Construction of airport digital runway based on in-situ sensing data
Performance evaluation of facilities in flight area is a key factor affects the safety of airport, and real-time monitoring of the infrastructures and reporting the performance of the airport runway are the critical methods for ensuring the airport in safe condition. However, traditional way of evaluating the airport infrastructure needs to shutdown the traffic and cannot report the performance of airport infrastructure in real time. Nowadays, many airport authorities are trying to use multiple sensors to measure the properties of airport infrastructure in real time, but the performance evaluation parameters for the airport runway are still needed. This work proposed an airport digital runway construction method based on in-situ sensing data for potentially developing the airport runway performance evaluation parameters in a timely format. The method consists of obtaining real-time multi-source state information of the runway through sensors, analyzing the runway evaluation indexes through the measured data, as well as the architecture and main functions of the digital runway system. The airport digital runway constructed by using 3Dsmax + Datav, can provide the performance information of runway and predict the potential risks of runway, which helps the airport runway management department to better understand the performance of airport runway. This result has been piloted at Chengdu Tianfu International Airport and greatly enhanced the ability to manage safety risks.
Authors
- Han Li-bin
- Fan Yang (ORCID: https://orcid.org/0000-0003-4801-763X)
- Jianming Ling
- Zhaoyang Li
- Zhang Jiake
Institutions
- Tongji University (CN)
- Manchester Airport (GB)
- Yuntianhua Group (China) (CN)
Publication Details
- Journal
- International Journal of Transportation Science and Technology
- Published
- 2025-01-22
- DOI
- https://doi.org/10.1016/j.ijtst.2025.01.010
- Citations
- 2
- Primary Topic
- Simulation and Modeling Applications
- Type
- article
- Field-Weighted Citation Impact
- 2.43
Funders
- National Natural Science Foundation of China