Summary of Key Points
Recently, leading companies that were initially focused on intelligent driving for passenger vehicles (such as Qingzhou Zhihang, Youjia Innovation, and Pony.ai) have collectively shifted to the field of autonomous logistics vehicles. This shift is driven by four main factors: intense competition in L2 intelligent driving for passenger vehicles resulting in thin profits, the emergence of image-free technology that lowers the barriers to implementing L4-level automation, the explosive growth of the last-mile logistics market, and gradually easing policies. Each company adopts different strategies (focusing on cost-effectiveness, partnering with platforms, or validating technologies), but the market is already dominated by pioneers like Jiushi Intelligence and New Stone, which hold nearly 90% of the share. New entrants face challenges such as price wars, verifying business models, and dealing with fragmented policies.
Why Are Intelligent Driving Companies Turning to Logistics Vehicles Instead of Passenger Vehicles?
The competition in the intelligent driving for passenger vehicles market has driven prices down to almost nothing: L2+ solutions, which cost 3,800 yuan last year, are now being sold for 1,800 yuan and still face price cuts from customers, resulting in minimal profits. In contrast, there are four compelling reasons for turning to autonomous logistics vehicles:
1. Reduced technical barriers: Image-free technology allows L4-level autonomous vehicles to operate without high-precision maps, reducing deployment time from weeks to days, making it feasible for companies that were previously unable to implement L4 solutions.
2. Large market potential: The last-mile logistics market is worth trillions of yuan, with an expected annual production of 860,000 autonomous delivery vehicles by 2030 (compared to less than 40,000 in 2025).
3. Fast revenue generation: Delivery for passenger vehicles requires a 1-2 year development cycle and long payment terms from car manufacturers, whereas autonomous logistics vehicles are delivered quickly, generating revenue promptly (for example, Youjia Innovation’s autonomous vehicle business saw a 450% increase in revenue in the second half of 2025).
4. Easing policies: In July 2026, the first national standard for autonomous delivery vehicles was implemented, and more cities are opening up access to these vehicles.
New Players Show Their Skills: Some Compete on Price, Some Partner with Platforms, Some Focus on Technology
Different companies adopt various strategies, which can be categorized into four main types:
- Cost-Effectiveness Focused: Qingzhou Zhihang has reduced the cost of its L4 autonomous vehicle solutions to below 10,000 yuan by bulk purchasing sensors, making its vehicles affordable and operational.
- Platform Partnering: Youjia Innovation collaborates with Didi to provide autonomous vehicles integrated into the Didi app, earning revenue through service fees rather than just selling vehicles.
- Technology Validation: Companies like Zhuoyu Technology and Momenta use logistics vehicles as a testing ground for their AI models, applying their general-purpose AI solutions (such as native multimodal models or the R7 base model) to both passenger and logistics scenarios.
- Experience Transfer: CaoCao Chuxing applies its Robotaxi scheduling experience to logistics, partnering with Geely to invest in 100,000 autonomous trucks for both passenger and freight transportation.
Are New Players Going to Have Success Against Established Players?
Before new companies entered the market, Jiushi Intelligence (part of the Cainiao Group) and New Stone already held nearly 90% of the market share: Jiushi has 25,000 vehicles, and New Stone has 17,000. They have also secured investments from industry giants like Ant Group and Tencent, as well as logistics companies like Cainiao and Didi. Their advantage lies not in technology but in their scale, data, and ecosystem: they own a large number of vehicles and operate in various scenarios, providing valuable data and access to logistics platforms.
With the addition of new players and traditional automakers (such as Geely, Changan, and Dongfeng), competition has intensified. The price of smaller vehicles has dropped from millions to below 20,000 yuan, and the cost of solutions has been reduced to below 10,000 yuan. For example, BaiXiniu and Xinyuan have formed joint venture vehicle manufacturers, while Dongfeng has launched its own autonomous vehicle brand, collaborating with both intelligent driving companies and established players.
Challenges for New Players
New entrants face significant hurdles:
1. Price Wars: Dropping prices squeeze profits; only those operating in a RaaS (Software as a Service) model can make money.
2. Verifying Business Models: The success of the RaaS model depends on generating enough daily orders per vehicle; for instance, Qingzhou Zhihang’s operations in Suzhou are only profitable in specific use cases like park delivery.
3. Fragmented Policies: Although a national standard has been established, policies vary from city to city, making it difficult to scale nationwide. For example, some cities allow autonomous vehicles on non-motorized lanes, while others do not, complicating scheduling.
In Conclusion
Autonomous logistics vehicles represent a second growth opportunity for intelligent driving companies, but it’s not an easy path to success. New players must compete with established players on price, secure orders, and navigate fragmented policies. Ultimately, only those who can effectively combine technology, operations, and an ecosystem will emerge victorious.