MPC-based multi-objective collision avoidance optimization algorithm

This work proposes a multi-objective collision avoidance optimization technique based on model predictive control (MPC) to reduce the probability of rear-end collisions during aircraft taxiing and for passenger comfort. Firstly, the longitudinal kinematic model of the airplane is established. Considering the safety of aircraft taxiing and passenger comfort design objective function and constraints. Secondly, the design of variable weight functions using relative velocity and spacing as parameters. Introducing it into the MPC to optimize security weights. The desired acceleration is obtained by solving the variable weight MPC control strategy using the sequential quadratic programming (SQP) algorithm, and analyzing the stability of variable weight MPCs. Lastly, simulation tests are used to confirm that the proposed algorithm can prevent collisions under two common operating situations The experimental results show that the proposed algorithm is useful in achieving the deceleration collision avoidance, and optimized acceleration change amplitude improves passenger comfort.