China Intelligent Driving Tier1s Leading the End-to-end Paradigm Shift
In this post, we look at a number of intelligent driving Tier1s in China that have revealed notable progress in developing end-to-end solutions.
Huawei
Huawei has become a leading supplier of smart car technologies in just five years since it revealed its auto ambitions in 2019. Speaking of intelligent driving, it was the first to make city NOA accessible across the entire country.
First launched in 2023, Huawei ADS2.0 adopted a General Obstacle Detection (GOD) network in the perception layer and a Road Cognition & Reasoning (RCR) network to replace HD map, together enabling city Navigation Cruise Assist (NCA), also known as NOA. In the latest ADS3.0, it has aggregated the perception task to a single GOD network with scenario comprehension capabilities (exhibit 1). It has also incorporated a single neural network in the Prediction, Decision and Planning (PDP) layer. In parallel to the PDP network, there is an instinct safety network with pre-defined rules to ensure safety bottom line (exhibit 2). ADS3.0 was claimed to bring human-like driving style with the new end-to-end architecture.
According to a recent press conference, Huawei has a total computing power of 5 EFLOPS, grown from 3.5 EFLOPS in June. The system is being trained with 35 million km data on a daily basis thanks to the rapid growing cars on the road fitted with ADS. ADS3.0 was first released on Stelato S9 (Stelato is a new brand under BAIC), and would be updated onto vehicle models from AITO, a brand under Seres, Luxeed, a brand under Chery, Avatr, a brand under Changan, etc.
Deeproute.ai
Deeproute started out in 2019 to develop L4 autonomous driving technologies. The company was less raved about as opposed to its robotaxi rivals like Pony.ai and WeRide until September 2021 when Alibaba led its series B funding round. Deeproute did launch a few L4 solution packages but has over time come to embrace L2 technologies, where the demand is much higher.
Last year, it introduced DeepRoute-Driver 3.0 for mass production passenger cars, which included hardware and software stack to enable city NOA without HD map reliance. In April of this year, it launched DeepRoute IO, an end-to-end solution built on Nvidia DRIVE Orin with 7 cameras and 1 LiDAR. According to the company’s marketing slide (exhibit 3), Deeproute has reached the one-model end-to-end architecture compared to most players in the modular end-to-end stage (reference post). The founder and CEO, in an interview, owned it to the team’s forward vision on autonomous driving technologies, due to which reason the development efforts have always been ahead of buzzwords like early fusion, BEV (Bird’s Eye-View), mapless and the ongoing end-to-end.
DeepRoute claimed to be working with several local and international OEMs at the moment and the first batch of about 10,000 vehicles carrying its end-to-end systems would hit the market within the year. Although not officially confirmed, one of the OEMs is said to be Great Wall Motor.
SenseAuto (SenseTime)
SenseTime has started devoting efforts in the automotive sector since 2017 (reference post). It officially introduced the brand name SenseAuto in 2021 aiming to become an automotive Tier1 supplier. Till now, it has delivered smart cabin solutions to major OEMs covering 100+ vehicle models. However, the attempts on smart driving didn’t get much attention until the new wave of end-to-end autonomous driving, where the company’s specialties in AI are crucial.
Obviously the team got the idea of end-to-end in 2017 when Honda requested an intelligent driving solution with cameras only (no HD map). A research team at SenseTime followed the direction ever since and came up with UniAD in late 2022 that won CVPR 2023 Best Paper Award. UniAD looks like a design of modular end-to-end system (reference post “Stage 3”). It coordinates five essential tasks in a planning-oriented philosophy. The query design serves as interfaces connecting all nodes resulting in flexible intermediate representations and exchanging multi-task knowledge toward planning (exhibit 4).
In recent months, SenseAuto demonstrated the capabilities of UniAD system on complex city roads with cameras only. In terms of model training, the company currently collects data from test drive and obtains synthetic data through world model. After the system is deployed on mass production vehicles, which is expected in 2025, partner OEMs would feed the data back to SenseAuto. It has established a supercomputing center in Shanghai that currently boasts over 45,000 GPUs with a total computing power of 12,000 PFLOPS.
Pony.ai
Pony.ai is one of the leading L4 autonomous driving technology companies with growing fleets of robotaxi and robotruck across China. It claimed to have proceeded to one end-to-end model in August last year and the model has been updated onto L4 robotaxis and L2 mass production passenger cars.
Pony sees its advantage in end-to-end autonomous driving as multiple data sources for training that include robotaxi fleets, L2 passenger cars and roadside sensors. It has also built up evaluation systems and simulation software over the years to better process data.
The company has teamed up with ROX motor, an EV startup that launched the first model in 2023 with a few hundred sales volumes per month, and Pony supplied the intelligent driving system in the premium version. It has not disclosed any other projects with OEMs.
Horizon Robotics
Horizon Robotics is known for developing cost-effective AI chips used in passenger vehicles’ intelligent driving systems as well as providing software and hardware co-optimized solutions to OEMs and Tier1s. The company was reported to have consolidated the solution team in October of last year dedicating all efforts on a high-level intelligent driving solution, later revealed as SuperDrive. It is built on the J6P chip with 560 TOPS, the most advanced one among Journey 6 series launched earlier this year.
SuperDrive adopts a world model in the perception task with sensors and navigation map as inputs, which outputs both feature-level info and dynamic & static objects. The feature representations then feed into an end-to-end planner and the object list feeds into a hybrid planner with some hand-coded rules and a validation network. Through an interactive evaluation process, the hybrid planner would eventually generate the optimal trajectory (exhibit 6).
Horizon recently demonstrated SuperDrive performance on pubic roads. It claims to be working with a number of OEMs on delivering the solution and the first vehicle model is expected to hit the market in Q3 2025.
PhiGent Robotics
PhiGent Robotics was founded in 2021 aiming to become an intelligent driving solution provider. The company is fairly young while the co-founders come with extensive experience in the semiconductor industry previously with such as AMD, Horizon and Baidu, probably for which reason it has completed six funding rounds so far with the latest one being Pre-B of $30 million.
PhiGent is looking to differentiate with pure vision and stereovision, in other words affordable cost, enabling the highly demanded city NOA functions. It claims to have won multiple projects with PhiGo, a mid-level intelligent driving solution, of which the basic version is built with 7 cameras only on a single Horizon J6E chip.
Meanwhile, the company teams up with Geely research institute and has together proposed GraphAD for end-to-end autonomous driving algorithm that employs a graph model to describe the complex interactions in traffic scenes. GraphAD will be incorporated in its high-level intelligent driving solutions to be launched in 2025. The CTO of PhiGent believed that the boom of large language models in 2023 in fact inspired a path for end-to-end autonomous driving to go from concept to reality. Eventually, they will deploy a multimodality foundation model on the cloud to work together with onboard GraphAD.
