Comparative Analysis of 2D Object Detection Algorithms and real-time implementation using RTMAPS

The development of autonomous vehicles has garnered significant attention in recent years due to its potential to revolutionize the way we move and its impact on society, security, and the environment. One of the crucial components of these vehicles is the object detection system, responsible for identifying and localizing objects in the road environment. This task is essential for decision-making processes in autonomous vehicles, such as navigating the vehicle, avoiding obstacles, and changing the driving direction.Despite the challenges posed by the variability of objects in the road environment, this paper proposes a system for autonomous vehicle guidance based on embedded systems and the RTMAPS tool. The primary focus of the system is to perform effective object detection.To achieve this objective, the study evaluates several stateof-the-art algorithms for 2D object detection and selects the best algorithms based on precision and inference time. The selected algorithm is then implemented using RTMAPS in realworld scenarios on the university’s track. The results of this study provide valuable insights for the research and practical community in the field of autonomous vehicles and serve as a reference for future work in object detection