Modelling and improving approach for carrying capacity in multi-modal super network by considering travel time - Xiangyue Huang (PLoS ONE, 2025)
For the sake of achieving the mensuration of network carrying capacity under regular even congested road conditions with crowded vehicles, passengers or cyclists in a median-scale network, this study examined the ideal travel time of a passenger or cyclist in the hybrid-congested roads (congested and non-congested road accounts for half), being the initial accumulated values for the independent variable in Aggregated Functional Equation. Besides, the various road section’s capacity was examined, together with the total travel time accumulated accordingly, and the capacity limitation took effect to alleviate the heavy load of vehicles on partial road sections. This study proposes a multi-objective bi-level planning model on the basis of the original capacity constraint model to address the potential congested problem, the model optimizes three aspects in the schematic diagram: carrying capacity, average travel time, and expansion cost. This experiment attains 9 effective hyper-paths with traffic flow and travel impedance attributes attached to each hyper-path. The scatter chart results show that the plural modulus of carrying capacity decreases with travel time’s descends; when the road saturation increases from 0.7 to 0.9, the plural modulus of carrying capacity declines by 27.1%. Meanwhile, raising the upper limit of expansion would slightly lift the carrying capacity in the proportion of 15.7%. This research could provide a reference for the majorization of multi-modal cyber flow distribution and also has indirect significance for route planning to a certain extent.