Data Allocation and Application for Time-dependent Delivery in Urban Areas

In this paper, we discuss the planning and the realization of last-mile delivery in urban areas. Two main prerequisites are identified in order to increase service quality in attended home delivery. First, empirical traffic data has to be collected and analyzed, and second, this raw data has to be converted into time-dependent data sets for route planning. Thus, an optimization framework is designed, integrating telematics based data collection by Floating Car Data (FCD), data allocation by Data Mining and the modelling of the time-dependent road network typology. The data sets provided are utilized in time-dependent vehicle routing heuristics, considering customer time slots. We compare the data sets regarding usefulness for time-dependent delivery in terms of a real data example in city logistics. The resulting itineraries are expected to meet the customers’ requirements regarding reliability and service quality of deliveries, keeping logistics service costs at a minimum.