt.  

The company has been exploring sidewalk detection technology since 2019. There appear to camp in the world of micro-mobility rider-assistance systems, populated by companies relying on sensor fusion and super precise positioning to detect poor riding behavior.