论文标题
在交叉点上的自动驾驶：左转弯的关键转变方法
Autonomous Driving at Intersections: A Critical-Turning-Point Approach for Left Turns
论文作者
论文摘要
左转计划是自动驾驶汽车面临的巨大挑战之一，尤其是在未知的迎面车的意图中，在未信号的交叉路口上。本文通过提出基于关键的转折点（CTP）的层次计划方法来应对挑战。这包括一个高级候选路径生成器和基于可观察到的低级马尔可夫决策过程（POMDP）计划者。提出的（CTP）概念是受人力驾驶行为在交叉口的启发的启发，旨在提高低级计划者的计算效率并实现人类友好的自主驾驶。基于POMDP的低水平计划者将迎面式车辆的未知意图付诸实践，以执行不保守而安全的行动。通过适当的整合，提出的层次结构方法能够实时在未信号的交叉点上以高通勤效率获得安全的计划结果。
Left-turn planning is one of the formidable challenges for autonomous vehicles, especially at unsignalized intersections due to the unknown intentions of oncoming vehicles. This paper addresses the challenge by proposing a critical turning point (CTP) based hierarchical planning approach. This includes a high-level candidate path generator and a low-level partially observable Markov decision process (POMDP) based planner. The proposed (CTP) concept, inspired by human-driving behaviors at intersections, aims to increase the computational efficiency of the low-level planner and to enable human-friendly autonomous driving. The POMDP based low-level planner takes unknown intentions of oncoming vehicles into considerations to perform less conservative yet safe actions. With proper integration, the proposed hierarchical approach is capable of achieving safe planning results with high commute efficiency at unsignalized intersections in real time.
