MapCorrect: Automatic correction and validation of road maps using public sensing

With the increasing proliferation of small and cheap GPS receivers, a new way of generating road maps could be witnessed over the last few years. Participatory mapping approaches like OpenStreetMap introduced a way to generate road maps collaboratively from scratch. Moreover, automatic mapping algorithms were proposed, which automatically infer road maps from a set of given GPS traces. Nevertheless, one of the main problems of these maps is their unknown quality in terms of accuracy, which makes them unreliable and, therefore, not applicable for the use in critical scenarios. To address this issue, we propose MapCorrect: An automatic map correction and validation system. MapCorrect automatically collects GPS traces from people's mobile devices to correct a given road map and validate it by identifying those parts of the map that are accurately mapped with respect to some user provided quality requirements. Since fixing a GPS position is a battery draining operation, the collection of GPS data raises concerns about the energy consumption of the participating mobile devices. We tackle this issue by introducing an optimized sensing mechanism that gives the mobile devices notifications indicating those parts of the map that are considered as sufficiently mapped and, therefore, require no further GPS data for their validation. Furthermore, we show by simulation that using this approach up to 50% of the mobile phones' energy can be saved while not impairing the effectiveness of the map correction and validation process at all.