关于自动驾驶汽车行为的调查:轨迹规划算法,感知碰撞风险和用户期望
1School of Automotive Studies, Tongji University, Shanghai 201804, China.
Sensors (Basel, Switzerland)
|August 10, 2024
概括
本研究审查了自动驾驶汽车轨迹规划算法,重点关注碰撞风险估计和与用户一致的规划. 它分析了更安全,类似人类的自动驾驶的方法,突出了当前的挑战和未来的方向.
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
- 运输工程 运输工程
背景情况:
- 自动驾驶汽车 (AV) 是交通运输领域的一个变革性技术.
- 有效的轨道规划对于安全和高效的AV运行至关重要.
- 现有的研究为当地轨迹规划提供了各种方法.
研究的目的:
- 综合审查和分类自动驾驶汽车运动轨迹规划算法.
- 通过使用环境数据来研究对碰撞风险估计的方法.
- 探索与用户结合的轨迹规划技术,以实现类似人类驾驶行为.
主要方法:
- 关于本地轨迹规划算法的最近研究的文献综述.
- 对碰撞风险估计方法的分类和分析.
- 探索利用人类数据的以用户体验为导向的方法.
主要成果:
- 详细讨论和区分各种轨迹规划算法类别.
- 基于环境传感和整合的风险估计方法的分类.
- 识别以用户为中心的方法,以提高轨迹规划性能.
结论:
- 对比分析揭示了轨迹规划,风险评估和用户体验之间的相互联系.
- 在自动驾驶汽车轨迹规划方面,仍然存在重大挑战.
- 未来的研究应该专注于推进这些强大的AV系统的综合方法.
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