Home / Metal News / Hyperview unveils autonomous racing system with successful track debut

Hyperview unveils autonomous racing system with successful track debut

iconSep 30, 2024 15:23
Source:gasgoo
On September 28, at the Zhuzhou International Circuit, a race car equipped with Hyperview's autonomous driving system Tianyuan completed a 3.77-kilometer lap in under three and a half minutes, marki...

Beijing (Gasgoo)- On September 28, at the Zhuzhou International Circuit, a race car equipped with Hyperview's autonomous driving system "Tianyuan" completed a 3.77-kilometer lap in under three and a half minutes, marking its successful track debut. This project, developed by Gaosheng Qingdong (name in Chinese pinyin) and Hyperview, features a track-level autonomous system designed to push the limits of high-speed performance rather than focusing on the safety and comfort of L4 and L5 systems.

The "Tianyuan" system represents a breakthrough in autonomous racing technology, combining AI, machine vision, and advanced control systems. Unlike traditional L2 and L3 systems, this technology emphasizes high-speed precision driving and seeks to unlock the full potential of autonomous racing.

Key technological highlights include the use of FOC (Field-Oriented Control) motors for steering and braking instead of the car’s original control system. This technology, often found in humanoid robots, ensures precise and rapid responses. Hyperview also developed a custom inertial navigation system for ultra-high precision and low latency, with a refresh rate of 400Hz—far surpassing the 100Hz typical of conventional autonomous vehicles.

Additionally, Hyperview created a specialized lateral control algorithm tailored for racing, offering exceptional accuracy and stability for high-speed straights and tight corners. With over 10 hours of durability testing and a faultless 1-hour endurance record, the system demonstrates strong reliability and maturity, paving the way for autonomous racing innovation.

For queries, please contact William Gu at williamgu@smm.cn

For more information on how to access our research reports, please email service.en@smm.cn