城市轨道交通网络客流瓶颈与状态演变特征分析

Analysis on Passenger Flow Bottlenecks and State Evolution Characteristics of Urban Rail Transit Networks

识别城市轨道交通网络客流瓶颈对保障运营安全至关重要。考虑网络客流时空动态变化特性,分别从能力和服务角度构建城市轨道交通网络动态瓶颈车站和区间识别模型,识别网络中负荷较高和服务水平较低的车站和区间。在空间Moran’s I指数基础上引入时间维度,以区间满载率为时空属性值构建城市轨道交通网络客流时空自相关分析模型,通过全局和局部时空Moran’s I指数和Moran散点图分析客流时空关联和聚类特性。以国内某市轨道交通网络早高峰时段的客流数据为例,对网络中车站和区间的能力和服务瓶颈点进行识别,并对区间满载率的时空演变规律进行了分析。结果表明,早高峰时段瓶颈车站主要集中于换乘站,瓶颈区间主要分布在环线和2号线,网络区间满载率表现出显著的时空正相关特性。

Identifying passenger flow bottlenecks of urban rail transit networks is essential to ensure the operation safety. Considering the spatiotemporal dynamic characteristics of network passenger flow, a dynamic bottleneck identification model for stations and sections was constructed from the perspective of capacity and service to identify stations and sections with a high load and a low service level in a network. Taking the section load factor as the spatiotemporal attribute, this study introduced the time dimension on the basis of the spatial Moran’s I to construct the spatiotemporal autocorrelation analysis model of passenger flow for urban rail transit networks. The global and local spatiotemporal Moran’s I and Moran scatter plots were used to analyze the spatiotemporal correlation and clustering characteristics of passenger flow. For the passenger flow data of a domestic urban rail transit network in the morning rush hours, the capacity and service bottleneck points of stations and sections in the network were identified, and the spatiotemporal evolution characteristics of the section load factor were analyzed. The results indicate that in the morning rush hours, the bottleneck stations are mainly the transfer stations, and the bottleneck sections are mainly distributed on the circle line and Line 2. The section load factor of the network shows a significant spatiotemporal positive correlation.