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Analysis Report on the Misjudgment Rate Reduction of Avatr ADS 4.0 System

#智能驾驶 #华为ADS #avatr #autonomous_driving #误判率 #感知系统 #激光雷达
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January 20, 2026

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Based on my comprehensive search and analysis, the following professional analysis is provided regarding the misjudgment rate reduction of the Avatr (HK01234) ADS 4.0 system:

Summary of Search Results

After systematic searches across multiple authoritative sources, including Huawei’s official technical documents, industry research reports, and professional media coverage,

I was unable to find specific percentage data on the “misjudgment rate reduction” of the Avatr ADS 4.0 system
.

Available Performance Improvement Data for ADS 4.0

Although the specific reduction range of the misjudgment rate has not been publicly disclosed, I have found the following key performance improvement indicators for the Huawei ADS 4.0 system:

Core Performance Indicators
  • 50% reduction in end-to-end latency
    [1][2]
  • 70% reduction in heavy braking rate
    [1][2]
  • 20% improvement in traffic efficiency
    [1][2]
  • Up to 43% improvement in detection distance for small targets
    [1]
Improvement in Perception Capability
  • The
    Limera Laser-Vision Technology
    enables physical-level fusion of lidar and cameras,
    significantly reducing the risk of misjudgment
    [3]
  • 43% improvement in detection distance for small targets at a height of 30cm [1]
  • Distributed millimeter-wave radars provide high-confidence detection [1]
Relevant Reference Data
Historical Performance of Avatr Models

According to the 2024 China Intelligent Driving Urban NOA Function Evaluation Report by EqualOcean Think Tank, the performance of Avatr 12 (equipped with Huawei ADS system) is as follows:

  • Misjudgment-induced Disengagement Rate
    : 0 disengagements per 10 km [4]
  • Manual Takeover Rate
    : Only 3.2 takeovers per 10 km [4]
  • Obstacle Avoidance Success Rate
    : Up to 2.4% [4]
Technical Architecture Upgrade

Huawei ADS 4.0 adopts the WEWA architecture (World Engine + World Behavior Model), which includes:

  • The World Engine can generate edge case scenarios with a density 1000 times that of the real world [2]
  • Full-modal perception capability processes multi-modal information including lidar, cameras, and distributed millimeter-wave radars [2]
Conclusion

No specific percentage data on the misjudgment rate reduction of the Avatr ADS 4.0 system can be found in current public materials.

Although technical documents repeatedly mention that the system “significantly reduces the risk of misjudgment”, there is a lack of quantified indicators for the reduction of misjudgment rate.

If you need more precise data, it is recommended that you:

  1. Contact Avatr’s official customer service for technical parameters
  2. Refer to the official technical white paper released by Huawei Qiankun Intelligent Driving
  3. Check the user manuals or technical specifications of Avatr models

References:

[1] Official Introduction of Huawei Qiankun Intelligent Driving ADS 4 (https://auto.huawei.com/cn/ads/)
[2] Bank of China Securities’ Research Report “In-depth Analysis of AI Edge Computing: Intelligent Driving (Part 1)”
[3] “New Era of Intelligent Driving Safety: Technological Breakthroughs of Huawei Qiankun ADS Pro Enhanced Edition” by Wangtong Auto Media
[4] EqualOcean Think Tank’s “2024 China Intelligent Driving Urban NOA Function Evaluation Report”

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Insights are generated using AI models and historical data for informational purposes only. They do not constitute investment advice or recommendations. Past performance is not indicative of future results.