考虑定位与环境不确定性，改进纯追踪路径跟踪算法。
Unscented Transform-based Pure Pursuit Path-Tracking Algorithm under Uncertainty
- 用无迹变换建模路径跟踪中的不确定性
- 仿真验证在直道和弯道上有效降低跟踪误差
- 适合自动驾驶系统在不确定环境下使用
自动驾驶因有望消除人为驾驶事故而日益普及。其中一项挑战是车辆需在存在自身定位或环境感知不确定性的情况下，仍能自主跟随预定路径行驶，例如如何调整转向以最小化跟踪误差。本文提出一种基于无迹变换改进的几何纯追踪路径跟踪算法，用于处理上述不确定性。算法在典型道路几何（如直线段和圆弧）的仿真中进行了测试，结果表明其在不确定环境下仍能有效保持路径跟踪性能。
原文摘要 · Abstract (English)
Automated driving has become more and more popular due to its potential to eliminate road accidents by taking over driving tasks from humans. One of the remaining challenges is to follow a planned path autonomously, especially when uncertainties in self-localizing or understanding the surroundings can influence the decisions made by autonomous vehicles, such as calculating how much they need to steer to minimize tracking errors. In this paper, a modified geometric pure pursuit path-tracking algorithm is proposed, taking into consideration such uncertainties using the unscented transform. The algorithm is tested through simulations for typical road geometries, such as straight and circular lines.
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