Understanding urban traffic-flow characteristics: a rethinking of betweenness centrality
Understanding urban traffic-flow characteristics: a rethinking of betweenness centrality
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了解城市交通流特征：重新思考介数中心性
DOI：
10.1068/b38141
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发表时间：
2013-01-01
期刊：
影响因子：
--
通讯作者：
Liu, Yu
中科院分区：
文献类型：
--
作者：
Gao, Song;Wang, Yaoli;Liu, Yu
在这项研究中，我们估计城市交通流量使用GPS启用的出租车轨迹数据在青岛，中国，并检查的介数中心的街道网络预测交通流量的能力。结果表明，介数中心性不是一个很好的预测变量的城市交通流，这已经在理论上指出，在现有的文献。通过对介数中心性作为预测因子的批判，我们进一步分析了介数中心性的特征，并指出了介数中心性度量与实际流量之间的“差距”。而不是只考虑一个街道网络的拓扑特性，我们考虑到两个方面，人类活动的空间异质性和距离衰减规律，来解释所观察到的交通流分布。利用移动的手机Erlang值估计人类活动的空间分布，并采用幂律距离衰减。我们运行蒙特卡罗模拟生成行程和预测交通流量分布，并使用加权相关系数来衡量观测数据和模拟数据之间的拟合度。当指数为2.0时，相关系数达到最大值（0.623），表明该模型结合了地理约束和人类移动模式，可以很好地解释城市交通流。
In this study we estimate urban traffic flow using GPS-enabled taxi trajectory data in Qingdao, China, and examine the capability of the betweenness centrality of the street network to predict traffic flow. The results show that betweenness centrality is not a good predictor variable for urban traffic flow, which has, theoretically, been pointed out in existing literature. With a critique of the betweenness centrality as a predictor, we further analyze the characteristics of betweenness centrality and point out the 'gap' between this centrality measure and actual flow. Rather than considering only the topological properties of a street network, we take into account two aspects, the spatial heterogeneity of human activities and the distance-decay law, to explain the observed traffic-flow distribution. The spatial distribution of human activities is estimated using mobile phone Erlang values, and the power law distance decay is adopted. We run Monte Carlo simulations to generate trips and predict traffic-flow distributions, and use a weighted correlation coefficient to measure the goodness of fit between the observed and the simulated data. The correlation coefficient achieves the maximum (0.623) when the exponent equals 2.0, indicating that the proposed model, which incorporates geographical constraints and human mobility patterns, can interpret urban traffic flow well.