Turbulence reflects individual changes in speed, headways, and lanes in the traffic stream. Turbulence in traffic is a commonly known phenomenon, but the exact characteristics of this phenomenon are not yet clear. (2) For weave bottlenecks, capacity-drop is governed by two counteracting effects of LCs: persisting voids and utilization of vacancies created by diverging vehicles (3) the more balanced the merging and diverging flows, the lower the capacity-drop and (4) capacity-drop is minimum if merging LCs occur downstream of diverging LCs, and maximum in the opposite alignment. We found that (1) LCs closer to the downstream end of bottlenecks are more likely to create persisting voids and contribute to capacity-drop. This study focuses on the impact of LC vehicles’ bounded acceleration on “void” (wasted space) creation in traffic streams when they insert/desert at a lower speed, and interactions among multiple voids. A hybrid approach is used to study the problem: analytical approach to capture the behavior of merging and diverging LCs and numerical simulations to quantify capacity-drop considering various geometric configurations of extended bottlenecks. This paper investigates the mechanisms of how spatially distributed lane changes (LCs) interact and contribute to “capacity-drop” at three types of extended bottlenecks: merge, diverge, and weave. It was found that for N wl = 2 the accepted regression model containing three new variables has an R ² value equal to 0.95, and for N wl = 3 two of the three variables were used for the model produced with an R ² value equal to 0.7. In these scenarios, two geometric parameters (N wl and L wmax ) and four traffic parameters were considered variable.
#Inklet weaving length plus#
There were 184 simulated scenarios in Aimsun using data collected from the three weaving segments in Tehran plus simulation. The simulation was therefore used on the basis of different traffic and geometric parameters, and the effects of these parameters on L wmax were carefully observed. Calibration of field data was performed using GEH values of freeways and ramps for simulation and field traffic volumes. In this study, three separate weaving segments in Tehran, Iran were used and their data were collected to further analyze the influence of the traffic parameters. However, certain cases can be found in which traffic conditions are different but N wl and VR values are equal.
#Inklet weaving length manual#
Based on an equation in the Highway Capacity Manual (HCM 2016), only two variables VR (volume ratio) and N wl (number of weaving lanes) influence this length. One of their key features is their maximum length (L wmax ), which determines the performance of the facility as a weaving or separate merge and diverge segments.
#Inklet weaving length portable#
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