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Zhongmin Huang, M.N. Smirnova, N.N. Smirnov, Zuojin Zhu. 2024: Predicting effects of tunnel throttling of annular freeway vehicular flow by a continuum model. Journal of Traffic and Transportation Engineering (English Edition), 11(4): 733-746. DOI: 10.1016/j.jtte.2022.08.005
Citation: Zhongmin Huang, M.N. Smirnova, N.N. Smirnov, Zuojin Zhu. 2024: Predicting effects of tunnel throttling of annular freeway vehicular flow by a continuum model. Journal of Traffic and Transportation Engineering (English Edition), 11(4): 733-746. DOI: 10.1016/j.jtte.2022.08.005

Predicting effects of tunnel throttling of annular freeway vehicular flow by a continuum model

  • Abstract: Fluid flow throttling is common in industrial and building services engineering. Similar tunnel throttling of vehicular flow is caused by the abrupt number reduction of roadway lane, as the tunnel has a lower lane number than in the roadway normal segment. To predict the effects of tunnel throttling of annular freeway vehicular flow, a three-lane continuum model is developed. Lane Ⅲ of the tunnel is completely blocked due to the need of tunnel rehabilitation, etc. There exists mandatory net lane-changing rate from lane Ⅲ to lane Ⅱ just upstream of the tunnel entrance, which is described by a model of random number generated through a golden section analysis. The net-changing rate between adjacent lanes is modeled using a lane-changing time expressed explicitly in algebraic form. This paper assumes that the annular freeway has a total length of 100 km, a two-lane tunnel of length 2 km with a speed limit of 80 km/h. The free flow speeds on lanes Ⅰ, Ⅱ and Ⅲ are assumed to be 110, 100 and 90 km/h respectively. Based on the three-lane continuum model, numerical simulations of vehicular flows on the annular freeway with such a tunnel are conducted with a reliable numerical method of 3rd-order accuracy. Numerical results reveal that the vehicular flow has a smaller threshold of traffic jam formation in comparison with the case without tunnel throttling. Vehicle fuel consumption can be estimated by interpolation with time averaged grid traffic speed and an assumed curve of vehicle performance. The vehicle fuel consumption is lane number dependent, distributes with initial density concavely, ranging from 5.56 to 8.00 L. Tunnel throttling leads to an earlier traffic jam formation in comparison with the case without tunnel throttling.

     

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