降低检测器数据获取频率，修复仅获取单车道数据的问题
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@ -76,14 +76,18 @@ class SUMOEdgeVSLEnvironment:
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net_file=self.net_file,
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)
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# 为每条边构建检测器映射（只用第一个检测器获取边级数据）
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self.edge_detector_map: Dict[str, str] = {}
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# 为每条边构建第一组检测器映射（所有车道）
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self.edge_detector_map: Dict[str, List[str]] = {}
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for edge_id in self.control_edges:
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ei = self.parser.edge_info.get(edge_id)
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if ei and ei.detectors:
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# 取第一个检测器作为该边的代表
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first_det = list(ei.detectors.values())[0]
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self.edge_detector_map[edge_id] = first_det
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# 获取第一组检测器（pos_index=0）的所有交通车道
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first_group_dets = []
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for lane_idx in ei.traffic_lane_indices:
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det_id = ei.detectors.get((lane_idx, 0))
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if det_id:
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first_group_dets.append(det_id)
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self.edge_detector_map[edge_id] = first_group_dets
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# 动作空间: 每条边独立选速度
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self.action_dims = [self.num_speed_actions] * self.num_edges
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@ -181,8 +185,10 @@ class SUMOEdgeVSLEnvironment:
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self._interval_arrived += traci.simulation.getArrivedNumber()
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self._interval_departed += traci.simulation.getDepartedNumber()
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state = self._collect_state()
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info = self._collect_metrics()
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# 只读取一次检测器数据
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detector_data = self._get_edge_detector_data()
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state = self._collect_state(detector_data)
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info = self._collect_metrics(detector_data)
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reward = self._calculate_reward(info)
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self._last_reward = reward
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@ -209,32 +215,54 @@ class SUMOEdgeVSLEnvironment:
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for i, edge_id in enumerate(self.control_edges):
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traci.edge.setMaxSpeed(edge_id, float(edge_speeds[i]))
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def _collect_state(self) -> np.ndarray:
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"""收集状态：每条边的平均速度/占有率/流量"""
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state_parts = []
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def _get_edge_detector_data(self) -> Tuple[List[float], List[float], List[int], List[float]]:
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"""获取所有控制边的检测器数据（速度、占有率、车辆数、有效速度）"""
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speeds, occs, counts, valid_speeds = [], [], [], []
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for edge_id in self.control_edges:
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det_id = self.edge_detector_map.get(edge_id)
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if det_id:
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det_ids = self.edge_detector_map.get(edge_id, [])
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if not det_ids:
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speeds.append(self.free_flow_speed)
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occs.append(0.0)
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counts.append(0)
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continue
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# 获取所有车道的数据
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lane_speeds, lane_occs, lane_counts = [], [], []
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for det_id in det_ids:
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try:
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spd = traci.inductionloop.getLastIntervalMeanSpeed(det_id)
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occ = traci.inductionloop.getLastIntervalOccupancy(det_id)
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cnt = traci.inductionloop.getLastIntervalVehicleNumber(det_id)
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if spd <= 0:
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spd = traci.lane.getMaxSpeed(traci.inductionloop.getLaneID(det_id))
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if spd > 0:
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lane_speeds.append(spd)
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lane_occs.append(occ)
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lane_counts.append(cnt)
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except Exception:
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spd = self.free_flow_speed
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occ = 0.0
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cnt = 0
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else:
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spd = self.free_flow_speed
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occ = 0.0
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cnt = 0
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pass
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# 聚合
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speeds.append(np.mean(lane_speeds) if lane_speeds else self.free_flow_speed)
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occs.append(np.mean(lane_occs) if lane_occs else 0.0)
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counts.append(sum(lane_counts))
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if lane_speeds:
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valid_speeds.append(np.mean(lane_speeds))
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return speeds, occs, counts, valid_speeds
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def _collect_state(self, detector_data: Optional[Tuple[List[float], List[float], List[int], List[float]]] = None) -> np.ndarray:
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"""收集状态：每条边的平均速度/占有率/流量"""
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state_parts = []
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if detector_data is None:
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speeds, occs, counts, _ = self._get_edge_detector_data()
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else:
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speeds, occs, counts, _ = detector_data
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for spd, occ, cnt in zip(speeds, occs, counts):
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mean_speed_norm = np.clip(spd / self.free_flow_speed, 0.0, 1.5)
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mean_occ = np.clip(occ / 100.0, 0.0, 1.0)
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flow_norm = min(cnt / 50.0, 1.0)
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state_parts.extend([mean_speed_norm, mean_occ, flow_norm])
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# 边限速
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@ -252,7 +280,7 @@ class SUMOEdgeVSLEnvironment:
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return np.array(state_parts, dtype=np.float32)
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def _collect_metrics(self) -> Dict:
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def _collect_metrics(self, detector_data: Tuple[List[float], List[float], List[int], List[float]]) -> Dict:
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"""收集交通指标"""
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info = {}
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@ -263,34 +291,14 @@ class SUMOEdgeVSLEnvironment:
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info["departed_count"] = self._interval_departed
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# 每条边的速度和占有率
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edge_speeds = []
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edge_occs = []
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all_speeds = []
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for edge_id in self.control_edges:
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det_id = self.edge_detector_map.get(edge_id)
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if det_id:
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try:
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spd = traci.inductionloop.getLastIntervalMeanSpeed(det_id)
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occ = traci.inductionloop.getLastIntervalOccupancy(det_id)
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if spd <= 0:
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spd = traci.lane.getMaxSpeed(traci.inductionloop.getLaneID(det_id))
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edge_speeds.append(spd)
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edge_occs.append(occ)
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all_speeds.append(spd)
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except Exception:
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edge_speeds.append(self.free_flow_speed)
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edge_occs.append(0.0)
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else:
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edge_speeds.append(self.free_flow_speed)
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edge_occs.append(0.0)
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edge_speeds, edge_occs, _, valid_speeds = detector_data
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info["edge_speeds_ms"] = edge_speeds
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info["edge_occupancies"] = edge_occs
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info["mean_speed"] = np.mean(all_speeds) if all_speeds else 0.0
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info["mean_speed"] = np.mean(valid_speeds) if valid_speeds else 0.0
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info["mean_speed_kmh"] = info["mean_speed"] * 3.6
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info["mean_occupancy"] = np.mean(edge_occs) if edge_occs else 0.0
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info["speed_std"] = np.std(all_speeds) if len(all_speeds) > 1 else 0.0
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info["speed_std"] = np.std(valid_speeds) if len(valid_speeds) > 1 else 0.0
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# 车辆数和密度
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try:
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