In city logistics, service providers have to consider dynamics within logistics processes in order to
achieve higher schedule reliability and delivery flexibility. To this end, city logistics routing demands for
time-dependent travel time estimates and time-dependent optimization models. We consider the process
of allocation and application of empirical traffic data for time-dependent vehicle routing in city logistics
with respect to its usage. Telematics based traffic data collection and the conversion from raw empirical
traffic data into information models are discussed. A city logistics scenario points out the applicability of
the information models provided, which are based on huge amounts of real traffic data (FCD). Thus, the
benefits of time-dependent planning in contrast to common static planning methods can be demonstrated.
