Let’s talk about the current state of intelligent driving from the Xiaopeng M03 automatic parking crash into the Audi

Recently, a netizen posted on Weibo that he hit someone else's car while using the automatic parking function of Xiaopeng MONA M03. He particularly emphasized that during the automatic parking process, the other vehicle had been detected, but he still hit the other vehicle directly. He also said that he had experienced the automatic parking function of many brands before and trusted this function too much. He did not believe that such a basic function would have problems.

After the incident fermented on the Internet, it received heated discussions from many netizens. In response to this , the relevant person in charge of Xpeng Motors responded to the media: The company's after-sales staff has contacted the customer and is actively handling the problem.

Regarding the cause of the vehicle scratching in the automatic parking state. The person in charge responded that the weak scene caused by light and other factors cannot be ruled out, and the specific cause needs to be analyzed in combination with specific data. ‍‍‍‍‍‍‍This incident not only makes people doubt the safety of autonomous driving technology, but also triggers deep thinking about the current status and future development of intelligent driving technology. In recent years, autonomous driving technology has made significant progress, from primary driving assistance functions to high-level autonomous driving, and the technology has continued to mature.

However, despite many breakthroughs in technology, there is still some uncertainty about the performance of autonomous driving systems in actual applications. Take the automatic parking function of Xiaopeng MONA M03 as an example. This type of function has been regarded as one of the relatively mature autonomous driving applications, but this accident shows that technology may still be unable to cope with complex or weak scenarios in some cases.

The automatic parking function relies on multi- sensor fusion technology, including ultrasonic radar , camera and sometimes equipped with lidar , which work together to perceive the environment around the vehicle. By processing the data collected by these sensors in real time, the vehicle is able to calculate the best parking path and automatically control steering, acceleration and braking to complete the parking maneuver. However, the effectiveness and reliability of sensors are key to the success of automatic parking. For example, the detection range and accuracy of ultrasonic radar may vary under different light conditions, and the performance of cameras in low-light environments may also be affected.

In this accident, the automatic parking system of Xiaopeng Motors may not be able to correctly perceive the surrounding environment due to insufficient light or reduced sensor detection accuracy, causing the vehicle to collide with an obstacle. This shows that although autonomous driving technology is developing rapidly, it is still not guaranteed to be completely reliable, especially in low-speed and complex environments, where the sensor's perception ability and the algorithm's decision-making ability may be affected by many factors.

• 
  

• Limitations of environmental perception: The accuracy and coverage of sensors are the basis for autonomous driving systems to perceive the environment. Low light, strong reflections, complex obstacles, etc. may cause the sensors to fail to perceive correctly, thus affecting the system's decision-making.

• 
  

• Complexity of algorithms: Autonomous driving systems rely on complex algorithms to process large amounts of sensor data and make real-time decisions. However, the design and implementation of algorithms need to take into account countless edge cases and abnormal situations, which places extremely high demands on the reliability of the system.

• 
  

• Data Insufficiency and Quality: The development of autonomous driving technology is highly dependent on massive amounts of high-quality data. However, the process of acquiring and labeling this data is not only expensive and time-consuming, but in some cases, data for specific scenarios may be insufficient, resulting in poor performance of the algorithm in these scenarios.

• 
  

• System integration and testing: Even if individual sensors or algorithms perform well, integrating these technologies into a comprehensive autonomous driving system still faces huge challenges. System integration requires ensuring that the various components can work together seamlessly and remain stable in a variety of situations.

The further development of autonomous driving technology still requires improvement and optimization in many aspects:

• Multi-sensor fusion and redundant design: To cope with complex driving environments, the autonomous driving system should adopt multi-sensor fusion technology to ensure that the system can still work normally when a single sensor fails or its performance degrades. In addition, adding redundant design and improving the system's fault tolerance can further improve the safety of autonomous driving.

• 
  

• Improve the robustness of the algorithm

• 
  

• For vulnerable scenarios and edge cases, autonomous driving algorithms need to be continuously optimized. Through large-scale simulation tests and the accumulation of real-world scenario data, the algorithms can maintain stable performance under a wider range of conditions.

• 
  

• Enhanced real-time data processing capabilities: As the demand for data from autonomous driving systems continues to increase, the system needs to have stronger real-time data processing capabilities to ensure real-time decision-making in complex environments.

• 
  

• User education and expectation management: Before autonomous driving technology is fully mature, automakers should strengthen user education to help them understand the capabilities and limitations of autonomous driving systems and set correct expectations for the systems. This can reduce unnecessary risks caused by misunderstandings.

This accident reminds us that with the continuous improvement of technology and comprehensive optimization of the system, autonomous driving will inevitably become a safer and more reliable travel option. However, in the intermediate transition stage, both manufacturers and users need to be aware of the limitations of technology and use it with caution!