Map-aided dead-reckoning using only measurements of speed
Wahlstrom, J; Skog, I; Rodrigues, JGP; et al.Handel, P; Aguiar, A
Date: 14 January 2017
Journal
IEEE Transactions on Intelligent Vehicles
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Publisher DOI
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 ...
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.
Computer Science
Faculty of Environment, Science and Economy
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