端到端的自动驾驶:挑战和边界
概括
端到端的自动驾驶系统整合了感知和规划,以提高性能. 这项调查分析了关于端到端驾驶的270多篇论文,涵盖了方法,挑战和未来的趋势.
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:
- 自动驾驶领域越来越多地采用端到端框架.
- 这些系统处理原始传感器数据,用于直接运动规划,与模块化方法不同.
- 对感知和规划的联合优化比特定任务的模块提供了优势.
研究的目的:
- 提供一个全面的自动驾驶研究端到端的综合调查.
- 分析该领域的动机,方法,挑战和未来方向.
- 涵盖了270多篇相关的学术论文.
主要方法:
- 对端到端自动驾驶证书的系统文献综述.
- 分析方法,包括感知,规划和传感器融合.
- 讨论诸如多模式,可解释性和可靠性等挑战.
主要成果:
- 确定了端到端自动驾驶的关键趋势和进展.
- 详细分析了270多篇论文,对其方法和发现进行了分类.
- 在调查文献中强调了关键的挑战和潜在的解决方案.
结论:
- 端到端的驱动系统显示出显著的希望,从联合优化中受益.
- 应对强度和可解释性等挑战对于未来的发展至关重要.
- 像基础模型这样的新兴技术为端到端的驱动框架提供了新的途径.
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