摘 要
随着智能交通系统的发展，自动驾驶汽车成为当前研究热点，计算机视觉作为其核心技术之一发挥着不可替代的作用。本研究旨在探讨计算机视觉在自动驾驶汽车中的应用，以提高车辆行驶的安全性和智能化水平为目的。通过融合深度学习算法与传统图像处理技术，构建了多传感器协同的视觉感知系统，实现了对道路环境、交通标志、行人及其他障碍物的精准识别。创新性地提出了基于卷积神经网络的目标检测与跟踪算法，有效解决了复杂环境下目标遮挡和光照变化带来的挑战。实验结果表明，该系统能够在多种路况下稳定运行，检测准确率达到95%以上，响应时间缩短至毫秒级，显著提升了自动驾驶汽车的环境适应能力。此外，还开发了场景理解模块，使车辆具备预测其他交通参与者行为的能力，进一步增强了系统的安全性和可靠性。本研究为推动自动驾驶技术向更高级别发展提供了理论依据和技术支持，主要贡献在于建立了完整的计算机视觉解决方案框架，为后续研究奠定了坚实基础。
关键词：自动驾驶汽车 计算机视觉 目标检测与跟踪
Abstract
With the development of intelligent transportation systems, autonomous vehicles have become a current research hotspot, and computer vision, as one of its core technologies, plays an irreplaceable role. This study aims to explore the application of computer vision in autonomous driving, with the ob jective of enhancing vehicle safety and intelligence. By integrating deep learning algorithms with traditional image processing techniques, a multi-sensor collaborative visual perception system has been constructed, achieving precise recognition of road environments, traffic signs, pedestrians, and other obstacles. An innovative ob ject detection and tracking algorithm based on convolutional neural networks has been proposed, effectively addressing challenges posed by occlusions and lighting variations in complex environments. Experimental results demonstrate that the system can operate stably under various road conditions, with a detection accuracy exceeding 95%, and response time shortened to milliseconds, significantly improving the environmental adaptability of autonomous vehicles. Additionally, a scene understanding module has been developed, enabling the vehicle to predict the behavior of other traffic participants, further enhancing system safety and reliability. This research provides theoretical basis and technical support for advancing autonomous driving technology to higher levels, with the main contribution being the establishment of a comprehensive computer vision solution fr amework, laying a solid foundation for future studies.
Keyword:Autonomous Vehicle Computer Vision ob ject Detection And Tracking
目 录
引言 1
1计算机视觉基础与自动驾驶 1
1.1计算机视觉技术概述 1
1.2自动驾驶汽车的需求分析 2
1.3视觉系统在自动驾驶中的作用 2
2环境感知与物体识别 3
2.1道路环境的视觉感知 3
2.2行人与车辆检测识别 3
2.3交通标志与信号识别 4
3视觉导航与路径规划 4
3.1基于视觉的定位技术 4
3.2路径规划中的视觉应用 5
3.3复杂环境下的导航策略 5
4安全保障与系统优化 6
4.1视觉系统的可靠性评估 6
4.2应对突发状况的视觉方案 7
4.3系统性能的持续优化 7
结论 8
参考文献 9
致谢 9
