Automatic collision avoidance using model-predictive online optimization

In many traffic emergency situations a collision cannot be prevented by braking alone. Therefore, we propose an obstacle avoidance algorithm that simultaneously optimizes steering and braking. As an emergency scenario approaches the driving limits, a strong nonlinear constraint between braking and cornering develops, suggesting the formulation of a nonlinear constrained online optimization. On this account the proposed algorithm embarks on the nonlinear model-predictive control (NMPC) paradigm, which is capable of solving the optimization problem online. The performance of the algorithm is demonstrated in a simulated pedestrian collision avoidance scenario.