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We present a particle-based framework for estimating the position of avehicle using map information and measurements of speed. Two measurementfunctions are considered. The first is based on the assumption that the lateralforce on the vehicle does not exceed critical limits derived from physicalconstraints. The second is based on the assumption that the driver approaches atarget speed derived from the speed limits along the upcoming trajectory.Performance evaluations of the proposed method indicate that end destinationsoften can be estimated with an accuracy in the order of $100\,[m]$. Theseresults expose the sensitivity and commercial value of data collected in manyof today's insurance telematics programs, and thereby have privacy implicationsfor millions of policyholders. We end by discussing the strengths andweaknesses of different methods for anonymization and privacy preservation intelematics programs.

Map-aided Dead-reckoning --- A Study on Locational Privacy in Insurance Telematics