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From Openstreetmap and Cell Phone Data to Road Network Simulation Models

机译:从Openstreetmap和手机数据到道路网络仿真模型

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In the field of supply chain simulation, transport relations are often modeled as transport times using distributions. Considering long-distance transport relations, this is usually a suitable approach. But, for short-distance transports within large cities, delays depend on specific roads and the time of day. Some simulation tools offer geographical data for modeling actual roads. However, in order to model time-dependent transport times, additional data are needed. In this paper, we present an approach to tackle this problem. Road networks are derived from OpenStreetMap data (including traffic signals). In order to obtain the average speed of vehicles on an hourly basis, we conduct pre-simulation runs modeling the entire inner-city traffic. The respective vehicle rides are derived from trajectory data of cell phone users, where the assignment of users to cell phone tower sections is given for each hour of the day. First results for the city of Winnipeg are presented.
机译:在供应链模拟领域,运输关系通常使用分布建模为运输时间。考虑到长距离运输关系,这通常是一种合适的方法。但是,对于大城市内的短途运输,延误取决于特定的道路和一天中的时间。一些模拟工具提供了用于对实际道路进行建模的地理数据。但是,为了对时间相关的运输时间进行建模,需要附加数据。在本文中,我们提出一种解决此问题的方法。道路网络从OpenStreetMap数据(包括交通信号灯)派生而来。为了获得每小时的平均车辆速度,我们进行了模拟整个城市内部交通的模拟运行。相应的乘车行程是从手机用户的轨迹数据中得出的,其中在一天中的每个小时都将用户分配到手机塔段。介绍了温尼伯市的初步结果。

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