Map-aided dead-reckoning using only measurements of speed

Abstract

We present a particle-based framework for estimating the position of a vehicle using map information and measurements of speed. The filter propagates the particles’ position estimates by means of dead-reckoning, and then updates the particle weights using two measurement functions. The first measurement function is based on the assumption that the lateral force on the vehicle does not exceed critical limits derived from physical constraints. The second is based on the assumption that the driver approaches a target speed derived from the speed limits along the upcoming trajectory. Assuming some prior knowledge of the initial position, performance evaluations of the proposed method indicate that end destinations often can be estimated with an accuracy in the order of 100 [m]. These results expose the sensitivity and commercial value of speed data collected in many of today’s insurance telematics programs, where the data is used to adjust premiums and provide driver feedback. We end by discussing the strengths and weaknesses of different methods for anonymization and privacy preservation in telematics programs.