A cyber-physical system(CPS) is composed of a physical system and its corresponding cyber systems that are tightly fused at all scales and levels.CPS is helpful to improve the controllability,efficiency and reliability of a physical system,such as vehicle collision avoidance and zero-net energy buildings systems.It has become a hot R&D and practical area from US to EU and other countries.In fact,most of physical systems and their cyber systems are designed,built and used by human beings in the social and natural environments.So,social systems must be of the same importance as their CPSs.The indivisible cyber,physical and social parts constitute the cyber-physical-social system(CPSS),a typical complex system and it’s a challengeable problem to control and manage it under traditional theories and methods.An artificial systems,computational experiments and parallel execution(ACP) methodology is introduced based on which data-driven models are applied to social system.Artificial systems,i.e.,cyber systems,are applied for the equivalent description of physical-social system(PSS).Computational experiments are applied for control plan validation.And parallel execution finally realizes the stepwise control and management of CPSS.Finally,a CPSS-based intelligent transportation system(ITS) is discussed as a case study,and its architecture,three parts,and application are described in detail.
Gang XiongFenghua ZhuXiwei LiuXisong DongWuling HuangSonghang ChenKai Zhao
In order to control the large-scale urban traffic network through hierarchical or decentralized methods, it is necessary to exploit a network partition method, which should be both effective in extracting subnetworks and fast to compute. In this paper, a new approach to calculate the correlation degree, which determines the desire for interconnection between two adjacent intersections, is first proposed. It is used as a weight of a link in an urban traffic network, which considers both the physical characteristics and the dynamic traffic information of the link. Then, a fast network division approach by optimizing the modularity, which is a criterion to distinguish the quality of the partition results, is applied to identify the subnetworks for large-scale urban traffic networks. Finally, an application to a specified urban traffic network is investigated using the proposed algorithm. The results show that it is an effective and efficient method for partitioning urban traffic networks automatically in real world.
