• 专利附录
  • 专利说明
  • 权利要求
  • 类似技术
  • 同族专利
  • 引用文献
  • 法律状态
  • 优先权
    • 专利摘要:
    To allow a vehicle (1) to comfortably follow a lane, in particular but not necessarily a lane with turns with a large radius of curvature, the vehicle trajectory control device (1) comprises an observer module (2) which generates real-time from a current measurement vector (η) an estimated track condition vector (ξ) of the vehicle (1) traveling at a current speed (va), so as to produce a first command ( ust) to stabilize the path of the vehicle relative to the track. The device further comprises an anticipating module (7) which adds to the first steering control (ust) a second steering control (uff) which is a function of a radius of curvature (ρff) to be applied to the trajectory.
    公开号:FR3051756A1
    申请号:FR1654617
    申请日:2016-05-24
    公开日:2017-12-01
    发明作者:Iris Ballesteros-Tolosana；Renaud Deborne；Joan Davins-Valldaura；Maud Geoffriault
    申请人:Renault SAS；
    IPC主号:
    专利说明:

    Device for controlling the trajectory of a vehicle
    The work leading to the present invention has been financially supported by the European Community's Coal and Steel Research Fund under grant agreement No 607957. The invention relates generally to a real-time control of vehicle trajectory. The invention relates more precisely to a lateral control device for generating in real time steering control of a vehicle, in particular of a self-driving or partially-delegated motor vehicle, that is to say of a vehicle that can move totally or partially without a human driver.
    Devices or systems for real-time state-trajectory control are already known in many technical fields, including that of the automobile.
    For example, patent EP1074903B1 discloses a system for tracking a track with detection of marking of the track. A direct chain action module produces a directional steering term based on a target line position from a graphics processor. The disclosed elements suggest an application of this system to a straight path, or even with low curvature curves without significant influence on the dynamics of the vehicle. An application on a lane with bends with strong curvature, as can be encountered for example on mountain roads can pose a problem of dynamic responsiveness of the vehicle to maintain flexibility in the lane.
    For example still patent US8751089B2 discloses a tracking control system for mobile unit. The system controls a mobile unit to follow a target path described by free-form curves. While this type of system may be suitable for controlling a robot in an unrestrained space such as to prevent the freedom of shape of the curves that are suitable for a target path, it may cause problems for an autonomous vehicle whose pilot does not consist in it. following a target path but keeping it in a traffic lane, regardless of the shape of the curves imposed by the geometry of the lane. The invention aims to address the problems posed by the prior art, particularly in terms of efficiency, responsiveness and ease of implementation.
    To achieve this objective, the invention relates to a device for real-time control of a vehicle trajectory comprising an observer module that generates in real time from a current measurement vector an estimated state vector of monitoring of vehicle traveling at a current speed, so as to produce a first steering command to stabilize the path of the vehicle relative to the track. The device is remarkable in that it comprises a anticipator module which adds to the first steering control a second steering control which is a function of a radius of curvature to be applied to the trajectory.
    Thus, as high as is the curvature imposed by the track, of course within the limits usually set by the regulations in force, the device allows the vehicle to comfortably negotiate many curves imposed by the nature of the taxiway.
    Advantageously, the curvature is the inverse of a radius of curvature of a track at a distance ahead of the vehicle.
    Preferably, said distance varies according to said current speed of the vehicle.
    In particular, the device comprises an apparatus combining the properties of an optical camera and a radar to provide at least one guide line geometry in the form of a polynomial.
    More particularly, the anticipator module comprises a curvature calculation sub-module from the median center line geometry of the channel by means of a formula expressing in the form of a ratio comprising in the numerator a second derivative of the polynomial and at the denominator a square root of an expression raised to the cube of the square of the first derivative of the polynomial increased by one.
    Particularly also, the anticipator module comprises a sub-module for calculating the second steering control as a solution of the equations of the dynamic giving a stable state vector or zero time derivative.
    More particularly, the anticipator module generates an evaluated measurement vector for said stable state vector so as to remove said evaluated measurement vector from said current measurement vector at the input of the observer module.
    More particularly, the calculation sub-module further comprises an adjustable gain of the second steering control.
    Still more particularly, the current measurement vector includes coordinates relating to a yaw rate and a steering angle and the estimated state vector includes yaw rate coordinates at a trajectory deviation angle. of the vehicle, a steering angle time derivative and the steering angle.
    More particularly, to align with the roadway, the current measurement vector further comprises coordinates relating to the angle of deviation relative to the trajectory of the vehicle, the lateral deviation to the trajectory of the vehicle tracking path and the opposite of the temporal integral of lateral deviation to the trajectory, and the estimated state vector further comprises coordinates relating to a time derivative of lateral deviation to the trajectory of the vehicle, to the deviation lateral to the trajectory of the vehicle, and the opposite of the temporal integral of lateral deviation to the trajectory. Other characteristics and advantages will become apparent on reading the description which follows, with reference to the appended drawings, in which: FIG. 1 represents a vehicle to which the invention is applicable, FIG. 2 is a diagram of implementation of FIG. device according to the invention.
    With reference to FIG. 1, a motor vehicle 1, driven by a motor (not shown in the figures), comprises four wheels comprising two front wheels 11 which are preferably the steering wheels, and two rear wheels 12. Each wheel is equipped with or not respectively an instantaneous speed sensor to know a current speed Va of the vehicle, including a current longitudinal speed of the vehicle.
    The vehicle 1 comprises a steering column 44 whose upper part is equipped or not with a steering wheel, the latter becoming useless for a purely autonomous vehicle, and whose lower part acts on a steering member which allows to orient the wheels before. The steering column 44 is equipped with an actuator controlled by a control signal u. The steering member is equipped with a sensor 46 at the base of the steering column or at any other place, for example a rack acting on the front wheels, to measure an effective steering angle δ of the front wheels of the steering wheel. vehicle. The sensor 46 is for example a torque sensor whose value is easily converted into a steering angle.
    The vehicle 1 also comprises a sensor 31 of the yaw rate
    the vehicle, that is to say the speed of rotation of the vehicle around its center of gravity along an axis perpendicular to the plane of the road on which the vehicle is traveling. The sensor 31 is for example a gyro located very close to the center of gravity (CoG for center of gravity in English) of the vehicle. A device 15 of the RaCam type, that is to say combining the properties of an optical camera and a radar, makes it possible to measure coordinates of Ycam objects transverse to a median axis of the vehicle and Xcam along the axis median towards the front of the vehicle 1.
    As also known from the supplier of the apparatus 15, a fusion of optical measurements and radar measurements makes it possible to detect, for each marking point on the roadway, the distance x of this point with respect to the front face of the apparatus 15 along its axis of vision and the distance y of this same point relative to the axis of vision. An image processing, outside the scope of the present invention, allows the apparatus 15 to provide a geometry y (x) of at least one guide line of the vehicle taxiway in the form of a polynomial, by example of the delimitation line on the left and the delimitation line on the right of the lane or the center line of the lane in the center of the two delimitation lines. For a given guideline, the polynomial has for example the following form:
    The vehicle 1 is equipped in a manner known per se of an on-board computer (not shown as such) for controlling and controlling different vehicle components. The computer can receive, via connections, in particular via a CAN, Lin or Ethernet Ethernet bus, information from the longitudinal speed sensors, the yaw rate sensor 31, the steering angle sensor δ and the angle sensor. 15. The on-board computer can also control the steering column 44 by communicating the control signal u. The on-board computer may furthermore host a controller device 3 for generating a control signal Ust so as to make a physical state vector ξ of the vehicle conform to a reference state vector ξ * to ensure a desired trajectory tracking. by the vehicle 1. The physical state of the vehicle depends on many physical data more or less well controlled that affect its dynamic behavior. The on-board computer accommodates an observer device 2 for generating in real time an estimated state vector ξ for tracking the trajectory of the vehicle 1 moving at the current speed Va, from the command Ust and a current measurement vector η correlated to the vehicle trajectory tracking physical state vector,, as now explained with reference to FIG. 2.
    In the embodiment illustrated in FIG. 2, an effective state vector ξ of the vehicle 1 comprising more than two scalar coordinates, or state variables, among which can be cited for example in any predetermined order but preferably definitively for a given vehicle, an effective yaw rate
    of the vehicle, an angle ΨΓεί, εί of the vehicle's actual relative deviation to its ideal trajectory and an effective lateral speed
    distance from the center of gravity of the vehicle relative to its ideal trajectory. The angle ΨΓεί, εί of effective relative deviation is the angle actually made by the median axis of the vehicle with the tangent to the ideal trajectory at each instant considered. Effective lateral speed
    distance from the center of gravity is the speed at which the center of gravity of the vehicle actually moves away from the ideal trajectory, perpendicular to the tangent to the ideal trajectory at the moment considered. The state vector ξ of the vehicle 1 may comprise other scalar coordinates, for example the actual distance Ycog.ef from the center of gravity of the vehicle with respect to its ideal trajectory, the actual variation
    turning angle of the vehicle wheels over time, and the actual steering angle of the wheels.
    The state variables may have a meaning independent of the mode in which the vehicle operates or a meaning specific to the mode in which the vehicle operates. The yaw rate, which is the speed with which the vehicle pivots about an axis perpendicular to the plane of the roadway, is independent of the mode of operation. The same is true of the actual variation
    steering angle of the vehicle wheels over time, and the actual steering angle S ^ j- wheels as these variables are related to the state of the wheels themselves relative to the chassis of the slave vehicle. On the other hand, the effective distance Ycog.ef from the center of gravity of the servo vehicle with respect to its ideal trajectory is the lateral deviation between the guide line of the track and the center of gravity of the enslaved vehicle on the axis perpendicular to the vehicle axis in LCA mode. Effective lateral speed
    distance from the center of gravity is the temporal variation of the previous variable.
    The state vector ξ of the vehicle 1 may also include scalar coordinates different in number and / or in kind depending on the mode of operation of the vehicle. Using the illustrative example above, an optional state variable
    may represent a temporal integral of the deviations of the center of gravity of the servo vehicle from the point of the guideline of the track on which it should be. In fact this state variable does not correspond to any real physical state, it is rather an artifice inherited from PID closed-loop servocontrols, in which the integral component of the gain makes it possible to obtain a non-zero output of the amplifier for a zero error applied to its entry, with the technical effect of imposing a zero error, here on the actual distance Ycog, ef the center of gravity of the vehicle relative to the center line of the taxiway. To this vector ξ of effective state of the vehicle 1 corresponds a vector ξ * reference state that it is desired to be achieved at each moment of travel of the slave vehicle. For example at the coordinates βΐ, βΓ, coCGG, ef ^ YcoG.ef of the state vector ξ correspond to the coordinates Tref, ŸcoG, ref ^ YcoG.ref of the state vector ξ * of null values because it is of course desired to have no difference between the effective trajectory of the servo vehicle and its ideal trajectory.
    The vector ξ of effective state of the vehicle 1 is unknown because the internal state of the enslaved vehicle, governed by the natural laws of physics, is inaccessible in its entirety.
    It is recalled that the known laws of physics pose that a vector ξ of temporal evolution of the state vector ξ of the physical system constituted by the vehicle 1, is linked to the state vector ξ by a dynamic relation A which, in absence of external disturbance, generally tends to bring the state of the vehicle to a stable final state. Since the stable final state of the vehicle is not necessarily the one that is to be attained, the object of the invention is to produce a control u which continuously disturbs the system in order to maintain the effective state vector conforme in accordance with FIG. vector ξ * reference state. The perturbation thus provoked on the vector ξ of temporal evolution, is related to the control U by an invasive relation B, also governed by the laws of physics. Other external disturbances, of a globally unknown nature, also acting on the physical system constituted by the vehicle 1, use a feedback servo mechanism in which the observer device 2 aims to generate in real time a vector ξ estimated state representing as closely as possible the vector ξ of effective state.
    To achieve its goal, the observer device 2 comprises a module 4 which models the physical system constituted by the vehicle 1, in particular in terms of trajectory tracking. The module 4 comprises a computed numerical matrix representative of the dynamic relationship A and a digital matrix B® representative of the invasive relationship B.
    The numerical matrix A 'can have different forms, each adapted to a mode of operation of the vehicle. The shape of the digital matrix is essentially related to the vehicle state vector ξ 1 and the dynamic relationship applied. The example form shown below, is based on the bicycle model well known in the technical field considered, as illustrated by many previous documents such as FR2925005 or WO2012084465. The example considered here is that of the LCA mode, for which the numerical matrix A '' has the following form:
    In which some coefficients are variable and others are constant during the same rolling sequence.
    The variable coefficients are essentially those which depend on a speed v, in particular on the longitudinal velocity Va of the vehicle. To adapt to speed variations, the variable coefficients are recalculated in real time by reading on the one hand the speed v, in particular the longitudinal velocity Va generally accessible on the on-board network (CAN bus type, LIN, Ethernet car or other) and on the other hand generally accessible parameters in memory, by means of the following formulas:
    In which the parameters Cr, Cf, h, If, Iz, M quantify in a manner known per se (see applications FR1255068, FR1255188, or FR12563339) each respectively the drift rigidity of the rear wheels 12 and the drift rigidity of the front wheels 11 obtained from the tire supplier of the wheels or by means of circuit-rolling tests, the distance of the rear wheel center line and the distance of the front wheel axis from the vehicle's CoG center of gravity 1, the moment of inertia of the vehicle around the perpendicular to the plane passing through the front and rear wheel axles, and finally the mass of the vehicle.
    The constant coefficients during a rolling sequence can be precalculated during the design of the vehicle and then stored in onboard computer memory. They are determined by the following formulas:
    In which on the one hand μ and ω respectively denote a damping coefficient and a specific pulse of the transfer function of the wheel steering control.
    The constant coefficients during a rolling sequence may also be calculated at each start of the vehicle to take account of a mass M and a moment of inertia Iz which may be different at each start depending on the number of passengers and loading. Variations in these parameters, for example caused by fuel consumption or a passenger descending from the vehicle en route, are generally insignificant.
    The unit coefficients exist on the line corresponding to the time derivative of a state variable which is itself a state variable of rank equal to that of the column of the matrix.
    The other coefficients are damaged, with the exception of the last column where they are all damaged and the last line where only the median coefficient is not zero but equal to -1 to artificially reproduce a linear linear servo feedback reaction. PID type.
    The number of columns of the matrix is equal to the number of coordinates of the state vector and the number of lines is equal to the number of coordinates of the temporal variation vector of state, that is to say equal to the number of lines . It will be understood that the numerical matrix may comprise numbers of rows and columns different from those of the examples above, notably higher if the need arises to consider an additional or lower state variable if a variable of state, including the state variable corresponding to the last line as explained above.
    The B® digital matrix representative of the invasive relationship B, is adapted to the control mode of the vehicle and taking into account external factors. The shape of the digital matrix B® is essentially linked to the vector η of state whose number of coordinates fixes the number of lines and the interactions with the system whose number sets the number of columns. The main example of form set out below corresponds to the example set out above.
    For LCA mode, the B® digital matrix has the following form:
    In which the first column is here associated with the first perturbation which is the control u steering while the second column is associated with a second perturbation which is the curvature jref equal to the inverse of the radius of curvature pref of the taxiway himself where the vehicle is. The coefficient bsi is here again equal to the square of the own pulsation ω of the transfer function of the wheel steering control. In the second column however. two coefficients bu and b32 are harmless considering that the curvature Yref acts directly on the angle Trei.ef of the actual relative deviation of the vehicle to its ideal trajectory and on the effective lateral velocity
    distance from the center of gravity of the vehicle relative to its ideal trajectory. The coefficient b22 is equal to the opposite of the longitudinal velocity Va of the vehicle and the coefficient b32 is equal to the opposite of the square of the longitudinal velocity Va of the vehicle.
    To model the vehicle 1, the module 4 receives the command Ust so as to generate the estimated state vector en by reproducing the equations of the dynamics by means of the numerical matrices and B * intervening in the formulas:
    Several conditions should be satisfied for the estimated state vector reprod to faithfully reproduce the vehicle of the physical state of the vehicle.
    In the first formula which is an integral with respect to time, it would be necessary that at an initial instant, the estimated state vector soit be equal to the vector ξ of the physical state of the vehicle.
    In the second formula, the digital matrices and B® should perfectly model the dynamic relationship A and the invasive relationship B that actually impact the vehicle.
    It is understandable that these conditions can not be satisfied for many reasons such as the accuracy of the parameters that qualify the vehicle while they are subject to manufacturing dispersions and aging, unplanned disturbances and well other known or unknown reasons.
    To reduce the difference between the estimated estimated state vector ξ and the unknown vehicle physical state vector l', the observer 2 receives on a second input a vector η of current measurements that are representative the condition of the vehicle. The vector η of current measurements is correlated with the physical state vector ξ by an instrumental relation C which depends on the configuration of the state vector, that is to say the operating mode of the vehicle, and measurement sensors which equip the vehicle.
    Taking the example for the LCA operating mode, the current measurement vector η comprises five components which are the yaw rate ψ as measured by the sensor 31, the relative difference angle Trei as it is measured by the apparatus 15 aiming at a center line of the taxiway, the radial distance Ycog of the center of gravity with respect to the center line of the taxiway such that this distance is obtained from the aircraft 15 , the steering angle δ of the wheels 11 as measured by the sensor 46 and the accumulation
    during the time of the opposite of the distance Ycog of the center of gravity provided by the apparatus 15. By assimilating the duration dt to the sampling period for each instant k, this pseudo measure is obtained by the very simple formula :
    initialized to zero.
    The instrumental relation C is approximated in the module 4 by a digital matrix C '^ to generate a measurement vector ή estimated from the estimated state vector pour for the operating mode considered.
    In the LCA operating mode, the digital matrix preferably has the following form:
    In which the non-harm coefficients Cn, C22, C34, C46, C57 are constant and unitary because the measurements considered are part of the state variables.
    The module 4 then calculates the estimated measurement vector ή by multiplying in real time the state vector ξ estimated by the matrix
    Whatever the mode of operation of the vehicle, an estimation gain module 5 (sometimes called Kalman gain) has the function of correcting the time derivative ξ of the state vector so that the estimated measurement vector ή from the estimated state vector co coincides in steady state with the actual measurement vector η, so that the estimated state vector co thus coincides with the vehicle trajectory tracking physical state vector 1. 1. To do this, the module 5 adjusts in real time the temporal variation ξ of estimated state vector ξ so as to reduce a stabilization difference between the current measurement vector η and the estimated measurement vector ή by multiplying the stabilization difference by a matrix estimation gain The stabilization gap between the two measurement vectors η and ή, being a vector of dimension equal to that of the measurement vectors and the correction to be added to the temporal variation ξ estimated state vector, being a vector of dimension equal to that of the state vectors, the matrix L ^ 'comprises a number of lines equal to the number of coordinates of the state vector and a number of columns equal to the number of coordinates of the measurement vector.
    Thus, the observer device 2 can behave as a Kalman observer defined by the equation:
    The matrix L ^ 'corresponds to the matrix of the gains of the Kalman observer, without it being necessary here to develop in more detail its obtaining which is known elsewhere. The Kalman observer described above is essentially illustrative to better understand the implementation of the invention but other observers may be used such as high gain observers, Kalman type observers. extended, observers Luenberger or other Bayesian type filters for which the skilled person should know without difficulty transpose the teaching here lavished.
    The controller device 3 generates the command Ust so as to reduce until canceling the difference between a reference state ξ * and the estimated state vector ξ in particular by virtue of the last integral type state variable. Since the reference state vector is defined as a zero vector of size 7x1, the solution proposed for the controller is exactly the conventional approach called "static state feedback", which is defined as:
    The gain matrix K, defined as 7x1, contains the control gains. In total there are seven parameters to set, each associated with a different state variable:
    The optimization method used is, for purely illustrative and nonlimiting purposes, the linear quadratic method (LQR for Linear-Quadratic Regulator in English), based on the Ricatti equations and on the minimization of the matrix S of solutions:
    Here again the matrices A and B result from the equations of the lateral dynamics, Qu is the weight matrix of each of the state variables and Λ * is the weight matrix of the control (in this case R is fixed to a single scalar because there is only one command u).
    The matrix ç *, which must be developed, is defined as follows:
    The matrix is assumed to be diagonal because it is considered that there is no correlation between the weights of the state variables.
    Here we briefly recall the well-known principle of separation which governs the link between the optimization of the control in the devices and that of the observer in the device 2 which is very strong because the performance of the controller depends directly on the estimation of the observer, and the synthesis of the command is made from the estimated value ξ by the observer.
    To ensure the stability of the looped system, observer stability (A-LC) and control stability should be verified independently using the actual state (A + BK). This property allows us to guarantee that the optimization of the observer, in other words the optimization of the matrix L 'and the optimization of the command, in other words the optimization of the matrix K of gains , can be made independently of each other while guaranteeing the stability of the system. This principle is known as the separation principle.
    However, in variations of high-speed taxiway geometry, as is the case for example on assembly roads or certain bifurcations, an optimization that is too rigid can adversely affect the comfort of the passengers or require the vehicle to the extreme. its mechanical abilities with the effect of accelerating its aging. On the other hand, under-optimization risks disastrous approaches to difficult turns or imposes a boring driving style. In order to allow both the best optimization of the state servo loop without harming the comfort of the passengers or the vehicle to the extreme of its mechanical capabilities or road adhesion conditions, the device of Real-time trajectory control includes a anticipator module 7 which adds to the first steering command Ust generated from the observer module 2, a second steering command Uff which is a function of a curvature yff to be applied to the trajectory.
    The module 7 comprises a first calculation sub-module E which quantifies the curvature yff and a second calculation sub-module E which quantifies the second steering command Uff.
    The calculation sub-module D quantizes the second steering command Uff so that it is a solution of the equations of the dynamic giving a state vector ξ stable or time-derivative ξ zero. In other words, the steering command Uff is generated by ignoring the tracking instabilities which are managed by the observer module 2. In the equations related to the dynamics of the vehicle, one considers a state of equilibrium equilibrium steering control Ueq and one reuses the matrices and B * to model the relations A and B.
    Either by taking the same index for the state variables as for the state vector:
    The fifth line of the system then gives, in combination with the sixth line:
    By replacing the coefficients ase and bsi by their parameterizable mechanical evaluation,
    At equilibrium, Ueq = ô ^ q.
    The first and the third line of the system give, on the other hand, in combination with the fourth line, then with the second line:
    Is :
    So that the resolution of the system gives:
    By replacing the matrix coefficients by their parameterizable mechanical evaluation:
    It should be noted that the Ueq control is independent of the vehicle speed Va when the drift rigidities of the rear and front wheels are equal and that the center of gravity of the vehicle is equidistant from the rear and front wheel axles. Thus a vehicle with a drifting rigidity Cf, Cr identical on all wheels and its center of gravity equidistant from the front and rear axle wheels, would have the advantage of having a control independent of its mass M and its momentum. Iz inertia, calculated using the very simple formula:
    Ueq = 0f + lr) Tff
    The command Uff = Ueq = Ôeq could be summed directly with the command to obtain the steering command u = Ueq + Ust applied to the wheels.
    However, taking into account that the modeling may not represent perfectly the real behavior of the vehicle because of factors that may not be taken into account or that the human feeling may vary according to the type of passenger, an interesting variant is to multiply the order Ueq by a gain G adjustable during testing of the vehicle and possibly adjustable according to a mode of driving, sports, family or other. The term gain is to be taken in its most general sense, which may correspond to an increase when it is greater than unity or to an attenuation in the opposite case. We then obtain:
    Uff = G * Ueq
    At equilibrium state vector ξeq corresponds to a pseudo equilibrium qeq vector of equilibrium:
    The pseudo measurement vector qeq obtained in the computation sub-module D is then subtracted from the effective measurement vector η so as to make the observer module bear only on the path deviations.
    The curvature yff to be applied to the path may for example relate to that of a gap to be made by the vehicle to avoid an obstacle or to change lanes. The preferred example of implementation that we are now explaining relates to a track curvature at a distance x ahead of the vehicle. Thus, the control device of the invention can anticipate the announcement of a turn in the manner of a driver who looks at the road in front of the vehicle to initiate a turn rather than guide the vehicle as if it were on a road. rail.
    Advantageously, the distance x varies according to the current speed Va of the vehicle. For purely illustrative and non-limiting, it is possible to consider a distance x equal to the product of the speed Va multiplied by a given response time fixed value or value itself depending on the speed. This response time can also be parameterized to allow to adjust during the tests of the vehicle.
    The computation sub-module E then receives from the apparatus 15 the polynomial y (x) which gives the geometry of the guide line of the taxiway for each point at the distance x at the front of the vehicle. generally in the form of a vector (po, pi, p2, Ps) whose coordinates correspond to the coefficients of the polynomial.
    The submodule E then calculates the curvature yff by means of the formula:
    If the polynomial is of degree 3 as evoked above, the first derivative is given by the simple formula:
    Similarly, the second derivative is given by the simple formula:
    The curvature yff can thus easily be calculated in real time by means of the formula:
    权利要求:
    Claims (10)
    [1" id="c-fr-0001]
    Claims:
    A device for real-time control of a vehicle trajectory (1) comprising an observer module (2) which generates in real time from a current measurement vector (η) an estimated state vector A (ξ) ) for tracking the vehicle (1) traveling at a current speed (Va), so as to produce a first steering control (Ust) for stabilizing the vehicle trajectory with respect to said track, characterized in that comprises: - an anticipating module (7) which adds to said first steering command (ust) a second steering command (Uff) which is a function of a curvature (yrr) to be applied to the trajectory.
    [2" id="c-fr-0002]
    2. Control device according to claim 1, characterized in that said curvature (Yff) is equal to the inverse of a radius of curvature of a track at a distance (x) in front of the vehicle.
    [3" id="c-fr-0003]
    3. Control device according to claim 2, characterized in that said distance (x) varies according to said current speed (Va).
    [4" id="c-fr-0004]
    4. Control device according to one of the preceding claims, characterized in that it comprises an apparatus (15) combining the properties of an optical camera and a radar to provide at least one geometry (y (x) ) of the channel guideline as a polynomial.
    [5" id="c-fr-0005]
    5. Control device according to claim 4, characterized in that the anticipating module (7) comprises a curvature calculation sub-module (E) (γ ff), 4 - from the geometry (y (x) ) the median center line of the track using the formula


    [6" id="c-fr-0006]
    6. Control device according to one of the preceding claims, characterized in that the anticipating module (7) comprises a sub-module (D) for calculating the second steering control (uff) as a solution of the equations of the dynamic giving a stable state vector or zero time derivative.
    [7" id="c-fr-0007]
    7. Control device according to claim 6, characterized in that the anticipating module (7) generates an evaluated measurement vector (qeq) for said stable state vector so as to remove said evaluated measurement vector (qeq) from said vector current measurement (η) at the input of the observer module (2).
    [8" id="c-fr-0008]
    8. Control device according to one of claims 6 or 7, characterized in that the sub-module (D) calculation further comprises an adjustable gain of the second control (Uff) steering.
    [9" id="c-fr-0009]
    9. Control device according to one of the preceding claims, characterized in that said current measurement vector (η) comprises coordinates relating to a yaw rate {ψ) and to a steering angle (δ) and in that the estimated state vector {ξ) comprises coordinates relating to the yaw rate {ψ), to a deviation angle (Ψ,,) relative to a trajectory of the vehicle (1), to a derivative time of steering angle (^) and steering angle (δ).
    [10" id="c-fr-0010]
    10. Control device according to claim 9, characterized in that to wedge on the roadway, said current measurement vector (η) further comprises coordinates relating to the angle of deviation relative to the trajectory of the vehicle (1), lateral deviation (Ycog) ^ vehicle trajectory χΐ) -lane tracking and the opposite of the time integral of lateral deviation

    to the trajectory, and in that the estimated state vector (ξ) furthermore comprises coordinates relating to a time derivative (Ÿcog) of lateral deviation to the trajectory of the vehicle (1), to the lateral deviation (Ycog ) ^ trajectory of the vehicle (1), and the opposite of the temporal integral of lateral deviation

    to the trajectory.
    类似技术:
    公开号 | 公开日 | 专利标题
    EP3464003B1|2020-07-01|Device for controlling the path of a vehicle
    EP3344506B1|2019-07-17|Device and method for correcting the direction of travel of a motor vehicle
    EP1544080B1|2008-08-06|Rear wheel steering angle control system and method and corresponding vehicle
    EP1304270B1|2005-01-26|Vehicle stability control method using tyre lateral forces and taking into account inertia of the vehicle
    EP2870040A1|2015-05-13|Device and method for controlling the trajectory of a vehicle
    EP3442840B1|2020-07-29|Device for tracking the path of a vehicle
    EP1907260B1|2010-03-24|Method for controlling the steering orientation of a vehicle
    EP3589533A1|2020-01-08|Device for controlling the trajectory of a vehicle
    FR3094324A1|2020-10-02|Autonomous piloting method of a device trajectory control member
    EP3321758A1|2018-05-16|A method of controlling an electrical taxiing system
    EP2027004B1|2014-05-21|Process and control system for vehicle steering wheel
    FR3044994A1|2017-06-16|METHOD FOR DETERMINING A COEFFICIENT VECTOR FOR DETERMINING A BRAKING ANGLE FOR APPLICATION TO WHEELS OF A MOTOR VEHICLE
    FR3093687A1|2020-09-18|Method of autonomous piloting of a mobility device
    WO2021111616A1|2021-06-10|Vehicle control device and vehicle control method
    FR3097828A1|2021-01-01|Method of regulating the lateral position of a vehicle
    FR3083766A1|2020-01-17|METHOD FOR THE PREPARATION OF A PREDICTIVE ORDER INSTRUCTIONS WHICH CAN BE IMPLANTED IN A TRAJECTORY CONTROL UNIT OF A MOTOR VEHICLE
    FR3101832A1|2021-04-16|High level side assist controller suitable for 4RD vehicles
    FR3094317A1|2020-10-02|Anticipator module, real-time trajectory control device and associated process
    FR3099450A1|2021-02-05|Autonomous control method of an actuator of an automotive device
    EP2115542B1|2012-03-07|Method for the autonomous guidance of an aircraft and corresponding aircraft
    FR3110129A1|2021-11-19|Trajectory calculation module, associated trajectory control device and method
    FR3092914A1|2020-08-21|Method for determining the trajectory of a vehicle comprising four steered wheels
    FR3082163A1|2019-12-13|METHOD AND DEVICE FOR ASSISTING THE DRIVING OF A VEHICLE BY DETERMINING THE TURNING ANGLE AS A FUNCTION OF A PREDICTIVE GAIN
    同族专利:
    公开号 | 公开日
    JP6907238B2|2021-07-21|
    EP3464003B1|2020-07-01|
    KR20190013886A|2019-02-11|
    EP3464003A1|2019-04-10|
    WO2017203159A1|2017-11-30|
    CN109415058A|2019-03-01|
    KR102194119B1|2020-12-22|
    FR3051756B1|2020-03-20|
    JP2019518648A|2019-07-04|
    引用文献:
    公开号 | 申请日 | 公开日 | 申请人 | 专利标题
    JP3740787B2|1997-04-28|2006-02-01|日産自動車株式会社|Automatic vehicle steering system|
    JPH1191609A|1997-09-24|1999-04-06|Nissan Motor Co Ltd|Automatic steering system for vehicle|
    EP1661793A2|2004-11-24|2006-05-31|Renault s.a.s.|System and method to control the steering angle of steerable vehicle wheels|
    WO2010053408A1|2008-11-06|2010-05-14|Volvo Technology Corporation|Method and system for determining road data|
    WO2013107978A1|2012-01-19|2013-07-25|Peugeot Citroen Automobiles Sa|Method for correcting the course of a motor vehicle and associated motor vehicle course correction device|
    WO2014006327A1|2012-07-03|2014-01-09|Renault S.A.S|Device and method for controlling the trajectory of a vehicle|WO2020126840A1|2018-12-21|2020-06-25|Renault S.A.S|Device and method for monitoring the trajectory of a motor vehicle|
    FR3094317A1|2019-04-01|2020-10-02|Renault S.A.S|Anticipator module, real-time trajectory control device and associated process|FR1255068A|1960-01-21|1961-03-03|Work furniture for hairdressing salons and the like|
    FR1255188A|1960-04-09|1961-03-03|Centripetal automatic clutch|
    FR1256339A|1960-05-05|1961-03-17|Girard Et Cie Ets|Paper hairstyle and its manufacturing process|
    JP3740785B2|1997-04-28|2006-02-01|日産自動車株式会社|Automatic steering device|
    JP3575343B2|1999-08-02|2004-10-13|日産自動車株式会社|Lane tracking device|
    JP3725090B2|2002-04-18|2005-12-07|三菱電機株式会社|Vehicle steering control device|
    JP4297123B2|2006-03-14|2009-07-15|トヨタ自動車株式会社|Trajectory tracking control system and trajectory tracking control method for moving body|
    FR2925005A3|2007-12-14|2009-06-19|Renault Sas|Tire and ground adhesion estimating method for controlling stability of motor vehicle during turning, involves selecting calculating model corresponding to determined situation of vehicle, and calculating adhesion of vehicle based on model|
    DE102009028261A1|2009-08-05|2011-02-10|Robert Bosch Gmbh|Method and control for calibrating an automatically steering parking aid|
    FR2969564B1|2010-12-22|2012-12-28|Renault Sa|METHOD AND DEVICE FOR MONITORING A MOTOR VEHICLE IN A BRAKING CONDITION WITH ASYMMETRIC ADHESION|
    WO2013030974A1|2011-08-31|2013-03-07|トヨタ自動車株式会社|Vehicle drive-control device|
    US9168924B2|2012-03-26|2015-10-27|GM Global Technology Operations LLC|System diagnosis in autonomous driving|
    US9150246B2|2013-12-06|2015-10-06|GM Global Technology Operations LLC|Algorithm for steering angle command to torque command conversion|
    CN104977933B|2015-07-01|2017-11-14|吉林大学|A kind of domain type path tracking control method of autonomous land vehicle|
    CN104925054B|2015-07-23|2017-04-19|吉林大学|Vehicle stable steering integrated control method based on differential flatness|CN108454623B|2018-01-22|2019-10-29|大连理工大学|A kind of unmanned electric vehicle Trajectory Tracking Control method of four motorized wheels|
    FR3082162B1|2018-06-11|2020-06-05|Renault S.A.S|METHOD AND DEVICE FOR DEVELOPING A CLOSED LOOP OF AN ADVANCED DRIVING AID DEVICE|
    FR3089927B1|2018-12-14|2020-11-20|Renault Sas|Method and device for maintaining a vehicle in its lane.|
    法律状态:
    2017-05-23| PLFP| Fee payment|Year of fee payment: 2 |
    2017-12-01| PLSC| Publication of the preliminary search report|Effective date: 20171201 |
    2018-05-22| PLFP| Fee payment|Year of fee payment: 3 |
    2019-05-23| PLFP| Fee payment|Year of fee payment: 4 |
    2020-05-22| PLFP| Fee payment|Year of fee payment: 5 |
    2021-05-20| PLFP| Fee payment|Year of fee payment: 6 |
    优先权:
    申请号 | 申请日 | 专利标题
    FR1654617|2016-05-24|
    FR1654617A|FR3051756B1|2016-05-24|2016-05-24|VEHICLE TRAJECTORY CONTROL DEVICE|FR1654617A| FR3051756B1|2016-05-24|2016-05-24|VEHICLE TRAJECTORY CONTROL DEVICE|
    EP17731614.8A| EP3464003B1|2016-05-24|2017-05-23|Device for controlling the path of a vehicle|
    CN201780032604.6A| CN109415058A|2016-05-24|2017-05-23|For controlling the device of vehicle route|
    KR1020187037350A| KR102194119B1|2016-05-24|2017-05-23|Devices that control the path of the vehicle|
    PCT/FR2017/051273| WO2017203159A1|2016-05-24|2017-05-23|Device for controlling the path of a vehicle|
    JP2018561554A| JP6907238B2|2016-05-24|2017-05-23|A device for controlling the route of a vehicle|
    [返回顶部]