<div>A precise knowledge of the road profile ahead of the vehicle is required to
successfully engage a proactive suspension control system. If this profile
information is generated by preceding vehicles and stored on a server, the
challenge that arises is to accurately determine one’s own position on the
server profile. This article presents a localization method based on a particle
filter that uses the profile observed by the vehicle to generate an estimated
longitudinal position relative to the reference profile on the server. We tested
the proposed algorithm on a quarter vehicle test rig using real sensor data and
different road profiles originating from various types of roads. In these tests,
a mean absolute position error of around 1 cm could be achieved. In addition,
the algorithm proved to be robust against local disturbances, added noise, and
inaccurate vehicle speed measurements. We also compared the particle filter with
a correlation-based method and found it to be advantageous. Even though the
intended application lies in the context of proactive suspension control, other
use cases with precise localization requirements such as self-driving cars might
also benefit from our method.</div>