CLC number: TP18;U495
On-line Access: 2023-01-21
Received: 2022-04-03
Revision Accepted: 2023-01-21
Crosschecked: 2022-08-10
Cited: 0
Clicked: 1418
Citations: Bibtex RefMan EndNote GB/T7714
Huiqian LI, Jin HUANG, Zhong CAO, Diange YANG, Zhihua ZHONG. Stochastic pedestrian avoidance for autonomous vehicles using hybrid reinforcement learning[J]. Frontiers of Information Technology & Electronic Engineering,in press.https://doi.org/10.1631/FITEE.2200128 @article{title="Stochastic pedestrian avoidance for autonomous vehicles using hybrid reinforcement learning", %0 Journal Article TY - JOUR
基于混合强化学习的自动驾驶汽车行人避撞方法1清华大学车辆与运载学院,中国北京市,100084 2中国工程院,中国北京市,100088 摘要:确保行人的安全对自动驾驶汽车而言至关重要,同时也具有一定挑战。经典的行人避撞策略无法应对不确定性,而基于学习的方法缺乏明确的性能保障。本文提出一种基于混合强化学习的行人避撞方法,以使自动驾驶车辆能够与具有行为不确定性的行人安全交互。该方法集成了规则策略和强化学习策略,并设计了一个激活函数选择具有更高置信度的作为最终策略,通过这种方式保证最终策略的表现不亚于规则策略。为说明所提方法的有效性,本文使用一种加速测试方法生成了行为随机的行人进行仿真验证。结果表明,该方法在测试场景中的成功率,相比基准方法的94.4%,提升至98.8%。 关键词组: Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article
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