A study of sensor fusion based vehicle distance estimation for self-driving cars

The self-driving car has become attractive and modern. The self-driving car consists of several systems such as navigation, localization, avoidance, and more. LiDAR, Radar, GPS, Inertial Measurement Unit (IMU), Ultrasonic, camera were sensors, which those sensors were used in the self-driving car. The method to integrate those sensors work together is Sensor Fusion. This method uses diverse types of sensors that work similarly to one sensor. This research proposes a method that uses a combination of sensors for distance estimation. Multiple Lidars and a camera contribute to the improvement of data processing for the Kalman filter. The Object detectionmethod will locate and classify the object in the research. This research will help develop driving systems such as emergency braking, velocity calculation, and collision warning system.