Department of Rail Transit, Hebei Jiaotong Vocational and Technical College, Shijiazhuang, Hebei, China.
PLoS One. 2024 Oct 7;19(10):e0311538. doi: 10.1371/journal.pone.0311538. eCollection 2024.
Studies of macroscopic speed modeling of bidirectional pedestrian cross-flows have relied heavily on scenario experiments, but the data itself may be deficient because large-scale scenario experiments are not easy to organize and subjects may not be walking under normal conditions. In order to explore the possibility of using microscopic pedestrian flow simulations for macroscopic speed modeling of pedestrian flows, a series of two-way pedestrian cross-flow simulation experiments were designed. Bidirectional pedestrian flows are defined as Peds1 and Peds2. The crossing angle and pedestrian flow rate are used as variables, and a bidirectional pedestrian flows simulation is designed as an orthogonal experiment. The crossing angles range from 15 to 165 degrees, and bidirectional pedestrian flow rate range from 1 ped/s to 8 ped/s. A series of simulations are built and performed on the GIS agent-based modeling architecture (GAMA) platform. By analyzing the flow data of bidirectional flows in the crossing area, it is found that when the Peds1 density falls below a threshold, Peds1 speed is determined by pedestrians themselves and mainly remains in a free flow state; otherwise, the Peds1 speed decreases with density. The clear effects such as Peds2 density on the Peds1 speed cannot be determined. A piecewise function combined with a linear function and an exponential function is constructed as the Peds1 speed model considering the influence of the crossing angle. The calibration results show that the piecewise function should be better than the non-piecewise function. Compared to the results of established studies, the results in this paper have some differences. Therefore, the simulation method cannot completely replace the scene experiments. However, this approach can provide suggestions for subsequent refinement of the experimental program, as well as a feasible direction for the construction of a speed relationship for bidirectional pedestrian flows.
双向行人流宏观速度建模的研究主要依赖于场景实验，但数据本身可能存在缺陷，因为大规模场景实验不易组织，且实验对象可能无法在正常条件下行走。为了探索使用微观行人流模拟进行行人流宏观速度建模的可能性，设计了一系列双向行人流交叉模拟实验。将双向行人流定义为 Peds1 和 Peds2。以交叉角度和行人流率作为变量，设计双向行人流模拟作为正交实验。交叉角度范围为 15 度至 165 度，双向行人流率范围为 1 人/秒至 8 人/秒。在 GIS 基于代理的建模架构 (GAMA) 平台上构建并执行了一系列模拟。通过分析交叉区域双向流的流量数据，发现当 Peds1 密度低于某个阈值时，Peds1 速度由行人自身决定，主要保持在自由流状态；否则，Peds1 速度随密度降低而降低。无法确定 Peds2 密度对 Peds1 速度的明确影响。构建了一个分段函数，结合线性函数和指数函数，作为考虑交叉角度影响的 Peds1 速度模型。校准结果表明，分段函数应该优于非分段函数。与已建立的研究结果相比，本文的结果存在一些差异。因此，模拟方法不能完全替代场景实验。然而，这种方法可以为后续实验方案的改进提供建议，并为双向行人流速度关系的构建提供可行的方向。
