Design of Distributed Cyber-Physical Systems for Connected and Automated Vehicles with Implementing Methodologies
- Zhejiang Univ., Hangzhou (China)
- Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
- Zhejiang Univ., Hangzhou (China). Yicong Gao State Key Lab. of Fluid Power and Mechatronic Systems
- Xidian Univ., Xi'an, Shaanxi (China)
With the development of communication and control technology, intelligent transportation systems have received increasing attention from both industry and academia. Intelligent transportation systems are supported by the Internet of Things, Cyber-Physical System, Artificial Intelligence, Cloud Computing and many other technologies, which supply fundamental information for connected and automated vehicles. Although plenty of studies have provided different formulations for intelligent transportation systems, many of them depend on Master Control Center. However, a centralized control mode requires a huge amount of data transmission and high level of hardware configuration and may cause communication delay and privacy leak. Some distributed architectures have been proposed to overcome the above problems but systematized technologies to collect and exchange information, process large amounts of data, model the dynamics of vehicles, and safely control the connected and automated vehicles are not explored in detail. In this paper, we proposed a novel distributed cyber-physical system for connected and automated vehicles in which every vehicle is modeled as a double-integrator using edge computing to analyze information collected from its nearest neighbors. The vehicles are supposed to travel along a desired trajectory and to maintain a rigid formation geometry. Related methodologies for the proposed system are illustrated and experiments are conducted showing that the performance of the connected and automated vehicles matches very well with analytic predictions. Some design guidelines and open questions are provided for the future study.
- Research Organization:
- Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
- Sponsoring Organization:
- USDOE; National Natural Science Foundation of China (NSFC)
- Grant/Contract Number:
- AC0576RL01830
- OSTI ID:
- 1423627
- Journal Information:
- IEEE Transactions on Industrial Informatics, Vol. PP, Issue 99; ISSN 1551-3203
- Publisher:
- IEEECopyright Statement
- Country of Publication:
- United States
- Language:
- English
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