{ "cells": [ { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [], "source": [ "import os\n", "import pandas as pd\n", "import numpy as np\n", "import sys\n", "sys.path.append('../../Scripts')\n", "from preprocess_daily import DailyPreprocessor\n", "from generate_signals import SignalGenerator" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "비보호좌회전, 신호우회전, 유턴\n", "\n", "줄임말 목록\n", "- `i` : 교차로번호, `inter_no`\n", "- `f` : 진입, from, `inc_edge_id`\n", "- `t` : 진출, to, `out_edge_id`\n", "- `vec` : 방향벡터, unit vector (`np.array([0.6, 0.8])`)\n", "- `dire` : 방위, direction (동, 서, 남, 북, 북동, 북서, 남동, 남서)\n", "- `rvec` : 정방향 방향벡터, unit vector to the right direction (`np.array([0,1])`)\n", "\n", "필요한 객체들 목록\n", "\n", "- `inter2dire2rvec` : `inter_no` $\\mapsto$ `dire2rvec`\n", " - `dire2rvec` : `dire` $\\mapsto$ `rvec`\n", "- `inter2incs` : `inter_no` $\\mapsto$ `inc_edge_ids`\n", "- `inter2outs` : `inter_no` $\\mapsto$ `out_edge_ids`\n", "- `inter2inc2dire` : `inter_no` $\\mapsto$ `int2dire`\n", " - `inc2dire` : `out_edge_id` $\\mapsto$ `dire`\n", "- `inter2out2dire` : `inter_no` $\\mapsto$ `out2dire`\n", " - `out2dire` : `inc_edge_id` $\\mapsto$ `dire`\n", "- `inter2inc2vec` : `inter_no` $\\mapsto$ `int2vec`\n", " - `inc2vec` : `out_edge_id` $\\mapsto$ `vec`\n", "- `inter2out2vec` : `inter_no` $\\mapsto$ `out2vec`\n", " - `out2vec` : `inc_edge_id` $\\mapsto$ `vec`\n", "\n", "좌회전 판단\n", "\n", "Given `inter_no`, `inc_edge_id` and `out_edge_id`, we have `inc_vec = inter2inc2vec[inter_no][inc_edge_id]` and `out_vec = inter2out2vec[inter_no][out_edge_id]`.\n", "Rotate `inc_vec` by 90, 180 and 270 degrees clockwise, to define \n", "`out_vec_left`, `out_vec_straight` and `out_vec_right`.\n", "Define `out_vecs={'right':out_vec_left, 'straight':out_vec_straight, 'right':out_vec_right}`.\n", "Select the key that maximize the similarity of the corresponding value of the key and `inc_vec`." ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "1. 데이터를 로드합니다.\n", "1-1. 네트워크가 로드되었습니다.\n", "1-2. 테이블들이 로드되었습니다.\n", "1-3. 네트워크의 모든 clean state requirement들을 체크했습니다.\n", "1-4. 테이블들의 무결성 검사를 완료했습니다.\n", "1-5. 주요 객체 (리스트, 딕셔너리)들을 저장했습니다.\n" ] }, { "data": { "text/html": [ "
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" ], "text/plain": [ " parent_id child_id adj_inc_edge_id adj_out_edge_id inc_edge_id \\\n", "0 i0 u00 -571500487_01 571500487_01 571500487_02 \n", "1 i2 u20 571542811_02 571542811_01 571542810_01.51 \n", "2 i3 u30 571556450_02 571556450_01 571556452_01 \n", "3 i3 u31 -571500475_01 571500475_01 571500475_02 \n", "4 i3 u32 571540303_02.21 571540303_01 571540303_02 \n", "5 i6 u60 571500535_02.18 571500535_01 571500535_02 \n", "\n", " out_edge_id \n", "0 571500487_01.32 \n", "1 571542810_02 \n", "2 571556452_02 \n", "3 571500475_01.26 \n", "4 -571540303_02 \n", "5 -571500535_02 " ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "self = DailyPreprocessor()\n", "self.load_data()\n", "self.make_match1()\n", "self.make_match2()\n", "self.make_match3()\n", "self.make_match4()\n", "self.make_match5()\n", "display(self.u_turn)" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [], "source": [ "self.u_turn = pd.merge(self.u_turn, self.u_condition, on='child_id')\n", "\n", "# p2inc_edge2angle : node_id to inc_edge2angle\n", "p2inc_edge2angle = dict()\n", "# p2out_edge2angle : node_id to out_edge2angle\n", "p2out_edge2angle = dict()\n", "# p2inc_angle2edge : node_id to inc_angle2edge\n", "p2inc_angle2edge = dict()\n", "# p2out_angle2edge : node_id to out_angle2edge\n", "p2out_angle2edge = dict()\n", "for node_id in self.parent_ids:\n", " m5 = self.match5[self.match5.node_id==node_id]\n", " m5 = m5.dropna(subset=['inc_edge_id', 'out_edge_id'])\n", " # inc_edge2angle : inc_edge_id to inc_angle\n", " inc_edge2angle = dict(zip(m5.inc_edge_id, m5.inc_angle.astype(int)))\n", " p2inc_edge2angle[node_id] = inc_edge2angle\n", " # out_edge2angle : out_edge_id to out_angle\n", " out_edge2angle = dict(zip(m5.out_edge_id, m5.out_angle.astype(int)))\n", " p2out_edge2angle[node_id] = out_edge2angle\n", " # inc_angle2edge : inc_angle to inc_edge_id\n", " inc_angle2edge = dict(zip(m5.inc_angle.astype(int), m5.inc_edge_id))\n", " p2inc_angle2edge[node_id] = inc_angle2edge\n", " # out_angle2edge : out_angle to out_edge_id\n", " out_angle2edge = dict(zip(m5.out_angle.astype(int), m5.out_edge_id))\n", " p2out_angle2edge[node_id] = out_angle2edge\n", "\n", "# 각 uturn node에 대하여 (inc_edge_id, out_edge_id) 부여\n", "cmatches = []\n", "for row in self.u_turn.itertuples():\n", " parent_id = row.parent_id\n", " child_id = row.child_id\n", " condition = row.condition\n", " inc_edge_id = row.inc_edge_id\n", " out_edge_id = row.out_edge_id\n", " adj_inc_edge_id = row.adj_inc_edge_id\n", " adj_out_edge_id = row.adj_out_edge_id\n", "\n", " # match5에서 부모노드id에 해당하는 행들을 가져옴 (cmatch)\n", " cmatch = self.match5.copy()[self.match5.node_id==parent_id] # match dataframe for a child node\n", " cmatch = cmatch.sort_values(by=['phase_no', 'ring_type']).reset_index(drop=True)\n", " cmatch['node_id'] = child_id\n", "\n", " # 진입엣지 각도\n", " inc_angle = p2inc_edge2angle[parent_id][adj_inc_edge_id]\n", "\n", " # 이격각도\n", " self.angle_separation = 10\n", "\n", " # 진입로 각도 목록\n", " inc_angles = cmatch.dropna(subset=['inc_angle', 'out_angle']).inc_angle.astype(int).unique()\n", " inc_angles = np.sort(inc_angles)\n", " inc_angles = list(inc_angles - 360) + list(inc_angles) + list(inc_angles + 360)\n", " inc_angles = np.array(inc_angles)\n", "\n", " # 보행신호시의 진입로 각도\n", " inc_angles_left = inc_angles[inc_angles >= inc_angle + self.angle_separation]\n", " inc_angle_pedes = np.sort(inc_angles_left)[0] % 360\n", "\n", " # 보행신호시의 진입로 엣지id\n", " inc_angle2edge = p2inc_angle2edge[parent_id]\n", " inc_edge_id_pedes = inc_angle2edge[inc_angle_pedes]\n", "\n", " # 진출로 각도 목록\n", " out_angles = cmatch.dropna(subset=['inc_angle', 'out_angle']).out_angle.astype(int).unique()\n", " out_angles = np.sort(out_angles)\n", " out_angles = list(out_angles - 360) + list(out_angles) + list(out_angles + 360)\n", " out_angles = np.array(out_angles)\n", "\n", " # 보행신호시의 진입로 각도\n", " out_angles_right = out_angles[out_angles <= inc_angle - self.angle_separation]\n", " out_angle_pedes = np.sort(out_angles_right)[-1] % 360\n", "\n", " # 보행신호시의 진입로 엣지id\n", " out_angle2edge = p2out_angle2edge[parent_id]\n", " out_edge_id_pedes = out_angle2edge[out_angle_pedes]\n", "\n", " # 진입엣지/진출엣지 포함 조건\n", " inc_true = (cmatch.inc_edge_id==adj_inc_edge_id)\n", " out_true = (cmatch.out_edge_id==adj_out_edge_id)\n", "\n", " # 보행신호시 조건\n", " pedes_flag = (cmatch.inc_edge_id==inc_edge_id_pedes) & (cmatch.out_edge_id==out_edge_id_pedes)\n", "\n", " # 좌회전시 조건\n", " right_flag = inc_true & (cmatch.turn_type=='left')\n", "\n", " # 보행신호이동류(17) 조건\n", " crosswalk_on = (cmatch.move_no==17) & ~ out_true\n", "\n", " # 신호없음이동류(18) 조건\n", " all_redsigns = (cmatch.move_no==18) & ~ out_true\n", "\n", " # 보행신호시/좌회전시 진입/진출 엣지id 배정\n", " cmatch[['inc_edge_id', 'out_edge_id']] = np.nan\n", " if condition == \"보행신호시\":\n", " cmatch.loc[pedes_flag, ['inc_edge_id', 'out_edge_id']] = [inc_edge_id, out_edge_id]\n", " elif condition == \"좌회전시\":\n", " cmatch.loc[right_flag, ['inc_edge_id', 'out_edge_id']] = [inc_edge_id, out_edge_id]\n", "\n", " uturn_not_assigned = cmatch[['inc_edge_id','out_edge_id']].isna().any(axis=1).all()\n", "\n", " if uturn_not_assigned:\n", " # 보행신호시\n", " if pedes_flag.any():\n", " cmatch.loc[pedes_flag, ['inc_edge_id', 'out_edge_id']] = [inc_edge_id, out_edge_id]\n", " # 좌회전시\n", " elif right_flag.any():\n", " cmatch.loc[right_flag, ['inc_edge_id', 'out_edge_id']] = [inc_edge_id, out_edge_id]\n", " # 보행신호이동류(17) 발생시\n", " elif crosswalk_on.any():\n", " cmatch.loc[crosswalk_on, ['inc_edge_id', 'out_edge_id']] = [inc_edge_id, out_edge_id]\n", " # 신호없음이동류(18) 발생시\n", " elif all_redsigns.any():\n", " cmatch.loc[all_redsigns, ['inc_edge_id', 'out_edge_id']] = [inc_edge_id, out_edge_id]\n", " # 진출엣지 미포함시\n", " elif out_true.any():\n", " cmatch.loc[~ out_true, ['inc_edge_id', 'out_edge_id']] = [inc_edge_id, out_edge_id]" ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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642105서북571500535_02-571500535_02u60
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" ], "text/plain": [ " inter_no move_no inc_dire out_dire inc_edge_id out_edge_id node_id\n", "64 210 5 서 북 571500535_02 -571500535_02 u60" ] }, "execution_count": 52, "metadata": {}, "output_type": "execute_result" } ], "source": [ "self.matching[self.matching.node_id=='u60']" ] }, { "cell_type": "code", "execution_count": 43, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "ggggggggg\n", "ggggrgggg\n", "ggggrgggg\n" ] } ], "source": [ "NODE_ID = 'u00'\n", "self.nodes = [self.net.getNode(node_id) for node_id in self.node_ids]\n", "self.node2init = {}\n", "# 모든 노드들을 순회\n", "for node in self.nodes:\n", " node_id = node.getID()\n", " # 모든 connection\n", " conns = [(c.getJunctionIndex(), c) for c in node.getConnections()]\n", " conns = [c for c in conns if c[0] >= 0]\n", " conns = sorted(conns, key=lambda x: x[0])\n", " state = []\n", " # i번째 connection : ci\n", " for i, ci in conns:\n", " if ci.getTLLinkIndex() < 0:\n", " continue\n", " are_foes = False\n", " # j번째 connection : cj\n", " # 합류지점이 다르면서 상충되는 cj가 존재하면 are_foes = True (r)\n", " # 그외의 경우에는 are_foes = False (g)\n", " for j, cj in conns:\n", " # ci, cj의 합류지점이 같으면 통과\n", " if ci.getTo() == cj.getTo():\n", " continue\n", " # ci, cj가 상충되면 are_foes를 True로 지정.\n", " if node.areFoes(i, j):\n", " are_foes = True\n", " break\n", " state.append('r' if are_foes else 'g')\n", " self.node2init[node_id] = state\n", "print(''.join(self.node2init[NODE_ID]))\n", "\n", "# 어떤 연결과도 상충이 일어나지는 않지만, 신호가 부여되어 있는 경우에는 r을 부여\n", "for _, row in self.matching.iterrows():\n", " node_id = row.node_id\n", " move_no = row.move_no\n", " inc_edge_id = row.inc_edge_id\n", " out_edge_id = row.out_edge_id\n", " if move_no != 21:\n", " inc_edge = self.net.getEdge(inc_edge_id)\n", " out_edge = self.net.getEdge(out_edge_id)\n", " for conn in inc_edge.getConnections(out_edge):\n", " index = conn.getTLLinkIndex()\n", " if index >= 0:\n", " self.node2init[node_id][index] = 'r'\n", "print(''.join(self.node2init[NODE_ID]))\n", "\n", "# 유턴교차로\n", "for _, row in self.u_turn.iterrows():\n", " node_id = row.child_id\n", " inc_edge_id = row.inc_edge_id\n", " out_edge = row.out_edge_id\n", " if not (pd.isna(inc_edge_id) and pd.isna(out_edge_id)):\n", " inc_edge = self.net.getEdge(inc_edge_id)\n", " out_edge = self.net.getEdge(out_edge_id)\n", " for conn in inc_edge.getConnections(out_edge):\n", " index = conn.getTLLinkIndex()\n", " if index >= 0:\n", " self.node2init[node_id][index] = 'r'\n", "print(''.join(self.node2init[NODE_ID]))\n", "\n" ] }, { "cell_type": "code", "execution_count": 22, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "2-2. 비보호우회전(g)을 배정했습니다.\n" ] }, { "data": { "text/plain": [ "['g', 'g', 'g', 'g', 'g', 'g']" ] }, "execution_count": 22, "metadata": {}, "output_type": "execute_result" } ], "source": [ "self.initialize_state()\n", "\n", "self.node2init['u20']" ] }, { "cell_type": "code", "execution_count": 131, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "['r', 'r', 'g', 'g', 'r', 'r', 'r']" ] }, "execution_count": 131, "metadata": {}, "output_type": "execute_result" } ], "source": [ "self.node2init['i2']" ] }, { "cell_type": "code", "execution_count": 132, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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inter_nonode_idphase_noring_typemove_noinc_edge_idout_edge_idstate
0175i01A8-571542797_02571500487_01grrrgrrrgGGGGrgrr
1175i01B4-571500487_01571542797_02gGGrgrrrgrrrrrgrr
2175i02A7-571500487_01571545870_01grrGgrrrgrrrrrgrr
3175i02B3-571542797_02571510153_01grrrgrrrgrrrrGgrr
4175i03A6571545870_02571510153_01grrrgGGrgrrrrrgrr
5175i03B1571545870_02571542797_02grrrgrrGgrrrrrgrr
6175i04A5571510153_02571500487_01grrrgrrrgrrrrrgrG
7175i04B2571510153_02571545870_01grrrgrrrgrrrrrgGr
8175u001A8NaNNaNggggrgggg
9175u001B4NaNNaNggggrgggg
10175u002A7571500487_02571500487_01.32ggggGgggg
11175u002B3NaNNaNggggrgggg
12175u003A6NaNNaNggggrgggg
13175u003B1NaNNaNggggrgggg
14175u004A5NaNNaNggggrgggg
15175u004B2NaNNaNggggrgggg
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" ], "text/plain": [ " inter_no node_id phase_no ring_type move_no inc_edge_id \\\n", "0 175 i0 1 A 8 -571542797_02 \n", "1 175 i0 1 B 4 -571500487_01 \n", "2 175 i0 2 A 7 -571500487_01 \n", "3 175 i0 2 B 3 -571542797_02 \n", "4 175 i0 3 A 6 571545870_02 \n", "5 175 i0 3 B 1 571545870_02 \n", "6 175 i0 4 A 5 571510153_02 \n", "7 175 i0 4 B 2 571510153_02 \n", "8 175 u00 1 A 8 NaN \n", "9 175 u00 1 B 4 NaN \n", "10 175 u00 2 A 7 571500487_02 \n", "11 175 u00 2 B 3 NaN \n", "12 175 u00 3 A 6 NaN \n", "13 175 u00 3 B 1 NaN \n", "14 175 u00 4 A 5 NaN \n", "15 175 u00 4 B 2 NaN \n", "\n", " out_edge_id state \n", "0 571500487_01 grrrgrrrgGGGGrgrr \n", "1 571542797_02 gGGrgrrrgrrrrrgrr \n", "2 571545870_01 grrGgrrrgrrrrrgrr \n", "3 571510153_01 grrrgrrrgrrrrGgrr \n", "4 571510153_01 grrrgGGrgrrrrrgrr \n", "5 571542797_02 grrrgrrGgrrrrrgrr \n", "6 571500487_01 grrrgrrrgrrrrrgrG \n", "7 571545870_01 grrrgrrrgrrrrrgGr \n", "8 NaN ggggrgggg \n", "9 NaN ggggrgggg \n", "10 571500487_01.32 ggggGgggg \n", "11 NaN ggggrgggg \n", "12 NaN ggggrgggg \n", "13 NaN ggggrgggg \n", "14 NaN ggggrgggg \n", "15 NaN ggggrgggg " ] }, "execution_count": 132, "metadata": {}, "output_type": "execute_result" } ], "source": [ "self.match6[self.match6.node_id.isin(['i0', 'u00'])]" ] }, { "cell_type": "code", "execution_count": 127, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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inter_nonode_idphase_noring_typemove_noinc_edge_idout_edge_idstate
22177i21A8-571542809_01571542811_01rrggGGG
23177i21B4571542811_02571542809_01GGggrrr
24177i22A17NaNNaNrrggrrr
25177i22B18NaNNaNrrggrrr
26177u201A8NaNNaNgggggg
27177u201B4NaNNaNgggggg
28177u202A17571542810_01.51571542810_02ggGggg
29177u202B18NaNNaNgggggg
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" ], "text/plain": [ " inter_no node_id phase_no ring_type move_no inc_edge_id \\\n", "22 177 i2 1 A 8 -571542809_01 \n", "23 177 i2 1 B 4 571542811_02 \n", "24 177 i2 2 A 17 NaN \n", "25 177 i2 2 B 18 NaN \n", "26 177 u20 1 A 8 NaN \n", "27 177 u20 1 B 4 NaN \n", "28 177 u20 2 A 17 571542810_01.51 \n", "29 177 u20 2 B 18 NaN \n", "\n", " out_edge_id state \n", "22 571542811_01 rrggGGG \n", "23 571542809_01 GGggrrr \n", "24 NaN rrggrrr \n", "25 NaN rrggrrr \n", "26 NaN gggggg \n", "27 NaN gggggg \n", "28 571542810_02 ggGggg \n", "29 NaN gggggg " ] }, "execution_count": 127, "metadata": {}, "output_type": "execute_result" } ], "source": [ "self.match6[self.match6.node_id.isin(['i2', 'u20'])]" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "'''Given `inter_no`, `inc_edge_id` and `out_edge_id`, we have `inc_vec = inter2inc2vec[inter_no][inc_edge_id]` and `out_vec = inter2out2vec[inter_no][out_edge_id]`.\n", "Rotate `inc_vec` by 90, 180 and 270 degrees clockwise, to define \n", "`out_vec_left`, `out_vec_straight` and `out_vec_right`.\n", "Define `out_vecs={'right':out_vec_left, 'straight':out_vec_straight, 'right':out_vec_right}`.\n", "Select the key that maximize the similarity of the corresponding value of the key and `inc_vec`.'''" ] } ], "metadata": { "kernelspec": { "display_name": "sts", "language": "python", "name": "sts" }, "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 }