Camera and LiDAR Integration for Lane-Following and Obstacle Avoidance in Self-Driving Cars

In the rapidly evolving field of autonomous vehicle technology, this study represents a crucial step toward the development of a safer and more efficient self-driving system. The core of this paper is realized through the seamless integration of Camera Serial Interface (CSI) camera and Light Detection and Ranging (LiDAR) technologies. The CSI camera operates with precision in lane detection, ensuring a consistent alignment of the vehicle within the designated left lane. Complementing this, the utilization of LiDAR technology plays a pivotal role in identifying obstacles along the vehicle's path. The primary focus of this research lies in the approach to obstacle avoidance; when an obstacle is detected, the system directs the vehicle right, making calculated decisions guided by LiDAR data. The methodology is further enriched by the LiDAR system, providing crucial data to maintain an optimal and safe distance from detected obstacles, enabling the system to rejoin the lane with caution while strictly adhering to the lane detection methodology. This study is not only confined to theoretical frameworks; it is deeply rooted in practical experimentation. The outcomes strongly endorse the feasibility of the system and its potential to significantly enhance the safety and efficiency of autonomous driving. In conclusion, this research represents a pivotal advancement in self-driving systems, uniting CSI camera-based lane detection with LiDAR-based obstacle avoidance and contributing substantially to the ever-evolving field of autonomous transportation.