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首页> 外文会议>International conference on very large data bases >Path Cost Distribution Estimation Using Trajectory Data
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Path Cost Distribution Estimation Using Trajectory Data

机译：使用轨迹数据路径成本分布估计

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With the growing volumes of vehicle trajectory data, it becomes increasingly possible to capture time-varying and uncertain travel costs in a road network, including travel time and fuel consumption. The current paradigm represents a road network as a weighted graph; it blasts trajectories into small fragments that fit the underlying edges to assign weights to edges; and it then applies a routing algorithm to the resulting graph. We propose a new paradigm, the hybrid graph, that targets more accurate and more efficient path cost distribution estimation. The new paradigm avoids blasting trajectories into small fragments and instead assigns weights to paths rather than simply to the edges. We show how to compute path weights using trajectory data while taking into account the travel cost dependencies among the edges in the paths. Given a departure time and a query path, we show how to select an optimal set of weights with associated paths that cover the query path and such that the weights enable the most accurate joint cost distribution estimation for the query path. The cost distribution of the query path is then computed accurately using the joint distribution. Finally, we show how the resulting method for computing cost distributions of paths can be integrated into existing routing algorithms. Empirical studies with substantial trajectory data from two different cities offer insight into the design properties of the proposed method and confirm that the method is effective in real-world settings.
机译：随着越来越多的车辆轨迹数据，越来越多的是在道路网络中捕获时变不确定的旅行成本，包括旅行时间和燃料消耗。当前的范式表示作为加权图的道路网络;它将轨迹爆炸到符合底层边缘的小片段中，以将权重分配给边缘;然后它将路由算法应用于结果图。我们提出了一种新的范例，混合图，其瞄准更准确和更有效的路径成本分布估计。新的范式避免爆破轨迹进入小碎片，而是将权重分配给路径而不是简单地到边缘。我们展示了如何使用轨迹数据计算路径权重，同时考虑到路径中的边缘之间的旅行成本依赖性。鉴于出发时间和查询路径，我们展示了如何选择具有覆盖查询路径的关联路径的最佳权重集，使得权重使得查询路径最准确的联合成本分布估计。然后使用联合分布准确地计算查询路径的成本分布。最后，我们展示了如何集成到现有路径算法中的计算成本分布的所得方法。具有两种不同城市的大量轨迹数据的经验研究提供了深入了解所提出的方法的设计属性，并确认该方法在现实世界中有效。

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