Trajectory User Linking in C-ITS Data Analysis

Vehicles in an Intelligent Transport Network exchange a lot of messages. Every message sent is generated with an identifier of the transmitting vehicle. To respect the user privacy, an identifier is kept only over a specified time interval. The need that arises is, given that multiple identifiers are assigned to a vehicle, are we able to group the identifiers and detect those which belong to the same vehicle? We solved this Trajectory-User Linking problem by chaining anonymous trajectories to potential vehicles by considering similarity in movement patterns. Our method managed to link trajectory segments to their common vehicles which we validated through map matching of the trajectories using QGIS.