Method and device for timely triggering an automatic emergency braking operation and controlling the longitudinal motion of a vehicle

Abstract

The subject of this invention is a procedure for timely initiating an automatic emergency braking process for a vehicle and controlling the vehicle's longitudinal movement to avoid collisions with and / or continuously follow objects moving in front, using radar and / or cameras and / or lidar instead of directly using object acceleration data. As part of this procedure, instantaneous kinematic values ​​are measured and preset or adaptively determined relative speeds and distances are reached or maintained. If these preset or adaptively determined relative speed and distance predictions fail, the driver is warned, and then an emergency braking process is initiated or, as needed, intervention is made to follow the object. A unique feature of this invention is that the current instantaneous kinematic values ​​are used in conjunction with previously observed kinematic values, as described below: the previously observed kinematic values, together with the vehicle's desired acceleration, are used to determine hypothetical kinematic values, where the hypothetical value refers to the current processing cycle, and the previously observed kinematic values ​​refer to at least one previous processing time cycle. The hypothetical values ​​are determined to correspond to an idealized situation that takes into account the previously observed kinematic values ​​and the vehicle's own desired acceleration, and the actual warning and / or acceleration commands to be executed by the vehicle are determined based on the relationship between the hypothetical values ​​and the actual current instantaneous values. The subject matter of this invention also includes a connection device for the automatic emergency braking process of a vehicle. A typical implementation is shown in Figure 1.

Description

[0001] The subject of this invention is a program and apparatus for timely initiation of an automatic emergency braking process for a vehicle and control of the vehicle's longitudinal movement, as well as for advance warning.

[0002] In the passenger and commercial vehicle industries, the application of Advanced Driver Assistance Systems (ADAS) is becoming increasingly common. Many such systems can be found in the latest vehicles; such as Stability Support Systems (ESP – Electronic Stability Program, ESC – Electronic Stability Control), Cruise Control (CC – Cruise Control), Adaptive Cruise Control (ACC – Adaptive Cruise Control), Collision Warning and Automatic Emergency Braking Systems (FCW – Forward Collision Warning, AEBS – Advanced Emergency Braking System), Lane Departure Warning Systems (LDWS – Lane Departure Warning System), etc. Systems, such as AEBS, intervene in multiple stages. The first stage warns the driver so that the driver is aware of the perceived danger. The warning can be auditory and / or visual and / or tactile. When using AEBS, the warning stage is followed by emergency braking. The FCW system itself does not perform braking intervention. Emergency braking is prohibited during the warning stage, but the braking system can be used for moderate deceleration.

[0003] In terms of their operation, several of the aforementioned systems require vehicles to be equipped with some kind of sensor capable of sensing the environment in order to detect nearby vehicles, pedestrians, lane markings, etc. During their operation, these systems typically use simple kinematic relationships to predict the motion of their own vehicle and nearby vehicles (including pedestrians and cyclists). In the simplest case, this prediction assumes, for example, a constant speed, and on this basis, predicts the motion and position of vehicles and / or other transport participants. If the vehicle / participant in question is constantly changing its speed by decelerating or accelerating, this assumption may lead to interventions that are too early, too late, too weak, or potentially too strong compared to the expected ones. Premature or excessive intervention increases the number of false alarms and / or braking / acceleration (and also increases dissatisfaction with the system), while delayed or weak intervention can even lead to collisions in extreme cases, which could have been avoided based on the available information. Since speed is not constant under real conditions as assumed, the system's performance can be improved if the algorithm takes into account the acceleration values ​​of vehicles / participants measured or calculated by environmental sensors; therefore, the system can account for speed variations when calculating the expected motion.

[0004] The closest possible solutions are described in documents No. US7425043 B2 and No. EP 1539523 B1. The solutions described in these documents provide an assistance function to avoid or mitigate the impact of a rear-end collision with the vehicle in front. The driver is alerted and an automatic emergency braking process is initiated to avoid a collision with the vehicle in front, provided that predetermined conditions require it, but only after a predetermined warning period has elapsed.

[0005] US6470986 B2 mandates that emergency braking be performed as quickly as possible when the distance between vehicles is reduced to a critical value. This type of emergency braking uses physical means to ensure rapid deceleration of the vehicles, thereby helping to avoid rear-end collisions.

[0006] The solution described in document No. US2009 / 0210114A1 continuously assesses the vehicle's environmentally relevant data and initiates independent emergency braking in the event of an unavoidable collision. Emergency braking must be maintained until a predetermined event occurs. The predetermined event can be the progression of a predetermined period of time until a collision occurs or is actually detected.

[0007] The solution described in document No. DE10102772 A1 includes a permanent storage unit that stores data records containing actual braking and steering commands in the event of certain accidents, and has a device that can initiate emergency braking or steering operations using additional set values. This device initiates automatic braking or steering when the accident calculation algorithm reaches a set threshold.

[0008] The solution described in document No. US 2009 / 0024282 A1 discloses a preventative protection system for a vehicle, equipped with a vehicle-to-vehicle distance detection system and safety devices for mitigating the effects of a collision. Drive state sensor systems are used to collect drive state data, and this data is monitored for critical conditions of vehicle motion and dynamics during the evaluation phase.

[0009] The most effective known solutions are those that consider the vehicle's acceleration in addition to the current distance and speed of the vehicle and the vehicles ahead. Systems that do not use acceleration information cannot yet effectively handle accelerating objects.

[0010] The object of this invention is to overcome the shortcomings of known solutions and to provide a solution that can provide effective drive support and avoid linear longitudinal collisions in a simple manner, for example, by using radar and / or cameras and / or lasers or lidar, without measuring acceleration values. Our objective is to develop an advanced driver assistance system that can respond to surrounding objects in a timely manner and has an appropriate level of comfort and safety, wherein "response" can be a warning to the driver (e.g., visual and / or auditory warnings), a change in system behavior, or continuous adaptation when using closed-loop control. According to this objective, the driver assistance system described herein can simultaneously satisfy the purposes of comfort and safety.

[0011] The steps of this invention are based on the understanding that a more advantageous solution than previous solutions can be created by implementing the steps of claim 1. Common and economical environmental monitoring tools (such as radar, cameras, and lidar) cannot directly detect acceleration, and therefore, known solutions estimate the time derivative of the measured (or calculated) velocity, taking into account changes in the object's velocity. However, estimating the derivative can lead to problems: if the velocity is estimated too quickly, the calculated acceleration value may be severely affected by noise (especially when using sensors with derived velocities); if the velocity is estimated too slowly, it can also cause undesirable delays in intervention. We have recognized that these problems can be mitigated or even eliminated by not directly calculating the object's acceleration. This solution improves the efficiency of both new and existing systems.

[0012] Without measuring specific acceleration data, a hypothetical acceleration of the vehicle ahead is calculated. This hypothetical acceleration is defined as a critical acceleration value for initiating automatic emergency braking. For this critical acceleration value, emergency braking and a previous driver warning must be triggered based on other measured kinematic quantities (distance, the vehicle's own speed and the speed of the vehicle ahead, and the vehicle's own acceleration). Using dynamic tracking with memory, hypothetical distance and speed values ​​are calculated based on the hypothetical acceleration value and other actually measured kinematic quantities (distance, the vehicle's own speed and the speed of the vehicle ahead, and the vehicle's own acceleration). These hypothetical distance and speed values ​​are then compared to their corresponding current (currently measured) distance and speed values. If the values ​​are appropriate, the system will not intervene. However, if the vehicle ahead significantly decelerates, or at least does not accelerate as required, causing the hypothetical distance and speed values ​​to deviate significantly from the measured values, a warning signal will be given or action will be taken as needed.

[0013] The same principle can be applied to determining continuous vehicle control intervention signals (where the intervention signal is, for example, the vehicle's own acceleration command): calculate the hypothetical acceleration of the vehicle ahead such that it corresponds to an ideal acceleration value, at which the desired intervention should not be altered based on other kinematic quantities (distance, the vehicle's speed, the speed of the vehicle ahead, and the vehicle's acceleration). Using this hypothetical acceleration value, hypothetical distance and speed values ​​can be calculated as described above, and the vehicle control intervention signal can be increased or decreased as needed based on a comparison of these hypothetical values ​​with actual measurements.

[0014] According to the present invention, not only another vehicle, but any "object" (pedestrian, cyclist, etc.) can move or stand in front of the driver's own vehicle.

[0015] The most general embodiments of the invention are described in claim 1 and the independent claims relating to the apparatus.

[0016] According to the established objectives, the program of the present invention is used to initiate an automatic emergency braking process for a vehicle in a timely manner and control the longitudinal movement of the vehicle using radar and / or cameras and / or lidar instead of directly using object acceleration data, in order to avoid collisions with moving objects in front and / or to continuously follow moving objects in front. As part of this program, instantaneous kinematic values ​​are measured and preset or adaptively determined relative speeds and distances are reached or maintained. If these preset or adaptively determined relative speed and distance predictions fail, the driver is warned, and then the emergency braking process is initiated or intervention is performed as needed to follow the object. A unique feature of the present invention is the combined use of current instantaneous kinematic values ​​with previously observed kinematic values, as described below:

[0017] -Previously observed kinematic values, together with the vehicle's expected acceleration, were used to determine the hypothesized kinematic values.

[0018] - The assumed value refers to the current processing cycle, while the previously observed kinematic value refers to at least one previous processing cycle.

[0019] - The assumed values ​​were determined to correspond to an idealized situation that takes into account previously observed kinematic values ​​and the vehicle's expected acceleration.

[0020] - Determine the actual warning and / or acceleration commands to be executed by this vehicle based on the relationship between the assumed values ​​and the actual current instantaneous values.

[0021] The connection device according to the invention is used to promptly initiate the automatic emergency braking process of a vehicle and to control longitudinal movement. The connection device includes a power supply, environmental sensors, actuators, warning and operating devices, a control system, an interface, and a static handling predictor. A unique feature of the device according to the invention is that it includes a dynamic tracker for ideal conditions, and the dynamic tracker for ideal conditions calculates assumed values ​​through the static handling predictor. The control system uses intervention signals from a control protocol unit and is connected to the operating and warning devices and actuators in a manner suitable for signal transmission.

[0022] The invention is illustrated below with reference to the accompanying drawings, which depict possible implementations.

[0023] Figure 1 A simplified diagram of the system's theoretical layout is shown.

[0024] Figure 2 This is an example of an intervention flowchart.

[0025] Figure 3 This is an intervention flowchart as another example.

[0026] Figure 4a , Figure 4b and Figure 4c A manipulation diagram is shown as an example.

[0027] Figure 5a , Figure 5b and Figure 5c A manipulation diagram is shown as another example.

[0028] To illustrate typical applications in vehicles Figure 1 The diagram shows the control system 5, power supply 1, environmental sensor 2, and actuator 3, namely the braking system 7, engine 8, cruise control 9, steering system 10, transmission system 11, and interface 6.

[0029] Power is supplied to the control system 5 via power source 1. Environmental sensor 2 is connected to the control system 5 via a communication channel, such as a CAN bus, and provides measurement / calculation information about objects near the vehicle (e.g., longitudinal and lateral distances, speeds). Actuator 3 is also connected to the control system 5 via a communication channel, and provides information about the vehicle's status (e.g., the vehicle's speed). Actuator 3 can receive commands from the control system 5, such as braking requests to the braking system 7, torque requests to the engine 8, etc. Interfaces 6 available by default in the vehicle (e.g., indicators, windshield wiper switches, instrument panel, etc.) and system-specific warning devices 4 provide the control inputs required by the control system 5 (e.g., function on / off switches), and system-specific warning devices 4 can execute warnings (e.g., visual, audible warnings, etc.) as outputs of the control system 5.

[0030] Figure 2 The process for determining the command that allows the initiation of emergency braking or warning operations is illustrated. A dynamic tracker 19 for critical states is connected to a static predictor 16 for intervention cascades via a critical value 20 for unmeasurable states. This static predictor 16 is fed by an input 15 to the static predictor for intervention cascades. A critical value 12 for measurable states is fed to a comparator algorithm 17, which matches the output 14 from the comparator algorithm. Finally, the critical distance and / or velocity values ​​are compared with the corresponding instantaneous (currently measured) values ​​to determine the necessary intervention to be initiated. Figure 2 Additional input 13 of the dynamic tracker and additional input 28 of the comparator algorithm are shown.

[0031] A key feature of this process is that it does not use actual object acceleration information, yet it can intervene at an appropriate safety level even when an object in front of the vehicle is accelerating or decelerating significantly. The static predictor 16 for the intervention cascade calculates a critical value 20 for the unmeasurable state based on available data; in the current situation, the static predictor 16 calculates the critical acceleration value of the object in front of the vehicle, and if this value is met when calculated based on actual measured data of other kinematic quantities (distance, the speed of the vehicle and the vehicle in front, and the vehicle's acceleration), the static predictor 16 for the intervention cascade initiates emergency braking and an initial warning. If we assume that a single warning phase is applied without any general limitations, and in this example, to avoid a collision, we set the objective to match the vehicle's speed to the object's speed and the distance between the vehicle and the object to a preset distance at the end of the intervention, and we assume constant acceleration, then the following two equations can be expressed as:

[0032] v ego,I +a ego,I ·twarn +a ego,interven ·t interven =v obj,I +a obj,I ·(t warn +t interven )v ego,I ·(t warn +t interven )+1 / 2a ego,I ·t warn 2 +1 / 2a ego,interven ·t interven 2 +a ego,I ·t warn ·t interven =d rel,I +v obj,I ·(t warn +t interven )+1 / 2a obj,I ·(t warn +t interven ) 2 -d rel,desired in:

[0033]

[0034]

[0035] To apply these equations, the environmental sensors and the input 15 of the static predictor for the intervention cascade, based on system parameters, provide the following values: d rel,I v ego,I v obj,I a ego,I a ego,interven t warn d rel,desired (Note that the data may also be available in other coordinate systems or other formats.) As mentioned above, if a solution exists that satisfies the conditions, this set of equations can be used to calculate the assumed value of a. obj,IThis means that the critical object acceleration can be calculated. The critical object acceleration, as the critical value 20 for the unmeasurable state, and the additional input 13 of the dynamic tracker provide the information needed for the dynamic tracker 19 for the critical state. The dynamic tracker 19 is also equipped with memory (and is therefore dynamic rather than static), so that for the purpose of determining the critical value 12 for the measurable state, i.e., in this case, for determining the critical velocity and / or distance values ​​associated with the object, the dynamic tracker 19 can store and use the data measured or calculated in the current processing loop, along with the corresponding previous values. This allows "danger" zones and "safe" zones to be defined within the velocity and distance ranges, and these zones are separated by critical values. For this determination, the additional input 13 of the dynamic tracker can provide both the vehicle's velocity and acceleration values ​​and the object's distance and velocity values. As the final step in this process, in addition to the critical value 12 of the measurable state, information is provided to the comparator algorithm 17 through the additional input 28. The comparator algorithm 17 determines whether to initiate a warning / emergency braking operation based on the relationship between these inputs, and sends this information as the output 14 of the comparator algorithm. (The additional input 28 of the comparator algorithm contains the measured values ​​of the measurable state (the current distance and velocity of the object), which can be directly compared with the inputs of the comparator algorithm.)

[0036] It should be noted that the equations relating to the operation of the static predictor 16 used in the intervention cascade are merely illustrative and may require other considerations known to those skilled in the art to effectively handle certain situations. However, it should be emphasized again that in Figure 2 The actual acceleration of the object is not required during the process outlined in the text (the critical acceleration is merely a hypothetical value).

[0037] Figure 3 The process of calculating continuous vehicle control intervention signals (such as acceleration commands) is shown. Figure 3 The input 31 of the static manipulation predictor and the static manipulation predictor 21 are shown. The next item in the flowchart is the ideal state dynamic tracker 22, whose inputs are the additional input 29 of the ideal state dynamic tracker and the ideal value 23 of the unmeasurable state; in this case, the output of the ideal state dynamic tracker 22 is the input of the control protocol unit 24, namely the ideal value 25 of the measurable state. The additional input of the control protocol unit 24 is the additional input 30 of the control protocol unit, and the output of the control protocol unit 24 is the output 26 from the control protocol unit.

[0038] The continuous vehicle control illustrated can be used during emergency braking, as well as during comfortable deceleration and even comfortable acceleration. An example of its use as a convenience feature is the ACC (Adaptive Cruise Control) function, which enables continuous following of another vehicle in front of the vehicle; in simpler terms, maintaining a safe distance. A key feature of the vehicle control process described herein is that it does not use actual object acceleration information, yet it intervenes with sufficient comfort and safety even when an object in front of the vehicle is significantly accelerating or decelerating. This process differs from other methods if the assumed acceleration of the object is interpreted as ideal acceleration rather than critical acceleration. Figure 2 The process shown is very similar. The task of the static handling predictor 21 is to calculate the ideal value 23 for an unmeasurable state based on available data, in this case, the ideal acceleration value of the object in front of the vehicle (if this value is satisfied when calculated based on actual measured data of other kinematic quantities (distance, the speed of the vehicle itself and the speed of the vehicle in front, and the acceleration of the vehicle itself), then the desired acceleration of the vehicle should not change). Depending on the type of handling and the desired behavior, the static handling predictor 21 can use different methods to generate its output; in some cases, it combines... Figure 2 The formalized equations can also yield satisfactory results. Based on environmental sensors and system parameters, the input 31 of the static manipulation predictor provides the following values: d rel,I v ego,I v obj,I a ego,I a ego,interven d rel,desired These markers have the meanings specified above, with the condition that the marker a ego,interven and d rel,desired This can be understood as being applicable to any maneuver, not just emergency braking. (Regarding...) Figure 2 The examples described are different, t warn It is not included in the list because the warning phase does not need to be considered in the case of continuous intervention. Based on the above, the hypothetical a can be calculated. obj,IThis means that the ideal acceleration of the object can be determined. The ideal object acceleration 23, as the ideal value 23 for the unmeasurable state, and the additional input 29 for the dynamic tracker 22 for the ideal state provide the information required for the dynamic tracker 22, which is equipped with memory (and is therefore dynamic rather than static) to store and use data measured or calculated in the current processing loop, along with corresponding previous values, to determine the ideal value 25 for the measurable state, in this case, the ideal velocity and / or distance value associated with the object. For this determination, the additional input 29 for the dynamic tracker for the ideal state can provide both the vehicle's velocity and acceleration values ​​and the object's distance and velocity values. As the final step of the process, the ideal value 25 for the measurable state and the additional input 30 of the control protocol unit provide information to the control protocol unit 24, which calculates the signal required for continuous intervention (e.g., the vehicle's current acceleration command) based on the relationship between the inputs and represents this signal as an output 26 from the control protocol unit. The additional input 30 of the control protocol unit contains measurements of the measurable state (the object's current distance and velocity), which can be directly compared to the ideal values ​​of the measurable state. Under ideal conditions, and assuming that real-life circumstances develop exactly as predicted, the calculated ideal distance and velocity values ​​of the object must match the actual distance and velocity values ​​of the object, and the intervention signal used for continuous intervention can match the expected values ​​under these conditions. However, if the actual situation deviates from the prediction, the calculated ideal distance and velocity values ​​of the object will deviate from the actual distance and velocity values ​​of the object, and in this case, the intervention signal used for continuous intervention needs to be adjusted according to the given circumstances and the magnitude and sign of any discrepancies.

[0039] A possible general-form expression for calculating the intervention signal (in this case, the current acceleration command) for continuous intervention:

[0040] a ego,req =f(d obj,M ,v obj,M ,d obj,ideal ,v obj,ideal ,…)

[0041] in:

[0042] mark meaning <![CDATA[d obj,M ]]> Current distance of the object relative to this vehicle <![CDATA[v obj,M ]]> The object's current velocity <![CDATA[d obj,ideal ]]> Ideal distance between the object and the vehicle <![CDATA[v obj,ideal ]]> Ideal velocity of an object <![CDATA[a ego,req ]]> This vehicle's acceleration command

[0043] Possible implementations of the function f(·) and thus the above expression with control parameters k1 and k2, which can be obtained, for example, through parameter tuning:

[0044] a ego,req =aego,interven +k1·(d obj,M -d obj,ideal )+k2·(v obj,M -v obj,ideal )

[0045] Among them, as mentioned above, a ego,interven This is the expected acceleration of the vehicle during the intervention period.

[0046] It should be noted that the above expression is merely an example, and control can also be implemented using another algorithm. It should also be noted that not only can the output 26 from the control protocol unit be used as an acceleration value; this value can also be, for example, the desired speed, jerk (i.e., the derivative of acceleration with respect to time), the thrust or torque applied by the motor or engine, or even a binary true-false signal, which is also... Figure 2 The activation of warning and / or emergency braking is shown in conjunction with this. In this way, it can be concluded that... Figure 3 The example shown is larger than Figure 2 The example shown is more general, and in addition to calculating the control signals used for continuous intervention, Figure 3 The example shown can also be used to initiate warning and emergency braking processes.

[0047] Figure 4a , Figure 4b and Figure 4c The diagram illustrates a maneuver where another vehicle moves in front of the current vehicle along the same path, necessitating the activation of automatic emergency braking. The labels in the diagram have the following meanings: d_rel represents the current distance between the current vehicle and the vehicle in front, v_obj represents the speed of the vehicle in front (relative to the ground), a_obj represents the acceleration of the vehicle in front (relative to the ground), and v_obj_crit and a_obj_crit represent the critical speed and acceleration values ​​calculated for the vehicle in front, respectively. Figure 4a , Figure 4b and Figure 4c A graph showing the relationship with the same manipulation is presented.

[0048] Let's assume our vehicle is traveling at 20 m / s, the vehicle in front is moving at a constant speed of 10 m / s, and the initial distance between us is 100 m. Unless the driver intervenes, this situation will become critical at some point, and the system will have to issue a warning or even brake as our vehicle approaches the vehicle in front due to the speed difference. However, the exact timing of this depends not only on the current distance and speed values ​​but also on how these values ​​change; if the vehicle in front begins to brake, our vehicle will catch up sooner, but if the vehicle in front begins to accelerate, the second vehicle will only catch up slightly later, or, depending on the degree of acceleration, will not catch up at all. Therefore, there is a critical acceleration value for the vehicle in front, and the system must issue a warning; in other words, the critical value divides the acceleration range into a "safe" zone and a "dangerous" zone. Figure 4c As shown in this example, when a_obj = a_obj_crit, the vehicle's acceleration moves from the "safe" zone to the "danger" zone at 8 seconds, so the system must issue a warning at this time.

[0049] Importantly for this invention is that if commonly used sensors are applied, the result cannot be directly determined. Figure 4c The intersection shown is due to the inability of such sensors to measure the object's acceleration. This is where the dynamic tracking described in this invention becomes important: based on a critical acceleration value (which is an assumed value) and using other measured kinematic quantities, critical velocity and critical distance values ​​can be calculated, which also divides the velocity and distance ranges into "safe" and "dangerous" zones. Based on velocity and distance values ​​that can also be measured using ordinary sensors, it can be determined whether the velocity and distance values ​​fall into the "safe" or "dangerous" zone, and the system can decide to intervene based on this determination. Figure 4b The system indicates the described critical velocity value (obtained with the help of a dynamic tracker) and the current object velocity; when these values ​​intersect at approximately 8 seconds, the system must initiate intervention.

[0050] and Figure 4a , Figure 4b and Figure 4c similar, Figure 5a , Figure 5b and Figure 5c The behavior of the program is also illustrated as an example, except that in this example, the vehicle in front is traveling at -2 m / s. 2 The rate of acceleration is increasing (i.e., it is decelerating). The markings on these graphs are... Figure 4a , Figure 4b , Figure 4cThe markers used are exactly the same. As shown in this example, due to deceleration, the intersection points of a_obj_crit = a_obj and v_obj_crit = v_obj calculated using dynamic tracking appear significantly earlier than before, around 3 seconds, and this means that the system must also issue a warning earlier due to deceleration. This aligns with the fundamental objective of this invention, which is to initiate intervention at the appropriate time even when the speed is not constant.

[0051] The solution according to the invention has several advantages. Since the assumed constant velocity does not exist under most real-world conditions, ignoring the acceleration of objects that cannot be directly measured by environmental sensors can lead to degraded system performance. The solution according to the invention can provide effective drive support and avoid linear longitudinal collisions in a simple manner, for example, by using radar and / or cameras and / or lasers or lidar, without measuring acceleration values, but without ignoring the consequences of acceleration. Even if the absolute value of any object's acceleration is large, the solution according to the invention can respond to surrounding objects in a timely manner with appropriate levels of comfort and safety, where "response" can be a warning to the driver (e.g., light and / or audible warnings), a change in system behavior, or continuous adaptation when using closed-loop control.

[0052] This invention can be implemented in other forms and procedures within the scope of protection. This invention can be applied to the automotive industry.

Claims

1. A procedure for timely initiating an automatic emergency braking process of a vehicle and controlling the longitudinal movement of the vehicle to avoid collision with and / or continuously follow a moving object in front, using radar and / or cameras and / or lidar instead of directly using acceleration data of a moving object in front, wherein, as part of the procedure, instantaneous kinematic values ​​are measured and preset or adaptively determined relative speeds and distances are reached or maintained, and if these preset or adaptively determined relative speed and distance predictions fail, the driver is warned, and then an emergency braking process is initiated or, as needed, intervention is made to follow the object, wherein the current instantaneous kinematic values ​​are used in combination with previously observed kinematic values, wherein the assumed kinematic values ​​refer to the current processing cycle, and the previously observed kinematic values ​​refer to at least one previous processing time cycle, and the actual warning and / or acceleration command to be executed by the vehicle is determined based on the relationship between the assumed values ​​and the actual current instantaneous values, characterized in that, - The previously observed kinematic values, together with the vehicle's expected acceleration, are used to determine the hypothesized kinematic values. - The assumed kinematic values ​​are determined to correspond to an idealized situation that takes into account the previously observed kinematic values ​​and the vehicle's desired acceleration. The instantaneous kinematic values ​​and the previously observed kinematic values ​​refer to the speed and acceleration of the vehicle and the distance and speed of the moving object in front, while the hypothetical kinematic values ​​refer to the hypothetical distance, speed and acceleration of the moving object in front.

2. A connection device for timely initiation of an automatic emergency braking process of a vehicle and control of the longitudinal movement of the vehicle using the procedure according to claim 1, the connection device comprising a power supply (1), an environmental sensor (2), an actuator (3), a warning and operation device (4), a control system (5), an interface (6), and a static handling predictor (21), characterized in that, The connection device includes a dynamic tracker (22) for ideal conditions.

3. The connecting device according to claim 2, characterized in that, The dynamic tracker (22) for ideal conditions calculates the assumed value through the static manipulation predictor (21), and the control system (5) uses intervention signals from the control protocol unit (24) and is connected to the warning and operation device (4) and the execution unit (3) in a manner suitable for transmitting signals.

Images