Fuzzy rules of interval type-2.

In this study, we present an algorithm to estimate the distance between a vehicle and a target object using light from headlights captured by a camera. In situations with limited distance data, we also design a fuzzy controller using the adaptive neuro–fuzzy inference system (ANFIS). To enhance robustness against disturbances, the interval type-2 approach is used. For the distance estimation algorithm, the vehicle is positioned at predefined intervals from the target object, capturing images of the headlights at each point. The region of interest containing the light is extracted from each image and segmented by light intensity. Weighted values are then assigned to each segment based on intensity, producing an image value that correlates with the distance. This image-derived value is then used as distance data for the design of the fuzzy controller. The controller is implemented using the interval type-2 fuzzy logic toolbox in MATLAB/SIMULINK, with vehicle speed and image intensity values as inputs and control torque as the output to adjust vehicle speed. The noise from the vehicle speed sensor is treated as a disturbance, and the performance of the interval type-2 fuzzy controller is evaluated under these disturbance conditions. Additionally, fuzzy controllers are designed for vehicle positions between 41–43 m and 47–49 m, and these controllers are trained using ANFIS to function effectively across the entire 41–49 m range. Simulation results demonstrate that, with the controller integrated into the vehicle system, the vehicle is successfully controlled to reach the target position.

本研究提出一种算法，可利用摄像头采集的前照灯光束，估算车辆与目标物体之间的距离。在距离数据有限的场景下，我们还采用自适应神经模糊推理系统（Adaptive Neuro-Fuzzy Inference System, ANFIS）设计了模糊控制器。为提升抗扰动鲁棒性，本研究引入了区间二型方法（Interval Type-2 Approach）。针对该距离估计算法，我们将车辆置于距目标物体的预设间隔点位，在每个位置采集前照灯的成像画面。从每幅图像中提取包含光束的感兴趣区域（Region of Interest, ROI），并基于光强完成图像分割。随后根据各分割区域的光强赋予加权值，生成与距离存在相关性的图像特征值。该图像衍生特征值随后被用作距离数据，用于模糊控制器的设计。本控制器基于MATLAB/SIMULINK中的区间二型模糊逻辑工具箱实现，以车辆车速与图像光强值作为输入，以控制转矩作为输出，用于调节车辆行驶速度。将车速传感器引入的噪声视作扰动，并在该扰动条件下评估区间二型模糊控制器的性能。此外，我们还针对41~43米与47~49米的车辆间距设计了模糊控制器，并通过ANFIS对这些控制器进行训练，使其可在41~49米的全间距范围内有效运行。仿真结果表明，将该控制器集成至车辆系统后，车辆可被成功控制至目标位置。