How Does Travel Demand Follow the Change in Infrastructure? Multiple-Year Eigenvector Centrality Analysis
How Does Travel Demand Follow the Change in Infrastructure? Multiple-Year Eigenvector Centrality Analysis
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DOI：
10.3390/su132313366
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发表时间：
2021-12
期刊：
影响因子：
3.9
通讯作者：
Hiroe Ando;F. Kurauchi
中科院分区：
文献类型：
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作者：
Hiroe Ando;F. Kurauchi
道路网是城市物理结构中最持久的要素之一，应考虑其长期影响，以便有效和高效地改善道路网。因此，重要的是要及时了解这条道路在建设后将如何使用。然而，我们对现实情况下出行需求和供给变化过程中的模式和时滞了解不多。为了探索这种变化，本研究建议使用特征向量中心性(EC)度量来评估网络，该度量可以评估网络中节点的重要性。我们认为，基于图论的基于拓扑性质的分析适合于验证路网的演化。这项研究分析了一个实际城市20年来的长期变化，以了解道路网络改善的影响。EC分析利用调查数据获得的交通指数的权重来评估道路服务在供给侧的连通性，以及在需求侧的交通集中度。
The road network is one of the most permanent elements of the physical structure of cities, and the long-term impacts should be considered for effective and efficient road network improvement. It is therefore important to catch up on how the road will be used after construction. However, we do not have much knowledge on the pattern and time lag in the change process of travel demand and supply in the real situation. To explore such changes, this study proposes to evaluate a network with eigenvector centrality (EC) measures that can evaluate the importance of nodes in a network. We believe the analysis based on topological properties by the graph theory is suitable to verify the evolution of road networks. This study analysed long-term changes over 20 years in an actual city to understand the impact of road network improvements. The EC analysis with the weights of traffic indices obtained from survey data evaluates the connectivity of road services on the supply side, and traffic concentration on the demand side.