Alex Sutton
Head of Technology

[Watch] What the Next Big Breakthroughs in Tech and Design Mean for Micromobility

Teeth-rattling rides. Geofencing frustrations. Sidewalk clutter. Emerging micromobility solutions have huge potential to help ease congestion and prevent climate catastrophe, but they won’t get far unless we can overcome some of the frustration points for riders.

New designs and technologies, including AI, sensors, sidewalk detection, and gamification, could fundamentally reshape user behavior, improve safety, streamline maintenance and pave the way for automated vehicles.

Watch the lively discussion about the big breakthroughs that are coming in tech and design, and how they could transform micromobility as we know it, featuring:

Alex Sutton, Head of Technology, Synapse
David Hyman, CEO, Unagi Scooters
Kelly Custer, Founder and Design Director, Knack Design Studio
Eugene Kwak, Head of Bike and Scooter Hardware, Lyft

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How Micromobility Can Stay in the Game

While micromobility solutions have flourished and grown during the pandemic, the existential question of how to solve the biggest challenge ahead for the micromobility segment—how users ride—remains unanswered. In this post, we’ll touch on a number of opportunities for the industry to embrace innovation and technology in order to remain the chosen method of transportation, even in a post-COVID world.

November 25, 2020

[Watch] What the Next Big Breakthroughs in Tech and Design Mean for Micromobility

Watch an expert-packed panel discussion exploring new technologies like VR, AI, sensors, sidewalk detection, and gamification which hold the promise to reshape user behavior and solve micromobility issues for cities and operators. The panel is moderated by micromobility International and features leaders from Lyft, Unagi, Knack, and Synapse.

June 29, 2020

Sidewalk Detection on the Edge and Shared Micromobility: A Solution Analysis

As the only form of public transit that is readily capable of supporting social distancing, shared bikes and scooters will be an essential component of an effective urban economic recovery strategy in the coming months. Prior to COVID-19, the city of San Francisco announced that future shared scooter platforms will be required to have deterrents to riding on sidewalks. Naturally, being both SF residents who will be affected by this decision, and curious engineers with micromobility industry experience, we decided to leverage our expertise in machine learning to explore the specifics involved in implementing a system which can determine if a scooter is riding on a street or a sidewalk.