AEB algorithm failure scene searching method based on particle swarm optimization

The invention discloses an AEB algorithm failure scene searching method based on a particle swarm algorithm, and belongs to the technical field of vehicle systems. The searching method comprises the following steps of: S10, initializing a particle swarm, and setting the maximum number of iterations, the particle number of the particle swarm, a particle position range and a particle speed range; S20, taking vehicle data and obstacle data corresponding to all the particles as parameters to generate a simulation test scene; S30, performing a simulation test on the AEB algorithm by using the simulation test scene to obtain the fitness of the corresponding particles; S40, migrating the positions of the corresponding particles according to the fitness and a preset rule, resetting the positions and the speeds of the particles, completing one iteration, repeating the steps S20-S30, and stopping iteration until the number of iterations is equal to the maximum number of iterations; and S50, determining all the simulati