The design of intelligent highway transportation system in smart city based on the internet of things

The design of intelligent expressway transportation system based on the Internet of Things is studied to improve the safety, travel experience, and operation management of expressway. The characteristics of the Internet of Things and cloud computing technology and its application on the expressway are analyzed, and the system design requirements of expressway intelligent transportation are understood. Besides, the overall architecture of the system is studied and designed. The IaaS layer, PaaS layer, and SaaS layer of the cloud platform are designed and deployed. The intelligent information system can make expressway highly informative. The simulation experiments reveal that the system only needs 120 milliseconds in accident processing time, which is far lower than the intelligent transportation system that only uses edge computing technology (201 milliseconds) and the intelligent transportation system that only uses cloud computing technology (443 milliseconds). Meanwhile, the accident response time is only 12 s, which is also superior to other models. In terms of cost-effectiveness, the monthly cost of the system is 7004 yuan, with a CPU utilization rate of 53%, demonstrating good cost-effectiveness and resource utilization efficiency. In addition, compared with the existing system, the average traffic congestion time has been reduced by 25%, the traffic accident rate has been reduced by 18%, and the accident rate has been reduced by 27%. The intelligent traffic system design of expressway, expressway safety, travel service, and operation management is effectively improved by researching the intelligent traffic system design of expressway.

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Publication Details

Journal
Scientific Reports
Published
2024-11-15
DOI
https://doi.org/10.1038/s41598-024-79903-0
Citations
10
Primary Topic
Traffic Prediction and Management Techniques
Type
article
Field-Weighted Citation Impact
2.65

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article

The design of intelligent highway transportation system in smart city based on the internet of things

Rui‐Ting Huang, Zhiming Xu, Huichao Guo
10 citations
Scientific Reports
Traffic Prediction and Management Techniques
2.65
article

The design of intelligent highway transportation system in smart city based on the internet of things

Rui‐Ting Huang, Zhiming Xu, Huichao Guo
article en
10 citations

Abstract

The design of intelligent expressway transportation system based on the Internet of Things is studied to improve the safety, travel experience, and operation management of expressway. The characteristics of the Internet of Things and cloud computing technology and its application on the expressway are analyzed, and the system design requirements of expressway intelligent transportation are understood. Besides, the overall architecture of the system is studied and designed. The IaaS layer, PaaS layer, and SaaS layer of the cloud platform are designed and deployed. The intelligent information system can make expressway highly informative. The simulation experiments reveal that the system only needs 120 milliseconds in accident processing time, which is far lower than the intelligent transportation system that only uses edge computing technology (201 milliseconds) and the intelligent transportation system that only uses cloud computing technology (443 milliseconds). Meanwhile, the accident response time is only 12 s, which is also superior to other models. In terms of cost-effectiveness, the monthly cost of the system is 7004 yuan, with a CPU utilization rate of 53%, demonstrating good cost-effectiveness and resource utilization efficiency. In addition, compared with the existing system, the average traffic congestion time has been reduced by 25%, the traffic accident rate has been reduced by 18%, and the accident rate has been reduced by 27%. The intelligent traffic system design of expressway, expressway safety, travel service, and operation management is effectively improved by researching the intelligent traffic system design of expressway.

Scientific ReportsVol. 14(1)
City University of New York (US), Wuhan University of Technology (CN), XTC (China) (CN), Anhui Xinhua University (CN), Guangzhou Xinhua University
People's Government of Jilin Province
Sustainable cities and communities
Openalex Percentile: Top 11%
Traffic Prediction and Management Techniques
2.65
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