Terranet, developer of the VoxelFlow computer vision system for autonomous driving, has announced the launch of a product for bicycle applications, called BlincBike. The company describes it as a connected e-bike product comprising a rearview monitoring system that classifies objects, calculates their distance and predicts their intention.
The monitoring system detects, tracks and classifies objects using AI-based computer vision, machine learning and deep neural networks. Terranet claims its algorithms will be able to classify objects and discern the appropriate threat and risk level, empowering cyclists to make smart and safe decisions in time to avoid collisions. Furthermore, in-motion recordings will capture critical traffic situations to assist insurance claims processes, but also for easy social editing and sharing via smartphone.
“BlincBike is our first product to target micromobility, but we see a tremendous potential in providing safety products in the forsaken and rapidly expanding micromobility space,” said Terranet CTO Nihat Küçük. “In the last four years, e-bikes were responsible for nearly 200,000 emergency room visits in the US. With our urban safety mission in mind, expanding into rapidly growing micromobility solutions is the logical next step for Terranet. We are thrilled to progress in using our unique technologies and continue advancing our mission of revolutionizing urban roadway safety.”
The company notes that 30% of all bicycle crashes are caused by cars and the most common bicyclist-motorist collision type is a rear end collision. With BlincBike, if a car suddenly approaches from behind, the cyclist will receive a warning on the rearview display mounted on the handlebars and/or through haptic feedback placed at the choice of the cyclist. This will allow the cyclist to avoid making any drastic turns that can cause a collision with the recognized object. A smart taillight will indicate the cyclist’s actions to the upcoming traffic: braking, moving, or stopping.