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 simulation test scenes corresponding to the fitness smaller than a preset value as failure scenes. According to the method, the AEB algorithm can be rapidly tested, the failure scene of the AEB algorithm is found out, and then whether the AEB algorithm meets the safety requirement or not is judged.

    本发明公开了一种基于粒子群算法的AEB算法失效场景搜索方法,涉及车辆系统技术领域。搜索方法包括:步骤S10:初始化粒子群,设定最大迭代次数、粒子群的粒子数量、粒子位置范围、粒子速度范围;步骤S20:将所有粒子对应的车辆数据和障碍物数据作为参数生成模拟测试场景;步骤S30:利用模拟测试场景对AEB算法进行仿真试验,得到对应粒子的适应度;步骤S40:根据适应度和预设规则对对应粒子的位置进行迁移,并对粒子的位置和速度进行重置,完成一次迭代,重复步骤S20~S30,直至迭代次数等于到最大迭代次数停止迭代;步骤S50:将所有适应度小于预设值对应的模拟测试场景认定为失效场景。本发明能够快速地对AEB算法进行测试,找出AEB算法的失效场景,进而判断AEB算法是否符合安全要求。


    Access

    Download


    Export, share and cite



    Title :

    AEB algorithm failure scene searching method based on particle swarm optimization


    Additional title:

    一种基于粒子群算法的AEB算法失效场景搜索方法


    Contributors:
    CAI JINKANG (author) / DENG WEIWEN (author) / DING JUAN (author)

    Publication date :

    2022-01-28


    Type of media :

    Patent


    Type of material :

    Electronic Resource


    Language :

    Chinese


    Classification :

    IPC:    G06F ELECTRIC DIGITAL DATA PROCESSING , Elektrische digitale Datenverarbeitung / B60W CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION , Gemeinsame Steuerung oder Regelung von Fahrzeug-Unteraggregaten verschiedenen Typs oder verschiedener Funktion / G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen



    Particle Swarm Optimization Algorithm

    Chen, G.-c. / Yu, J.-s. | British Library Online Contents | 2005



    Compact Particle Swarm Optimization Algorithm

    Yu, L. / Zheng, Q. / Zhewen, S. | British Library Online Contents | 2006


    Improved particle filter algorithm based on chaos particle swarm optimization

    Wang, Ershen / Pang, Tao / Qu, Pingping et al. | British Library Online Contents | 2016


    Optimized Algorithm for Particle Swarm Optimization

    Fuzhang Zhao | BASE | 2016

    Free access