A Novel Highway Traffic Capacity Analyzing Method under Road Region Atmospheric Environment Constrains Based on Computational Fluid Dynamics Model
<|reference_start|>A Novel Highway Traffic Capacity Analyzing Method under Road Region Atmospheric Environment Constrains Based on Computational Fluid Dynamics Model: Highways always have a huge impact on the environment, quantifying the level of pollution and calculating the traffic capacity under environmental constraints is an important part of practicing environmental protection. Available traffic capacity methods do not focus on the traffic emissions impact on road region environment. To fill this research gap, this paper proposes a method consisting of Computational Fluid Dynamics (CFD) model and Traffic Flow Field and the Gas Flow Field coupled model for the traffic capacity model. The COPERT 5 model is adopted to simulate the traffic emissions on highways with field measurement data and traffic conditions as initial conditions. Then, these are served as the inputs, set and further calculated using coupled model in the CFD numerical simulation phase. Finally, modeling the Traffic Capacity model and calculating the traffic capacity. The experiment results in G30 Yongshan highway section demonstrate that, with the proposed method, the CFD simulation model for traffic emissions in highway region can reflect the practical conditions (the overall error is within 10%), while the traffic capacity can be well performance with the traffic capacity model under the atmospheric pollution constraints. The annual average traffic capacity of G30 Yongshan is 739,800 vehicles, and SO2 under different constraints has the greatest limitation on traffic capacity (90,9662 vehicles), which is the most dominant impact in the environmental constraints of the road region, rest are ranked in: NO2 (246,5373), PM2.5 (323,6022), CO (771,8717), CO2 (803,7217), and PM10 (2202,0013).<|reference_end|>
@article{li2024a,
    title={A Novel Highway Traffic Capacity Analyzing Method under Road Region
  Atmospheric Environment Constrains Based on Computational Fluid Dynamics
  Model},
    author={Ruohan Li, Hualan Wang, Qiyang Zhang, Ting Nie},
    journal={arXiv preprint arXiv:2408.00896},
    year={2024},
    archivePrefix={arXiv},
    eprint={2408.00896},
    primaryClass={math.NA cs.NA}
}