CN104401323A - Rollover warning method and rollover warning device for heavy vehicle - Google Patents

Abstract

The invention belongs to the technical field of vehicle active safety, and particularly provides a rollover warning method and a rollover warning device for a heavy vehicle. The rollover warning method and the rollover warning device are low in cost, are free of influence on heavy vehicle load and mass center height, and can warn impending rollover accidents of the heavy vehicle in the next period of time in advance. The method solves the problem that an existing heavy vehicle rollover warning method can warn a vehicle rollover risk in a static threshold value mode but cannot warn an impending rollover accident to a driver in advance. The rollover warning method adopts a classical Kalman filtering technology to simplify a rollover warning model in a combination mode, the motion state of the heavy vehicle is accurately estimated, and then a TTR algorithm is utilized for predicting the rollover risks in the next period of time. The warning algorithm has better universality, and meanwhile prevents inaccurate or invalid warning caused by the changes such as the load, center-of-gravity position and rotary inertia of the heavy vehicle.

Description

A kind of heavy-duty vehicle rollover method for early warning and device

Technical field

The invention belongs to automobile active safety technical field, particularly relate to the rollover of a kind of heavy-duty vehicle dangerous active safety method for early warning and device in real time.

Background technology

Rollover accident is the most dangerous accident of heavy-duty vehicle, and when rollover accident occurs, nearly all chaufeur all cannot perceive the generation of rollover.According to Univ Michigan-Ann Arbor USA traffic study center (UMTRI) statistics, 2002 to 2006, the rollover accident of the annual all kinds of heavy-duty commercial vehicle of the U.S. on average had 5,200.Die from the number of heavy-duty commercial vehicle rollover accident every year simultaneously, be also increased to 5,537 people of 2006 from 5,314 people of 2002.Vehicle side turning has become the major issue destroying lives and properties and safety traffic.Therefore all the time, the driving safety of heavy-duty vehicle, early warning technology of especially turning on one's side studies a question and enjoys the concern of Chinese scholars.

Comparatively early, a lot of automobile manufacturing enterprise, scientific research institution all conduct in-depth research for vehicle rollover forewarn system in the research starting of the American-European countries such as the U.S., Canada, Germany, Japan in heavy-duty vehicle rollover early warning field.At present, whether early stage rollover forewarn system is generally greater than setting under static steering condition static gates limit value by comparing lateral acceleration or vehicle side inclination angle in real time judges vehicle running state, and can warn chaufeur.These class methods are comparatively simple, but can not the imminent rollover danger of warning in advance chaufeur.Calendar year 2001, Chen and Peng proposes the rollover warning algorithm that a set of use rollover time (Time to Rollover, TTR) predicts, in order to improve the precision of TTR value, this algorithm adopts nerual network technique, but have impact on the real-time of algorithm.

At present, the research of China to vehicle side turning early warning is still in the junior stage, specially for the researches of heavy-duty vehicle rollover early warning technology, Jin You Jilin University, Tsing-Hua University, BJ University of Aeronautics & Astronautics, Harbin Institute of Technology and Nanjing Aero-Space University contour check and correction vehicle side turning early warning technology has done part research.Such as, CN101350137 discloses and judges according to lateral acceleration and rollover acceleration rate threshold the car forewarn system that rollover is dangerous.CN10119658 discloses and carries out truck at curves rollover prior-warning device based on lateral acceleration, but based on static gates limit value (lateral acceleration threshold value), above-mentioned patent all judges that rollover is dangerous, the rollover danger that the method occurred heavy-duty vehicle following a period of time is unpredictable.Meanwhile, because the parameter such as load, center-of-gravity position, rotor inertia of heavy-duty vehicle often changes, cause early warning inaccurate or lost efficacy.Dynamically to turn on one's side early warning in order to heavy-duty vehicle can be realized, need to propose a kind ofly can predict that the dangerous heavy-duty vehicle of following a period of time rollover is dynamically turned on one's side prior-warning device.

Summary of the invention

The object of this invention is to provide a kind of low cost, according to current heavy-duty vehicle state, heavy-duty vehicle rollover method for early warning and the implement device thereof of early warning can be made in advance to vehicle rollover accident.This device calculates in the following 3 second time in real time, and whether heavy-duty vehicle reaches rollover stable threshold, draws rollover pre-warning time TTR value.Determine whether to trigger prior-warning device (buzzer phone and early warning Warning light) according to rollover early warning TTR value, remind chaufeur to slow down and revise dangerous driving in time and handle, thus avoid dangerous generation.

The technical solution used in the present invention is:

A kind of heavy-duty vehicle rollover method for early warning, comprises following calculation procedure:

The first step: heavy-duty vehicle Kalman state estimation;

Second step: heavy-duty vehicle rollover early warning.

As the above-mentioned first step, first obtain current heavy-duty vehicle state of kinematic motion, and according to heavy-duty vehicle state of kinematic motion, estimate vehicle side inclination angle, yaw velocity and side slip angle.Specifically comprise the following steps:

(1) heavy-duty vehicle movement state information is obtained: the speed of a motor vehicle, steering wheel angle, lateral acceleration;

(2) heavy-duty vehicle rollover Early-warning Model is set up;

(3) Kalman filter technology is utilized to estimate vehicle side inclination angle, yaw velocity and side slip angle;

Set up heavy-duty vehicle rollover Early-warning Model step as above, measures the heavy-duty vehicle movable information obtained according to step (1), completing steps (2) is set up heavy-duty vehicle under steady state conditions and to be turned on one's side Early-warning Model; Described heavy-duty vehicle rollover Early-warning Model content, its differential equation of motion, and it is as follows to be converted into state space form:

$\stackrel{\·}{x}=\mathrm{Ax}+B_{\mathrm{\δ}}\mathrm{\δ}$

In formula, the state variable of early warning reference model is $x={\left[\begin{array}{cccc}\mathrm{\β}& \stackrel{\·}{\mathrm{\ψ}}& \stackrel{\·}{\mathrm{\φ}}& \mathrm{\φ}\end{array}\right]}^T$

$A=\left[\begin{array}{cccc}-\frac{\mathrm{\σ}{J}_{\mathrm{xeq}}}{m{J}_{\mathrm{xx}}v}& \frac{\mathrm{\ρ}{J}_{\mathrm{xeq}}}{m{J}_{\mathrm{xx}}{v}^2}-1& -\frac{\mathrm{hc}}{J_{\mathrm{xx}}v}& \frac{h(\mathrm{mgh}-k)}{J_{\mathrm{xx}}v}\\ \frac{\mathrm{\ρ}}{J_{\mathrm{zz}}}& -\frac{\mathrm{\κ}}{J_{\mathrm{zz}}v}& 0& 0\\ -\frac{\mathrm{h\σ}}{J_{\mathrm{xeq}}}& \frac{\mathrm{h\ρ}}{J_{\mathrm{xeq}}v}& -\frac{c}{J_{\mathrm{xeq}}}& \frac{\mathrm{mgh}-k}{J_{\mathrm{xeq}}}\\ 0& 0& 1& 0\end{array}\right]$

$B_{\mathrm{\δ}}={\left[\begin{array}{cccc}\frac{C_v{J}_{\mathrm{xeq}}}{m{J}_{\mathrm{xx}}v}& \frac{C_v{l}_v}{J_{\mathrm{zz}}}& \frac{h{C}_v}{J_{\mathrm{xx}}}& 0\end{array}\right]}^T$

In formula, m is complete vehicle quality; J _xxthe rotor inertia of complete vehicle quality around the longitudinal axis of vehicle body center of gravity; J _xeqthe rotor inertia of complete vehicle quality around roll axis; J _zzthe rotor inertia of complete vehicle quality around Z axis.L _vthat car load center of gravity is longitudinally to the distance of front axle; l _hthat car load center of gravity is longitudinally to the distance of rear axle; a _yit is the lateral acceleration of vehicle; ψ is the course angle of vehicle; the yaw velocity of vehicle; φ is the angle of roll of vehicle; the angle of roll speed of vehicle; V is longitudinal speed of a motor vehicle of vehicle; The cornering stiffness of forward and backward tire is defined as C respectively _vand C _h; Power is the distance that center of gravity arrives roll center; K is suspension roll stiffness; δ is front wheel angle; C is suspension damping coefficient, and β is side slip angle, and σ, ρ and κ are auto model system parameter.

Kalman filter technology is utilized to estimate vehicle side inclination angle, yaw velocity and side slip angle step (3) as above, by the heavy-duty vehicle rollover Early-warning Model measured the heavy-duty vehicle movable information that obtains and step (2) according to step (1) and set up, utilize Kalman filter technology to estimate vehicle side inclination angle, yaw velocity and side slip angle, specific implementation step is as follows:

(1) the state variable setting that vehicle rollover model is initial is defined: and P ₀=eye (4); Kalman filter estimator coefficients sets: measurement noises covariance R=1, procedure activation noise covariance Q=1000 × eye (4), observing matrix H=C.

(2) filter temporal upgrades part

${{\hat{x}}_k}^{-}=G{\hat{x}}_{k-1}+F{\mathrm{\δ}}_{k-1}$

P _k ^-＝GP _k-1G ^T+Q

(3) filter status upgrades part

K _k＝P _k ^-H ^T(HP _k ^-H ^T+R) ^-1

${\hat{x}}_k={{\hat{x}}_k}^{-}+K_k(a_y-H{{\hat{x}}_k}^{-})$

P _k＝(I-K _kH)P _k ^-

In formula, P _kwith represent error covariance; K _kfor Kalman filter gain; G, F and Q are system parameter; I is unit matrix; a _yfor the lateral acceleration measured; δ is system interference.

As above-mentioned second step heavy-duty vehicle rollover early warning, the heavy-duty vehicle set up before utilization rollover Early-warning Model, with the running state of vehicle current time for initial value, according to vehicle rollover rule with T _sstep size computation rollover warning index LTR _d.Write down when this index first time meets rollover condition and calculate step number N, namely can obtain vehicle rollover pre-warning time is TTR=N × T _s.TTR value is less, shows that vehicle rollover risk is higher; If when TTR is 0, show that heavy-duty vehicle is turned on one's side.

Wherein, turn on one's side warning index dynamic load rate of transform LTR _dcomputing formula is as follows:

${\mathrm{LTR}}_d=-\frac{2(c\stackrel{\·}{\mathrm{\φ}}+\mathrm{k\φ})}{\mathrm{mgT}}$

In formula: T is the wheelspan of vehicle, and g is acceleration due to gravity.

The threshold value of heavy-duty vehicle rollover prior-warning device of the present invention is set to 3 seconds, if namely calculated rollover index do not meet rollover condition in 3 seconds, stop calculating, TTR is set to 3, thus avoids endless loop.

Realize a device for method described above, comprise onboard sensor, rollover early warning controller and warning and read out instrument; Movable information for detecting vehicle movable information, and is sent to early warning decision unit by described onboard sensor; Rollover early warning controller receives the vehicle movement information from onboard sensor, and the rollover danger judging program according to setting carries out real time operation, and the rollover of sensed in advance imminent heavy-duty vehicle is dangerous, and above-mentioned result of calculation is sent to read out instrument; The heavy-duty vehicle rollover early warning result received is shown by LED Warning light and buzzer phone by read out instrument, and alerting drivers reduces the speed of a motor vehicle in time and revises dangerous driving operation, thus effectively avoids the generation of heavy-duty vehicle rollover accident.

The invention has the beneficial effects as follows:

The present invention is based on vehicle-mounted lesser amt and the sensor information of kind, Real-time Obtaining heavy-duty vehicle movable information also realizes giving warning in advance of heavy-duty vehicle rollover accident, is significant to minimizing major traffic accidents and property personal casualty loss.Meanwhile, this rollover method for early warning has strong interference immunity, distinguishing feature that cost is low.

In addition, the rollover Early-warning Model set up in the present invention has following characteristics: (1) desired parameters is less, not only can meet Controller gain variations and simplify requirement, and can well describe vehicle dynamic characteristics.(2) vehicle rollover Early-warning Model is built based on state space form, is easy to adopt classical linear control theory and stability control theory.(3) vehicle rollover Early-warning Model is easily understood, and is convenient to transplant in controller micro controller system, and real-time is good.Secondly, the present invention selects the dynamic load rate of transform of heavy-duty vehicle as rollover dynamic threshold, relative to traditional static state rollover early warning threshold value, is not subject to the impact of type of vehicle and construction parameter, possesses better universality.Meanwhile, this rollover method for early warning has very strong anti-interference resistance and robustness.

Accompanying drawing explanation

Fig. 1 is heavy vehicle rollover prior-warning device overall plan;

Fig. 2 is Kalman filter fundamental diagram;

Fig. 3 is TTR rollover warning algorithm structure flow chart;

Detailed description of the invention

In order to understand technical characterstic of the present invention better, below in conjunction with accompanying drawing, the present invention is further described.

As shown in Figure 1, a kind of heavy-duty vehicle rollover method for early warning, comprises the steps:

The first step: heavy-duty vehicle Kalman state estimation;

Obtain vehicle movement information, and according to vehicle movement information, estimate vehicle side declination angle, vehicle side inclination angle , yaw velocity with side slip angle β; Specifically comprise the steps:

1. obtain vehicle movement information;

Adopt the motoring condition of onboard sensor Real-time Collection vehicle, comprising: vehicle front wheel angle δ, lateral acceleration a _ywith longitudinal direction of car speed of a motor vehicle v.

2. set up rollover Early-warning Model;

Heavy-duty vehicle rollover Early-warning Model content, its differential equation of motion, and it is as follows to be converted into state space form:

$\stackrel{\·}{x}=\mathrm{Ax}+B_{\mathrm{\δ}}\mathrm{\δ}$

In formula, the state variable of early warning reference model is $x={\left[\begin{array}{cccc}\mathrm{\β}& \stackrel{\·}{\mathrm{\ψ}}& \stackrel{\·}{\mathrm{\φ}}& \mathrm{\φ}\end{array}\right]}^T$

3. utilize above-mentioned rollover Early-warning Model and Kalman filter technology to estimate vehicle side inclination angle, yaw velocity and side slip angle;

Vehicle-state Kalman filter is structurally divided into the time to upgrade (prediction) part and state updating (correction) two parts.Concrete vehicle-state Kalman filter design procedure is as follows:

(1) the state variable setting that vehicle rollover model is initial is defined: and P ₀=eye (4); Kalman filter estimator coefficients sets: measurement noises covariance R=1, procedure activation noise covariance Q=1000 × eye (4), observing matrix H=C.

(2) filter temporal upgrades part

${{\hat{x}}_k}^{-}=G{\hat{x}}_{k-1}+F{\mathrm{\δ}}_{k-1}$

P _k ^-＝GP _k-1G ^T+Q

(3) filter status upgrades part

K _k＝P _k ^-H ^T(HP _k ^-H ^T+R) ^-1

${\hat{x}}_k={{\hat{x}}_k}^{-}+K_k(\mathrm{Ay}-H{{\hat{x}}_k}^{-})$

P _k＝(I-K _kH)P _k ^-

In formula, P _kwith represent error covariance; K _kfor Kalman filter gain; G, F and Q are system parameter; I is unit matrix; a _yfor the lateral acceleration measured; δ is system interference.

According to above-mentioned calculation procedure, vehicle side declination angle, vehicle side inclination angle accurately can be estimated , yaw velocity with side slip angle β.

Second step: heavy-duty vehicle rollover early warning;

The vehicle movement information recorded according to the first step and Kalman filter estimate vehicle side declination angle, the vehicle side inclination angle of acquisition , yaw velocity with side slip angle β, the rollover of prediction heavy-duty vehicle is dangerous, carries out rollover early warning, specifically comprise the steps: it

(1) rollover warning index LTR is calculated _d

According to the above-mentioned vehicle movement information recorded, rollover warning index dynamic load rate of transform LTR _dcomputing formula is as follows:

${\mathrm{LTR}}_d=-\frac{2(c\stackrel{\·}{\mathrm{\φ}}+\mathrm{k\φ})}{\mathrm{mgT}}$

In formula: T is the wheelspan of vehicle, and g is acceleration due to gravity.

(2) the rollover method for early warning of TTR

With the running state of vehicle current time for initial value, according to vehicle rollover rule with T _sstep size computation rollover warning index LTR _d.Write down when this index first time meets rollover condition and calculate step number N, namely can obtain vehicle rollover pre-warning time is TTR=N × T _s.

The threshold value of heavy-duty vehicle rollover prior-warning device of the present invention is set to 3 seconds, if namely calculated rollover index do not meet rollover condition in 3 seconds, stop calculating, TTR is set to 3, thus avoids endless loop.Therefore, when the rollover pre-warning time obtained is 3 seconds, shows that automobile is not turned on one's side in following 3 seconds danger, then think when being less than threshold value that vehicle exists rollover risk, and make TTR=N × T _s, trigger rollover prior-warning device simultaneously.

Realize a device for said method, comprise onboard sensor, rollover early warning controller and warning and read out instrument.

Movable information for detecting vehicle movable information, and is sent to rollover early warning controller by onboard sensor.Above-mentioned onboard sensor comprises longitudinal car speed sensor, steering wheel angle sensor, lateral acceleration sensor.Wherein, lateral acceleration sensor, for measuring the lateral acceleration of vehicle body, is generally arranged on vehicle centroid position; Steering wheel angle sensor, for measuring steering wheel angle, is generally arranged on bearing circle inside; Longitudinal car speed sensor is used for measuring vehicle longitudinal velocity, is generally arranged on vehicle centroid place, sometimes also can uses this signal of wheel speed sensors indirect calculation.

Rollover early warning controller receives from the vehicle movement information of onboard sensor and Kalman filter estimating vehicle states amount, carries out computing according to setting program, obtains above-mentioned heavy-duty vehicle rollover early warning result, and this result is sent to read out instrument.Early warning controller adopts Intelligent treatment chip as the realization such as micro controller system, DSP, ARM.

The heavy-duty vehicle rollover early warning result display that pre-alarm display device will receive, for chaufeur reference, read out instrument comprises buzzer phone and LED display lamp.

By this method and device for carrying out said thereof, do not increasing on the basis of actuating unit, only need the early warning that less onboard sensor and early warning controller can realize heavy vehicle rollover danger, help chaufeur to take the necessary measures in time under dangerous working condition, reduce the generation of casualty accident.

The foregoing is only the preferred embodiment of the present invention; not thereby the scope of the claims of the present invention is limited; every equivalent structure transformation utilizing specification sheets of the present invention and accompanying drawing content to do; or be directly or indirectly used in other relevant technical fields, be all in like manner included in scope of patent protection of the present invention.

Claims (6)

1. a heavy-duty vehicle rollover method for early warning, comprises following content:

(1) heavy-duty vehicle current motion state is obtained;

(2) heavy-duty vehicle Kalman state estimation;

(3) heavy-duty vehicle rollover early warning.

2. a kind of heavy-duty vehicle rollover method for early warning according to claim 1, is characterized in that: obtain current heavy-duty vehicle state of kinematic motion, and according to heavy-duty vehicle state of kinematic motion, estimates vehicle side inclination angle, yaw velocity and side slip angle.Specifically comprise the steps:

(1) heavy-duty vehicle movement state information is obtained: the speed of a motor vehicle, steering wheel angle, lateral acceleration;

(2) heavy-duty vehicle rollover Early-warning Model;

(3) Kalman filter technology is utilized to estimate vehicle side inclination angle, yaw velocity and side slip angle;

(4) based on improvement TTR rollover warning algorithm.

3. a kind of heavy-duty vehicle rollover method for early warning according to claim 2, is characterized in that: described heavy-duty vehicle rollover Early-warning Model content, its differential equation of motion, and it is as follows to be converted into state space form:

$\stackrel{\·}{x}=\mathrm{Ax}+B_{\mathrm{\δ}}\mathrm{\δ}$

In formula, the state variable of early warning reference model is $x={\left[\begin{array}{cccc}\mathrm{\β}& \stackrel{\·}{\mathrm{\ψ}}& \stackrel{\·}{\mathrm{\φ}}& \mathrm{\φ}\end{array}\right]}^T$

$A=\left[\begin{array}{cccc}-\frac{{\mathrm{\σJ}}_{\mathrm{xeq}}}{{\mathrm{mJ}}_{\mathrm{xx}}v}& \frac{{\mathrm{\ρJ}}_{\mathrm{xeq}}}{{\mathrm{mJ}}_{\mathrm{xx}}{v}^2}-1& -\frac{\mathrm{hc}}{J_{\mathrm{xx}}v}& \frac{h(\mathrm{mgh}-k)}{J_{\mathrm{xx}}v}\\ \frac{\mathrm{\ρ}}{J_{\mathrm{zz}}}& -\frac{\mathrm{\κ}}{J_{\mathrm{zz}}v}& 0& 0\\ -\frac{\mathrm{h\σ}}{J_{\mathrm{xeq}}}& \frac{\mathrm{h\ρ}}{J_{\mathrm{xeq}}v}& -\frac{c}{J_{\mathrm{xeq}}}& \frac{\mathrm{mgh}-k}{J_{\mathrm{xeq}}}\\ 0& 0& 1& 0\end{array}\right]$

$B_{\mathrm{\δ}}={\left[\begin{array}{cccc}\frac{C_v{J}_{\mathrm{xeq}}}{{\mathrm{mJ}}_{\mathrm{xx}}v}& \frac{C_v{l}_v}{J_{\mathrm{zz}}}& \frac{{\mathrm{hC}}_v}{J_{\mathrm{xx}}}& 0\end{array}\right]}^T$

In formula, m is complete vehicle quality; J _xxthe rotor inertia of complete vehicle quality around the longitudinal axis of vehicle body center of gravity; J _xeqthe rotor inertia of complete vehicle quality around roll axis; J _zzthe rotor inertia of complete vehicle quality around Z axis.L _vthat car load center of gravity is longitudinally to the distance of front axle; l _hthat car load center of gravity is longitudinally to the distance of rear axle; a _yit is the lateral acceleration of vehicle; ψ is the course angle of vehicle; the yaw velocity of vehicle; φ is the angle of roll of vehicle; the angle of roll speed of vehicle; V is longitudinal speed of a motor vehicle of vehicle; The cornering stiffness of forward and backward tire is defined as C respectively _vand C _h; H is the distance that center of gravity arrives roll center; K is suspension roll stiffness; δ is front wheel angle; C is suspension damping coefficient; β is side slip angle, and σ, ρ and κ are auto model system parameter.

4. a kind of heavy-duty vehicle rollover method for early warning according to claim 2, it is characterized in that: the described Kalman filter technology that utilizes estimates vehicle side inclination angle, yaw velocity and side slip angle content, measure the heavy-duty vehicle movement state information obtained according to content (1), the heavy-duty vehicle utilizing content (2) to set up rollover Early-warning Model and Kalman filter technology estimate the quantity of state of vehicle side inclination angle, yaw velocity, side slip angle.Concrete vehicle-state Kalman filter design procedure is as follows:

(1) the state variable setting that vehicle rollover model is initial is defined: kalman filter estimator coefficients sets: measurement noises covariance R=1, procedure activation noise covariance Q=1000 × eye (4), observing matrix H=C.

(2) filter temporal upgrades part

${{\hat{x}}_k}^{-}=G{\hat{x}}_{k-1}+{\mathrm{F\δ}}_{k-1}$

P _k ^-＝GP _k-1G ^T+Q

(3) filter status upgrades part

K _k＝P _k ^-H ^T(HP _k ^-H ^T+R) ^-1

${\hat{x}}_k={{\hat{x}}_k}^{-}+K_k(a_y-H{{\hat{x}}_k}^{-})$

P _k＝(I-K _kH)P _k ^-

In formula, P _kand P _k ^-represent error covariance; K _kfor Kalman filter gain; G, F and Q are system parameter; I is unit matrix; a _yfor the lateral acceleration measured; δ is system interference.

5. a kind of heavy-duty vehicle rollover method for early warning according to claim 2, it is characterized in that: described to turn on one's side warning algorithm based on improvement TTR, this algorithm principle predicts the state parameter response of real vehicles, the heavy-duty vehicle rollover Early-warning Model set up before utilization, with the running state of vehicle current time for initial value, according to vehicle rollover rule with T _sstep size computation rollover warning index LTR _d.Write down when this index first time meets rollover condition and calculate step number N, namely can obtain vehicle rollover pre-warning time is TTR=N × T _s.TTR value is less, shows that vehicle rollover risk is higher; If when TTR is 0, show that heavy-duty vehicle is turned on one's side.

Wherein, turn on one's side warning index dynamic load rate of transform LTR _dcomputing formula is as follows:

${\mathrm{LTR}}_d=-\frac{2(c\stackrel{\·}{\mathrm{\φ}}+\mathrm{k\φ})}{\mathrm{mgT}}$

In formula: T is the wheelspan of vehicle, and g is acceleration due to gravity.

In order to reduce rollover Early-warning Model calculated amount, ensureing the real-time of vehicle rollover early warning, needing setting one rollover early warning threshold value to be X second.The threshold value of medium-weight vehicle of the present invention rollover prior-warning device is set to 3 seconds, and in 3 seconds, namely calculate rollover index do not meet rollover condition and then stop calculating, TTR is set to 3, thus avoids endless loop.Therefore, when the rollover pre-warning time obtained is 3 seconds, shows that automobile is not turned on one's side in following 3 seconds danger, then think when being less than threshold value that vehicle exists rollover risk, and make TTR=N × T _s, trigger rollover prior-warning device simultaneously.

6. realize a device for method according to claim 1, it is characterized in that: it comprises onboard sensor, rollover early warning controller and warning and read out instrument.Movable information for detecting heavy-duty vehicle movable information, and is sent to rollover early warning decision unit by described onboard sensor; Vehicle rollover early warning controller, by receiving vehicle movement parameter information, carries out rollover hazard level according to pre-set program and calculates, and obtains above-mentioned heavy-duty vehicle rollover early warning result, and this result is sent to read out instrument; The rollover alarming result display that read out instrument will receive, revises dangerous manipulation in time for chaufeur, thus effectively avoids rollover accident to occur.