A matching algorithm to study the evolution of logistics facilities extracted from GPS traces

Abstract

The ubiquity of anonymous GPS data has opened the door to a promising data source in the field of city logistics modelling. From this data the locations of logistics facilities can be extracted and their evolution studied over time. The minimum edge cover problem, weighted by the Hausdorff distance, is used as a basis for a matching algorithm to study the location of facilities across longitudinal datasets. The efficacy and validity of the algorithm is assessed through the visual inspection of results in three urban areas across five time instances. Prevalent errors are unpacked and algorithm modifications suggested. This paper makes a methodological contribution to the handling of GPS data for the purpose of city logistics modelling.