A skidding prediction model and speed–acceleration feasible domain for vehicles on icy curved slopes

On icy curved slopes of mountainous highways or urban interchange ramps, drivers often drive at low speeds to prevent vehicle skidding. However, contrary to drivers’ intuitive judgment of the skidding direction, vehicles frequently skid toward the inside of the curve and struggle to stop, increasing collision risk. To investigate this phenomenon, this study integrates road geometric characteristics and vehicle mechanical analysis to develop a prediction model for skidding on icy curved slopes. The model reveals the mechanisms of inward skidding and ineffective braking at low speeds under low-friction conditions. Speed–acceleration feasible domain (SAFD) is proposed based on the coupling of longitudinal and lateral forces at the friction limit, accounting for both longitudinal and cross slopes. The SAFD provides explicit constraint boundaries for vehicle speed and acceleration, enabling the identification of high-risk operating conditions and supporting the optimization of speed and traction/braking torque control for autonomous vehicles. The study further proposes that vehicles can reduce lateral friction demand and increase safety margins by maintaining speeds near the lateral frictionless critical speed, lowering lateral skidding risk. Finally, the model is validated through vehicle dynamics simulations. Findings can serve as a reference for the optimization of autonomous vehicle control under dynamic conditions and the improvement of traffic safety in icy and snowy regions.