LiDAR and Ultrasonic Sensor-Based Intelligent Obstacle Detection Systems For E-Vehicles

This paper presents a comprehensive framework for the seamless integration of LiDAR (Light Detection and Ranging) technology into autonomous electric vehicles (AEVs) while prioritizing safety.With the rapid advancement of autonomous driving technology, LiDAR sensors play a crucial role in providing real-time, highresolution environmental perception for AEVs.However, ensuring the safety of both passengers and pedestrians remains a paramount concern.Our proposed approach addresses this challenge by incorporating advanced safety measures into the LiDAR integration process.We introduce novel methodologies for data fusion and sensor redundancy to enhance the reliability and accuracy of perception systems in AEVs.Additionally, we discuss proactive strategies for hazard detection, risk assessment, and collision avoidance, leveraging the rich spatial information obtained from LiDAR sensors.Furthermore, we highlight the importance of robust cybersecurity protocols to safeguard LiDAR data against potential cyber threats.Through extensive simulations and real-world experiments, we demonstrate the effectiveness and reliability of our proposed framework in enhancing the safety and performance of autonomous electric vehicles.This research contributes to the ongoing efforts to advance autonomous driving technology and promoting the widespread adoption of LiDAR-equipped AEVs in future transportation systems.