With the acceleration of automobile intellectualization and networking, autonomous vehicle have become an important development direction of the future automobile industry and play a key role in the transformation of the automobile industry. As an emerging technology, autonomous vehicle needs to have a level of safety recognized by the public, which is an obstacle that must be overcome to move towards commercial application. Especially in the complex weather conditions, the environmental conditions of autonomous vehicle are worse than those of conventional weather, leading to higher risk of accidents and greater technical challenges.
Complex meteorological conditions refer to the weather or environment unfavorable to the normal operation of autonomous vehicle sensors, such as rain, snow, haze, sand and strong light. At present, there are proprietary products suitable for autonomous driving, which will greatly enhance the rapid development of the autonomous driving industry. This includes visibility meters, integrated weather sensors, weather phenomenon meters, and road condition sensors.
|Wind / Temperature / Humidity / Pressure / Rainfall / Present Weather / Road Status
|Ultrasonic wind measurement
Piezoelectric rain measurement
Laser disdrometer present weather
Laser road status measurement
|DC12/24V / Solar Power
The interference factors caused by complex meteorological conditions to the safe driving of autonomous vehicle can be summarized as follows: temperature change, gale and crosswind, road surface change and visibility change.
1. Temperature changes
Both high and low temperature environments can affect the working characteristics of sensors, especially when the operating environment exceeds the design temperature, the accuracy of the sensor will decrease, and it will be temporarily or permanently damaged.
Therefore, higher requirements are put forward for the temperature adaptability and durability of the sensor.
In addition, the external surface of the external sensor is prone to frost or ice formation in low-temperature environments, which can cause the sensor to malfunction.
2. Impact of gale
When driving on bridges in windy weather or over large areas of water, vehicles bear a huge force perpendicular to the direction of their travel. This is called sideslip, usually caused by crosswind.
Cross wind stability is usually the task of the ESC system, which stabilizes the lateral movement of the vehicle to prevent slipping. However, when the vehicle begins to slip, the ESC system is delayed in starting as redundancy.
3 Road surface changes
Rainy weather can cause slippery and waterlogged roads, while snowy weather can cause snow and ice on the road surface, both of which can significantly reduce the adhesion coefficient of the road surface and have a significant impact on the handling and braking performance of vehicles.
At present, the environment perception system of autonomous vehicle can not capture the road information and can not effectively deal with possible tire slip, braking distance increase and other situations.
In addition, rain, snow, and ice generated by rainy and snowy weather can cover road guidance signs such as lane markings, making it difficult for radar sensors and visual sensors to recognize them.
Additionally, reflections generated on the road surface can cause cognitive confusion and object misjudgment in visual sensors.
4 Visualization changes
Complex meteorological conditions such as rain, snow, haze, sand and dust, and strong light environment seriously reduce the visibility of the environment, causing great difficulties to the driving safety of autonomous vehicle.
Visual sensors are most affected by the aforementioned weather conditions, and falling objects (rain, snow) or floating objects (haze, sand and dust) can obstruct the camera’s line of sight, resulting in incorrect perception of the driving environment. In addition, when raindrops or water droplets melted by snowflakes adhere to the camera, it can have a serious impact on the aperture, causing phenomena such as field of view occlusion or background blurring.
A strong light environment can reduce the visibility of the camera to almost zero, causing the car to become blind. The radar sensor will also be limited by the above weather.
The transmitted signal, such as light pulse, will be reflected back when encountering falling objects or floating objects. The signal transmission rate will decline with the increase of the density of falling objects or floating objects and the transmission distance.
It will even mistake falling objects or floating objects for objects to avoid, which will interfere with the correct judgment of autonomous vehicle on the surrounding environment.
Strong light environments can make radar sensors unable to effectively recognize target objects such as lane markings, signs, etc.
We will provide corresponding monitoring products for the four main meteorological conditions mentioned above, which can accurately and real-time obtain weather conditions, provide early warning, and provide technical support for safe driving.