Intelligent correction of telemetric data in public transport systems

A major public transport company, working in an urban environment in Portugal, has adopted a telemetric system for automatic vehicle location (AVL) in order to optimise vehicle use, timetabling and scheduling. The system provides real time location and load of the buses, exchanges voice messages with the driver and proposes preventive maintenance actions on the vehicles. The control centre exchanges messages with all the buses. These messages have two different components: the real-time control component, that is thrown away after use, and the off-line component that has its data stored sequentially on disk, for later analysis. The authors extract relevant information from this bulk of data to provide the bus management expert with a more accurate knowledge of fleet performance, namely operation efficiency, to improve vehicle use and scheduling. Several factors may corrupt the disk data and make it impossible to automatically extract useful information. A pre-processing stage is needed to classify data as consistent or inconsistent. A strategy to implement this preprocessing, based on a virtual bus model, is presented. The virtual bus travels on a bus route and recreates the real bus service. It compares messages which have been received with those that could be expected in the model. The model is extended in this paper, in order to analyse inconsistent data and take automatic correction actions. In less common situations, control is passed to a human operator for him/her to make an appropriate correction