构建交通运输的未来:关于AV感知,定位和映射的全面调查
Ashok Kumar Patil1, Bhargav Punugupati1, Himanshi Gupta1
1Department of Computer Science Engineering, PES University, Bangalore 560085, India.
Sensors (Basel, Switzerland)
|April 12, 2025
概括
本综述涵盖了自动驾驶汽车 (AV) 的感知,定位和映射. 它分析了对象检测,跟踪和映射技术,为AV开发提供了洞察力.
科学领域:
- 机器人和人工智能 机器人和人工智能
- 计算机视觉和传感器融合
背景情况:
- 自动驾驶汽车 (AV) 需要复杂的感知,定位和绘图系统来安全导航.
- 现有的方法在复杂的城市环境和GPS拒绝的场景中面临挑战.
研究的目的:
- 审查和分析AV感知,定位和映射当前的方法和最佳实践.
- 通过现实世界的测试,提供对各种技术有效性的见解.
主要方法:
- 对象检测 (例如YOLOv8) 和跟踪 (例如ByteTrack,BoT-SORT).
- 定位技术包括基于LiDAR,基于相机和传感器融合.
- 绘图策略,如SLAM和高清地图等.
主要成果:
- 评估实时性能和感知算法的稳定性.
- 在GPS不可靠条件下评估定位准确性.
- 对绘图技术进行分析,以进行详细的环境表示.
结论:
- 总结了AV感知,定位和映射方面的进步,挑战和实际考虑.
- 作为自动驾驶汽车领域的研究人员和开发人员的参考.
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