On November 5, 2019, Intel subsidiary Mobileye and Chinese high-end electric car brand NIO reached a strategic cooperation, and the two parties will develop high-level autonomous vehicles (AVs) for the consumer market in China and other major regions. According to the cooperation plan between the two parties, NIO will develop and manufacture autonomous driving systems based on Mobileye's autonomous vehicle kit. This world's first L4-level autonomous driving system is mainly designed for consumer-grade autonomous driving and will cover automotive certification standards, quality, cost and scale. NIO will mass-produce models equipped with this system and build a special edition model for Mobileye specifically for autonomous taxi services. This special edition model will be launched in China for the first time and is planned to be promoted in the global market. Professor Amnon Shashua, Intel senior vice president and president and CEO of Intel subsidiary Mobileye, said: "We are excited about the prospect and potential of our collaboration with NIO in the field of autonomous vehicles. We attach great importance to and are working hard to bring a safer road traffic environment to China and other markets. We look forward to working with NIO to promote the global intelligent transportation revolution." Mobileye is a leader in the field of autonomous vehicles. In recent years, Mobileye has created a new meaning of road transportation for drivers and passengers in China and other regions, which is the cornerstone of the cooperation between the two parties. In this cooperation, NIO will become Mobileye's manufacturing partner, which will help Mobileye's leading autonomous driving systems and innovative technologies enter the consumer market and benefit global automotive customers. This cooperation also marks that NIO has become the first major Chinese automaker to provide vehicles to Mobileye, which will be used for Mobileye's autonomous taxi service. Currently, Mobileye is building a commercial fleet of autonomous taxis around the world to meet the travel needs of people in the 21st century; in addition, this service will help reduce environmental pollution and traffic congestion, and can effectively improve the level of urban road safety and traffic quality around the world. For NIO, supporting the production and integration of Mobileye's autonomous driving system is consistent with NIO's mission to provide high-end smart electric vehicles and redefine user experience. Through cooperation with Mobileye, NIO will provide safer and more powerful autonomous vehicles with advanced driver assistance systems (ADAS) and L4 autonomous driving technology, maintaining its leading position in the high-end electric vehicle market. According to the cooperation plan between the two parties, Mobileye will provide NIO with an autonomous driving system design based on the Mobileye autonomous driving car kit. This L4-level autonomous driving car kit includes the Mobileye EyeQ® system-on-chip (SoC), hardware, driving strategy, safety software and high-precision map solutions. In the cooperation between the two parties, NIO will be responsible for the development, integration and mass production of autonomous driving systems at the vehicle level, and will help Mobileye enter the consumer automotive market and its mobility as a service (MaaS) applications. In addition, NIO will also build a special edition electric vehicle model for Mobileye suitable for autonomous taxis, which will be used in Mobileye's globally deployed shared ride services based on autonomous taxis. “We are proud of our tireless pursuit of innovation and cutting-edge technology, which not only enhances our product competitiveness, but also creates a pleasant lifestyle for NIO users,” said William Li, founder, chairman and CEO of NIO. “We are very excited about our strategic partnership with Mobileye to improve vehicle safety and driving performance, and strive to realize NIO’s vision of becoming a ‘user enterprise’.” Mobileye Autonomous Driving Kit: Mobileye Autonomous Driving Kit is an L4 autonomous driving technology solution that can provide vehicles with autonomous driving capabilities, thereby effectively reducing the occurrence of car accidents. Hardware: Mobileye’s self-driving car kit provides the necessary hardware support for fully autonomous vehicles, including cameras, radar, lidar, cables, modems, GPS and other mechanical parts, all driven by the fifth-generation EyeQ® SoC, which is designed for low-cost, low-power autonomous driving with excellent deep learning capabilities and performance efficiency. Driving Strategy: Mobileye’s proprietary reinforcement learning algorithm enables vehicle systems to have human-like driving skills, and through the technology’s sensing and computing platform, it can have visual capabilities and reaction speeds that surpass humans. With Mobileye’s driving strategy technology, vehicles equipped with the self-driving car kit can perform corresponding operations in complex road conditions based on the situation of other human-driven vehicles on the road. Safety Software: Mobileye’s driving strategy also uses the Responsibility-Sensitive Safety model (RSS), which ensures that autonomous vehicles make safe decisions. RSS is an open, transparent formal model for providing safety assurance for autonomous driving decisions, which formalizes human-centered common sense for safe driving. Route planning may help you get forward, but RSS can help you stay safe along the way. As a winner of Toutiao's Qingyun Plan and Baijiahao's Bai+ Plan, the 2019 Baidu Digital Author of the Year, the Baijiahao's Most Popular Author in the Technology Field, the 2019 Sogou Technology and Culture Author, and the 2021 Baijiahao Quarterly Influential Creator, he has won many awards, including the 2013 Sohu Best Industry Media Person, the 2015 China New Media Entrepreneurship Competition Beijing Third Place, the 2015 Guangmang Experience Award, the 2015 China New Media Entrepreneurship Competition Finals Third Place, and the 2018 Baidu Dynamic Annual Powerful Celebrity. |
[[436754]] This article is reprinted from the WeC...
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