Dublin, March 28, 2024 (GLOBE NEWSWIRE) -- The "L3/L4 Autonomous Driving and Startups Research Report, 2024" report has been added to ResearchAndMarkets.com's offering.
The favorable policies for the autonomous driving industry will speed up the commercialization of L3/L4.
In the second half of 2023, China introduced a range of policies concerning autonomous driving, allowing L3/L4 autonomous vehicles to take to the roads legally in China. These important policies also invigorate China's autonomous driving industry, further spur the development of technologies and business models for L3/L4 autonomous vehicles, and accelerate their large-scale commercialization.
As China releases autonomous driving policies, the competition in intelligent driving is about to enter a new phase. So far, nine auto brands, including Deepal, Avatr, Seres, IM, Mercedes-Benz, BMW, Arcfox, BYD, and GAC, officially announced that they had acquired L3 autonomous driving road test licenses.
L2++ reversely feeds L3/L4, and parallel strategy enables data and technology iteration.
Thanks to breakthroughs in core technologies such as chips and algorithms in the past few years, L2++ high-level driving assistance (highway NOA and urban NOA) has begun to enter a phase of large-scale promotion. This type of vehicles is very large in scale and can record a variety of complex scenarios and accumulate massive training data.
Suppliers working on L3/L4 autonomous driving, such as Baidu Apollo, Pony.ai and DeepRoute.ai, have started partnering with automakers to commercialize L2++ high-level driving assistance. On the one hand, they aim to increase business profits; on the other hand, they hope to collect road test data trained for L3/L4 use, and then enable a closed loop through autonomous driving iteration. In addition, quite a few emerging carmakers also use the L2 and L3/L4 parallel strategy to deploy high-level autonomous driving.
As L4 Robotaxi faces setbacks overseas, how to continue to forge ahead with commercialization in China?
The commercialization of Robotaxi has been hampered at abroad. In August 2023, Waymo and Cruise were allowed to launch paid 24/7 Robotaxi services in San Francisco, California. Yet since the launch of the paid Robotaxi services, safety issues and accidents involving the operating vehicles have appeared one after another. Currently Cruise has lost its self-driving licenses in California, and has suspended all its self-driving services in the United States.
Then how to forge ahead with commercialization of Robotaxi in China? The operation of Robotaxi needs to consider how to cooperate with governments, OEMs, mobility platforms, technology companies and other parties to build an effective ecosystem. At present, in China Robotaxi players include: 1. L4 autonomous driving technology solution providers such as Baidu, Pony.ai, WeRide, and Auto X; 2. Conventional automakers like BMW and Audi, and emerging carmakers such as Tesla and Xpeng.
Robotaxi Business Model 1: 'Iron Triangle'.
The combination of RoboTaxi company + mobility platform + automaker is the mainstream cooperation mode in current stage. This 'iron triangle' model gives full play to the respective strength of the three parties, and allows each party to be responsible for what it is best at, so that Robotaxi can be promoted faster and more efficiently, and a closed loop for the commercial implementation of autonomous driving in scenarios can be built.
As technology solution providers, Robotaxi companies enable asset-light operation. The use of OEMs' autonomous driving platforms, vehicle design and manufacturing capabilities makes them superior in terms of mass production speed and manufacturing cost;
Mobility service operators already boast a stable user base, good mobility service experience and massive data. They have great advantages in traffic entrance, user mobility data and operation management experience. Without the traffic support of mobility platforms, Robotaxi companies will be very slow in subsequent data accumulation, which will in turn affect the quality and speed of software algorithm iterations;
OEMs with strong manufacturing capabilities can provide infrastructures and physical bases for the large-scale deployment of Robotaxi.
In addition to its own mobility platform PonyPilot+, Pony.ai also cooperates with automakers like Geely, GAC, FAW and SAIC, and is connected to OEM-backed mobility platforms such as Caocao, ONTIME, T3 Mobility, and Hongqi Smart Mobility. Pony.ai has put its Robotaxi into commercial operation. At present, Pony.ai has deployed autonomous fleets in the four cities of Beijing, Shanghai, Guangzhou and Shenzhen. As of December 2023, Pony.ai has boasted a total mileage of more than 28 million kilometers of autonomous driving road tests on complex urban public roads.
In January 2024, the GAC Toyota Sienna Robotaxi model packing Pony.ai's 6th-generation autonomous driving software and hardware system obtained the commercial demonstration operation license from Nansha District, Guangzhou. It launches paid services via Pony.ai's own platform PonyPilot+ and ONTIME. The Robotaxi covers all of Nansha District with 803 square kilometers, and runs at 8:00-22:30 including morning and evening peak periods.
This Robotaxi model was jointly developed by Pony.ai and Toyota, and GAC Toyota was responsible for producing it. 15 units of this vehicle have been connected to ONTIME. It is also the second model that Pony.ai has joined ONTIME for mixed operation. The two parties will facilitate the large-scale commercialization of Robotaxi services by complementing each other with the 'technology + platform' model.
Robotaxi Business Model 2: emerging carmakers make a foray into the field.
Utilizing their own resource system, emerging carmakers have more abilities to build their own ecosystem in Robotaxi. Their full-stack self-developed autonomous driving capabilities, large chip and sensor procurement, vehicle mass production capabilities, and massive user data will give them a bigger initiative in the competition in the Robotaxi market.
Xpeng Robotaxi, built on the model G9, is a completely OEM model with no hardware additions, and functional iterations only via software. Compared with other aftermarket Robotaxi models on market which often cost hundreds of thousands to one million yuan, Xpeng Robotaxi offers higher cost performance, making it feasible to truly and fully implement this business model in the future.
In addition, Robotaxi cannot be commercialized without the support of favorable policies. In current stage, governments across China are doubling down on the Robotaxi market, and there have been more than over 30 cities introducing policies concerning intelligent connection. In January 2024, 17 departments including the National Data Administration jointly issued the Three-Year Action Plan for 'Data Elements ' (2024-2026), suggesting promoting the innovative development of intelligent connected vehicles, supporting the commercial trial operation of autonomous vehicles in specific areas and specific periods, and breaking down the data barriers between automakers, third-party platforms, transportation companies and other entities.
A new mobility ecosystem cannot be built in a short period of time. It not only requires incentive policies, but also cooperation of the entire industry to jointly advance the maturity and implementation of technologies and standards and continue exploration of mature models for commercial implementation. In the short term, Robotaxi's commercial closed loop may mainly rely on the coordinated development of mobility service operators and autonomous driving technology companies.
Key Topics Covered:
1 L3/L4 Autonomous Driving Policies, Regulations and Standards
1.1 Driving Automation Taxonomy and Standardization
1.2 China's Autonomous Driving Policies and Regulations
1.3 Global Autonomous Driving Policies and Regulations
2 Status Quo of L4 Autonomous Driving Market
2.1 L4 Autonomous Driving Market Size
2.2 L4 Autonomous Driving Competitive Pattern
3 Application Sub-scenarios of L4 Autonomous Driving
3.1 Business Model
3.2 L4 Application Scenario - Robotaxi
3.3 L4 Application Scenario - Autonomous Shuttle
3.4 L4 Application Scenario - Autonomous Delivery
3.5 L4 Application Scenario - Autonomous Truck
4 Key Technologies for Mass Production of L4 Autonomous Driving
4.1 Key Technologies for L4 Autonomous Driving: Algorithms
4.2 Key Technologies for L4 Autonomous Driving: Data Closed Loop
4.3 Key Technologies for L4 Autonomous Driving: Redundancy
4.4 Key Technologies for L4 Autonomous Driving: Vehicle-Road-Cloud Cooperation
4.5 Key Technologies for L4 Autonomous Driving: HD Maps and Positioning
5 L3/L4 Autonomous Driving Solutions of OEMs
5.1 L3/L4 Autonomous Driving Layout of OEMs
5.2 Xpeng
5.3 Li Auto
5.4 Chery
5.5 GAC
5.6 Great Wall Motor
5.7 Tesla
5.8 Toyota
5.9 Volvo
5.10 Mercedes-Benz
5.11 Volkswagen
5.12 SAIC
5.13 Other Automakers
5.13.1 BMW's L3 Autonomous Driving Solution
5.13.2 Hongqi's L4 Autonomous Driving Technology Solution
5.13.3 Yutong's L4 Autonomous Driving Technology Solution
6 L4 Autonomous Driving Solutions of Tier1s and Startups
6.1 Waymo
6.2 Cruise
6.3 Aurora
6.4 Valeo
6.5 Baidu Apollo
6.6 Pony.ai
6.7 WeRide
6.8 AutoX
6.9 Momenta
6.10 DeepRoute.ai
6.11 Huawei
6.12 Haomo.ai
6.13 Allride.ai
6.14 UISEE Technology
6.15 Idriverplus
6.16 QCraft
6.17 TuSimple
6.18 Plus.ai
6.19 Inceptio Technology
6.20 CiDi
6.21 Deepway
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