Visually-Driven Urban Simulation: Exploring Fast and Slow Change in Residential Location
Visually-Driven Urban Simulation: Exploring Fast and Slow Change in Residential Location
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视觉驱动的城市模拟：探索住宅位置的快速和缓慢变化
DOI：
10.1068/a44153
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发表时间：
2013
期刊：
影响因子：
--
通讯作者：
Batty M
中科院分区：
文献类型：
--
作者：
Batty M
正在开发大伦敦地区的大型住宅区模型，其中模型构建过程的所有阶段（从数据输入、分析到校准再到预测）都可以快速执行，并以可视化和即时的方式进行访问。该模型的结构是为了在从就业地点到人口所在地的竞争交通方式之间分配行程。它采用熵最大化框架，该框架已扩展为测量能源的实际组成部分——旅行成本、免费能源和无法使用的能源（熵本身）——这些为根据都会区旅行成本变化来检查未来情景提供了指标。尽管该模型相对静态，但我们根据快速和慢速过程来解释其预测——“快”与交通方式的变化相关，“慢”与位置的变化相关。在使用适当的可视化分析开发和解释模型后，测试了道路旅行成本加倍的场景：这表明模式切换比位置变化要重要得多（位置变化很小）。
A large-scale residential-location model of the Greater London region is being developed in which all stages of the model-building process—from data input, analysis through calibration to prediction—are rapid to execute and accessible in a visual and immediate fashion. The model is structured to distribute trips across competing modes of transport from employment to population locations. It is cast in an entropy-maximising framework which has been extended to measure actual components of energy—travel costs, free energy, and unusable energy (entropy itself)—and these provide indicators for examining future scenarios based on changing the costs of travel in the metro region. Although the model is comparatively static, we interpret its predictions in terms of fast and slow processes—‘fast’ relating to changes in transport modes, and ‘slow’ relating to changes in location. After developing and explaining the model using appropriate visual analytics, a scenario in which road-travel costs double is tested: this shows that mode switching is considerably more significant than shifts in location—which are minimal.