CN113065804B - Hazardous chemical substance road transportation risk assessment method and system - Google Patents
Hazardous chemical substance road transportation risk assessment method and system Download PDFInfo
- Publication number
- CN113065804B CN113065804B CN202110461366.9A CN202110461366A CN113065804B CN 113065804 B CN113065804 B CN 113065804B CN 202110461366 A CN202110461366 A CN 202110461366A CN 113065804 B CN113065804 B CN 113065804B
- Authority
- CN
- China
- Prior art keywords
- accident
- road
- transportation
- loss
- dangerous chemical
- 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
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
- 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
- G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
- G06Q10/06311—Scheduling, planning or task assignment for a person or group
-
- 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
- G06Q10/00—Administration; Management
- G06Q10/08—Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
- G06Q10/083—Shipping
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/50—Context or environment of the image
- G06V20/59—Context or environment of the image inside of a vehicle, e.g. relating to seat occupancy, driver state or inner lighting conditions
- G06V20/597—Recognising the driver's state or behaviour, e.g. attention or drowsiness
Landscapes
- Business, Economics & Management (AREA)
- Engineering & Computer Science (AREA)
- Human Resources & Organizations (AREA)
- Economics (AREA)
- Strategic Management (AREA)
- Entrepreneurship & Innovation (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Development Economics (AREA)
- Marketing (AREA)
- Operations Research (AREA)
- Quality & Reliability (AREA)
- Tourism & Hospitality (AREA)
- General Business, Economics & Management (AREA)
- Educational Administration (AREA)
- Game Theory and Decision Science (AREA)
- Multimedia (AREA)
- Traffic Control Systems (AREA)
Abstract
The invention provides a method and a system for evaluating dangerous chemical road transportation risks, which are characterized in that risk factors influencing the transportation safety of dangerous chemical vehicles are identified in an all-around manner on the basis of analyzing large dangerous chemical vehicle transportation risk data, the probability of accident occurrence and the loss of potential consequences of the accident during the transportation of the dangerous chemical vehicles are taken as main lines, a qualitative and quantitative combination method is adopted to analyze the coupling relevance among multiple risk factors, estimation models of the probability of accident occurrence and the loss of potential consequences of the accident are respectively constructed, and accurate and reliable dangerous chemical vehicle transportation risk evaluation grades are obtained through the superposition effect analysis between the probability of accident occurrence and the loss of potential consequences of the accident, so that the probability of possible occurrence and the possible consequences of the dangerous chemical vehicle transportation accidents are actively reduced, and the safety and the stability of the transportation of the dangerous chemical vehicles are improved.
Description
Technical Field
The invention belongs to the technical field of intelligent traffic data analysis, and particularly relates to a method and a system for evaluating dangerous chemical road transportation risks.
Background
The statements in this section merely provide background information related to the present disclosure and may not necessarily constitute prior art.
In recent years, with the continuous development of petroleum and chemical industries, the transportation demand of hazardous chemical products is rapidly increased, and the hazardous chemical products become an indispensable part in the field of transportation. Compared with a waterway and railway transportation mode, the road transportation mode has fewer limited conditions, and belongs to the mainstream dangerous chemical transportation mode at present. Considering that the hazardous chemical transport medium has unstable chemical characteristics such as flammability, explosiveness, toxicity, corrosion and the like, once an accident occurs in the transport process, immeasurable consequences such as casualties, property damage, environmental pollution and the like can be caused. Under the background environment that modern detection technology is mature day by day and data is shared and shared in an open and deepened manner, the method and the device are urgently needed to utilize multi-source data such as human-road-environment and the like, identify dangerous chemical substance road transportation risk factors, evaluate the dangerous chemical substance road transportation risk level, accurately guide the optimization and supervision decision of dangerous chemical substance transportation lines, improve the safety of the road transportation of the dangerous chemical substances and actively prevent and control the occurrence of transportation accidents.
The identification and evaluation of the risk of dangerous chemical transportation have important decision-making value for traffic management departments. At present, various methods exist for the research on dangerous chemical transportation risk assessment, researchers provide a dangerous chemical transportation risk prediction system based on big data, the system calculates risk indexes of risk factors in a classification mode on the basis of building a data warehouse model facing dangerous chemical transportation, a risk source risk grade structure diagram is obtained by using a K-means clustering algorithm, and meanwhile, the risk factors are subjected to correlation analysis to build a dangerous chemical transportation risk multi-dimensional factor combination prediction model. Researchers provide a dangerous chemical road transportation risk early warning system and method, the system adopts a coupling metric method to calculate a real-time risk value of a transportation road section, plans an optimal transportation path for a freight vehicle by using the risk value, and designs a risk warning mechanism. Researchers provide a method and a system for evaluating the risk of the water environment of the hazardous chemical substance road transportation basin, an environment sensitive receptor influence deduction method is adopted to identify the environment risk road sections, and the environment risk evaluation and the grade division are carried out on the road sections one by one.
The scheme relates to researches on dangerous chemical transport risk assessment and prediction methods, risk alarm mechanism design and the like, most of adopted data sources are concentrated on single road transport environment data or multi-source multi-dimensional mass big data, and the later is more comprehensive in dangerous chemical transport risk factor analysis, but the proposed general data processing method cannot well meet the difference processing requirements of each risk data source.
Disclosure of Invention
The invention aims to solve the problems and provides a method and a system for evaluating the road transportation risk of hazardous chemicals.
According to some embodiments, the invention adopts the following technical scheme:
a hazardous chemical substance road transportation risk assessment method comprises the following steps:
acquiring vehicle-mounted video monitoring data, and analyzing the fatigue driving degree of a driver according to the monitoring data;
acquiring historical data of road traffic accidents, and analyzing the operation accident rate and the accident equivalent loss of a road section according to the historical data;
extracting corresponding road section and accident point information based on the historical data, and constructing an accident possible occurrence probability model of dangerous chemical vehicle transportation by combining factors influencing accident occurrence;
acquiring surrounding environment data of each road, and analyzing potential personnel loss and potential environment loss of dangerous chemical vehicle accident consequences;
comprehensively considering the accident equivalent loss, the potential personnel loss, the potential environment loss and the distribution situation of emergency guarantee resources, and constructing an accident possible consequence model of dangerous chemical vehicle transportation;
on the basis of the accident possible occurrence probability model and the accident possible consequence model of dangerous chemical substance vehicle transportation, establishing a dangerous chemical substance vehicle transportation risk evaluation model, and determining transportation risk or selecting an optimal transportation path according to the dangerous chemical substance vehicle transportation risk evaluation model.
As an alternative embodiment, the method further comprises: the method comprises the steps of establishing a full-factor database comprising driver video monitoring data, road basic condition data, traffic flow operation data, road accident data, meteorological data and road surrounding environment data in advance, and identifying risk factors influencing dangerous chemical vehicle transportation, wherein the risk factors comprise a driver fatigue index, a road accident space distribution rule, an accident average loss value, the relevance of a road section and a special structure, a traffic flow state, a meteorological state, the personnel distribution around the road, the ecological sensitive area distribution and the emergency guarantee resource condition.
As an alternative embodiment, the specific process of analyzing the fatigue driving degree of the driver according to the monitoring data comprises the following steps:
extracting human eye edges from the driver video monitoring data to obtain a minimum rectangular area containing human eyes, and calculating the human eye aspect ratio, namely the ratio of the longitudinal distance to the transverse distance of the human eye feature points;
defining the eye closing degree larger than a set percentage as an eye closing state, and setting an eye closing threshold of a driver;
calculating the closing rate of the eyes of the driver in an observation period, namely the ratio of the number of the image frames with the eyes in a closed state to the total number of the effective image frames; and learning by utilizing video monitoring data of different states of the driver, acquiring eye closure rate judgment threshold values of full, light and severe fatigue of the driver, and judging the fatigue grade of the driver.
As an alternative embodiment, the specific process of analyzing the accident rate and the accident equivalent loss of the operation of the road section according to the historical data comprises the following steps:
extracting longitude and latitude information of the position of an accident point from historical road accident data;
counting the accumulated accident frequency of each road section, and calculating the operation accident rate of the road section, namely the annual accident occurrence frequency of unit road length;
preprocessing the operation accident rate of all road sections of the road network to obtain corresponding percentage digits, identifying extreme abnormal values and modifying the extreme abnormal values;
normalizing the operation accident rate of the preprocessed road section;
and obtaining the equivalent loss value of the road accident through the death number, the casualty number and the economic loss of the road accident.
As an alternative embodiment, the specific process of constructing the probability model of the occurrence possibility of the dangerous chemical vehicle transportation accident includes:
analyzing the relevance of the road section and the special structure to obtain correction factors of different road types;
judging the traffic state type by using the floating car data, and acquiring correction factors of different traffic states;
detecting weather information every day, and acquiring correction factors of different weather states;
and calculating the possible accident occurrence probability of the transportation of the hazardous chemical substance vehicle based on the road section operation accident rate of each road section, the correction factor and the fatigue driving correction factor.
As an alternative embodiment, the specific process of analyzing the potential loss of personnel as a consequence of a hazardous chemical vehicle accident includes:
calculating the number of potential influencing personnel in the road according to the density of the personnel, the area of an influencing area, the annual average daily traffic volume, the average number of the personnel driving each vehicle, the average speed and the lane width in the corresponding road section;
calculating the number of potential influencing personnel on two sides of a road according to population density, area of an influencing area, outdoor distribution proportion, risk mitigation coefficient and the number of influencing personnel in a population dense area on two sides of a corresponding road section;
and calculating corresponding potential personnel loss value according to the number of potential influencing personnel in the road and the number of potential influencing personnel on two sides.
As an alternative embodiment, a specific process of analyzing the potential environmental loss value of the consequences of a hazardous chemical vehicle accident: and calculating the potential environmental loss value according to the unit volume value of the water source area, the volume of the polluted water source area, the unit area value of the land resource, the area of the polluted land resource and the depreciation values of the buildings on two sides of the corresponding road section.
As an alternative embodiment, the specific process of establishing a hazardous chemical substance vehicle transportation risk assessment model and determining the transportation risk or selecting the optimal transportation path according to the hazardous chemical substance vehicle transportation risk assessment model includes:
acquiring emergency guarantee resource levels and emergency guarantee correction factors according to the distribution of the quantity of emergency resources around the road, and calculating possible consequences of the accident by combining the equivalent loss value of the accident of the road section, the loss value of potential personnel and the loss value of the environment;
drawing an accumulated frequency distribution map of the probability of the road network accident to obtain statistical distribution characteristics;
drawing an accumulated frequency distribution map of possible consequences of a road network accident to obtain statistical distribution characteristics;
and constructing a road section risk synthesis judgment matrix by utilizing the probability level of the possible occurrence of the accident and the consequence level of the possible occurrence of the accident, and acquiring the dangerous chemical transport risk level of each road section.
A hazardous chemical substance road transportation risk assessment system comprises:
the fatigue driving degree analysis module is configured to acquire vehicle-mounted video monitoring data and analyze the fatigue driving degree of a driver according to the monitoring data;
the accident analysis module is configured to acquire historical data of road traffic accidents and analyze the operation accident rate and the accident equivalent loss of the road section according to the historical data;
the accident probability model building module is configured to extract corresponding road sections and accident point information based on the historical data, and build an accident possible occurrence probability model of dangerous chemical vehicle transportation by combining factors influencing accident occurrence;
the loss model building module is configured to acquire surrounding environment data of each road and analyze potential personnel loss and potential environment loss of dangerous chemical vehicle accident consequences;
the accident consequence model building module is configured to comprehensively consider the accident equivalent loss, the potential personnel loss, the environmental loss and the distribution situation of emergency guarantee resources, and build an accident possible consequence model of dangerous chemical vehicle transportation;
the risk assessment module is configured to establish a dangerous chemical substance vehicle transportation risk assessment model on the basis of the accident possible occurrence probability model and the accident possible consequence model of dangerous chemical substance vehicle transportation, and determine transportation risks or select an optimal transportation path according to the dangerous chemical substance vehicle transportation risk assessment model.
An electronic device comprises a memory, a processor and computer instructions stored in the memory and executed on the processor, wherein the computer instructions are executed by the processor to complete the steps of the method for assessing risk of hazardous chemical substances in road transportation.
A computer readable storage medium for storing computer instructions, which when executed by a processor, perform the steps of the above method for assessing risk of road transportation of hazardous chemical substances.
Compared with the prior art, the invention has the beneficial effects that:
according to the method, on the basis of analyzing the human-road-environment integrated hazardous chemical substance vehicle transportation risk big data, risk elements influencing the hazardous chemical substance vehicle transportation safety are identified in an all-around manner, the probability of occurrence of an accident and the potential consequence loss of the accident in hazardous chemical substance vehicle transportation are taken as main lines, a qualitative and quantitative combination method is adopted, the coupling relevance among multiple risk elements is analyzed, estimation models of the probability of occurrence of the accident and the potential consequence loss of the accident are respectively constructed, and the accurate and reliable hazardous chemical substance vehicle transportation risk evaluation grade is obtained through the superposition effect analysis between the probability of occurrence of the accident and the potential consequence loss of the accident.
According to the road network hazardous chemical transportation risk assessment result obtained by the method, on one hand, real-time key control objects can be provided for traffic management departments, and road section rectification schemes under interference of different risk factors are designed in a targeted manner; on the other hand, the driver can be accurately reminded of avoiding the road section with a higher risk level, and real-time effective basis is provided for the optimization of the transportation route of the hazardous chemical substance vehicle responding to the dynamic demand, so that the possible occurrence probability and possible occurrence consequences of the hazardous chemical substance vehicle transportation accident are actively reduced, and the safety and stability of the hazardous chemical substance vehicle transportation are improved.
In order to make the aforementioned and other objects, features and advantages of the present invention comprehensible, preferred embodiments accompanied with figures are described in detail below.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, are included to provide a further understanding of the invention, and are included to illustrate an exemplary embodiment of the invention and not to limit the invention.
Fig. 1 is a schematic flow chart of an implementation of the hazardous chemical substance road transportation risk assessment method based on full-factor data provided by the invention.
FIG. 2 is a flow chart of a risk assessment model for hazardous chemical vehicle transportation provided by the present invention.
The specific implementation mode is as follows:
the invention is further described with reference to the following figures and examples.
It is to be understood that the following detailed description is exemplary and is intended to provide further explanation of the invention as claimed. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of exemplary embodiments according to the invention. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, and it should be understood that when the terms "comprises" and/or "comprising" are used in this specification, they specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof, unless the context clearly indicates otherwise.
As shown in fig. 1, an embodiment 1 of the present invention provides a hazardous chemical substance road transportation risk assessment method based on full-element data, including the following steps:
s1: constructing a human-road-environment full-element risk database, and identifying risk elements influencing the transportation safety of dangerous chemical vehicles;
s2: analyzing the fatigue driving degree of the driver based on the vehicle-mounted video monitoring data;
s3: analyzing the operation accident rate and the accident equivalent loss of the road section based on the road traffic accident data;
s4: constructing a probability model of possible accidents of dangerous chemical vehicle transportation;
s5: potential personnel loss and potential environment loss of dangerous chemical vehicle accident consequences are analyzed based on the road surrounding environment data;
s6: constructing a possible consequence model of the dangerous chemical vehicle transportation accident;
s7: and establishing a dangerous chemical vehicle transportation risk assessment model.
In S1 of this embodiment, a full-factor database including driver video monitoring data, road basic condition data, traffic flow operation data, road accident data, meteorological data, and road surrounding environment data is established, and risk factors affecting transportation of dangerous chemical vehicles are identified by using an expert scoring method, including driver fatigue index, road accident spatial distribution rule, accident average loss value, relevance between road sections and special structures, traffic flow state, meteorological state, personnel distribution around roads, ecological sensitive area distribution, and emergency guarantee resource condition.
In S2 of this embodiment, the state of the eyes of the driver is determined in real time by using the driver video monitoring data of the dangerous chemical vehicle, and the fatigue driving correction factor of the driver is obtained by calculation.
In this embodiment, the following contents are specifically included:
in S21, the edges of the human eyes are extracted from the driver video monitoring data to obtain a minimum rectangular region including the human eyes, and the aspect ratio EAR of the human eyes, that is, the ratio of the longitudinal distance to the transverse distance of the characteristic points of the human eyes, is calculated:
in the formula, EAR l And EAR r Respectively representing a left-eye aspect ratio and a right-eye aspect ratio; b 1 ,b 2 ,b 3 ,b 4 ,b 5 ,b 6 Indicating 6 human eye edge landmark positions numbered clockwise from the eye lateral canthus landmark position.
In S22, the eye-closing state is defined as an eye-closing state in which the degree of eye closure is greater than 80%, and the eye-closing threshold EAR' of the driver is estimated by definition, and is calculated by using the following formula:
EAR′＝EAR min +0.2×(EAR max -EAR min )
in the formula, EAR max And EAR min Respectively the maximum and minimum of the aspect ratio of the human eye of each driver.
In S23, calculating the closing rate of the eyes of the driver in an observation period, namely the ratio of the number of image frames with the eyes in a closed state to the total number of effective image frames; the video monitoring data of the driver in different states are utilized for learning, eye closure rate judgment threshold values of full, light and severe fatigue of the driver are obtained, and judgment of the fatigue level of the driver is achieved.
In S24, a fatigue driving correction factor f is obtained according to the judgment result of the fatigue level of the driver driv I.e. the driver is at a mental fullness of 1.0, mild fatigue of 1.4 and severe fatigue of 2.0.
In the embodiment of S3, the gis space analysis technique is adopted to extract longitude and latitude information of the accident point from the historical accident data of the road, calculate the accident rate of the road operation by using the cumulative accident frequency of the road section, and comprehensively consider the number of deaths, casualties and economic loss of the accident itself to obtain the equivalent loss of the accident of the road section.
In this embodiment, the following contents are specifically included:
in S31, longitude and latitude information of the accident point position is extracted from the historical road accident data;
in S32, the accumulated number of accidents of each road segment is counted, and the operation accident rate of the road segment, that is, the annual accident occurrence number of the unit road length, is calculated as follows:
in the formula, p j The operation accident rate of the road section j; n is j,acc The accumulated accident frequency of the road section j is obtained; l j Is the length of the segment j.
In S33, the operation accident rate of all road sections of the road network is preprocessed to obtain a 15% digit p 15％ 25% digit p 25％ And 75% bit number p 75％ (ii) a P is to be j Case of =0 is modified to (0,p) 15％ ]Random number of (2), using p j >p 75％ +3(p 75％ -p 25％ ) Identifying an extreme outlier and modifying the extreme outlier to 1.0;
in S34, the operation accident rate of the preprocessed road section is normalized, and the operation accident rate is calculated as follows:
when p is j ＝p min Is normalized to p' j Is measured.
In the formula, p max And p min To the roadAnd the maximum value and the minimum value of the operation accident rate of all the sections of the network.
In S35, the equivalent loss value of the road accident is obtained through the death number, the casualties and the economic loss of the road accident
The calculation is as follows:
in the formula (I), the compound is shown in the specification,
(ii) a dead person, human; />
Is casualty, human; />
The economic loss value is ten thousand yuan; z is the traffic accident death compensation standard, namely all urban residents can control income to multiply 20 years by ten thousand yuan.
In S4 of this embodiment, probability elements that may occur to the accident that affects the transportation of the hazardous chemical substance vehicle are selected, including the fatigue degree of the driver, the traffic state, the weather state, and the relevance to the special structure, and the four impact factor correction factors are assigned by using an expert scoring method, so as to construct a dynamic model of the probability that the accident may occur to the transportation of the hazardous chemical substance vehicle.
In this embodiment, the following contents are specifically included:
in S41, the relevance between the road section and the special structure is analyzed to obtain the road type correction factor
Namely, the road section associated with the special structure is 1.2, and the common road section is 1.0; the special structures comprise bridges, tunnels, railway crossings and viaducts;
in S42, the floating car data is used for judging the traffic state type and obtaining the traffic state correction factor
Namely smooth traffic is 0.8, slow traffic is 1.0, congestion is 1.4 and severe congestion is 2.0;
in S43, detecting weather information every day and obtaining weather state correction factor
I.e. weather good 1.0, rain/fog 1.3 and snow/hail 1.2;
in S44, the possible accident occurrence probability of the dangerous chemical substance vehicle transportation is calculated, namely
In the step S5, potential personnel loss of dangerous chemical vehicle accident consequences is calculated according to the population distribution conditions inside and on two sides of the road; and calculating the potential environmental loss of the dangerous chemical vehicle accident consequence according to the distribution conditions of water source areas, farmlands and buildings on two sides of the road.
In the present embodiment, the following are included:
in S51, the number of potentially influencing people inside the road is calculated
Namely: />
In the formula (I), the compound is shown in the specification,
the density of drivers and passengers in the road section j is person/km 2; />
Inside the section jArea of affected area, km2; AADT j The average daily traffic volume per year of the road section j, vehicle/day; />
The average number of drivers and passengers per vehicle, person/vehicle;
the average speed of the vehicle is km/h; d j,lane Is the lane width, km, for road segment j.
In S52, the number of potentially influencing people on two sides of the road is calculated
Namely:
in the formula (I), the compound is shown in the specification,
the population density of the two sides of the road section j is people/km 2; />
The area of the affected area on the two sides of the road section j is km2; />
The outdoor distribution proportion of the influencing personnel on the two sides of the road section j is shown; f. of del Risk mitigation coefficients for persons in the influence areas on two sides of the road section j; />
The number of people in the densely populated areas on the two sides of the road section j, such as hospitals and schools, is the number of the people.
In S53, potential personnel loss value of the road section j is calculated
Namely that
In S54, the environmental loss value of the link j, that is, the environmental loss value
In the formula (I), the compound is shown in the specification,
the unit volume value of a water source area is ten thousand yuan/km 3; />
Km3, volume of contaminated water source; />
The unit area value of land resources is ten thousand yuan/km 2; />
Km2 for the contaminated land resource area;
the method is a ten thousand yuan old-fashioned method for buildings on two sides of a road section j.
In S6 of this embodiment, a model of possible consequences of an accident in transportation of hazardous chemical substance vehicles is constructed by comprehensively considering the equivalent loss of the accident at the road section, the potential personnel loss of the accident consequences, the environmental loss, and the distribution of emergency security resources.
In this embodiment, the following contents are specifically included:
s61, according to the distribution of the quantity of emergency resources around the road, acquiring the grade of the emergency guarantee resource and the emergency guarantee correction factor
Namely, the preparation is reasonably 0.75, and the preparation is generally 09, no equipment 1.0;
s62, calculating possible consequences C of dangerous chemical vehicle transportation accidents j I.e. by
In this embodiment, as shown in fig. 2, on the basis of the probability of occurrence of an accident and the possible consequences of the accident in the transportation of the hazardous chemical substance vehicles, a risk synthesis determination matrix is established, a hazardous chemical substance vehicle transportation risk assessment model is established, the transportation risk comprehensive assessment classification of the hazardous chemical substance vehicles is performed, and the risk is determined or the transportation road is selected according to the classification result.
The method specifically comprises the following steps:
s71, calculating the possible occurrence probability and possible consequences of dangerous chemical vehicle transportation accidents of all road sections of the road network;
s72, drawing an accumulated frequency distribution map of the probability of the road network accidents, and obtaining statistical distribution characteristics, namely 15% digit, 50% digit, 85% digit and 100% digit of the probability of the accidents; when P is present j The probability distribution grade of the road section j is less than or equal to 15 percent of the bit number
When P is present j Greater than 15% of the number of bits and less than or equal to 50% of the number of bits
When P is present j Greater than 50% of the number of bits and less than or equal to 85% of the number of bits, then->
When P is j Greater than 85% of the number of bits and less than or equal to 100% of the number of bits, then%>
S73, drawing an accumulated frequency distribution map of possible consequences of road network accidents to obtain statistical distribution characteristicsNamely, the 15% digit, the 50% digit, the 85% digit and the 100% digit of possible consequences of an accident; when C is present j Less than or equal to 15% of the number of bits, the consequence grade of the road section j is
When C is j More than 15% of the bits and less than or equal to 50% of the bits, then
When C is j Greater than 50% of the number of bits and less than or equal to 85% of the number of bits, then->
When C is present j Greater than 85% of the number of bits and less than or equal to 100% of the number of bits, then->
S74, constructing a road section risk synthesis judgment matrix by utilizing the probability level and the consequence level of the accident, and acquiring the dangerous chemical transportation risk level of each road section, namely when
In time, the risk grade of the road section j is A, and dangerous chemical vehicles are allowed to pass; when/is>
Then, if the dangerous chemical transport risk level of the road section j is B, a restriction rule needs to be set; when the temperature is higher than the set temperature
When the dangerous chemical transportation risk grade of the road section j is C, a restriction rule needs to be established and the vehicle can pass conditionally; when/is>
And meanwhile, the transportation risk grade of the road section j is D, and dangerous chemical vehicle passing is forbidden.
The present embodiment also provides the following product embodiments:
a hazardous chemical substance road transportation risk assessment system comprises:
the fatigue driving degree analysis module is configured to acquire vehicle-mounted video monitoring data and analyze the fatigue driving degree of a driver according to the monitoring data;
the accident analysis module is configured to acquire historical data of road traffic accidents and analyze the operation accident rate and the accident equivalent loss of the road section according to the historical data;
the accident probability model building module is configured to extract corresponding road sections and accident point information based on the historical data, and build an accident possible occurrence probability model of transportation of the hazardous chemical substance vehicles by combining factors influencing accident occurrence;
the loss model building module is configured to acquire surrounding environment data of each road and analyze potential personnel loss and potential environment loss of dangerous chemical vehicle accident consequences;
the accident consequence model building module is configured to comprehensively consider the accident equivalent loss, the potential personnel loss, the environmental loss and the distribution situation of emergency guarantee resources, and build an accident possible consequence model of dangerous chemical vehicle transportation;
the risk assessment module is configured to establish a dangerous chemical vehicle transportation risk assessment model on the basis of an accident possible occurrence probability model and an accident possible consequence model of dangerous chemical vehicle transportation, and determine transportation risks or select an optimal transportation path according to the dangerous chemical vehicle transportation risk assessment model.
An electronic device comprises a memory, a processor and computer instructions stored in the memory and executed on the processor, wherein the computer instructions are executed by the processor to complete the steps of the method for assessing risk of hazardous chemical substances in road transportation.
A computer readable storage medium for storing computer instructions, which when executed by a processor, perform the steps of the above method for assessing risk of road transportation of hazardous chemical substances.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Although the embodiments of the present invention have been described with reference to the accompanying drawings, it is not intended to limit the scope of the present invention, and it should be understood by those skilled in the art that various modifications and variations can be made without inventive efforts by those skilled in the art based on the technical solution of the present invention.
Claims (8)
1. A hazardous chemical substance road transportation risk assessment method is characterized by comprising the following steps: the method comprises the following steps:
acquiring vehicle-mounted video monitoring data, and analyzing the fatigue driving degree of a driver according to the monitoring data;
acquiring historical data of road traffic accidents, and analyzing the operation accident rate and the accident equivalent loss of a road section according to the historical data;
obtaining the equivalent loss value of the road accident through the death number, casualty number and economic loss of the road accident
The calculation is as follows:
in the formula (I), the compound is shown in the specification,
the number of the dead people is the number of the dead people,
in order to ensure that the patient is injured and killed,
the value is lost for economy; z is the traffic accident death compensation standard;
extracting corresponding road section and accident point information based on the historical data, and constructing an accident possible occurrence probability model of dangerous chemical vehicle transportation by combining factors influencing accident occurrence;
the method comprises the following steps of obtaining surrounding environment data of each road, and analyzing potential personnel loss and potential environment loss of dangerous chemical vehicle accident consequences, wherein the method specifically comprises the following steps: calculating potential personnel loss of dangerous chemical vehicle accident consequences from the population distribution conditions inside and on two sides of the road; calculating the potential environmental loss of dangerous chemical vehicle accident consequences from the distribution conditions of water source areas, farmlands and buildings on two sides of a road;
calculating the number of potentially influencing persons inside a road
Namely:
in the formula (I), the compound is shown in the specification,
for the density of occupants within road segment j,
area of influence within road section j, AADT j Is the annual average daily traffic volume for road segment j,
for the average number of occupants per vehicle,
is the average speed of the vehicle, d j,lane Is the lane width of road segment j;
calculating the number of potentially influencing persons on both sides of a road
Namely:
in the formula (I), the compound is shown in the specification,
the population density on both sides of the road segment j,
area of influence region on both sides of the road section j
The outdoor distribution proportion f of the influencing personnel on both sides of the road section j del For the risk mitigation factors affecting the personnel in the zone on both sides of the road section j,
the number of the influencing people in the densely populated areas on the two sides of the road section j;
calculating potential personnel loss value of road section j
Namely:
calculating the environmental loss value of the section j, namely:
in the formula (I), the compound is shown in the specification,
is the value per unit volume of the water source,
is the volume of the contaminated water source,
is the unit area value of land resources,
in order to provide a contaminated land resource area,
depreciation value of buildings on two sides of the road section j;
comprehensively considering the accident equivalent loss, the potential personnel loss, the environmental loss and the distribution situation of emergency guarantee resources, and constructing an accident possible consequence model of dangerous chemical vehicle transportation, wherein the possible consequence model is as follows:
establishing a dangerous chemical substance vehicle transportation risk evaluation model on the basis of an accident possible occurrence probability model and an accident possible consequence model of dangerous chemical substance vehicle transportation, and determining transportation risk or selecting an optimal transportation path according to the dangerous chemical substance vehicle transportation risk evaluation model;
the specific process for constructing the probability model of the possible occurrence of the dangerous chemical vehicle transportation accident comprises the following steps:
analyzing the relevance between the road section and the special structure to obtain the correction factors of different road types
Determining traffic state categories by using floating car data and obtaining correction factors of different traffic states
Detecting weather information every day to obtain correction factors of different weather states
Calculating the probability of possible accidents of dangerous chemical vehicle transportation based on the road section operation accident rate of each road section, the correction factor and the fatigue driving correction factor, namely:
establishing a dangerous chemical substance vehicle transportation risk evaluation model, wherein the specific process of determining the transportation risk or selecting the optimal transportation path according to the dangerous chemical substance vehicle transportation risk evaluation model comprises the following steps:
acquiring emergency guarantee resource levels and emergency guarantee correction factors according to the distribution of the quantity of emergency resources around the road, and calculating possible consequences of the accident according to the equivalent loss value of the accident of the road section, the loss value of potential personnel and the loss value of the environment;
drawing an accumulated frequency distribution map of the probability of the road network accident to obtain statistical distribution characteristics;
drawing an accumulated frequency distribution map of possible consequences of a road network accident to obtain statistical distribution characteristics;
and constructing a road section risk synthesis judgment matrix by utilizing the probability level of the possible occurrence of the accident and the consequence level of the possible occurrence of the accident, and acquiring the dangerous chemical transport risk level of each road section.
2. The method for assessing the risk of the hazardous chemical substance in road transportation according to claim 1, wherein the method comprises the following steps: further comprising: the method comprises the steps of establishing a full-factor database comprising driver video monitoring data, road basic condition data, traffic flow operation data, road accident data, meteorological data and road surrounding environment data in advance, and identifying risk factors influencing dangerous chemical vehicle transportation, wherein the risk factors comprise a driver fatigue index, a road accident space distribution rule, an accident average loss value, the relevance of a road section and a special structure, a traffic flow state, a meteorological state, the personnel distribution around the road, the ecological sensitive area distribution and the emergency guarantee resource condition.
3. The method for assessing the risk of the hazardous chemical substance in road transportation according to claim 1, wherein the method comprises the following steps: the specific process for analyzing the fatigue driving degree of the driver according to the monitoring data comprises the following steps:
extracting human eye edges from the driver video monitoring data to obtain a minimum rectangular area containing human eyes, and calculating the human eye aspect ratio, namely the ratio of the longitudinal distance to the transverse distance of the human eye feature points;
defining the eye closing degree larger than a set percentage as an eye closing state, and setting an eye closing threshold of a driver;
calculating the closing rate of the eyes of the driver in an observation period, namely the ratio of the number of the image frames with the eyes in a closed state to the total number of the effective image frames;
the video monitoring data of the driver in different states are utilized for learning, eye closure rate judgment threshold values of full, light and severe tiredness of the driver are obtained, and the fatigue grade of the driver is judged.
4. The method for assessing the risk of the hazardous chemical substance in road transportation according to claim 1, wherein the method comprises the following steps: the specific process for analyzing the road section operation accident rate and the accident equivalent loss according to the historical data comprises the following steps:
extracting longitude and latitude information of the position of an accident point from historical accident data of a road;
counting the accumulated accident frequency of each road section, and calculating the operation accident rate of the road section, namely the annual accident occurrence frequency of unit road length;
preprocessing the operation accident rate of all road sections of the road network to obtain corresponding percentage digits, identifying extreme abnormal values and modifying the extreme abnormal values;
normalizing the operation accident rate of the preprocessed road section;
and obtaining the equivalent loss value of the road accident through the death number, the casualty number and the economic loss of the road accident.
5. The method for assessing the risk of the hazardous chemical substance in road transportation according to claim 1, wherein the method comprises the following steps: the specific process for analyzing the potential personnel loss of the dangerous chemical vehicle accident consequence comprises the following steps:
calculating the number of potential influencing personnel in the road according to the density of the personnel, the area of an influencing area, the annual average daily traffic volume, the average number of the personnel driving each vehicle, the average speed and the lane width in the corresponding road section;
calculating the number of potential influencing personnel on two sides of a road according to the population density, the area of an influencing area, the outdoor distribution proportion, the risk mitigation coefficient and the number of influencing personnel in a population dense area on two sides of a corresponding road section;
calculating corresponding potential personnel loss values according to the number of potential influencing personnel in the road and the number of potential influencing personnel on two sides;
or, the specific process of analyzing the potential environmental loss value of the dangerous chemical vehicle accident consequence: and calculating the potential environmental loss value according to the unit volume value of the water source area, the volume of the polluted water source area, the unit area value of the land resource, the area of the polluted land resource and the depreciation values of the buildings on two sides of the corresponding road section.
6. The utility model provides a danger chemical substance road transport risk assessment system which characterized by: the method comprises the following steps:
the fatigue driving degree analysis module is configured to acquire vehicle-mounted video monitoring data and analyze the fatigue driving degree of a driver according to the monitoring data;
the accident analysis module is configured to acquire historical data of road traffic accidents and analyze the operation accident rate and the accident equivalent loss of the road section according to the historical data;
obtaining the equivalent loss value of the road accident through the death number, casualty number and economic loss of the road accident
The calculation is as follows:
in the formula (I), the compound is shown in the specification,
the number of the dead people is the number of the dead people,
in order to ensure that the patient is injured and killed,
the value is lost for economy; z is the traffic accident death compensation standard;
the accident probability model building module is configured to extract corresponding road sections and accident point information based on the historical data, and build an accident possible occurrence probability model of dangerous chemical vehicle transportation by combining factors influencing accident occurrence;
the loss model building module is configured to acquire surrounding environment data of each road and analyze potential personnel loss and potential environment loss of dangerous chemical vehicle accident consequences, and specifically comprises the following steps: calculating the potential personnel loss of dangerous chemical vehicle accident consequences from the population distribution conditions inside and on two sides of the road; calculating the potential environmental loss of dangerous chemical vehicle accident consequences from the distribution conditions of water source areas, farmlands and buildings on two sides of a road;
calculating the number of potentially influencing persons inside a road
Namely:
in the formula (I), the compound is shown in the specification,
for the density of occupants within road segment j,
area of influence within road section j, AADT j Is the annual average daily traffic volume for road segment j,
for the average number of occupants per vehicle,
is the average speed of the vehicle, d j,lane Is the lane width of road segment j;
calculating the number of potentially influencing persons on both sides of a road
Namely:
in the formula (I), the compound is shown in the specification,
the population density on both sides of the road segment j,
area of influence region on both sides of the road section j
For the proportion of outdoor distribution, f, of influencing personnel on both sides of the section j del For the risk mitigation factors of the persons in the affected area on both sides of the road section j,
the number of the influencing people in the densely populated areas on the two sides of the road section j;
calculating potential personnel loss value of road section j
Namely:
calculating the environmental loss value of the section j, namely:
in the formula (I), the compound is shown in the specification,
is the value per unit volume of the water source,
is the volume of the source of the contaminated water,
is the unit area value of land resources,
in order to provide a contaminated land resource area,
depreciation value of buildings on two sides of the road section j;
the accident consequence model building module is configured to comprehensively consider the accident equivalent loss, the potential personnel loss, the environmental loss and the distribution situation of emergency guarantee resources, and build an accident possible consequence model of dangerous chemical vehicle transportation, wherein the consequence model is as follows:
the risk assessment module is configured to establish a dangerous chemical vehicle transportation risk assessment model on the basis of an accident possible occurrence probability model and an accident possible consequence model of dangerous chemical vehicle transportation, and determine transportation risks or select an optimal transportation path according to the dangerous chemical vehicle transportation risk assessment model;
the specific process for constructing the probability model of the possible occurrence of the dangerous chemical vehicle transportation accident comprises the following steps:
analyzing the relevance between the road section and the special structure to obtain the correction factors of different road types
Determining traffic state category by using floating car data to obtain correction factors of different traffic states
Detecting weather information every day to obtain correction factors of different weather states
Calculating the probability of possible accidents of transportation of dangerous chemical vehicles based on the road section operation accident rate of each road section, the correction factors and the fatigue driving correction factors, namely:
establishing a dangerous chemical substance vehicle transportation risk evaluation model, wherein the specific process of determining the transportation risk or selecting the optimal transportation path according to the dangerous chemical substance vehicle transportation risk evaluation model comprises the following steps:
acquiring emergency guarantee resource levels and emergency guarantee correction factors according to the distribution of the quantity of emergency resources around the road, and calculating possible consequences of the accident according to the equivalent loss value of the accident of the road section, the loss value of potential personnel and the loss value of the environment;
drawing an accumulated frequency distribution map of the probability of the road network accident to obtain statistical distribution characteristics;
drawing an accumulated frequency distribution map of possible consequences of a road network accident to obtain statistical distribution characteristics;
and constructing a road section risk synthesis judgment matrix by utilizing the probability level of the possible occurrence of the accident and the consequence level of the possible occurrence of the accident, and acquiring the dangerous chemical transport risk level of each road section.
7. An electronic device, characterized by: the system comprises a memory, a processor and computer instructions stored in the memory and executed on the processor, wherein the computer instructions, when executed by the processor, perform the steps of the hazardous chemical substance road transportation risk assessment method according to any one of claims 1 to 5.
8. A computer-readable storage medium, comprising: storing computer instructions which, when executed by a processor, perform the steps of the method for assessing risk of road transportation of hazardous chemical substances according to any one of claims 1-5.
Priority Applications (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110461366.9A CN113065804B (en) | 2021-04-27 | 2021-04-27 | Hazardous chemical substance road transportation risk assessment method and system |
| PCT/CN2021/094156 WO2022227129A1 (en) | 2021-04-27 | 2021-05-17 | Road transportation risk assessment method and system for hazardous chemical |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110461366.9A CN113065804B (en) | 2021-04-27 | 2021-04-27 | Hazardous chemical substance road transportation risk assessment method and system |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN113065804A CN113065804A (en) | 2021-07-02 |
| CN113065804B true CN113065804B (en) | 2023-03-24 |
Family
ID=76567813
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110461366.9A Active CN113065804B (en) | 2021-04-27 | 2021-04-27 | Hazardous chemical substance road transportation risk assessment method and system |
Country Status (2)
| Country | Link |
|---|---|
| CN (1) | CN113065804B (en) |
| WO (1) | WO2022227129A1 (en) |
Families Citing this family (38)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| TWI789876B (en) * | 2021-08-19 | 2023-01-11 | 奇點無限有限公司 | Generation method for a least risk route |
| CN113780783A (en) * | 2021-09-01 | 2021-12-10 | 苏交科集团股份有限公司 | Automatic analysis method for risk degree of road traffic safety accident |
| CN113516323B (en) * | 2021-09-15 | 2021-11-30 | 山东蓝湾新材料有限公司 | Transportation path recommendation method |
| CN114168646A (en) * | 2021-10-29 | 2022-03-11 | 山东大学 | Multi-data fusion-based commercial vehicle transportation monitoring method and system |
| CN115083167A (en) * | 2022-08-22 | 2022-09-20 | 深圳市城市公共安全技术研究院有限公司 | Early warning method, system, terminal device and medium for vehicle leakage accident |
| CN115331449B (en) * | 2022-10-17 | 2023-02-07 | 四川省公路规划勘察设计研究院有限公司 | Method and device for identifying accident-prone area of long and large continuous longitudinal slope section and electronic equipment |
| CN115630848B (en) * | 2022-12-20 | 2023-03-10 | 航天神舟智慧系统技术有限公司 | Regional security state dynamic evaluation management and control method and system |
| CN115796605A (en) * | 2023-01-29 | 2023-03-14 | 北京迈道科技有限公司 | Risk level assessment method and device for major hazard source and electronic equipment |
| CN116484056B (en) * | 2023-02-20 | 2023-11-07 | 北京交通大学 | Rail transit accident prevention method based on knowledge graph |
| CN116311933B (en) * | 2023-03-13 | 2023-10-31 | 北京市生态环境保护科学研究院 | Method and system for managing traffic crossing risk of drinking water source |
| CN115994362B (en) * | 2023-03-23 | 2023-06-09 | 卡斯柯信号(北京)有限公司 | Safety analysis method and device for full-automatic operation system |
| CN116485038B (en) * | 2023-06-08 | 2023-11-24 | 南京工业大学 | Dynamic prediction method for secondary domino accident of fire disaster in pressure storage tank area |
| CN116739345B (en) * | 2023-06-08 | 2024-03-22 | 南京工业大学 | Real-time evaluation method for possibility of dangerous chemical road transportation accident |
| CN116520856B (en) * | 2023-07-04 | 2023-09-22 | 交通运输部水运科学研究所 | Wharf transport vehicle quantitative safety avoiding system based on IGV intelligent navigation |
| CN116579619B (en) * | 2023-07-13 | 2023-09-22 | 万联易达物流科技有限公司 | Air control method and system for freight bill |
| CN116664079B (en) * | 2023-07-24 | 2024-05-17 | 中天昊建设管理集团股份有限公司 | Building design dynamic flow supervision system and method based on Internet |
| CN117010776B (en) * | 2023-08-14 | 2024-06-25 | 铁正检测科技有限公司 | Railway construction raw material transportation management system based on data analysis |
| CN116777085B (en) * | 2023-08-23 | 2023-11-10 | 北京联创高科信息技术有限公司 | Coal mine water damage prediction system based on data analysis and machine learning technology |
| CN117278940B (en) * | 2023-08-29 | 2024-04-05 | 广东车卫士信息科技有限公司 | Car machine interconnection system based on hicar |
| CN117634869A (en) * | 2023-09-04 | 2024-03-01 | 大唐保定热电厂 | Safe operation early warning method and system for thermal power plant |
| CN117169121B (en) * | 2023-09-05 | 2024-01-30 | 南京交科数智科技发展有限公司 | Traffic road disease detection system and method based on cloud edge end architecture |
| CN116957443B (en) * | 2023-09-18 | 2023-12-08 | 深圳市升蓝物流有限公司 | Logistics transportation state real-time supervision system based on internet of things technology |
| CN117334066A (en) * | 2023-09-20 | 2024-01-02 | 广州亿胜鑫网络科技有限公司 | Risk analysis method, system, terminal and storage medium based on vehicle data |
| CN117314287A (en) * | 2023-10-07 | 2023-12-29 | 张家港凝卓科技有限公司 | Refrigerated medicine low temperature transportation monitoring and early warning system |
| CN117078020B (en) * | 2023-10-12 | 2024-01-30 | 山东龙翼航空科技有限公司 | Logistics transportation data management system based on unmanned aerial vehicle |
| CN117058888B (en) * | 2023-10-13 | 2023-12-22 | 华信纵横科技有限公司 | Traffic big data processing method and system thereof |
| CN117474318A (en) * | 2023-10-18 | 2024-01-30 | 国网湖北省电力有限公司直流公司 | Current transformer station valve hall operation supervisory systems based on portable infrared temperature measurement technique |
| CN117217968B (en) * | 2023-11-07 | 2024-01-23 | 安元科技股份有限公司 | Dangerous chemical enterprise safety risk management and control platform based on UE4 twin technology |
| CN117474337B (en) * | 2023-11-08 | 2024-06-18 | 上海海勃物流软件有限公司 | Port hazard source detection method and system based on big data |
| CN117273245B (en) * | 2023-11-23 | 2024-02-02 | 深圳市中农网有限公司 | Intelligent optimization method and system for logistics transportation cost management |
| CN117575872B (en) * | 2023-11-23 | 2024-05-31 | 周波 | Dangerous chemical management method and system |
| CN117454274B (en) * | 2023-12-21 | 2024-03-08 | 交通运输部天津水运工程科学研究所 | Method and system for evaluating ecological resistance value of living area of wild animal |
| CN117592891B (en) * | 2024-01-19 | 2024-03-22 | 河北科技大学 | Logistics management system for dangerous chemicals |
| CN117706413B (en) * | 2024-02-02 | 2024-04-19 | 青岛元通电子有限公司 | Standard power module operation self-checking system based on data analysis |
| CN117962747A (en) * | 2024-03-29 | 2024-05-03 | 长城汽车股份有限公司 | Early warning method and device, vehicle-mounted terminal and vehicle |
| CN117973977B (en) * | 2024-04-01 | 2024-06-07 | 南京工业大学 | Explosion risk assessment method and system in operation of dangerous chemical transport vehicle |
| CN118072260A (en) * | 2024-04-18 | 2024-05-24 | 山东双百电子有限公司 | Vehicle offset analysis method and system based on image |
| CN118197061A (en) * | 2024-05-15 | 2024-06-14 | 江苏中天交通工程有限公司 | Road guidance system and method based on data analysis technology |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110232519A (en) * | 2019-06-11 | 2019-09-13 | 大连海事大学 | A kind of inland river Transportation of Dangerous Chemicals risk evaluating system |
| CN110765980A (en) * | 2019-11-05 | 2020-02-07 | 中国人民解放军国防科技大学 | Abnormal driving detection method and device |
Family Cites Families (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20140074402A1 (en) * | 2012-09-12 | 2014-03-13 | Lexisnexis Risk Solutions Fl Inc. | Systems and methods for determining risks associated with driving routes |
| CN109165630A (en) * | 2018-09-19 | 2019-01-08 | 南京邮电大学 | A kind of fatigue monitoring method based on two-dimentional eye recognition |
| CN109886568B (en) * | 2019-02-01 | 2021-01-05 | 生态环境部华南环境科学研究所 | Risk chemical road transportation basin water environment risk assessment method and system |
| CN110033614A (en) * | 2019-03-22 | 2019-07-19 | 山西省交通科学研究院有限公司 | A kind of road hazard cargo transport dynamic risk early warning system based on technology of Internet of things |
| CN110033615B (en) * | 2019-03-22 | 2020-09-01 | 山西省交通科学研究院有限公司 | Road dangerous cargo transportation dynamic risk assessment method based on Internet of things |
| CN112562337B (en) * | 2020-12-10 | 2022-05-13 | 之江实验室 | Expressway real-time traffic accident risk assessment method based on deep learning |
-
2021
- 2021-04-27 CN CN202110461366.9A patent/CN113065804B/en active Active
- 2021-05-17 WO PCT/CN2021/094156 patent/WO2022227129A1/en unknown
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110232519A (en) * | 2019-06-11 | 2019-09-13 | 大连海事大学 | A kind of inland river Transportation of Dangerous Chemicals risk evaluating system |
| CN110765980A (en) * | 2019-11-05 | 2020-02-07 | 中国人民解放军国防科技大学 | Abnormal driving detection method and device |
Also Published As
| Publication number | Publication date |
|---|---|
| CN113065804A (en) | 2021-07-02 |
| WO2022227129A1 (en) | 2022-11-03 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN113065804B (en) | Hazardous chemical substance road transportation risk assessment method and system | |
| Lord et al. | Highway safety analytics and modeling | |
| Mussone et al. | Analysis of factors affecting the severity of crashes in urban road intersections | |
| Wang et al. | Expressway crash risk prediction using back propagation neural network: A brief investigation on safety resilience | |
| CN110288200A (en) | A kind of harmful influence transportation safety risk prevention system system and method | |
| CN105719510B (en) | Road traffic accident chain blocks the efficiency rating method of system under car networking environment | |
| CN113033840A (en) | Method and device for judging highway maintenance | |
| Shamsashtiany et al. | Road accidents prediction with multilayer perceptron MLP modelling case study: roads of Qazvin, Zanjan and Hamadan | |
| Olusina et al. | Spatial analysis of accident spots using weighted severity index (WSI) and density-based clustering algorithm | |
| CN114550445A (en) | Urban area traffic safety state evaluation method and device | |
| Li et al. | A multidimensional quantitative risk assessment framework for dense areas of stay points for urban HazMat vehicles | |
| Zhang | Research on risk projection of urban road traffic safety based on RS-SVM combination model. | |
| CN117238126A (en) | Traffic accident risk assessment method under continuous flow road scene | |
| Abbas et al. | Real-time traffic jam detection and congestion reduction using streaming graph analytics | |
| Bavar et al. | Evaluating the spatial effects of environmental influencing factors on the frequency of urban crashes using the spatial Bayes method based on Euclidean distance and contiguity | |
| Ehsani Sohi et al. | Effects of roadway and traffic characteristics on accidents frequency at city entrance zone | |
| Khabiri et al. | Application of data mining algorithm to investigate the effect of intelligent transportation systems on road accidents reduction by decision tree | |
| Khaksar et al. | Comparison of accident severity and frequency index method in identifying hotspot segments of intercity road network | |
| Yang et al. | Rapid analysis and detection algorithm and prevention countermeasures of urban traffic accidents under artificial intelligence | |
| Obeng et al. | Modelling risk factors of pedestrian accidents on trunk roads in Ghana | |
| CN111652487B (en) | Ecological influence evaluation system for road construction project in natural conservation area | |
| CN117409576B (en) | Neural network-based integrated monitoring system for disaster sky along road | |
| Donnell et al. | The Development of Crash Modification Factors: Highway Safety Statistical Paper Synthesis | |
| CN117057601B (en) | Non-coal mine safety monitoring and early warning system based on Internet of things | |
| Tang et al. | Safety risk factors identification and safety risk classification assessment for rural roadsides |
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 | ||
| CB03 | Change of inventor or designer information | ||
| CB03 | Change of inventor or designer information |
Inventor after: Guo Yajuan Inventor before: Guo Yajuan Inventor before: Yao Tianmu |
|
| GR01 | Patent grant | ||
| GR01 | Patent grant |