通过遵守法律的潜在领域,加强自动驾驶汽车的合法驾驶
Chengxiang Zhao1, Zichun Xiong2, Lei Song1
1School of Vehicle and Mobility, Tsinghua University, Beijing, 100084, China.
Accident; analysis and prevention
|February 15, 2026
概括
自动驾驶汽车需要更好地遵守交通法规. 这项研究引入了一种使用潜在领域的新方法,以改善法律遵守,即使安全受到挑战.
科学领域:
- 自主驾驶系统 自主驾驶系统
- 交通法规遵守 交通法规遵守
- 决策框架 决策框架
背景情况:
- 混合交通环境需要自动驾驶汽车 (AV) 与人类驾驶员一起遵守交通法规.
- 当前的AV决策往往优先考虑安全而不是系统的法律合规性,在复杂的场景中冒着违规的风险.
研究的目的:
- 开发一种新的方法来提高AV交通法规的遵守.
- 解决混合交通中现有的以安全为中心的决策方法的局限性.
主要方法:
- 提出了一种法律合规潜在领域 (LCPF) 方法,将交通法约束归类为四个潜在领域.
- 这些字段编码车辆状态,环境元素和合规门.
- 一种新的融合策略解决了场重叠扭曲,集成到模型预测控制 (MPC) 框架中.
主要成果:
- 在五个代表性场景中进行了实验验证,包括安全合规冲突.
- 通过LCPF方法显著提高了自动驾驶汽车遵守交通法规的能力.
- 证明了安全和合规的有效平衡,即使在具有挑战性的条件下也是如此.
结论:
- 拟议的LCPF方法提供了一个可靠的解决方案,以确保自动驾驶汽车遵守交通法规.
- 这种方法对于混合交通环境中的安全和合法的AV运行至关重要.
- 未来的工作可以探索进一步的改进和现实世界的部署.
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