Abstract
Public transportation navigation systems require reliable information on motion states of passengers. This information cannot be delivered via GNSS, however acceleration data gathered by smartphone sensors can be a supporting source of information for navigation processes. This article describes all development steps from raw data to motion states and first results of signal analyses for designing a motion state classifier. Used sources are acceleration measurements of the Dresden measurement tram with sensors in the vehicle body and measurements of Android smartphones. Both sources show similarities useful for motion state classification.