.png){kind=icon}
返回
Influence diagrams for speed profile optimization
.png){kind=icon}
PRE
AI
DOI：10.1016/j.ijar.2016.11.018.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Influence diagrams have been applied to diverse decision problems. In this paper, we describe their application to the speed profile optimization problem a problem traditionally solved by the methods of optimal control theory. Influence diagrams appeared to be well-suited to these types of problems. It is mainly due to their ability to perform computations efficiently if the utility function is additively decomposed along the vehicle path, which is the case for utility functions based on, e.g., the total driving time or the total fuel consumption. Also, driving constraints can be efficiently included in the influence diagram. If the vehicle speed deviates from the optimal speed profile during the real drive, a new optimal speed profile can be quickly computed in the compiled influence diagram. The theory of influence diagrams has not yet been sufficiently developed for continuous variables and nonlinear utility functions. We cope with this issue by discretization and by stochastic approximations of deterministic problems. We performed experiments on a real problem the speed control of a Formula 1 race car. Influence diagrams can provide a good solution of the problem very quickly. This solution can be used as an initial solution for the methods of the optimal control theory and improves the convergence of these methods. (C) 2016 Elsevier Inc. All rights reserved.
Keyword:
Influence diagrams
Optimal control
Vehicle control
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
论文数:
3.0K
被引数:
5.1K
机构
引用论文
.png){kind=icon}
Hopfield learning‐based and non‐linear programming methods for resource allocation in OCDMA networks
OAAI
OAAI分享收藏
查看更多内容