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The five major research institutes of Hon Hai (Hon Hai Institute of Artificial Intelligence, the fir

 

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To join the intelligent connected industry cluster, please show your business card on WeChat (Gasgoo111). GAC Automotive News. On May 23rd, the Artificial Intelligence Research Institute of Hon Hai Research Institute, a subsidiary of Hon Hai Technology Group, collaborated with City University of Hong Kong to launch the new generation of autonomous driving trajectory prediction deep learning model QCNet, which is ranked among the world's largest and most challenging self driving trajectory prediction challenges, Argverse 1 and Argverse 2, Achieved the top ranking achievement.

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This model can be applied to the auto drive system of the group's electric vehicles in the future, greatly improving the real-time and safety of self driving decisions

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Image source: The past trajectory prediction methods of Hon Hai Technology Group did not have the ability of stream processing, and a dedicated scenario code must be calculated for each traffic participant to achieve higher prediction accuracy. This has led to a significant computational burden. The QCNet proposed by Hon Hai Research Institute and City University of Hong Kong is an intelligent trajectory prediction model, Its main advantage lies in its ability to understand the global information of real driving scenarios, utilizing the Transformer architecture with the same technical foundation as ChatGPT, and modifying it to be suitable for autonomous driving scenarios, enabling it to learn the diversity and uncertainty of vehicle history, vehicle interaction behavior, and road environment, thereby obtaining rich scene feedback.

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QCNet can capture multiple potential intentions of vehicles in complex road environments, predict future motion trajectories over ultra long distances (6 to 8 seconds), accurately predict multiple targets in the scene simultaneously, and improve the computational efficiency of the encoder by over 85%. In addition to efficient and accurate prediction, QCNet has established a set of local coordinate systems for each scene element in traffic scenes, including lanes, zebra crossings, vehicles, and pedestrians, Learning representations in the local coordinate system corresponding to scene elements and capturing the relative relationships between different scene elements through relative spatiotemporal position encoding can avoid a large amount of repetitive calculations and ultimately improve the real-time computational efficiency of the model.

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Li Yonghui, Director of the Artificial Intelligence Research Institute of Hon Hai Research Institute, said: "Hon Hai Research Institute has invested a lot of manpower in the field of AI and autonomous driving, and has refined technology from basic models and algorithm cores. Therefore, QCNet can achieve the top ranking performance in Argverse 1 and Argverse 2, and will be published at the globally renowned top conference CVPR in the field of AI in June this year.

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We are pleased to see that the research and development achievements of our self driving team have been recognized by the world. In the future, QCNet can be applied to the group's electric vehicle auto drive system, greatly improving the real-time and safety of automatic driving decisions "- END - Past hot spot 1 After Samsung, Apple has also been exposed to restrict employees from using ChatGPT

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2 First time winning! Hyundai Motor Group's L4 autonomous vehicle opened road test in Shanghai, and Kechuangda released the "Rubik's Cube" big model -------- the group of Geshi Auto Intelligent Network has now covered domain control, intelligent chassis, intelligent driving software to define cars, semiconductors, laser radars

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The five major research institutes of Hon Hai (Hon Hai Institute of Artificial Intelligence, the fir

The five major research institutes of Hon Hai (Hon Hai Institute of Artificial Intelligence, the fir

该模型未来可应用于集团电动车自动驾驶系统,大幅提升自驾决策的实时性与安全性。...

2023-05-23 栏目:科技派

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