Chinese Autonomous Driving Firm Hong Jing Drive Receives $15M in Financing

Hong Jing Drive, an autonomous driving solutions provider based in China, announced on Monday that it had completed financing of over 100 million yuan ($15.77 million), featuring exclusive investment from Prosperity7, a diversified venture capital fund under Saudi Aramco. In less than one year, Hong Jing Drive has successively completed three rounds of financing worth several hundred million yuan.

These funds are mainly to be implemented for product R&D, talent recruitment and capacity expansion. Liu Feilong, founder and CEO of Hong Jing Drive, said that automated driving technology will lead the next generation travel revolution of mankind, representing the technical commanding heights of artificial intelligence algorithms and the integration of software and hardware, and is also one of the key areas supported by Chinese national policies.

Last year, in the field of passenger cars, Hong Jing Drive successfully mass-produced L2.5 advanced driving assistance systems based on domestic AI chips and 8M Ultra HD cameras, and nearly 100,000 sets had been shipped by December 2021. The system supports more than ten auxiliary driving functions, such as navigation assisted driving, intelligent following, front collision warning and adaptive cruise in the full speed domain.

During the Guangzhou Auto Show in 2021, Hong Jing Drive and JAC Motors launched an integrated intelligent pilot solution for driving and parking of main fuel vehicles in the industry. The system is equipped with AI chips, intelligent cameras and millimeter wave radars made in China, which provides efficient computing power and strong perception ability, ending the era in which fuel-based vehicles did not have high experience intelligence.

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In the field of intelligent heavy trucks, Hong Jing Drive officially released the HyperTruck One, a L3 digital logistics intelligent heavy truck. This product is equipped with more than ten autonomous driving functions for line-haul transportation scenarios, trying to reduce driver fatigue and labor costs, and at the same time improve safety and the driving experience.