基于本体推理和BN的无人驾驶行为决策  

Unmanned Driving Behavior Decision Based on Ontology Knowledge Reasoning and BN

作　　者：常嘉伟 施卫 刘斌 李展峰 封功源 CHANG Jiawei;SHI Wei;LIU Bin;LI Zhanfeng;FENG Gongyuan(School of Mechanical Engineering,Jiangsu University of Technology,Changzhou 213000,China)

机构地区：[1]江苏理工学院机械工程学院,江苏常州213000

出　　处：《汽车实用技术》2022年第17期14-19,共6页Automobile Applied Technology

基　　金：江苏省社科“公共利益导向的产教联合培养职教师资的路径与策略研究”(19JYB012)。

摘　　要：相较于高速与高架路段,无人驾驶行为决策系统在城区路段要面对更为复杂和多变的交通道路环境。文章提出一种将本体知识推理和贝叶斯网络(BN)相结合的方法,通过对道路环境本体模型加以逻辑推理,迁移为BN的结构参数,并根据历史驾驶案例和专家经验构建完整的贝叶斯网络。最后通过BN判断当前场景的最佳驾驶模式。本方法能使车辆较好地判断当前最优驾驶行为。Compared to high-speed and elevated road sections, driver’s decision systems should face more complex and multi-change traffic road environments in urban roads. This paper proposes a method of combining the ontology knowledge and Bayesian Network(BN). By logic reasoning to the road environment body model, migrates to the structural parameters of BN, and constructs a complete construction Bayesian network according to historical driving cases and expert experience.Finally the best driving mode of the current scene is judged by BN. The present method can make the vehicle better judge the current optimal driving behavior.

关 键 词：无人驾驶 本体推理 贝叶斯网络 行为决策 

分 类 号：U469.5[机械工程—车辆工程]