Technology Application of Autonomous Vehicle in Machine Learning

Fang Shang

2024

Abstract

The development of autonomous vehicle technology has significantly promoted innovation in Sensor Fusion and Object Detection methods based on Machine Learning, especially in single-modal target detection and Multi-Modal Data fusion. This research explores object detection techniques based on RGB images and point cloud data, such as Faster-RCNN and PointNet, to improve performance in complex scenes. These methods have significant advantages in distinguishing objects in complex scenes, thus enhancing the perception of vehicles. In addition, research has focused on Multi-Modal Data Fusion technologies, such as fusing images with point clouds and radar data, to enable autonomous driving systems to better cope with severe weather and complex environments. By integrating multiple sensor data, these Machine Learning methods improve the perception and decision reliability of the system. However, challenges in data quality, model generalization, and robustness remain. To solve these problems, it is necessary to optimize the sensor fusion algorithm and further enhance the reliability and security of the model. Future research will focus on improving these sensor fusion strategies to ensure that Autonomous Vehicles achieve reliable and efficient perception under a variety of real-world conditions, supporting safer and more intelligent autonomous driving systems.

Paper Citation

in Harvard Style

Shang F. (2024). Technology Application of Autonomous Vehicle in Machine Learning. In Proceedings of the 2nd International Conference on Data Analysis and Machine Learning - Volume 1: DAML; ISBN 978-989-758-754-2, SciTePress, pages 446-450. DOI: 10.5220/0013525800004619

in Bibtex Style

@conference{daml24,
author={Fang Shang},
title={Technology Application of Autonomous Vehicle in Machine Learning},
booktitle={Proceedings of the 2nd International Conference on Data Analysis and Machine Learning - Volume 1: DAML},
year={2024},
pages={446-450},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013525800004619},
isbn={978-989-758-754-2},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 2nd International Conference on Data Analysis and Machine Learning - Volume 1: DAML
TI - Technology Application of Autonomous Vehicle in Machine Learning
SN - 978-989-758-754-2
AU - Shang F.
PY - 2024
SP - 446
EP - 450
DO - 10.5220/0013525800004619
PB - SciTePress