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Distributed Model Predictive Control over Multiple Groups of Vehicles in Highway Intelligent Space for Large Scale System
Author(s) -
Xiaofeng Tang,
Feng Gao,
Xu Guoyan,
Ding Nenggen,
Yao Cai,
Liu Jian Xing
Publication year - 2014
Publication title -
mathematical problems in engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.262
H-Index - 62
eISSN - 1026-7077
pISSN - 1024-123X
DOI - 10.1155/2014/809124
Subject(s) - scale (ratio) , space (punctuation) , warning system , control (management) , distributed element model , computer science , engineering , simulation , real time computing , artificial intelligence , aerospace engineering , geography , cartography , electrical engineering , operating system
The paper presents the three time warning distances for solving the large scale system of multiple groups of vehicles safety driving characteristics towards highway tunnel environment based on distributed model prediction control approach. Generally speaking, the system includes two parts. First, multiple vehicles are divided into multiple groups. Meanwhile, the distributed model predictive control approach is proposed to calculate the information framework of each group. Each group of optimization performance considers the local optimization and the neighboring subgroup of optimization characteristics, which could ensure the global optimization performance. Second, the three time warning distances are studied based on the basic principles used for highway intelligent space (HIS) and the information framework concept is proposed according to the multiple groups of vehicles. The math model is built to avoid the chain avoidance of vehicles. The results demonstrate that the proposed highway intelligent space method could effectively ensure driving safety of multiple groups of vehicles under the environment of fog, rain, or snow

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