集成多传感器融合和决策架构的自动驾驶汽车在多对象的交通条件
Hai Ngoc Nguyen1, Thien Nguyen Luong1, Tuan Pham Minh1
1Vietnam National Space Center, Vietnam Academy of Science and Technology, Hanoi 100000, Vietnam.
Sensors (Basel, Switzerland)
|November 27, 2025
概括
本研究介绍了为越南量身定制的自动驾驶汽车系统.
科学领域:
- 机器人和智能系统 机器人和智能系统
- 计算机视觉 计算机视觉
- 运输工程 运输工程
背景情况:
- 自动驾驶汽车 (AV) 为提高运输安全和效率提供了巨大的潜力.
- 现有的自动驾驶系统往往难以应对各种全球交通条件所带来的独特挑战.
- 越南复杂的城市环境和特定的道路基础设施需要专门的AV解决方案.
研究的目的:
- 为越南的交通开发和验证一个全面的自动驾驶汽车系统.
- 解决越南城市和农村道路上驾驶的具体挑战.
- 通过自主技术提高越南移动系统的安全性和效率.
主要方法:
- 采用了多层系统,集成双2D LiDAR,摄像头视觉和GPS.
- 开发了一种专门的细分模型,用于识别越南特定的流量元素.
- 实施了具有长期和短期规划的层次决策架构.
- 采用经过验证的控制模型来调节转速和转向.
主要成果:
- 在细分和检测流量元素方面实现了高精度.
- 在现实世界测试中展示了精确的导航响应.
- 在越南独特的交通环境中验证了系统的强大性能.
- 成功应对混合流量和国家特定基础设施等挑战.
结论:
- 拟议的自动驾驶汽车系统对越南的交通条件有效.
- 专业化的细分和层次化的决策是系统成功的关键.
- 这项技术有可能显著提高越南的运输安全和效率.
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