CN115050186A - Road intelligent rescue management platform based on big data analysis - Google Patents
Road intelligent rescue management platform based on big data analysis Download PDFInfo
- Publication number
- CN115050186A CN115050186A CN202210704913.6A CN202210704913A CN115050186A CN 115050186 A CN115050186 A CN 115050186A CN 202210704913 A CN202210704913 A CN 202210704913A CN 115050186 A CN115050186 A CN 115050186A
- Authority
- CN
- China
- Prior art keywords
- bus
- rescue
- braking
- safety
- power
- 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.)
- Pending
Links
Images
Classifications
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
- G08G1/0125—Traffic data processing
-
- 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
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0635—Risk analysis of enterprise or organisation activities
-
- 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—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
- G06Q50/10—Services
- G06Q50/26—Government or public services
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
- G08G1/0137—Measuring and analyzing of parameters relative to traffic conditions for specific applications
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/052—Detecting movement of traffic to be counted or controlled with provision for determining speed or overspeed
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/123—Traffic control systems for road vehicles indicating the position of vehicles, e.g. scheduled vehicles; Managing passenger vehicles circulating according to a fixed timetable, e.g. buses, trains, trams
Landscapes
- Business, Economics & Management (AREA)
- General Physics & Mathematics (AREA)
- Physics & Mathematics (AREA)
- Human Resources & Organizations (AREA)
- Engineering & Computer Science (AREA)
- Strategic Management (AREA)
- Economics (AREA)
- Tourism & Hospitality (AREA)
- Entrepreneurship & Innovation (AREA)
- Theoretical Computer Science (AREA)
- Analytical Chemistry (AREA)
- Chemical & Material Sciences (AREA)
- Marketing (AREA)
- Educational Administration (AREA)
- General Business, Economics & Management (AREA)
- Development Economics (AREA)
- Radar, Positioning & Navigation (AREA)
- Game Theory and Decision Science (AREA)
- Remote Sensing (AREA)
- Health & Medical Sciences (AREA)
- General Health & Medical Sciences (AREA)
- Primary Health Care (AREA)
- Quality & Reliability (AREA)
- Operations Research (AREA)
- Traffic Control Systems (AREA)
Abstract
The invention discloses a road intelligent rescue management platform based on big data analysis. The road intelligent rescue management platform based on big data analysis comprises a bus reference information acquisition module, a bus power information acquisition and analysis module, a bus running parameter acquisition module, a bus brake information acquisition module, a bus brake safety analysis module, a bus rescue demand evaluation analysis module, a database and a bus rescue matching analysis and processing module; the bus is subjected to rescue demand assessment and automatic rescue calling through three layers of power information, driving information and braking information of each bus configured in the specified driving route, the problem that the damage degree of the bus accident cannot be reduced in the prior art is effectively solved, abnormal timely early warning of the bus is realized, the damage degree of the bus and the damage degree of the bus accident are greatly reduced, and the intelligent level is high.
Description
Technical Field
The invention belongs to the technical field of road rescue management, and relates to a road intelligent rescue management platform based on big data analysis.
Background
With the rapid development of economy and the gradual improvement of traffic systems, the traveling modes of people gradually become diversified. The bus is used as a necessary vehicle for urban travel, and the severity of damage caused by accidents is self-evident, so that the bus is particularly important for road rescue management of sudden problems.
When current road rescue management mainly breaks down for the bus or the accident, through personnel call road rescue hotline, and then the rescue activity is implemented to the bus to the corresponding vehicle of road rescue management center dispatching, and it is very obvious that the current technology still has the problem in several following aspects:
on the first hand, because the bus has a large passenger capacity, the loss rate caused by the fault is also large, the damage degree of the bus accident cannot be effectively reduced only by rescuing the bus after the bus fault occurs at present, meanwhile, the bus is damaged to a certain extent, the fault loss rate of the bus cannot be reduced, and the safety of passengers cannot be guaranteed;
on the second hand, accidents or faults of buses are not always accidental events, certain calls exist, and the awareness of personnel on the calls is insufficient, so that the current bus detection method has certain limitations, cannot reduce the accident rate of the buses, cannot reduce the difficulty of road rescue, and cannot improve the road rescue efficiency;
in the third aspect, the situation that calling is not timely exists in the current mode of carrying out road rescue by calling a rescue hot line through personnel, the timeliness of bus rescue cannot be improved, the potential safety hazard of personnel caused by bus faults or accidents cannot be reduced, the rescue effect cannot be improved, and the intelligent degree is low.
Disclosure of Invention
In view of this, in order to solve the problems in the background art, an intelligent road rescue management platform based on big data analysis is proposed;
the purpose of the invention can be realized by the following technical scheme:
the invention provides a road intelligent rescue management platform based on big data analysis, which comprises:
the bus reference information acquisition module is used for acquiring the number of buses configured in a specified driving route, and numbering the buses as 1,2,. j,. m in sequence;
the bus power information acquisition and analysis module is used for acquiring the current corresponding power information of each power unit through a power acquisition device carried by each bus, so as to analyze the current corresponding power state of each bus and output a power safety evaluation index corresponding to each bus;
the bus driving parameter acquisition module is used for acquiring current corresponding driving parameters of each bus through a driving acquisition device carried by each bus, wherein the driving parameters comprise positions, passenger carrying capacity and driving speed;
the bus braking information acquisition module is used for acquiring the current corresponding braking information of each bus, wherein the braking information comprises the accumulated braking times, the corresponding braking starting time point, the corresponding braking stopping time point and the corresponding braking distance during each braking;
the bus braking safety analysis module is used for analyzing the braking safety corresponding to each bus based on the current corresponding running parameter and braking information of each bus and outputting a braking safety evaluation index corresponding to each bus;
the bus rescue demand evaluation analysis module is used for analyzing and obtaining the number of buses needing rescue and rescue types corresponding to the buses needing rescue based on the power safety evaluation index and the braking safety evaluation index corresponding to each bus and constructing a rescue report;
the bus rescue matching analysis and processing module is used for performing matching analysis on target rescue stations of buses needing rescue based on rescue types corresponding to the buses needing rescue, sending rescue reports to the target rescue stations corresponding to the buses needing rescue, and simultaneously performing automatic rescue calling;
and the database is used for storing the corresponding positions of the rescue stations and the corresponding states of the rescue type vehicles in the rescue stations.
As a preferred scheme, the power acquisition device comprises a liquid level sensor, a temperature sensor, an air tightness detector, a vehicle-mounted ammeter, a vehicle-mounted voltmeter, an electric quantity collector and a pressure sensor.
Preferably, each power unit is respectively a water tank unit, an electric unit and a tire unit; wherein the content of the first and second substances,
the power information corresponding to the water tank unit is liquid level height, water body temperature and box body air tightness;
the power information corresponding to the electric unit is running current, running voltage and residual electric quantity;
the power information corresponding to the tire unit is the tire pressure corresponding to each tire.
As a preferred scheme, the current corresponding power state of each bus is analyzed, and the specific analysis process comprises the following steps:
step 1, extracting power information corresponding to water tank units from power information corresponding to power units in buses at present, calculating by using a calculation formula to obtain safety assessment indexes of the water tanks of the buses, and recording the safety assessment indexes as safety assessment indexes
j represents a bus number, j is 1, 2.
Step 2, extracting power information corresponding to the electric unit from the power information corresponding to each power unit in each bus at present, calculating by using a calculation formula to obtain an electric safety evaluation index of each bus, and recording the electric safety evaluation index as the electric safety evaluation index
Step 3, extracting power information corresponding to the tire units from the power information corresponding to the power units in the buses, calculating by using a calculation formula to obtain tire safety evaluation indexes of the buses, and recording the tire safety evaluation indexes as tire safety evaluation indexes
Step 4, safety assessment index based on each bus water tank
Index of electrical safety assessment
Tire safety evaluation index
Substitute it into the calculation formula
In the method, power safety evaluation indexes, Q, corresponding to all buses are obtained j The evaluation index is expressed as a power safety evaluation index corresponding to the jth bus, and epsilon 1, epsilon 2 and epsilon 3 are expressed as ratio weights corresponding to set water tank safety, electrical safety and tire safety respectively.
As a preferred scheme, the driving collection device specifically comprises a vehicle speed sensor, a GPS locator and a weight sensor, wherein the vehicle speed sensor is used for collecting the driving speed corresponding to the bus, the GPS locator is used for collecting the position corresponding to the bus, and the weight sensor is used for collecting the passenger carrying capacity corresponding to the bus.
As a preferred scheme, the analysis of the braking safety corresponding to each bus is performed, and the specific analysis process comprises the following steps:
firstly, setting the braking safety influence weight corresponding to each bus based on the current corresponding driving parameters of each bus, and recording the weight as delta j ；
Secondly, extracting accumulated braking times from the current corresponding braking information of each bus, numbering the brakes of each bus according to the braking sequence of each bus, and marking the brakes as 1,2,. d,. g;
thirdly, extracting the starting time point and the stopping time point corresponding to each braking from the current braking information corresponding to each bus, further obtaining the braking duration corresponding to each braking, and recording the duration as T jd D represents the number of each brake, and d is 1, 2.
Fourthly, based on the braking duration and the braking distance corresponding to the current braking of each bus and the braking safety influence weight corresponding to each bus, according to an analysis formula
Analyzing to obtain the correspondence of each busZeta index of power safety assessment j Expressing the power safety evaluation index corresponding to the jth bus, wherein T' is the set reference braking duration corresponding to the bus, and X jd The braking distance corresponding to the d-th braking of the jth bus is represented, X' is a reference braking distance corresponding to the set bus, delta T and delta X are a set allowable braking time length difference and an allowable braking distance difference, and c1 and c2 are respectively represented as a weighting factor corresponding to the set braking time length and a weighting factor corresponding to the braking distance.
As a preferred scheme, the braking safety influence weight corresponding to each bus is set, and the specific setting process is as follows:
extracting the running speed from the current corresponding running parameters of each bus through an analysis formula
Analyzing and obtaining the braking safety weight coefficient mu 1 corresponding to the running speed of each bus j ，v j The current corresponding running speed of the jth bus is shown, and v' shows the set standard running speed corresponding to the bus;
extracting passenger carrying capacity from the current corresponding driving parameters of each bus, matching and comparing the passenger carrying capacity corresponding to the bus with the set braking safety weight coefficient corresponding to each load, screening to obtain the braking safety weight coefficient corresponding to the passenger carrying capacity of each bus, and recording as mu 2 j ；
Based on the braking safety weight coefficient corresponding to the running speed and the braking safety weight coefficient corresponding to the passenger carrying weight of each bus, the braking safety influence weight corresponding to each bus is calculated, and the calculation formula is as follows
f1 and f2 are correction factors corresponding to the set traveling speed and the set passenger load, respectively.
As an optimal scheme, the number of buses needing rescue and the specific analysis process of the rescue types corresponding to the buses needing rescue configuration are as follows:
comparing the power safety evaluation index corresponding to each bus with a set standard power safety evaluation index, if the power safety evaluation index corresponding to a certain bus is smaller than the standard power safety evaluation index, judging that the bus needs to be rescued, and recording the rescue type corresponding to the bus as a power rescue type;
comparing the braking safety evaluation index corresponding to each bus with a set standard braking safety evaluation index, if the braking safety evaluation index corresponding to a certain bus is smaller than the standard braking safety evaluation index, judging that the bus needs to be rescued, and recording the rescue type corresponding to the bus as a braking rescue type;
if the rescue type corresponding to a certain bus comprises a dynamic rescue type and a braking rescue type, the rescue type corresponding to the bus is a comprehensive rescue type, and the number of buses needing rescue and the rescue type corresponding to each bus needing rescue are counted.
As a preferable scheme, the rescue report is specifically constructed by the following steps: and acquiring the corresponding position of each bus needing rescue, and integrating the corresponding position and rescue type of each bus needing rescue to form a rescue report corresponding to each bus needing rescue.
As a preferred scheme, the matching analysis is performed on the target rescue stations corresponding to the buses needing rescue, and the specific analysis process is as follows:
extracting the corresponding position of each rescue station from the database, and numbering each rescue station;
extracting the number corresponding to each bus needing rescue, calculating the position matching degree of each bus needing rescue and each rescue station based on the position corresponding to each bus needing rescue, and recording the position matching degree as B t←x T is a number corresponding to each bus needing rescue, t is 1,2, and.
Extracting the corresponding state of each rescue type vehicle in each rescue station from the database, analyzing and obtaining the type matching degree of each bus needing rescue and each rescue station based on the rescue type corresponding to each bus needing rescue,and is marked as
Based on the position matching degree and the type matching degree of each bus needing rescue and each rescue station, the calling optimization coefficient of each bus needing rescue and each rescue station is obtained through analysis, and the analysis formula is
The calling preference coefficients corresponding to the xth rescue stations are represented as t buses needing rescue,
the ratio weights are respectively corresponding to the set position and type;
and sequencing calling optimization coefficients of the buses needing rescue and the rescue stations from large to small, and taking the first-ranked rescue station as a target rescue station corresponding to each bus needing rescue.
Compared with the prior art, the invention has the following beneficial effects:
(1) according to the road intelligent rescue management platform based on big data analysis, rescue demand evaluation and automatic rescue calling are carried out on buses from three layers of power information, driving information and braking information of each bus configured in a specified driving route, on one hand, the problem that the harm degree of accidents of the buses cannot be reduced in the prior art is effectively solved, timely early warning of bus abnormity is realized, the damage degree and the harm degree of the accidents of the buses are greatly reduced, powerful guarantee is provided for the safety of passengers, on the other hand, rescue demand evaluation is carried out according to three dimensions of the power information, the driving information and the braking information of the buses, the limitation, the one-sidedness and the generality of the current bus rescue evaluation mode are broken, the subjective error of personnel detection is avoided, and the response efficiency of bus abnormity is improved, the accident rate and the road rescue difficulty of the bus are reduced, and the efficient and timely road emergency rescue is realized; on the other hand, through automatic rescue calling, the timeliness of bus rescue is guaranteed, the potential safety hazard of personnel caused by bus faults or accidents is reduced, and the intelligent level is high.
(2) According to the invention, by collecting and analyzing the power information, the driving information and the braking information of each bus, the abnormal timely rescue of the bus is realized, the comprehensiveness, the reliability and the rationality of the bus driving safety detection are improved, meanwhile, the positioning efficiency and the processing efficiency of the abnormal events of the bus are ensured to the greatest extent through the collection and analysis of a plurality of dimensional information, the complexity of bus road rescue can be effectively reduced, and the smoothness of the road rescue and the management level of the road rescue are improved.
(3) According to the invention, the rescue stations are subjected to matching analysis based on the rescue types corresponding to the buses needing rescue, so that the arrival efficiency and the rescue effect of the rescue vehicles are improved to the greatest extent, the processing efficiency of bus rescue events is ensured, the rapid rescue of the buses and the rapid dredging of roads are realized, and powerful guarantee is provided for the stable operation of road traffic.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a schematic diagram of the connection of the modules of the system of the present invention.
Detailed Description
While the foregoing is directed to embodiments of the present invention, other and further embodiments of the invention may be devised without departing from the basic scope thereof, and the scope thereof is determined by the claims that follow.
Referring to fig. 1, the invention provides a road intelligent rescue management platform based on big data analysis, which comprises a bus reference information acquisition module, a bus power information acquisition and analysis module, a bus driving parameter acquisition module, a bus braking information acquisition module, a bus braking safety analysis module, a bus rescue demand evaluation analysis module, a database and a bus rescue matching analysis and processing module.
Based on the connection relation shown in the figure, the bus reference information acquisition module is connected with the bus power information acquisition and analysis module, the bus brake safety analysis module is respectively connected with the bus running parameter acquisition module and the bus brake information acquisition module, the bus rescue demand evaluation analysis module is respectively connected with the bus power information acquisition and analysis module and the bus brake safety analysis module, and the bus brake safety analysis module is respectively connected with the bus rescue demand evaluation analysis module and the database;
the bus reference information acquisition module is used for acquiring the number of buses configured in a specified driving route, and the number of each bus is 1,2,. j,. m;
the bus power information acquisition and analysis module is used for acquiring the current corresponding power information of each power unit through a power acquisition device carried by each bus, so as to analyze the current corresponding power state of each bus and output a power safety evaluation index corresponding to each bus;
in the above, the power collecting device includes a liquid level sensor, a temperature sensor, an air tightness detector, a vehicle-mounted ammeter, a vehicle-mounted voltmeter, an electric quantity collector and a pressure sensor;
the power units are respectively a water tank unit, an electric unit and a tire unit; wherein the power information corresponding to the water tank unit comprises liquid level height, water body temperature and box body air tightness; the power information corresponding to the electric unit is running current, running voltage and residual electricity; the power information corresponding to the tire unit is the tire pressure corresponding to each tire.
The liquid level sensor is used for collecting the liquid level height corresponding to the bus water tank unit, the temperature sensor is used for collecting the water body temperature corresponding to the bus water tank unit, and the air tightness detector is used for detecting the air tightness of the box body corresponding to the bus water tank unit; the vehicle-mounted ammeter, the vehicle-mounted voltmeter and the electric quantity collector are respectively used for collecting the running current, the running voltage and the residual electric quantity corresponding to the electric unit of the bus; the pressure sensor is used for collecting tire units corresponding to the bus.
In the foregoing, the analysis of the current corresponding power state of each bus includes the following steps:
step 1, extracting power information corresponding to water tank units from power information corresponding to power units in buses at present, calculating by using a calculation formula to obtain safety assessment indexes of the water tanks of the buses, and recording the safety assessment indexes as safety assessment indexes
Wherein the content of the first and second substances,
a1, a2 and a3 respectively represent the safety influence weights corresponding to the set water tank liquid level, water tank water temperature and water tank air density, L j 、w j 、q j Respectively expressed as the current corresponding liquid level height, water body temperature and box body air tightness L 'of the jth bus water tank unit' min 、w Standard of merit 、Δw、q Standard of reference The minimum required liquid level height, the standard water body temperature, the allowable water tank temperature difference and the standard box body air tightness which correspond to the set bus water tank are respectively expressed, j represents the bus number, and j is 1, 2;
step 2, extracting power information corresponding to the electric unit from the power information corresponding to each power unit in each bus at present, calculating by using a calculation formula to obtain an electric safety evaluation index of each bus, and recording the electric safety evaluation index as the electric safety evaluation index
b1, b2 and b3 represent operation safety influence weights corresponding to set operation current, operation voltage and residual capacity, I j 、U j 、D j Respectively representing the current corresponding running current, running voltage and residual electric quantity of the jth bus electrical unit, wherein I ', U' is the set standard running current of the bus, the standard running voltage of the bus, delta I, delta U are respectively represented as the set allowable running current difference, allowable running voltage difference and D min The method comprises the following steps of setting the lowest driving demand electric quantity corresponding to a bus;
step 3, extracting power information corresponding to the tire units from the power information corresponding to the power units in the buses, calculating by using a calculation formula to obtain tire safety evaluation indexes of the buses, and recording the tire safety evaluation indexes as tire safety evaluation indexes
N jr The tire pressure is expressed as the tire pressure corresponding to the r-th tire in the jth bus, r is the tire number, r is 1,2, the preset standard tire pressure corresponding to the bus tire, N' is the preset reference bus proper tire pressure, delta N is the preset bus tire pressure allowable difference, and eta is the preset tire safety correction factor;
in one embodiment, p has a value of 5;
step 4, safety assessment index based on each bus water tank
Index of electrical safety assessment
Tire safety evaluation index
Substitute it into the calculation formula
In the method, power safety evaluation indexes, Q, corresponding to all buses are obtained j The evaluation index is expressed as a power safety evaluation index corresponding to the jth bus, and epsilon 1, epsilon 2 and epsilon 3 are expressed as ratio weights corresponding to set water tank safety, electrical safety and tire safety respectively.
The bus driving parameter acquisition module is used for acquiring current corresponding driving parameters of each bus through a driving acquisition device carried by each bus, wherein the driving parameters comprise positions, passenger carrying capacity and driving speed;
it should be noted that the driving collection device specifically comprises a vehicle speed sensor, a GPS locator and a weight sensor, wherein the vehicle speed sensor is used for collecting the driving speed corresponding to the bus, the GPS locator is used for collecting the position corresponding to the bus, and the weight sensor is used for collecting the passenger carrying capacity corresponding to the bus.
The bus braking information acquisition module is used for acquiring the current corresponding braking information of each bus, wherein the braking information comprises the accumulated braking times, the corresponding braking starting time point, the corresponding braking stopping time point and the corresponding braking distance during each braking;
the bus braking safety analysis module is used for analyzing the braking safety corresponding to each bus based on the current corresponding running parameter and braking information of each bus and outputting a braking safety evaluation index corresponding to each bus;
illustratively, the analysis of the braking safety corresponding to each bus includes the following steps:
firstly, setting the braking safety influence weight corresponding to each bus based on the current corresponding driving parameters of each bus, and recording the weight as delta j ；
Secondly, extracting accumulated braking times from the current corresponding braking information of each bus, numbering the brakes of each bus according to the braking sequence of each bus, and marking the brakes as 1,2,. d,. g;
thirdly, extracting the starting time point and the stopping time point corresponding to each braking from the current braking information corresponding to each bus, further obtaining the braking duration corresponding to each braking, and recording the braking duration as T jd D represents the number of each brake, and d is 1, 2.
Fourthly, based on the braking duration and the braking distance corresponding to the current braking of each bus and the braking safety influence weight corresponding to each bus, according to an analysis formula
Analyzing to obtain the power safety evaluation index, zeta, corresponding to each bus j Expressing the power safety evaluation index corresponding to the jth bus, wherein T' is the set reference braking duration corresponding to the bus, and X jd The braking distance corresponding to the d-th braking of the jth bus is represented, X' is a reference braking distance corresponding to the set bus, delta T and delta X are a set allowable braking time length difference and an allowable braking distance difference, and c1 and c2 are respectively represented as a weighting factor corresponding to the set braking time length and a weighting factor corresponding to the braking distance.
Further, the braking safety influence weight corresponding to each bus is set, and the specific setting process is as follows:
extracting the running speed from the current corresponding running parameters of each bus through an analysis formula
Analyzing and obtaining the braking safety weight coefficient mu 1 corresponding to the running speed of each bus j ，v j The current corresponding running speed of the jth bus is shown, and v' shows the set standard running speed corresponding to the bus;
extracting passenger carrying weight from the current corresponding driving parameters of each bus, matching and comparing the passenger carrying weight corresponding to the bus with the set braking safety weight coefficient corresponding to each load, and screening to obtain the braking safety corresponding to the passenger carrying weight of each busWeight coefficient and is recorded as mu 2 j ；
Based on the braking safety weight coefficient corresponding to the running speed and the braking safety weight coefficient corresponding to the passenger carrying weight of each bus, the braking safety influence weight corresponding to each bus is calculated, and the calculation formula is as follows
f1 and f2 are correction factors corresponding to the set traveling speed and the set passenger load, respectively.
According to the embodiment of the invention, the power information, the driving information and the braking information of each bus are collected and analyzed, so that the abnormal timely rescue of the bus is realized, the comprehensiveness, the reliability and the reasonability of the bus driving safety detection are improved, meanwhile, the positioning efficiency and the processing efficiency of the abnormal events of the bus are ensured to the greatest extent through the collection and analysis of a plurality of dimensional information, the complexity of bus road rescue can be effectively reduced, and the smoothness of the road rescue and the management level of the road rescue are improved.
The bus rescue demand evaluation analysis module is used for analyzing and obtaining the number of buses needing rescue and rescue types corresponding to the buses needing rescue based on the power safety evaluation index and the braking safety evaluation index corresponding to each bus and constructing a rescue report;
illustratively, the specific analysis process of the number of buses needing rescue and the rescue types corresponding to the buses needing rescue configuration is as follows:
comparing the power safety evaluation index corresponding to each bus with a set standard power safety evaluation index, if the power safety evaluation index corresponding to a certain bus is smaller than the standard power safety evaluation index, judging that the bus needs to be rescued, and recording the rescue type corresponding to the bus as a power rescue type;
comparing the braking safety evaluation index corresponding to each bus with a set standard braking safety evaluation index, if the braking safety evaluation index corresponding to a certain bus is smaller than the standard braking safety evaluation index, judging that the bus needs to be rescued, and recording the rescue type corresponding to the bus as a braking rescue type;
if the rescue type corresponding to a certain bus comprises a dynamic rescue type and a braking rescue type, the rescue type corresponding to the bus is a comprehensive rescue type, and the number of buses needing rescue and the rescue type corresponding to each bus needing rescue are counted.
Further, the rescue report is specifically constructed by the following steps: and acquiring the corresponding position of each bus needing rescue, and integrating the corresponding position and rescue type of each bus needing rescue to form a rescue report corresponding to each bus needing rescue.
The bus rescue matching analysis and processing module is used for carrying out matching analysis on target rescue stations of buses to be rescued based on rescue types corresponding to the buses to be rescued, sending rescue reports to the target rescue stations corresponding to the buses to be rescued and carrying out automatic rescue calling;
specifically, the matching analysis is performed on the target rescue stations corresponding to the buses needing rescue, and the specific analysis process is as follows:
1) extracting the corresponding position of each rescue station from the database, and numbering each rescue station;
2) extracting the number corresponding to each bus needing rescue, calculating the position matching degree of each bus needing rescue and each rescue station based on the position corresponding to each bus needing rescue, and recording the position matching degree as B t←x T is a number corresponding to each bus needing rescue, t is 1,2, and.
Wherein the content of the first and second substances,
and S' is a set rescue preferred reference distance.
3) Extracting rescues from a databaseThe corresponding state of each rescue type vehicle in the station is based on the rescue type corresponding to each bus needing rescue, the type matching degree of each bus needing rescue and each rescue station is obtained through analysis and recorded as
It should be noted that the schematic process of analyzing the type matching degree of each bus needing rescue and each rescue station is as follows: obtaining demand rescue vehicle types corresponding to buses needing rescue based on rescue types corresponding to the buses needing rescue, recording the type matching degree of the buses needing rescue and the rescue station as sigma 1 if the demand rescue vehicle type corresponding to a bus needing rescue in a certain rescue station is in an occupied state, and recording the type matching degree of the buses needing rescue and the rescue station as sigma 2 if the demand rescue vehicle type corresponding to a bus needing rescue in a certain rescue station is in an idle state, so that the type matching degree of the buses needing rescue and the rescue stations is obtained through analysis
Values of σ 1 or σ 2, σ 2>σ1；
4) Based on the position matching degree and the type matching degree of each bus needing rescue and each rescue station, the calling optimization coefficient of each bus needing rescue and each rescue station is obtained through analysis, and the analysis formula is
Expressed as calling preference coefficients corresponding to t buses needing rescue and the xth rescue station,
respectively the set position and typeCorresponding proportion weight;
5) and sequencing calling preference coefficients of the buses to be rescued and the rescue stations from large to small, and taking the first-ranked rescue station as a target rescue station corresponding to each bus to be rescued.
According to the embodiment of the invention, the rescue station is subjected to matching analysis based on the rescue type corresponding to the bus needing rescue, so that the arrival efficiency and the rescue effect of the rescue vehicle are improved to the greatest extent, the processing efficiency of bus rescue events is ensured, the bus is quickly rescued, the road is quickly dredged, and powerful guarantee is provided for the stable operation of road traffic.
And the database is used for storing the corresponding positions of the rescue stations and the corresponding states of the rescue type vehicles in the rescue stations.
The embodiment of the invention carries out rescue demand evaluation and automatic rescue calling on the bus from three layers of power information, driving information and braking information of each bus configured in the designated driving route, on one hand, effectively solves the problem that the damage degree of the bus accident cannot be reduced by the current technology, realizes timely early warning of the bus abnormality, greatly reduces the damage degree of the bus and the damage degree of the accident, and provides powerful guarantee for the safety of passengers, on the other hand, carries out rescue demand evaluation according to three dimensions of the power information, the driving information and the braking information of the bus, breaks the limitation, one-sidedness and generality of the current bus rescue evaluation mode, avoids subjective errors existing in personnel detection, improves the response efficiency of the bus abnormality, reduces the accident occurrence rate and road rescue difficulty of the bus, the efficient and timely road emergency rescue is realized; on the other hand, through automatic rescue calling, the timeliness of bus rescue is guaranteed, the potential safety hazard of personnel caused by bus faults or accidents is reduced, and the intelligent level is high.
The foregoing is merely exemplary and illustrative of the principles of the present invention and various modifications, additions and substitutions of the specific embodiments described herein may be made by those skilled in the art without departing from the principles of the present invention or exceeding the scope of the claims set forth herein.
Claims (10)
1. The utility model provides a road intelligence rescue management platform based on big data analysis which characterized in that includes:
the bus reference information acquisition module is used for acquiring the number of buses configured in a specified driving route, and numbering the buses as 1,2,. j,. m in sequence;
the bus power information acquisition and analysis module is used for acquiring the current corresponding power information of each power unit through a power acquisition device carried by each bus, so as to analyze the current corresponding power state of each bus and output a power safety evaluation index corresponding to each bus;
the bus driving parameter acquisition module is used for acquiring current corresponding driving parameters of each bus through a driving acquisition device carried by each bus, wherein the driving parameters comprise positions, passenger carrying capacity and driving speed;
the bus braking information acquisition module is used for acquiring the current corresponding braking information of each bus, wherein the braking information comprises the accumulated braking times, the corresponding braking starting time point, the corresponding braking stopping time point and the corresponding braking distance during each braking;
the bus braking safety analysis module is used for analyzing the braking safety corresponding to each bus based on the current corresponding running parameter and braking information of each bus and outputting a braking safety evaluation index corresponding to each bus;
the bus rescue demand evaluation analysis module is used for analyzing and obtaining the number of buses needing rescue and rescue types corresponding to the buses needing rescue based on the power safety evaluation index and the braking safety evaluation index corresponding to each bus and constructing a rescue report;
the bus rescue matching analysis and processing module is used for performing matching analysis on target rescue stations of buses needing rescue based on rescue types corresponding to the buses needing rescue, sending rescue reports to the target rescue stations corresponding to the buses needing rescue, and simultaneously performing automatic rescue calling;
and the database is used for storing the corresponding positions of the rescue stations and the corresponding states of the rescue type vehicles in the rescue stations.
2. The intelligent road rescue management platform based on big data analysis as claimed in claim 1, wherein: the power acquisition device comprises a liquid level sensor, a temperature sensor, an air tightness detector, a vehicle-mounted ammeter, a vehicle-mounted voltmeter, an electric quantity collector and a pressure sensor.
3. The intelligent road rescue management platform based on big data analysis as claimed in claim 2, wherein: each power unit is respectively a water tank unit, an electric unit and a tire unit; wherein the content of the first and second substances,
the power information corresponding to the water tank unit is liquid level height, water body temperature and box body air tightness;
the power information corresponding to the electric unit is running current, running voltage and residual electric quantity;
the power information corresponding to the tire unit is the tire pressure corresponding to each tire.
4. The road intelligent rescue management platform based on big data analysis as claimed in claim 3, characterized in that: the method is characterized in that the current corresponding power state of each bus is analyzed, and the specific analysis process comprises the following steps:
step 1, extracting power information corresponding to water tank units from power information corresponding to power units in buses at present, calculating by using a calculation formula to obtain safety assessment indexes of the water tanks of the buses, and recording the safety assessment indexes as safety assessment indexes
j represents a bus number, j is 1, 2.
Step 2, extracting power information corresponding to the electric unit from the power information corresponding to each power unit in each bus at present, and calculating by using a calculation formulaAnd (5) outputting the electrical safety evaluation index of each bus and recording the index
Step 3, extracting power information corresponding to the tire units from the power information corresponding to the power units in the buses, calculating by using a calculation formula to obtain tire safety evaluation indexes of the buses, and recording the tire safety evaluation indexes as tire safety evaluation indexes
Step 4, safety assessment index based on each bus water tank
Index of electrical safety assessment
Tire safety evaluation index
Substitute it into the calculation formula
In the method, power safety evaluation indexes, Q, corresponding to all buses are obtained j The evaluation index is expressed as a power safety evaluation index corresponding to the jth bus, and epsilon 1, epsilon 2 and epsilon 3 are expressed as ratio weights corresponding to set water tank safety, electrical safety and tire safety respectively.
5. The intelligent road rescue management platform based on big data analysis as claimed in claim 1, wherein: the driving acquisition device specifically comprises a vehicle speed sensor, a GPS (global positioning system) positioner and a weight sensor, wherein the vehicle speed sensor is used for acquiring the driving vehicle speed corresponding to the bus, the GPS positioner is used for acquiring the position corresponding to the bus, and the weight sensor is used for acquiring the passenger carrying capacity corresponding to the bus.
6. The intelligent road rescue management platform based on big data analysis as claimed in claim 1, wherein: the method is characterized in that the braking safety corresponding to each bus is analyzed, and the specific analysis process comprises the following steps:
firstly, setting the braking safety influence weight corresponding to each bus based on the current corresponding driving parameters of each bus, and recording the weight as delta j ；
Secondly, extracting accumulated braking times from the current corresponding braking information of each bus, numbering the braking times of each bus according to the braking sequence of each bus, and marking the braking times as 1,2,. d,. g;
thirdly, extracting the starting time point and the stopping time point corresponding to each braking from the current braking information corresponding to each bus, further obtaining the braking duration corresponding to each braking, and recording the braking duration as T jd D represents the number of each brake, and d is 1, 2.
Fourthly, based on the braking duration and the braking distance corresponding to the current braking of each bus and the braking safety influence weight corresponding to each bus, according to an analysis formula
Analyzing to obtain the power safety evaluation index, zeta, corresponding to each bus j The power safety evaluation index corresponding to the jth bus is shown, T' is the set reference braking duration corresponding to the bus, X jd The braking distance corresponding to the d-th braking of the jth bus is represented, X' is a reference braking distance corresponding to the set bus, delta T and delta X are a set allowable braking time length difference and an allowable braking distance difference, and c1 and c2 are respectively represented as a weighting factor corresponding to the set braking time length and a weighting factor corresponding to the braking distance.
7. The intelligent road rescue management platform based on big data analysis according to claim 6, characterized in that: the braking safety influence weight corresponding to each bus is set, and the specific setting process is as follows:
extracting the running speed from the current corresponding running parameters of each bus through an analysis formula
Analyzing to obtain a braking safety weight coefficient mu 1 corresponding to the running speed of each bus j ，v j The current corresponding running speed of the jth bus is shown, and v' shows the set standard running speed corresponding to the bus;
extracting passenger carrying weight from the current corresponding driving parameters of each bus, matching and comparing the passenger carrying weight corresponding to the bus with the set braking safety weight coefficient corresponding to each load, screening to obtain the braking safety weight coefficient corresponding to the passenger carrying weight of each bus, and recording as mu 2 j ；
Based on the braking safety weight coefficient corresponding to the running speed and the braking safety weight coefficient corresponding to the passenger carrying weight of each bus, the braking safety influence weight corresponding to each bus is calculated, and the calculation formula is as follows
f1 and f2 are correction factors corresponding to the set traveling speed and the set passenger load, respectively.
8. The road intelligent rescue management platform based on big data analysis as claimed in claim 1, characterized in that: the specific analysis process of the number of the buses needing rescue and the rescue types corresponding to the buses needing rescue configuration is as follows:
comparing the power safety evaluation index corresponding to each bus with a set standard power safety evaluation index, if the power safety evaluation index corresponding to a certain bus is smaller than the standard power safety evaluation index, judging that the bus needs to be rescued, and recording the rescue type corresponding to the bus as a power rescue type;
comparing the braking safety evaluation index corresponding to each bus with a set standard braking safety evaluation index, if the braking safety evaluation index corresponding to a certain bus is smaller than the standard braking safety evaluation index, judging that the bus needs to be rescued, and recording the rescue type corresponding to the bus as a braking rescue type;
if the rescue type corresponding to a certain bus comprises a dynamic rescue type and a braking rescue type, the rescue type corresponding to the bus is a comprehensive rescue type, and the number of buses needing rescue and the rescue type corresponding to each bus needing rescue are counted.
9. The intelligent road rescue management platform based on big data analysis as claimed in claim 1, wherein: the specific construction process of the rescue report comprises the following steps: and acquiring the corresponding position of each bus needing rescue, and integrating the corresponding position and rescue type of each bus needing rescue to form a rescue report corresponding to each bus needing rescue.
10. The intelligent road rescue management platform based on big data analysis as claimed in claim 1, wherein: the matching analysis is carried out on the target rescue stations corresponding to the buses needing rescue, and the specific analysis process is as follows:
extracting the corresponding positions of the rescue stations from the database, and numbering the rescue stations;
extracting the number corresponding to each bus needing rescue, calculating the position matching degree of each bus needing rescue and each rescue station based on the position corresponding to each bus needing rescue, and recording the position matching degree as B t←x T is a number corresponding to each bus needing rescue, t is 1,2, and.
Extracting the corresponding state of each rescue type vehicle in each rescue station from the database, analyzing and obtaining the type matching degree of each bus needing rescue and each rescue station based on the rescue type corresponding to each bus needing rescue, and recording the type matching degree as
Based on the position matching degree and the type matching degree of each bus needing rescue and each rescue station, the calling optimization coefficient of each bus needing rescue and each rescue station is obtained through analysis, and the analysis formula is
The calling preference coefficients corresponding to the xth rescue stations are represented as t buses needing rescue,
the ratio weights are respectively corresponding to the set position and type;
and sequencing calling preference coefficients of the buses to be rescued and the rescue stations from large to small, and taking the first-ranked rescue station as a target rescue station corresponding to each bus to be rescued.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210704913.6A CN115050186A (en) | 2022-06-21 | 2022-06-21 | Road intelligent rescue management platform based on big data analysis |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210704913.6A CN115050186A (en) | 2022-06-21 | 2022-06-21 | Road intelligent rescue management platform based on big data analysis |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN115050186A true CN115050186A (en) | 2022-09-13 |
Family
ID=83163813
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210704913.6A Pending CN115050186A (en) | 2022-06-21 | 2022-06-21 | Road intelligent rescue management platform based on big data analysis |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN115050186A (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115470638A (en) * | 2022-09-19 | 2022-12-13 | 中国人民解放军陆军装甲兵学院 | Military vehicle efficiency evaluation method |
| CN116434526A (en) * | 2022-12-09 | 2023-07-14 | 贵州鹰驾交通科技有限公司 | Intelligent expressway vehicle driving drainage monitoring management system based on data analysis |
-
2022
- 2022-06-21 CN CN202210704913.6A patent/CN115050186A/en active Pending
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115470638A (en) * | 2022-09-19 | 2022-12-13 | 中国人民解放军陆军装甲兵学院 | Military vehicle efficiency evaluation method |
| CN115470638B (en) * | 2022-09-19 | 2023-10-20 | 中国人民解放军陆军装甲兵学院 | Military vehicle efficiency evaluation method |
| CN116434526A (en) * | 2022-12-09 | 2023-07-14 | 贵州鹰驾交通科技有限公司 | Intelligent expressway vehicle driving drainage monitoring management system based on data analysis |
| CN116434526B (en) * | 2022-12-09 | 2023-11-10 | 贵州鹰驾交通科技有限公司 | Intelligent expressway vehicle driving drainage monitoring management system based on data analysis |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN115050186A (en) | Road intelligent rescue management platform based on big data analysis | |
| CN108303264B (en) | Cloud-based vehicle fault diagnosis method, device and system | |
| CN110126841B (en) | Pure electric vehicle energy consumption model prediction method based on road information and driving style | |
| CN106596135A (en) | Electric car real driving energy consumption test, evaluation and prediction method | |
| CN106546924B (en) | A kind of dynamic prediction method of automobile lithium battery performance | |
| CN103247185A (en) | Anti-rollover reminding system and method for vehicle entering turn | |
| CN106022512A (en) | Emergency rescue vehicle optimal-path-based rescue method for electric vehicles | |
| CN113781831A (en) | Smart cloud platform based on block chain technology | |
| CN111762096A (en) | New energy automobile safety early warning method and system based on artificial intelligence | |
| CN112419725B (en) | Overweight vehicle driving state risk early warning method and system based on structure monitoring | |
| CN114884054B (en) | Urban intelligent traffic emergency monitoring, regulation and control management system based on Internet of things | |
| CN114863675A (en) | Method for predicting position of key vehicle and alarming abnormity based on road police data fusion | |
| CN113642893B (en) | New energy automobile operation risk assessment method | |
| CN107918826A (en) | The driver's evaluation and dispatching method that a kind of driving environment perceives | |
| CN206056604U (en) | A kind of intelligent vehicle path planning system based on vehicle condition and road conditions | |
| CN111474565A (en) | Method for judging illegal plugging condition of road transport vehicle satellite positioning system terminal | |
| CN111695767A (en) | Highway network traffic efficiency evaluation method, electronic device and storage medium | |
| CN111381165A (en) | Vehicle power battery monitoring method, device and platform | |
| CN114550459A (en) | Method for accurately predicting bus arrival based on big data and dynamic multidimensional | |
| CN114779099A (en) | New energy automobile battery performance analysis monitoring system based on big data | |
| CN112991736B (en) | Electric public transport vehicle operation management method based on artificial intelligence and Internet of things | |
| CN116629807B (en) | Method and system suitable for using OBD interface data of new energy vehicle | |
| CN105716874A (en) | Remote brake diagnosis method | |
| CN212809451U (en) | Categorised device of prejudging of highway entry weighing equipment motorcycle type | |
| CN109901561A (en) | A kind of EMS terminal equipment failure remote diagnosis method based on various dimensions statistics |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |