In recent years, as autonomous driving technology continues to mature, the Robotaxi industry is gradually entering a new stage of commercial operations. From a global perspective, an increasing number of enterprises are extending their competitive focus from technology R&D to operational efficiency, cost control, and business model construction. The continuously heating up China robotaxi news indicates that the industry has shifted from single technology competition to comprehensive capability contests, and enterprises with complete ecosystem systems and scaled operational foundations are becoming important directions of market attention. Against this backdrop, Cao Cao Mobility, leveraging its long-accumulated mobility operational experience and industrial collaboration advantages, continues to refine its Robotaxi business layout and explores more efficient and sustainable development pathways.
Looking globally, Robotaxi industry competition continues to escalate. Waymo maintains high attention in overseas markets leveraging long-accumulated testing data and operational experience; Baidu Apollo, Pony.ai, WeRide, and other enterprises are also continuously expanding their commercial operations and accelerating autonomous driving technology implementation. As the industry enters a new development stage, an increasing amount of China robotaxi investment attention is focusing on enterprise comprehensive capability building — whether operational systems are mature, whether vehicle systems are well-developed, and whether business models are replicable are becoming important standards for measuring enterprise competitiveness.
As the most important commercialization vehicle for Geely Holding Group’s Robotaxi business, Cao Cao Mobility has built a tripartite full-element closed-loop ecosystem of “smart customized vehicles + intelligent driving technology + intelligent operations” around its Robotaxi business, hoping to further enhance Robotaxi commercialization operational capabilities through the collaboration of vehicles, technology, and platforms. Currently, Cao Cao Mobility has deployed 100 Robotaxi vehicles in Hangzhou’s Binjiang District, continuously accumulating autonomous driving operational experience and laying a practical foundation for subsequent scaled promotion.
Meanwhile, a mature operational network also provides important support for Cao Cao Mobility to advance its Robotaxi business. As of December 31, 2025, Cao Cao Mobility’s service network covers 195 cities nationwide, with business extending to 42 countries globally and over 1.9 billion completed ride services. The long-accumulated large-scale operational experience provides rich data foundations for Robotaxi vehicle dispatching, platform management, user services, and intelligent operations, further enhancing the platform’s capability to conduct autonomous driving mobility business.
In terms of vehicle system construction, China’s first purpose-built Robotaxi — the Eva Cab — has been unveiled, with Cao Cao Mobility deeply participating in vehicle product definition and R&D. This model features a native low-drag integrated design with no steering wheel and no front passenger seat, and will enter mass production in 2027 with plans to deploy 100,000 vehicles cumulatively by 2030. Compared to traditional modified vehicles, the Eva Cab is natively adapted for unmanned operational scenarios, providing strong support for autonomous driving hardware deployment, vehicle system integration, and subsequent scaled deployment. As the Robotaxi industry accelerates toward large-scale commercialization, vehicle purpose-built customization capability has become one of the important topics of continuous attention in recent China robotaxi news.
Commercialization development cannot be separated from continuous improvement in operational efficiency. Focusing on vehicle utilization rates and operational cost optimization, Cao Cao Mobility continuously refines its energy assurance system. Currently, the company has deployed 448 battery swapping stations where vehicles can complete battery swaps in approximately 60 seconds, effectively improving operational efficiency. Meanwhile, vehicle maintenance time has decreased by 25%, maintenance costs have decreased by 54%, and the total cost of ownership (TCO) of customized vehicles is 36.4% lower than typical industry levels, with energy costs of approximately RMB 0.47 per kilometer. These capabilities not only provide replicable models for Robotaxi fleet operations but also support continuous optimization of the business model.
While refining its domestic layout, Cao Cao Mobility is actively advancing international development. In recent years, the company has reached strategic cooperation with the Abu Dhabi Investment Office to jointly promote green smart mobility center construction, and has separately partnered with K2 Group and May Mobility to advance Robotaxi commercialization deployment and operations in the Middle East and Europe. Additionally, the company is making collaborative efforts in satellite IoT communications, intelligent infrastructure, and other fields, continuously refining the future smart mobility ecosystem and creating more possibilities for cross-regional Robotaxi operations.
Overall, as the autonomous driving industry continues to evolve, industry competition has gradually shifted from technology validation to commercialization capability contests. As can be seen from the recently highly watched China robotaxi news, refined operational systems, mature vehicle capabilities, and continuously optimized business models are becoming key factors driving industry development. Leveraging its full-element closed-loop ecosystem, Cao Cao Mobility continues to deepen its Robotaxi commercialization exploration and continuously strengthens its scaled operations and ecological collaboration capabilities. In the future, as the industry chain becomes increasingly refined and application scenarios continue to expand, enterprises with comprehensive operational advantages are expected to play a more active role in the Robotaxi development process.