283 lines
9.9 KiB
Python
283 lines
9.9 KiB
Python
"""
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SUMO 网络拓扑解析器
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解析 SUMO 网络文件和感应线圈定义文件，构建:
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1. Edge 顺序和长度信息
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2. 检测器到 edge/lane/position 的映射
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3. Zone 分组结构
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"""
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import os
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import sys
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import xml.etree.ElementTree as ET
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import re
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from dataclasses import dataclass, field
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from typing import Dict, List, Tuple, Optional
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from collections import defaultdict
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# 确保 traci/sumolib 可导入
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try:
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import sumo
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_tools = os.path.join(sumo.SUMO_HOME, "tools")
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if _tools not in sys.path:
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sys.path.insert(0, _tools)
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except ImportError:
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try:
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# 兼容服务器环境
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sys.path.insert(0, "/workspace/ctm-dqn/.venv/lib/python3.12/site-packages/sumo/tools")
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import sumo
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except:
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pass
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@dataclass
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class DetectorInfo:
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"""单个感应线圈检测器信息"""
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det_id: str
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edge: str
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lane_id: str # 完整 lane ID, e.g. "G1523_AM3_4.1_1"
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lane_idx: int # lane 编号 (0=应急车道, 1,2,3=交通车道)
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position: float # 在 edge 上的位置 (m)
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pos_index: int # 检测器序号 (metrics_0, metrics_1, ...)
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@dataclass
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class EdgeInfo:
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"""单条 edge 的信息"""
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edge_id: str
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length: float = 0.0
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speed_limit: float = 30.0 # m/s
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total_lanes: int = 0
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traffic_lane_indices: List[int] = field(default_factory=list) # 排除应急车道后的 lane 编号
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detector_positions: List[float] = field(default_factory=list) # 去重后的检测器位置列表（升序）
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detectors: Dict[Tuple[int, int], str] = field(default_factory=dict) # (lane_idx, pos_index) -> det_id
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class SUMONetworkParser:
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"""SUMO 网络和检测器拓扑解析器"""
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def __init__(self, detector_add_file: str, net_file: Optional[str] = None):
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"""
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Args:
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detector_add_file: 感应线圈定义文件路径 (metrics_il.add.xml)
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net_file: SUMO 网络文件路径 (modified.net.xml), 可选
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"""
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self.detector_add_file = detector_add_file
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self.net_file = net_file
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# 解析结果
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self.detectors: Dict[str, DetectorInfo] = {} # det_id -> DetectorInfo
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self.edges: List[str] = [] # 按行驶顺序排列
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self.edge_info: Dict[str, EdgeInfo] = {} # edge_id -> EdgeInfo
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self.edge_cumulative_offset: Dict[str, float] = {} # edge -> 起始累积距离
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# 派生属性
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self.max_traffic_lanes: int = 0
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self.max_detectors_per_edge: int = 0 # 单条 edge 上最大检测器位置数
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# 执行解析
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self._parse_detectors()
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if net_file:
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self._enrich_from_net()
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self._refresh_lane_metadata_from_net()
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self._compute_cumulative_offsets()
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def _parse_detectors(self):
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"""解析 metrics_il.add.xml, 构建检测器到 edge 的映射"""
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tree = ET.parse(self.detector_add_file)
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root = tree.getroot()
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edge_detector_map = defaultdict(list) # edge -> [DetectorInfo]
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edge_order = [] # 按出现顺序记录 edge
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seen_edges = set()
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for il in root.findall("inductionLoop"):
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det_id = il.get("id")
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lane_id = il.get("lane")
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pos = float(il.get("pos"))
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# 解析 lane ID: 最后一个 _ 后面是 lane_idx
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last_us = lane_id.rfind("_")
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edge_id = lane_id[:last_us]
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lane_idx = int(lane_id[last_us + 1:])
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# 解析检测器 ID 中的 pos_index: ..._metrics_N
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m = re.search(r"_metrics_(\d+)$", det_id)
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pos_index = int(m.group(1)) if m else 0
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info = DetectorInfo(
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det_id=det_id,
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edge=edge_id,
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lane_id=lane_id,
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lane_idx=lane_idx,
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position=pos,
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pos_index=pos_index,
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)
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self.detectors[det_id] = info
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edge_detector_map[edge_id].append(info)
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if edge_id not in seen_edges:
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seen_edges.add(edge_id)
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edge_order.append(edge_id)
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self.edges = edge_order
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# 构建 EdgeInfo
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for edge_id in self.edges:
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dets = edge_detector_map[edge_id]
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lane_indices = sorted(set(d.lane_idx for d in dets))
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# 排除应急车道 (lane 0): 通常应急车道不会有车辆通过
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traffic_lanes = [l for l in lane_indices if l > 0]
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if not traffic_lanes:
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traffic_lanes = lane_indices # 如果只有 lane 0 则保留
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# 检测器位置（去重，升序）
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positions = sorted(set(d.position for d in dets))
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# 构建 (lane_idx, pos_index) -> det_id 的映射
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det_map = {}
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for d in dets:
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det_map[(d.lane_idx, d.pos_index)] = d.det_id
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# 估算 edge 长度: 最大检测器位置 + 100m
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est_length = max(d.position for d in dets) + 100.0
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# 估算限速: 将在 _enrich_from_net 中覆盖
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self.edge_info[edge_id] = EdgeInfo(
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edge_id=edge_id,
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length=est_length,
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total_lanes=max(lane_indices) + 1,
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traffic_lane_indices=traffic_lanes,
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detector_positions=positions,
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detectors=det_map,
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)
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# 计算最大值
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self.max_traffic_lanes = max(
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len(ei.traffic_lane_indices) for ei in self.edge_info.values()
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)
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self.max_detectors_per_edge = max(
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len(ei.detector_positions) for ei in self.edge_info.values()
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)
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def _enrich_from_net(self):
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"""从 net.xml 补充 edge 长度和限速信息"""
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try:
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import sumolib
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net = sumolib.net.readNet(self.net_file)
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for edge_id in self.edges:
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try:
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edge = net.getEdge(edge_id)
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self.edge_info[edge_id].length = edge.getLength()
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lanes = edge.getLanes()
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if lanes:
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self.edge_info[edge_id].speed_limit = max(
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l.getSpeed() for l in lanes
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)
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except Exception:
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pass # 保留估算值
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except ImportError:
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pass # sumolib 不可用时保留估算值
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def _compute_cumulative_offsets(self):
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"""计算每条 edge 的累积起始距离"""
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cumulative = 0.0
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for edge_id in self.edges:
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self.edge_cumulative_offset[edge_id] = cumulative
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cumulative += self.edge_info[edge_id].length
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def _refresh_lane_metadata_from_net(self):
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"""Use lane permissions from net.xml instead of assuming lane 0 is emergency."""
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net_tree = ET.parse(self.net_file)
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net_root = net_tree.getroot()
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for edge in net_root.findall("edge"):
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edge_id = edge.get("id")
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if edge_id not in self.edge_info:
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continue
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lane_nodes = edge.findall("lane")
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if not lane_nodes:
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continue
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traffic_lanes = []
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for lane in lane_nodes:
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lane_idx = int(lane.get("index", "0"))
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allow = (lane.get("allow") or "").strip()
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allow_tokens = {token for token in allow.split() if token}
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if allow_tokens != {"emergency"}:
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traffic_lanes.append(lane_idx)
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if not traffic_lanes:
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traffic_lanes = list(range(len(lane_nodes)))
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self.edge_info[edge_id].traffic_lane_indices = sorted(traffic_lanes)
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self.edge_info[edge_id].total_lanes = len(lane_nodes)
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@property
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def total_length(self) -> float:
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"""监控路段总长度 (m)"""
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return sum(ei.length for ei in self.edge_info.values())
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@property
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def num_edges(self) -> int:
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return len(self.edges)
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def get_detector_ids_for_edge_lane(
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self, edge_id: str, lane_idx: int
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) -> List[str]:
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"""返回指定 edge 和 lane 上的检测器 ID 列表（按位置排序）"""
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ei = self.edge_info[edge_id]
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result = []
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for pi in range(len(ei.detector_positions)):
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det_id = ei.detectors.get((lane_idx, pi))
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if det_id:
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result.append(det_id)
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return result
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def get_all_detector_ids(self) -> List[str]:
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"""返回所有检测器 ID 列表"""
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return list(self.detectors.keys())
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def get_state_dimensions(self, num_features: int = 2) -> int:
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"""
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计算状态向量总维度
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state = [
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对每条 edge (num_edges):
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对每个 cell (padded 到 max_detectors_per_edge):
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对每条 traffic lane (padded 到 max_traffic_lanes):
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[speed, occupancy] (num_features)
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+ 每条 edge 的当前限速归一化值 (num_edges)
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]
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"""
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per_edge_dim = self.max_detectors_per_edge * self.max_traffic_lanes * num_features
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return self.num_edges * per_edge_dim + self.num_edges
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def summary(self):
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"""打印拓扑摘要"""
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print(f"=== SUMO Network Topology ===")
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print(f"Edges: {self.num_edges}")
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print(f"Max traffic lanes: {self.max_traffic_lanes}")
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print(f"Max detectors per edge: {self.max_detectors_per_edge}")
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print(f"Total length: {self.total_length:.0f} m ({self.total_length/1000:.1f} km)")
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print(f"Total detectors: {len(self.detectors)}")
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print(f"State dimension: {self.get_state_dimensions()}")
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print()
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for edge_id in self.edges:
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ei = self.edge_info[edge_id]
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print(
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f" {edge_id:25s} len={ei.length:8.1f}m "
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f"lanes={ei.traffic_lane_indices} "
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f"dets={len(ei.detector_positions):2d} "
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f"v_max={ei.speed_limit*3.6:.0f}km/h"
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)
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if __name__ == "__main__":
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parser = SUMONetworkParser(
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detector_add_file="sumo_resource/metrics_il.add.xml",
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net_file="sumo_resource/modified.net.xml",
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)
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parser.summary()
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