多目的高速公路的综合决策和运动规划使用自然驾驶研究
Feng Gao1, Xu Zheng1, Qiuxia Hu1
1College of Mechanical and Vehicle Engineering, Chongqing University, Chongqing 400044, China.
Sensors (Basel, Switzerland)
|January 11, 2025
概括
本研究介绍了一种集成的决策和运动规划系统,用于高速公路上的自动驾驶汽车. 它通过使用基于自然驾驶行为的认知安全区域来提高交通效率,安全性和舒适性.
科学领域:
- 机器人技术 机器人技术 机器人技术
- 人工智能的人工智能
- 汽车工程 汽车工程
背景情况:
- 自动驾驶系统越来越复杂,需要集成模块来最大限度地减少信息丢失并提高性能.
- 在多物体高速公路环境中实现适应性和效率仍然是当前自动驾驶系统面临的挑战.
研究的目的:
- 为在多对象高速公路环境中运行的自动化车辆设计一个集成的决策和运动规划系统.
- 提高自动驾驶系统的交通效率,驾驶舒适性,安全性和实时性能.
主要方法:
- 开发了一个两层结构,使用认知安全区域将环境影响与车辆动态脱.
- 人工潜力场方法和人类驾驶员的注意力机制被用来定义认知安全区域.
- 车辆与认知安全区域的互动被模拟为用于分析状态确定的弹阻尼系统.
主要成果:
- 拟议的系统在提高交通效率,驾驶舒适度和安全方面表现出有效性.
- 在复杂的多车辆场景中的比较测试验证了系统的实时性能.
- 认知安全区域方法成功地将环境因素与自我车辆动态脱.
结论:
- 综合决策和运动规划系统为增强高速公路自动驾驶提供了可行的解决方案.
- 通过自然驾驶来告知认知安全区域,为安全和高效的导航提供了有效的机制.
- 将分析简化为弹缓冲系统可以提高实时应用的计算效率.
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