traffic course (#20)

* traffic course * traffic course * traffic course * traffic course * traffic course * course * course * course * course
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diff --git a/docs/course/microscopic_Intersection_demo.md b/docs/course/microscopic_Intersection_demo.md
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+# 路口微观3D 动画演示运动场景spectator.py
+
+#### **介绍**
+
+此脚本连接到CARLA仿真环境，并定期切换湖工商附近的四个预设路口视角。通过不断改变观众（Spectator）的视角，用户可以观察到不同路口的交通状况。
+
+#### **环境要求**
+
+- Python 3.6 及以上版本
+
+- CARLA 仿真环境
+
+- 安装必要的Python库：
+
+  ```
+  pip install carla
+  ```
+
+#### **运行**
+
+此示例支持设置  **spectator**  视角来观察交通路口运动情形。
+
+以下示例通过预定义 **spectator** 对象视角的位置 **Location** 和旋转角度 **pitch** 来进行视角的更换
+
+```
+client = carla.Client('localhost', 2000)
+client.set_timeout(10)
+world = client.get_world()
+spectator_transform = [
+    carla.Transform(carla.Location(x=-323, y=-15.7, z=108), carla.Rotation(pitch=-90)),
+    carla.Transform(carla.Location(x=-359.6, y=391.3, z=94), carla.Rotation(pitch=-90)),
+    carla.Transform(carla.Location(x=426.2, y=-33.4, z=91.6), carla.Rotation(pitch=-90)),
+    carla.Transform(carla.Location(x=375.1, y=-558.4, z=91.6), carla.Rotation(pitch=-90))
+]
+spectator = world.get_spectator()
+spectator.set_transform(spectator_transform[0])
+```
+
+##### 定期切换视角
+
+脚本将连接到CARLA服务器，并每5秒切换一次预设的观众视角。
+
+```
+start_time = time.time()
+state = 0
+while True:
+    elapsed_time = time.time() - start_time
+    if elapsed_time >= 5:
+        spectator.set_transform(spectator_transform[state])
+        state += 1
+        if state > 3:
+            state = 0
+        start_time = time.time()
+```
+
+##### 运行结果：
+
+![](../img/traffic_course_img/1.gif)
+
+
+
+
+
+
+
+
+
+
+
diff --git a/docs/course/multi-view_ camera.md b/docs/course/multi-view_ camera.md
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+# 配置多视角摄像头camera.py
+
+#### **介绍**
+
+此脚本连接到CARLA仿真环境，在车辆的左右两侧设置相机，并使用Pygame显示相机捕获的实时图像。系统采用多进程架构，确保左右相机图像分别在不同窗口中实时显示。
+
+#### **环境要求**
+
+- Python 3.6 及以上版本
+- CARLA 仿真环境
+- 安装必要的Python库：
+
+```
+pip install carla pygame numpy opencv-python
+```
+
+#### **脚本结构**
+
+##### 初始化
+
+```
+def __init__(self):
+    self.client = None
+    self.world = None
+    self.camera_left = None
+    self.camera_right = None
+    self.car = None
+    self.image_left = None
+    self.image_right = None
+    self.capture = True
+```
+
+初始化CARLA客户端、世界、车辆和相机变量。
+
+##### 相机设置
+
+```python
+def setup_camera(self):
+    #设置相机的变换位置并附加到车辆上
+    #左相机
+    left_camera_transform = carla.Transform(carla.Location(x=-1.6, y=-1.5, z=1.7))
+    self.camera_left = self.world.spawn_actor(self.camera_bp(), left_camera_transform, attach_to=self.car)
+    #右相机
+    right_camera_transform = carla.Transform(carla.Location(x=-1.6, y=1.5, z=1.7))
+    self.camera_right = self.world.spawn_actor(self.camera_bp(), right_camera_transform, attach_to=self.car)
+    #监听左右相机图像
+    weak_self = weakref.ref(self)
+    self.camera_left.listen(lambda image: weak_self().set_image(weak_self, 'left', image))
+    self.camera_right.listen(lambda image: weak_self().set_image(weak_self, 'right', image))
+```
+
+在车辆的左右两侧生成相机，并设置监听器捕获相机图像。
+
+##### 图像处理
+
+```
+@staticmethod
+def set_image(weak_self, side, img):
+    self = weak_self()
+    if side == 'left':
+        self.image_left = img
+    elif side == 'right':
+        self.image_right = img
+
+def get_image_array(self, side):
+    if side == 'left' and self.image_left is not None:
+        array = np.frombuffer(self.image_left.raw_data, dtype=np.dtype("uint8"))
+        array = array.reshape((VIEW_HEIGHT, VIEW_WIDTH, 4))
+        array = array[:, :, :3]  # Drop alpha channel
+        array = array[:, :, ::-1]  # Convert from BGRA to RGB
+        return array
+    elif side == 'right' and self.image_right is not None:
+        array = np.frombuffer(self.image_right.raw_data, dtype=np.dtype("uint8"))
+        array = array.reshape((VIEW_HEIGHT, VIEW_WIDTH, 4))
+        array = array[:, :, :3]  # Drop alpha channel
+        array = array[:, :, ::-1]  # Convert from BGRA to RGB
+        return array
+    else:
+        return None
+```
+
+将相机捕获的图像从BGRA格式转换为RGB格式，并去除Alpha通道。
+
+##### 渲染函数
+
+```
+def render(queue, side, x, y):
+    pygame.init()
+    os.environ['SDL_VIDEO_WINDOW_POS'] = f"{x},{y}"
+    display = pygame.display.set_mode((VIEW_WIDTH, VIEW_HEIGHT), pygame.HWSURFACE | pygame.DOUBLEBUF)
+    pygame.display.set_caption(f'{side.capitalize()} Camera')
+    clock = pygame.time.Clock()
+
+    try:
+        while True:
+            array = queue.get()
+            if array is None:
+                break
+            surface = pygame.surfarray.make_surface(array.swapaxes(0, 1))
+            display.blit(surface, (0, 0))
+            pygame.display.flip()
+            for event in pygame.event.get():
+                if event.type == pygame.QUIT:
+                    return
+            clock.tick_busy_loop(30)
+    finally:
+        pygame.quit()
+```
+
+使用Pygame显示左右相机捕获的图像。
+
+##### 多线程
+
+为了在CARLA仿真环境中创建两个窗口来显示车辆的左右视角，我们需要利用Pygame和多进程来实现。
+
+```
+ left_process = multiprocessing.Process(target=render, args=(left_queue, 'left', 0, 100))
+ right_process = multiprocessing.Process(target=render, args=(right_queue, 'right', VIEW_WIDTH + 10, 100))
+```
+
+![](../img/traffic_course_img/2.gif)
+
+
+
diff --git a/docs/course/navigation.md b/docs/course/navigation.md
@@ -0,0 +1,170 @@
+# 自定义车辆运行轨迹
+
+	车辆运动支持定义车辆运动起点和目标位置，为每辆车指定随机速度值，使其沿轨迹移动时不会发生碰撞或模拟碰撞，看到车辆沿指定轨迹行驶以到达其目标位置。
+
+	本示例设计了一个**automatic_control_revised.py**脚本进行实现
+
+![](../img/traffic_course_img/4.gif)
+
+**注意**  需要将**agents**文件夹位置添加到代码环境变量中，或者复制该文件夹使其与本示例脚本同级。
+
+
+
+	自定义一些生成位置的起始点坐标
+
+```python
+diming = {
+    "北门": {"x": 224.2, "y": 1.7, "z": 1},
+    "西门": {"x": -146, "y": -161, "z": 10},
+    "楚枫桥": {"x": 1.8, "y": -15.9, "z": 30},
+    "楚枫轩": {"x": 14.8, "y": 64.7, "z": 20},
+    "日新楼": {"x": 58, "y": -75, "z": 30},
+    "体育馆": {"x": 160, "y": -265, "z": 40},
+    "湘江楼": {"x": -2.4, "y": -100, "z": 30},
+    "科技楼": {"x": -97.4, "y": -217, "z": 15},
+}
+```
+
+	定义命令行参数
+
+```python
+argparser = argparse.ArgumentParser(
+    description=__doc__)
+argparser.add_argument(
+    '--s',
+    default="北门",
+    type=str)
+argparser.add_argument(
+    '--e',
+    default="西门",
+    type=str)
+args = argparser.parse_args()
+
+```
+
+	获取仿真时间对象及设置
+
+```python
+client = carla.Client('localhost', 2000)
+client.set_timeout(10)
+world = client.get_world()
+origin_settings = world.get_settings()
+
+# 设置
+settings = world.get_settings()
+settings.synchronous_mode = True
+settings.fixed_delta_seconds = 0.05
+world.apply_settings(settings)
+```
+
+	从车辆蓝图中自定义车辆对象，并获取车辆起点坐标
+
+```python
+# 生成车辆和代理
+blueprint_library = world.get_blueprint_library()
+# 将diming字典中的每个键值对转换为一个carla.Location对象
+# 获取生成点
+locations = {key: carla.Location(**value) for key, value in diming.items()}
+spawn_location = carla.Location(locations[args.s])
+spawn_rotation = carla.Rotation(yaw=180)
+spawn_point = carla.Transform(spawn_location, spawn_rotation) #车辆起点
+# 生成车辆
+ego_vehicle_bp = blueprint_library.find('vehicle.audi.tt')
+ego_vehicle_bp.set_attribute('color', '100, 250, 250')
+vehicle = world.spawn_actor(ego_vehicle_bp, spawn_point)
+#推进仿真环境时间
+world.tick()
+```
+
+	生成终点，给起点和终点生成一个车辆运行轨迹
+
+```python
+# 创建代理
+agent = BehaviorAgent(vehicle, behavior='normal')
+destination = carla.Location(locations[args.e])
+start = vehicle.get_location()
+# 生成轨迹
+agent.set_destination(destination)
+```
+
+	给目标车辆设置多个相机传感器。这些相机可以提供不同的视角,用于观察和记录车辆在仿真环境中的行为。
+
+```python
+# 查找相机蓝图
+camera_bp = world.get_blueprint_library().find('sensor.camera.rgb')
+
+# 设置Camera的附加类型Camera跟随车辆
+Atment_SpringArmGhost = carla.AttachmentType.SpringArmGhost
+Atment_Rigid = carla.AttachmentType.Rigid
+# 设置相对车辆的安装位置，配置上帝视图(Camera无法实现上帝视图，画面会抖动)
+Vehicle_transform_list = [
+    (carla.Location(z=35), carla.Rotation(pitch=-90))
+]
+# 设置camera的安装位置，配置后往前视图以及前后左右视图
+Camera_transform_list = [
+    (carla.Transform(carla.Location(x=-8, y=0, z=5),
+                     carla.Rotation(pitch=15, yaw=0, roll=0)), Atment_SpringArmGhost)
+]
+
+# 拼接两个transform_list
+spectator_transform_list = Vehicle_transform_list + Camera_transform_list
+
+# 上帝视图坐标系以及所有camera对象填入spectator_obj_list；
+for spectator_transform_index in spectator_transform_list:
+
+    # spectator_transform_list第0个元素为上帝视图坐标系
+    if spectator_transform_list.index(spectator_transform_index) == 0:
+        spectator_obj_list.append(spectator_transform_index)
+
+    # spectator_transform_list其余元素为Camera安装参数，下面生成Camera对象
+    else:
+        camera = world.spawn_actor(camera_bp, spectator_transform_index[0],
+                                   attach_to=vehicle, attachment_type=spectator_transform_index[1])
+        spectator_obj_list.append(camera)
+```
+
+	更新代理、切换视角、处理代理局部规划器中的路径点。
+
+```python
+# 设置Vehicle_transform_list[0]为初始视图(上帝视图)；
+spectator_obj = Vehicle_transform_list[0]
+c = 1
+
+while True:
+    agent._update_information()
+
+    world.tick()
+
+    if len(agent._local_planner._waypoints_queue) < 1:
+        time.sleep(2)
+        print('======== Success=============')
+        break
+
+    # top view
+    spectator = world.get_spectator()
+    transform = vehicle.get_transform()
+    if c:
+        # 上一个spectator的索引号；
+        last_spectator_obj_index = spectator_obj_list.index(spectator_obj)
+        # 计算下一个spectator的索引，如果列表索引超限则重新拿第0个spectator；
+        spectator_obj_index = last_spectator_obj_index + 1 if len(
+            spectator_obj_list) - last_spectator_obj_index - 1 > 0 else 0
+        spectator_obj = spectator_obj_list[spectator_obj_index]
+        time.sleep(0.2)
+
+        # 更新视图
+    if spectator_obj_list.index(spectator_obj) == 0:
+        # 设置上帝视图
+        Vehicle_transform = carla.Transform(vehicle.get_transform().location + spectator_obj_list[0][0],
+                                            spectator_obj_list[0][1])
+        world.get_spectator().set_transform(Vehicle_transform)
+    else:
+        # 设置其他Camera视图
+        world.get_spectator().set_transform(spectator_obj.get_transform())
+    c = 0
+
+    # speed_limit = vehicle.get_speed_limit()
+    # agent.get_local_planner().set_speed(50)
+    control = agent.run_step(debug=True)
+    vehicle.apply_control(control)
+```