出租汽车出行轨迹网络结构复杂性与空间分异特征

Structural complexity and spatial differentiation characteristics of taxi trip trajectory network

基于出租汽车运行GPS轨迹数据,构建了一类城市出行复杂网络;使用有向加权复杂网络测度分析方法,研究了出租汽车出行轨迹网络结构复杂性与空间分异特征;以西安市数据为例,进行了网络指标测算。分析结果表明:出租汽车出行轨迹网络的平均最短路径长度为2.070(边数),聚类系数为0.653,网络密度为0.554,说明了该网络是一类典型复杂网络,具有典型的小世界和集团化特征,且实际平均出行距离符合对数正态分布;网络的节点强度均值为411,最大K-核值为59,网络中强度小于600的节点占77.97%,强度小于300的节点占50.24%,呈现典型的大少小多的空间分布特点;该网络具有显著的空间分异特征,重要小区的出行辐射范围具有全局性特征,总体出行强度空间布局与城市公共交通干线走向一致,呈十字型分布;在整个网络范围内,强中心性交通小区呈现集聚性分布,重要交通枢纽(车站)与商圈等区域节点强度大于2 200;出租汽车上下客区域呈现空间非均衡特征,即在城市重要功能聚集区的上客水平高于下客水平。研究结果反映了出租汽车出行轨迹网络的拓扑结构与空间分异特征间的相互关系,揭示了城市居民活动的空间特征、活动规律及其与城市功能空间布局之间的相互影响作用。

Based on the GPS trajectory data of taxis, a kind of urban trip complex network was constructed. The structural complexity and differentiation characteristics of taxi trip trajectory network were researched by using the directed-weighted complex network measuring method. Based on the taxi trip data of Xi’an, the network indexes were calculated. Analysis result shows that the average shortest path length of taxi trip trajectory network is 2.07（edge number）, the clustering coefficient is 0.653, and the network density is 0.554. So the network is a kind of typical complex network, with typical “small-world” and “collective” characteristic, and the actual average trip distance obeys log-normal distribution. The average value of node strengths for the network is 411, the largest K-nuclear value is 59, and the proportions of nodes with the strengths being less than 600 and 300 are 77.97% and 50.24%, respectively, which shows the typical spatial distribution that is described as “less nodes with greater strengths but more nodes with less strengths”. The network has significant spatial differentiation characteristic, the traveling radiation scopes of important traffic analysis zones（TAZs）have overall characteristic, the whole spatial layout of trip intensities is consistent with public transport arterial lines, and presents a cross type distribution. The high-level centricity TAZs in whole network present agglomeration distribution, and the node strengths of important transport hubs（stations）and CBD areas are more than 2 200. The distributions of pick-up and drop-off areas of taxis are non-equilibrium, and the pick-up level is higher than the drop-off level in the important functional zones of city. Obviously, this research result indicates the interaction relationship between the topology structure and spatial differentiation of taxi trip trajectory network, and reveals urban resident activities’ spatial characteristics, movement rules and the mutual influence of urban functions’ spatial layout and resident activities. 2 tabs, 12 figs, 31 refs.