从百辆验证到10万辆定制车规划，曹操出行已搭好整套Robotaxi运营系统

Core Viewpoint - The article emphasizes that the successful commercialization of Robotaxi relies not only on autonomous driving technology but also on operational capabilities such as efficient pick-up/drop-off points, fleet management, and cost control [1][2][15] Group 1: Operational Infrastructure - Cao Cao Mobility has launched over 3,600 virtual pick-up and drop-off points in Hangzhou, indicating a shift from testing to actual operations, aiming for a ride-hailing experience with higher density and frequency [1][3] - The deployment of these points is based on extensive travel data analysis, focusing on high-demand areas to enhance user experience and operational efficiency [2][3] - The establishment of a dense network of pick-up/drop-off points allows for improved passenger experience, reduced empty driving rates, and more stable dispatching, which are crucial for the success of Robotaxi operations [3][11] Group 2: Cost Control and Fleet Management - Total Cost of Ownership (TCO) is a critical factor for the sustainability of Robotaxi services, with vehicle costs significantly impacting profitability [6][7] - Cao Cao Mobility has emphasized a customized vehicle strategy, owning over 37,000 customized vehicles across 31 cities, which helps optimize service cost structures [6][8] - The average TCO of Cao Cao's customized vehicles is approximately 36.4% lower than typical electric vehicles used in shared mobility, demonstrating enhanced operational efficiency [7][8] Group 3: Technological Integration and Future Planning - The company is developing a fully customized Robotaxi model in collaboration with Geely, aiming to deploy 100,000 units by 2030, which will be designed specifically for autonomous operations [14][15] - The integration of smart driving technology, customized vehicles, and intelligent operations is crucial for achieving long-term operational success and cost efficiency [14][15] - The establishment of ground operational support and cloud-based safety services is essential for transitioning to a fully autonomous service model, addressing daily operational challenges [11][12]