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Chinese LiDAR companies take the lead in autonomous driving innovation

(Xinhua) 13:12, January 15, 2024

LAS VEGAS, United States, Jan. 14 (Xinhua) -- In the competitive area of autonomous driving, Chinese LiDAR companies are playing an increasingly important role in paving the way for a future where cars navigate through streets without human intervention.

High-level driving automation is driven by the advancement of a critical sensor technology called LiDAR, which detects objects and calculates their distance to create a map of the surrounding environment, serving as the vehicle's "eyes."

At present, Chinese LiDAR technologies dominate the global market, and this year, autonomous driving will enter "a golden age," Qiu Chunchao, executive president of RoboSense Technology, told Xinhua during the Consumer Electronics Show (CES) that concluded in Las Vegas Friday.

Chinese companies have filed 25,957 related patent applications since 2000, compared with 18,821 by American companies and 13,939 by Japanese companies, Nikkei Asia reported on Jan. 8, citing Tokyo-based Patent Result.

Two Chinese companies, RoboSense and Hesai Technology, which specialize in two major types of LiDAR, one for fully automated driving and the other for driver assistance, have sharply increased their patents since 2015, ranking fourth and fifth globally.

Hesai Technology is strong in LiDAR for fully automated driving, leading the automotive LiDAR market in 2022 with a 47-percent share, according to the French research firm Yole.

The Shenzhen-based RoboSense, which focuses on the less expensive LiDAR technology for driver assistance, brought a series of new products to the 2024 CES, including mid-range and long-range sensors, which are marketed as cost-effective and capable of high performance.

RoboSense has sped up the innovation of its chip-driven LiDAR hardware and AI perception software to advance autonomous solutions. It has become one of the world's largest LiDAR companies by market cap, said Qiu.

In 2023, RoboSense shipped over 256,000 LiDAR units, with December alone witnessing 72,200 units sold, compared to just a few thousand in the same month of the previous year, according to Qiu.

"China's booming electric vehicle (EV) market fuels our mass-production capabilities, allowing us to build smaller, more efficient and cost-effective LiDARs," he said.

Qiu likened the LiDAR development to the battery industry, where China also takes the lead.

"Unlike the development of the century-old auto industry, LiDAR technology is a brand-new field. Chinese companies are starting on the same footing as everyone else," he said.

This level playing field, combined with China's unparalleled manufacturing prowess and EV boom, has created the perfect breeding ground for LiDAR innovation, he added.

In the LiDAR area, the competition is fierce among Chinese players, which partly helps lower costs. For example, Robosense's LiDARs have saved 50 to 70 percent on costs while power consumption remains low, Qiu said.

Wang Shiwei, chief executive officer of Tanway Technology, echoed Qiu's sentiments. From his first-hand experience at CES, he observed a shift in the landscape.

"Ten years ago, LiDAR was dominated by overseas players. Now, the tables have turned," Wang said. Walking the CES halls, he encountered over a dozen LiDAR companies, most of which were from China.

Tanway, founded in 2017 in Beijing, is an example of this surge. As a relatively new company, Tanway has focused on solid-state LiDAR with hardware-based image fusion.

At this year's CES, the company showcased the new generation of automotive-grade LiDAR and another LiDAR product that has been mass-produced and delivered.

Chinese EV makers, such as BYD, Xiaopeng, Li Auto and Nio, are more willing to embrace new technologies, Wang added.

Wang attributed China's LiDAR innovation to its unique ecosystem. "Low production costs, a complete supply chain, and rapid development of the domestic EV market create the perfect environment for experimentation and innovation," Wang said.

(Web editor: Zhang Kaiwei, Liang Jun)

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