QINGZHOU Zhihang releases new strategy and unveils new autonomous driving solutions

On May 18th, QCraft, a general-purpose autonomous driving solutions company, held its inaugural QCRAFT DAY (QCraft Brand Day). Three years after its founding, QCraft has accumulated significant experience in autonomous driving. At this Brand Day, QCraft, leveraging its innovative "Autonomous Driving Super Factory," unveiled a new "Dual Engine" strategy: a "Power Engine" built on L4 autonomous driving capabilities on public roads to improve urban transportation efficiency; and an "Innovation Engine" built on cost-effective, pre-installed, mass-produced autonomous driving solutions to accelerate the realization of autonomous driving.

Based on this "Dual Engine" strategy, QCraft officially launched two major solutions: Dragon Boat SPACE, a mobile travel space solution based on the "Power Engine" strategy, and DBQ V4, a fourth-generation, mass-produced, automotive-grade autonomous driving solution based on the "Innovation Engine" strategy. QCraft CEO Yu Qian stated that DBQ V4 achieves 99% of L4 capabilities at only 10% of the cost, with a mass production cost as low as 10,000 RMB. Qingzhou also announced that the Qingzhou Matrix, a simulation-based autonomous driving R&D toolchain, is now officially available for customer service. In the future, customers will not only be able to purchase Qingzhou's complete autonomous driving solution but also develop their own autonomous driving platforms. These two innovative solutions and a toolchain together constitute the "Qingzhou Solution."

The future application of autonomous vehicles will not be limited to transportation alone. Instead, they can become intelligent entities connecting passengers, transportation, and services, creating innovative models for intelligent mobile services. As a mobile travel space solution suitable for operation on complex public roads, Longzhou SPACE is positioned as a mobile travel space solution that can operate on complex public roads. It is adaptable to a variety of vehicle types, enabling seamless connections from long to short distances. Its space is also adaptable to various scenarios, such as retail, logistics, and other service models.

In fact, the Longzhou SPACE solution has already been tested. In December 2021, Qingzhou Zhihang and Dongfeng Yuexiang launched the Sharing Bus based on the Longzhou SPACE solution, bringing this future-oriented mobile space concept to life. At present, Sharing Bus has been put into operation in many cities including Wuhan and Dali, and has been widely used in scenarios such as smart transfers and scenic spot sightseeing.

It's worth noting that QINGZHOU Zhihang began its autonomous driving development with Robobus, a path that sets it apart from other companies. For QINGZHOU, Robobus was the starting point; Robotaxi is more readily commercially viable, while Robotaxi represents a more significant goal and direction. However, this development is challenging, with widespread adoption expected to take five or even ten years.

Currently, autonomous driving is rapidly entering the era of pre-installed mass production. However, meeting the demands of a vast array of vehicle models and application scenarios at a reasonable cost has become a significant constraint on the large-scale development of autonomous driving. QINGZHOU Zhihang's answer is DBQ V4, its fourth-generation, mass-produced, automotive-grade autonomous driving solution. Yu Qian explained that DBQ V4 integrates QINGZHOU's full stack of self-developed autonomous driving software and hardware technologies. DBQ V4 boasts precise, blind-spot-free perception and robust scenario adaptability. It supports 1-5 lidars, 0-4 blind-spot radars, 6 millimeter-wave radars, and 12 perception cameras, achieving 360-degree, blind-spot-free perception with redundancy on both sides. Through algorithmic recognition, DBQ V4 maintains stable perception performance in diverse lighting conditions and vehicle motion. Its customized traffic light recognition camera accurately identifies the shape and color of traffic lights, unaffected by ambient light interference.

Notably, all configurations of DBQ V4 share a common technology stack, adapting to sedans, SUVs, MPVs, buses, and other vehicle types. This means that even vehicles with different configurations can utilize the same underlying autonomous driving solution, significantly reducing unnecessary R&D costs and improving efficiency.

Beyond its technological sophistication, it boasts a cost-effective price tag of just 10,000 yuan. This makes DBQ V4 exceptionally cost-effective, given the widespread cost of autonomous driving solutions often reaching hundreds of thousands of yuan. Efficient data utilization is crucial for the efficient iteration of autonomous driving technology. However, rising road testing costs and limited coverage of long-tail scenarios have constrained the technology's iteration cycle, becoming a significant bottleneck facing industry development. The QINGZHOU Matrix, a critical foundation for the autonomous driving superfactory, is QINGZHOU's independently developed simulation-centric autonomous driving R&D toolchain. It streamlines the entire process from data processing, annotation, training, large-scale simulation, and technical output, maximizing data utilization. By leveraging simulation scenarios constructed from real road test data and generated data, the QINGZHOU Matrix can help developers reduce autonomous driving testing costs to 1% of those for pure road testing.
This means that in the future, customers will not only be able to purchase QINGZHOU's complete autonomous driving solution, but will also be able to develop their own autonomous driving platforms. Regarding the QINGZHOU Matrix, Yu Qian stated that OEMs require a tool to better manage their data and enhance the value of their data assets. QINGZHOU recognizes strong demand from OEMs in this area. "This is especially true for system delivery in the pre-installed mass-produced passenger vehicle sector. For example, once a vehicle reaches SOP and its intelligent hardware and software are installed, this isn't the end; it's likely just the beginning. This requires continuous data reflow, offline data collection, continuous model improvement, and uninterrupted performance to fully leverage the capabilities of the hardware and software. Over-the-air (OTA) upgrades can continuously provide end-users with a better driving experience."

In the era of large-scale autonomous driving, a safer, more cost-effective, and more comfortable driving experience has become a key industry priority. And QINGZHOU Zhihang, like a small ship, is forging ahead in this turbulent waters. "Our ultimate goal is to advance in depth and encompass a wider range of scenarios within the field of fully autonomous driving, achieving high-level autonomous driving, and making autonomous driving a reality. This is our mission at QINGZHOU Zhihang, and it has never changed," said Yu Qian.

From Sina Auto

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