SinoAuto obtains RMB 300 million in Series C financing, the autonomous driving heavy truck sector heats up again | 36Kr Exclusive

The autonomous driving heavy truck sector has seen a notable surge in momentum this year.

36Kr has learned exclusively that SineDrone recently completed a RMB 300 million Series C financing round, co-invested by Xingzheng Capital and Yidao Capital. The funds will be primarily allocated to the research and development of a new generation of vehicle-grade autonomous driving solutions.

From January to June 2026, the sector has recorded 5 publicly disclosed financing deals totaling nearly RMB 7 billion, alongside a flurry of IPO activities. Behind this capital frenzy, autonomous driving heavy trucks are gradually gaining clear commercialization pathways. Closed scenarios such as ports, mines, and steel mills have developed steady demand for unmanned heavy trucks, while open scenarios like trunk logistics are also beginning to roll out alongside supportive policies, standing on the cusp of large-scale deployment.

Founded in April 2020, SineDrone is a company focused on the R&D and implementation of unmanned driving technologies in the heavy-duty logistics sector, providing autonomous driving solutions for multiple scenarios including ports, industrial parks, and trunk logistics.

Currently, SineDrone's business model features a multi-vehicle, multi-scenario, and multi-operation chain structure.

On the product front, unmanned container trucks, unmanned dump trucks, and unmanned flatbed trucks form SineDrone's core product lineup. Underpinning these offerings are its self-developed one-stage world model autonomous driving solution, as well as core hardware including domain controllers and positioning boards.

In terms of deployment models, SineDrone provides two options: direct sales of complete vehicles, or provision of capacity-as-a-service. In closed scenarios, the company has achieved implementation across traditional container ports, bulk cargo yards, steel plants, paper mills, aluminum plants, railway stations, and logistics hubs. In open scenarios, it has established partnerships with several logistics companies and state-owned enterprises.

Closed scenarios, with their inherent predictability, remain the core stronghold for the deployment of autonomous driving heavy trucks.

Although vehicles have achieved fully unmanned operation, surrounding links such as loading/unloading and trailer swapping still require human intervention in actual logistics operations, presenting new challenges to traditional logistics transportation models.

He Bei told 36Kr that expanding partial "unmanned transportation" into full-scale "unmanned operations" is one of the company's key priorities moving forward. "Horizontal transportation automation has already been realized. Can we introduce world models and embodied intelligence to achieve integrated upgrades for vertical transportation and end-side collaboration, ultimately delivering fully unmanned operations in closed scenarios? We expect to see an answer in the next 3-5 years."

However, He Bei predicts that open scenarios will see higher growth rates in the future. Therefore, following this financing round, SineDrone will drive the upgrade of its autonomous driving heavy truck domain controllers from non-vehicle-grade to vehicle-grade standards.

CEO He Bei candidly stated to 36Kr, "The domain controller is the true brain of unmanned driving." In the unmanned driving product chain, vehicle execution components including throttle, brakes, and by-wire technologies are already highly mature, while sensors such as radars and cameras are essentially just data collection tools. "Whether a vehicle can transition from human-operated to fully unmanned ultimately depends on all the software embedded in the controller."

"We have already launched our vehicle-grade solution," He Bei told 36Kr. Achieving vehicle-grade standards is extremely challenging, as "hardware, operating systems, middleware, and even upper-layer software model modules all require reconfiguration and optimization."

Compared to closed scenarios, open trunk logistics scenarios often face multiple challenges including long-distance bumpy roads, extreme temperature fluctuations, and strong electromagnetic interference, which drastically increase the failure risk of non-vehicle-grade components. The transition from small-scale testing to large-scale commercialization, and from closed environments to open public roads, makes vehicle-grade compliance a make-or-break threshold that all autonomous driving enterprises must cross.

The challenges in open scenarios extend far beyond vehicle-grade compliance. He Bei told 36Kr, "The data volume in open scenarios is 1 to 2 orders of magnitude higher than in closed scenarios. The industry has largely focused on deployment in closed environments in the past, so another key priority for us is to accumulate more data and optimize our entire model."

While scaling up its domestic operations, SineDrone has also made new progress in its overseas business. He Bei revealed to 36Kr that the company has secured a designated domain controller project from a leading overseas enterprise.

The RMB 300 million Series C financing for SineDrone not only represents a significant bet from scenario-based logistics players but also reflects a widespread consensus in the sector: only by fully consolidating the market foundation in closed scenarios and successfully crossing the vehicle-grade threshold in open scenarios can enterprises qualify to pursue the next level of growth.

Below is the edited conversation between He Bei, CEO of SineDrone, and 36Kr, with the original meaning fully preserved:

36Kr: What will be the key priority for closed scenarios moving forward?

He Bei: The goal is to transform unmanned transportation into fully unmanned operations. Heavy trucks are merely transportation tools, not loading/unloading equipment. From an end-to-end perspective, relying solely on autonomous driving heavy trucks leaves a missing link. A complete operational workflow requires combining the horizontal transportation capabilities of heavy trucks with vertical operations such as loading and unloading.

In many of our current scenarios, tasks like trailer swapping still require manual operation. We are exploring whether these tasks can be automated using robots in the future. For instance, can forklifts and cranes be fully unmanned through embodied intelligence technologies? Our ultimate objective is to achieve full-process unmanned operations covering both transportation and loading/unloading.

36Kr: Has this workflow already entered testing phases?

He Bei: It is currently in the R&D and testing stage, and full deployment will not happen overnight. This initiative presents enormous technical challenges, and I estimate it will take 3 to 5 years to launch. Compared to the 10-year development cycle for unmanned driving to reach commercialization, the timeline for unmanned logistics operations is already relatively short.

On one hand, the rapid advancement of AI is accelerating our entire R&D and deployment process. On the other hand, labor costs are continuously rising. In many domestic sanitation scenarios, unmanned operations have already made significant progress, with certain functions completely eliminating human involvement. Full unmanned operations will inevitably become a reality eventually, so we believe it is far better to start early than to lag behind.

36Kr: Humanoid robots are currently a major trend. Does SineDrone have relevant plans in this area?

He Bei: First, we will not develop humanoid robot hardware ourselves. Second, our domain controllers have already received orders from embodied intelligence enterprises. SineDrone's role in this ecosystem will focus on collaboration and ecosystem integration.

36Kr: What defines the critical competitive inflection point for autonomous driving heavy truck companies today?

He Bei: I believe three factors are decisive. First is brand recognition: there is little room left for new entrants or purely test-focused players, and a company's established reputation largely determines whether clients will choose to partner with them. Second is data accumulation: leading companies have built strong footprints across various scenarios, backed by their proprietary data advantages. Third is computing power and computing platforms, including integrated data closed-loop systems and flywheel architectures. These three elements represent the core areas of competition among industry players.

36Kr: What are the major obstacles preventing autonomous driving heavy truck companies from achieving profitability?

He Bei: Excluding R&D expenditures from gross profit calculations, I believe all companies are at roughly the same level with no fundamental differences. The core differentiator lies in controlling the three major expense categories.

Simply put, sales expenses depend on the scale of your business operations and the external support ecosystem you have established. R&D expenses are determined by how efficiently you leverage AI technologies and the maturity of your internal productization processes. These two factors are the primary constraints limiting profitability for enterprises.

Autonomous driving heavy truck operations are inherently part of the automotive manufacturing ecosystem. In China's manufacturing industry, profit margins are generally thin, so the only viable path is to continuously reduce hardware costs and overall operational expenses.

I believe this is the core key point for succeeding in China's manufacturing sector.

36Kr: Many companies are now pursuing global expansion. What is the strategic significance of going overseas for autonomous driving heavy truck companies?

He Bei: The primary benefit of overseas expansion is undoubtedly revenue generation, but the associated risks are directly proportional to potential profits. First, if your pricing cannot reach 3 to 4 times the domestic market level, you will not be able to achieve profitability overseas. Second, overseas markets come with numerous regulatory restrictions. Where is the demand for unmanned solutions most acute? It is primarily in developed economies such as Europe, the United States, Australia, Japan, and South Korea, but their strong labor unions slow down the deployment pace significantly.

Regions including the Middle East, South Asia, and South America are mostly developing countries with low labor costs, so their sole motivation for adopting unmanned technologies is efficiency improvement. Our current overseas orders are mainly concentrated in these regions.

36Kr: Both passenger and commercial vehicle autonomous driving companies are pursuing IPOs intensively. Is this year the final window for autonomous driving enterprises to go public?

He Bei: It is hard to say definitively whether this is the last opportunity, but we predict that regulatory conditions may tighten in the second half of 2027. The industry has always experienced cyclical ups and downs, and even if conditions become stricter next year, the window may reopen the following year. Compared to pursuing an IPO, I believe focusing on strengthening core business fundamentals is far more important.