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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.