Intelligent connected vehicle cloud data platform for park scene

Maoyuan Cui; Yanxi Gao; Huiqin Zhan; ZhongLin Luo; RunFa Zhou; ZhiBin Cui

doi:10.1117/12.2622724

1 December 2021 Intelligent connected vehicle cloud data platform for park scene

Maoyuan Cui, Yanxi Gao, Huiqin Zhan, ZhongLin Luo, RunFa Zhou, ZhiBin Cui

Proceedings Volume 12079, Second IYSF Academic Symposium on Artificial Intelligence and Computer Engineering; 1207904 (2021) https://doi.org/10.1117/12.2622724
Event: 2nd IYSF Academic Symposium on Artificial Intelligence and Computer Engineering, 2021, Xi'an, China

Abstract

With the development of autonomous driving technology, the level of intelligent vehicles has also become higher and higher. However, in the process of upgrading the level of automatic driving, the upgrading of the intelligent level of vehicles cannot effectively solve a series of functions that need to be realized in the process of high-level automatic driving, such as global traffic intelligent planning and scheduling, and beyond visual range perception. Combining intelligent vehicles with cloud computing technology to develop a cloud data platform is a practical and feasible solution for the development of high-level autonomous driving technology. Based on the key projects of the Intelligent Connected Laboratory, this paper conducts research on the rapid implementation plan of the small standardized intelligent connected vehicle cloud data platform, using the Internet of Things protocol Message Queuing Telemetry Transport to realize the intelligent vehicle-cloud platform’s data communication, MySQL database storage analysis and web front-end data visualization construction plan for related system development and experimental verification.

Citation Download Citation

Maoyuan Cui, Yanxi Gao, Huiqin Zhan, ZhongLin Luo, RunFa Zhou, and ZhiBin Cui "Intelligent connected vehicle cloud data platform for park scene", Proc. SPIE 12079, Second IYSF Academic Symposium on Artificial Intelligence and Computer Engineering, 1207904 (1 December 2021); https://doi.org/10.1117/12.2622724

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