The accident occurred in Leshan, Sichuan, and the vehicle involved was a newly purchased Mercedes-Benz sedan. At the time of the accident, the man was using the intelligent driving assistance function, but because he felt sleepy while driving, he relied too much on the system, causing the system to automatically exit in case of sleepiness, and the man failed to detect it in time, which eventually caused the vehicle to deviate from the lane and collide with a normal tanker truck next to it, causing serious damage to the right side of the vehicle and two doors needing to be replaced. According to reports, the naked price of this Mercedes sedan is 52980,000 yuan, about 600,000 yuan. The loss of the accident is estimated to be between 50,000 and 60,000 yuan, and the results of the damage assessment have not yet been released.
This accident has aroused widespread concern and heated discussions in society, and people have begun to discuss the importance of the correct use of intelligent driving systems and the maintenance of drivers' attention. At the same time, some voices pointed out that although intelligent driving technology provides convenience for driving, drivers still need to maintain sufficient attention when using it and avoid over-relying on or ignoring the system's prompts to ensure driving safety. In addition, similar accident cases also remind the public that even high-tech products cannot completely replace the safety awareness and operational skills of human drivers.
How does this intelligent driving assistance function work?
The specific working principle of the intelligent driving assistance function mainly includes the following aspects:
Contextual awarenessThe intelligent driving assistance system uses sensors such as cameras and lidars to perceive obstacles, traffic conditions, and surrounding conditions on the road in real time, providing drivers with accurate environmental information. These sensors can instantly and clearly identify obstacles on the road to ensure driving safety.
Multi-sensor fusionBy fusing data from multiple sensors, the sensing range and accuracy are expanded, enabling the system to have a more complete understanding of the driving environment. This technique helps to improve the accuracy and reliability of the system.
Intelligent decision-making and controlBased on the analysis results of environmental perception and sensor fusion, the intelligent driving assistance system can make driving decisions and perform corresponding operations. This includes adjusting the speed and direction of the vehicle according to the road conditions and the state of the vehicle to achieve the best driving effect.
Data analysis and processingThe system can accurately analyze the vehicle's driving data and process it through algorithms to make the best driving decisions. This not only reduces driving fatigue, but also enhances driving pleasure.
The difference between autonomous driving and assisted drivingWhile Advanced Driver Assistance Systems (ADS) are essentially assisted driving, their core is environmental awareness, covering different levels of autonomous driving (L0-L2). This suggests that ADS can be considered as a premise for autonomous vehicles to a certain extent.
The working principle of the intelligent driving assistance function is to achieve accurate perception, efficient decision-making and execution of the driving environment through advanced sensor technology, combined with complex algorithms and data processing capabilities, so as to provide drivers with a safe and comfortable driving experience.
In the intelligent driving system, how to deal with the situation that the driver is sleepy or distracted?
First of all, according to the provisions of the national standard "Performance Requirements and Test Methods for Driver Attention Monitoring Systems", intelligent driving systems (such as DAMS) should at least realize the monitoring of behaviors such as closed eyes, abnormal head posture, and hitting. In addition, it should also have a monitoring function for behaviors such as yawning and smoking. This shows that monitoring the driver's physiological and behavioral state through technical means is a way for the intelligent driving system to deal with the driver's sleepiness or distraction.
On the other hand, the intelligent driving system can also determine whether the driver is sleepy by evaluating the driver's driving action. For example, if a driver shows signs of fatigue without turning the steering wheel, the system may issue a warning or adjust the driving mode to mitigate the effects of fatigue. However, this approach may not be applicable in some cases, especially in self-driving cars, as this assessment may not work when the driver is not turning the wheel.
In addition to the above methods, the intelligent driving system can also detect whether the driver is distracted by multi-scale feature fusion. This approach uses information from each data source to synthesize the driver's attention state to more accurately identify distracted behaviors.
The intelligent driving system mainly relies on real-time monitoring of the driver's attention when the driver is sleepy or distracted, including but not limited to monitoring the behavior of closed eyes, head posture, and hitting**, as well as through technical means such as driving action evaluation and multi-scale feature fusion. At the same time, given the specificity of autonomous driving systems, these systems also need to be able to adapt to different driving environments to ensure that the driver's distraction can be effectively detected under various conditions.
In this accident, what are the specific circumstances and trigger conditions for the automatic exit of the intelligent driving system?
1.When the automatic driving control system does not detect any fault, the driver takes manual intervention in order to ensure the safe driving of the vehicle when monitoring the operating conditions, which will actively trigger the exit of the automatic driving mode to realize the manual takeover control of the vehicle.
2.In certain designs, such as SEOOC designs, if the HWP (Intelligent Driving System) is running off or off the feet for a long time within the ODD (autonomous driving speed range of 0-120kph), and the driver applies the brakes or exceeds the ODD condition, the function will be withdrawn.
The automatic exit of the intelligent driving system is usually due to the intervention of the driver, the serious failure of the vehicle itself, or the triggering of the exit conditions set by the system. These conditions work together to cause the automated driving system to exit from autonomous driving mode.
What are the latest studies or reports on the safety of intelligent driving systems?
Safety monitoring of intelligent driving domain controllersThe MCU responsible for functional safety in the intelligent driving domain controller can switch to a safe state when the autonomous driving system is detected to ensure the safety of the system.
C-V2X Converged Intelligent Driving Domain Controller Solution: The C-V2X Fusion Intelligent Driving Domain Controller solution released by CITIC Zhilian aims to solve problems such as bad weather, and achieve a safer intelligent driving experience through the integrated development of C-V2X and bicycle intelligence.
A data-driven approach to decision-making improves securityThe data-driven decision-making method not only improves the safety of autonomous driving, but also makes the autonomous driving technology more in line with human driving habits.
The evolution of the NVIDIA Drive platform: NVIDIA is developing an end-to-end NVIDIA Drive platform to create safer, more scalable, and more efficient modes of transportation.
Data analysis of autonomous driving accidents in the United StatesAccording to the NHTSA self-driving accident report, there have been more than 392 L2 autonomous driving accidents in the United States in ten months, of which Tesla accounts for 70%. The purpose of this data analysis is to drive improvements and the development of safety technologies in the autonomous driving industry.
The research and report on the safety of intelligent driving systems covers many aspects from technological innovation, system monitoring, data-driven decision-making to accident data analysis, etc., aiming to continuously improve the safety and reliability of autonomous driving.
How to improve the driver's attention and alertness to the intelligent driving system?
Driver Monitoring System (DMS) is usedThe :d MS system provides the necessary early warning and intervention for the driver by monitoring the driver's status in real time, such as fatigue level, attention situation, etc.
At the same time, computer vision and machine learning technology are used to analyze the real-time information of drivers and passengers, further improving the accuracy and practicability of the system.
Intelligent driver assistance systemsIntelligent driver assistance systems can help drivers avoid traffic accidents and improve their concentration. For example, a lane-keeping system can correct the direction of the vehicle in time when the driver is inattentive or fatigued, and avoid traffic accidents caused by the vehicle deviating from the lane.
Interaction design in intelligent cockpits: Studies have shown that having short, intermittent conversations with virtual assistants (VAs) can help increase driver alertness. Therefore, in the intelligent cockpit, reasonable interaction interfaces and dialogue modes should be designed to reduce driver distraction.
By integrating DMS driver monitoring systems, applying machine vision and AI technologies, optimizing the application of intelligent driver assistance systems, and improving the interactive design of intelligent cockpits, driver attention and alertness can be effectively improved.
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