CN104269070A - Active vehicle safety pre-warning method and safety pre-warning system with same applied - Google Patents

Abstract

The invention relates to the technical field of active vehicle safety control and the mobile internet, in particular to an active vehicle safety pre-warning method and a safety pre-warning system with the active vehicle safety pre-warning method applied. The safety pre-warning system comprises a mobile intelligent terminal, a wireless communication network and a satellite positioning system. The active vehicle safety pre-warning method includes the steps that a data preprocessing module, a line tracing and estimating module and a danger pre-warning module are installed on the mobile intelligent terminal, an own vehicle can judge whether a collision risk exists or not according to information of pedestrians and other vehicles within a target range, and a safety alarm is given if necessary. By ingenious utilization of popular smart phones, low-cost vehicles and pedestrians can enjoy protection of the active safety technology, individual privacy will not be leaked, and the active vehicle safety pre-warning method and the safety pre-warning system with the active vehicle safety pre-warning method applied are highly popular, low in cost and likely to be accepted by public.

Description

The safety pre-warning system of a kind of vehicle active safety method for early warning and utilization the method

Technical field

The present invention relates to vehicle active safety control and mobile interchange technical field, particularly relate to the safety pre-warning system of a kind of vehicle active safety method for early warning and utilization the method.

Background technology

Vehicle active safety control system can realize vehicle collision prewarning and the intervention to driver behavior, and driving variable is obtained more safely with light.In recent years, the research temperature of this technical field constantly heats up, active safety control system based on radar, first-class environment detection sensor of making a video recording is as ripe in ACC (adaptive cruise), EBA (brake hard is assisted), LKA (track keeps auxiliary) etc., and constantly optimised.As Korean Patent KR2007023392A (ADAPTIVE CRUISE CONTROL SYSTEM AND METHOD CONSIDERING DRIVING ENVIRONMENT, CAPABLE OF AUTOMATICALLY CONTROLLING AN INTER-CAR DISTANCE ESPECIALLY WHEN IT IS RAINY OR DARK) describe and utilize the existing ACC system of rain sensor, nighttime driving sensor optimization, make vehicle have better environment sensing function, thus realize active safety control more exactly.

But present stage also far can not realize the road active safety in complete meaning.First, trailer-mounted radar and camera are mainly used in the vehicle detecting fore-and-aft direction, comparatively far away for left and right directions, or the barrier in the dead range of Driver Vision, or the high-speed small-size motor vehicles having barrier to block, and cannot propose alarm in advance.Secondly, active safety control system price is expensive, is only applied at present in high-level vehicle, for the normal domestic use car that road vehicle accounting is maximum, also cannot realizes this function.3rd, the pedestrian on micro-car, motorcycle and road cannot enjoy the safety and comfort that active safety technologies brings especially.

Along with the rise of car networking concepts, based on interconnected new technology---V2V, namely Vehicle-to-Vehicle (also referred to as Car-to-Car) is also suggested.So-called V2V, is namely the message-switching technique realizing between vehicle by equipment such as onboard sensors, when colliding, reminds driver in time, the generation avoided traffic accident.Car industry bound pair has been placed on vehicular component in the principal focal point of V2V technology.But although these relevant vehicular components have been made significant headway technically, except V2V technology itself, the popularity of technology has also been very important factor, if can not popularize, then can not play predictive role at all.

Along with the fast development of mobile interchange technology, there is deep change in the nowadays life of people.Now, almost everyone can carry with a smart mobile phone, various application software has been installed, people can know oneself geographic position at any time, airmanship can be utilized to arrive destination smoothly, and smart mobile phone can externally send geographic location information by global position system and not leak privacy (if do not sent the personal information such as cell-phone number).

Summary of the invention

The object of the present invention is to provide the safety pre-warning system of a kind of vehicle active safety method for early warning and utilization the method.It utilizes extensively universal smart mobile phone externally to send the smart mobile phone holder position information of global position system location, and by being arranged on software on the mobile intelligent terminals such as smart mobile phone oneself and other people positional information carried out to the computational prediction of velocity location, and having risk of collision alarm, there is the function of active safety early warning, and can extensively popularize.

For active safety method for early warning of the present invention, above-mentioned technical matters solves like this:

Based on a vehicle active safety method for early warning for mobile intelligent terminal positional information, comprise the steps:

(1) in car target zone, the mobile intelligent terminal of moving target is sent in the data preprocessing module of car mobile intelligent terminal by their position data that global position system is located by cordless communication network;

(2) data preprocessing module on car mobile intelligent terminal calculates operating range from each moment of car and travel speed according to car's location in good time, calculate operating range and the travel speed in each moment of moving target according to the position of moving target in target zone in good time, and the data of moving target in car and target zone drawn be transferred to trajectory track on car mobile intelligent terminal and estimate module;

(3) trajectory track on car mobile intelligent terminal and estimate module according to front several moment car's location, velocity information, estimate from the position of car subsequent time, speed and direction of motion, the position of moving target in subsequent time target zone, speed and direction of motion is estimated according to the position of moving target in front several moment target zone, velocity information, and by the data information transfer of moving target in car and target zone that draws to the danger early warning module on car mobile intelligent terminal;

(4) the danger early warning module on car mobile intelligent terminal has judged whether risk of collision according to the position of moving target in car's location, speed and direction of motion and target zone, speed and direction of motion, and sends hydropac when being judged as risk of collision.

Further, target zone is take radius centered by car as the border circular areas of 250 meters in described step (1).

Data preprocessing module in described step (2) on car mobile intelligent terminal detect among a small circle have intensive multimachine with identical speed, equidirectional run time, then by this object judgement be intensive multimachine in groups.

Described data preprocessing module on car mobile intelligent terminal when carrying out intensive multimachine and judging in groups, using the line direction of a moment and current time position on moving target in target zone as velocity reversal.

His the machine distribution range run with identical speed, equidirectional when being judged as that intensive multimachine is in groups not more than radius for 6m ²border circular areas.

In described step (2) when data preprocessing module judge his machine be intensive multimachine in groups time, being standard from car local coordinate, by from being that bounding box draws rectangle frame line from car his machine farthest, and using rectangle frame line from from the nearest angle of car as risk object point.

In described step (2), in car or target zone, the speed calculation method of moving target is: the positional information first calling current time t and previous moment t-1 from the storage chip of mobile intelligent terminal, then according to the terrestrial coordinate (x in these two moment _t, y _t), (x _t-1, y _t-1) by 2 range formulas calculate 2 distance D (t), then calculate current time velocity magnitude V (t) according to speed computing formula V (t)=D (t)/Δ t, wherein Δ t is the system-computed cycle.

Current time speed V (t) that in described step (2), moving target goes out according to speed calculating formulae discovery in car or target zone need carry out filtering process by low-pass filtering, and then using the speed V'(t after low-pass filtering treatment) as the velocity magnitude of current time, and the trajectory track be input on car mobile intelligent terminal goes with estimating in module, described low-pass filtering algorithmic formula is: V'(t)=a ₀v (t)+a ₁v (t-1)+a ₂v (t-2)+b ₁v'(t-1)+b ₂v'(t-2), wherein: a ₀, a ₁, a ₂, b ₁, b ₂for filter constant.

In described step (3), in car or target zone, the position of moving target subsequent time is estimated by least square trajectory predictions algorithm.

The calculating process of described least square trajectory predictions algorithm is: call the position data from current time k moment measured object forward, and the track that this k is put is assumed straight line, show that the x coordinate of subsequent time measured object and the expression formula of y coordinate are respectively: x=a'+b't, y=a "+b " t, the minimum a' of k moment tracing point predictor error of sening as an envoy to is calculated by least square trajectory predictions algorithm, b', a ", b " value, thus draw subsequent time estimate position, wherein a', b', a ", b " be respectively by the computing formula of least square trajectory predictions algorithm:

$a^{\′}=\frac{\underset{i=1}{\overset{k}{\mathrm{\Σ}}}{t}_i^2\underset{i=1}{\overset{k}{\mathrm{\Σ}}}{x}_i-\underset{i=1}{\overset{k}{\mathrm{\Σ}}}{t}_i\underset{i=1}{\overset{k}{\mathrm{\Σ}}}{x}_i{t}_i}{k\underset{i=1}{\overset{k}{\mathrm{\Σ}}}{t}_i^2-{\left(\underset{i=1}{\overset{k}{\mathrm{\Σ}}}{t}_i\right)}^2},$ $b^{\′}=\frac{\underset{i=1}{\overset{k}{\mathrm{\Σ}}}{t}_i\underset{i=1}{\overset{k}{\mathrm{\Σ}}}{x}_i-k\underset{i=1}{\overset{k}{\mathrm{\Σ}}}{x}_i{t}_i}{k\underset{i=1}{\overset{k}{\mathrm{\Σ}}}{t}_i^2-{\left(\underset{i=1}{\overset{k}{\mathrm{\Σ}}}{t}_i\right)}^2},$

$a^{\′\′}=\frac{\underset{i=1}{\overset{k}{\mathrm{\Σ}}}{t}_i^2\underset{i=1}{\overset{k}{\mathrm{\Σ}}}{y}_i-\underset{i=1}{\overset{k}{\mathrm{\Σ}}}{t}_i\underset{i=1}{\overset{k}{\mathrm{\Σ}}}{y}_i{t}_i}{k\underset{i=1}{\overset{k}{\mathrm{\Σ}}}{t}_i^2-{\left(\underset{i=1}{\overset{k}{\mathrm{\Σ}}}{t}_i\right)}^2},$ $b^{\′\′}=\frac{\underset{i=1}{\overset{k}{\mathrm{\Σ}}}{t}_i\underset{i=1}{\overset{k}{\mathrm{\Σ}}}{y}_i-k\underset{i=1}{\overset{k}{\mathrm{\Σ}}}{y}_i{t}_i}{k\underset{i=1}{\overset{k}{\mathrm{\Σ}}}{t}_i^2-{\left(\underset{i=1}{\overset{k}{\mathrm{\Σ}}}{t}_i\right)}^2}.$

Wherein, t _ifor the time interval in i-th moment apart from initial calculation moment forward, t+1 is the time interval of subsequent time apart from initial calculation point, x _i, y _ifor the actual coordinate of i-th moment measured object forward.

In described step (3), in car or target zone, the velocity magnitude of moving target subsequent time is the current time velocity magnitude V'(t after low-pass filtering treatment).

In described step (3), in car or target zone, the velocity reversal of moving target subsequent time is the rectilinear direction using least square model.

The judgment mode of risk of collision is in described step (4): go out the point of impingement according to the velocity information of subsequent time moving target in the velocity information of car and position and target zone and position calculation, if the running time from the point of impingement is less than the hydropac time, then dangerous working condition is put zone bit 1, carry out repeatedly dangerous working condition within the danger early warning module short time to judge, if dangerous working condition zone bit puts 1 continuous 5 times, then send hydropac.

For safety pre-warning system of the present invention, above-mentioned technical matters solves like this:

Comprise mobile intelligent terminal, for externally sending from truck position information, moving target position information within the scope of receiving target also carries out velocity arithmetic, trace predicating and danger warning to moving target position in target zone;

Cordless communication network, for the mutual transmission of moving target position in car and target zone;

Global position system, for determining mobile intelligent terminal position.

Further, described mobile intelligent terminal is one or more in smart mobile phone, on-vehicle information harvester T-Box, panel computer, notebook computer.

The invention has the beneficial effects as follows: the present invention is based on the extensively universal smart mobile phone that externally can send geographical location information, and by installation data pretreatment module, trajectory track and estimate module, these three softwares of danger early warning module on the mobile intelligent terminals such as smart mobile phone, enable to make according to the pedestrian in target zone and his car information the judgement whether having risk of collision from car, and send safety alarm where necessary.By the utilization dexterously to generally universal smart mobile phone, enable low cost vehicle and pedestrian enjoy the protection of active safety technologies, do not leak individual privacy again, popularization degree is high, and cost is low, easily accepted by the public.

Accompanying drawing explanation

Fig. 1 is that the present invention controls main flow chart;

Fig. 2 is data preprocessing module processing flow chart;

Fig. 3 is trajectory track and estimates resume module process flow diagram;

Fig. 4 is danger early warning resume module process flow diagram;

Fig. 5 is intensive multimachine schematic diagram in groups;

Fig. 6 be trajectory track and prediction from truck position information schematic diagram;

Fig. 7 is risk of collision point prediction schematic diagram;

In figure: 1-data preprocessing module, 2-trajectory track and estimate module, 3-danger early warning module.

Embodiment

In order to make object of the present invention, technical scheme and advantage clearly understand, below in conjunction with drawings and Examples, the present invention is further elaborated.Specific embodiment described herein only in order to explain the present invention, is not intended to limit the present invention.In addition, if below in described each embodiment of the present invention involved technical characteristic do not form conflict each other and just can mutually combine.

Active safety early warning system of the present invention comprises mobile intelligent terminal, cordless communication network and global position system.Mobile intelligent terminal is smart mobile phone, panel computer, on-vehicle information harvester (T-Box), notebook computer etc. have user friendly operation interface, and can install the intelligent carrier of software required for the present invention.All location, position is carried out by global position system from car and Ta Che or other people mobile intelligent terminal, and the geographical location information of oneself is externally sent by cordless communication network, simultaneously do not reveal the individual privacies such as the cell-phone number of oneself, be i.e. externally can send the positional information of oneself between the mobile intelligent terminal of Pedestrians and vehicles simultaneously and accept other people geographical location information.These mobile intelligent terminals are gone back Matching installation data preprocessing module 1, trajectory track and estimates module 2 and these active safety early warning softwares of danger early warning module 3.From the mobile intelligent terminal of car after receiving other people geographical location information, by data preprocessing module 1 mounted thereto, trajectory track and the process estimating module 2 and danger early warning module 3, and the cartographic information by matching, on the display screen from car mobile intelligent terminal, in real time display is from the position of machine and his machine and movement locus.

Suppose that certain vehicle travels on road, driver A has run software of the present invention in smart mobile phone, and active safety early warning enters starting state.As shown in Figure 1, data preprocessing module 1 in driver's smart mobile phone starts the positional information receiving his machine within the scope of circumference 250m, and distribute unique interim No. ID to each his machine entered in monitoring range, in the data bit of the positional information that his machine produces stored in the corresponding ID of smart mobile phone storage chip.When his machine shifts out monitoring range, corresponding No. ID and the positional information that stores are removed automatically.Data preprocessing module 1 first call smart mobile phone storage chip in each ID object at current time and previous moment (t-1, t) position, calculate the velocity magnitude of moving target and his machines all in machine and target zone respectively, because oneself process with information such as the speed of his machine in several module, positions is the same with account form, for convenience later all to be described from machine.

(x is respectively at the terrestrial coordinate in two moment of t-1 and t from machine _t, y _t) and (x _t-1, y _t-1), then by 2 range formulas the distance D (t) travelled to current t from car from the t-1 moment can be calculated, calculate current time velocity magnitude V (t) according to speed computing formula V (t)=D (t)/Δ t again, wherein Δ t is the system-computed cycle.Vehicle speed data is avoid larger fluctuation, can eliminate curve peak valley by application of low-pass algorithm, and make speed curves more level and smooth, low-pass filtering algorithmic formula is:

V'(t)＝a ₀V(t)+a ₁V(t-1)+a ₂V(t-2)+b ₁V'(t-1)+b ₂V'(t-2)，

Wherein: a ₀, a ₁, a ₂, b ₁, b ₂for filter constant, and the computing formula of this series of filter constant is as follows:

ω _d＝2π·1.25·CutOff_Frq

${\mathrm{\ω}}_a=\frac{{\sin \mathrm{\ω}}_d\frac{T}{2}}{{\cos \mathrm{\ω}}_d\frac{T}{2}}$

$a_0=\frac{{{\mathrm{\ω}}_a}^2}{1+\sqrt{2}{\mathrm{\ω}}_a+{{\mathrm{\ω}}_a}^2}$

a ₁＝2a ₀

a ₂＝a ₀

$b_1=\frac{-2({{\mathrm{\ω}}_a}^2-1)}{1+\sqrt{2}{\mathrm{\ω}}_a+{{\mathrm{\ω}}_a}^2}$

$b_2=\frac{-1+\sqrt{2}{\mathrm{\ω}}_a-{{\mathrm{\ω}}_a}^2}{1+\sqrt{2}{\mathrm{\ω}}_a+{{\mathrm{\ω}}_a}^2}$

Wherein CutOff_Frq is the cutoff frequency of filtering, and acquiescence value is 5, and concrete value can adjust according to the concrete fluctuation of speed curves.

V (t) is the speed without low-pass filtering treatment, and data preprocessing module 1 is using the speed V'(t after low-pass filtering treatment) as the velocity magnitude of current time, and the trajectory track be input on car mobile intelligent terminal and estimating in module 2 goes.Carry out calculating according to the moment in system-computed cycle to the operating range of moving target in car and target zone and travel speed in data preprocessing module 1 in good time.And his secret collection multimachine judgement in groups also can be carried out when carrying out this series of computation.

As shown in Figure 5, in data preprocessing module 1, movement direction decision is the line direction, position (velocity reversal here judges just to use in intensive multimachine judges in groups, also can rejudge at trajectory track and estimating in module) of current time and previous moment.If synchronization, calculate four his machines that ID is numbered 5,6,7,8 and be not more than 6m ²scope in identical speed, equidirectional run.Now, native system judges that four his machines that ID is numbered 5,6,7,8 are a grouping, is intensive multimachine in groups, and gives this grouping ID numbering 5*6*7*8=1680, deletes ID simultaneously and is numbered 6,7,8 three his machine datas.Meanwhile, being standard from car local coordinate, by from being that bounding box draws rectangular wire frame from machine his machine farthest, and using rectangular wire frame from from the nearest angle of machine as risk object point, the movement velocity of grouping is consistent with his machine that ID is numbered 5 with direction of motion.

As shown in Figure 3, trajectory track and estimate the current time speed V'(t crossed through low-pass filtering treatment that data preprocessing module 1 inputs by module 2) as the subsequent time velocity information of the prediction from car, the estimation of subsequent time car's location is then predicted by least square trajectory predictions algorithm.Trajectory track and estimate the positional information that module 2 calls k (k<=10) the individual moment before car in smart mobile phone storage chip, calculated rate due to native system is more than 10Hz, before the movement locus in k moment can work as in alignment, then can according to formula x for the x (t+1) of subsequent time position and y (t+1) coordinate _(t+1)=a'+b'(t+1), y _(t+1)=a "+b " (t+1) draws.Because in fact movement locus can not be straight line, therefore error can be there is, and the error formula of x coordinate and y coordinate is respectively: ε _i'=x _i-a'-b't _i, ε _i"=y _i-a "-b " t _i, the variance of position on x and y coordinate of k point is respectively: $E^{\&prime;}=\underset{i=1}{\overset{k}{\mathrm{\&Sigma;}}}{(x_i-a^{\&prime;}-b^{\&prime;}{t}_i)}^2,$ $E^{\&prime;\&prime;}=\underset{i=1}{\overset{k}{\mathrm{\&Sigma;}}}{(y_i-a^{\&prime;\&prime;}-b^{\&prime;\&prime;}{t}_i)}^2,$ For making error minimum, needing to carry out partial differential to a', b', a ", b ", finally showing that the expression formula of a', b', a when error is minimum ", b " is respectively:

$a^{\&prime;}=\frac{\underset{i=1}{\overset{k}{\mathrm{\&Sigma;}}}{t}_i^2\underset{i=1}{\overset{k}{\mathrm{\&Sigma;}}}{x}_i-\underset{i=1}{\overset{k}{\mathrm{\&Sigma;}}}{t}_i\underset{i=1}{\overset{k}{\mathrm{\&Sigma;}}}{x}_i{t}_i}{k\underset{i=1}{\overset{k}{\mathrm{\&Sigma;}}}{t}_i^2-{\left(\underset{i=1}{\overset{k}{\mathrm{\&Sigma;}}}{t}_i\right)}^2},$ $b^{\&prime;}=\frac{\underset{i=1}{\overset{k}{\mathrm{\&Sigma;}}}{t}_i\underset{i=1}{\overset{k}{\mathrm{\&Sigma;}}}{x}_i-k\underset{i=1}{\overset{k}{\mathrm{\&Sigma;}}}{x}_i{t}_i}{k\underset{i=1}{\overset{k}{\mathrm{\&Sigma;}}}{t}_i^2-{\left(\underset{i=1}{\overset{k}{\mathrm{\&Sigma;}}}{t}_i\right)}^2},$

$a^{\&prime;\&prime;}=\frac{\underset{i=1}{\overset{k}{\mathrm{\&Sigma;}}}{t}_i^2\underset{i=1}{\overset{k}{\mathrm{\&Sigma;}}}{y}_i-\underset{i=1}{\overset{k}{\mathrm{\&Sigma;}}}{t}_i\underset{i=1}{\overset{k}{\mathrm{\&Sigma;}}}{y}_i{t}_i}{k\underset{i=1}{\overset{k}{\mathrm{\&Sigma;}}}{t}_i^2-{\left(\underset{i=1}{\overset{k}{\mathrm{\&Sigma;}}}{t}_i\right)}^2},$ $b^{\&prime;\&prime;}=\frac{\underset{i=1}{\overset{k}{\mathrm{\&Sigma;}}}{t}_i\underset{i=1}{\overset{k}{\mathrm{\&Sigma;}}}{y}_i-k\underset{i=1}{\overset{k}{\mathrm{\&Sigma;}}}{y}_i{t}_i}{k\underset{i=1}{\overset{k}{\mathrm{\&Sigma;}}}{t}_i^2-{\left(\underset{i=1}{\overset{k}{\mathrm{\&Sigma;}}}{t}_i\right)}^2}.$

In formula, t _ifor the time interval in i-th moment apart from initial calculation moment forward, t+1 is the time interval of subsequent time apart from initial calculation point, x _i, y _ifor the actual coordinate of i-th moment measured object forward.

A', b', a ", b " are substituted into formula x respectively _(t+1)=a'+b'(t+1), y _(t+1)in=a "+b " (t+1), thus derive from the position that car goes out subsequent time.The rectilinear direction that subsequent time is then estimated for least square trajectory predictions algorithm from the direction of motion of car.Trajectory track with estimate the subsequent time speed of moving target in target zone in module 2, direction also carries out computing by identical mode with position.Trajectory track and estimate the subsequent time speed of the moving target in car and target zone that module 2 will draw, direction and Position input are in danger early warning module 3.

As shown in Figure 4, danger early warning module 3, according to from the running orbit of car and Ta Che and travelling speed, dopes the location point collided, and when being less than hydropac time 3s from car from the operating range of the point of impingement, is then 1 by dangerous working condition mark position.Such as, danger early warning module 3 according to subsequent time from machine and be numbered 3 his machine positional information and velocity information, calculate at terrestrial coordinate mooring points P (x0, y0) position will collide (as shown in Figure 7), and from machine from Δ t' working time of a P be 2.8s, now, dangerous working condition mark position is 1 and stored in storage chip by danger early warning module 4, and calls the dangerous working condition zone bit in front four moment in storage chip simultaneously.If find, front four moment dangerous working condition zone bits are 1, and now danger early warning module 4 sends hydropac order, and control system sends hydropac.

When the vehicle is stopped, calculating position vehicle velocity signal from machine is 0, and judge that vehicle stops, system is automatically out of service.

Should be understood that, for those of ordinary skills, can be improved according to the above description or convert, and all these improve and convert the protection domain that all should belong to claims of the present invention.

Claims (15)

1. a vehicle active safety method for early warning, is characterized in that, comprises the steps:

(1) in car target zone, the mobile intelligent terminal of moving target is sent in the data preprocessing module of car mobile intelligent terminal by their position that global position system is located by cordless communication network;

(2) data preprocessing module on car mobile intelligent terminal calculates operating range from each moment of car and travel speed according to car's location in good time, calculate operating range and the travel speed in each moment of moving target according to the position of moving target in target zone in good time, and the data of moving target in car and target zone drawn be transferred to trajectory track on car mobile intelligent terminal and estimate module;

(3) trajectory track on car mobile intelligent terminal and estimate module according to front several moment car's location, velocity information, estimate from the position of car subsequent time, speed and direction of motion, the position of moving target in subsequent time target zone, speed and direction of motion is estimated according to the position of moving target in front several moment target zone, velocity information, and by the data information transfer of moving target in car and target zone that draws to the danger early warning module on car mobile intelligent terminal;

(4) the danger early warning module on car mobile intelligent terminal has judged whether risk of collision according to the position of moving target in car's location, speed and direction of motion and target zone, speed and direction of motion, and sends hydropac when being judged as risk of collision.

2. a kind of vehicle active safety method for early warning as claimed in claim 1, is characterized in that: target zone is take radius centered by car as the border circular areas of 250 meters in described step (1).

3. a kind of vehicle active safety method for early warning as claimed in claim 1, it is characterized in that: the data preprocessing module in described step (2) on car mobile intelligent terminal detect among a small circle have intensive multimachine with identical speed, equidirectional run time, then by this object judgement be intensive multimachine in groups.

4. a kind of vehicle active safety method for early warning as claimed in claim 3, it is characterized in that: described data preprocessing module on car mobile intelligent terminal when carrying out intensive multimachine and judging in groups, using the line direction of a moment and current time position on moving target in target zone as velocity reversal.

5. a kind of vehicle active safety method for early warning as claimed in claim 3, is characterized in that: described among a small circle for radius is not more than 6m ²border circular areas.

6. a kind of vehicle active safety method for early warning as claimed in claim 1, it is characterized in that: in described step (2) when data preprocessing module judge his machine be intensive multimachine in groups time, being standard from car local coordinate, by from being that bounding box draws rectangle frame line from car his machine farthest, and using rectangle frame line from from the nearest angle of car as risk object point.

7. a kind of vehicle active safety method for early warning as claimed in claim 1, it is characterized in that: in described step (2), in car or target zone, the speed calculation method of moving target is: the position of first calling current time t and previous moment t-1 from the storage chip of mobile intelligent terminal, then according to the terrestrial coordinate (x of these two moment moving targets in car or target zone _t, y _t), (x _t-1, y _t-1) by 2 range formulas calculate 2 distance D (t), then calculate current time velocity magnitude V (t) according to speed computing formula V (t)=D (t)/Δ t, wherein Δ t is the system-computed cycle.

8. a kind of vehicle active safety method for early warning as claimed in claim 1, is characterized in that: in described step (2), in car or target zone, moving target calculates current time speed V (t) that goes out of formulae discovery by low-pass filtering algorithm: V'(t according to speed)=a ₀v (t)+a ₁v (t-1)+a ₂v (t-2)+b ₁v'(t-1)+b ₂v'(t-2) process, and using the speed V'(t after process) as the velocity magnitude of current time, be input to the trajectory track on car mobile intelligent terminal and estimate in module and go, wherein: a ₀, a ₁, a ₂, b ₁, b ₂for filter constant.

9. a kind of vehicle active safety method for early warning as claimed in claim 1, is characterized in that: in described step (3), in car or target zone, the position of moving target subsequent time is estimated by least square trajectory predictions algorithm.

10. a kind of vehicle active safety method for early warning as claimed in claim 9, it is characterized in that: the calculating process of described least square trajectory predictions algorithm is: call the position data from current time k moment measured object forward, and the track that this k is put is assumed straight line, show that the x coordinate of subsequent time measured object and the expression formula of y coordinate are respectively: x=a'+b't, y=a "+b " t, the minimum a' of k moment tracing point predictor error of sening as an envoy to is calculated by least square trajectory predictions algorithm, b', a ", b " value, thus draw subsequent time estimate position, wherein a', b', a ", b " be respectively by the computing formula of least square trajectory predictions algorithm:

$a^{\&prime;}=\frac{\underset{i=1}{\overset{k}{\mathrm{\&Sigma;}}}{t}_i^2\underset{i=1}{\overset{k}{\mathrm{\&Sigma;}}}{x}_i-\underset{i=1}{\overset{k}{\mathrm{\&Sigma;}}}{t}_i\underset{i=1}{\overset{k}{\mathrm{\&Sigma;}}}{x}_i{t}_i}{k\underset{i=1}{\overset{k}{\mathrm{\&Sigma;}}}{t}_i^2-{\left(\underset{i=1}{\overset{k}{\mathrm{\&Sigma;}}}{t}_i\right)}^2},$ $b^{\&prime;}=\frac{\underset{i=1}{\overset{k}{\mathrm{\&Sigma;}}}{t}_i\underset{i=1}{\overset{k}{\mathrm{\&Sigma;}}}{x}_i-k\underset{i=1}{\overset{k}{\mathrm{\&Sigma;}}}{x}_i{t}_i}{k\underset{i=1}{\overset{k}{\mathrm{\&Sigma;}}}{t}_i^2-{\left(\underset{i=1}{\overset{k}{\mathrm{\&Sigma;}}}{t}_i\right)}^2},$

$a^{\&prime;\&prime;}=\frac{\underset{i=1}{\overset{k}{\mathrm{\&Sigma;}}}{t}_i^2\underset{i=1}{\overset{k}{\mathrm{\&Sigma;}}}{y}_i-\underset{i=1}{\overset{k}{\mathrm{\&Sigma;}}}{t}_i\underset{i=1}{\overset{k}{\mathrm{\&Sigma;}}}{y}_i{t}_i}{k\underset{i=1}{\overset{k}{\mathrm{\&Sigma;}}}{t}_i^2-{\left(\underset{i=1}{\overset{k}{\mathrm{\&Sigma;}}}{t}_i\right)}^2},$ $b^{\&prime;\&prime;}=\frac{\underset{i=1}{\overset{k}{\mathrm{\&Sigma;}}}{t}_i\underset{i=1}{\overset{k}{\mathrm{\&Sigma;}}}{y}_i-k\underset{i=1}{\overset{k}{\mathrm{\&Sigma;}}}{y}_i{t}_i}{k\underset{i=1}{\overset{k}{\mathrm{\&Sigma;}}}{t}_i^2-{\left(\underset{i=1}{\overset{k}{\mathrm{\&Sigma;}}}{t}_i\right)}^2}.$

Wherein, t _ifor the time interval in i-th moment apart from initial calculation moment forward, t+1 is the time interval of subsequent time apart from initial calculation point, x _i, y _ifor the actual coordinate of i-th moment measured object forward.

11. a kind of vehicle active safety method for early warning as claimed in claim 1, is characterized in that: in described step (3) from the velocity magnitude of moving target subsequent time in car or target zone be the current time velocity magnitude V'(t after low-pass filtering algorithm process).

12. a kind of vehicle active safety method for early warning as claimed in claim 1, is characterized in that: in described step (3), in car or target zone, the velocity reversal of moving target subsequent time is the rectilinear direction using least square model.

13. a kind of vehicle active safety method for early warning as claimed in claim 1, it is characterized in that: the judgment mode of risk of collision is in described step (4): go out the point of impingement according to the velocity information of subsequent time moving target in the velocity information of car and position and target zone and position calculation, if the running time from the point of impingement is less than the hydropac time, then by dangerous working condition mark position 1, carry out repeatedly dangerous working condition within the danger early warning module short time to judge, if dangerous working condition zone bit puts 1 continuous 5 times, then send hydropac.

14. 1 kinds of safety pre-warning systems using vehicle active safety method for early warning described in claim 1-13, it is characterized in that: comprise mobile intelligent terminal, for externally sending from truck position information, moving target position information within the scope of receiving target also carries out velocity arithmetic, trace predicating and danger warning to moving target position in target zone;

Cordless communication network, for the mutual transmission of moving target position in car and target zone;

Global position system, for determining mobile intelligent terminal position.

15. active safety early warning systems as claimed in claim 14, is characterized in that: described mobile intelligent terminal is one or more in smart mobile phone, on-vehicle information harvester T-Box, panel computer, notebook computer.