构建了电动小车自动变道环境感知系统.介绍了自动变道实车平台和转向系统结构改造方案，并设计了低成本、可靠的环境感知方案.对于同车道前车，采用加权融合算法对 24 Ghz毫米波雷达和前视摄像头进行数据融合，通过实车采集，拟合了两种传感器在不同距离上的理想权重曲线，提高了环境感知的精度和稳定性.最后通过避障变道工况的试验，验证了自动变道环境感知系统的适用性.
An automatic lane change (ALC) environment perception system of an electric vehicle is established. Besides, the ALC real vehicle platform and steering system structural transformation scheme are introduced. In addition, a low-cost and reliable environment perception scheme is designed. Moreover, for the front vehicle of the same lane, the data of a 24 Ghz millimeter wave radar and a forwardlooking camera are fused through weighted fusion algorithm. Furthermore, through real vehicle acquisition, the ideal weight curves of the two sensors at different distances are fitted, which improves the accuracy and stability of the environment perception. Finally, the applicability of the ALC environment perception system of the electric vehicle is verified in an obstacle avoidance lane change experiment.