CN104575063A - Pre-warning method for vehicle - Google Patents
Pre-warning method for vehicle Download PDFInfo
- Publication number
- CN104575063A CN104575063A CN201410831737.8A CN201410831737A CN104575063A CN 104575063 A CN104575063 A CN 104575063A CN 201410831737 A CN201410831737 A CN 201410831737A CN 104575063 A CN104575063 A CN 104575063A
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- vehicle
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- early warning
- warning method
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Classifications
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- G—PHYSICS
- G07—CHECKING-DEVICES
- G07C—TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
- G07C5/00—Registering or indicating the working of vehicles
- G07C5/08—Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle or waiting time
- G07C5/0816—Indicating performance data, e.g. occurrence of a malfunction
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/09—Arrangements for giving variable traffic instructions
- G08G1/0962—Arrangements for giving variable traffic instructions having an indicator mounted inside the vehicle, e.g. giving voice messages
- G08G1/09626—Arrangements for giving variable traffic instructions having an indicator mounted inside the vehicle, e.g. giving voice messages where the origin of the information is within the own vehicle, e.g. a local storage device, digital map
Abstract
The invention discloses a pre-warning method for a vehicle. According to the method, the most appropriate pre-warning rule can be customized according to specific feature information of the vehicle, the pre-warning accuracy is high, and risks in the vehicle driving process are greatly reduced. The method is executed by a vehicle terminal and a background processing system mounted on the vehicle and comprises steps as follows: (1), indexes requiring attention are abstracted according to factors related to driving safety, and a corresponding weighted value is set for each index; (2), vehicle data are collected and comprise static data, vehicle driving dynamic data, space data and driver information; (3), a risk coefficient of each index is calculated according to the weighted value of each index and the corresponding vehicle data, the risk coefficients of all the indexes are accumulated, and a total risk coefficient is obtained; (4), whether the total risk coefficient is in a specified range is judged, if yes, the step (5) is executed, and otherwise, the step (2) is executed; (5), a pre-warning message is sent to the vehicle terminal.
Description
Technical field
The present invention relates to the technical field of car alarming, relate to a kind of vehicle early warning method particularly, for pre-setting the warning restriction of vehicle, triggering the warning system of vehicle when exceeding this warning restriction.
Background technology
Along with the development and progress of human society, people adopt automobile as the vehicles more and more, and the automobile on road increases swift and violent, and traffic hazard also increases thereupon fast.
At present, market there are some vehicle early warning methods, has mainly contained following several:
1. vehicle exceedes fixing velocity amplitude early warning.
2. calculate the need of early warning according to the speed limit of place road and vehicle present speed.
3. the terminal that vehicle is installed judges whether fatigue driving according to the running time of vehicle.
But these vehicle early warning methods are relatively single, the rule of trigger alarm is more stiff, and the ratio reported by mistake or fail to report is higher, and too much wrong report will cause driver numb to warning message, fail to report, add accident risk.Therefore, the accuracy rate improving early warning has very large meaning for reduction vehicle travel risk.
Summary of the invention
Technology of the present invention is dealt with problems and is: overcome the deficiencies in the prior art, a kind of vehicle early warning method is provided, it can for the concrete characteristic information of vehicle for it customizes most suitable early warning rule, and the accuracy rate of early warning is high, greatly reduces the risk in vehicle travel process.
Technical solution of the present invention is: this vehicle early warning method, and the method performs in the disposal system on the car machine terminal be installed on vehicle and backstage, and comprises the following steps:
(1) take out the index of needs concern according to the factor being related to driving safety, and be the corresponding weighted value of each setup measures;
(2) gather vehicle data, vehicle data comprises static data, vehicle travels dynamic data, spatial data, driver information;
(3), after receiving the vehicle data that step (2) gathers, calculate the risk factor of each index according to the weighted value of each index and corresponding vehicle data, finally the risk factor of cumulative all indexs, draws overall risk coefficient;
(4) judge whether overall risk coefficient reaches specified scope, if it is perform step (5), otherwise perform step (2);
(5) early warning information is sent to car machine terminal.
Static data, the vehicle of collection vehicle of the present invention travel dynamic data, spatial data, driver information, calculate the risk factor of vehicle within the next time period in real time, and according to the scope at risk factor place, early warning information is sent to car machine terminal, so can for the concrete characteristic information of vehicle for it customizes most suitable early warning rule, the accuracy rate of early warning is high, greatly reduces the risk in vehicle travel process.
Accompanying drawing explanation
Fig. 1 is the process flow diagram of vehicle according to the invention method for early warning.
Embodiment
As shown in Figure 1, this vehicle early warning method, the method performs in the disposal system on the car machine terminal be installed on vehicle and backstage, and comprises the following steps:
(1) take out the index of needs concern according to the factor being related to driving safety, and be the corresponding weighted value of each setup measures;
(2) gather vehicle data, vehicle data comprises static data, vehicle travels dynamic data, spatial data, driver information;
(3), after receiving the vehicle data that step (2) gathers, calculate the risk factor of each index according to the weighted value of each index and corresponding vehicle data, finally the risk factor of cumulative all indexs, draws overall risk coefficient;
(4) judge whether overall risk coefficient reaches specified scope, if it is perform step (5), otherwise perform step (2);
(5) early warning information is sent to car machine terminal.
Static data, the vehicle of collection vehicle of the present invention travel dynamic data, spatial data, driver information, calculate the risk factor of vehicle within the next time period in real time, and according to the scope at risk factor place, early warning information is sent to car machine terminal, so can for the concrete characteristic information of vehicle for it customizes most suitable early warning rule, the accuracy rate of early warning is high, greatly reduces the risk in vehicle travel process.
In addition, static data comprises vehicle model, vehicle brand, vehicle dimension, the highest design speed per hour, own wt, dead weight, accurate traction gross mass, tire quantity and specification, year of manufacture and the time of setting out on a journey, distance travelled, vitals maintenance history ((comprise, detent, engine, wheel box, tire, semiaxis etc.) in described step (2)), history accident information.
In addition, in described step (2) vehicle travel that dynamic data comprises travel speed, gross mass (deadweight+goods weight), acceleration change situation (speed fluctuation coefficients of nearest 5 minutes), tire pressure, water temperature, vehicle travel duration continuously, whether there is fatigue driving, cockpit image, acoustic information.
In addition, described step (2) spatial data comprises the history accident conditions in visibility, humidity, temperature, the speed limit of road, place road traffic, the track quantity of place road, current longitude and latitude 3 kilometer range.
In addition, in described step (2), driver information comprises birthday, sex, driving age, history, history accident, blood group, eyesight and hearing loss violating the regulations.
In addition, when described step (2) gathers, static data is obtained in car machine terminal input vehicle model code (or mobile phone photograph vehicle driving license) by car owner; Vehicle is travelled dynamic data and is gathered by car machine terminal; Spatial data is obtained by the relevant interface of Chinese weather network interface and Traffic Administration Bureau; Driver information is inputted by car owner and obtains.
In addition, described weighted value is 0.01-1.The weighted value of index shows more greatly the potential safety hazard in driving process larger, otherwise less.
Particularly, providing the example of an early warning, getting following a few item number according to calculating:
1. speed:
Exceed every 5 kilometers/hour of place road speed limit, danger coefficient increases by 0.2, and such as current speed limit is x kilometer/hour, speed of a motor vehicle y kilometer/hour, then danger coefficient is (y-x)/5*0.2.Be no more than 5 kilometers/hour, by 5 kilometers/hour of calculating.
2. dead weight capacity:
Exceed the often increase by 1000 kilograms appraising and deciding core dead weight capacity, danger coefficient increases progressively 0.1, and such as load weight is 15000kg, actual load-carrying be 18000kg then danger coefficient be: (18000-15000)/100*0.1.Overweight less than 1000 kilograms by 1000 kilograms of calculating.
3. surface friction coefficient:
First the friction factor of vehicle running region at that time under weather condition is calculated according to weather interface, friction factor rank is gone out according to calculation of friction coefficient, from 2 grades, each rank danger coefficient increases by 0.1, the rank x of such as friction factor, its danger coefficient account form is: (x-1) * 0.1
Calculation of friction coefficient mode:
4. driver's driving age:
Driving age there is not increase danger coefficient minimizing 0.01 in 1 year to be 0.1 to the maximum, and the such as driving age is x danger coefficient (10-x) * 0.1.Less than 1 year by 0 year calculate, the driving age be greater than 10 years then danger coefficient ignore.
5. vehicle condition:
Car often to increase by 1 year danger coefficient age and increases by 0.02, and such as car age is x, and its danger coefficient account form is: x*0.02.Car calculated by 1 year less than 1 year age.
In addition: above strictly all rules is greater than the situation of 5 kilometers/hour for speed, if the speed of a motor vehicle is less than 5 kilometers/hour, then danger coefficient is 0.
According to rule above, COMPREHENSIVE CALCULATING goes out vehicle risk coefficient summation, arranges warning level by mode below:
Danger coefficient is divided into several scope below, corresponding different warning levels:
| Danger coefficient | Alert levels |
| ＜0.8 | Alarm free |
| 0.8-1.0 | 3 grades of warnings |
| 1.0-1.2 | 2 grades of warnings |
| ＞1.2 | 1 grade of warning |
For the some shortcomings part of current warning system, the present invention is mainly conceived to as " customization " early warning rule, and be such as the speed of a motor vehicle 80 kilometers/hour equally, the danger coefficient that fully loaded vehicle will occur than empty-car accident will be high.
Therefore, the static data of collection vehicle and the factor of the aspect such as dynamic data and binding time, space, weather can be passed through, calculate vehicle danger coefficient within the next time period in real time, and according to the scope at danger coefficient place, send the early warning information of different stage to car owner and driver.Driver and car owner also can subscribe to early warning information and the alarm mode of different stage according to the wish of oneself, high level early warning does not subscribe to restriction by driver, can force to push.
The above; it is only preferred embodiment of the present invention; not any pro forma restriction is done to the present invention, every above embodiment is done according to technical spirit of the present invention any simple modification, equivalent variations and modification, all still belong to the protection domain of technical solution of the present invention.
Claims (7)
1. a vehicle early warning method, is characterized in that: the method performs in the disposal system on the car machine terminal be installed on vehicle and backstage, and comprises the following steps:
(1) take out the index of needs concern according to the factor being related to driving safety, and be the corresponding weighted value of each setup measures;
(2) gather vehicle data, vehicle data comprises static data, vehicle travels dynamic data, spatial data, driver information;
(3), after receiving the vehicle data that step (2) gathers, calculate the risk factor of each index according to the weighted value of each index and corresponding vehicle data, finally the risk factor of cumulative all indexs, draws overall risk coefficient;
(4) judge whether overall risk coefficient reaches specified scope, if it is perform step (5), otherwise perform step (2);
(5) early warning information is sent to vehicle.
2. vehicle early warning method according to claim 1, is characterized in that: static data comprises vehicle model, vehicle brand, vehicle dimension, the highest design speed per hour, own wt, dead weight, accurate traction gross mass, tire quantity and specification, year of manufacture and the time of setting out on a journey, distance travelled, vitals maintenance history, history accident information in described step (2).
3. vehicle early warning method according to claim 2, is characterized in that: in described step (2) vehicle travel that dynamic data comprises travel speed, gross mass, acceleration change situation, tire pressure, water temperature, vehicle travel duration continuously, whether there is fatigue driving, cockpit image, acoustic information.
4. vehicle early warning method according to claim 3, is characterized in that: described step (2) spatial data comprises the history accident conditions in visibility, humidity, temperature, the speed limit of road, place road traffic, the track quantity of place road, current longitude and latitude 3 kilometer range.
5. vehicle early warning method according to claim 4, is characterized in that: in described step (2), driver information comprises birthday, sex, driving age, history, history accident, blood group, eyesight and hearing loss violating the regulations.
6. vehicle early warning method according to claim 5, is characterized in that: when described step (2) gathers, and static data inputs vehicle model Code obtaining by car owner in car machine terminal; Vehicle is travelled dynamic data and is gathered by car machine terminal; Spatial data is obtained by the relevant interface of Chinese weather network interface and Traffic Administration Bureau; Driver information is inputted by car owner and obtains.
7. vehicle early warning method according to claim 1, is characterized in that: described weighted value is 0.01-1.
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| CN201410831737.8A CN104575063A (en) | 2014-12-26 | 2014-12-26 | Pre-warning method for vehicle |
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Cited By (27)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104882017A (en) * | 2015-05-05 | 2015-09-02 | 惠州Tcl移动通信有限公司 | Safe driving method and system based on mobile terminal |
| CN105225525A (en) * | 2015-09-23 | 2016-01-06 | 宇龙计算机通信科技(深圳)有限公司 | Information processing method, signal conditioning package and server |
| CN105225509A (en) * | 2015-10-28 | 2016-01-06 | 努比亚技术有限公司 | A kind of road vehicle intelligent early-warning method, device and mobile terminal |
| CN105405306A (en) * | 2015-12-24 | 2016-03-16 | 小米科技有限责任公司 | Vehicle alarm method and device |
| CN105522984A (en) * | 2016-01-20 | 2016-04-27 | 太仓红码软件技术有限公司 | Method for acquiring target vehicle driver level during driving |
| CN106101641A (en) * | 2016-07-18 | 2016-11-09 | 中国科学院地理科学与资源研究所 | Video frequency monitoring system and monitoring method thereof |
| CN106205054A (en) * | 2016-09-13 | 2016-12-07 | 深圳市几米软件有限公司 | Safe driving intelligent early-warning method, mobile unit and server |
| CN106504367A (en) * | 2016-11-02 | 2017-03-15 | 中车青岛四方机车车辆股份有限公司 | Vehicle trouble method for early warning and device |
| CN106780049A (en) * | 2016-12-06 | 2017-05-31 | 北京中交兴路信息科技有限公司 | A kind of vehicle finance credit method and device |
| CN107316458A (en) * | 2017-06-22 | 2017-11-03 | 南京理工大学 | Safety monitoring node and system based on car networking |
| CN107507455A (en) * | 2017-08-14 | 2017-12-22 | 苏州马尔萨斯文化传媒有限公司 | A kind of advertisement board on highway for monitoring traffic route driving risk |
| CN107730656A (en) * | 2017-09-29 | 2018-02-23 | 深圳市轱辘车联数据技术有限公司 | A kind of method and mobile unit of registration of vehicle oiling behavioral data |
| CN107818658A (en) * | 2017-10-24 | 2018-03-20 | 罗燕 | Car steering indicating risk method and its device |
| CN107867130A (en) * | 2017-11-08 | 2018-04-03 | 深圳市招科智控科技有限公司 | A kind of harbour container is carried unmanned vehicle and blown out risk checking method and system |
| CN107909839A (en) * | 2017-11-21 | 2018-04-13 | 北京华油信通科技有限公司 | Vehicle safety processing method and processing device |
| CN109754153A (en) * | 2018-11-23 | 2019-05-14 | 北京交通大学 | A kind of driver violation disaster risk estimation method based on duration model |
| CN110310485A (en) * | 2019-04-11 | 2019-10-08 | 泰州市朗嘉尚网络科技有限公司 | Peripheral information acquires display system |
| CN110622227A (en) * | 2017-05-15 | 2019-12-27 | 量子门股份公司 | Traffic prediction system |
| CN110648532A (en) * | 2019-09-22 | 2020-01-03 | 江苏顺泰交通集团有限公司 | Traffic monitoring system based on wisdom traffic thing networking |
| CN111332313A (en) * | 2020-02-24 | 2020-06-26 | 重庆众鸿科技有限公司 | Vehicle driving safety early warning control method and system |
| CN111382883A (en) * | 2018-12-29 | 2020-07-07 | 北京嘀嘀无限科技发展有限公司 | Network appointment vehicle order-receiving authority control method, device and equipment |
| CN111516681A (en) * | 2020-05-12 | 2020-08-11 | 广东工贸职业技术学院 | High-speed driving safety early warning method and system for automobile based on inner wheel difference |
| CN111516705A (en) * | 2020-05-12 | 2020-08-11 | 广东工贸职业技术学院 | Automobile high-speed driving safety early warning method and system based on tire working conditions |
| CN112498021A (en) * | 2020-12-11 | 2021-03-16 | 苏州并作汽车电子有限公司 | Method and system for preventing tire burst based on tire pattern depth |
| CN113593075A (en) * | 2020-04-30 | 2021-11-02 | 比亚迪股份有限公司 | Information display method and information display system for test yard |
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2014
- 2014-12-26 CN CN201410831737.8A patent/CN104575063A/en active Pending
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| CN104882017A (en) * | 2015-05-05 | 2015-09-02 | 惠州Tcl移动通信有限公司 | Safe driving method and system based on mobile terminal |
| CN105225525A (en) * | 2015-09-23 | 2016-01-06 | 宇龙计算机通信科技(深圳)有限公司 | Information processing method, signal conditioning package and server |
| CN105225509A (en) * | 2015-10-28 | 2016-01-06 | 努比亚技术有限公司 | A kind of road vehicle intelligent early-warning method, device and mobile terminal |
| CN105405306A (en) * | 2015-12-24 | 2016-03-16 | 小米科技有限责任公司 | Vehicle alarm method and device |
| CN105522984A (en) * | 2016-01-20 | 2016-04-27 | 太仓红码软件技术有限公司 | Method for acquiring target vehicle driver level during driving |
| CN106101641B (en) * | 2016-07-18 | 2022-06-14 | 中国科学院地理科学与资源研究所 | Video monitoring system and monitoring method thereof |
| CN106101641A (en) * | 2016-07-18 | 2016-11-09 | 中国科学院地理科学与资源研究所 | Video frequency monitoring system and monitoring method thereof |
| CN106205054A (en) * | 2016-09-13 | 2016-12-07 | 深圳市几米软件有限公司 | Safe driving intelligent early-warning method, mobile unit and server |
| CN106504367A (en) * | 2016-11-02 | 2017-03-15 | 中车青岛四方机车车辆股份有限公司 | Vehicle trouble method for early warning and device |
| CN106780049A (en) * | 2016-12-06 | 2017-05-31 | 北京中交兴路信息科技有限公司 | A kind of vehicle finance credit method and device |
| CN106780049B (en) * | 2016-12-06 | 2020-12-04 | 北京中交兴路信息科技有限公司 | Vehicle financial credit granting method and device |
| CN110622227A (en) * | 2017-05-15 | 2019-12-27 | 量子门股份公司 | Traffic prediction system |
| CN107316458A (en) * | 2017-06-22 | 2017-11-03 | 南京理工大学 | Safety monitoring node and system based on car networking |
| CN107507455A (en) * | 2017-08-14 | 2017-12-22 | 苏州马尔萨斯文化传媒有限公司 | A kind of advertisement board on highway for monitoring traffic route driving risk |
| CN107507455B (en) * | 2017-08-14 | 2021-07-09 | 陕西专壹知识产权运营有限公司 | Highway billboard for monitoring traffic road driving risk |
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| CN107818658A (en) * | 2017-10-24 | 2018-03-20 | 罗燕 | Car steering indicating risk method and its device |
| CN107867130A (en) * | 2017-11-08 | 2018-04-03 | 深圳市招科智控科技有限公司 | A kind of harbour container is carried unmanned vehicle and blown out risk checking method and system |
| CN107909839A (en) * | 2017-11-21 | 2018-04-13 | 北京华油信通科技有限公司 | Vehicle safety processing method and processing device |
| CN109754153A (en) * | 2018-11-23 | 2019-05-14 | 北京交通大学 | A kind of driver violation disaster risk estimation method based on duration model |
| CN111382883A (en) * | 2018-12-29 | 2020-07-07 | 北京嘀嘀无限科技发展有限公司 | Network appointment vehicle order-receiving authority control method, device and equipment |
| CN110310485A (en) * | 2019-04-11 | 2019-10-08 | 泰州市朗嘉尚网络科技有限公司 | Peripheral information acquires display system |
| CN110310485B (en) * | 2019-04-11 | 2020-09-01 | 安徽极玩云科技有限公司 | Surrounding information acquisition and display system |
| CN110648532A (en) * | 2019-09-22 | 2020-01-03 | 江苏顺泰交通集团有限公司 | Traffic monitoring system based on wisdom traffic thing networking |
| CN111332313A (en) * | 2020-02-24 | 2020-06-26 | 重庆众鸿科技有限公司 | Vehicle driving safety early warning control method and system |
| CN113593075A (en) * | 2020-04-30 | 2021-11-02 | 比亚迪股份有限公司 | Information display method and information display system for test yard |
| CN111516705A (en) * | 2020-05-12 | 2020-08-11 | 广东工贸职业技术学院 | Automobile high-speed driving safety early warning method and system based on tire working conditions |
| CN111516681A (en) * | 2020-05-12 | 2020-08-11 | 广东工贸职业技术学院 | High-speed driving safety early warning method and system for automobile based on inner wheel difference |
| CN111516705B (en) * | 2020-05-12 | 2021-03-26 | 广东工贸职业技术学院 | Automobile high-speed driving safety early warning method and system based on tire working conditions |
| CN111516681B (en) * | 2020-05-12 | 2021-03-26 | 广东工贸职业技术学院 | High-speed driving safety early warning method and system for automobile based on inner wheel difference |
| CN112498021A (en) * | 2020-12-11 | 2021-03-16 | 苏州并作汽车电子有限公司 | Method and system for preventing tire burst based on tire pattern depth |
| CN113642893A (en) * | 2021-08-16 | 2021-11-12 | 公安部交通管理科学研究所 | New energy automobile operation risk assessment method |
| CN116959261A (en) * | 2023-09-20 | 2023-10-27 | 武汉车凌智联科技有限公司 | Vehicle safety driving monitoring and early warning system based on cloud platform |
| CN116959261B (en) * | 2023-09-20 | 2023-12-15 | 武汉车凌智联科技有限公司 | Vehicle safety driving monitoring and early warning system based on cloud platform |
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Application publication date: 20150429 |