Narrow Space Warning and Slope Control System Compatible With Adas

Abstract

The number of studies on autonomous vehicle systems is increasing day by day. Autonomous vehicles can perform various tasks without human intervention. However, in the environment where these tasks are performed, there are locations that can pose a danger in terms of width and height. These locations are generally referred to as narrow spaces. The autonomous vehicle must detect these narrow spaces from the front with the sensors on the vehicle to minimize the accident rate. In this study, a narrow space detection algorithm is created by including width detection, height detection, positive and negative obstacle detection in autonomous vehicle algorithms. LiDAR sensor data is utilized in the conducted studies, utilizing a 16-layered, 100-meter range product manufactured by Velodyne. When the width and height measurements obtained from the sensor data did not match the vehicle dimensions, the user is informed. This notification is conveyed to the user as a visual warning message on an interface. In addition, the incline of the hills that the vehicle cannot climb (positive obstacle) and the cliffs that it cannot descend (negative obstacle) were determined by measuring the slope. According to the results of the study, the average error rate is calculated as 2.7% for width measurements, 1.84% for height measurements, and 2.22% for slope measurements for positive and negative obstacle detection. The outputs of this study can also be included in advanced driver assistance systems (ADAS).