LiDAR Sensing-Based Exponential Adaptive Cruise Control and Steering Assist for ADAS

Autonomous vehicles represent a groundbreaking advancement, prompting innovative solutions for safer, more efficient transportation. These self-driving vehicles rely on advanced driver assistance system (ADAS) features, which are essential for safe navigation through complex environments. Nevertheless, ensuring safety and smooth operation remains a formidable challenge, particularly when faced with obstacles and responsive steering. Although LiDAR serves as a comprehensive sensor for mapping, localization, and perception in autonomous navigation. Extensive research has been carried out on radar in the context of ADAS, but there is a need for more focus and exploration on LiDAR-based cruise control. Most cruise control systems primarily integrate hard-coded or linear speed variations or ignore the critical aspect of steering rotation. In this article, we propose a LiDAR-based novel exponential approach (e-ACCSA) for the adaptive Cruise control (ACC) and adaptive steering assist (ASA), as well as their integration along with the continuous gradual acceleration mechanism ensures smoother velocity transitions. The ACC module controls the vehicle’s speed based on the obstacles detected within the region of interest (ROI) by the LiDAR sensor. Simultaneously, the ASA module enhances steering control and adjusts the vehicle’s speed based on steering rotation. The integration of ACC and ASA ultimately ensures safe and seamless autonomous driving. Coupled with a gradual acceleration mechanism, ensures smoother velocity transitions. Our algorithm aligns with the safe velocity standards set by the National Highway Traffic Safety Administration (NHTSA) and National Association of City Transportation Officials (NACTO). The ADAS system is tested in real-time on an e-vehicle mounted with a LiDAR sensor. The code will be released at https://github.com/abhishekt711/LiDAR-ADAS-ACC-ASA.