顺丰三次加注，无人车公司「白犀牛」完成近5亿元B轮融资｜36氪独家

Core Insights - The core focus of the article is on the recent B+ round financing of the autonomous driving company, White Rhino, which has raised nearly 500 million RMB in total during its B round, indicating strong investor confidence in the logistics automation sector [1][2]. Financing and Investment - White Rhino has completed its B+ round financing, accumulating nearly 500 million RMB in total for its B round, with existing investors like SF Express and Linear Capital participating alongside new investors such as Jun Capital and 360 Fund [1]. - The funds from this round will be directed towards the development of vehicle-grade autonomous vehicles, continuous iteration of AI technology, and expansion into commercial scenarios [1][6]. Market and Business Model - The company is targeting the unmanned logistics sector, which is currently experiencing a commercial explosion due to technological advancements, cost reductions, and supportive government policies [1][3]. - White Rhino's primary product, the R5 series unmanned vehicle, has a cargo volume of 5.5 m³ and can carry over 500 packages, with a range of over 120 kilometers on a full charge [4]. - The company aims to increase its daily active vehicle count to 5,000 by 2026, with current active vehicles growing from nearly 100 at the end of 2023 to around 1,000 by August [4][9]. Operational Efficiency - White Rhino's unmanned vehicles can reduce last-mile delivery costs by 30%-50%, addressing the inefficiencies and high labor costs associated with traditional delivery methods [5]. - The vehicles operate 24/7, allowing for remote scheduling and execution of delivery tasks, thus enhancing operational efficiency for clients [5]. Technological Development - The company is focusing on developing vehicle-grade autonomous vehicles, which are expected to enhance asset value and improve market deployment rates and safety [6]. - White Rhino is transitioning from high-precision mapping to a BEV+Transformer architecture, which integrates multi-sensor data to reduce errors and improve adaptability in complex scenarios [7][8]. Future Prospects - As the company approaches a scale of 10,000 vehicles, it anticipates achieving financial profitability, with a clear path towards commercialization as the industry shifts from technology validation to rational consumer adoption [9].