Microvision eyes trucking with next-gen LiDAR strategy Microvision says commercial trucking could emerge as one of the most practical early adopters of next-generation LiDAR technology, as fleets search for ways to reduce crashes, insurance costs, and eventually enable autonomous freight operations. During a presentation at a House of Journalists event ahead of ACT Expo, Greg Scharenbroch, vice president of engineering at Microvision outlined the company’s “LiDAR 2.0” strategy. He said the company is already testing its systems on commercial trucks in Europe and repositioning its technology away from the robo-taxi hype cycle that defined the industry’s first wave of investment. “The economics just didn’t work,” Scharenbroch said of earlier autonomous vehicle programs focused on self-driving taxis and trucks. Instead, the company is targeting more immediate commercial applications including advanced driver assistance, autonomous hub-to-hub trucking, blind-spot monitoring, yard automation, and long-range obstacle detection. Microvision describes its LiDAR 2.0 approach as a shift toward scalable, lower-cost systems designed specifically around commercial viability. Presentation slides shown during the briefing emphasized four core pillars: broader multi-sector deployment, design-to-cost engineering, software integration, and financial discipline. Scharenbroch said one of the key advantages of LiDAR over conventional camera-based systems is its ability to detect hazards far beyond headlight range. “If a truck is traveling down the highway at a certain speed, it needs to look out so far and see something in the dark with very low reflectivity on the ground … and be able to detect it in time to provide enough advanced warning to allow the driver to do an evasive maneuver or slow down,” he explained The company said its current long-range systems can detect objects at roughly 820 feet (250 meters), while an ultra-long-range sensor under development could eventually scale to approximately one kilometer. Microvision also outlined the financial case for LiDAR