Chinese autonomous driving firm Pony.ai launched commercial robotaxi services in Zagreb, Croatia on April 8. Photo:Courtesy of Pony.ai Chinese autonomous-driving company Pony.ai said on Monday that its cumulative autonomous-driving distance worldwide has surpassed 100 million kilometers, marking the latest milestone as China's driverless sector moves from technology validation toward mass production and scaled commercial deployment. The milestone comes as L4 autonomous driving gains commercial traction across passenger transport and logistics in China, while Chinese companies are accelerating overseas deployment through partnerships with local operators in markets including Europe and Southeast Asia. Industry experts said that the significance goes beyond rising distance. As commercialization gathers pace, the next phase of competition will increasingly hinge on whether autonomous-driving technology can be deployed at scale, brought down to commercially viable costs and replicated across different transport scenarios and markets. At a recent media briefing, Pony.ai said that its fourth-generation L4 autonomous electric heavy-duty truck had entered mass production, with commercial operations expected to begin in the coming months. The company plans to deploy 500 to 1,000 trucks over the next two to three years across long-haul freight, bulk cargo transport and port logistics. A notable part of that transition is the sharp decline in costs. Autonomous-driving hardware costs for Pony.ai's fourth-generation heavy truck are about 70 percent lower than for the previous generation, according to the company. Similar cost reductions are also emerging in robotaxis. Pony.ai said on its official blog that the bill-of-materials cost of the autonomous-driving kit for its seventh-generation robotaxi has fallen 70 percent from the previous generation, helping the company achieve unit-economics breakeven in Guangzhou and Shenzhen, South China's Guangdong Province. China's autonomous-driving sector is moving from technology validation to large-scale commercial deployment, underpinned by the rapid accumulation of real-world driving data, Pan Helin, a member of the Expert