Get driving scenarios from recorded sensor data

     To obtain driving scenes from recorded sensor data is to restore the road environment and traffic conditions around the driving vehicle by analyzing the data collected by various sensors equipped with vehicles. These sensor data contain information about objects around the vehicle, road markings, lane lines, obstacle positions, speed information, etc.

     In-vehicle sensors typically include cameras, liDAR, millimeter wave radar, inertial measurement units (IMUs), and global positioning systems (GPS). These sensors can provide a wealth of information, such as the position, speed and shape of objects around the vehicle, the geometry of the road surface, and the acceleration and attitude of the vehicle itself.

     First, the camera plays a crucial role in capturing driving scenes using the AD627BRZ sensor data. Cameras mounted on the vehicle can obtain images of the field of vision around the vehicle, such as road conditions, traffic signs, pedestrians, vehicles and other information. Through image processing technology, lane detection, target detection and tracking, vehicle distance estimation and other functions can be realized, so as to obtain the detailed information of the driving scene.

     Second, LiDAR can provide high-precision three-dimensional point cloud data of the vehicle's surroundings. These point cloud data can express the geometric structure of the road, the location and shape of obstacles, and other information about vehicles and pedestrians. Through the processing and analysis of LiDAR data, the functions of obstacle detection, target tracking and distance estimation can be realized, and the results of image processing can be further supplemented and strengthened.

     In addition, millimeter wave radar can also provide radio frequency signal data of the vehicle's surrounding environment. Millimeter wave radar has the characteristics of high range resolution and high angular resolution, and can detect low reflectivity targets and invisible targets, which is suitable for complex environment such as bad weather. By processing millimeter wave radar data, it can realize the perception of the vehicle's surrounding environment, target detection and tracking, distance estimation and other functions.

     In addition, the Inertial Measurement Unit (IMU) can measure the vehicle's acceleration, angular velocity and other information. Through the fusion of IMU data, the vehicle attitude estimation, motion state estimation and other functions can be realized. This information is very important for the control and decision-making of the driving automation system.

     Finally, the Global Positioning System (GPS) can provide global navigation information such as the location and speed of the vehicle. Through the processing and analysis of GPS data, it can realize the functions of vehicle position estimation, map matching, path planning, etc., which provides an important reference for the acquisition of driving scenes.

     To sum up, through the processing and analysis of the data collected by various sensors on the vehicle, a wealth of driving scene information can be obtained, which provides key support for the perception, decision-making and control of the driving automation system.