Real-time risk assessment framework for tractors: part 2

— Risk point estimation using discriminant analysis based on behaviour —

Abstract

We present a behaviour-based, real-time estimator of tractor rollover risk suitable for embedded use. A four-degree-of-freedom vehicle model generated labelled scenarios across speeds (0.5–4.0 m/s), slope angles (0–20 °), and ISO 8608 roughness classes. Two closed-form discriminants for pitch and roll require only three onboard signals—vehicle speed, vertical acceleration, and a 0.3 s double-integrated angular-acceleration angle. On simulated runs, the pitch discriminant achieved 96.4 % sensitivity and specificity; the roll discriminant reached 100 % and 99.5 %, with mean lead times of 0.88 s and 0.53 s before rollover onset. Discriminant scores are mapped to a unified Risk Point scale, enabling interpretable warnings for proactive operator assistance during field and road operation.