以环境为导向的方法实现5级自动驾驶
Mohammad Hurair1, Jaeil Ju1, Junghee Han1
1School of Electronics and Information Engineering, Korea Aerospace University, 76 Hanggongdaehang-ro, Goyang-si 412-791, Gyeonggi-do, Republic of Korea.
Sensors (Basel, Switzerland)
|January 23, 2024
概括
本研究引入了完全自动驾驶汽车的环境驱动框架. 它管理内部参数以满足实时的截止日期,确保在复杂的驾驶场景中安全操作.
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
- 计算机科学 计算机科学
背景情况:
- 技术的进步正在推动完全自动驾驶汽车 (5级) 的发展.
- 实现5级自动驾驶需要超过4级的大量研究,特别是复杂环境中的安全操作.
- 实时性能至关重要,因为自动驾驶汽车中的传感器系统和机器学习算法必须遵守严格的端到端延迟截止日期.
研究的目的:
- 为自动驾驶汽车提出一个新的框架,以确保端到端的延迟截止日期.
- 解决自动驾驶系统中机器学习模块的计算强度问题.
- 为了保持驾驶精度,同时满足性能要求.
主要方法:
- 开发了一种以环境为导向的方法,区分无法控制的环境因素和可控制的内部因素 (例如传感频率,图像分辨率,预测率,汽车速度).
- 设计了一个入口控制模块来调节内部参数,如图像分辨率和检测周期.
- 该框架根据当前的环境情景确定了满足端到端截止日期的参数的可接受性.
主要成果:
- 拟议的框架成功地管理了内部参数,以满足端到端的最后期限.
- 该系统证明了其在各种条件下保持自主驾驶精度的能力.
- 验证使用远程控制 (RC) 汽车和模拟环境进行.
结论:
- 环境驱动的框架提供了一个可行的解决方案,以确保自动驾驶汽车的及时性能.
- 根据环境背景控制内部参数是实现可靠的5级自动驾驶的关键.
- 该方法提供了一种在复杂的自动驾驶系统中平衡计算负载和驾驶精度的方法.
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