Road roughness is more than a comfort issue – it affects safety, vehicle wear, fuel consumption, and the lifespan of road surfaces. Traditionally, measuring it accurately requires expensive laser-scanning vehicles, which limits large-scale monitoring. But a new study, “Road Roughness Estimation via Fusion of Standard Onboard Automotive Sensors,” offers a cost-effective alternative by harnessing technology that’s already built into modern cars.
The paper was authored by Martin Agebjär and Johan Wahlström from NIRA Dynamics, together with Gustav Zetterqvist, Fredrik Gustafsson, and Gustaf Hendeby from Linköping University. The work builds on Martin Agebjär’s master’s thesis at NIRA Dynamics, in close collaboration with the academic team. Fredrik Gustafsson, co-founder of NIRA Dynamics, and his colleagues contributed expertise in sensor fusion, vehicle dynamics, and advanced estimation methods.
The research introduces a Kalman filter-based method for estimating the International Roughness Index (IRI) — the standard measure of road unevenness — using data from a vehicle’s inertial measurement unit (IMU) and speed sensors. By fusing these inputs, the method reconstructs the road’s longitudinal profile and calculates the IRI, eliminating the need for costly dedicated measurement equipment.
A notable aspect of the study is that it examines both vertical and lateral vehicle vibrations. While vertical vibrations are a proven input for roughness estimation, lateral vibrations — already widely available in vehicle stability control systems — could enable broader, easier deployment of the technology.
Testing was conducted on 230 kilometers of roads in and around Linköping, Sweden, covering highways, urban streets, and rural roads. Using vertical vibrations, the method achieved an impressive accuracy of 1–10% compared to high-precision laser measurements. Lateral-only measurements proved less accurate, especially for rougher roads, but still demonstrated potential for certain applications.
By leveraging sensors already present in millions of vehicles, the method could pave the way for real-time, large-scale road condition monitoring — helping road authorities improve maintenance planning, extend pavement life, and enhance safety.
Download the paper here: Road Roughness Estimation via Fusion of Standard Onboard Automotive Sensors