CN108959196B - A kind of traffic accident space-time analysis system - Google Patents
A kind of traffic accident space-time analysis system Download PDFInfo
- Publication number
- CN108959196B CN108959196B CN201810742942.5A CN201810742942A CN108959196B CN 108959196 B CN108959196 B CN 108959196B CN 201810742942 A CN201810742942 A CN 201810742942A CN 108959196 B CN108959196 B CN 108959196B
- Authority
- CN
- China
- Prior art keywords
- accident
- data
- analysis
- traffic
- traffic accident
- 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
- 206010039203 Road traffic accident Diseases 0.000 title claims abstract description 93
- 238000004458 analytical method Methods 0.000 title claims abstract description 59
- 238000012545 processing Methods 0.000 claims abstract description 11
- 238000000611 regression analysis Methods 0.000 claims abstract description 6
- 238000012795 verification Methods 0.000 claims abstract description 4
- 238000000034 method Methods 0.000 claims description 24
- 230000008569 process Effects 0.000 claims description 11
- 238000007689 inspection Methods 0.000 claims description 9
- 238000004140 cleaning Methods 0.000 claims description 8
- 238000012732 spatial analysis Methods 0.000 claims description 6
- 230000008859 change Effects 0.000 claims description 5
- 230000007613 environmental effect Effects 0.000 claims description 4
- 230000004927 fusion Effects 0.000 abstract description 5
- 230000010354 integration Effects 0.000 abstract description 5
- 238000013523 data management Methods 0.000 abstract description 3
- 230000015572 biosynthetic process Effects 0.000 description 5
- 238000007726 management method Methods 0.000 description 5
- 238000005516 engineering process Methods 0.000 description 4
- 238000007405 data analysis Methods 0.000 description 3
- 238000011161 development Methods 0.000 description 3
- 238000003860 storage Methods 0.000 description 3
- 241001269238 Data Species 0.000 description 2
- 206010027146 Melanoderma Diseases 0.000 description 2
- 230000008901 benefit Effects 0.000 description 2
- 238000013461 design Methods 0.000 description 2
- 238000003745 diagnosis Methods 0.000 description 2
- 238000009826 distribution Methods 0.000 description 2
- 239000000284 extract Substances 0.000 description 2
- 230000006872 improvement Effects 0.000 description 2
- 230000007246 mechanism Effects 0.000 description 2
- 238000003012 network analysis Methods 0.000 description 2
- 230000008520 organization Effects 0.000 description 2
- 238000012098 association analyses Methods 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 238000013500 data storage Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 230000005611 electricity Effects 0.000 description 1
- 238000002474 experimental method Methods 0.000 description 1
- 238000000605 extraction Methods 0.000 description 1
- 231100001261 hazardous Toxicity 0.000 description 1
- 230000010365 information processing Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000005457 optimization Methods 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 239000013589 supplement Substances 0.000 description 1
- 230000002123 temporal effect Effects 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F40/00—Handling natural language data
- G06F40/20—Natural language analysis
- G06F40/205—Parsing
- G06F40/216—Parsing using statistical methods
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/18—Complex mathematical operations for evaluating statistical data, e.g. average values, frequency distributions, probability functions, regression analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F40/00—Handling natural language data
- G06F40/30—Semantic analysis
-
- 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
- G06Q50/265—Personal security, identity or safety
Abstract
The present invention provides a kind of traffic accident space-time analysis systems, including data Layer: acquisition Fundamental Geographic Information Data, and standardization casualty data warehouse is established in data cleansing and fusion verification;Application layer: according to standardization casualty data warehouse analysis Frequent Accidents region, excavate reason, establish reason countermeasure library, propose reform advice;Presentation layer: showing the analysis of application layer as a result, including traffic accident information, hotspots, reason report, multiple position processing suggestions report.This system is constructed based on the network geographic information system of Browser/Server distributed structure/architecture, promotes traffic accident data management, analysis level, gets rid of terminal constraint, isolated traffic accident Data Integration can be analyzed.Using the iteration of encryption algorithm, the exact position of traffic accident is obtained.Accident Causes Analysis model is established with control statistics, regression analysis, Clustering Model, diagnoses traffic accident feature level occurrence cause, and establish Accident-causing countermeasure library.
Description
Technical field
The present invention relates to network analysis technique field more particularly to a kind of traffic accident space-time analysis systems.
Background technique
With the continuous construction of urban road traffic network, demand pull car ownership of the people for convenient traffic
Continue to increase.Consequent is that traffic accident number is high, and traffic safety has become concerning people's life wealth
The critical problem for producing safety, influencing and restrict socio-economic development quality and benifit is closed in National Security Strategy height
Note and attention.With the extensive use of the new technologies such as computer, internet, sensor, people's lives initially enter " big data
Epoch ", traffic accident data also belong to one of them.Geography information processing technology, information service, spatial analysis and expression
The fast development of technology and development of information system technology proposes the research of traffic accident big data to lot of domestic and international researcher
Preferable platform is supplied.
As Chinese invention patent CN201611063554.1 discloses a kind of particularly serious traffic accident based on correlation rule
Reason recognition methods.This method extracts particularly serious traffic accident data from China's road traffic accident annual report over the years, and will mention
It is people, vehicle, road, environment and other factors totally five class accident variable that the casualty data taken, which divides,.On this basis, this method is transported
With Association Rule Analysis, the reasonable threshold value of support, confidence level and promotion degree in severe and great casualty association analysis is set, is based on
Apriori algorithm, calculates two item collections, three item collections and four item collection rule association rules of particularly serious traffic accident, and combines defeated
Regular grid DEM, confidence level and promotion degree are analyzed out, identify the common reason of particularly serious road traffic accident and thing
Therefore genesis mechanism.Present invention reduces randomnesss and decision-maker's subjective judgement to influence, and can effectively carry out particularly serious traffic thing
Therefore reason identifies, analyzes particularly serious traffic accident mechanism.But to the extraction of traffic accident data not established standards, and not base
A kind of traffic accident space-time analysis system is developed in GIS platform.
For another example Chinese invention patent CN201210143278.5 provides a kind of road traffic accident analysis method.This method
By GIS-Geographic Information System by road data typing server, the geographic information database for having map is established;Eventually by acquisition
End acquisition scene of a traffic accident data, and typing server, generate traffic accident point, establish traffic accident database.By the party
Traffic accident database can be imported geographic information database and show traffic on map by combination between the two by method
Scene of the accident data, accident black-spot, escape accident track down and arrest content.And it can be by the presence of accident black-spot, by road traffic
Accident and surrounding geographical environment etc. combine, the analysis rule that accidents happened occurs, generation of preventing accident.But comprehensive study is not wanted respectively
Inner link between element can not construct reason countermeasure library, and traffic accident to be diagnosed to be Accident Characteristic grade occurrence cause
The acquisition of field data depends on server, and data are extremely inconvenient.Therefore it provides a kind of data acquisition is convenient, can diagnose thing
Therefore the feature level occurrence cause and traffic accident space-time analysis system of decision support can be provided for traffic management department is ability
Domain problem to be solved.
Summary of the invention
The problem to be solved in the present invention is to provide a kind of acquisitions of data conveniently, and data inputting standardization can be integrated effectively
Traffic accident information, infrastructure information, meteorological data, traffic flow data, traffic accident video data are simultaneously analyzed, finally
It obtains the exact address in Frequent Accidents region, and analyzes the inherent connection in personnel-vehicle-road-environmental system between four elements
System establishes Accident Causes Analysis model, diagnoses traffic accident feature level occurrence cause, and establishing Accident-causing countermeasure library is traffic pipe
The traffic accident space-time analysis system of reason department proposition decision support.
To solve the above problems, the present invention adopts the following technical scheme that, a kind of traffic accident space-time analysis system, including number
According to layer, application layer, presentation layer, the data Layer is for establishing standardization casualty data warehouse, and the application layer is according to the mark
Standardization casualty data warehouse carries out crash analysis, and the presentation layer is for showing crash analysis as a result, the data Layer includes base
Plinth geographic information data acquisition typing, to Fundamental Geographic Information Data carry out cleaning with merge verification, using through over cleaning with melt
Close the vertical standardization casualty data warehouse of Building Basic Geographic Information of verification;The crash analysis includes analysis accident-prone area
Domain excavates Accident-causing, establishes Accident-causing countermeasure library and propose reform advice;
The crash analysis result that the presentation layer is shown includes traffic accident information and Frequent Accidents region, Accident-causing
Report, accident prone location processing suggestions report.
Further, the Fundamental Geographic Information Data include traffic accident information based on fundamental geological information platform,
Infrastructure information, meteorological data, traffic flow data, traffic accident video information and naturally drive experimental data.
Further, the analysis system uses the network geographic information system based on Browser/Server distributed structure/architecture
System is to construct.
Further, the traffic accident information is divided into four generic attributes when acquiring typing.
Further, four generic attribute divides into attribute field, and the attribute field divides into attribute value, the attribute
Value includes level-one attribute value and/or secondary attributes value.
Further, with spatial neighborhood relation and road accident safety index when the application layer analysis Frequent Accidents region
For foundation, using GIS map overlay, Spatial analysis method.
Further, analysis Frequent Accidents region process includes accident spot geocoding, the accident spot
Reason coding includes the following steps:
(1) address descriptor inspection, including word frequency statistics and Address factor general term determine;
(2) Address Standardization, change history, missing information including name of satisfying the need carry out completion;
(3) accident semantic locations coordinatograph determines the position on map according to the geographical location information of language description
Coordinate is operated by map api interface;
(4) coding result inspection compares in the true geographical coordinate library in system realm with algorithm coding result
It checks, re-starts step (1), (2), (3) if not by checking, if carrying out step (5) by checking;
(5) accident coordinate is obtained.
Further, the process for excavating Accident-causing specifically includes:
(1) the inherent connection in the comprehensive traffic accident origin cause of formation in researcher-vehicle-road-environmental system between four elements
System;
(2) Accident Causes Analysis model is established according to Traffic Accidents Reasons Analyzed, diagnoses traffic accident feature level occurrence cause;
(3) processing suggestions are proposed for Accident-causing.
Further, the process for establishing Accident Causes Analysis model passes through control statistics, regression analysis, clustering
It is completed with disaggregated model.
Further, the presentation layer shows that traffic accident information and Frequent Accidents region, accident cause by GIS platform
Because of report, accident prone location processing suggestions report, accident prone location temporal-spatial evolution, road hazard grade figure.
Compared with prior art, technical solution provided by the invention has the advantage that
(1) this system is developed based on GIS GIS-Geographic Information System, has the characteristics that the various of transaction information system, and
And can be using its geographical space visually intuitive feature and powerful space analysis ability, it can will be original many and diverse and isolated
Traffic accident data are effectively integrated, manage and are analyzed.
(2) this system is constructed based on the network geographic information system of Browser/Server distributed structure/architecture, Ke Yiyou
Effect promotes traffic accident data management and analysis level;The system can be made to get rid of terminal constraint, realized trans-regional, interdepartmental
Traffic accident file administration and Analysis Service;Accident is associated with can not be by region, portion when the related datas such as weather, road obtain
Door, the limitation of time reduce the procurement cost of data, and can be effectively integrated in internal system, improve data sharing
Degree of integration, reduce data distributes cost.
(3) the application has formulated the typing standard of traffic accident, is divided into traffic accident information in traffic accident typing
Four generic attributes, and attribute field is divided into these four types of attributes, attribute value is divided into attribute field, attribute value further includes level-one attribute
Value and/or secondary attributes value have built good number by the way that traffic accident information is carried out classification for traffic management department
According to processing standard, while it can guarantee the integrality of field again, to provide Data safeguard for subsequent traffic accident analysis.
(4) it at the multiple position of analysis traffic accident, is checked really by the process of accident code optimization, including address descriptor
The accuracy for recognizing address descriptor carries out completion to change history, missing information by Address Standardization, thus with ensure that accident
The accuracy, comprehensive of location description;By accident semantic locations coordinatograph, by the seat on the accident address of language description and map
It marks corresponding, and true geographical coordinate library and algorithm coding result is compared into inspections, and utilization encryption algorithm is not
Disconnected iteration, guarantees to obtain traffic accident accurate coordinates on map.
(5) inner link in comprehensive study personnel-vehicle-road-environmental system between four elements is united with control
Meter, regression analysis, Clustering Model establish Accident Causes Analysis model, are carried out with a variety of Data Analysis Models to accident factors
Analysis diagnoses traffic accident feature level occurrence cause, ensure that the reliability of this feature grade occurrence cause;And according to this feature grade
It is that traffic management department proposes decision support that occurrence cause, which targetedly establishes Accident-causing countermeasure library,.
(6) this system is developed based on GIS GIS-Geographic Information System, can analyze the exact position of traffic accident, and can
Analysis obtains the inner link in researcher-vehicle-road-environmental system between four elements, facilitates traffic administration personnel couple
Distribution of the traffic accident on time and space gives positive and comprehensive control and analysis, and can be to road administration department
The traffic programme of traffic design and traffic control department brings reference value.
Detailed description of the invention
Fig. 1 is a kind of traffic accident space-time analysis system schematic;
Fig. 2 is accident spot geocoding step schematic diagram;
Fig. 3 is Traffic Accidents Reasons Analyzed classification chart.
Specific embodiment
In order to make the objectives, technical solutions, and advantages of the present invention clearer, the content of present invention is done into one below
Step is described in detail.
As shown in Figure 1, a kind of traffic accident space-time analysis system, including data Layer, application layer, presentation layer, data Layer are used
In acquisition and typing Fundamental Geographic Information Data, the Fundamental Geographic Information Data includes the friendship based on fundamental geological information platform
Lead to accident information, infrastructure information, meteorological data, traffic flow data, traffic accident video data and drives experiment number naturally
According to.After these foundation geography information data acquistions, together by these data summarizations, data are merged, clean and
Pretreatment carries out completion to missing information.Data after fusion cleaning, missing information completion are arranged, by building
Vertical casualty data storage model, determines storage organization and relationship, ultimately forms standardization casualty data warehouse.Active set of the present invention
It drives at traffic accident information, infrastructure information, meteorological data, traffic flow data, traffic accident video data and naturally
Experimental data improves data sharing degree of integration, reduces data and distributes cost.Principle based on data warehouse simultaneously, will
Big data extracts, conversion, loads progress structured storage, establishes time series database and solves the excessive technological difficulties of data volume,
By the way that road net data and interest point data over the years and accident semantic information are carried out temporal associativity matching, while utilizing business
Map software (Baidu map, Google Maps, Amap etc.) carry out online crawler and space correlation matching solves positioning
The low problem low with road network precision of precision.
Fusion cleaning, the pretreatment of data are the wrong address dates being related to for traffic accident, comprising: misspelling
Accidentally, the mistakes such as information redundancy, address incompleteness ambiguity are cleaned and are pre-processed.The data of missing can by online crawler, go through
History data supplement.Traffic flow data specifically includes: electricity alert data, bayonet data on flows, loop data;Traffic accident video data
It include: bayonet video data, scene of the accident video data;Naturally driving experimental data includes: driver's driving behavior data;It hands over
Through-flow data and video data can show the details of vehicular traffic and ambient enviroment on road surface when traffic accident occurs, from
So driving experimental data is the behavior expression record for reflecting driver when traffic accident occurs.It is divided into when traffic accident information typing
Accident road conditions occur for four generic attributes, respectively (1) cause of accident, scene and form, (2), (3) accident personnel and vehicle feelings
Condition, (4) accident casualty personnel's situation, these four types of attributes divide into attribute field, and the attribute field divides into attribute value, described
Attribute value includes one of level-one attribute value or secondary attributes value or a variety of, and specific typing standard is shown in Table 1.
1. traffic accident data inputting standard of table
The application layer is according to the data in standardization casualty data warehouse, with spatial neighborhood relation and road accident safety
Index is foundation, using GIS map overlay, Spatial analysis method, according to the geospatial coordinates and road network of casualty data
Structure carries out space correlation and linking parsing, acquires in conjunction with accident prone location identification system, accident prone location environmental characteristic
Network analysis obtains Frequent Accidents region.Improvement is optimized to GIS map overlay, Spatial analysis method in the present invention,
Geocoding processing is specifically carried out to traffic accident semantic information according to existing road net data, using history road net data and is ground
Study carefully geographical library, commercial map API etc. inside region to be analyzed.Then in conjunction with city road network, small towns division, street lamp pile No. and other places
The reason related datas such as information data and telecommunication flow information, accident prone location driving behavior carry out temporal-spatial evolution characteristics and grind
Study carefully, and these data and the multiple position data of traffic accident is combined to determine road hazard grade.
Analyzing Frequent Accidents region process includes accident spot geocoding process, is obtained using the encryption algorithm of continuous iteration
To the exact position of traffic accident, traffic administration personnel is facilitated to give actively distribution of the traffic accident on time and space
And comprehensive control and analysis, accident spot geocoding process are specific as follows:
(1) address descriptor inspection, the address descriptor inspection include that word frequency statistics and Address factor general term determine;
(2) Address Standardization, the Address Standardization include that the satisfy the need change history of name, missing information carries out completion;
(3) accident semantic locations coordinatograph determines the position on map according to the geographical location information of language description
Coordinate is carried out by map api interface;
(4) coding result inspection compares in the true geographical coordinate library in system realm with algorithm coding result
It checks, re-starts step (1), (2), (3) if not by checking, if carrying out step (5) by checking;
(5) accident coordinate is obtained.
As shown in figure 3, Causes of Road Accidents is various, by influence factor range can be divided into macroscopical origin cause of formation and it is microcosmic at
Cause, the former refers to the factor that accident is influenced in terms of big regional scope, such as All population capacities, economic level, vehicle guaranteeding organic quantity
Refer to the factor that accident is influenced in terms of specific accident or characteristic point Deng, the latter, such as driver's situation, road conditions, vehicle item
Part etc.;The direct origin cause of formation can be divided by influence factor type and be associated to because the direct origin cause of formation, which refers to acquire from the scene of the accident, to be believed
Cause of accident attribute in breath, such as parking offense, drink-driving, reverse driving are associated to related with the direct origin cause of formation because referring to
The macroscopic aspect influence factor of connection property, such as road and environmental factor.Therefore, after the accurate coordinates for obtaining Frequent Accidents region, institute
State application layer can inner link in comprehensive study personnel-vehicle-road-environmental system between four elements, with control statistics,
Causes of Road Accidents is created as Accident Causes Analysis model by regression analysis, clustering, disaggregated model, forms road peace
Full assessment indicator system, diagnosis obtain traffic accident feature level occurrence cause i.e. with the biggish element of the correlation of accidents, and needle
Accident-causing countermeasure library is established to different accidents, the type of reason and feature, proposes the rectification of corresponding hazardous location
Opinion.So as to propose decision support for traffic management department, and the traffic design and traffic control of road administration department can be given
The traffic programme of department brings reference value.The presentation layer is used to show the analysis of the application layer as a result, including passing through GIS
Platform shows traffic accident information and Frequent Accidents region, Accident-causing report, accident prone location processing suggestions report, thing
Therefore multiple position temporal-spatial evolution, road hazard grade figure.
Traffic accident space-time analysis system of the present invention uses the net based on Browser/Server distributed structure/architecture
Network GIS-Geographic Information System constructs, and the system can be made to get rid of terminal constraint, realize trans-regional, interdepartmental traffic accident archives
Management and Analysis Service, and effective integration traffic accident information, infrastructure letter are developed based on GIS GIS-Geographic Information System
Breath, meteorological data, traffic flow data, traffic accident video data, improve data sharing degree of integration, reduce data and distribute
Cost, it is final effectively to promote traffic accident data management and analysis level.
A method of traffic accident space-time analysis being carried out with traffic accident space-time analysis system of the present invention, including
Following steps:
Step 1: acquisition and typing Fundamental Geographic Information Data, including traffic accident information, infrastructure information, meteorology
Data, traffic accident video information, drive experimental data at traffic flow data naturally, and when typing need to be with four generic attributes, four generic attributes
The attribute value that attribute field, the attribute field divided into are divided into is corresponding;
Step 2: carrying out the fusion, cleaning and pretreatment of data after data acquire, completion is carried out to missing information,
Mainly for interpreter thus the wrong address date that is related to, comprising: misspelling, the mistakes such as information redundancy, address incompleteness ambiguity;
Step 3: will arrange by fusion, cleaning and pretreated data, mould is stored by establishing casualty data
Type determines storage organization and relationship, ultimately forms standardization casualty data warehouse;
Step 4: being referred to safely according to the data in standardization casualty data warehouse with spatial neighborhood relation and road accident
It is designated as foundation, using GIS map overlay, Spatial analysis method, according to the geospatial coordinates of casualty data and road network knot
Structure carries out space correlation and linking parsing, in conjunction with accident prone location identification system, accident prone location environmental characteristic acquisition system
System utilizes the continuous iteration of encryption algorithm by accident spot geocoding process, and analysis obtains Frequent Accidents region;
Step 5: with control statistics, regression analysis, clustering, dividing after obtaining the accurate coordinates in Frequent Accidents region
Class model establishes Accident Causes Analysis model, to obtain the inherence in personnel-vehicle-road-environmental system between four elements
Connection, diagnosis obtain traffic accident feature level occurrence cause i.e. with the biggish element of the correlation of accidents, and for traffic accident
Feature level occurrence cause establishes Accident-causing countermeasure library and proposes reform advice, forms road safety assessment index system;
Step 6: showing traffic accident information and Frequent Accidents region, Accident-causing report, accident by GIS platform
Multiple position processing suggestions report, accident prone location temporal-spatial evolution, road hazard grade figure.
Embodiment is described in detail in above content, but the present invention is not by the limit of the above-described embodiment and examples
System, without departing from the purpose of the present invention, within the knowledge of those skilled in the art can also to its into
Row various changes and modifications, these changes and improvements are each fallen within scope of protection of the present invention.
Claims (3)
1. a kind of traffic accident space-time analysis system, including data Layer, application layer, presentation layer, the data Layer is for establishing mark
Standardization casualty data warehouse, the application layer carry out crash analysis, the presentation layer according to the standardization casualty data warehouse
For showing crash analysis as a result,
It is characterized by: the data Layer includes foundation geography information data acquistion typing, carries out to Fundamental Geographic Information Data
Cleaning with merge verification, using through over cleaning with merge verify Building Basic Geographic Information stand standardize casualty data storehouse
Library;
The crash analysis includes analysis Frequent Accidents region, excavates Accident-causing, establishes Accident-causing countermeasure library and propose whole
Change opinion;Using spatial neighborhood relation and road accident safety index as foundation when the analysis Frequent Accidents region, schemed using GIS
Layer superposition, Spatial analysis method carry out space correlation and company according to the geospatial coordinates of casualty data and road network structure
Analysis is connect, analyzes to obtain Frequent Accidents in conjunction with accident prone location identification system, accident prone location environmental characteristic acquisition system
Region;Analysis Frequent Accidents region process further includes accident spot geocoding, is obtained using the encryption algorithm of continuous iteration
To the exact position of traffic accident, the accident spot geocoding includes the following steps:
(1) address descriptor inspection, including word frequency statistics and Address factor general term determine;
(2) Address Standardization, change history, missing information including name of satisfying the need carry out completion;
(3) accident semantic locations coordinatograph determines coordinate of the position on map according to the geographical location information of language description,
It is operated by map api interface;
(4) the true geographical coordinate library in system realm is compared inspection with algorithm coding result by coding result inspection,
Step (1), (2), (3) are re-started if not by checking, if carrying out step (5) by checking;
(5) accident coordinate is obtained;
The crash analysis result that the presentation layer is shown includes traffic accident information and Frequent Accidents region, Accident-causing report
Table, accident prone location processing suggestions report;
The Fundamental Geographic Information Data include traffic accident information based on fundamental geological information platform, infrastructure information,
Meteorological data, traffic flow data, traffic accident video information and naturally drive experimental data;
The analysis system is used and is constructed based on the network geographic information system of Browser/Server distributed structure/architecture;
The traffic accident information is divided into four generic attributes when acquiring typing;
Four generic attribute divides into attribute field, and the attribute field divides into attribute value, and the attribute value includes level-one category
Property value and/or secondary attributes value;
The process for excavating Accident-causing specifically includes:
(1) inner link in comprehensive study Traffic Accidents Reasons Analyzed in personnel-vehicle-road-environmental system between four elements;
(2) Accident Causes Analysis model is established according to Traffic Accidents Reasons Analyzed, diagnoses traffic accident feature level occurrence cause;
(3) processing suggestions are proposed for Accident-causing.
2. analysis system according to claim 1, it is characterised in that: the process for establishing Accident Causes Analysis model is logical
Control statistics, regression analysis, clustering and disaggregated model is crossed to complete.
3. analysis system according to claim 2, it is characterised in that: the presentation layer shows traffic thing by GIS platform
Therefore information and Frequent Accidents region, Accident-causing report, accident prone location processing suggestions report, accident prone location space-time
Develop, road hazard grade figure.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201810742942.5A CN108959196B (en) | 2018-07-09 | 2018-07-09 | A kind of traffic accident space-time analysis system |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201810742942.5A CN108959196B (en) | 2018-07-09 | 2018-07-09 | A kind of traffic accident space-time analysis system |
Publications (2)
Publication Number | Publication Date |
---|---|
CN108959196A CN108959196A (en) | 2018-12-07 |
CN108959196B true CN108959196B (en) | 2019-06-28 |
Family
ID=64483313
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN201810742942.5A Active CN108959196B (en) | 2018-07-09 | 2018-07-09 | A kind of traffic accident space-time analysis system |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN108959196B (en) |
Families Citing this family (10)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN109841061A (en) * | 2019-01-24 | 2019-06-04 | 浙江大华技术股份有限公司 | A kind of traffic accident treatment method, apparatus, system and storage medium |
CN110009907A (en) * | 2019-03-25 | 2019-07-12 | 大夏数据服务有限公司 | A kind of traffic administration data calculating analysis system |
CN110222247A (en) * | 2019-06-10 | 2019-09-10 | 交通运输部公路科学研究所 | A kind of highway engineering construction safety hazard analysis system |
CN110532298B (en) * | 2019-08-07 | 2021-06-15 | 北京交通大学 | Multi-attribute railway accident cause weight analysis method |
CN111009122A (en) * | 2019-11-13 | 2020-04-14 | 青岛国信城市信息科技有限公司 | Tunnel traffic operation risk assessment method |
CN111369792B (en) * | 2019-11-22 | 2021-09-10 | 杭州海康威视系统技术有限公司 | Traffic incident analysis method and device and electronic equipment |
CN111046260B (en) * | 2019-12-11 | 2023-04-18 | 中国兵器工业第五九研究所 | Visualization method based on natural environment factor data |
CN112862646A (en) * | 2020-12-31 | 2021-05-28 | 广州智能科技发展有限公司 | Safety accident analysis method and system based on multi-model integration |
CN113112794A (en) * | 2021-03-31 | 2021-07-13 | 四川省气象服务中心(四川省专业气象台 四川省气象影视中心) | Traffic accident occurrence rate prediction method based on space-time meteorological grid |
CN113470357B (en) * | 2021-06-30 | 2022-09-02 | 中国汽车工程研究院股份有限公司 | Road traffic accident information processing system and method |
Citations (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN102411843A (en) * | 2011-09-21 | 2012-04-11 | 中盟智能科技(苏州)有限公司 | Traffic accident prevention analysis system |
CN107784832A (en) * | 2016-08-25 | 2018-03-09 | 上海电科智能系统股份有限公司 | A kind of method and apparatus for being used to identify the accident black-spot in traffic route |
Family Cites Families (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN104574251A (en) * | 2015-01-06 | 2015-04-29 | 熊国顺 | Intelligent public safety information system and application method |
CN105788256B (en) * | 2016-03-30 | 2018-07-24 | 北京交通大学 | Traffic information cognitive method based on car networking |
-
2018
- 2018-07-09 CN CN201810742942.5A patent/CN108959196B/en active Active
Patent Citations (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN102411843A (en) * | 2011-09-21 | 2012-04-11 | 中盟智能科技(苏州)有限公司 | Traffic accident prevention analysis system |
CN107784832A (en) * | 2016-08-25 | 2018-03-09 | 上海电科智能系统股份有限公司 | A kind of method and apparatus for being used to identify the accident black-spot in traffic route |
Non-Patent Citations (1)
Title |
---|
基于GIS的城市道路黑点分析与决策支持研究;任光贤;《中国优秀硕士学位论文全文数据库 基础科学辑》;20160815;第2016年卷(第08期);第A008-27页 |
Also Published As
Publication number | Publication date |
---|---|
CN108959196A (en) | 2018-12-07 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN108959196B (en) | A kind of traffic accident space-time analysis system | |
Souza et al. | City Information Modelling as a support decision tool for planning and management of cities: A systematic literature review and bibliometric analysis | |
Hao et al. | The rise of big data on urban studies and planning practices in China: Review and open research issues | |
CN109145170A (en) | A kind of data mining of road traffic accident server, method and system | |
CN105550758A (en) | GIS-based underground pipeline operation and maintenance system | |
CN101814076A (en) | Visualizing information and information correlation analysis system and establishing method | |
CN105022769A (en) | Data interaction system of urban underground pipeline, and method thereof | |
CN110555568A (en) | Road traffic running state real-time perception method based on social network information | |
Chen | Analysis and forecast of traffic accident big data | |
Liu et al. | Multi-scale urban passenger transportation CO2 emission calculation platform for smart mobility management | |
CN108182218A (en) | A kind of video character recognition method, system and electronic equipment based on GIS-Geographic Information System | |
Ding et al. | RTVEMVS: Real-time modeling and visualization system for vehicle emissions on an urban road network | |
Sun et al. | Scientometric analysis and mapping of transit-oriented development studies | |
Chen et al. | Intelligent management information system of urban planning based on GIS | |
Li et al. | Spatial accessibility to shopping malls in Nanjing, China: Comparative analysis with multiple transportation modes | |
CN107844890A (en) | A kind of mineral properties comprehensive survey monitoring method and system based on GIS | |
Cui et al. | Research on the driving forces of urban hot spots based on exploratory analysis and binary logistic regression model | |
Zeng et al. | Design of data model for urban transport GIS | |
Lian et al. | Advances in estimating pedestrian measures through artificial intelligence: From data sources, computer vision, video analytics to the prediction of crash frequency | |
CN114666738A (en) | Territorial space planning method and system based on mobile phone signaling | |
CN114925994A (en) | Urban village risk assessment and risk factor positioning method based on deep learning | |
Beukes et al. | Quantifying the contextual influences on road design | |
CN110598755B (en) | OD flow clustering method based on vector constraint | |
Wang et al. | GIS cloud computing based government Big Data analysis platform | |
Kwan | Human Mobility, Spatiotemporal Context, and Environmental Health: Recent Advances in Approaches and Methods |
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 | ||
GR01 | Patent grant | ||
GR01 | Patent grant | ||
CP01 | Change in the name or title of a patent holder | ||
CP01 | Change in the name or title of a patent holder |
Address after: 215000 surveying and mapping geographic information building, No. 101, Suhong Middle Road, Suzhou Industrial Park, Suzhou City, Jiangsu Province Patentee after: Yuance Information Technology Co.,Ltd. Address before: 215000 surveying and mapping geographic information building, No. 101, Suhong Middle Road, Suzhou Industrial Park, Suzhou City, Jiangsu Province Patentee before: SUZHOU INDUSTRIAL PARK SURVEYING MAPPING AND GEOINFORMATION Co.,Ltd. |