matlab 自动驾驶仿真案例 代码

以下是一个基于 MATLAB 的自动驾驶仿真案例代码：

% 定义车辆控制器
function [throttle, brake, steering] = VehicleController(vehicleState, targetState)
% 控制器参数
Kp_speed = 0.3;
Ki_speed = 0.05;
Kp_heading = 0.6;
Ki_heading = 0.1;
% 计算车辆速度误差
speed_error = targetState.velocity - vehicleState.velocity;
% 计算车辆速度控制量
throttle = Kp_speed * speed_error + Ki_speed * sum(speed_error);
% 计算车辆转向角度误差
heading_error = targetState.heading - vehicleState.heading;
% 将转向角度误差限制在 -pi 和 pi 之间
heading_error = mod(heading_error + pi, 2*pi) - pi;
% 计算车辆转向控制量
steering = Kp_heading * heading_error + Ki_heading * sum(heading_error);
% 将转向控制量限制在 -1 和 1 之间
steering = max(-1, min(steering, 1));
% 如果车辆速度小于 0，应该刹车
if vehicleState.velocity < 0
    brake = abs(throttle);
    throttle = 0;
else
    brake = 0;
end
end

% 定义车辆动力学模型
function vehicleState = VehicleModel(vehicleState, throttle, brake, steering, dt)
% 车辆参数
mass = 1500; % 质量 kg
inertia = 3000; % 转动惯量 kg*m^2
Cf = 100000; % 前轮侧向刚度 N/rad
Cr = 100000; % 后轮侧向刚度 N/rad
lf = 1.5; % 前轴到质心的距离 m
lr = 1.5; % 后轴到质心的距离 m
% 计算车辆速度
vx = vehicleState.velocity;
% 计算车辆前进方向和侧向方向速度
vy = vx * tan(steering);
% 计算车辆加速度
Ff = Cf * steering;
Fr = Cr * atan2(vy, vx);
Ft = (throttle - brake * sign(vx)) * 5000;
a = (Ff + Fr + Ft) / mass;
% 计算车辆角加速度
Mz = lf * Cf * steering - lr * Cr * atan2(vy, vx);
alpha = Mz / inertia;
% 更新车辆状态
vehicleState.x = vehicleState.x + vx * cos(vehicleState.heading) * dt;
vehicleState.y = vehicleState.y + vx * sin(vehicleState.heading) * dt;
vehicleState.heading = vehicleState.heading + vehicleState.angularVelocity * dt;
vehicleState.angularVelocity = vehicleState.angularVelocity + alpha * dt;
vehicleState.velocity = vehicleState.velocity + a * dt;
end

% 定义目标点生成器
function targetState = TargetGenerator(t)
% 生成一个周期为 10 秒的前进方向速度为 10 m/s 的目标点
targetState.x = 1000 * (1 - cos(t/10*2*pi));
targetState.y = 1000 * sin(t/10*2*pi);
targetState.heading = atan2(diff(targetState.y), diff(targetState.x));
targetState.velocity = 10;
end

% 初始化车辆状态
vehicleState.x = 0;
vehicleState.y = 0;
vehicleState.heading = 0;
vehicleState.velocity = 0;
vehicleState.angularVelocity = 0;

% 模拟车辆行驶过程
t = 0;
dt = 0.1;
while t < 100
    % 生成目标点
    targetState = TargetGenerator(t);
    % 执行车辆控制器
    [throttle, brake, steering] = VehicleController(vehicleState, targetState);
    % 更新车辆状态
    vehicleState = VehicleModel(vehicleState, throttle, brake, steering, dt);
    % 绘制车辆和目标点
    plot(vehicleState.x, vehicleState.y, 'ro');
    hold on;
    plot(targetState.x, targetState.y, 'r*');
    hold off;
    axis equal;
    axis([-2000 2000 -2000 2000]);
    grid on;
    drawnow;
    % 更新时间
    t = t + dt;
end

这个代码实现了一个简单的自动驾驶示例，包括车辆控制器、车辆动力学模型和目标点生成器。在模拟过程中，车辆根据当前状态和目标点生成器生成的目标点计算出控制量，通过车辆动力学模型模拟车辆行驶过程，并将车辆和目标点绘制在图像上，以便观察仿真结果。