Mamozhixing, an autonomous driving company under Great Wall
HAOMO AI DAY, Haomo Zhixing announced that it had delivered three generations of assisted driving products for passenger cars in the past two and a half years, and the first one equipped with mass-produced urban NOH (city) The Mocha DHT-PHEV lidar version is planned to be mass-produced in September and released this year.
Zhang Kai, Chairman of Maomo Zhixing, said: "In the era of autonomous driving 3.0, assisted driving is the only way to achieve autonomous driving. At present, China has become the main battlefield of smart cars in the world. It is estimated that by 2025, the loading rate of high-level assisted driving will exceed 70%. "
Based on the huge consumption demand of large model training on computing power in autonomous driving 3.0, MMO also launched the MMO Supercomputing Center. Gu Weihao, CEO of Momo Zhixing, said that the goal of Momo Supercomputing Center is to meet the needs of large models with 100 billion parameters, the scale of training data is 1 million clips, and the overall training cost is reduced by 200 times.
At the same time, Haomo Zhixing also cooperated with Zhejiang Deqing and Alibaba Cloud to release "China's first large-scale autonomous driving scene library based on vehicle-road collaborative cloud services", which is an autonomous driving scene library generated using real traffic data and meeting data compliance requirements. , which is expected to further accelerate the maturity of autonomous driving in China and the coordinated development of vehicles, roads, and clouds.
In terms of automatic distribution of terminal logistics, five months after its listing, the delivery of "Xiaomo Xiaomo Tuo 2.0" officially began. This terminal logistics automatic distribution vehicle has L4-level automatic driving, remote driving, low-cost deployment, vehicle management platform, remote Monitoring platform, order management platform, WeChat applet, and other functions, the price of a bicycle is 128,800, and the annual output is expected to be 10,000, which can cover parks and urban open roads.
The predecessor of Maomo Zhixing was the intelligent driving forwarding department of Great Wall Motors. In 2019, Momozhixing was incubated by Great Wall Motors and became an independent self-driving artificial intelligence technology company. At present, Great Wall Motors is not only a major shareholder of Momo Zhixing but also a major customer of Momo Zhixing.
The Wei brand Mocha DHT-PHEV lidar version released at the Chengdu Auto Show on August 26 will be the first model to be equipped with the third-generation intelligent driving system HPilot 3.0. It is reported that the Wei brand Mocha DHT-PHEV lidar version adopts a new generation of the technical routes of "heavy perception, light map". This is based on the complex urban traffic scene in China, and Wei Pai gives a technical solution.
The so-called "heavy perception" route means that the vehicle does not rely too much on high-precision maps, and allows the vehicle to rely on its own fusion perception to complete high-level intelligent assisted driving and achieve large-scale urban coverage in a short period of time. According to the current plan, Wei brand city NOH will cover 10 cities before the end of the year and plans to cover more than 100 cities next year.
It is reported that Wei brand city NOH is equipped with a number of software and hardware configurations, including 2 125-line laser radars, 5 millimeter-wave radars, 12 ultrasonic radars, 12-megapixel high-definition cameras, a total of 31 sensing components composed of super sensing components module. According to reports, in urban traffic scenarios, Wei brand city NOH can realize core functions such as automatic lane changing and overtaking, traffic light recognition and vehicle control, complex intersection traffic, unprotected left and right turns, etc. , and can also deal with vehicles cutting in at close range, blocking road occupation, intersections, tunnels, overpasses and other complex urban traffic scenarios, the coverage rate of core urban scenarios exceeds 90%.