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445 lines
17 KiB
445 lines
17 KiB
{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {},
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"outputs": [],
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"source": [
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"import pandas as pd\n",
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"import numpy as np\n",
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"import os\n",
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"import sumolib\n",
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"import copy\n",
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"from tqdm import tqdm\n",
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"from datetime import datetime"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {},
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"outputs": [],
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"source": [
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"m = 105\n",
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"midnight = int(datetime(2024, 1, 5, 0, 0, 0).timestamp())\n",
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"next_day = int(datetime(2024, 1, 6, 0, 0, 0).timestamp())\n",
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"fmins = range(midnight, next_day, 300)\n",
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"\n",
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"# 현재시각\n",
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"present_time = fmins[m]\n",
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"sigtable_start = fmins[m] - 1200\n",
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"sim_start = fmins[m] - 900\n",
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"sim_end = fmins[m] - 600\n",
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"\n",
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"# network and dataframes\n",
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"net = sumolib.net.readNet('../../Data/networks/sn.net.xml')\n",
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"inter_node = pd.read_csv('../../data/tables/inter_node.csv', index_col=0)\n",
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"plan = pd.read_csv('../../data/tables/plan.csv', index_col=0)\n",
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"match6 = pd.read_csv('../../Data/tables/matching/match6.csv', index_col=0)\n",
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"match6 = match6[['node_id', 'phase_no', 'ring_type', 'inc_edge', 'out_edge']].reset_index(drop=True)\n",
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"histid = pd.read_csv(f'../../Data/tables/histids/histids_{present_time}.csv', index_col=0)\n",
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"histid = histid.reset_index(drop=True).drop(columns=['inter_no'])\n",
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"\n",
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"# helper dictionaries\n",
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"inter2node = dict(zip(inter_node['inter_no'], inter_node['node_id']))\n",
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"node2inter = dict(zip(inter_node['node_id'], inter_node['inter_no']))\n",
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"pa2ch = {'i0':['u00'], 'i1':[], 'i2':['u20'], 'i3':['c30', 'u30', 'u31', 'u32'], 'i6':['u60'], 'i7':[], 'i8':[], 'i9':[]}\n",
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"node_ids = sorted(inter_node.node_id.unique())\n",
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"parent_ids = sorted(inter_node[inter_node.inter_type=='parent'].node_id.unique())\n",
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"nodes = [net.getNode(node_id) for node_id in node_ids]"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"['c30',\n",
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" 'i0',\n",
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" 'i1',\n",
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" 'i2',\n",
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" 'i3',\n",
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" 'i6',\n",
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" 'i7',\n",
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" 'i8',\n",
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" 'i9',\n",
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" 'u00',\n",
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" 'u20',\n",
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" 'u30',\n",
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" 'u31',\n",
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" 'u32',\n",
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" 'u60']"
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]
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},
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"execution_count": 3,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"node_ids"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"c30 140\n",
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"i0 150\n",
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"i1 150\n",
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"i2 150\n",
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"i3 150\n",
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"i6 150\n",
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"i7 150\n",
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"i8 150\n",
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"i9 150\n",
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"u00 160\n",
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"u20 150\n",
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"u60 150\n"
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]
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}
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],
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"source": [
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"node2mincycle = {}\n",
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"for inter_no in sorted(plan.inter_no.unique()):\n",
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" mincycle = plan[plan.inter_no==inter_no].cycle.min()\n",
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" parent_id = inter2node[inter_no]\n",
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" node2mincycle[parent_id] = mincycle\n",
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" for child_id in pa2ch:\n",
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" node2mincycle[child_id] = mincycle\n",
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"for node_id in sorted(node2mincycle):\n",
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" print(node_id, node2mincycle[node_id])"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"metadata": {},
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"outputs": [],
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"source": [
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"def make_histids(histid, match6, parent_ids, pa2ch):\n",
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" new_histids = []\n",
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" for parent_id in parent_ids:\n",
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" for child_id in pa2ch[parent_id]:\n",
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" new_histid = histid.copy()[histid.node_id==parent_id]\n",
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" new_histid[['inc_edge_A', 'out_edge_A', 'inc_edge_B', 'out_edge_B']] = np.nan\n",
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" for i, row in new_histid.iterrows():\n",
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" phas_A = row.phas_A\n",
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" phas_B = row.phas_B\n",
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" new_match = match6[match6.node_id==child_id]\n",
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" Arow = new_match[(new_match.phase_no==phas_A) & (new_match.ring_type=='A')]\n",
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" if ~ Arow[['inc_edge', 'out_edge']].isna().all().all():\n",
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" inc_edge = Arow.iloc[0].inc_edge\n",
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" out_edge = Arow.iloc[0].out_edge\n",
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" new_histid.loc[i, ['inc_edge_A', 'out_edge_A']] = [inc_edge, out_edge]\n",
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" Brow = new_match[(new_match.phase_no==phas_B) & (new_match.ring_type=='B')]\n",
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" if ~ Brow[['inc_edge', 'out_edge']].isna().all().all():\n",
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" inc_edge = Brow.iloc[0].inc_edge\n",
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" out_edge = Brow.iloc[0].out_edge\n",
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" new_histid.loc[i, ['inc_edge_B', 'out_edge_B']] = [inc_edge, out_edge]\n",
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" new_histid.loc[i, 'node_id'] = child_id\n",
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" new_histids.append(new_histid)\n",
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" new_histids = pd.concat(new_histids)\n",
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" histids = pd.concat([histid.copy(), new_histids])\n",
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" histids = histids.sort_values(by=['start_unix', 'node_id', 'phas_A', 'phas_B']).reset_index(drop=True)\n",
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" return histids"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 6,
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"metadata": {},
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"outputs": [],
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"source": [
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"def initialize_states(net, nodes, histids):\n",
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" node2init = {}\n",
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" for node in nodes:\n",
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" node_id = node.getID()\n",
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" conns = [(c.getJunctionIndex(), c) for c in node.getConnections()]\n",
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" conns = [c for c in conns if c[0] >= 0]\n",
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" conns = sorted(conns, key=lambda x: x[0])\n",
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" state = []\n",
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" for i, ci in conns:\n",
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" if ci.getTLLinkIndex() < 0:\n",
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" continue\n",
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" are_foes = False\n",
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" for j, cj in conns:\n",
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" if ci.getTo() == cj.getTo():\n",
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" continue\n",
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" if node.areFoes(i, j):\n",
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" are_foes = True\n",
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" break\n",
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" state.append('r' if are_foes else 'g')\n",
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" node2init[node_id] = state\n",
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"\n",
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" # 어떤 연결과도 상충이 일어나지는 않지만, 신호가 부여되어 있는 경우에는 r을 부여\n",
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" for _, row in histids.iterrows():\n",
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" node_id = row['node_id']\n",
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" inc_edge_A = row.inc_edge_A\n",
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" inc_edge_B = row.inc_edge_B\n",
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" out_edge_A = row.out_edge_A\n",
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" out_edge_B = row.out_edge_B\n",
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"\n",
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" if pd.isna(inc_edge_A) or pd.isna(out_edge_A):\n",
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" pass\n",
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" else:\n",
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" inc_edge_A = net.getEdge(inc_edge_A)\n",
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" out_edge_A = net.getEdge(out_edge_A)\n",
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" for conn in inc_edge_A.getConnections(out_edge_A):\n",
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" index = conn.getTLLinkIndex()\n",
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" if index >= 0:\n",
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" node2init[node_id][index] = 'r'\n",
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"\n",
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" if pd.isna(inc_edge_B) or pd.isna(out_edge_B):\n",
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" pass\n",
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" else:\n",
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" inc_edge_B = net.getEdge(inc_edge_B)\n",
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" out_edge_B = net.getEdge(out_edge_B)\n",
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" for conn in inc_edge_B.getConnections(out_edge_B):\n",
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" index = conn.getTLLinkIndex()\n",
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" if index >= 0:\n",
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" node2init[node_id][index] = 'r'\n",
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" return node2init"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 7,
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"metadata": {},
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"outputs": [],
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"source": [
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"def make_sigtable(histids, node2init, net):\n",
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" sigtable = histids.copy()\n",
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" sigtable['init_state'] = sigtable['node_id'].map(node2init)\n",
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" sigtable['state'] = sigtable['init_state'].map(lambda x:''.join(x))\n",
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" for i, row in sigtable.iterrows():\n",
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" node_id = row.node_id\n",
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" inc_edge_A = row.inc_edge_A\n",
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" inc_edge_B = row.inc_edge_B\n",
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" out_edge_A = row.out_edge_A\n",
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" out_edge_B = row.out_edge_B\n",
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" state = copy.deepcopy(node2init)[node_id]\n",
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" if pd.isna(inc_edge_A) or pd.isna(out_edge_A):\n",
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" pass\n",
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" else:\n",
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" inc_edge_A = net.getEdge(inc_edge_A)\n",
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" out_edge_A = net.getEdge(out_edge_A)\n",
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" for conn in inc_edge_A.getConnections(out_edge_A):\n",
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" index = conn.getTLLinkIndex()\n",
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" if index >= 0:\n",
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" state[index] = 'G'\n",
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" sigtable.at[i, 'state'] = ''.join(state)\n",
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"\n",
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" if pd.isna(inc_edge_B) or pd.isna(out_edge_B):\n",
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" pass\n",
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" else:\n",
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" inc_edge_B = net.getEdge(inc_edge_B)\n",
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" out_edge_B = net.getEdge(out_edge_B)\n",
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" for conn in inc_edge_B.getConnections(out_edge_B):\n",
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" index = conn.getTLLinkIndex()\n",
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" if index >= 0:\n",
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" state[index] = 'G'\n",
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" sigtable.at[i, 'state'] = ''.join(state)\n",
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" sigtable = sigtable.dropna(subset='state')\n",
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" sigtable = sigtable.reset_index(drop=True)\n",
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" sigtable['phase_sumo'] = sigtable.groupby(['node_id', 'start_unix']).cumcount()\n",
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" # sigtable = sigtable[sigtable.start_unix >= sigtable_start]\n",
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" sigtable = sigtable[['node_id', 'start_unix', 'phase_sumo', 'duration', 'state']]\n",
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" sigtable = sigtable.sort_values(by=['start_unix', 'node_id'])\n",
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" sigtable['start_dt'] = sigtable['start_unix'].apply(lambda x:datetime.fromtimestamp(x))\n",
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" return sigtable"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 8,
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"metadata": {},
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"outputs": [],
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"source": [
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"def make_Sigtable(sigtable):\n",
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" Sigtable = []\n",
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" for node_id, group in sigtable.groupby('node_id'):\n",
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" new_rows_list = []\n",
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" for i in range(1, len(group)):\n",
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" prev_row = group.iloc[i-1:i].copy()\n",
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" next_row = group.iloc[i:i+1].copy()\n",
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" new_rows = pd.concat([prev_row, prev_row, next_row]).reset_index(drop=True)\n",
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" new_rows.loc[0, 'phase_sumo'] = str(prev_row.phase_sumo.iloc[0]) + '_g'\n",
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" new_rows.loc[0, 'duration'] = new_rows.loc[0, 'duration'] - 5\n",
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" new_rows.loc[1, 'phase_sumo'] = str(prev_row.phase_sumo.iloc[0]) + '_y'\n",
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" new_rows.loc[1, 'duration'] = 4\n",
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" yellow_state = ''\n",
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" red_state = ''\n",
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" for a, b in zip(prev_row.state.iloc[0], next_row.state.iloc[0]):\n",
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" if a == 'G' and b == 'r':\n",
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" yellow_state += 'y'\n",
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" red_state += 'r'\n",
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" else:\n",
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" yellow_state += a\n",
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" red_state += a\n",
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" new_rows.loc[2, 'phase_sumo'] = str(next_row.phase_sumo.iloc[0]) + '__r'\n",
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" new_rows.loc[2, 'duration'] = 1\n",
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" new_rows.loc[1, 'state'] = yellow_state\n",
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" new_rows.loc[2, 'state'] = red_state\n",
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" new_rows_list.append(new_rows)\n",
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" next_row['phase_sumo'] = str(next_row.phase_sumo.iloc[0]) + '_g'\n",
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" next_row['duration'] -= 5\n",
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" # next_row.loc['duration'] -= 5\n",
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" new_rows_list.append(next_row)\n",
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" new_rows = pd.concat(new_rows_list)\n",
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" Sigtable.append(new_rows)\n",
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" Sigtable = pd.concat(Sigtable).sort_values(by=['node_id', 'start_unix', 'phase_sumo']).reset_index(drop=True)\n",
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" return Sigtable"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 9,
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"metadata": {},
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"outputs": [],
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"source": [
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"# # sigtable 시작시각 : 현재시각 - 1200 = 08:25\n",
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"# # 시뮬레이션 시작시각 : 현재시각 - 900 = 08:30\n",
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"# # 시뮬레이션 종료시각 : 현재시각 - 600 = 08:35\n",
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"# # 현재시각 : 08:45\n",
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"# print(datetime.fromtimestamp(sigtable_start))\n",
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"# print(datetime.fromtimestamp(sim_start))\n",
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"# print(datetime.fromtimestamp(sim_end))\n",
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"# print(datetime.fromtimestamp(present_time))"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 10,
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"metadata": {},
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"outputs": [],
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"source": [
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"def make_SIGTABLE(Sigtable, sim_start, sim_end):\n",
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" offsets = {}\n",
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" SIGTABLE = []\n",
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" for node_id, group in Sigtable.groupby('node_id'):\n",
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" lsbs = group[group['start_unix'] < sim_start]['start_unix'].max() # the last start_unix before sim_start\n",
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" offsets[node_id] = lsbs - sim_start\n",
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" group = group[(group['start_unix'] < sim_end) & (group['start_unix'] >= lsbs)]\n",
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" SIGTABLE.append(group)\n",
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" SIGTABLE = pd.concat(SIGTABLE)\n",
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" return SIGTABLE, offsets\n",
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"\n",
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"def make_signals(SIGTABLE, offsets, present_time):\n",
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" strings = ['<additional>\\n']\n",
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" for node_id, group in SIGTABLE.groupby('node_id'):\n",
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" strings.append(f' <tlLogic id=\"{node_id}\" type=\"static\" programID=\"{node_id}_prog\" offset=\"{offsets[node_id]}\">\\n')\n",
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" for i, row in group.iterrows():\n",
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" duration = row.duration\n",
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" state = row.state\n",
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" strings.append(f' <phase duration=\"{duration}\" state=\"{state}\"/>\\n')\n",
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" strings.append(' </tlLogic>\\n')\n",
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" strings.append('</additional>')\n",
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" strings = ''.join(strings)\n",
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" # 저장\n",
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" path_output = f'../../Data/networks/sn_{present_time}.add.xml'\n",
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" with open(path_output, 'w') as f:\n",
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" f.write(strings)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 11,
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"metadata": {},
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"outputs": [],
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"source": [
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"def generate_signals(m):\n",
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" midnight = int(datetime(2024, 1, 5, 0, 0, 0).timestamp())\n",
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" next_day = int(datetime(2024, 1, 6, 0, 0, 0).timestamp())\n",
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" fmins = range(midnight, next_day, 300)\n",
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"\n",
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" # 현재시각\n",
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" present_time = fmins[m]\n",
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" sigtable_start = fmins[m] - 1200\n",
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" sim_start = fmins[m] - 900\n",
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" sim_end = fmins[m] - 600\n",
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" \n",
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" # network and dataframes\n",
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" net = sumolib.net.readNet('../../Data/networks/sn.net.xml')\n",
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" inter_node = pd.read_csv('../../data/tables/inter_node.csv', index_col=0)\n",
|
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" match6 = pd.read_csv('../../Data/tables/matching/match6.csv', index_col=0)\n",
|
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" match6 = match6[['node_id', 'phase_no', 'ring_type', 'inc_edge', 'out_edge']].reset_index(drop=True)\n",
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" histid = pd.read_csv(f'../../Data/tables/histids/histids_{present_time}.csv', index_col=0)\n",
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" histid = histid.reset_index(drop=True).drop(columns=['inter_no'])\n",
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" \n",
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" # helper dictionaries\n",
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" inter2node = dict(zip(inter_node['inter_no'], inter_node['node_id']))\n",
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" node2inter = dict(zip(inter_node['node_id'], inter_node['inter_no']))\n",
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" pa2ch = {'i0':['u00'], 'i1':[], 'i2':['u20'], 'i3':['c30', 'u30', 'u31', 'u32'], 'i6':['u60'], 'i7':[], 'i8':[], 'i9':[]}\n",
|
|
" node_ids = sorted(inter_node.node_id.unique())\n",
|
|
" parent_ids = sorted(inter_node[inter_node.inter_type=='parent'].node_id.unique())\n",
|
|
" nodes = [net.getNode(node_id) for node_id in node_ids]\n",
|
|
"\n",
|
|
" # histids\n",
|
|
" histids = make_histids(histid, match6, parent_ids, pa2ch)\n",
|
|
"\n",
|
|
" # node2init\n",
|
|
" node2init = initialize_states(net, nodes, histids)\n",
|
|
"\n",
|
|
" # sigtable\n",
|
|
" sigtable = make_sigtable(histids, node2init, net)\n",
|
|
"\n",
|
|
" # Sigtable\n",
|
|
" Sigtable = make_Sigtable(sigtable)\n",
|
|
"\n",
|
|
" # SIGTABLE\n",
|
|
" SIGTABLE, offsets = make_SIGTABLE(Sigtable, sim_start, sim_end)\n",
|
|
"\n",
|
|
" make_signals(SIGTABLE, offsets, present_time)\n",
|
|
" print(f'A signal file (add.xml) has been created for the timeslot between {datetime.fromtimestamp(sim_start)} and {datetime.fromtimestamp(sim_end)}')"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 12,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"A signal file (add.xml) has been created for the timeslot between 2024-01-05 08:30:00 and 2024-01-05 08:35:00\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"generate_signals(105)"
|
|
]
|
|
}
|
|
],
|
|
"metadata": {
|
|
"kernelspec": {
|
|
"display_name": "rts",
|
|
"language": "python",
|
|
"name": "python3"
|
|
},
|
|
"language_info": {
|
|
"codemirror_mode": {
|
|
"name": "ipython",
|
|
"version": 3
|
|
},
|
|
"file_extension": ".py",
|
|
"mimetype": "text/x-python",
|
|
"name": "python",
|
|
"nbconvert_exporter": "python",
|
|
"pygments_lexer": "ipython3",
|
|
"version": "3.8.10"
|
|
}
|
|
},
|
|
"nbformat": 4,
|
|
"nbformat_minor": 2
|
|
}
|