Abstract
An increasing number of extra-long highway tunnels have been built and put into operation around the world, but the quantified segmentation criteria for evaluating the in-tunnel operational status have not yet been enacted up till the present moment. Meanwhile, ventilation facilities could not satisfy the dynamic requirements of fresh air demand under fast spatial-temporal variation of traffic conditions and operating environment. In this study, the operational data collected from an extra-long highway tunnel were deeply analyzed using big data technology. By combining traffic flow and environmental monitoring data, a data-driven perception model based on the Random Forests was structured. The prediction results show that the proposed model provides better performances as compared to contrast models, indicating it had better ability to adapt to the dynamic changes of in-tunnel operational status while realizing accurate prediction. The designed intelligent control strategies of ventilation facilities and traffic operation applying for different operational status would provide a theoretical basis and data support for lifting the level of intelligent control as well as promoting energy saving and consumption reducing in extra-long highway tunnels.
Highlights
By the end of 2016, 815 extra-long highway tunnels with a total length of 3622.7 km were built in China [1]
Determining the optimal number of clusters is a fundamental issue in clustering analysis
Naıve Bayes classifier assumes that the value of a particular feature is independent of the value of any other feature, which is always invalid in practice
Summary
By the end of 2016, 815 extra-long highway tunnels with a total length of 3622.7 km were built in China [1]. Owing to the influence of traffic volume and fleet composition, vehicle emissions accumulate sequentially. These emissions are difficult to disperse, especially in the case of extra-long highway tunnels with high traffic loads and frequent traffic congestions. There exist several, very different approaches to ventilation concepts [2]. They have common objectives, opposite in nature: (a) the pollution levels within admissible margins and (b) the energy consumption for ventilation facilities to fulfill objective (a) should be minimal. Many advanced control methodologies have been proposed in recent decades
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
