CN108195385A - A kind of threat identification system and method for combination geographical feature - Google Patents
A kind of threat identification system and method for combination geographical feature Download PDFInfo
- Publication number
- CN108195385A CN108195385A CN201711474871.7A CN201711474871A CN108195385A CN 108195385 A CN108195385 A CN 108195385A CN 201711474871 A CN201711474871 A CN 201711474871A CN 108195385 A CN108195385 A CN 108195385A
- Authority
- CN
- China
- Prior art keywords
- harmful grade
- danger
- dangerous
- danger zone
- harmful
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/26—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
- G01C21/28—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network with correlation of data from several navigational instruments
- G01C21/30—Map- or contour-matching
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/02—Services making use of location information
Landscapes
- Engineering & Computer Science (AREA)
- Radar, Positioning & Navigation (AREA)
- Remote Sensing (AREA)
- Automation & Control Theory (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Computer Networks & Wireless Communication (AREA)
- Signal Processing (AREA)
- Navigation (AREA)
Abstract
The invention discloses a kind of threat identification systems and method of combination geographical feature.Its system includes setting danger zone and dangerous point and harmful grade module, obtains position data and judge whether in danger zone internal module, hazard recognition level block, judge harmful grade variation module, prompting danger and harmful grade module.The mobile terminal of map has been installed in the outfits such as personnel or vehicle.Existing electronic navigation technology is relied on to position personnel or vehicle etc., analyzes the variation with the presence or absence of dangerous, harmful grade and harmful grade such as personnel or vehicle on this basis.The method and system of the present invention solve the problems, such as that existing navigation is not combined with geographical feature and cannot recognize whether dangerous and harmful grade.
Description
Technical field
The invention belongs to technical field of going on a journey, the more particularly to a kind of threat identification system and method for combination geographical feature.
Background technology
Personnel and vehicle are traveling on road, some roads are normal roads, such as highway, railway etc., some roads are
Improper road, such as road and backroad of tourist attraction or scenic spot etc..Current electronic navigation is primarily adapted for use in
The location navigation of normal road, the geographical feature for being not bound with normal road and improper road carry out location navigation.In order to protect
The safety of pedestrian and vehicle is demonstrate,proved, needs existing airmanship being combined with the geographical feature of road, identifies personnel and vehicle
With the presence or absence of dangerous and harmful grade.Therefore a kind of threat identification system and method for combination geographical feature are needed.
Invention content
The technical problems to be solved by the invention are that existing navigation is not combined and cannot identify with geographical feature and is
The problem of no dangerous and harmful grade, proposes a kind of threat identification system and method for combination geographical feature.
Setting positioning intervals T in advance, according to existing airmanship, the position of computing staff or vehicle simultaneously records position
Data are put, position data includes but not limited to longitude and latitude and altitude coordinates value.
The mobile terminal of map has been installed in the outfits such as personnel or vehicle.On the map installed in the terminal in advance, knot
Conjunction geographical feature identifies the region that safety accident easily occurs, such as near steep cliff, on suspension bridge, near lake etc..
A kind of threat identification system of combination geographical feature, including setting danger zone and dangerous point and harmful grade mould
Block obtains position data and judges whether in danger zone internal module, hazard recognition level block, judges harmful grade changing pattern
Block, prompting danger and harmful grade module.It is provided with danger zone and dangerous point and harmful grade module and acquisition positional number
According to and judge whether that in danger zone internal module be necessary module.
Danger zone and dangerous point and harmful grade module are set：The easy region that safety accident occurs is set as dangerous
Region；The critical point of accident will can occur in danger zone or critical line is set as dangerous point；Risk distance and hazard class are set
Other matrix S=[S1S2…Si…SN] in SiValue, 1≤i≤N, N are positive integers, the bigger S of i valuesiIt is worth smaller, corresponding hazard class
It is not higher, wherein, when the distance of mobile terminal and dangerous point is in (Si+1,Si] in the range of, then harmful grade is i；Work as mobile terminal
It is less than S with the distance of dangerous pointNWhen, then harmful grade is N；When the distance of mobile terminal and dangerous point is more than S1When, then judge nothing
It is dangerous.
It obtains position data and judges whether in danger zone internal module：Read the position data at current time；Judging should
Whether position data is in danger zone, if the dangerous point of the danger zone and harmful grade information are then read, into identification
Harmful grade module；Otherwise judgement current time without danger, returns and obtains position data and judge whether in danger zone internal model
Block.
Hazard recognition level block：The position at current time and the distance of dangerous point are calculated using existing method, with variable r
It represents, the side r values from no danger to dangerous point are just, opposite side r values are negative；If r≤SN, then hazard recognition rank is N；If
Si+1<r≤Si, then hazard recognition rank is i；Otherwise judgement current time is without danger.Into judge harmful grade change module.
Judge that harmful grade changes module：Read the harmful grade of previous moment；If the harmful grade at current time is with before
The harmful grade at one moment is identical, then judges that harmful grade is constant；If the harmful grade at current time is more than the danger of previous moment
Dangerous rank then judges that harmful grade increases；Otherwise judgement harmful grade reduces.It returns and obtains position data and judge whether endangering
Danger zone domain internal module.
Prompting danger and harmful grade module：Prompting is in danger zone, danger on the map installed in the terminal
The variation of rank and harmful grade.
A kind of threat identification system block diagram of combination geographical feature is as shown in Figure 1.
A kind of dangerous discernment method of combination geographical feature.It is as follows：
Step 1, setting danger zone and dangerous point and harmful grade.
The easy region that safety accident occurs is set as danger zone；The critical point of accident will can occur in danger zone
Or critical line is set as dangerous point；Risk distance and harmful grade matrix S=[S are set1S2…Si…SN] in SiValue, 1≤i≤
N, N are positive integers, the bigger S of i valuesiIt is worth smaller, corresponding harmful grade is higher, wherein, when mobile terminal and the distance of dangerous point
In (Si+1,Si] in the range of, then harmful grade is i；When the distance of mobile terminal and dangerous point is less than SNWhen, then harmful grade is N；
When the distance of mobile terminal and dangerous point is more than S1When, then judgement is without danger.
Step 2 obtains position data and judges whether in danger zone.
Read the position data at current time；The position data is judged whether in danger zone, if then reading the danger
The dangerous point in danger zone domain and harmful grade information, enter step 3；Otherwise judgement current time is without danger, return to step 2.
Step 3, hazard recognition rank.
The position at current time and the distance of dangerous point are calculated using existing method, is represented with variable r, from no danger to danger
The side r values nearly put are just, opposite side r values are negative；If r≤SN, then hazard recognition rank is N；If Si+1<r≤Si, then danger is identified
Dangerous rank is i；Otherwise judgement current time is without danger.Enter step 4.
Step 4 judges that harmful grade changes.
Read the harmful grade of previous moment；If the harmful grade at current time is identical with the harmful grade of previous moment,
Then judge that harmful grade is constant；If the harmful grade at current time is more than the harmful grade of previous moment, harmful grade is judged
Increase；Otherwise judgement harmful grade reduces.Return to step 2.
Step 5, prompting danger and harmful grade.
Variation of the prompting in danger zone, harmful grade and harmful grade on the map installed in the terminal.
A kind of flow chart of the dangerous discernment method of combination geographical feature is as shown in Figure 2.Wherein, step 1 and step 2 be must
Want step.
The system and method for the present invention has the following advantages：
(1) setting danger zone and dangerous point and harmful grade are combined with geographical feature in navigation map.
(2) by mobile terminal locations and dangerous point apart from size identification whether in danger zone and harmful grade,
It reminds in time dangerous.
Description of the drawings：
Fig. 1 is a kind of threat identification system block diagram of combination geographical feature of the present invention；
Fig. 2 is the flow chart for the dangerous discernment method that the present invention combines geographical feature；
Fig. 3 is the danger zone of steep cliff of the embodiment of the present invention and dangerous point and harmful grade schematic diagram；
Fig. 4 is the danger zone in lake of the embodiment of the present invention and dangerous point and harmful grade schematic diagram.
Specific embodiment
It elaborates below to the present invention to specific embodiment
The dangerous discernment that the present invention is suitable for personnel at all levels and vehicle is advanced on road.Particularly with tourist attraction or wind
Scenic spot (hereinafter referred to as scenic spot), geographical feature are complicated, and most of road in scenic area is non-normal road, such as mountain pass, bridge, hole
Deng.In order to ensure the safety of scenic spot one skilled in the art and vehicle, need existing airmanship being combined with geographical feature, identify people
Member and vehicle whether there is the variation of dangerous, harmful grade and harmful grade.
Setting positioning intervals T in advance, according to existing airmanship, the position of computing staff or vehicle simultaneously records position
Data are put, position data includes but not limited to longitude and latitude and altitude coordinates value.In the present embodiment, positioning intervals T=1 is set
Second, according to existing airmanship, the position of computing staff or vehicle and record position data, position data are longitude and latitude and sea
Pull out coordinate value.
The mobile terminal of map has been installed in the outfits such as personnel or vehicle.On the map installed in the terminal in advance, knot
Conjunction geographical feature identifies the region that safety accident easily occurs, such as near steep cliff, on suspension bridge, near lake etc..The present embodiment
In, the mobile terminal of certain scenic spot map has been installed in the outfits such as personnel and vehicle, on the scenic spot map installed in the terminal, knot
Geographical feature is closed, it is at steep cliff and lake two to identify the region that safety accident easily occurs in scenic spot.
A kind of threat identification system of combination geographical feature, including setting danger zone and dangerous point and harmful grade mould
Block obtains position data and judges whether in danger zone internal module, hazard recognition level block, judges harmful grade changing pattern
Block, prompting danger and harmful grade module.It is provided with danger zone and dangerous point and harmful grade module and acquisition positional number
According to and judge whether that in danger zone internal module be necessary module.
Danger zone and dangerous point and harmful grade module are set：The easy region that safety accident occurs is set as dangerous
Region；The critical point of accident will can occur in danger zone or critical line is set as dangerous point；Risk distance and hazard class are set
Other matrix S=[S1S2…Si…SN] in SiValue, 1≤i≤N, N are positive integers, the bigger S of i valuesiIt is worth smaller, corresponding hazard class
It is not higher, wherein, when the distance of mobile terminal and dangerous point is in (Si+1,Si] in the range of, then harmful grade is i；Work as mobile terminal
It is less than S with the distance of dangerous pointNWhen, then harmful grade is N；When the distance of mobile terminal and dangerous point is more than S1When, then judge nothing
It is dangerous.In the present embodiment, the steep cliff region that safety accident easily occurs in the scenic spot and lake region are set as danger zone,
The lake edge on the cliffside edge in steep cliff region and lake region is set as dangerous point, and (dangerous point is dangerous critical herein
Line), setting risk distance and harmful grade matrix S=[S1S2…Si…SN]=[10 98765432 1], unit is
Rice, N=10, then the danger zone in steep cliff and lake and dangerous point and harmful grade as shown in Figure 3 and Figure 4, wherein, when it is mobile eventually
The distance of end and dangerous point is in (Si+1,Si] in the range of, then harmful grade is i, when the distance of mobile terminal and dangerous point is less than SN
At=1 meter, then harmful grade is N；When the distance of mobile terminal and dangerous point is more than S1At=10 meters, then judgement is without danger.
It obtains position data and judges whether in danger zone internal module：Read the position data at current time；Judging should
Whether position data is in danger zone, if the dangerous point of the danger zone and harmful grade information are then read, into identification
Harmful grade module；Otherwise judgement current time without danger, returns and obtains position data and judge whether in danger zone internal model
Block.In the present embodiment, read certain moment longitude and latitude and altitude coordinates value for (121.04007 ° of east longitude, 28.322 ° of north latitude,
1000 meters), which then reads the dangerous point of the danger zone and harmful grade such as figure in the steep cliff danger zone of scenic spot
Shown in 3, the position data of dangerous critical line is 121.04 ° of east longitude, 1000 meters of height above sea level, 28.3214 ° of north latitude to north latitude
28.32232 °, into hazard recognition level block.
Hazard recognition level block：The position at current time and the distance of dangerous point are calculated using existing method, with variable r
It represents, the side r values from no danger to dangerous point are just, opposite side r values are negative；If r≤SN, then hazard recognition rank is N；If
Si+1<r≤Si, then hazard recognition rank is i；Otherwise judgement current time is without danger.Into judge harmful grade change module.
In the present embodiment, the side r values from mountain side to steep cliff are just, opposite side r values are negative；Using existing latitude and longitude coordinates calculating side
Method calculates r=7.8 meters of the distance of moment position and dangerous point, S3=7<R=7.8≤S2=8, then hazard recognition rank is 2,
As shown in figure 3, represent personnel current location with black circle.Into judge harmful grade change module.
Judge that harmful grade changes module：Read the harmful grade of previous moment；If the harmful grade at current time is with before
The harmful grade at one moment is identical, then judges that harmful grade is constant；If the harmful grade at current time is more than the danger of previous moment
Dangerous rank then judges that harmful grade increases；Otherwise judgement harmful grade reduces.It returns and obtains position data and judge whether endangering
Danger zone domain internal module.In the present embodiment, the harmful grade for reading previous moment is 0, and the harmful grade at current time is more than previous
The harmful grade at moment then judges that harmful grade increases.It returns and obtains position data and judge whether in danger zone internal module.
Prompting danger and harmful grade module：Prompting is in danger zone, danger on the map installed in the terminal
The variation of rank and harmful grade.In the present embodiment, on the scenic spot map installed in the terminal prompting endanger in steep cliff
In the domain of danger zone, current dangerous rank is 2, and harmful grade is increasing.
A kind of dangerous discernment method of combination geographical feature.It is as follows：
Step 1, setting danger zone and dangerous point and harmful grade.
The easy region that safety accident occurs is set as danger zone；The critical point of accident will can occur in danger zone
Or critical line is set as dangerous point；Risk distance and harmful grade matrix S=[S are set1S2…Si…SN] in SiValue, 1≤i≤
N, N are positive integers, the bigger S of i valuesiIt is worth smaller, corresponding harmful grade is higher, wherein, when mobile terminal and the distance of dangerous point
In (Si+1,Si] in the range of, then harmful grade is i；When the distance of mobile terminal and dangerous point is less than SNWhen, then harmful grade is N；
When the distance of mobile terminal and dangerous point is more than S1When, then judgement is without danger.In the present embodiment, will easily it pacify in the scenic spot
The steep cliff region and lake region of full accident are set as danger zone, by the cliffside edge in steep cliff region and the lake of lake region
Edge is set as dangerous point (dangerous point is dangerous critical line herein), setting risk distance and harmful grade matrix S=
[S1S2…Si…SN]=[10 98765432 1], unit is rice, i.e. N=10, then the danger zone in steep cliff and lake
With dangerous point and harmful grade as shown in Figure 3 and Figure 4, wherein, when the distance of mobile terminal and dangerous point is in (Si+1,Si] range
Interior, then harmful grade is i, when the distance of mobile terminal and dangerous point is less than SNAt=1 meter, then harmful grade is N；When mobile whole
The distance at end and dangerous point is more than S1At=10 meters, then judgement is without danger.
Step 2 obtains position data and judges whether in danger zone.
Read the position data at current time；The position data is judged whether in danger zone, if then reading the danger
The dangerous point in danger zone domain and harmful grade information, enter step 3；Otherwise judgement current time is without danger, return to step 2.This reality
It applies in example, it is (121.04007 ° of east longitude, 28.322 °, 1000 meters of north latitude) to read the longitude and latitude at certain moment and altitude coordinates value, should
Position data in the steep cliff danger zone of scenic spot, then read the danger zone dangerous point and harmful grade as shown in figure 3, its endanger
The position data of dangerous critical line is 121.04 ° of east longitude, and 1000 meters of height above sea level, 28.3214 ° of north latitude is to 28.32232 ° of north latitude, into step
Rapid 3.
Step 3, hazard recognition rank.
The position at current time and the distance of dangerous point are calculated using existing method, is represented with variable r, from no danger to danger
The side r values nearly put are just, opposite side r values are negative；If r≤SN, then hazard recognition rank is N；If Si+1<r≤Si, then danger is identified
Dangerous rank is i；Otherwise judgement current time is without danger.Enter step 4.In the present embodiment, the side r values from mountain side to steep cliff are
Just, opposite side r values are negative；The distance r=of moment position and dangerous point is calculated using existing latitude and longitude coordinates computational methods
7.8 meters, S3=7<R=7.8≤S2=8, then hazard recognition rank is 2, as shown in figure 3, representing personnel's present bit with black circle
It puts.Enter step 4.
Step 4 judges that harmful grade changes.
Read the harmful grade of previous moment；If the harmful grade at current time is identical with the harmful grade of previous moment,
Then judge that harmful grade is constant；If the harmful grade at current time is more than the harmful grade of previous moment, harmful grade is judged
Increase；Otherwise judgement harmful grade reduces.Return to step 2.In the present embodiment, the harmful grade for reading previous moment is 0, currently
The harmful grade at moment is more than the harmful grade of previous moment, then judges that harmful grade increases.Return to step 2.
Step 5, prompting danger and harmful grade.
Variation of the prompting in danger zone, harmful grade and harmful grade on the map installed in the terminal.
In the present embodiment, in steep cliff danger zone, current dangerous rank is for prompting on the scenic spot map installed in the terminal
2, harmful grade is increasing.
Certainly, ordinary skill in the art it should be appreciated that above example is intended merely to illustrate the present invention,
And limitation of the invention is not intended as, as long as within the scope of the invention, variation, modification to above example are fallen within
Protection scope of the present invention.
Claims (10)
1. a kind of threat identification system of combination geographical feature, which is characterized in that including setting danger zone and dangerous point and danger
Dangerous level block obtains position data and judges whether in danger zone internal module；
The setting danger zone and dangerous point and harmful grade module：The easy region that safety accident occurs that will be identified in advance
It is set as danger zone；The critical point of accident will can occur in danger zone or critical line is set as dangerous point；Setting it is dangerous away from
From with harmful grade matrix S=[S1S2…Si…SN] in SiValue, 1≤i≤N, N are positive integers, the bigger S of i valuesiBe worth it is smaller, it is right
The harmful grade answered is higher, wherein, when the distance of mobile terminal and dangerous point is in (Si+1,Si] in the range of, then harmful grade is i；
When the distance of mobile terminal and dangerous point is less than SNWhen, then harmful grade is N；When the distance of mobile terminal and dangerous point is more than S1
When, then judgement is without danger；
It is described to obtain position data and judge whether in danger zone internal module：Read the position data at current time；Judging should
Whether position data is in danger zone, if then reading the dangerous point of the danger zone and harmful grade information；Otherwise judge
Current time is without danger.
2. the threat identification system of a kind of combination geographical feature according to claim 1, which is characterized in that further include identification
Harmful grade module：The position at current time and the distance of dangerous point are calculated, is represented with variable r, from no danger to dangerous point
Side r values are just, opposite side r values are negative；If r≤SN, then hazard recognition rank is N；If Si+1<r≤Si, then hazard recognition rank
For i；Otherwise judgement current time is without danger.
3. the threat identification system of a kind of combination geographical feature according to claim 2, which is characterized in that further include judgement
Harmful grade changes module：Read the harmful grade of previous moment；If the harmful grade at current time and the danger of previous moment
Rank is identical, then judges that harmful grade is constant；If the harmful grade at current time is more than the harmful grade of previous moment, judge
Harmful grade increases；Otherwise judgement harmful grade reduces.
4. according to a kind of threat identification system of combination geographical feature of claim 1-3 any one of them, which is characterized in that also
Including prompting danger and harmful grade module：Prompting is in danger zone, harmful grade on the map installed in the terminal
And the variation of harmful grade.
5. according to a kind of threat identification system of combination geographical feature of claim 1-3 any one of them, which is characterized in that thing
On the map first installed in the terminal, with reference to geographical feature, the region that safety accident easily occurs is identified.
A kind of 6. dangerous discernment method of combination geographical feature, which is characterized in that include the following steps：
The easy region that safety accident occurs identified in advance is set as danger zone by step 1；It will can occur in danger zone
The critical point of accident or critical line are set as dangerous point；Risk distance and harmful grade matrix S=[S are set1S2…Si…SN] in
SiValue, 1≤i≤N, N are positive integers, the bigger S of i valuesiBe worth smaller, corresponding harmful grade is higher, wherein, when mobile terminal with
The distance of dangerous point is in (Si+1,Si] in the range of, then harmful grade is i；When the distance of mobile terminal and dangerous point is less than SNWhen, then
Harmful grade is N；When the distance of mobile terminal and dangerous point is more than S1When, then judgement is without danger；
Step 2, the position data for reading current time；The position data is judged whether in danger zone, it should if then reading
The dangerous point of danger zone and harmful grade information；Otherwise judgement current time is without danger.
7. the dangerous discernment method of a kind of combination geographical feature according to claim 6, which is characterized in that further include step
3：Calculate the position at current time and the distance of dangerous point, represented with variable r, the side r values from no danger to dangerous point for just,
Opposite side r values are negative；If r≤SN, then hazard recognition rank is N；If Si+1<r≤Si, then hazard recognition rank is i；Otherwise judge
Current time is without danger.
8. the dangerous discernment method of a kind of combination geographical feature according to claim 7, which is characterized in that further include step
4：Read the harmful grade of previous moment；If the harmful grade at current time is identical with the harmful grade of previous moment, judge
Harmful grade is constant；If the harmful grade at current time is more than the harmful grade of previous moment, judge that harmful grade increases；It is no
Then judge that harmful grade reduces.
9. according to a kind of dangerous discernment method of combination geographical feature of claim 6-8 any one of them, which is characterized in that also
Including step 5：Change of the prompting in danger zone, harmful grade and harmful grade on the map installed in the terminal
Change.
10. according to a kind of dangerous discernment method of combination geographical feature of claim 6-8 any one of them, which is characterized in that
On the map installed in the terminal in advance, with reference to geographical feature, the region that safety accident easily occurs is identified.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201711474871.7A CN108195385A (en) | 2017-12-29 | 2017-12-29 | A kind of threat identification system and method for combination geographical feature |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201711474871.7A CN108195385A (en) | 2017-12-29 | 2017-12-29 | A kind of threat identification system and method for combination geographical feature |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN108195385A true CN108195385A (en) | 2018-06-22 |
Family
ID=62586069
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201711474871.7A Pending CN108195385A (en) | 2017-12-29 | 2017-12-29 | A kind of threat identification system and method for combination geographical feature |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN108195385A (en) |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109118829A (en) * | 2018-09-10 | 2019-01-01 | 北京航空航天大学东营研究院 | A kind of airport personnel dynamic monitoring and controlling method and system |
| CN109272705A (en) * | 2018-09-10 | 2019-01-25 | 杭州后博科技有限公司 | A kind of user security based on knapsack position judges system and method |
| CN112641434A (en) * | 2020-12-22 | 2021-04-13 | 江汉大学 | Navigation positioning based old people monitoring method, storage medium and system |
| CN113627405A (en) * | 2021-10-12 | 2021-11-09 | 环球数科集团有限公司 | Scenic spot danger monitoring method and device and computer equipment |
Citations (19)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102298850A (en) * | 2011-06-17 | 2011-12-28 | 福建工程学院 | Method for prompting user actively in dangerous driving area |
| CN102361777A (en) * | 2010-05-26 | 2012-02-22 | 三菱电机株式会社 | Device for generating sound to outside of vehicle |
| CN103106396A (en) * | 2013-01-06 | 2013-05-15 | 中国人民解放军91655部队 | Danger zone detection method |
| CN103208205A (en) * | 2013-03-20 | 2013-07-17 | 北京航空航天大学 | Vehicle safety driving early warning method based on vehicle internet |
| CN103247144A (en) * | 2012-02-07 | 2013-08-14 | 宇龙计算机通信科技(深圳)有限公司 | Traffic safety prompting method and mobile terminal |
| CN103578288A (en) * | 2013-11-13 | 2014-02-12 | 惠州Tcl移动通信有限公司 | Traffic safety reminding method, mobile terminal and traffic safety reminding system |
| CN104236558A (en) * | 2013-06-21 | 2014-12-24 | 英华达（上海）科技有限公司 | Dangerous zone caution system and dangerous zone caution method |
| JP2016057808A (en) * | 2014-09-09 | 2016-04-21 | 株式会社日立国際八木ソリューションズ | Risk management system |
| CN105575049A (en) * | 2015-06-26 | 2016-05-11 | 宇龙计算机通信科技(深圳)有限公司 | Early warning method, device and terminal |
| CN105592416A (en) * | 2015-11-24 | 2016-05-18 | 北京安赛捷智能科技股份有限公司 | Warning region determination method and system and mobile terminal |
| CN105701964A (en) * | 2014-12-15 | 2016-06-22 | 西门子公司 | Dynamic virtual fencing for a hazardous environment |
| CN106133801A (en) * | 2014-03-27 | 2016-11-16 | 三菱电机株式会社 | Driving assistance information generates system, driving assistance information provides device, driving assistance information to generate method and driving assistance information generates program |
| CN106164997A (en) * | 2014-02-27 | 2016-11-23 | 通腾运输公司 | For the method that danger is associated with the area of numerical map |
| CN106314440A (en) * | 2015-07-07 | 2017-01-11 | 大陆汽车电子(芜湖)有限公司 | Vehicle distance display method |
| CN106355881A (en) * | 2016-10-12 | 2017-01-25 | 同济大学 | Space-autocorrelation-based traffic accident blackspot identification method and device |
| CN106899766A (en) * | 2017-03-13 | 2017-06-27 | 宇龙计算机通信科技(深圳)有限公司 | A kind of safety instruction method and its device and mobile terminal |
| CN107154133A (en) * | 2017-06-22 | 2017-09-12 | 南京邮电大学 | A kind of regional early warning method based on defined position |
| CN107221152A (en) * | 2016-03-21 | 2017-09-29 | 福特全球技术公司 | Geography fence application for facilitating driver |
| CN107430006A (en) * | 2014-12-02 | 2017-12-01 | 凯文·孙林·王 | Avoid the method and system of accident |
-
2017
- 2017-12-29 CN CN201711474871.7A patent/CN108195385A/en active Pending
Patent Citations (19)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102361777A (en) * | 2010-05-26 | 2012-02-22 | 三菱电机株式会社 | Device for generating sound to outside of vehicle |
| CN102298850A (en) * | 2011-06-17 | 2011-12-28 | 福建工程学院 | Method for prompting user actively in dangerous driving area |
| CN103247144A (en) * | 2012-02-07 | 2013-08-14 | 宇龙计算机通信科技(深圳)有限公司 | Traffic safety prompting method and mobile terminal |
| CN103106396A (en) * | 2013-01-06 | 2013-05-15 | 中国人民解放军91655部队 | Danger zone detection method |
| CN103208205A (en) * | 2013-03-20 | 2013-07-17 | 北京航空航天大学 | Vehicle safety driving early warning method based on vehicle internet |
| CN104236558A (en) * | 2013-06-21 | 2014-12-24 | 英华达（上海）科技有限公司 | Dangerous zone caution system and dangerous zone caution method |
| CN103578288A (en) * | 2013-11-13 | 2014-02-12 | 惠州Tcl移动通信有限公司 | Traffic safety reminding method, mobile terminal and traffic safety reminding system |
| CN106164997A (en) * | 2014-02-27 | 2016-11-23 | 通腾运输公司 | For the method that danger is associated with the area of numerical map |
| CN106133801A (en) * | 2014-03-27 | 2016-11-16 | 三菱电机株式会社 | Driving assistance information generates system, driving assistance information provides device, driving assistance information to generate method and driving assistance information generates program |
| JP2016057808A (en) * | 2014-09-09 | 2016-04-21 | 株式会社日立国際八木ソリューションズ | Risk management system |
| CN107430006A (en) * | 2014-12-02 | 2017-12-01 | 凯文·孙林·王 | Avoid the method and system of accident |
| CN105701964A (en) * | 2014-12-15 | 2016-06-22 | 西门子公司 | Dynamic virtual fencing for a hazardous environment |
| CN105575049A (en) * | 2015-06-26 | 2016-05-11 | 宇龙计算机通信科技(深圳)有限公司 | Early warning method, device and terminal |
| CN106314440A (en) * | 2015-07-07 | 2017-01-11 | 大陆汽车电子(芜湖)有限公司 | Vehicle distance display method |
| CN105592416A (en) * | 2015-11-24 | 2016-05-18 | 北京安赛捷智能科技股份有限公司 | Warning region determination method and system and mobile terminal |
| CN107221152A (en) * | 2016-03-21 | 2017-09-29 | 福特全球技术公司 | Geography fence application for facilitating driver |
| CN106355881A (en) * | 2016-10-12 | 2017-01-25 | 同济大学 | Space-autocorrelation-based traffic accident blackspot identification method and device |
| CN106899766A (en) * | 2017-03-13 | 2017-06-27 | 宇龙计算机通信科技(深圳)有限公司 | A kind of safety instruction method and its device and mobile terminal |
| CN107154133A (en) * | 2017-06-22 | 2017-09-12 | 南京邮电大学 | A kind of regional early warning method based on defined position |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109118829A (en) * | 2018-09-10 | 2019-01-01 | 北京航空航天大学东营研究院 | A kind of airport personnel dynamic monitoring and controlling method and system |
| CN109272705A (en) * | 2018-09-10 | 2019-01-25 | 杭州后博科技有限公司 | A kind of user security based on knapsack position judges system and method |
| CN112641434A (en) * | 2020-12-22 | 2021-04-13 | 江汉大学 | Navigation positioning based old people monitoring method, storage medium and system |
| CN113627405A (en) * | 2021-10-12 | 2021-11-09 | 环球数科集团有限公司 | Scenic spot danger monitoring method and device and computer equipment |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN108195385A (en) | A kind of threat identification system and method for combination geographical feature | |
| US9501934B2 (en) | Notification system, electronic device, notification method, and program | |
| CN102016507B (en) | Self-learning map on basis of environment sensors | |
| JP2009140008A (en) | Dangerous traveling information provision device, dangerous traveling decision program and dangerous traveling decision method | |
| US20120296539A1 (en) | Driver assistance system | |
| Saiprasert et al. | Driver behaviour profiling using smartphone sensory data in a V2I environment | |
| CN107533800A (en) | Cartographic information storage device, automatic Pilot control device, control method, program and storage medium | |
| US20120303222A1 (en) | Driver assistance system | |
| US9812007B2 (en) | Map generation system, map generation device, map generation method, and program | |
| CN102903254B (en) | School regional safety device of advanced safety vehicle, and method thereof | |
| JP2014522049A (en) | Traffic sign recognition method | |
| MX2015002236A (en) | Autonomous driving sensing system and method. | |
| US20120245756A1 (en) | Driver assistance system | |
| CN101750069A (en) | Navigation device and limitation information promoting method thereof | |
| JP4141007B2 (en) | Navigation device | |
| US20160046297A1 (en) | Driving evaluation system, electronic device, driving evaluation method, and program | |
| CN104567885A (en) | Navigation device and judgment method of elevated upper and lower roads | |
| CN104299441A (en) | Computer program product and driver assistance system for a vehicle | |
| CN105157709A (en) | ADASIS (advanced driver assistance systems interface specifications) extended information output device and method based on safe driving map | |
| JP7462396B2 (en) | Method and apparatus for operating a vehicle | |
| CN110310499A (en) | A kind of method and device of ring road speed limit identification | |
| WO2013136778A1 (en) | Device for determining sensitivity to prediction of unexpected situations | |
| CN110276971A (en) | A kind of auxiliary control method of vehicle drive, system and vehicle | |
| CN103198689A (en) | A method for assisting a driver | |
| CN104157160A (en) | Vehicle drive control method and device as well as vehicle |
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 | ||
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20180622 |