1155 lines
58 KiB
Python
1155 lines
58 KiB
Python
# -*- coding: utf-8 -*-
|
||
# @Author: Owl
|
||
# @Date: 2025/10/10 19:51
|
||
# @Description: 路口评价相关的公共函数
|
||
import copy
|
||
import json
|
||
import logging
|
||
|
||
import requests
|
||
from google.protobuf.json_format import MessageToJson
|
||
|
||
import proto.xlcomm_pb2 as pb
|
||
from app.common_worker import *
|
||
from proto.phase_grpc import QueryCrossRunningPhase
|
||
|
||
src_reverse = {'N': 'S', 'S': 'N', 'W': 'E', 'E': 'W', 'NE': 'SW', 'SW': 'NE', 'SE': 'NW', 'NW': 'SE'}
|
||
|
||
dir_str_dict = {
|
||
'E': '东', 'S': '南', 'W': '西', 'N': '北', 'NE': '东北', 'SE': '东南', 'SW': '西南', 'NW': '西北'
|
||
}
|
||
|
||
int_turn_type2str = {
|
||
0: '直行',
|
||
1: '左转',
|
||
2: '右转',
|
||
3: '掉头'
|
||
}
|
||
|
||
int_internet_code2str = {
|
||
0: '无',
|
||
1: '联网',
|
||
2: '脱机',
|
||
3: '未接入'
|
||
}
|
||
|
||
int_cross_model2str = {
|
||
'1': '快',
|
||
'2': '主',
|
||
'3': '次',
|
||
'4': '支'
|
||
}
|
||
|
||
|
||
def gen_avg_cross_delay_pb(cross_delay_data_list):
|
||
"""
|
||
路口评价指标数据聚合
|
||
:param cross_delay_data_list:
|
||
:return:
|
||
"""
|
||
cross_delay_pb_list = []
|
||
for item in cross_delay_data_list:
|
||
item_delay_pb = pb.xl_cross_delayinfo_t()
|
||
item_delay_pb.ParseFromString(item['data'])
|
||
cross_delay_pb_list.append(item_delay_pb)
|
||
avg_cross_delay = None
|
||
if len(cross_delay_pb_list) == 0:
|
||
return avg_cross_delay
|
||
elif len(cross_delay_pb_list) == 1:
|
||
avg_cross_delay = cross_delay_pb_list[0]
|
||
return avg_cross_delay
|
||
avg_cross_delay = pb.xl_cross_delayinfo_t()
|
||
avg_cross_delay.crossid = cross_delay_pb_list[0].crossid
|
||
avg_cross_delay.tp.start_hm = cross_delay_pb_list[0].tp.start_hm
|
||
avg_cross_delay.tp.end_hm = cross_delay_pb_list[0].tp.end_hm
|
||
avg_cross_delay.tp.weekday = cross_delay_pb_list[0].tp.weekday
|
||
avg_cross_delay.tp.type = cross_delay_pb_list[0].tp.type
|
||
avg_cross_delay.daynum = 0
|
||
sum_car_num, delay_time, stop_times, queue_len, speed, jam_index, park_time, std_flow, high_park_percent, truck_percent, park_percent, move_speed, imbalance_index\
|
||
= 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
|
||
# 路口延误数据指标聚合逻辑
|
||
for item in cross_delay_pb_list:
|
||
item_delay_info = item.delay_info
|
||
item_car_num = item_delay_info.car_num
|
||
if item_car_num != 0:
|
||
sum_car_num += item_car_num
|
||
delay_time += item_delay_info.delay_time * item_car_num
|
||
stop_times += item_delay_info.stop_times * item_car_num
|
||
queue_len += item_delay_info.queue_len * item_car_num
|
||
speed += item_delay_info.speed * item_car_num
|
||
jam_index += item_delay_info.jam_index * item_car_num
|
||
park_time += item_delay_info.park_time * item_car_num
|
||
high_park_percent += item_delay_info.high_park_percent * item_car_num
|
||
truck_percent += item_delay_info.truck_percent * item_car_num
|
||
park_percent += item_delay_info.park_percent * item_car_num
|
||
move_speed += item_delay_info.move_speed * item_car_num
|
||
# imbalance_index += item_delay_info.imbalance_index * item_car_num
|
||
std_flow += item_delay_info.std_flow
|
||
|
||
avg_cross_delay.delay_info.car_num = sum_car_num
|
||
avg_cross_delay.delay_info.delay_time = int(delay_time / sum_car_num)
|
||
avg_cross_delay.delay_info.stop_times = stop_times / sum_car_num
|
||
avg_cross_delay.delay_info.queue_len = int(queue_len / sum_car_num)
|
||
avg_cross_delay.delay_info.speed = int(speed / sum_car_num)
|
||
avg_cross_delay.delay_info.jam_index = jam_index / sum_car_num
|
||
avg_cross_delay.delay_info.park_time = int(park_time / sum_car_num)
|
||
avg_cross_delay.delay_info.high_park_percent = int(high_park_percent / sum_car_num)
|
||
avg_cross_delay.delay_info.truck_percent = int(truck_percent / sum_car_num)
|
||
avg_cross_delay.delay_info.park_percent = int(park_percent / sum_car_num)
|
||
avg_cross_delay.delay_info.move_speed = int(move_speed / sum_car_num)
|
||
# avg_cross_delay.delay_info.imbalance_index = imbalance_index / sum_car_num
|
||
avg_cross_delay.delay_info.std_flow = int(std_flow / len(cross_delay_pb_list))
|
||
|
||
# 进口道延误数据聚合处理逻辑
|
||
inroad_delay_info_dict = {}
|
||
for item in cross_delay_pb_list:
|
||
inroad_delay_infos = item.inroad_delay_infos
|
||
for inroad_item in inroad_delay_infos:
|
||
inroadid = inroad_item.inroadid
|
||
if inroadid not in inroad_delay_info_dict:
|
||
inroad_delay_info_dict[inroadid] = [inroad_item]
|
||
else:
|
||
inroad_delay_info_dict[inroadid].append(inroad_item)
|
||
flow_delay_list, inroad_delay_pb_list = [], []
|
||
flow_delay_info_dict = {}
|
||
max_stop_times, min_stop_times = 0, 99999
|
||
for inroadid in inroad_delay_info_dict.keys():
|
||
road_delay_infos = inroad_delay_info_dict[inroadid]
|
||
inroad_sum_car_num, inroad_delay_time, inroad_stop_times, inroad_queue_len, inroad_speed, inroad_jam_index, inroad_park_time, inroad_high_park_percent, inroad_truck_percent, inroad_park_percent, inroad_move_speed, inroad_imbalance_index, inroad_std_flow, inroad_travel_time\
|
||
= 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
|
||
ffs, capacity = road_delay_infos[0].delay_info.ffs, road_delay_infos[0].delay_info.capacity
|
||
turn_ratio_0, turn_ratio_1, turn_ratio_2, turn_ratio_3 = 0, 0, 0, 0
|
||
for road_delay_info in road_delay_infos:
|
||
inroad_sum_car_num += road_delay_info.delay_info.car_num
|
||
inroad_delay_time += road_delay_info.delay_info.delay_time * road_delay_info.delay_info.car_num
|
||
inroad_stop_times += road_delay_info.delay_info.stop_times * road_delay_info.delay_info.car_num
|
||
inroad_queue_len += road_delay_info.delay_info.queue_len * road_delay_info.delay_info.car_num
|
||
inroad_speed += road_delay_info.delay_info.speed * road_delay_info.delay_info.car_num
|
||
inroad_jam_index += road_delay_info.delay_info.jam_index * road_delay_info.delay_info.car_num
|
||
inroad_park_time += road_delay_info.delay_info.park_time * road_delay_info.delay_info.car_num
|
||
inroad_high_park_percent += road_delay_info.delay_info.high_park_percent * road_delay_info.delay_info.car_num
|
||
inroad_truck_percent += road_delay_info.delay_info.truck_percent * road_delay_info.delay_info.car_num
|
||
inroad_park_percent += road_delay_info.delay_info.park_percent * road_delay_info.delay_info.car_num
|
||
inroad_move_speed += road_delay_info.delay_info.move_speed * road_delay_info.delay_info.car_num
|
||
inroad_travel_time += road_delay_info.delay_info.travel_time * road_delay_info.delay_info.car_num
|
||
# inroad_imbalance_index += delay_info.imbalance_index * delay_info.car_num
|
||
inroad_std_flow += road_delay_info.delay_info.std_flow
|
||
turn_ratio_0 += road_delay_info.delay_info.turn_ratio_0
|
||
turn_ratio_1 += road_delay_info.delay_info.turn_ratio_1
|
||
turn_ratio_2 += road_delay_info.delay_info.turn_ratio_2
|
||
turn_ratio_3 += road_delay_info.delay_info.turn_ratio_3
|
||
# 流向级别数据指标聚合处理逻辑
|
||
flow_delay_infos = road_delay_info.flow_delay_infos
|
||
flow_delay_list.extend(flow_delay_infos)
|
||
inroad_delay_info = pb.xl_inroad_delayinfo_t()
|
||
inroad_delay_info.inroadid = inroadid
|
||
inroad_delay_info.delay_info.ffs = ffs
|
||
inroad_delay_info.delay_info.capacity = capacity
|
||
inroad_delay_info.delay_info.car_num = inroad_sum_car_num
|
||
inroad_delay_info.delay_info.delay_time = int(inroad_delay_time / inroad_sum_car_num)
|
||
inroad_delay_info.delay_info.stop_times = inroad_stop_times / inroad_sum_car_num
|
||
if stop_times > max_stop_times:
|
||
max_stop_times = stop_times
|
||
if stop_times < min_stop_times:
|
||
min_stop_times = stop_times
|
||
inroad_delay_info.delay_info.queue_len = int(inroad_queue_len / inroad_sum_car_num)
|
||
inroad_delay_info.delay_info.speed = int(inroad_speed / inroad_sum_car_num)
|
||
inroad_delay_info.delay_info.jam_index = inroad_jam_index / inroad_sum_car_num
|
||
inroad_delay_info.delay_info.park_time = int(inroad_park_time / inroad_sum_car_num)
|
||
inroad_delay_info.delay_info.high_park_percent = int(inroad_high_park_percent / inroad_sum_car_num)
|
||
inroad_delay_info.delay_info.truck_percent = int(inroad_truck_percent / inroad_sum_car_num)
|
||
inroad_delay_info.delay_info.park_percent = int(inroad_park_percent / inroad_sum_car_num)
|
||
inroad_delay_info.delay_info.move_speed = int(inroad_move_speed / inroad_sum_car_num)
|
||
inroad_delay_info.delay_info.travel_time = int(inroad_travel_time / inroad_sum_car_num)
|
||
# inroad_delay_info.delay_info.imbalance_index = inroad_imbalance_index / inroad_sum_car_num
|
||
inroad_delay_info.delay_info.std_flow = int(inroad_std_flow / len(road_delay_infos))
|
||
inroad_delay_info.delay_info.turn_ratio_0 = turn_ratio_0
|
||
inroad_delay_info.delay_info.turn_ratio_1 = turn_ratio_1
|
||
inroad_delay_info.delay_info.turn_ratio_2 = turn_ratio_2
|
||
inroad_delay_info.delay_info.turn_ratio_3 = turn_ratio_3
|
||
inroad_delay_pb_list.append(inroad_delay_info)
|
||
cross_imbalance_index = round((max_stop_times - min_stop_times) / avg_cross_delay.delay_info.stop_times, 2) if avg_cross_delay.delay_info.stop_times != 0 else 0
|
||
avg_cross_delay.delay_info.imbalance_index = cross_imbalance_index
|
||
|
||
for flow_delay_info in flow_delay_list:
|
||
xlink_id = flow_delay_info.xlink_id
|
||
if xlink_id not in flow_delay_info_dict:
|
||
flow_delay_info_dict[xlink_id] = [flow_delay_info]
|
||
else:
|
||
flow_delay_info_dict[xlink_id].append(flow_delay_info)
|
||
for xlink_id in flow_delay_info_dict.keys():
|
||
flow_delay_infos = flow_delay_info_dict[xlink_id]
|
||
inroadid = flow_delay_infos[0].inroadid
|
||
turn_type = flow_delay_infos[0].turn_type
|
||
flow_sum_car_num, flow_delay_time, flow_stop_times, flow_queue_len, flow_speed, flow_jam_index, flow_park_time, flow_high_park_percent, flow_truck_percent, flow_park_percent, flow_move_speed, flow_imbalance_index, flow_std_flow, flow_travel_time \
|
||
= 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
|
||
for flow_delay_info in flow_delay_infos:
|
||
flow_sum_car_num += flow_delay_info.delay_info.car_num
|
||
flow_delay_time += flow_delay_info.delay_info.delay_time * flow_delay_info.delay_info.car_num
|
||
flow_stop_times += flow_delay_info.delay_info.stop_times * flow_delay_info.delay_info.car_num
|
||
flow_queue_len += flow_delay_info.delay_info.queue_len * flow_delay_info.delay_info.car_num
|
||
flow_travel_time += flow_delay_info.delay_info.travel_time * flow_delay_info.delay_info.car_num
|
||
flow_speed += flow_delay_info.delay_info.speed * flow_delay_info.delay_info.car_num
|
||
flow_jam_index += flow_delay_info.delay_info.jam_index * flow_delay_info.delay_info.car_num
|
||
flow_park_time += flow_delay_info.delay_info.park_time * flow_delay_info.delay_info.car_num
|
||
flow_high_park_percent += flow_delay_info.delay_info.high_park_percent * flow_delay_info.delay_info.car_num
|
||
flow_truck_percent += flow_delay_info.delay_info.truck_percent * flow_delay_info.delay_info.car_num
|
||
flow_park_percent += flow_delay_info.delay_info.park_percent * flow_delay_info.delay_info.car_num
|
||
flow_move_speed += flow_delay_info.delay_info.move_speed * flow_delay_info.delay_info.car_num
|
||
# flow_imbalance_index += flow_delay_info.delay_info.imbalance_index * flow_delay_info.delay_info.car_num
|
||
flow_std_flow += flow_delay_info.delay_info.std_flow
|
||
flow_info = pb.xl_flow_delayinfo_t()
|
||
flow_info.xlink_id = xlink_id
|
||
flow_info.inroadid = inroadid
|
||
flow_info.turn_type = turn_type
|
||
flow_info.delay_info.car_num = flow_sum_car_num
|
||
flow_info.delay_info.delay_time = int(flow_delay_time / flow_sum_car_num)
|
||
flow_info.delay_info.stop_times = flow_stop_times / flow_sum_car_num
|
||
flow_info.delay_info.queue_len = int(flow_queue_len / flow_sum_car_num)
|
||
flow_info.delay_info.speed = int(flow_speed / flow_sum_car_num)
|
||
flow_info.delay_info.travel_time = int(flow_travel_time / flow_sum_car_num)
|
||
flow_info.delay_info.jam_index = flow_jam_index / flow_sum_car_num
|
||
flow_info.delay_info.park_time = int(flow_park_time / flow_sum_car_num)
|
||
flow_info.delay_info.high_park_percent = int(flow_high_park_percent / flow_sum_car_num)
|
||
flow_info.delay_info.truck_percent = int(flow_truck_percent / flow_sum_car_num)
|
||
flow_info.delay_info.park_percent = int(flow_park_percent / flow_sum_car_num)
|
||
flow_info.delay_info.move_speed = int(flow_move_speed / flow_sum_car_num)
|
||
# flow_info.delay_info.imbalance_index = flow_imbalance_index / flow_sum_car_num
|
||
flow_info.delay_info.std_flow = int(flow_std_flow / len(flow_delay_infos))
|
||
for inroad_info in inroad_delay_pb_list:
|
||
if inroad_info.inroadid == inroadid:
|
||
inroad_info.flow_delay_infos.append(flow_info)
|
||
inroad_delay_infos_with_imbalance = calc_inroad_imbalance_index(inroad_delay_pb_list)
|
||
avg_cross_delay.inroad_delay_infos.extend(inroad_delay_infos_with_imbalance)
|
||
|
||
# 出口道流量数据聚合逻辑
|
||
outroad_delay_info_dict = {}
|
||
|
||
for item in cross_delay_pb_list:
|
||
outroadid_infos = item.outroad_infos
|
||
for outroadid_info in outroadid_infos:
|
||
outroadid = outroadid_info.outroadid
|
||
if outroadid not in outroad_delay_info_dict:
|
||
outroad_delay_info_dict[outroadid] = [outroadid_info]
|
||
else:
|
||
outroad_delay_info_dict[outroadid].append(outroadid_info)
|
||
|
||
for outroadid in outroad_delay_info_dict.keys():
|
||
outroadid_infos = outroad_delay_info_dict[outroadid]
|
||
car_num, turn_ratio_0, turn_ratio_1, turn_ratio_2, turn_ratio_3 = 0, 0, 0, 0, 0
|
||
for outroadid_info in outroadid_infos:
|
||
turn_info = outroadid_info.turn_info
|
||
car_num += turn_info.car_num
|
||
turn_ratio_0 += turn_info.turn_ratio_0
|
||
turn_ratio_1 += turn_info.turn_ratio_1
|
||
turn_ratio_2 += turn_info.turn_ratio_2
|
||
turn_ratio_3 += turn_info.turn_ratio_3
|
||
outroadid_info = pb.xl_outroad_info_t()
|
||
outroadid_info.outroadid = outroadid
|
||
outroadid_info.turn_info.car_num = car_num
|
||
outroadid_info.turn_info.turn_ratio_0 = turn_ratio_0
|
||
outroadid_info.turn_info.turn_ratio_1 = turn_ratio_1
|
||
outroadid_info.turn_info.turn_ratio_2 = turn_ratio_2
|
||
outroadid_info.turn_info.turn_ratio_3 = turn_ratio_3
|
||
avg_cross_delay.outroad_infos.append(outroadid_info)
|
||
|
||
return avg_cross_delay
|
||
|
||
|
||
# 生成路口诊断页面路口概览数据指标的函数
|
||
def gen_overview_index(avg_cross_delay_info, inroad_static_info_dict, nodeid, date_list, roads_dir_dict):
|
||
car_num = avg_cross_delay_info.delay_info.car_num
|
||
crossid = avg_cross_delay_info.crossid
|
||
jam_index = round(avg_cross_delay_info.delay_info.jam_index, 2)
|
||
stop_times = round(avg_cross_delay_info.delay_info.stop_times, 2)
|
||
high_park_percent = str(avg_cross_delay_info.delay_info.high_park_percent) + '%'
|
||
imbalance_index = round(avg_cross_delay_info.delay_info.imbalance_index, 2)
|
||
speed = avg_cross_delay_info.delay_info.speed / 100
|
||
move_speed = avg_cross_delay_info.delay_info.move_speed / 100
|
||
park_time = avg_cross_delay_info.delay_info.park_time
|
||
delay_time = avg_cross_delay_info.delay_info.delay_time
|
||
high_stop_turn_ratio_desc, main_flow_src_desc = gen_high_stop_turn_ratio_desc(avg_cross_delay_info.inroad_delay_infos, inroad_static_info_dict, car_num)
|
||
|
||
tide_index_list = calc_tide_index(crossid, nodeid, date_list, roads_dir_dict)
|
||
usable_tide_list = [item for item in tide_index_list if item != 0]
|
||
tide_index = round(sum(usable_tide_list) / len(usable_tide_list), 2) if len(usable_tide_list) > 0 else 0
|
||
service_level = calc_service_level(delay_time)
|
||
overview_res = {
|
||
'jam_index': jam_index,
|
||
'stop_times': stop_times,
|
||
'high_park_percent': high_park_percent,
|
||
'imbalance_index': imbalance_index,
|
||
'speed': speed,
|
||
'move_speed': move_speed,
|
||
'park_time': park_time,
|
||
'delay_time': delay_time,
|
||
'service_level': service_level,
|
||
'high_stop_turn_ratio_desc': high_stop_turn_ratio_desc,
|
||
'main_flow_src_desc': main_flow_src_desc,
|
||
'tide_index': tide_index
|
||
}
|
||
return overview_res
|
||
|
||
|
||
def gen_high_stop_turn_ratio_desc(inroad_delay_infos, inroad_static_info_dict, car_num):
|
||
src_dict, src_desc_list, main_flow_src_list = {}, [], []
|
||
for inroad_info in inroad_delay_infos:
|
||
inroadid = inroad_info.inroadid
|
||
if inroadid not in inroad_static_info_dict.keys():
|
||
continue
|
||
inroad_car_num = inroad_info.delay_info.car_num
|
||
src_dir = dir_str_dict[inroad_static_info_dict[inroadid]['src_direct']]
|
||
if inroad_car_num / car_num > 0.25:
|
||
check_res = found_max_car_num_flow(inroad_car_num, inroad_info)
|
||
if check_res != -1:
|
||
main_flow_src_list.append(src_dir + int_turn_type2str[check_res])
|
||
flow_delay_infos = inroad_info.flow_delay_infos
|
||
for item in flow_delay_infos:
|
||
if item.stop_times >= 1:
|
||
turn_type = int_turn_type2str[item.turn_type]
|
||
if src_dir not in src_dict.keys():
|
||
src_dict[src_dir] = [turn_type]
|
||
else:
|
||
src_dict[src_dir].append(turn_type)
|
||
for item in src_dict.keys():
|
||
src_desc_list.append(item + '/'.join(src_dict[item]))
|
||
return '、'.join(src_desc_list) if src_desc_list else '无', '、'.join(main_flow_src_list) if main_flow_src_list else '无'
|
||
|
||
|
||
def found_max_car_num_flow(inroad_car_num, inroad_info):
|
||
data_list = [inroad_info.turn_ratio_0, inroad_info.turn_ratio_1, inroad_info.turn_ratio_2, inroad_info.turn_ratio_3]
|
||
for i in range(len(data_list)):
|
||
if data_list[i] / inroad_car_num > 0.5:
|
||
return i
|
||
return -1
|
||
|
||
|
||
def query_cross_ledger_info(crossid, nodeid, area_id, userid):
|
||
ledger_url = f"http://120.53.125.169:7070/api/common/cross_ledger_detail?crossid={crossid}&crossno=&nodeid={nodeid}&area_id={area_id}&userid={userid}"
|
||
headers = {"Content-Type": "application/json"}
|
||
cross_ledger_info = requests.get(ledger_url, headers=headers)
|
||
if cross_ledger_info.status_code != 200 or cross_ledger_info.json()['status'] != 0:
|
||
logging.error(f"查询路口台账信息失败,crossid:{crossid},nodeid:{nodeid},area_id:{area_id},userid:{userid}")
|
||
return None, None
|
||
|
||
cross_ledger_info_dict = json.loads(cross_ledger_info.text)
|
||
return cross_ledger_info_dict
|
||
|
||
|
||
def gen_cross_static_info(crossid, nodeid, area_id, cross_ledger_info_dict):
|
||
division_list, company_list, slc_company_dict, slckind_list, detector_type_dict = gen_ledger_base_info(nodeid, area_id)
|
||
slc_company = cross_ledger_info_dict['data']['ledger']['slc_company']
|
||
location = cross_ledger_info_dict['data']['ledger']['location']
|
||
slc_company_name = slc_company_dict[slc_company] if slc_company in slc_company_dict.keys() else '-'
|
||
internet = cross_ledger_info_dict['data']['ledger']['internet']
|
||
internet_str = int_internet_code2str[internet]
|
||
primary = cross_ledger_info_dict['data']['ledger']['primary']
|
||
secondary = cross_ledger_info_dict['data']['ledger']['secondary']
|
||
cross_model = int_cross_model2str[primary] + '-' + int_cross_model2str[secondary]
|
||
light_infos = cross_ledger_info_dict['data']['light_infos']
|
||
src_light_dict = gen_dir_light_info_dict(light_infos)
|
||
roads = cross_ledger_info_dict['data']['roads']
|
||
dir_list = roads.keys()
|
||
length_info, lane_nums_list, road_special_info = {}, [], {}
|
||
sum_length = 0
|
||
for dir in dir_list:
|
||
dir_length = roads[dir]['topology']['entry']['road_length']
|
||
straight_left_split, reverse_turn, left_turn_waiting_area, straight_turn_waiting_area, reversible_lanes_info, outside_left = 0, 0, 0, 0, 0, 0
|
||
if 2 in src_light_dict[dir] and (1 in src_light_dict[dir] or 3 in src_light_dict[dir]):
|
||
straight_left_split = 1
|
||
if roads[dir]['canaliza']['reverse_turn'] == 1:
|
||
reverse_turn = 1
|
||
if roads[dir]['canaliza']['hold_left'] == 1:
|
||
left_turn_waiting_area = 1
|
||
if roads[dir]['canaliza']['hold_straight'] == 1:
|
||
straight_turn_waiting_area = 1
|
||
if len(roads[dir]['canaliza']['reversible_lanes_info']) > 0:
|
||
reversible_lanes_info = 1
|
||
lane_turn_info = roads[dir]['topology']['entry']['lane_turn_info']
|
||
if check_outside_left(lane_turn_info):
|
||
outside_left = 1
|
||
road_special_info[dir_str_dict[dir]] = {
|
||
'straight_left_split': straight_left_split,
|
||
'reverse_turn': reverse_turn,
|
||
'hold_left': left_turn_waiting_area,
|
||
'hold_straight': straight_turn_waiting_area,
|
||
'reversible_lanes_info': reversible_lanes_info,
|
||
'outside_left': outside_left
|
||
}
|
||
lane_nums_list.append([dir_str_dict[dir] + '进口', roads[dir]['entry_lane_num'], dir_str_dict[src_reverse[dir]] + '出口', roads[dir]['exit_lane_num']])
|
||
if dir_length != '-':
|
||
sum_length += dir_length
|
||
length_info[dir] = dir_length
|
||
avg_length = round(sum_length / len(length_info.keys()), 0) if length_info else 0
|
||
cross_static_info = {
|
||
'crossid': crossid,
|
||
'nodeid': nodeid,
|
||
'area_id': area_id,
|
||
'location': location,
|
||
'slc_company': slc_company_name,
|
||
'internet': internet_str,
|
||
'cross_model': cross_model,
|
||
'lane_nums_list': lane_nums_list,
|
||
'road_special_info': road_special_info,
|
||
'length_info': length_info,
|
||
'avg_length': avg_length
|
||
}
|
||
return cross_static_info, cross_ledger_info_dict['data']
|
||
|
||
|
||
def gen_ledger_base_info(nodeid, area_id):
|
||
node_base_params_info = db_tmnet.query_base_info(nodeid, area_id)
|
||
# 下列字段当为空时需在前端展示尚未针对该城市进行配置的同义提示语句
|
||
division_list, company_list, slc_company_dict, slckind_list, detector_type_dict = [], [], {}, [], {}
|
||
for row in node_base_params_info:
|
||
if row['param_type'] == 'division':
|
||
division_list.append(row['param_value'])
|
||
elif row['param_type'] == 'company':
|
||
company_list.append(row['param_value'])
|
||
elif row['param_type'] == 'slc_company':
|
||
slc_company_dict[row['param_code']] = row['param_value']
|
||
elif row['param_type'] == 'slckind':
|
||
slckind_list.append(row['param_value'])
|
||
elif row['param_type'] == 'detector_type':
|
||
detector_type_dict[row['param_code']] = row['param_value']
|
||
return division_list, company_list, slc_company_dict, slckind_list, detector_type_dict
|
||
|
||
|
||
def gen_dir_light_info_dict(light_infos):
|
||
dir_light_dict = {}
|
||
for row in light_infos:
|
||
srcDir = row['srcDir']
|
||
light_type = row['light_type']
|
||
if srcDir not in dir_light_dict.keys():
|
||
dir_light_dict[srcDir] = [light_type]
|
||
else:
|
||
dir_light_dict[srcDir].append(light_type)
|
||
return dir_light_dict
|
||
|
||
|
||
def check_outside_left(lane_turn_info):
|
||
seen_s = False # 是否已出现直行车道
|
||
for func in lane_turn_info:
|
||
if 's' in func: # 当前是直行车道
|
||
seen_s = True
|
||
if seen_s and ('l' in func): # 直行车道右侧出现左转
|
||
return True
|
||
return False
|
||
|
||
|
||
def gen_road_delay_index(avg_cross_delay_info, roads_dir_dict):
|
||
road_delay_infos = []
|
||
if not avg_cross_delay_info:
|
||
return road_delay_infos
|
||
road_delay_infos = avg_cross_delay_info.inroad_delay_infos
|
||
road_dir = {v['in']: k for k, v in roads_dir_dict.items()}
|
||
road_flow_index = {}
|
||
for road_index in road_delay_infos:
|
||
roadid = road_index.inroadid
|
||
if roadid not in road_dir.keys():
|
||
continue
|
||
service_level = calc_service_level(road_index.delay_info.delay_time)
|
||
road_flow_index[roadid] = {
|
||
'src_dir': road_dir[roadid],
|
||
'stop_times': round(road_index.delay_info.stop_times, 2),
|
||
'high_park_percent': str(road_index.delay_info.high_park_percent) + '%',
|
||
'imbalance_index': round(road_index.delay_info.imbalance_index, 2),
|
||
'park_time': road_index.delay_info.park_time,
|
||
'delay_time': road_index.delay_info.delay_time,
|
||
'speed': road_index.delay_info.speed / 100,
|
||
'move_speed': road_index.delay_info.move_speed / 100,
|
||
'service_level': service_level,
|
||
'flow_delays': {}
|
||
}
|
||
flow_delay_infos = road_index.flow_delay_infos
|
||
for flow_delay_info in flow_delay_infos:
|
||
if flow_delay_info.turn_type not in (0, 1):
|
||
continue
|
||
flow_service_level = calc_service_level(flow_delay_info.delay_info.delay_time)
|
||
road_flow_index[roadid]['flow_delays'][flow_delay_info.turn_type] = {
|
||
'stop_times': round(flow_delay_info.delay_info.stop_times, 2),
|
||
'high_park_percent': str(flow_delay_info.delay_info.high_park_percent) + '%',
|
||
'park_time': flow_delay_info.delay_info.park_time,
|
||
'delay_time': flow_delay_info.delay_info.delay_time,
|
||
'speed': flow_delay_info.delay_info.speed / 100,
|
||
'service_level': flow_service_level,
|
||
'move_speed': flow_delay_info.delay_info.move_speed / 100
|
||
}
|
||
return road_flow_index
|
||
|
||
|
||
def gen_road_dir_dict(cross_ledger_info_dict):
|
||
roads_dir_dict = {}
|
||
if not cross_ledger_info_dict:
|
||
return roads_dir_dict
|
||
roads = cross_ledger_info_dict['roads'] if 'roads' in cross_ledger_info_dict.keys() else None
|
||
for dir in roads.keys():
|
||
roads_dir_dict[dir] = {
|
||
'in': roads[dir]['roadid'],
|
||
'out': roads[dir]['out_roadid']
|
||
}
|
||
return roads_dir_dict
|
||
|
||
|
||
def calc_inroad_imbalance_index(inroad_delay_pb_list):
|
||
for item in inroad_delay_pb_list:
|
||
avg_stop_times = item.delay_info.stop_times
|
||
max_stop_times, min_stop_times = 0, 99999
|
||
flow_delay_infos = item.flow_delay_infos
|
||
for flow_delay_info in flow_delay_infos:
|
||
if flow_delay_info.delay_info.stop_times > max_stop_times:
|
||
max_stop_times = flow_delay_info.delay_info.stop_times
|
||
if flow_delay_info.delay_info.stop_times < min_stop_times:
|
||
min_stop_times = flow_delay_info.delay_info.stop_times
|
||
imbalance_index = round((max_stop_times - min_stop_times) / avg_stop_times, 2) if avg_stop_times > 0 and max_stop_times > 0 and min_stop_times != 99999 else 0
|
||
item.delay_info.imbalance_index = imbalance_index
|
||
return inroad_delay_pb_list
|
||
|
||
|
||
def gen_flow_turn_rate_index(avg_cross_delay_info, roads_dir_dict):
|
||
road_delay_infos = avg_cross_delay_info.inroad_delay_infos
|
||
outroad_infos = avg_cross_delay_info.outroad_infos
|
||
road_delay_dict = {item.inroadid: item for item in road_delay_infos}
|
||
outroad_info_dict = {item.outroadid: item for item in outroad_infos}
|
||
cross_sum_car_num = sum([item.delay_info.car_num for item in road_delay_infos])
|
||
cross_out_sum_car_num = sum([item.turn_info.car_num for item in outroad_infos])
|
||
road_flow_turn_rate = {}
|
||
for dir in roads_dir_dict.keys():
|
||
roadid = roads_dir_dict[dir]['in']
|
||
l_rate, s_rate, r_rate = '-', '-', '-'
|
||
out_l_rate, out_s_rate, out_r_rate = '-', '-', '-'
|
||
in_flow_rate, out_flow_rate = '-', '-'
|
||
if roadid != '-' and roadid in road_delay_dict.keys():
|
||
car_num = road_delay_dict[roadid].delay_info.car_num
|
||
in_flow_rate = round(car_num / cross_sum_car_num, 2) if cross_out_sum_car_num != 0 else '-'
|
||
|
||
flow_delay_infos = road_delay_dict[roadid].flow_delay_infos
|
||
for flow_delay_info in flow_delay_infos:
|
||
if flow_delay_info.turn_type not in (0, 1, 2):
|
||
continue
|
||
if flow_delay_info.turn_type == 0:
|
||
l_rate = round(flow_delay_info.delay_info.car_num / car_num, 2) if car_num != 0 else '-'
|
||
elif flow_delay_info.turn_type == 1:
|
||
s_rate = round(flow_delay_info.delay_info.car_num / car_num, 2) if car_num != 0 else '-'
|
||
elif flow_delay_info.turn_type == 2:
|
||
r_rate = round(flow_delay_info.delay_info.car_num / car_num, 2) if car_num != 0 else '-'
|
||
out_road_id = roads_dir_dict[dir]['out']
|
||
if out_road_id != '-' and out_road_id in outroad_info_dict.keys():
|
||
out_car_num = outroad_info_dict[out_road_id].turn_info.car_num
|
||
out_flow_rate = round(out_car_num / cross_out_sum_car_num, 2) if cross_out_sum_car_num != 0 else '-'
|
||
out_l_rate = round(outroad_info_dict[out_road_id].turn_info.turn_ratio_1 / out_car_num, 2) if out_car_num != 0 else '-'
|
||
out_s_rate = round(outroad_info_dict[out_road_id].turn_info.turn_ratio_0 / out_car_num, 2) if out_car_num != 0 else '-'
|
||
out_r_rate = round(outroad_info_dict[out_road_id].turn_info.turn_ratio_2 / out_car_num, 2) if out_car_num != 0 else '-'
|
||
road_flow_turn_rate[roadid] = {
|
||
'src_dir': dir,
|
||
'in_flow_rate': in_flow_rate,
|
||
'out_flow_rate': out_flow_rate,
|
||
'l_rate': l_rate,
|
||
's_rate': s_rate,
|
||
'r_rate': r_rate,
|
||
'out_l_rate': out_l_rate,
|
||
'out_s_rate': out_s_rate,
|
||
'out_r_rate': out_r_rate
|
||
}
|
||
return road_flow_turn_rate
|
||
|
||
|
||
def calc_service_level(delay_time):
|
||
if delay_time <= 10:
|
||
service_level = 'A'
|
||
elif 10 < delay_time <= 20:
|
||
service_level = 'B'
|
||
elif 20 < delay_time <= 35:
|
||
service_level = 'C'
|
||
elif 35 < delay_time <= 55:
|
||
service_level = 'D'
|
||
elif 55 < delay_time <= 80:
|
||
service_level = 'E'
|
||
else:
|
||
service_level = 'F'
|
||
return service_level
|
||
|
||
|
||
def calc_tide_index(crossid, nodeid, date_list, roads_dir_dict):
|
||
tide_index_list = []
|
||
am_tp_start, am_tp_end = 't700', '900'
|
||
pm_tp_start, pm_tp_end = 't1700', '1900'
|
||
am_cross_delay_data_list = db_cross.query_cross_delay_info(crossid, nodeid, date_list, am_tp_start)
|
||
pm_cross_delay_data_list = db_cross.query_cross_delay_info(crossid, nodeid, date_list, pm_tp_start)
|
||
date_am_delay_info_dict = {item['day']: item['data'] for item in am_cross_delay_data_list}
|
||
date_pm_delay_info_dict = {item['day']: item['data'] for item in pm_cross_delay_data_list}
|
||
|
||
# 构建对向进口道对
|
||
subtend_road_pair = gen_subtend_road_pair(roads_dir_dict)
|
||
for date in date_list:
|
||
max_am_flow, max_pm_flow, tide_index, max_am_flow_road, max_pm_flow_road = 0, 99999999999, 0, '', ''
|
||
if date not in date_am_delay_info_dict.keys() or date not in date_pm_delay_info_dict.keys():
|
||
tide_index_list.append(tide_index)
|
||
continue
|
||
item_am_cross_delay_info = pb.xl_cross_delayinfo_t()
|
||
item_pm_cross_delay_info = pb.xl_cross_delayinfo_t()
|
||
item_am_cross_delay_info.ParseFromString(date_am_delay_info_dict[date])
|
||
item_pm_cross_delay_info.ParseFromString(date_pm_delay_info_dict[date])
|
||
if not item_am_cross_delay_info or not item_pm_cross_delay_info:
|
||
tide_index_list.append(tide_index)
|
||
continue
|
||
am_inroad_infos = item_am_cross_delay_info.inroad_delay_infos
|
||
pm_inroad_infos = item_pm_cross_delay_info.inroad_delay_infos
|
||
am_inroad_info_dict = {item.inroadid: item for item in am_inroad_infos}
|
||
pm_inroad_info_dict = {item.inroadid: item for item in pm_inroad_infos}
|
||
|
||
# 找出早高峰最高流量的进口道
|
||
for am_inroad_info in am_inroad_infos:
|
||
am_flow = am_inroad_info.delay_info.car_num
|
||
if am_flow > max_am_flow:
|
||
max_am_flow = am_flow
|
||
max_am_flow_road = am_inroad_info.inroadid
|
||
if max_am_flow_road == '' or max_am_flow_road not in subtend_road_pair.keys():
|
||
tide_index_list.append(tide_index)
|
||
continue
|
||
subtend_road_am_flow = am_inroad_info_dict[subtend_road_pair[max_am_flow_road]].delay_info.car_num if subtend_road_pair[max_am_flow_road] in am_inroad_info_dict.keys() else 0
|
||
# 如果进口道流量小于20 则无意义
|
||
if min(subtend_road_am_flow, max_am_flow) < 20:
|
||
tide_index_list.append(tide_index)
|
||
continue
|
||
|
||
# 找出晚高峰最高流量的进口道
|
||
for pm_inroad_info in pm_inroad_infos:
|
||
pm_flow = pm_inroad_info.delay_info.car_num
|
||
if pm_flow > max_pm_flow:
|
||
max_pm_flow = pm_flow
|
||
max_pm_flow_road = pm_inroad_info.inroadid
|
||
# 如果路段id为空或不在对向对里，则无意义
|
||
if max_pm_flow_road == '' or max_pm_flow_road not in subtend_road_pair.keys():
|
||
tide_index_list.append(tide_index)
|
||
continue
|
||
subtend_road_pm_flow = pm_inroad_info_dict[subtend_road_pair[max_pm_flow_road]].delay_info.car_num
|
||
if min(subtend_road_pm_flow, max_pm_flow) < 20:
|
||
tide_index_list.append(tide_index)
|
||
continue
|
||
# 如果早晚高峰的最大流量进口道不处于同一个对向对中，则无意义
|
||
if max_pm_flow_road != max_am_flow_road and max_pm_flow_road != subtend_road_pair[max_am_flow_road]:
|
||
tide_index_list.append(tide_index)
|
||
continue
|
||
Fam = max(max_am_flow_road, subtend_road_am_flow) / min(max_am_flow_road, subtend_road_am_flow)
|
||
Fpm = max(max_pm_flow_road, subtend_road_pm_flow) / min(max_pm_flow_road, subtend_road_pm_flow)
|
||
if Fam >= 1.5 and Fpm >= 1.5 and max_pm_flow_road == subtend_road_pair[max_am_flow_road]:
|
||
tide_index = min(Fam, Fpm) / max(Fam, Fpm)
|
||
elif min(Fam, Fpm) <= 0:
|
||
tide_index = 0
|
||
elif max_pm_flow_road == max_am_flow_road:
|
||
tide_index = Fam * Fpm
|
||
tide_index_list.append(tide_index)
|
||
|
||
return tide_index_list
|
||
|
||
|
||
def gen_subtend_road_pair(roads_dir_dict):
|
||
subtend_road_pair = {}
|
||
tmp_road_dir = copy.deepcopy(roads_dir_dict)
|
||
keys_to_process = list(tmp_road_dir.keys())
|
||
for dir in keys_to_process:
|
||
if dir in tmp_road_dir.keys() and tmp_road_dir[dir]['in'] == '-':
|
||
continue
|
||
subtend_dir = src_reverse[dir]
|
||
if subtend_dir in tmp_road_dir.keys() and tmp_road_dir[subtend_dir]['in'] != '-':
|
||
subtend_road_pair[tmp_road_dir[dir]['in']] = tmp_road_dir[subtend_dir]['in']
|
||
tmp_road_dir.pop(dir)
|
||
tmp_road_dir.pop(subtend_dir)
|
||
|
||
return subtend_road_pair
|
||
|
||
|
||
def parse_single_cross_delay_info(crossid, nodeid, data_list, data_type, roads_dir_dict):
|
||
data_dict = {}
|
||
max_cross_car_num, max_road_car_num, max_flow_car_num = 0, 0, 0
|
||
pb_data_list = []
|
||
for item in data_list:
|
||
if item:
|
||
pb_data_list.append(item['data'])
|
||
road_delay_infos = item['data'].inroad_delay_infos if item['data'] and item['data'].inroad_delay_infos else []
|
||
for road_delay_info in road_delay_infos:
|
||
if road_delay_info.delay_info.car_num > max_road_car_num:
|
||
max_road_car_num = road_delay_info.delay_info.car_num
|
||
flow_delay_infos = road_delay_info.flow_delay_infos
|
||
for flow_delay_info in flow_delay_infos:
|
||
if flow_delay_info.delay_info.car_num > max_flow_car_num:
|
||
max_flow_car_num = flow_delay_info.delay_info.car_num
|
||
max_cross_car_num = max(
|
||
(x for x in pb_data_list if x is not None),
|
||
key=lambda x: x.delay_info.car_num,
|
||
default=None
|
||
).delay_info.car_num
|
||
for item in data_list:
|
||
tp_start = item['tp_start']
|
||
tp_end = item['tp_end']
|
||
day = item['day']
|
||
if data_type == 'day':
|
||
key = day
|
||
elif data_type == 'hour':
|
||
key = convert_time(int(tp_start.replace('h', ''))) + '-' + convert_time(int(tp_end.replace('h', '')))
|
||
else:
|
||
key = day
|
||
|
||
item_cross_delay_info = item['data']
|
||
# 指标内容依次是 停车次数 多次停车率 停车时间 延误时间 平均速度 不停车速度 相对流量 路口失衡系数 潮汐指数 服务水平
|
||
overview_data = ['-', '-', '-', '-', '-', '-', '-', '-', '-', '-',
|
||
# 下方为上述指标变化率颜色展示flag
|
||
0, 0, 0, 0, 0, 0, 0, 0, 0, 0]
|
||
tide_index = calc_tide_index(crossid, nodeid, [day], roads_dir_dict) if data_type == 'day' or data_type == 'week' else '-'
|
||
road_data_dict = {}
|
||
cross_car_num = 0
|
||
if item_cross_delay_info:
|
||
cross_car_num = item_cross_delay_info.delay_info.car_num
|
||
road_delay_infos = item_cross_delay_info.inroad_delay_infos
|
||
max_stop_times = max(road_delay_infos, key=lambda x: x.delay_info.stop_times).delay_info.stop_times
|
||
min_stop_times = min(road_delay_infos, key=lambda x: x.delay_info.stop_times).delay_info.stop_times
|
||
cross_imbalance_index = round((max_stop_times - min_stop_times) / item_cross_delay_info.delay_info.stop_times, 2) if item_cross_delay_info.delay_info.stop_times != 0 else 0
|
||
overview_data = [
|
||
# 停车次数
|
||
round(item_cross_delay_info.delay_info.stop_times, 2),
|
||
# 多次停车率 停车时间
|
||
item_cross_delay_info.delay_info.high_park_percent, item_cross_delay_info.delay_info.park_time,
|
||
# 延误时间 平均速度
|
||
item_cross_delay_info.delay_info.delay_time, item_cross_delay_info.delay_info.speed / 100,
|
||
# 不停车速度 相对流量占比
|
||
item_cross_delay_info.delay_info.move_speed / 100, round(cross_car_num / max_cross_car_num * 100, 2) if max_cross_car_num != 0 else 0,
|
||
# 路口失衡系数 潮汐指数（当为小时级指标时，不计算该值） 服务水平
|
||
cross_imbalance_index, tide_index[0], calc_service_level(item_cross_delay_info.delay_info.delay_time),
|
||
# 指标变化率颜色展示flag, 不含服务水平
|
||
0, 0, 0, 0, 0, 0, 0, 0, 0
|
||
]
|
||
inroad_delay_infos_with_imbalance = calc_inroad_imbalance_index(road_delay_infos)
|
||
road_data_dict = {item.inroadid: item for item in inroad_delay_infos_with_imbalance}
|
||
data_dict[key] = {
|
||
'overview': overview_data,
|
||
'roads_data': {}
|
||
}
|
||
src_dir_list = list(roads_dir_dict.keys())
|
||
for src_dir in src_dir_list:
|
||
if roads_dir_dict[src_dir]['in'] != '-' and roads_dir_dict[src_dir]['in'] in road_data_dict.keys():
|
||
road_car_num = road_data_dict[roads_dir_dict[src_dir]['in']].delay_info.car_num
|
||
src_data = [
|
||
# 停车次数
|
||
round(road_data_dict[roads_dir_dict[src_dir]['in']].delay_info.stop_times, 2),
|
||
# 多次停车率
|
||
road_data_dict[roads_dir_dict[src_dir]['in']].delay_info.high_park_percent,
|
||
# 转向失衡指数
|
||
round(road_data_dict[roads_dir_dict[src_dir]['in']].delay_info.imbalance_index, 2),
|
||
# 停车时间
|
||
road_data_dict[roads_dir_dict[src_dir]['in']].delay_info.park_time,
|
||
# 延误时间
|
||
road_data_dict[roads_dir_dict[src_dir]['in']].delay_info.delay_time,
|
||
# 平均速度
|
||
road_data_dict[roads_dir_dict[src_dir]['in']].delay_info.speed / 100,
|
||
# 不停车速度
|
||
road_data_dict[roads_dir_dict[src_dir]['in']].delay_info.move_speed / 100,
|
||
# 相对流量占比
|
||
round(road_car_num / max_road_car_num * 100, 2) if max_road_car_num > 0 else '-',
|
||
# 进口道流量占比
|
||
round(road_car_num / cross_car_num * 100, 2) if cross_car_num > 0 else '-',
|
||
# 服务水平
|
||
calc_service_level(road_data_dict[roads_dir_dict[src_dir]['in']].delay_info.delay_time),
|
||
# 指标变化率颜色展示flag, 顺序为上述指标顺序, 不含服务水平
|
||
0, 0, 0, 0, 0, 0, 0, 0, 0
|
||
]
|
||
flow_delay_infos = road_data_dict[roads_dir_dict[src_dir]['in']].flow_delay_infos
|
||
flow_data_dict = {}
|
||
for flow_delay_info in flow_delay_infos:
|
||
turn_type = flow_delay_info.turn_type
|
||
if turn_type not in (0, 1):
|
||
continue
|
||
flow_data = [
|
||
# 停车次数
|
||
round(flow_delay_info.delay_info.stop_times, 2),
|
||
# 多次停车率
|
||
flow_delay_info.delay_info.high_park_percent,
|
||
# 停车时间
|
||
flow_delay_info.delay_info.park_time,
|
||
# 延误时间
|
||
flow_delay_info.delay_info.delay_time,
|
||
# 平均速度
|
||
flow_delay_info.delay_info.speed / 100,
|
||
# 不停车速度
|
||
flow_delay_info.delay_info.move_speed / 100,
|
||
# 相对流量
|
||
round(flow_delay_info.delay_info.car_num / max_flow_car_num * 100, 2) if max_flow_car_num > 0 else '-',
|
||
# 分流转向占比
|
||
round(flow_delay_info.delay_info.car_num / road_car_num * 100, 2) if road_car_num > 0 else '-',
|
||
# 服务水平
|
||
calc_service_level(flow_delay_info.delay_info.delay_time),
|
||
# 指标变化率颜色展示flag 不含服务水平
|
||
0, 0, 0, 0, 0, 0, 0, 0
|
||
]
|
||
flow_data_dict[turn_type] = flow_data
|
||
data_dict[key]['roads_data'][src_dir] = {
|
||
'road': src_data,
|
||
'flow': flow_data_dict
|
||
}
|
||
return data_dict
|
||
|
||
|
||
def calc_single_day_delay_info_change_rate(data_dict):
|
||
res_data_dict = copy.deepcopy(data_dict)
|
||
key_list = list(res_data_dict.keys())
|
||
empty_overview = ['-', '-', '-', '-', '-', '-', '-', '-', '-', '-',
|
||
# 指标变化率颜色展示flag
|
||
0, 0, 0, 0, 0, 0, 0, 0, 0]
|
||
for i in range(len(key_list)-1, -1, -1):
|
||
overview_data = res_data_dict[key_list[i]]['overview'] # list
|
||
roads_data = res_data_dict[key_list[i]]['roads_data'] # dict 内部包含多个方向路段和各个方向路段的流向级别的数据
|
||
if i != 0:
|
||
prev_item_index = i - 1
|
||
prev_overview_data = res_data_dict[key_list[prev_item_index]]['overview']
|
||
prev_roads_data = res_data_dict[key_list[prev_item_index]]['roads_data']
|
||
if overview_data != empty_overview and prev_overview_data != empty_overview:
|
||
overview_data_with_change_rate = calc_overview_change_rate(overview_data, prev_overview_data)
|
||
res_data_dict[key_list[i]]['overview'] = overview_data_with_change_rate
|
||
roads_data_wit_change_rate = calc_roads_data_change_rate(roads_data, prev_roads_data)
|
||
res_data_dict[key_list[i]]['roads_data'] = roads_data_wit_change_rate
|
||
return res_data_dict
|
||
|
||
|
||
def calc_overview_change_rate(overview_data, prev_overview_data):
|
||
res_data = copy.copy(overview_data)
|
||
for i in range(len(overview_data)):
|
||
if i >= 9:
|
||
continue
|
||
if overview_data[i] == '-' or prev_overview_data[i] == '-':
|
||
res_data[i + 10] = 0
|
||
# 变化率 0表示正常 1表示恶化 2表示优化
|
||
if i in (0, 1, 2, 3, 6, 7, 8):
|
||
# 指标提升代表恶化的有停车次数、多次停车率、转向失衡指数、停车时间、延误时间、相对流量、进口道流量占比
|
||
rate = (overview_data[i] - prev_overview_data[i]) / prev_overview_data[i] * 100 if prev_overview_data[i] != '-' and prev_overview_data[i] > 0 else 0
|
||
if rate < -20:
|
||
res_data[i + 10] = 1
|
||
elif rate > 20:
|
||
res_data[i + 10] = 2
|
||
else:
|
||
# 指标下降代表恶化的有平均速度、不停车速度
|
||
rate = (overview_data[i] - prev_overview_data[i]) / prev_overview_data[i] * 100 if prev_overview_data[i] != '-' and prev_overview_data[i] > 0 else 0
|
||
if rate > 20:
|
||
res_data[i + 10] = 1
|
||
elif rate < -20:
|
||
res_data[i + 10] = 2
|
||
return res_data
|
||
|
||
|
||
def calc_roads_data_change_rate(roads_data, prev_roads_data):
|
||
res_data = copy.deepcopy(roads_data)
|
||
src_dir_list = list(roads_data.keys())
|
||
|
||
for src_dir in src_dir_list:
|
||
src_dir_road_data = roads_data[src_dir]['road']
|
||
if src_dir not in prev_roads_data.keys():
|
||
continue
|
||
# 指标提升代表恶化的有停车次数、多次停车率、停车时间、延误时间、相对流量、分流转向占比
|
||
prev_src_dir_road_data = prev_roads_data[src_dir]['road']
|
||
for i in range(len(src_dir_road_data)):
|
||
if i >= 9:
|
||
continue
|
||
if src_dir_road_data[i] == '-' or prev_src_dir_road_data[i] == '-':
|
||
src_dir_road_data[i + 10] = 0
|
||
if i in (0, 1, 2, 3, 4, 7, 8):
|
||
rate = (src_dir_road_data[i] - prev_src_dir_road_data[i]) / prev_src_dir_road_data[i] * 100 if prev_src_dir_road_data[i] > 0 else 0
|
||
if rate < -20:
|
||
src_dir_road_data[i + 10] = 1
|
||
elif rate > 20:
|
||
src_dir_road_data[i + 10] = 2
|
||
else:
|
||
# 指标下降代表恶化的有平均速度、不停车速度
|
||
rate = (src_dir_road_data[i] - prev_src_dir_road_data[i]) / prev_src_dir_road_data[i] * 100 if prev_src_dir_road_data[i] > 0 else 0
|
||
if rate > 20:
|
||
src_dir_road_data[i + 10] = 1
|
||
elif rate < -20:
|
||
src_dir_road_data[i + 10] = 2
|
||
flow_datas = roads_data[src_dir]['flow']
|
||
prev_flow_datas = prev_roads_data[src_dir]['flow']
|
||
for turn_type in flow_datas.keys():
|
||
flow_data = flow_datas[turn_type]
|
||
if turn_type not in prev_flow_datas.keys():
|
||
continue
|
||
prev_flow_data = prev_flow_datas[turn_type]
|
||
for i in range(len(flow_data)):
|
||
if i >= 8:
|
||
continue
|
||
if flow_data[i] == '-' or prev_flow_data[i] == '-':
|
||
flow_data[i + 9] = 0
|
||
if i in (0, 1, 2, 3, 6, 7):
|
||
rate = (flow_data[i] - prev_flow_data[i]) / prev_flow_data[i] * 100 if prev_flow_data[i] > 0 else 0
|
||
if rate < -20:
|
||
flow_data[i + 9] = 1
|
||
elif rate > 20:
|
||
flow_data[i + 9] = 2
|
||
else:
|
||
rate = (flow_data[i] - prev_flow_data[i]) / prev_flow_data[i] * 100 if prev_flow_data[i] > 0 else 0
|
||
if rate > 20:
|
||
flow_data[i + 9] = 1
|
||
elif rate < -20:
|
||
flow_data[i + 9] = 2
|
||
return res_data
|
||
|
||
|
||
def parse_data2pb(data_list):
|
||
res_list = []
|
||
for row in data_list:
|
||
day = row['day']
|
||
tp_start = row['tp_start']
|
||
tp_end = row['tp_end']
|
||
item_cross_delay_info = pb.xl_cross_delayinfo_t()
|
||
item_cross_delay_info.ParseFromString(row['data'])
|
||
res_list.append({
|
||
'day': day,
|
||
'tp_start': tp_start,
|
||
'tp_end': tp_end,
|
||
'data': item_cross_delay_info
|
||
})
|
||
return res_list
|
||
|
||
|
||
def gen_cross_problems(avg_cross_delay_info, roads_dir_dict, inroad_static_info_dict):
|
||
# 运行效率、均衡调控、配时方案、路口渠化
|
||
operating_efficiency_problems = gen_operating_efficiency_problems(avg_cross_delay_info, roads_dir_dict)
|
||
balanced_control_problems = gen_balanced_control_problems(avg_cross_delay_info, roads_dir_dict, inroad_static_info_dict)
|
||
phase_problems = gen_phase_problems()
|
||
cross_channelized_problems = gen_cross_channelized_problems()
|
||
problems = [operating_efficiency_problems, balanced_control_problems, phase_problems, cross_channelized_problems]
|
||
return problems
|
||
|
||
|
||
def gen_operating_efficiency_problems(avg_cross_delay_info, roads_dir_dict):
|
||
if not avg_cross_delay_info:
|
||
return [{
|
||
'item': '运行效率',
|
||
'values': []
|
||
}]
|
||
road_delay_infos = avg_cross_delay_info.inroad_delay_infos
|
||
high_park_problems, high_park_suggestions = gen_high_park_problems(road_delay_infos, roads_dir_dict)
|
||
|
||
operating_efficiency_problems = {
|
||
'item': '运行效率',
|
||
'values': [
|
||
{
|
||
'item': '多次排队',
|
||
'detail': high_park_problems,
|
||
'reason': '某一进口道转向的多次停车率大于15%',
|
||
'suggestions': high_park_suggestions
|
||
},
|
||
]
|
||
}
|
||
pass
|
||
|
||
|
||
def gen_high_park_problems(road_delay_infos, roads_dir_dict):
|
||
detail = [{
|
||
'text': '未见异常'
|
||
}]
|
||
suggestion = []
|
||
err_src_dict = {}
|
||
src_list = list(roads_dir_dict.keys())
|
||
road_delays_dict = {item.inroadid: item for item in road_delay_infos}
|
||
for src_dir in src_list:
|
||
if roads_dir_dict[src_dir]['in'] == '-' or roads_dir_dict[src_dir]['in'] not in road_delays_dict.keys():
|
||
continue
|
||
road_info = road_delays_dict[roads_dir_dict[src_dir]['in']]
|
||
flow_delay_infos = road_info.flow_delay_infos
|
||
turn_type_flow_delay_info_dict = {item.turn_type: item for item in flow_delay_infos}
|
||
for turn_type in turn_type_flow_delay_info_dict.keys():
|
||
flow_delay_info = turn_type_flow_delay_info_dict[turn_type]
|
||
if turn_type not in (0, 1):
|
||
continue
|
||
if flow_delay_info.delay_info.high_park_percent > 15:
|
||
if src_dir not in err_src_dict.keys():
|
||
err_src_dict[src_dir] = [str(turn_type) + ':' + str(flow_delay_info.delay_info.high_park_percent)]
|
||
else:
|
||
err_src_dict[src_dir].append(str(turn_type) + ':' + str(flow_delay_info.delay_info.high_park_percent))
|
||
if err_src_dict:
|
||
detail = []
|
||
for src_dir in err_src_dict.keys():
|
||
src_detail = []
|
||
for turn_type in err_src_dict[src_dir]:
|
||
flow_detail = {
|
||
'turn_type': int_turn_type2str[int(turn_type.split(':')[0])],
|
||
'text': '车辆多次停车率过大（',
|
||
'percent': turn_type.split(':')[1] + '%），'
|
||
}
|
||
src_detail.append(flow_detail)
|
||
src_detail.append({
|
||
'text': '车辆需要多次排队才能通过'
|
||
})
|
||
detail.append({
|
||
'src_dir': dir_str_dict[src_dir] + '进口',
|
||
'src_detail': src_detail
|
||
})
|
||
# todo 补充生成建议的逻辑
|
||
return detail, suggestion
|
||
|
||
|
||
def gen_high_stop_time_problems(road_delay_infos, roads_dir_dict):
|
||
detail = [{
|
||
'text': '未见异常'
|
||
}]
|
||
suggestion = []
|
||
# todo 需与产品再次确认逻辑
|
||
pass
|
||
|
||
|
||
def gen_balanced_control_problems(avg_cross_delay_info, roads_dir_dict, inroad_static_info_dict):
|
||
road_delay_infos = avg_cross_delay_info.inroad_delay_infos
|
||
cross_imbalance_detail, cross_imbalance_suggestions = gen_cross_imbalance_problems(road_delay_infos, roads_dir_dict)
|
||
turn_imbalance_detail, turn_imbalance_suggestions = gen_turn_imbalance_problems(road_delay_infos, roads_dir_dict, inroad_static_info_dict)
|
||
# todo 需要与产品确认路口潮汐问题诊断的逻辑
|
||
balanced_control_problems = {
|
||
'item': '均衡调控',
|
||
'values': [
|
||
{
|
||
'item': '路口失衡',
|
||
'detail': cross_imbalance_detail,
|
||
'reason': '路口存在某个流向绿灯时长不足而另一个方向绿灯存在空放的现象',
|
||
'suggestions': cross_imbalance_suggestions
|
||
},
|
||
{
|
||
'item': '转向失衡',
|
||
'detail': turn_imbalance_detail,
|
||
'reason': '同一进口道，直行与左转停车次数之差的绝对值大于0.5，且转向停车次数的最大值大于1',
|
||
'suggestions': turn_imbalance_suggestions
|
||
},
|
||
]
|
||
}
|
||
return balanced_control_problems
|
||
|
||
|
||
# 路口失衡问题诊断
|
||
def gen_cross_imbalance_problems(road_delay_infos, roads_dir_dict):
|
||
detail = [{
|
||
'text': '未见异常'
|
||
}]
|
||
suggestion = []
|
||
road_src_dict = {item['in']: item for item in roads_dir_dict}
|
||
max_stop_times_road = max(road_delay_infos, key=lambda x: x.delay_info.stop_times)
|
||
min_stop_times_road = min(road_delay_infos, key=lambda x: x.delay_info.stop_times)
|
||
if max_stop_times_road.delay_info.stop_times > 1 \
|
||
and max_stop_times_road.delay_info.stop_times - min_stop_times_road.delay_info.stop_times > 0.5:
|
||
max_roadid = max_stop_times_road.inroadid
|
||
min_roadid = min_stop_times_road.inroadid
|
||
max_src = road_src_dict[max_roadid]
|
||
min_src = road_src_dict[min_roadid]
|
||
detail = [
|
||
{
|
||
'src_dir': dir_str_dict[max_src] + '进口',
|
||
'text': '的停车次数（' + str(round(max_stop_times_road.delay_info.stop_times, 2)) + '）与'
|
||
},
|
||
{
|
||
'src_dir': dir_str_dict[min_src] + '进口',
|
||
'text': f"""的停车次数（{str(round(max_stop_times_road.delay_info.stop_times, 2))}）相差过大，两者之比为{int(round(max_stop_times_road.delay_info.stop_times, 2) / round(min_stop_times_road.delay_info.stop_times, 2) * 100)}%，分配的绿灯时长不匹配"""
|
||
}
|
||
]
|
||
suggestion = [
|
||
{
|
||
'text': '调整',
|
||
'max_src_dir': dir_str_dict[max_src] + '进口',
|
||
},
|
||
{
|
||
'text': '和',
|
||
'min_src_dir': dir_str_dict[min_src] + '进口',
|
||
},
|
||
{
|
||
'text': '的绿灯时长的分配情况'
|
||
}
|
||
]
|
||
if max_src == src_reverse[min_src]:
|
||
# todo 补充对向情况下额外建议的情况
|
||
pass
|
||
return detail, suggestion
|
||
|
||
|
||
# 转向失衡问题诊断
|
||
def gen_turn_imbalance_problems(road_delay_infos, roads_dir_dict, inroad_static_info_dict):
|
||
detail = [{
|
||
'text': '未见异常'
|
||
}]
|
||
suggestion = []
|
||
err_road_dict = {}
|
||
road_src_dict = {item['in']: item for item in roads_dir_dict}
|
||
for road_delay_info in road_delay_infos:
|
||
inroadid = road_delay_info.inroadid
|
||
flow_delay_infos = road_delay_info.flow_delay_infos
|
||
turn_type_flow_delay_info_dict = {item.turn_type: item for item in flow_delay_infos}
|
||
lane_num_info = count_lsr(inroad_static_info_dict[inroadid]['lane_turn_info']) if inroadid in inroad_static_info_dict.keys() else None
|
||
if 0 in turn_type_flow_delay_info_dict.keys() and 1 in turn_type_flow_delay_info_dict.keys():
|
||
s_stop_times = turn_type_flow_delay_info_dict[0].delay_info.stop_times
|
||
l_stop_times = turn_type_flow_delay_info_dict[1].delay_info.stop_times
|
||
if s_stop_times > 1 or l_stop_times > 1 and abs(l_stop_times - s_stop_times) > 0.5:
|
||
if s_stop_times > l_stop_times:
|
||
err_road_dict[road_src_dict[inroadid]] = ['直行' + ':' + str(round(s_stop_times, 2)), '左转' + ':' + str(round(l_stop_times, 2)), lane_num_info]
|
||
else:
|
||
err_road_dict[road_src_dict[inroadid]] = ['左转' + ':' + str(round(s_stop_times, 2)), '直行' + ':' + str(round(l_stop_times, 2)), lane_num_info]
|
||
if len(err_road_dict.keys()) > 0:
|
||
detail, suggestion, road_num_suggestion = [], [], []
|
||
for src_dir in err_road_dict.keys():
|
||
item_detail = [
|
||
{
|
||
'src_dir': dir_str_dict[src_dir] + '进口',
|
||
'child_detail': [
|
||
{
|
||
'turn_type': err_road_dict[src_dir][0].split(':')[0],
|
||
},
|
||
{
|
||
'text': '的停车次数（' + str(err_road_dict[src_dir][0].split(':')[1]) + '）与'
|
||
},
|
||
{
|
||
'turn_type': err_road_dict[src_dir][1].split(':')[0],
|
||
},
|
||
{
|
||
'text': '的停车次数（' + str(err_road_dict[src_dir][1].split(':')[1]) + '）相差过大，两者之比为' + str(int(float(err_road_dict[src_dir][0].split(':')[1]) / float(err_road_dict[src_dir][1].split(':')[1]) * 100)) + '%，分配的绿灯时长不匹配'
|
||
}
|
||
]
|
||
}
|
||
]
|
||
detail.append(item_detail)
|
||
item_suggestion = [
|
||
{
|
||
'src_dir': dir_str_dict[src_dir] + '进口',
|
||
'text': '信号灯直左分控，调整执行和左转车辆绿灯时长分配情况'
|
||
},
|
||
# todo 补充配时相关建议
|
||
]
|
||
suggestion.extend(item_suggestion)
|
||
if err_road_dict[src_dir][2]:
|
||
road_num_suggestion.append(
|
||
{
|
||
'src_dir': dir_str_dict[src_dir] + '进口',
|
||
'text': '左转/直行/右转现有车道数分别为' + err_road_dict[src_dir][2]
|
||
}
|
||
)
|
||
|
||
lane_num_suggestion = [
|
||
{
|
||
'text': '调整',
|
||
'src_dir': '、'.join([dir_str_dict[item] + '进口' for item in err_road_dict.keys()])
|
||
},
|
||
{
|
||
'text': '车道分配情况'
|
||
}
|
||
]
|
||
lane_num_suggestion.extend(road_num_suggestion)
|
||
suggestion = suggestion + lane_num_suggestion
|
||
|
||
return detail, suggestion
|
||
|
||
|
||
def gen_phase_problems():
|
||
pass
|
||
|
||
|
||
def gen_cross_channelized_problems():
|
||
pass
|
||
|
||
|
||
def query_cross_phase(nodeid, crossid):
|
||
cross_phases, err = QueryCrossRunningPhase(nodeid, [crossid])
|
||
if err or not cross_phases or cross_phases.code != 0:
|
||
return None
|
||
cross_phase_info = cross_phases.data[0]
|
||
|
||
pass |