CN106530176B - A method for diagnosing bottlenecks in bus operation - Google Patents

A method for diagnosing bottlenecks in bus operation Download PDF

Info

Publication number
CN106530176B
CN106530176B CN201610948332.1A CN201610948332A CN106530176B CN 106530176 B CN106530176 B CN 106530176B CN 201610948332 A CN201610948332 A CN 201610948332A CN 106530176 B CN106530176 B CN 106530176B
Authority
CN
China
Prior art keywords
bus
line
bottleneck
time
station
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Active
Application number
CN201610948332.1A
Other languages
Chinese (zh)
Other versions
CN106530176A (en
Inventor
王宝杰
王元庆
阮天承
胡晓健
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Jining Siyuan Business Service Co ltd
Original Assignee
Changan University
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Changan University filed Critical Changan University
Priority to CN201610948332.1A priority Critical patent/CN106530176B/en
Publication of CN106530176A publication Critical patent/CN106530176A/en
Application granted granted Critical
Publication of CN106530176B publication Critical patent/CN106530176B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/10—Services
    • G06Q50/26—Government or public services
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/40—Business processes related to the transportation industry

Landscapes

  • Business, Economics & Management (AREA)
  • Tourism & Hospitality (AREA)
  • Marketing (AREA)
  • Primary Health Care (AREA)
  • Health & Medical Sciences (AREA)
  • Economics (AREA)
  • General Health & Medical Sciences (AREA)
  • Human Resources & Organizations (AREA)
  • Theoretical Computer Science (AREA)
  • Engineering & Computer Science (AREA)
  • Strategic Management (AREA)
  • Physics & Mathematics (AREA)
  • General Business, Economics & Management (AREA)
  • General Physics & Mathematics (AREA)
  • Educational Administration (AREA)
  • Development Economics (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)
  • Traffic Control Systems (AREA)

Abstract

本发明公开了一种公交运行瓶颈诊断方法，能够利用公交车位置、行驶速度、公交乘客数量等实时数据，综合诊断公交车的运营瓶颈。本发明首先通过在线匹配AVL定位系统信息与IC卡收费系统信息，实时获取公交运行和乘客运输信息；接着将公交运营效益、公交出行效率等主观因素，与公交客观运行因素进行融合，构建公交运行综合评价指标；最后从公交站点和公交线路层面分别实现公交运行瓶颈诊断。本发明客观可靠、操作简便，能够有效诊断公交运行过程中的实时瓶颈，具有较好的工程实用价值。

Figure 201610948332

The invention discloses a method for diagnosing the operation bottleneck of a bus, which can comprehensively diagnose the operation bottleneck of the bus by using real-time data such as the bus position, the running speed and the number of bus passengers. The present invention firstly obtains real-time bus operation and passenger transportation information by online matching AVL positioning system information and IC card charging system information; and then integrates subjective factors such as bus operation efficiency and bus travel efficiency with objective bus operation factors to construct bus operation Comprehensive evaluation indicators; finally, the bottleneck diagnosis of bus operation is realized from the level of bus stops and bus lines. The present invention is objective, reliable, easy to operate, can effectively diagnose real-time bottlenecks in the operation of public transport, and has good engineering practical value.

Figure 201610948332

Description

Bus operation bottleneck diagnosis method
Technical Field
The invention relates to the technical field of urban public transportation management, in particular to a public transportation operation bottleneck diagnosis method.
Background
Urban public transport is an important component of urban infrastructure, and has great influence on the development of urban political economy, cultural education, scientific technology and the like. The method improves the public traffic service level and the travel attraction, is not only an effective measure for relieving urban traffic jam, but also an important means for improving urban living environment, improving the utilization rate of traffic resources, relieving traffic jam, reducing traffic pollution and saving land resources and energy, and has very important effects on enhancing urban functions, coordinating urban and rural development and promoting urban and rural joint prosperity.
Urban public transport is a huge urban transport system, and the operation condition of the urban public transport is influenced by various factors such as road facilities, weather conditions, road traffic flow, bus passenger flow and the like. The urban public transport manager is difficult to objectively and comprehensively and clearly master the real-time operation condition of the public transport and quickly find the operation bottleneck of the public transport. According to the method, dynamic public transportation information acquired by common public transportation equipment such as a public transportation vehicle-mounted AVL positioning system and an IC card public transportation charging system is utilized, background static information such as public transportation operation timetables and public transportation historical operation information is combined, and the comprehensive evaluation indexes of the public transportation operation state are respectively constructed from a site level, a line level and a line network level, so that the rapid diagnosis of the operation bottleneck of the urban public transportation can be realized.
Disclosure of Invention
The invention aims to overcome the defects and provide a method for diagnosing the operation bottleneck of the bus, which can diagnose the operation state of the bus in real time and assist management departments to quickly find the operation bottleneck of the bus and make relevant responses in time.
In order to achieve the above object, the present invention comprises the steps of:
acquiring dynamic data of bus position, bus running speed and bus passenger number, and static data of a bus operation schedule and bus historical operation information;
step two, determining real-time information of bus operation and passenger transportation according to the dynamic operation data collected in the step one;
thirdly, according to the real-time information of the bus operation and the passenger transportation determined in the second step, a bus operation state comprehensive evaluation index integrating bus operation benefits, bus passenger travel efficiency and bus objective operation factors is constructed;
step four, outputting a bus operation bottleneck at the bus stop level according to the dynamic operation data collected in the step one and the bus operation state comprehensive evaluation index constructed in the step three;
step five, outputting a bus operation bottleneck at the bus route level according to the dynamic operation data collected in the step one and the bus operation state comprehensive evaluation index constructed in the step three;
and step six, outputting the bus operation bottleneck at the bus net level according to the dynamic operation data collected in the step one, the comprehensive evaluation index of the bus operation state constructed in the step three, the bus operation bottleneck at the bus stop level output in the step four and the bus operation bottleneck at the bus line level output in the step five.
In the step one, the acquired dynamic bus data comprises the time T of the bus reaching key nodes of the road section in real timesecTime T of bus arriving at each bus stop in real timestopNumber of times of card swiping of bus on real time by IC card at each bus stopstop(ii) a The collected static data comprises the operation schedule specified time S of the bus reaching the key node of the road sectionsecThe operation schedule of the bus arriving at each bus stop is scheduled time SstopDeparture interval D specified by bus operation scheduleintThe historical average number of passengers on each bus stop of the bus Nstop。
The second step comprises the following steps:
firstly, determining bus running information;
returning the time T of the bus reaching each key node in real time by utilizing the bus-mounted AVL positioning system, the preset key node position of the road section and the preset bus stop point positionsecAnd the time T of the bus arriving at each bus stopstop；
Secondly, determining the transportation information of the passengers in the bus;
when the bus arrives at the station m, the accumulated number of the transported passengers of the bus is
Figure BDA0001141522230000021
Wherein, thetaiAnd (4) average IC card swiping and vehicle taking proportion of the history of the bus passengers at the station i.
The third step comprises the following steps:
firstly, constructing a comprehensive evaluation index of the bus running state at a station level;
Figure BDA0001141522230000031
wherein, Tsec(i +1, j) is the time when the i +1 th bus of the j line reaches the station S; t issec(i, j) is the arrival of the ith bus on the j lineThe time of site S; dint(i, j) is the departure interval of the ith +1 bus and the ith bus of the j line specified by the operation schedule; i is a bus shift number and i is 1,2, 3.; j is a bus route number and j is 1,2, 3;
secondly, constructing a comprehensive evaluation index of the bus running state at the line level;
Figure BDA0001141522230000032
Figure BDA0001141522230000033
wherein, Tsec,j(L, i) is the time when the ith bus of the j line reaches the key node L; ssec,j(L) the time of the bus on the j line to reach the key node L specified by the operation schedule, η the bus operation benefit;
Figure BDA0001141522230000034
the number of the passengers transported is the accumulated number of the passengers transported when the ith bus of the j line reaches the key node L;
Figure BDA0001141522230000035
accumulating the number of transport passengers for the history when the bus of the j line arrives at the key node L; m is the accumulated passing station number when the bus of the j line reaches the key node L; (ii) a i is a bus shift number and i is 1,2, 3.; j is a bus route number and j is 1,2, 3; k is 1,2,3.. m;
thirdly, constructing a comprehensive evaluation index of the bus running state on the line network level;
Figure BDA0001141522230000036
wherein, p is the total number of bus stops contained in the bus network; q (k) is the total number of bus lines contained in the bus stop k; t is the total number of key nodes of the road section contained in the public traffic network; and r (k) is the total number of bus lines contained in the bus stop k.
The fourth step comprises the following steps:
first, for a bus stop k on a bus line j 1,2,3.. d, if any
Figure BDA0001141522230000041
Figure BDA0001141522230000042
The bus line j has no operation bottleneck on the site level; wherein d is the total number of bus stops of the bus line j, omegaSIs the bus bottleneck judgment standard and omega of the station levelS∈[0,1]；
A second step, if any, of setting 1,2,3.. d for a bus stop k on a bus line j
Figure BDA0001141522230000043
k∈[1,d]Then the bus line j has an operation bottleneck, and the station bottleneck of the output bus line j is station k, k is the [1, d ]]。
The fifth step comprises the following steps:
the first step is that key nodes k on a section of a bus line j are 1,2,3
Figure BDA0001141522230000044
Figure BDA0001141522230000045
The bus line j has no operation bottleneck on the line level; wherein e is the total number of key nodes in the section of the bus line j, omegaLIs the bus bottleneck judgment standard and omega of the line levelL∈[0,1]；
The second step, for the key node k of the road section on the bus line j, 1,2,3
Figure BDA0001141522230000046
k∈[1,e]If so, the bus line j has an operation bottleneck at the line level, and the line bottleneck of the output bus line j is a key node k of the road section, wherein k is an element [1, d ]]。
The sixth step comprises the following steps:
first step, if HRI is presentN≤ΩNAnd TTRN≤Ω′NThe bus net does not have an operation bottleneck on the online net layer surface; wherein omegaNIs the bus bottleneck judgment standard of the line network level and omegaN∈[0,1]；
Second step, if HRI is presentN＞ΩNAnd TTRN＞Ω′NAnd if so, the bus network has an operation bottleneck on the network layer surface of the bus, and the step four and the step five are returned to find the specific bottleneck position.
Compared with the prior art, the method comprises the steps of firstly acquiring bus operation dynamic information and bus background static information, and matching the bus operation dynamic information and the bus background static information to obtain real-time information of bus operation and passenger transportation; then, by fusing bus operation benefits, bus travel efficiency and bus objective operation factors, bus operation comprehensive evaluation indexes are respectively constructed from the levels of stations, lines, line networks and the like; finally, comparing the bus bottleneck judgment standard, and outputting the bus operation bottleneck in real time; the invention only uses the AVL positioning system and the IC card charging system which are commonly matched with the bus as equipment support, and fully considers the multi-party requirements of bus operation benefit, bus trip efficiency, bus objective operation factors and the like; the invention can provide comprehensive and objective evaluation of the bus running state for the bus management department and provide information guidance for the bus manager to deal with various sudden bus running bottlenecks by diagnosing the bus running bottlenecks in real time.
Drawings
FIG. 1 is a flow chart of the present invention;
fig. 2 is a schematic diagram of an example of a public transportation network according to an embodiment of the present invention.
Detailed Description
The invention is further illustrated with reference to the following figures and examples.
Referring to fig. 1, the present invention comprises the steps of:
the method comprises the steps of firstly, acquiring dynamic data of bus positions, bus running speeds and bus passenger numbers, and static data of a bus operation schedule and bus historical operation information;
the acquired dynamic data of the bus comprises the time T of the bus to reach key nodes of the road section in real timesecTime T of bus arriving at each bus stop in real timestopNumber of times of card swiping of bus on real time by IC card at each bus stopstop(ii) a The collected static data comprises the operation schedule specified time S of the bus reaching the key node of the road sectionsecThe operation schedule of the bus arriving at each bus stop is scheduled time SstopDeparture interval D specified by bus operation scheduleintThe historical average number of passengers on each bus stop of the bus Nstop。
Secondly, determining bus running information;
returning the time T of the bus reaching each key node in real time by utilizing the bus-mounted AVL positioning system, the preset key node position of the road section and the preset bus stop point positionsecAnd the time T of the bus arriving at each bus stopstop；
Thirdly, determining the transportation information of the passengers in the bus;
when the bus arrives at the station m, the accumulated number of the transported passengers of the bus is
Figure BDA0001141522230000061
Wherein, thetaiAnd (4) average IC card swiping and vehicle taking proportion of the history of the bus passengers at the station i.
Fourthly, constructing a comprehensive evaluation index of the bus running state at the site level;
Figure BDA0001141522230000062
wherein, Tsec(i +1, j) is the time when the i +1 th bus of the j line reaches the station S; t issec(i, j) is the time when the ith bus on the j line reaches the stop S; dint(i, j) is the departure interval of the ith +1 bus and the ith bus of the j line specified by the operation schedule; i is a bus shift number and i is 1,2, 3.; j is a bus route number and j is 1,2, 3;
fifthly, constructing a comprehensive evaluation index of the bus running state at the line level;
Figure BDA0001141522230000063
Figure BDA0001141522230000064
wherein, Tsec,j(L, i) is the time when the ith bus of the j line reaches the key node L; ssec,j(L) the time of the bus on the j line to reach the key node L specified by the operation schedule, η the bus operation benefit;
Figure BDA0001141522230000065
the number of the passengers transported is the accumulated number of the passengers transported when the ith bus of the j line reaches the key node L;
Figure BDA0001141522230000066
accumulating the number of transport passengers for the history when the bus of the j line arrives at the key node L; m is the accumulated passing station number when the bus of the j line reaches the key node L; (ii) a i is a bus shift number and i is 1,2, 3.; j is a bus route number and j is 1,2, 3; k is 1,2,3.. m;
sixthly, constructing a comprehensive evaluation index of the bus running state on the line network level;
Figure BDA0001141522230000071
wherein, p is the total number of bus stops contained in the bus network; q (k) is the total number of bus lines contained in the bus stop k; t is the total number of key nodes of the road section contained in the public traffic network; and r (k) is the total number of bus lines contained in the bus stop k.
The seventh step, if the bus stop k on the bus line j exists, the bus stop k is 1,2,3
Figure BDA0001141522230000072
Figure BDA0001141522230000073
The bus line j has no operation bottleneck on the site level; wherein d is the total number of bus stops of the bus line j, omegaSIs the bus bottleneck judgment standard and omega of the station levelS∈[0,1]；
The eighth step, if the bus stop k on the bus line j is 1,2,3
Figure BDA0001141522230000074
k∈[1,d]Then the bus line j has an operation bottleneck, and the station bottleneck of the output bus line j is station k, k is the [1, d ]]。
The ninth step, if the key node k on the bus line j is 1,2,3
Figure BDA0001141522230000075
Figure BDA0001141522230000076
The bus line j has no operation bottleneck on the line level; wherein e is the total number of key nodes in the section of the bus line j, omegaLIs the bus bottleneck judgment standard and omega of the line levelL∈[0,1]；
The tenth step, aiming at key nodes k of the road sections on the bus line j, namely 1,2,3
Figure BDA0001141522230000077
k∈[1,e]If so, the bus line j has an operation bottleneck at the line level, and the line bottleneck of the output bus line j is a key node k of the road section, wherein k is an element [1, d ]]。
Eleventh step, if HRI is presentN≤ΩNAnd TTRN≤Ω′NThe bus net does not have an operation bottleneck on the online net layer surface; wherein omegaNIs the bus bottleneck judgment standard of the line network level and omegaN∈[0,1]；
Twelfth, if HRI is presentN＞ΩNAnd TTRN＞Ω′NIf the bus network runs on the network layerAnd (5) the bottleneck is searched for the specific bottleneck position by returning to the step four and the step five.
Referring to fig. 2, example:
the method comprises the steps of firstly, acquiring dynamic data of bus positions, bus running speeds and bus passenger numbers, and static data of a bus operation schedule and bus historical operation information.
In the step, the acquired dynamic bus data comprises the time T of the bus reaching the key node of the road section in real timesecTime T of bus arriving at each bus stop in real timestopNumber of times of card swiping of bus on real time by IC card at each bus stopstop(ii) a The collected static data comprises the operation schedule specified time S of the bus reaching the key node of the road sectionsecThe operation schedule of the bus arriving at each bus stop is scheduled time SstopDeparture interval D specified by bus operation scheduleintThe historical average number of passengers on each bus stop of the bus Nstop。
In this example, the time T of the bus reaching the key node of the road section in real timesecAnd the time T of the bus arriving at each bus stop in real timestopThe real-time bus running information is obtained through a bus-mounted AVL positioning system; IC card real-time getting-on and card-swiping times O of bus at each bus stopstopThe real-time operation information of the buses is obtained through a bus-mounted IC card charging system; operation schedule setting time S for bus to reach key node of road sectionsecThe operation schedule of the bus arriving at each bus stop is scheduled time SstopDeparture interval D specified by bus operation scheduleintThe static information of the bus background can be obtained by inquiring a bus operation schedule; historical average number of passengers on each bus stop for bus NstopAnd the static information of the bus background can be obtained by inquiring the historical operation data of the bus.
Step two, determining real-time information of bus operation and passenger transportation according to the dynamic operation data collected in the step one, wherein the specific method comprises the following steps:
step one, determining real-time information of bus operation;
returning the time T of the bus reaching each key node in real time by utilizing the bus-mounted AVL positioning system, the preset key node position of the road section and the preset bus stop point positionsecAnd the time T of the bus arriving at each bus stopstop。
In this example, a schematic diagram of an example of a bus network is shown in fig. 2, and a time T of a bus returning in real time when the bus arrives at a key node of each road sectionsecAnd the time T of the bus arriving at each bus stopsecAs shown in table 1.
TABLE 1 time of bus to reach each section of road key node and each bus stop
Figure BDA0001141522230000091
Figure BDA0001141522230000101
Second, determining real-time information of public transport passenger transportation
When the bus arrives at the station m, the accumulated number of the transported passengers of the bus is
Figure BDA0001141522230000102
Wherein, thetaiAnd (4) average IC card swiping and vehicle taking proportion of the history of the bus passengers at the station i.
In this example, the bus passenger information at each stop is shown in table 2.
TABLE 2 bus passenger real-time information at each stop
Figure BDA0001141522230000103
Figure BDA0001141522230000111
And step three, according to the real-time information of the bus operation and the passenger transportation determined in the step two, a comprehensive evaluation index of the bus operation state, which integrates the bus operation benefit, the bus passenger trip efficiency and the bus objective operation factors, is constructed.
Firstly, constructing a comprehensive evaluation index of the bus running state at a station level;
Figure BDA0001141522230000112
wherein, Tsec(i +1, j) is the time when the i +1 th bus of the j line reaches the station S; t issec(i, j) is the time when the ith bus on the j line reaches the stop S; dint(i, j) is the departure interval of the ith +1 bus and the ith bus of the j line specified by the operation schedule; i is a bus shift number and i is 1,2, 3.; j is the bus route number and j 1,2,3.
In this example, the bus operation comprehensive evaluation index at the station level is shown in table 3.
TABLE 3 station level comprehensive evaluation index for bus operation
Figure BDA0001141522230000121
Secondly, constructing a comprehensive evaluation index of the bus running state at the line level;
Figure BDA0001141522230000122
Figure BDA0001141522230000123
wherein, Tsec,j(L, i) is the time when the ith bus of the j line reaches the key node L; ssec,j(L) the time of the bus on the j line to reach the key node L specified by the operation schedule, η the bus operation benefit;
Figure BDA0001141522230000131
the number of the passengers transported is the accumulated number of the passengers transported when the ith bus of the j line reaches the key node L;
Figure BDA0001141522230000132
accumulating the number of transport passengers for the history when the bus of the j line arrives at the key node L; m is the accumulated passing station number when the bus of the j line reaches the key node L; (ii) a i is a bus shift number and i is 1,2, 3.; j is a bus route number and j is 1,2, 3; k is 1,2,3.
In this example, the bus operation comprehensive evaluation index at the line level is shown in table 4.
Table 4 bus running comprehensive evaluation index of line level
Figure BDA0001141522230000133
Thirdly, constructing a comprehensive evaluation index of the bus running state on the line network level;
Figure BDA0001141522230000134
wherein, p is the total number of bus stops contained in the bus network; q (k) is the total number of bus lines contained in the bus stop k; t is the total number of key nodes of the road section contained in the public traffic network; and r (k) is the total number of bus lines contained in the bus stop k.
In this example, HRIN＝0.71，TTRN＝0.96。
And step four, outputting the bus operation bottleneck at the bus stop level according to the dynamic operation data collected in the step one and the bus operation state comprehensive evaluation index constructed in the step three.
First, for a bus stop k on a bus line j 1,2,3.. d, if any
Figure BDA0001141522230000141
Figure BDA0001141522230000142
The bus line j has no operation bottleneck at the site level. Wherein d is the total number of bus stops of the bus line j, omegaSIs the bus bottleneck judgment standard and omega of the station levelS∈[0,1]。
A second step, if any, of setting 1,2,3.. d for a bus stop k on a bus line j
Figure BDA0001141522230000143
k∈[1,d]Then the bus line j has an operation bottleneck, and the station bottleneck of the output bus line j is station k, k is the [1, d ]]。
In this example, ΩS0.6. The bus bottleneck diagnosis at the station level is shown in table 5.
TABLE 5 bus bottleneck diagnostic at site level
Figure BDA0001141522230000144
And fifthly, outputting the bus operation bottleneck at the bus route level according to the dynamic operation data collected in the first step and the bus operation state comprehensive evaluation index constructed in the third step.
The first step is that key nodes k on a section of a bus line j are 1,2,3
Figure BDA0001141522230000145
Figure BDA0001141522230000146
The bus line j has no operation bottleneck at the line level. Wherein e is the total number of key nodes in the section of the bus line j, omegaLIs the bus bottleneck judgment standard and omega of the line levelL∈[0,1]。
The second step, for the key node k of the road section on the bus line j, 1,2,3
Figure BDA0001141522230000151
k∈[1,e]If so, the bus line j has an operation bottleneck at the line level, and the line bottleneck of the output bus line j is a key node k of the road section, wherein k is an element [1, d ]]。
In this example, ΩL0.8. Bus bottleneck diagnosis conditions at line level are shown in table 6As shown.
Table 6 bus bottleneck diagnostic situation at line level
Figure BDA0001141522230000152
And step six, outputting the bus operation bottleneck at the bus net level according to the dynamic operation data collected in the step one, the comprehensive evaluation index of the bus operation state constructed in the step three, the bus operation bottleneck at the bus stop level output in the step four and the bus operation bottleneck at the bus line level output in the step five.
First step, if HRI is presentN≤ΩNAnd TTRN≤Ω′NAnd the bus network does not have an operation bottleneck at the network level. Wherein omegaNIs the bus bottleneck judgment standard of the line network level and omegaN∈[0,1]。
Second step, if HRI is presentN＞ΩNAnd TTRN＞Ω′NAnd if so, the bus network has an operation bottleneck on the network layer surface of the bus, and the step four and the step five are returned to find the specific bottleneck position.
In this example, ΩN＝0.6，Ω′N0.8. The bus bottleneck diagnosis at the net level is shown in table 7.
Bus bottleneck diagnosis condition of table 7 wire net layer
Figure BDA0001141522230000161
By returning to the fourth step and the fifth step, Stop 1, Stop 2 and Stop 3 of which the bottlenecks of the public transport stations are Line 1 can be diagnosed; the bottleneck of the key nodes of the road section is Site 1 and Site 2 of Line 3.

Claims (1)

1.一种公交运行瓶颈诊断方法，其特征在于，包括以下步骤：1. A method for diagnosing bottlenecks in bus operation, comprising the following steps: 步骤一，采集公交车位置、公交车行驶速度、公交乘客数量的动态数据，以及公交运营时刻表、公交历史运营信息的静态数据；Step 1: Collect the dynamic data of the bus position, the bus speed, and the number of bus passengers, as well as the static data of the bus operation timetable and the historical bus operation information; 步骤二，根据步骤一中采集的动态数据，确定公交运行和乘客运输的实时信息；Step 2, according to the dynamic data collected in step 1, determine the real-time information of bus operation and passenger transportation; 步骤三，根据步骤二中确定的公交运行和乘客运输的实时信息，构建融合公交运营效益、公交乘客出行效率与公交客观运行因素的公交运行状态综合评价指标；Step 3, according to the real-time information of bus operation and passenger transportation determined in step 2, construct a comprehensive evaluation index of bus operation state that integrates bus operation benefit, bus passenger travel efficiency and bus objective operation factors; 步骤四，根据步骤一中采集的动态数据，以及步骤三中构建的公交运行状态综合评价指标，输出公交站点层面的公交运行瓶颈；Step 4: According to the dynamic data collected in Step 1 and the comprehensive evaluation index of the bus operation state constructed in Step 3, output the bus operation bottleneck at the bus station level; 步骤五，根据步骤一中采集的动态数据，以及步骤三中构建的公交运行状态综合评价指标，输出线路层面的公交运行瓶颈；Step 5: According to the dynamic data collected in Step 1 and the comprehensive evaluation index of the bus operation state constructed in Step 3, output the bus operation bottleneck at the line level; 步骤六，根据步骤一中采集的动态数据、步骤三中构建的公交运行状态综合评价指标、步骤四中输出的公交站点层面的公交运行瓶颈、步骤五中输出的公交线路层面的公交运行瓶颈，输出公交线网层面的公交运行瓶颈；Step 6: According to the dynamic data collected in step 1, the comprehensive evaluation index of the bus operation state constructed in step 3, the bus operation bottleneck at the bus station level output in step 4, and the bus operation bottleneck at the bus line level output in step 5, Output the bus operation bottleneck at the bus network level; 所述步骤一中，采集的动态数据包括公交车实时到达路段关键节点的时间Tsec，公交车实时到达各站点的时间Tstop，Tsec和Tstop通过公交车载AVL定位系统获得；公交车在各站点的IC卡实时上车刷卡次数Ostop通过公交车载IC卡收费系统获得；采集的静态数据包括公交车到达路段关键节点的运营时刻表规定时间Ssec，公交车到达各站点的运营时刻表规定时间Sstop，公交车运营时刻表规定的发车间隔Dint，Ssec、Sstop和Dint通过查询公交运营时刻表获得；公交车在各站点的历史平均上车乘客数Nstop通过查询公交历史运营资料获得；In the first step, the collected dynamic data includes the time T sec when the bus arrives at the key node of the road section in real time, the time T stop when the bus arrives at each station in real time, and T sec and T stop are obtained through the bus-borne AVL positioning system; The real-time IC card swiping times O stop at each station are obtained through the bus IC card toll collection system; the collected static data includes the operation schedule of the bus arriving at the key nodes of the road section, the specified time S sec , the operation time of the bus arriving at each station The time S stop specified in the timetable, the departure interval D int specified in the bus operation timetable, S sec , S stop and D int are obtained by querying the bus operation timetable; the historical average number of passengers on the bus at each station N stop passed Query the historical operation data of public transport to obtain; 所述步骤二包括以下步骤：The second step includes the following steps: 第一步，确定公交运行信息；The first step is to determine the bus operation information; 利用公交车载AVL定位系统、预先设置的路段关键节点位置和站点位置，实时返回公交车到达各关键节点的时间Tsec，以及公交车到达各站点的时间Tstop；Using the bus-borne AVL positioning system, the preset key node positions and station positions of the road section, return the time T sec when the bus arrives at each key node and the time T stop when the bus arrives at each station in real time; 第二步，确定公交乘客运输信息；The second step is to determine the transportation information of bus passengers; 公交车到达关键节点L时累计通过m个站点时，该公交车累计运输乘客数为
Figure FDA0002397652520000021
其中，θk为k站点的公交乘客历史平均刷IC卡乘车比例；When the bus reaches the key node L and passes through m stations, the cumulative number of passengers transported by the bus is
Figure FDA0002397652520000021
Among them, θk is the historical average IC card riding ratio of bus passengers at station k ; 所述步骤三包括以下步骤：The third step includes the following steps: 第一步，构建站点层面的公交运行状态综合评价指标；The first step is to construct a comprehensive evaluation index of bus operation status at the station level;
Figure FDA0002397652520000022
Figure FDA0002397652520000022
 其中，Tstop(i+1,j)为j线路第i+1班公交车到达站点S的时间；Tstop(i,j)为j线路第i班公交车到达站点S的时间；Dint(i,j)为运营时刻表规定的j线路第i+1班公交车和第i班公交车的发车间隔；i为公交班次编号且i＝1,2,3...；j为公交线路编号且j＝1,2,3...；Among them, T stop (i+1,j) is the time when the i+1th bus of line j arrives at station S; T stop (i,j) is the time when the i-th bus of line j arrives at station S; D int (i,j) is the departure interval of the i+1th bus and the ith bus of the j line specified in the operation timetable; i is the bus number and i=1,2,3...; j is the bus line number and j=1,2,3...; 第二步，构建线路层面的公交运行状态综合评价指标；The second step is to construct a comprehensive evaluation index of bus operation status at the line level;
Figure FDA0002397652520000023
Figure FDA0002397652520000023
Figure FDA0002397652520000024
Figure FDA0002397652520000024
 其中，Tsec,j(L,i)为j线路第i班公交车到达关键节点L的时间；Ssec,j(L)为运营时刻表规定的j线路公交车到达关键节点L的时间；η为公交运营效益；
Figure FDA0002397652520000025
为j线路第i班公交车到达关键节点L时的累计运输乘客数；
Figure FDA0002397652520000026
为j线路公交车到达关键节点L时的历史累计运输乘客数；m为j线路公交车到达关键节点L时的累计通过站点数；i为公交班次编号且i＝1,2,3...；j为公交线路编号且j＝1,2,3...；k＝1,2,3...m；Among them, T sec,j (L,i) is the time for the i-th bus of line j to reach the key node L; S sec,j (L) is the time for the bus of line j to reach the key node L specified in the operation schedule; η is the bus operation benefit;
Figure FDA0002397652520000025
is the cumulative number of passengers transported when the i-th bus of line j arrives at the key node L;
Figure FDA0002397652520000026
is the historical cumulative number of passengers transported when the j-line bus reaches the key node L; m is the cumulative number of stations passed by the j-line bus when it reaches the key node L; i is the bus schedule number and i=1,2,3... ;j is the bus line number and j=1,2,3...;k=1,2,3...m; 第三步，构建线网层面的公交运行状态综合评价指标；The third step is to construct a comprehensive evaluation index of bus operation status at the line network level;
Figure FDA0002397652520000031
Figure FDA0002397652520000031
 其中，p为该公交线网所包含的站点总数；q(k)为站点k所包含的公交线路总数；t为该公交线网所包含的路段关键节点总数；r(k)为站点k所包含的公交线路总数；Among them, p is the total number of stations included in the bus line network; q(k) is the total number of bus lines included in site k; t is the total number of key nodes in the road section included in the bus line network; r(k) is the total number of bus lines included in site k the total number of bus routes included; 步骤四包括以下步骤：Step four includes the following steps: 第一步，针对公交线路j上的站点L＝1,2,3...d，如果存在
Figure FDA0002397652520000032
则公交线路j在站点层面不存在运行瓶颈；其中，d为公交线路j的站点总数，ΩS为站点层面的公交瓶颈评判标准且ΩS∈[0,1]；The first step, for the station L=1,2,3...d on the bus line j, if there is
Figure FDA0002397652520000032
Then bus line j has no operation bottleneck at the station level; where d is the total number of stations of bus line j, Ω S is the bus bottleneck evaluation criterion at the station level and Ω S ∈ [0,1]; 第二步，针对公交线路j上的站点k＝1,2,3...d，如果存在
Figure FDA0002397652520000033
则公交线路j具有运行瓶颈，且输出公交线路j的站点瓶颈为站点k，k∈[1,d]；The second step, for the station k=1,2,3...d on the bus line j, if there is
Figure FDA0002397652520000033
Then bus line j has an operation bottleneck, and the station bottleneck of output bus line j is station k, k∈[1,d]; 步骤五包括以下步骤：Step five includes the following steps: 第一步，针对公交线路j上的路段关键节点L＝1,2,3...e，如果存在
Figure FDA0002397652520000034
则公交线路j在线路层面不存在运行瓶颈；其中，e为公交线路j的路段关键节点总数，ΩL为线路层面的公交瓶颈评判标准且ΩL∈[0,1]；The first step is for the key nodes L=1, 2, 3...e of the road section on the bus line j, if there is
Figure FDA0002397652520000034
Then the bus line j does not have an operation bottleneck at the line level; among them, e is the total number of key nodes in the section of bus line j, Ω L is the bus bottleneck evaluation criterion at the line level and Ω L ∈ [0,1]; 第二步，针对公交线路j上的路段关键节点L＝1,2,3...e，如果存在
Figure FDA0002397652520000035
则公交线路j在线路层面存在运行瓶颈，且输出公交线路j的线路瓶颈为路段关键节点L，L∈[1,e]；In the second step, for the key nodes L=1, 2, 3...e of the road section on the bus line j, if there is
Figure FDA0002397652520000035
Then the bus line j has an operation bottleneck at the line level, and the line bottleneck of the output bus line j is the key node L, L∈[1,e]; 步骤六包括以下步骤：Step six includes the following steps: 第一步，如果存在HRIN≤ΩN且TTRN≤Ω′N，则该公交线网在线网层面不存在运行瓶颈；In the first step, if there is HRI N ≤Ω N and TTR N ≤Ω′ N , there is no operational bottleneck at the online network level of the bus network; 其中，ΩN为线网层面的公交瓶颈评判标准且ΩN∈[0,1]；Among them, Ω N is the bus bottleneck evaluation standard at the line network level and Ω N ∈ [0,1]; 第二步，如果存在HRIN＞ΩN且TTRN＞Ω′N，则该公交线网在线网层面存在运行瓶颈，返回步骤四和步骤五寻找具体瓶颈位置。In the second step, if there is HRI N >Ω N and TTR N >Ω′ N , then the bus network has an operation bottleneck at the online network level, and returns to steps 4 and 5 to find the specific bottleneck location.
CN201610948332.1A 2016-10-26 2016-10-26 A method for diagnosing bottlenecks in bus operation Active CN106530176B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201610948332.1A CN106530176B (en) 2016-10-26 2016-10-26 A method for diagnosing bottlenecks in bus operation

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201610948332.1A CN106530176B (en) 2016-10-26 2016-10-26 A method for diagnosing bottlenecks in bus operation

Publications (2)

Publication Number Publication Date
CN106530176A CN106530176A (en) 2017-03-22
CN106530176B true CN106530176B (en) 2020-04-28

Family

ID=58293220

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201610948332.1A Active CN106530176B (en) 2016-10-26 2016-10-26 A method for diagnosing bottlenecks in bus operation

Country Status (1)

Country Link
CN (1) CN106530176B (en)

Families Citing this family (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106991804B (en) * 2017-04-26 2020-09-22 长安大学 A method for constructing urban public transport conditions based on multi-line coupling
CN109543934B (en) * 2018-10-08 2021-11-02 北京交通大学 Evaluation method of comprehensive index of urban bus network

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101572011A (en) * 2009-06-10 2009-11-04 上海理工大学 System and method for intelligently dispatching and managing urban public transports
CN101872544A (en) * 2010-06-12 2010-10-27 江苏省交通科学研究院股份有限公司 Simple urban road congestion statistic evaluation method
CN101944288A (en) * 2010-08-25 2011-01-12 东南大学 Method for setting stop stations of urban bus line
CN102800190A (en) * 2012-07-27 2012-11-28 北京工业大学 Bus transportation velocity extraction method based GPS (Global Positioning System) data of bus
CN103680163A (en) * 2013-12-03 2014-03-26 青岛海信网络科技股份有限公司 Regional bus signal priority method based on bus demands

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101572011A (en) * 2009-06-10 2009-11-04 上海理工大学 System and method for intelligently dispatching and managing urban public transports
CN101872544A (en) * 2010-06-12 2010-10-27 江苏省交通科学研究院股份有限公司 Simple urban road congestion statistic evaluation method
CN101944288A (en) * 2010-08-25 2011-01-12 东南大学 Method for setting stop stations of urban bus line
CN102800190A (en) * 2012-07-27 2012-11-28 北京工业大学 Bus transportation velocity extraction method based GPS (Global Positioning System) data of bus
CN103680163A (en) * 2013-12-03 2014-03-26 青岛海信网络科技股份有限公司 Regional bus signal priority method based on bus demands

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
"一路一线直行式"公交模式下公交车行驶诱导和调度集成方法;王炜;《东南大学学报（自然科学版）》;20081130;第36卷(第6期);全文 *
基于公交OD数据的居民公交出行特征研究;芦方强;《交通运输工程与信息学报》;20100630;第8卷(第2期);全文 *

Also Published As

Publication number Publication date
CN106530176A (en) 2017-03-22

Similar Documents

Publication Publication Date Title
CN107545320B (en) A method and system for urban rail transit passenger path planning based on graph theory
CN109272175B (en) A data collection system and method based on urban mobile network
CN104778834B (en) Urban road traffic jam judging method based on vehicle GPS data
Shaheen et al. Intelligent transportation systems
CN105844362B (en) Urban traffic comprehensive trip decision-making device
CN110111575A (en) A kind of Forecast of Urban Traffic Flow network analysis method based on Complex Networks Theory
CN102521965B (en) Effect evaluation method of traffic demand management measures based on identification data of license plates
Ma et al. Modeling bus travel time reliability with supply and demand data from automatic vehicle location and smart card systems
CN111191816B (en) System for identifying travel time chain of urban rail transit passengers
CN110363985B (en) Traffic data analysis method, device, storage medium and equipment
CN101615340A (en) Real-time Information Processing Method in Dynamic Bus Dispatching
CN105809292A (en) Passenger getting-off station reckoning method of bus IC (Integrated Circuit) card
CN111932925A (en) Method, device and system for determining travel passenger flow of public transport station
Ram et al. SMARTBUS: A web application for smart urban mobility and transportation
CN103714696B (en) High-speed transit information access disposal system
CN108364464B (en) A Probabilistic Model-Based Method for Modeling Travel Time of Public Transport Vehicles
Yatskiv et al. Evaluating Riga transport system accessibility
CN106530176B (en) A method for diagnosing bottlenecks in bus operation
CN105070060B (en) A kind of urban road traffic state method of discrimination based on public transport vehicle-mounted gps data
Das et al. Smart urban traffic management system
Oskarbski et al. Multi-level transport systems model for traffic management activities
CN211604175U (en) Data acquisition system based on urban mobile network
Krishna et al. Analysis of urban public transportation network in Hyderabad: Telangana
Erdei et al. Analysis of flexibility on the FTS
Nagpal Urban Computing: Key Challenges and Issues of Traffic Management System

Legal Events

Date Code Title Description
C06 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant
TR01 Transfer of patent right
TR01 Transfer of patent right

Effective date of registration: 20201231

Address after: 272000 37 Jining Avenue, taibaihu New District, Jining City, Shandong Province

Patentee after: SHANDONG POLYTECHNIC College

Address before: 710064 Shaanxi province Xi'an Beilin District South Second Ring Road No. 33 in the middle

Patentee before: CHANG'AN University

TR01 Transfer of patent right
TR01 Transfer of patent right

Effective date of registration: 20211026

Address after: 272000 Beihu provincial tourist resort, Jining City, Shandong Province 908, 9th floor, administration building, Shandong Polytechnic Vocational College

Patentee after: Jining Siyuan Business Service Co.,Ltd.

Address before: 272000 37 Jining Avenue, taibaihu New District, Jining City, Shandong Province

Patentee before: SHANDONG POLYTECHNIC College

PE01 Entry into force of the registration of the contract for pledge of patent right
PE01 Entry into force of the registration of the contract for pledge of patent right

Denomination of invention: A diagnosis method of bus operation bottleneck

Effective date of registration: 20221123

Granted publication date: 20200428

Pledgee: Jining Rushang Village Bank Co.,Ltd. Tangkou sub branch

Pledgor: Jining Siyuan Business Service Co.,Ltd.

Registration number: Y2022980022977