一个空间时间预测变压器网络,用于3级自动驾驶汽车决策
IEEE transactions on neural networks and learning systems
|November 6, 2024
概括
这项研究通过准确预测接管时间 (TOT) 来增强自动驾驶汽车的决策能力. 改进的TOT预测可以为3级自动驾驶汽车带来更安全,更舒适的驾驶体验.
科学领域:
- 自主驾驶系统 自主驾驶系统
- 决策算法 决策算法
- 人与机器的互动 人与机器的互动
背景情况:
- 现有关于3级自动驾驶汽车 (L3-AV) 的研究缺乏对接管时间 (TOT) 机制的深入分析.
- 目前的L3-AV研究忽略了对TOT预测至关重要的特征的时空变化.
- 在L3-AV的下游轨迹规划中,TOT没有得到充分的考虑.
研究的目的:
- 调查接管时间 (TOT) 对3级自动驾驶汽车 (L3-AV) 决策的影响.
- 为准确的TOT预测和轨迹预测开发先进的模型.
- 为了提高L3-AV决策过程的安全性和舒适性.
主要方法:
- 为TOT预测提出了一个指数级光滑变压器 (ETSformer) 模型.
- 采用时空预测变压器 (ST-Preformer) 进行周围车辆轨迹预测.
- 整合TOT预测和轨迹评估到L3-AV决策框架中.
主要成果:
- ETSformer模型解释了超过83%的TOT分布特征.
- 实现了对TOT预测的绝对百分比误差的0.7%降低.
- 决策框架使安全和舒适的最佳决策成为可能.
结论:
- 准确的TOT预测对于L3-AV安全性和决策稳定性至关重要.
- 了解TOT的影响可以改善自动驾驶的安全性和决策技巧.
- 拟议的模型为更强大,更可靠的L3-AV系统提供了途径.
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