自动驾驶汽车 3D 物体检测的最新进展:调查

AI Pub Date : 2024-07-25 DOI:10.3390/ai5030061
Oluwajuwon A. Fawole, Danda B. Rawat
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引用次数: 0

摘要

自驾车或自动驾驶汽车的发展带动了三维物体检测技术的重大进步,这对自动驾驶的安全性和效率至关重要。尽管最近取得了一些进展,但在传感器集成、处理稀疏和噪声数据以及确保不同环境条件下的可靠性能等方面仍存在一些挑战。本文全面介绍了最先进的自动驾驶汽车三维物体检测技术,强调了多传感器融合技术和高级深度学习模型的重要性。此外,我们还介绍了未来研究的关键领域,包括增强传感器融合算法、提高计算效率以及解决道德、安全和隐私问题。通过强调潜在的优势和局限性,介绍了如何将这些技术整合到自动驾驶的实际应用中。我们还以表格形式对不同技术进行了并列比较。通过全面回顾,本文旨在深入探讨三维物体检测的未来发展方向及其对自动驾驶发展的影响。
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Recent Advances in 3D Object Detection for Self-Driving Vehicles: A Survey
The development of self-driving or autonomous vehicles has led to significant advancements in 3D object detection technologies, which are critical for the safety and efficiency of autonomous driving. Despite recent advances, several challenges remain in sensor integration, handling sparse and noisy data, and ensuring reliable performance across diverse environmental conditions. This paper comprehensively surveys state-of-the-art 3D object detection techniques for autonomous vehicles, emphasizing the importance of multi-sensor fusion techniques and advanced deep learning models. Furthermore, we present key areas for future research, including enhancing sensor fusion algorithms, improving computational efficiency, and addressing ethical, security, and privacy concerns. The integration of these technologies into real-world applications for autonomous driving is presented by highlighting potential benefits and limitations. We also present a side-by-side comparison of different techniques in a tabular form. Through a comprehensive review, this paper aims to provide insights into the future directions of 3D object detection and its impact on the evolution of autonomous driving.
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