Enhanced SSD Algorithm-Based Object Detection and Depth Estimation for Autonomous Vehicle Navigation
Vaibhav Saini, MVV Prasad Kantipudi, Pramoda Meduri · International Journal of Transport Development and Integration · 2023
Autonomous vehicles necessitate robust stability and safety mechanisms for effective navigation, relying heavily upon advanced perception and precise environmental awareness.This study addresses the object detection challenge intrinsic to autonomous navigation, with a focus on the system architecture and the integration of cutting-edge hardware and software technologies.The efficacy of various object recognition algorithms, notably the Single Shot Detector (SSD) and You Only Look Once (YOLO), is rigorously compared.Prior research has indicated that SSD, when augmented with depth estimation techniques, demonstrates superior performance in real-time applications within complex environments.Consequently, this research proposes an optimized SSD algorithm paired with a Zed camera system.Through this integration, a notable improvement in detection accuracy is achieved, with a precision increase to 87%.This advancement marks a significant step towards resolving the critical challenges faced by autonomous vehicles in object detection and distance estimation, thereby enhancing their operational safety and reliability.