.png){kind=icon}
返回
Unexpected Collision Avoidance Driving Strategy Using Deep Reinforcement Learning
.png){kind=icon}
OA
AI
DOI：10.1109/ACCESS.2020.2967509.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
In this paper, we generated intelligent self-driving policies that minimize the injury severity in unexpected traffic signal violation scenarios at an intersection using the deep reinforcement learning. We provided guidance on reward engineering in terms of the multiplicity of objective function. We used a deep deterministic policy gradient method in the simulated environment to train self-driving agents. We designed two agents, one with a single-objective reward function of collision avoidance and the other with a multi-objective reward function of both collision avoidance and goal-approaching. We evaluated their performances by comparing the percentages of collision avoidance and the average injury severity against those of human drivers and an autonomous emergency braking (AEB) system. The percentage of collision avoidance of our agents were 78.89 & x0025; higher than human drivers and 84.70 & x0025; higher than the AEB system. The average injury severity score of our agents were only 8.92 & x0025; of human drivers and 6.25 & x0025; of the AEB system.
Keyword:
Autonomous vehicles
collision avoidance
intelligent vehicles
injury severity
multi-objective optimization
reinforcement learning
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
3.6
论文数:
9.8W
被引数:
29.4W
机构
引用论文
.png){kind=icon}
Study of bi-directional buck-boost converter topologies for application in electrical vehicle motor drives应用于电动汽车电机驱动的双向buck-boost变换器拓扑研究
PREAI
分享收藏Cooperative Collision Avoidance for Overtaking Maneuvers in Cellular V2X-Based Autonomous Driving
PREAI
分享收藏Toward an Effective Risk-Conscious and Collaborative Vehicular Collision Avoidance System走向有效的风险意识和协作的车辆防撞系统
PREAI
分享收藏Driving Assistant Companion With Voice Interface Using Long Short-Term Memory Networks使用长短期记忆网络的带语音接口的驾驶辅助伴侣
PREAI
分享收藏Path Planning and Tracking for Vehicle Collision Avoidance Based on Model Predictive Control With Multiconstraints基于多约束模型预测控制的车辆避碰路径规划与跟踪
PREAI
分享收藏
查看更多内容