LAS VEGAS — The automated driving gold rush of the past decade produced hundreds of companies chasing self-driving trucks and robotaxis. Unfortunately for many, the economics never panned out. Things like billion-dollar development costs, expensive sensor suites and unsustainable business models led to flash-in-the-pan announcements that quietly faded. What survived, according to MicroVision’s leadership, was something more valuable: the infrastructure, algorithms and talent that now form the foundation of what the company calls LiDAR 2.0. “The mindset of Silicon Valley was to focus on performance: deliver the highest performance system and solution that you can give. And then over time, volumes will come and prices go down,” said Greg Scharenbroch, vice president of global engineering at MicroVision. “But that’s not really what happened.” Scharenbroch, a 30-year automotive veteran who joined MicroVision in November after working on ADAS systems and software-defined vehicle compute, believes the industry learned hard lessons from what he calls LiDAR 1.0. The company is now applying automotive discipline to sensor development, targeting commercial trucks, passenger vehicles, industrial automation and defense applications. This modular portfolio is designed primarily for cost efficiency. Four Pillars Driving the Strategy MicroVision’s approach rests on a broad portfolio that smooths revenue cycles by reusing core technology across sectors. Its design-to-cost mindset is rooted in automotive heritage and an emphasis on software differentiation. “We’re automotive folks. Our legacy is automotive,” Scharenbroch said. “Automotive development runway times are two, three, three and a half years of development investment before you see the first dollar of…
