Speed bump detection on LiDAR point cloud for autonomous vehicles

Abstract

Abstract Speed bump detection is paramount for ensuring the safe and comfortable operation of autonomous vehicles while complying with traffic regulations. Detecting speed bumps well in advance enables timely brake application, ensuring a smooth travel experience for passengers in autonomous vehicles. These vehicles rely on a range of sensors for perception, including cameras, radar, stereo vision, and light detection and ranging (LiDAR). LiDAR, in particular, stands out for its ability to generate dense point clouds accurately capturing the geometry and depth of surrounding objects, providing unparalleled detail for robust perception systems. This paper introduces a novel technique for speed bump detection leveraging LiDAR data. The method capitalizes on the variance in Z -values between road surfaces and speed bumps, offering promising insights for enhancing road safety and passenger comfort. The proposed method underwent rigorous testing using a dataset collected within the IIT Hyderabad campus and demonstrated effective speed bump detection. With this system, speed bumps could be reliably detected up to a distance of 15 meters at a rate of approximately 18 frames per second. Moreover, the method’s integration potential into autonomous vehicles promises to contribute significantly to a seamless and safe journey for passengers. The successful implementation of this technique underscores its potential to enhance autonomous driving systems, providing vehicles with advanced perception capabilities to navigate complex road environments with heightened safety and comfort. Further research and development in this area hold promise for continued advancements in autonomous vehicle technology, paving the way for a future of safer and more efficient transportation.