Classifications

• • B—PERFORMING OPERATIONS; TRANSPORTING
  • B62—LAND VEHICLES FOR TRAVELLING OTHERWISE THAN ON RAILS
  • B62D—MOTOR VEHICLES; TRAILERS
  • B62D15/00—Steering not otherwise provided for
  • B62D15/02—Steering position indicators ; Steering position determination; Steering aids
  • B62D15/025—Active steering aids, e.g. helping the driver by actively influencing the steering system after environment evaluation
• • B—PERFORMING OPERATIONS; TRANSPORTING
  • B60—VEHICLES IN GENERAL
  • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
  • B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
  • B60W50/0098—Details of control systems ensuring comfort, safety or stability not otherwise provided for
• • B—PERFORMING OPERATIONS; TRANSPORTING
  • B60—VEHICLES IN GENERAL
  • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
  • B60W60/00—Drive control systems specially adapted for autonomous road vehicles
  • B60W60/001—Planning or execution of driving tasks

Definitions

• the present invention generally relates to automating the trajectory tracking of automotive devices.
• the present invention proposes a control method as defined in the introduction, in which the controller satisfies a modeling of said at least one saturation function by nonlinear sector.
• the controller is synthesized on the basis of a non-linear sector approach, so as to be able to guarantee not only the stability of the automobile apparatus in all situations, but also a good performance from as the situation permits.
• the invention proposes a more appropriate technique for modeling the saturation functions. This technique indeed has many advantages compared to the solution described in the document FR3099450.
• the claimed solution also ensures great stability as long as the disturbances have a bounded energy, that is to say in particular as long as the trajectory to be followed has a curvature remaining within acceptable limits.
• this solution makes it possible to know quickly whether the avoidance trajectory calculated can be performed dynamically by the vehicle, so as to activate the AES function only when this is the case.
• the invention also proposes to synthesize the controller by separating the stability conditions and those of performance. More precisely, in linear mode (when the controller is not saturated), the controller guarantees performance (which implies stability). In saturation mode (when the controller is saturated), this controller seeks to stabilize the closed-loop system. Thus the controller does not always seek to guarantee stability and performance at the same time, whatever the operating mode, which makes it possible to obtain better performance in certain operating modes.
• the controller in the event of saturation, the controller mainly seeks to guarantee the stability of the system. In the absence of saturation (which is statistically generally the case), it also seeks to guarantee performance, i.e. good avoidance trajectory tracking. It thus makes it possible to obtain better results than those obtained by the methods proposed in the prior art, where stability always took precedence over performance.
• the controller operates even if the initial states of the vehicle when the AES function is triggered are not adversely affected (initial heading, initial yaw rate, etc.), which happens when the vehicle has already a certain dynamic (for example because it is in a bend when the AES obstacle avoidance function is triggered), which is not the case with the solution described in the document FR3099450.
• the controller is synthesized by considering the initial states of the vehicle.
• the invention also proposes an automatic calculation of the gains of the corrector used in the control law of the vehicle, which makes it possible to reduce the design time of this control law.
• the proposed controller is optimal and consistent with the controllability limits specific to the vehicle, because the constraints on the steering angle and on the steering speed are taken into account beforehand in the synthesis of the controller.
• the method for estimating the stability zone in which the controller must remain consists here of an estimation of a basin of attraction.
• This method guarantees stability if the initial state of the vehicle, when the AES function is activated, meets certain criteria.
• the method according to the invention offers good results in terms of vehicle stability, performance (good trajectory following), tolerance to data measurement delays used in the context of the invention.
• the device is a motor vehicle which is suitable for driving on the road and which comprises at least one steered wheel, in which said actuator is adapted to control the steering of said steered wheel, and in which the steering setpoint is a saturated setpoint steering angle of said steering wheel;
• ⁇ (x) sa ⁇ iKx - Kx, with K the controller, sat n an amplitude limiting function, and x a state vector of said device;
• the controller guarantees that a state vector of said device has successive values over time which remain in the basin of attraction and which converge asymptotically towards the origin in a predetermined time;
• the controller guarantees that a state vector of said device has successive values over time which remain in the basin of attraction;
• ⁇ z e VL + a y . y ⁇ with e yi _ the trajectory tracking error, Yi_ the heading angle error and a y an adjustment coefficient which varies over time;
• the controller guarantees that the synthesis of the H norm applied to the controller is less than a predetermined scalar
• one of said parameters is a variable which depends on the curvature of the trajectory
• said basin of attraction is defined by means of a Lyapunov function, disturbances which apply to said device and a term which depends on said at least a saturation function;
• the controller satisfies a modeling of said device in which an output to be minimized is a function of a path tracking error and a heading angle error;
• This controller deactivation method is determined based on the stability zone and on vehicle state parameters (drift angle, yaw rate, heading angle, lateral position, steering wheel angle, steering wheel speed and curvature of the trajectory to be followed).
• vehicle state parameters drift angle, yaw rate, heading angle, lateral position, steering wheel angle, steering wheel speed and curvature of the trajectory to be followed.
• the deactivation conditions enacted make it possible to guarantee the correct operation of the controller and to diagnose abnormal situations (risk of vehicle instability, failure of sensors, actuators, unforeseen vehicle/driver behavior, etc.).
• the invention also relates to an automotive device comprising at least one actuator which is adapted to influence the trajectory of said device and a computer for controlling said actuator, programmed to implement a method according to one of the preceding claims.
• FIG. 1A is a schematic top view of a motor vehicle traveling on a road and which is adapted to implement a method according to the invention;
• FIG. 1B is a homologous view of FIG. 1A;
• FIG. 2 is a schematic perspective view of the motor vehicle of the FIG. 1A, represented in four successive positions situated along an obstacle avoidance trajectory;
• FIG. 3 is a diagram illustrating the closed-loop transfer function used to drive the motor vehicle of FIG. 1A;
• FIG. 4 is a graph illustrating the saturation polyhedra and the basin of attraction of the controller used in the context of the invention, and an example of variation in the state of the vehicle in the absence of disturbance,
• FIG. 5 is a graph similar to that of FIG. 4, on which the example of variation in the state of the vehicle is represented in the event of the presence of a disturbance;
• FIG. 6 is a graph illustrating the influence of a setting on the performance of the controller.
• FIG. 7 is a graph illustrating a vehicle steering algorithm according to a method according to the invention.
• FIG. 1A there is shown a motor vehicle 10 conventionally comprising a frame which delimits a passenger compartment, two front wheels 11 steered, and two rear wheels 12 not steered. As a variant, these two rear wheels could also be steered with an adaptation of the control law.
• This motor vehicle 10 comprises a conventional steering system making it possible to act on the orientation of the front wheels 11 so as to be able to turn the vehicle.
• This conventional steering system comprises in particular a steering wheel connected to connecting rods in order to cause the front wheels 11 to pivot.
• it also comprises an actuator making it possible to act on the orientation of the front wheels according to the orientation of the steering wheel and/or according to a request received from a computer 13.
• this motor vehicle includes a differential braking system making it possible to act differently on the speeds of rotation of the front wheels 11 (and if necessary on those of the rear wheels 12) so as to slow down the motor vehicle by turning it.
• This differential braking system comprises for example a controlled differential or electric motors placed at the wheels of the vehicle.
• the steering system considered will be formed by the conventional steering system alone. Alternatively, it could be formed by the combination of the conventional steering system and the differential braking system.
• the computer 13 is then provided to control the power steering actuator. It comprises for this purpose at least one processor, at least one memory and various input and output interfaces.
• the computer 13 is suitable for receiving input signals from different sensors.
• a device such as a front camera, making it possible to identify the position of the vehicle in relation to its traffic lane,
• a device such as a RADAR or LIDAR remote sensor, making it possible to detect an obstacle 20 lying in the path of the motor vehicle 10 (FIG. 2),
• At least one lateral device such as a RADAR or LIDAR remote sensor, allowing observation of the environment on the sides of the vehicle,
• a device such as a gyrometer, making it possible to determine the speed of rotation in yaw (around a vertical axis) of the motor vehicle 10, and
• the computer 13 is suitable for transmitting a setpoint to the power steering actuator.
• the computer 13 stores data used in the process described below.
• FIGS. 1A and 1B Before describing this process, the various variables which will be used can be introduced, some of which are illustrated in FIGS. 1A and 1B.
• the total mass of the motor vehicle will be denoted "m” and will be expressed in kg.
• J The inertia of the motor vehicle around a vertical axis passing through its center of gravity CG will be denoted "J" and will be expressed in N.m.
• the distance between the center of gravity CG and the front axle of the vehicle will be denoted “I f ” and will be expressed in meters.
• the distance between the center of gravity CG and the rear axle will be denoted “l r ” and will be expressed in meters.
• C f The drift stiffness coefficient of the front wheels will be denoted “C f ” and will be expressed in N/rad.
• C r The coefficient of drift stiffness of the rear wheels will be denoted “C r ” and will be expressed in N/rad.
• the steering angle that the front steered wheels make with the longitudinal axis A1 of the motor vehicle 10 will be denoted “d” and will be expressed in rad.
• variable ⁇ ref expressed in rad, will designate the saturated steering angle setpoint, as it will be transmitted to the power steering actuator.
• variable dk expressed in rad
• ⁇ ref the variable ⁇ sat
• the reference point of the vehicle will here originate from its center of gravity CG. Its abscissa Xv will be oriented along the longitudinal axis A1 of the motor vehicle 10, and its ordinate Yv will be oriented laterally, on the left side of the vehicle.
• the yaw rate of the vehicle (around the vertical axis passing through its center of gravity CG) will be denoted “r” and will be expressed in rad/s.
• the lateral deviation setpoint between the longitudinal axis A1 of the motor vehicle 10 (passing through the center of gravity CG) and the avoidance trajectory T0, at a sighting distance "Is" located in front of the vehicle, will be noted “yi_- ref " and will be expressed in meters.
• the trajectory tracking error will be denoted “e yi _” and will be expressed in meters. It will be equal to the difference between the lateral deviation setpoint yi_- ref and the lateral deviation yi_.
• the aforementioned aiming distance “Is” will be measured from the center of gravity CG and will be expressed in meters.
• the drift angle of the motor vehicle 10 (angle that the speed vector of the motor vehicle makes with its longitudinal axis A1) will be denoted “b” and will be expressed in rad.
• the speed of the motor vehicle will be denoted “V” and will be expressed in m/s.
• the constants “x” and “w” will represent dynamic characteristics of the steering angle of the front wheels of the vehicle.
• the constant “oo f ” will represent a dynamic characteristic of a bounded arbitrary disturbance “w” applied to the vehicle.
• the constant “g” will be the acceleration due to gravity, expressed in ms 2 .
• the steering speed will designate the angular steering speed of the steered front wheels.
• the method according to the invention is provided to enable the vehicle to follow the avoidance trajectory T0 as precisely as possible, in autonomous mode. This process is implemented when the AES automatic obstacle avoidance function is triggered and an avoidance trajectory T0 has been calculated. It will be noted that the manner of triggering the AES function and of calculating the avoidance trajectory T0 is not strictly speaking the subject of the present invention, and will therefore not be described here. This method is designed to be implemented in a loop, during successive “time steps”.
• trajectory tracking is provided to be operated autonomously by the computer 13, but that it must also be able to be interrupted at any time to allow the driver to regain control of the vehicle. It must also be able to be used as an aid for the driver when the latter is holding the steering wheel but is not exerting the torque required on the steering wheel to avoid the obstacle.
• the idea of the first part of the presentation is in fact to describe the way in which it is possible to synthesize a controller which, once implemented in the computer 13, will make it possible to control the vehicle in such a way that it follows the avoidance trajectory T0 in a stable and efficient manner.
• This model is an improved bicycle model.
• oo f is used to model the dynamics of the curvature of the avoidance trajectory T0 to be followed (which is calculated elsewhere and is therefore already known).
• p ref of curvature of the avoidance trajectory T0 makes it possible to take account of the trajectory of the vehicle (and therefore of the curvature of the road) in the modeling of the dynamic behavior of the vehicle.
• this model does not in itself make it possible to limit the steering angle and the steering speed of the front wheels 11 of the vehicle.
• such a limitation is particularly important to ensure that the driver of the vehicle is able to regain control of the vehicle at any time.
• the coefficient u is a constant which represents the steering speed not to be exceeded. This constant is defined either by calculation or at the end of a test campaign carried out on a test vehicle. It is for example equal to 0.0491 Rad/s, which corresponds to 0.785 Rad/s at the level of the steering wheel (i.e. 45°/s) if the steering reduction coefficient is equal to 16 .
• the coefficient h is a constant which represents the steering angle not to be exceeded. This constant is defined either by calculation or at the end of a test campaign carried out on a test vehicle. It is for example equal to 0.0328 Rad, which corresponds in our example to 0.524 Rad at the steering wheel (i.e. 30°).
• a controller K which makes it possible to calculate an unsaturated steering angle dk setpoint.
• This controller K advantageously comprises an adder which outputs the unsaturated steering angle setpoint dk and which receives as input a state feedback term (coming from a state feedback block K p ) which depends on the state of the vehicle, and a saturation compensation term (resulting from a saturation compensation block K a ) which depends on the saturated steering angle setpoint ⁇ ref calculated at the previous time step.
• the saturation compensation term makes it possible to reinforce the stability of the controller in nonlinear mode, that is to say in cases where the control of the power steering actuator is saturated in amplitude or in speed.
• the block SAT1 represented in FIG. 3 illustrates the saturation in amplitude of the unsaturated steering angle dk setpoint. It receives as input the output of the controller K and it provides as output a semi-saturated steering angle setpoint ⁇ sat . We observe that this block operates in an open loop.
• the set of blocks SAT2 illustrates the saturation in speed of the semi-saturated steering angle setpoint ⁇ sat . It receives this semi-saturated setpoint as input and it supplies the saturated steering angle setpoint ⁇ ref as output. We observe that it is a closed loop.
• this set of blocks SAT2 corresponding to a “pseudo rate limiter” function, an adder is therefore provided at the input which makes it possible to calculate the difference D between the semi-saturated steering angle setpoint ⁇ sat and the saturated setpoint steering angle ⁇ ref at the previous time step.
• It comprises a multiplier block making it possible to multiply this difference by a parameter l, a saturation block making it possible to not exceed the derivative of the saturated steering angle setpoint ⁇ ref according to the equation Math2 and an integrator block making it possible to obtain the saturated steering angle setpoint ⁇ ref (via a Laplace transform).
• the block P sy s represents the open loop system which describes the dynamics of the vehicle and the behavior of the power steering actuator. It is observed that this block receives as input a disturbance w and the saturated steering angle setpoint d GQ ⁇ . It outputs an output vector y and an error z.
• this error z to be minimized is a function of the trajectory tracking error e yi _ and of the relative heading angle between the longitudinal axis A1 of the vehicle and the tangent to the trajectory d avoidance T0 (denoted below heading error Yi_), which we know should be minimized.
• Yi_ heading error
• the term ay is an adjustment coefficient which makes it possible to adjust the error which it is primarily desired to minimize (heading-angle tracking error or position tracking error) . It will be seen later in this presentation how the value of this adjustment coefficient is chosen. This choice of error z at the output makes it possible to guarantee both correct position tracking and correct heading tracking.
• the output vector y is here considered equal to a preliminary state vector x p , all the elements of which can be measured or estimated while driving, and which can be written in the form:
• the objective is then to determine the form of the controller K which is a state feedback regulator making it possible to calculate the unsaturated steering angle setpoint dk on the basis of the preliminary state vector x p .
• the state variable p ref depends on the curvature of the avoidance trajectory T0.
• the dynamics (ie the derivative) of the curvature is assumed to be known (since the avoidance trajectory T0 is known).
• the curvature compensation is treated in a more precise way (via the knowledge of the dynamics of the curvature) than it would be if we used a more classic method (of the "FeedForward” type) which considers static or slightly varying curvatures.
• u p is the saturated control input, here equal to the saturated steering angle set point ô ref ,
• UK is the unsaturated command input, here equal to the unsaturated steering angle set point dk
• the controller K for which we are looking for the optimal gains that meet our control criteria, which is defined as a static state feedback regulator, can be expressed in the form:
• x is the state vector increased by the saturated steering angle setpoint ⁇ ref which will be considered later in this presentation. Its parameters will be called state variables.
• U K is, in our application, considered equal to the unsaturated steering angle dk setpoint.
• I is the identity matrix
• satro(f) a saturation function denoted satro(f)
• two polyhedra can be defined, one of which, denoted Si(x,q), models the behavior of the saturation in amplitude and the other, denoted 82(c,Yi ,n) models the behavior of velocity saturation.
• Si(x,q) the behavior of the saturation in amplitude
• 82(c,Yi ,n) models the behavior of velocity saturation.
• the matrix G1 could be considered equal to the product of the matrix K by a scalar ak.
• the math equation 21 could be rewritten in a form involving the term (1-ak), which will therefore constitute an adjustment of the allowed overshoot.
• This overshoot could for example be set to 10%. To adjust this excess, it will be necessary to do road tests.
• this matrix G1 will not be a function of the matrix K. It will have to be optimized not by road tests, but by calculations, for example by the method of linear matrix inequalities. In this way, the conservatism of a solution such as the one described in the previous paragraph will be avoided.
• this two-dimensional representation would only be valid if the state vector x comprised only two state variables, one forming the abscissa and the other the ordinate of each of these graphics.
• the state vector comprises eight state variables.
• a representation of the invention should therefore be drawn in eight dimensions.
• the Math equations 21 and 22 are two saturation models, respectively in amplitude and speed, which, as long as they remain valid within the meaning of the Math equation 23, make it possible to ensure that the equations Math 24 are too.
• the closed-loop equation Math 12 and the representation of the Psys system represented in FIG. 3 make it possible to write:
• the matrix Cz is then expressed as follows:
• Equation Math 27 where the term w represents the curvature of the avoidance trajectory, the maximum value w max of this curvature is known (since we know the dynamic limits of the vehicle and therefore the curvature maximum that the vehicle can follow in complete safety and in fact taxable by trajectory planning). Therefore, the parameter o can be defined as:
• the TAES time corresponds to the maximum activation duration of the AES function, which is generally between 1 and 3 seconds, and corresponds in particular to the duration of the avoidance maneuver.
• k is the understeer gradient, which is calculated as follows:
• V t ) x T Px
• n g( ) c t R gc
• the matrices P and P Y are positive and symmetric definite.
• W 2.
• the basin of attraction e is therefore a space of stability (or invariant space) of the system considered.
• it is a space within which the trajectories of the state variables (i.e. the components of the state vector x) remain, insofar as they have been initialized in this space (even if the system is subject to disturbances and saturations of the actuators).
• controller K is then synthesized in such a way as to meet three objectives.
• the first objective is that in the absence of disturbance, the controller K guarantees that the trajectories of the state variables of the closed-loop system remain in the basin of attraction e (which ensures stability) and converge asymptotically towards the origin (which ensures performance), in particular within a predefined time.
• the second objective is that in the presence of disturbance, the controller K guarantees that the trajectories of the state variables of the closed-loop system remain in the basin of attraction e (which ensures stability) whatever the disturbance w, provided that the latter is limited in energy (within the meaning of equation Math 27).
• this case has been considered where a disturbance occurs.
• the space of the initial conditions of the system, denoted Eo are necessarily contained in the estimate Ei of the basin of attraction e.
• the trajectory T2 of the state variables, when it starts from any initial situation contained in the space Eo remains well contained inside the basin of attraction e.
• the third objective is that in linear mode (without saturation in amplitude and in speed), the controller K guarantees the performance of the system, which then takes precedence over stability, by ensuring that the synthesis of the norm H is less than a predetermined scalar.
• y is the norm H of the transfer function of w -> z.
• the method used here is preferably the use of Finsler's lemma applied to linear matrix inequalities (LMI) to reduce conservatism (LMI relaxation), this Finsler's lemma being applied in particular to the both stability (Math equation 33) and performance (Math equation 35). It is thus carried out on the basis of convex optimization criteria under constraints of linear matrix inequalities (the linearity of the terms of the matrices used ensuring that the mathematical problem can be solved without requiring too great a computational load).
• the objective is more precisely to optimize the gains of the closed loop defined by the controller K by playing on the choice of the poles.
• the matrices R, Q, Q, Q Y , Li, L2, T 1 , T2 are expressed here in the following form:
• J is a non-singular matrix
• the controller K is defined by the equation:
• K R.Q ⁇ 1
• the speed V of the vehicle is assumed to be constant (therefore all the matrices of the system are considered constant).
• the fifth inequality Math 41 guarantees the performance (within the meaning of the H 00 standard) of the closed-loop system when the system is subjected to a disturbance and when the output of the control K is not yet saturated (nor in amplitude , nor in speed, i.e. when the steering instructions ô ref and dk are equal). This inequality ensures that the third condition is satisfied.
• controller K can be obtained depending on the chosen value of a y .
• the adjustment coefficient a y when it has a reduced value, makes it possible to obtain a controller K which minimizes the position tracking error (zone ZC1).
• the controller K when it has a high value, it makes it possible to obtain a controller K which minimizes the heading tracking error (zone ZC2).
• zone ZC3 Between these extreme values, it is possible to make a compromise between position tracking and heading tracking (zone ZC3).
• the adjustment coefficient a y will be chosen with a reduced value (less than 20), to minimize the position tracking error and ensure that the vehicle follows the avoidance trajectory T0.
• the adjustment coefficient a y will be chosen with a high value (greater than 20), to minimize the heading tracking error and ensure that the vehicle is positioned parallel to the road.
• the high value of the adjustment coefficient a y is such that the saturated steering angle setpoint ⁇ ref transmitted to the power steering actuator will help the driver stabilize the vehicle.
• the high value of the adjustment coefficient a y at the end of avoidance ensures that the saturated steering angle setpoint ⁇ ref does not unnecessarily bring the vehicle back onto the avoidance trajectory when the latter has been exceeded by a great deal (which would otherwise be destabilizing for the driver).
• the proposed method therefore proves to be effective when it comes to determining the steering wheel angle at each instant in a reasonable way (and manageable by a driver with average skills) and in a way that can be carried out by the actuator.
• controller K is recalculated using the following equation:
• the computer can be used to calculate the unsaturated steering angle setpoint dk using the following formula:
• the controller K found during the design of the vehicle can then be implemented in the computers 13 of the motor vehicles 10 of the range.
• the computer 13 is here programmed to implement this method recursively, that is to say step by step, and in a loop.
• the computer 13 checks that the autonomous obstacle avoidance function (AES) is activated and that an obstacle avoidance trajectory has been planned.
• AES autonomous obstacle avoidance function
• the computer 13 will then seek to define a steering setpoint for the conventional steering system, namely a saturated steering angle setpoint ⁇ ref , making it possible to follow this avoidance trajectory T0 as well as possible.
• the computer 13 uses the controller K stored in its memory. This controller K will therefore make it possible to determine, during a first step, the values of the unsaturated steering angle dk and saturated ⁇ ref values.
• controller K is synthesized taking into account the saturation functions, so that the setpoints are perfectly adapted to the chosen saturation model.
• the saturated steering angle setpoint ⁇ ref will then be transmitted to the power steering actuator to steer the wheels of the motor vehicle 10.
• the first step E1 occurs when the AES function is activated.
• the computer 13 acquires the initial state of the vehicle, defined by the state vector x (denoted, at this initial instant, xo).
• the computer can, with the aid of the controller K and taking into account the avoidance trajectory to be followed, determine a saturated steering angle setpoint ⁇ ref .
• This instruction is sent to the power steering actuator of the motor vehicle 10, which reacts so that the vehicle can be defined by a new state vector x.
• the method for calculating the saturated steering angle setpoint ⁇ ref is then repeated in a loop, at regular time intervals, so that the vehicle follows the avoidance trajectory as well as possible.
• the computer 13 checks whether it is in the presence of an anomaly requiring the deactivation of the AES function.
• the computer checks whether two cumulative conditions are fulfilled.
• the first condition is that the initial state vector xo does not belong to the space Eo of the initial conditions of the system.
• the second condition is that the state vector x (of the considered time step) does not belong to the estimate Ei of the basin of attraction e.
• step E5 the computer decides to maintain the autonomous obstacle avoidance AES function in the activated state, in order to avoid the obstacle.
• the computer could deactivate the AES function on the basis of the first condition only. It is in fact probable, when this first condition is met, that it is not possible to steer the vehicle so that it follows the avoidance trajectory in complete safety.
• the second condition makes it possible to wait to detect a real instability of the control of the vehicle before deactivating the AES function. It can indeed happen, when the initial state vector is outside the space Eo, that the control of the vehicle remains stable, for example under the action of the wind or because the driver has not let go of the steering wheel. and participates in avoidance.
• the method can be applied to other types of fields in which a particular trajectory must be followed, for example in aeronautics or robotics (in particular when the robot is small and it is necessary to saturate one of his orders).

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• Engineering & Computer Science (AREA)
• Automation & Control Theory (AREA)
• Transportation (AREA)
• Mechanical Engineering (AREA)
• Human Computer Interaction (AREA)
• Chemical & Material Sciences (AREA)
• Combustion & Propulsion (AREA)
• Steering Control In Accordance With Driving Conditions (AREA)
• Control Of Driving Devices And Active Controlling Of Vehicle (AREA)
• Control Of Position, Course, Altitude, Or Attitude Of Moving Bodies (AREA)
• Control Of Vehicle Engines Or Engines For Specific Uses (AREA)

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• 2021
  • 2021-04-06 FR FR2103505A patent/FR3121410B1/fr active Active
• 2022
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  • 2022-03-09 WO PCT/EP2022/056097 patent/WO2022214268A1/fr active Application Filing
  • 2022-03-09 EP EP22710413.0A patent/EP4320026A1/de active Pending
  • 2022-03-09 CN CN202280026942.XA patent/CN117120323A/zh active Pending
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