手把手教你学AUTOSAR（15.5）--基于AUTOSAR的自动驾驶交通标志识别系统（TSR）

 % 创建SWC

    
 trafficSignDetection_SWC = createSWC('TrafficSignDetection_SWC');
    
  
    
 % 添加端口
    
 addPort(trafficSignDetection_SWC, 'CameraData', 'in');
    
 addPort(trafficSignDetection_SWC, 'DetectedSigns', 'out');
    
  
    
 % 添加行为
    
 addBehavior(trafficSignDetection_SWC, 'onCameraData', 'detectTrafficSigns');
    
  
    
 % 实现行为
    
 function detectTrafficSigns(cameraData)
    
     % 处理摄像头数据，检测道路上的交通标志
    
     fprintf('Detecting traffic signs...\n');
    
     detectedSigns = processImage(cameraData);
    
     sendToPort(trafficSignDetection_SWC, 'DetectedSigns', detectedSigns);
    
 end
    
  
    
 % 辅助函数：处理摄像头数据
    
 function signs = processImage(cameraData)
    
     % 使用OpenCV处理摄像头数据
    
     image = cameraData.Image;
    
     grayImage = rgb2gray(image);
    
     edges = edge(grayImage, 'Canny');
    
     contours = findContours(edges);
    
     signs = [];
    
     for i = 1:length(contours)
    
     sign = extractSign(contours(i), image);
    
     if isTrafficSign(sign)
    
         signs = [signs; sign];
    
     end
    
     end
    
 end
    
  
    
 % 辅助函数：提取交通标志
    
 function sign = extractSign(contour, image)
    
     % 提取交通标志区域
    
     boundingBox = boundingRect(contour);
    
     sign = image(boundingBox.y:boundingBox.y+boundingBox.height, boundingBox.x:boundingBox.x+boundingBox.width);
    
 end
    
  
    
 % 辅助函数：判断是否为交通标志
    
 function isSign = isTrafficSign(sign)
    
     % 使用特征匹配或模板匹配判断是否为交通标志
    
     isSign = false;
    
     % 示例：假设有一个已知的交通标志模板
    
     template = loadTrafficSignTemplate();
    
     matchScore = matchTemplate(sign, template);
    
     if matchScore > threshold
    
     isSign = true;
    
     end
    
 end
    
    
    
    

 % 创建SWC

    
 trafficSignRecognition_SWC = createSWC('TrafficSignRecognition_SWC');
    
  
    
 % 添加端口
    
 addPort(trafficSignRecognition_SWC, 'DetectedSigns', 'in');
    
 addPort(trafficSignRecognition_SWC, 'RecognizedSigns', 'out');
    
  
    
 % 添加行为
    
 addBehavior(trafficSignRecognition_SWC, 'onDetectedSigns', 'recognizeTrafficSigns');
    
  
    
 % 实现行为
    
 function recognizeTrafficSigns(detectedSigns)
    
     % 识别交通标志的类型和内容
    
     fprintf('Recognizing traffic signs...\n');
    
     recognizedSigns = classifyTrafficSigns(detectedSigns);
    
     sendToPort(trafficSignRecognition_SWC, 'RecognizedSigns', recognizedSigns);
    
 end
    
  
    
 % 辅助函数：分类识别交通标志
    
 function signs = classifyTrafficSigns(detectedSigns)
    
     % 使用机器学习算法（如SVM、CNN）进行交通标志分类
    
     signs = [];
    
     for i = 1:length(detectedSigns)
    
     sign = detectedSigns(i);
    
     features = extractFeatures(sign);
    
     classification = classify(features);
    
     signs = [signs; struct('Image', sign, 'Type', classification)];
    
     end
    
 end
    
  
    
 % 辅助函数：提取特征
    
 function features = extractFeatures(sign)
    
     % 提取交通标志的特征
    
     features = [];
    
     % 示例：使用HOG特征
    
     hogFeatures = hog(sign);
    
     features = [features; hogFeatures];
    
 end
    
  
    
 % 辅助函数：分类
    
 function type = classify(features)
    
     % 使用训练好的模型进行分类
    
     model = loadTrafficSignModel();
    
     type = predict(model, features);
    
 end
    
    
    
    

 % 创建SWC

    
 vehicleBehaviorAdjustment_SWC = createSWC('VehicleBehaviorAdjustment_SWC');
    
  
    
 % 添加端口
    
 addPort(vehicleBehaviorAdjustment_SWC, 'RecognizedSigns', 'in');
    
 addPort(vehicleBehaviorAdjustment_SWC, 'VehicleState', 'in');
    
 addPort(vehicleBehaviorAdjustment_SWC, 'ControlCommand', 'out');
    
  
    
 % 添加行为
    
 addBehavior(vehicleBehaviorAdjustment_SWC, 'onRecognizedSigns', 'adjustVehicleBehavior');
    
  
    
 % 实现行为
    
 function adjustVehicleBehavior(recognizedSigns, vehicleState)
    
     % 根据识别结果调整车辆的行为
    
     fprintf('Adjusting vehicle behavior...\n');
    
     controlCommand = generateControlCommand(recognizedSigns, vehicleState);
    
     sendToPort(vehicleBehaviorAdjustment_SWC, 'ControlCommand', controlCommand);
    
 end
    
  
    
 % 辅助函数：生成控制命令
    
 function command = generateControlCommand(recognizedSigns, vehicleState)
    
     % 使用决策树或规则引擎进行行为决策
    
     command = [];
    
     for i = 1:length(recognizedSigns)
    
     sign = recognizedSigns(i);
    
     action = decideAction(sign.Type, vehicleState);
    
     command = [command; action];
    
     end
    
 end
    
  
    
 % 辅助函数：决定行动
    
 function action = decideAction(signType, vehicleState)
    
     % 根据交通标志类型和车辆状态决定行动
    
     action = [];
    
     switch signType
    
     case 'Stop'
    
         action = struct('Type', 'Brake', 'Strength', 1.0);
    
     case 'SpeedLimit'
    
         speedLimit = getSpeedLimit(signType);
    
         if vehicleState.Speed > speedLimit
    
             action = struct('Type', 'Throttle', 'Strength', 0.5);
    
         end
    
     otherwise
    
         action = struct('Type', 'None', 'Strength', 0.0);
    
     end
    
 end
    
  
    
 % 辅助函数：获取速度限制
    
 function speedLimit = getSpeedLimit(signType)
    
     % 获取交通标志的速度限制
    
     speedLimit = 0;
    
     % 示例：假设有一个已知的速度限制表
    
     speedLimitTable = loadSpeedLimitTable();
    
     speedLimit = speedLimitTable(signType);
    
 end