保存方向级别拥堵信息

wj-realtime-computing/src/main/java/com/wanji/indicators/constant/Constant.java

@@ -78,6 +78,11 @@ public class Constant {
    */
   public static final String PEDESTRAIN_LIGHT_CODE = "20";
 
+  /**
+   * 右转灯转向
+   */
+  public static final String RIGHT_LIGHT_CODE = "3";
+
   /**
    * 入侵结果
    */

wj-realtime-computing/src/main/java/com/wanji/indicators/task/trajectory/func/CarDataValidatorFlatMap.java

@@ -88,6 +88,6 @@ public class CarDataValidatorFlatMap implements FlatMapFunction<FrameModel, CarT
     }
 
     public static boolean isQualifiedPlate(String plate){
-        return StringUtils.isNotEmpty(plate) && !Objects.equals("null", plate) && !Objects.equals("默A00000", plate);
+        return StringUtils.isNotEmpty(plate) && !Objects.equals("null", plate) && !plate.contains("00000");
     }
 }

wj-realtime-computing/src/main/java/com/wanji/indicators/task/trajectory/func/CoordCongestionDataFunction.java

+package com.wanji.indicators.task.trajectory.func;
+
+import com.wanji.indicators.task.trajectory.CarTrajectoryIndexMain;
+import com.wanji.indicators.task.trajectory.pojo.RidIndexResult;
+import com.wanji.indicators.task.trajectory.pojo.StartDuration;
+import org.apache.flink.api.common.state.MapState;
+import org.apache.flink.api.common.state.MapStateDescriptor;
+import org.apache.flink.configuration.Configuration;
+import org.apache.flink.streaming.api.functions.KeyedProcessFunction;
+import org.apache.flink.util.Collector;
+
+import java.time.Instant;
+import java.time.temporal.ChronoUnit;
+import java.util.Iterator;
+
+/**
+ * 协调方向拥堵数据
+ *
+ * @author Kent HAN
+ * @date 2023/11/14 10:02
+ */
+public class CoordCongestionDataFunction extends KeyedProcessFunction<String, RidIndexResult, RidIndexResult> {
+
+    // Key：方向
+    private MapState<Integer, StartDuration> dirState;
+
+    @Override
+    public void open(Configuration parameters) throws Exception {
+        dirState = getRuntimeContext()
+                .getMapState(new MapStateDescriptor<>("dir_map",
+                        Integer.class, StartDuration.class));
+    }
+
+
+    @Override
+    public void processElement(RidIndexResult value,
+                               KeyedProcessFunction<String, RidIndexResult, RidIndexResult>.Context ctx,
+                               Collector<RidIndexResult> out) throws Exception {
+
+        String rid = ctx.getCurrentKey();
+        Integer dir = CarTrajectoryIndexMain.ridDirMap.get(rid);
+        value.setDir(dir);
+
+        Double index = value.getIndex();
+        boolean isCongestion = index > 1.5;
+
+        Integer stateKey = dir;
+
+        if (isCongestion) {
+            try {
+                if (!dirState.contains(stateKey)) {
+                    StartDuration startDuration = new StartDuration();
+
+                    // 获取当前的时间戳
+                    Instant now = Instant.now();
+                    // 获取1分钟前的时间戳
+                    Instant oneMinuteBefore = now.minus(1, ChronoUnit.MINUTES);
+                    // 转换成毫秒
+                    long timestampOneMinuteBefore = oneMinuteBefore.toEpochMilli();
+                    value.setStartTime(timestampOneMinuteBefore);
+                    startDuration.setStartTime(timestampOneMinuteBefore);
+
+                    value.setDuration(1);
+                    startDuration.setDuration(1);
+
+                    dirState.put(stateKey, startDuration);
+                } else {
+                    StartDuration startDuration = dirState.get(stateKey);
+                    value.setStartTime(startDuration.getStartTime());
+                    Integer duration = startDuration.getDuration();
+                    duration += 1;
+                    startDuration.setDuration(duration);
+                    value.setDuration(duration);
+                    dirState.put(stateKey, startDuration);
+                }
+            } catch (Exception e) {
+                throw new RuntimeException(e);
+            }
+        } else {
+            // 删除状态
+            try {
+                Iterator<Integer> mapStateIterator = dirState.keys().iterator();
+                while (mapStateIterator.hasNext()){
+                    Integer key = mapStateIterator.next();
+                    if(key.equals(stateKey)){
+                        mapStateIterator.remove();
+                    }
+                }
+            } catch (Exception e) {
+                throw new RuntimeException(e);
+            }
+        }
+        out.collect(value);
+    }
+}

wj-realtime-computing/src/main/java/com/wanji/indicators/task/trajectory/pojo/RidIndexResultOfEastAndWest.java → wj-realtime-computing/src/main/java/com/wanji/indicators/task/trajectory/pojo/RidIndexResult.java

@@ -9,7 +9,10 @@ import lombok.Data;
  * @Description :
  */
 @Data
-public class RidIndexResultOfEastAndWest {
+public class RidIndexResult {
+
+    private Integer dir;
+
     private String rid;
     //该路段的结束路口
     private String crossId;
@@ -27,4 +30,7 @@ public class RidIndexResultOfEastAndWest {
     private Long startTime;
 
     private Long endTime;
+
+    private Integer duration;
+
 }

wj-realtime-computing/src/main/java/com/wanji/indicators/task/trajectory/pojo/StartDuration.java

+package com.wanji.indicators.task.trajectory.pojo;
+
+import lombok.Data;
+
+@Data
+public class StartDuration {
+
+    // 开始时间（毫秒时间戳）
+    private Long startTime;
+    // 持续时长（分钟）
+    private Integer duration;
+
+}

wj-realtime-computing/src/main/resources/config.properties

@@ -44,15 +44,15 @@ cross.event.data.topic=analysis.cross.event
 plate.prefix=鲁
 #路段默认自由流速度配置值 km/h
 rid.default.free.speed=80
-#东西方向路段拥堵指数统计
+#协调方向路段拥堵指数统计
 rid.traffic.index.analysis.topic=rid.traffic.index.analysis
-#南北方向饱和度计算
+#非协调方向饱和度计算
 rid.traffic.index.north.south.topic=rid.traffic.index.north.south.analysis
 
-#东西方向路段的rid和方向
-east.west.rid.direction.list=13NED0B5Q9013NF80B5QN00:6,13NGH0B5RC013NF80B5QN00:2,13NI00B5RM013NGH0B5RC00:3,13NF80B5QN013NGH0B5RC00:6,13NGH0B5RC013NI00B5RM00:7,13NID0B5RM013NI00B5RM00:3
-#南北方向路段的rid和方向
-north.south.rid.direction.list=13NG40B5SK013NI00B5RM00:1,13NEH0B5RJ013NGH0B5RC00:1,13NEP0B5QJ013NGH0B5RC00:5,13NDG0B5RI013NF80B5QN00:1,13NDT0B5Q9013NF80B5QN00:4
+# 协调方向路段的rid和方向
+coord.rid.direction.list=13NED0B5Q9013NF80B5QN00:6,13NGH0B5RC013NF80B5QN00:2,13NI00B5RM013NGH0B5RC00:3,13NF80B5QN013NGH0B5RC00:6,13NGH0B5RC013NI00B5RM00:7,13NID0B5RM013NI00B5RM00:3
+# 非协调方向路段的rid和方向
+no.coord.rid.direction.list=13NG40B5SK013NI00B5RM00:1,13NEH0B5RJ013NGH0B5RC00:1,13NEP0B5QJ013NGH0B5RC00:5,13NDG0B5RI013NF80B5QN00:1,13NDT0B5Q9013NF80B5QN00:4
 
 #路口溢出评价指标
 road.overflow.avg.speed=5.0
@@ -69,8 +69,10 @@ cross.road.deadlock.avg.speed=5.0
 #相位灯的状态数据
 light.status.topic=cross_lights_status
 
-#虚拟路口区域
+# 虚拟路口区域
+# 霞景路西，旅游路与回龙山路交叉口
 virtual.crossroad.13NED0B5Q90=13NED0B5Q90:117.08503591467242,36.64125732273356;117.08495255127629,36.641426722875224;117.08499878952986,36.641454206982246;117.08508543702352,36.641286700399476
+# 福地街东，旅游路与隧道交叉口
 virtual.crossroad.13NH20B5RH0=13NH20B5RH0:117.09669255282627,36.644871615002884;117.09669985552095,36.645055610398025;117.09675474612689,36.64505324101935;117.09674606214631,36.64486930675771
 
 #相位空放topic

wj-realtime-computing/src/main/resources/documentation/ReadMe.md

@@ -5,9 +5,9 @@
 ## 2. 指标说明
     
     ### 2.1 拥堵
-    拥堵指标计算分为东西方向和南北方向
-    - 东西方向拥堵指数计算会针对每个路口的进口路段进行计算，统计每个路段的拥堵指数，并根据拥堵指数进行阈值判断后，获取该路段的交通状态
-    - 南北方向的拥堵指数计算是根据饱和度计算绿灯时间内，车辆空档时间。根据算法文档给出的计算公式进行相关计算后，判断其阈值范围，从而获取该路段的交通状态
+    拥堵指标计算分为协调方向方向和非协调方向
+    - 协调方向拥堵指数计算会针对每个路口的进口路段进行计算，统计每个路段的拥堵指数，并根据拥堵指数进行阈值判断后，获取该路段的交通状态
+    - 非协调方向的拥堵指数计算：根据绿灯时间内车辆空档时间，计算饱和度。根据算法文档阈值判断拥堵等级。
  
     ### 2.2 失衡
     - 根据算法指标计算文档给出的计算公式，计算每个路口是否处于失衡状态