Great Wall Motor to realize Level 3 autonomous driving with full-car redundancy in 2021

Monika From Gasgoo| December 30 , 2020

Shanghai (Gasgoo)- On December 30, Great Wall Motor (GWM) announced it will achieve the Level 3 autonomous driving function with redundancy throughout a vehicle in 2021.

Meanwhile, the automaker launched the “331 Strategy” under its “Coffee Intelligence Driving” program. Under the new strategy, GWM aims to be a leading intelligent driving tech developer that owns the most users and application scenarios in China, and boasts the greatest reputation from users over the next three years.

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Photo credit: Great Wall Motor

The “Coffee Intelligence” encompasses six redundancy systems for vehicle perception, controller, braking, framework, power source and steering. Through the world's first mass-produced fully redundant autonomous driving platform, GWM expects its intelligent driving system to work with no blind spot left unattended to.

In 2021, GWM will strive to output China's first autonomous car equipped with LiDAR and afford its vehicles with NOH (Navigation On Highwaypilot) capability, said the company

At the strategy launching ceremony, GWM inked agreements with Qualcomm and Huawei to technically support the development of intelligent driving technologies.

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GWM, Qualcomm signing agreement; photo credit: Great Wall Motor

The automaker will team up with Qualcomm, the world's leading wireless telecommunication tech developer, on the in-car intelligent chips used in autonomous cars. Under the in-depth cooperation, GWM will introduce Snapdragon Ride platform, a scalable and fully customizable automated driving platform developed by Qualcomm, into the intelligent driving system of the premium models to be rolled out in 2022.

GWM and Huawei agreed to work on some innovative technologies about intelligent connectivity and intelligent driving. The smart device supplier will supply the automaker with a MDC (Mobile Data Center)-based intelligent driving computing platform, and support GWM in evaluating and testing various sensors like cameras and LiDAR used in intelligent driving cars.

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