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Towards Data-Driven Multilinear Metro Maps

机译:走向数据驱动的多线性地铁地图

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摘要

Traditionally, most schematic metro maps as well as metro map layout algorithms adhere to an octolinear layout style with all paths composed of horizontal, vertical, and 45°-diagonal edges. Despite growing interest in more general multilinear metro maps, generic algorithms to draw metro maps based on a system of k ≥ 2 not necessarily equidistant slopes have not been investigated thoroughly. We present and implement an adaptation of the octolinear mixed-integer linear programming approach of Noellenburg and Wolff (2011) that can draw metro maps schematized to any set C of arbitrary orientations. We further present a data-driven approach to determine a suitable set C by either detecting the best rotation of an equidistant orientation system or by clustering the input edge orientations using a k-means algorithm. We demonstrate the new possibilities of our method in a real-world case study.
机译:传统上,大多数示意图地铁地图以及地铁地图布局算法都遵循八角形布局样式,其所有路径均由水平,垂直和45°对角线边缘组成。尽管人们对更通用的多线性地铁地图越来越感兴趣,但基于k≥2(不一定等距斜率)的系统绘制地铁地图的通用算法尚未得到彻底研究。我们提出并实施了Noellenburg和Wolff(2011)的八角形混合整数线性规划方法的改编,该方法可以绘制图示化为任意方向的任意C集的地铁地图。我们进一步提出了一种数据驱动的方法,通过检测等距定向系统的最佳旋转或通过使用k-means算法对输入边缘定向进行聚类来确定合适的集合C。我们在一个实际案例研究中证明了我们方法的新可能性。

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