Data are increasingly available that enable detailed capture of travel costs associated with the movements of vehicles in road networks, notably travel time, and greenhouse gas emissions. In addition to varying across time, such costs are inherently uncertain, due to varying traffic volumes, weather conditions, different driving styles among drivers, etc. In this setting, we address the problem of enabling fast route planning with time-varying, uncertain edge weights. We initially present a practical approach to transforming GPS trajectories into time-varying, uncertain edge weights that guarantee the first-in-first-out property. Next, we propose time-dependent uncertain contraction hierarchies (TUCHs), a generic speed-up technique that supports a wide variety of stochastic route planning functionality in the paper’s setting. In particular, we propose query processing methods based on TUCH for two representative types of stochastic routing: non-dominated routing and probabilistic budget routing. Experimental studies with a substantial GPS data set offer insight into the design properties of the paper’s proposals and suggest that they are capable of enabling efficient stochastic routing.

中文翻译：

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时变不确定性下的快速随机路由

越来越多的数据可用于详细捕获与道路网络中车辆的行驶有关的旅行成本，尤其是旅行时间和温室气体排放量。除了随时间变化之外，由于交通量，天气条件变化，驾驶员之间的驾驶方式不同等原因，此类成本也固有地不确定，在这种情况下，我们解决的问题是能够实现时变，不确定的边缘的快速路线规划重量。我们最初提出了一种实用的方法来将GPS轨迹转换为随时间变化的不确定边缘权重，以确保先进先出的特性。接下来，我们提出时间相关的不确定收缩层次结构（TUCH），这是一种通用的加速技术，可在本文的设置中支持多种随机路线规划功能。特别是，我们提出了基于TUCH的两种代表性的随机路由查询处理方法：非主导路由和概率预算路由。利用大量GPS数据集进行的实验研究可深入了解本文建议的设计属性，并表明它们能够实现有效的随机路由。