• 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:
    SYSTEM AND METHOD OF ESTIMATING THE STEERING STYLE OF A VEHICLE WITH MOTOR. The present invention relates to a system for estimating the driving style of a motor vehicle (100) comprising a measuring device (1) of a kinematic signal representative of the trend in the amount of movement of a motor vehicle (v ( t)). The system is characterized by the fact that it still comprises a low-pass filtering module of the kinematic signal (8) configured to provide a corresponding filtered reference signal, associated with the reference trend of said quantity (VF (t)). In addition, the system comprises a kinematic signal and the filtered reference signal processing module (2), configured to provide an indication of the driving style depending on the comparison between the motor vehicle's movement trend and the reference trend .
    公开号:BR112012020504B1
    申请号:R112012020504-8
    申请日:2010-12-20
    公开日:2021-02-09
    发明作者:Sergio Matteo Savaresi；Vincenzo Manzoni；Andrea Corti
    申请人:Drive2Go S.R.L.；
    IPC主号:
    专利说明:

    TECHNICAL FIELD OF THE INVENTION
    [001] The present invention relates to the driving style estimation techniques adopted by a motor vehicle driver. KNOWN TECHNIQUE
    [002] Several estimates of the driving style are from motor vehicle drivers, to be implemented with reference to the fuel consumption estimate, the safety of the driver's behavior or in order to generally assess their driving skills. According to some techniques, the estimate is also made in order to advance with an automatic control of some aspects of the direction of the vehicle with engine.
    [003] Patent application EP-A-1780090 describes a method for defining the driving style of a motor vehicle driver, which provides the monitoring of several characteristics including: the number of horn activations, the speed variation, the variation of the pedal position, the angular speed determined by the movements of the steering wheel. The estimate is then based on the calculation of differences between these monitored characteristics and the predetermined limit values.
    [004] Patent application EP-A-0777071 describes a method of controlling the automatic transmission of a vehicle depending on the driver's steering style based, inter alia, on the following information: opening of the fuel valve, vehicle speed , angular speed of the motor.
    [005] Patent application EP-A-1498297 describes a method of estimating fuel consumption which serves to monitor numerous characteristics, among which are: a sign of speed of rotation of the steering wheel, a sign of speed of rotation the geometric axis of the engine, a coolant temperature signal, a fuel temperature signal. BRIEF SUMMARY OF THE INVENTION
    [006] The depositor noted that traditional techniques for estimating driving style are too complex and costly from a computational point of view, and they adopt criteria for classifying the driver's style based on predefined standards which often seem unrealistic. .
    [007] The objective of the present invention is to propose techniques for estimating the driving style of the vehicle with an engine that combine not so great complexity and that at the same time lead to a definition of the guide style that is generated in a realistic and reliable way .
    [008] The purpose of the present invention is achieved by a system of estimating the driving style as defined according to claim 1. Preferred modalities are defined by pending claims 2 to 11. The subject of the invention is also a method of estimating the driving style as defined in claim 12. BRIEF DESCRIPTION OF THE DRAWINGS
    [009] The additional features and advantages of the invention result from the following description of a preferred embodiment and its variations, provided in an exemplary manner with reference to the attached drawings, in which:
    [010] Figure 1 shows schematically an example of an estimation system with the driving style of the driver of a motor vehicle;
    [011] Figure 2 shows a flow chart that refers to a method of estimating the driving style for motor vehicles, which can be implemented using the estimation method described with reference to figure 1;
    [012] Figure 3 shows a curve referring to a measured speed signal and a curve referring to a signal obtained through low-pass filtering of the measured speed;
    [013] Figure 4 shows a curve referring to an estimate of the energy used by the motor vehicle and a curve referring to the reference energy;
    [014] Figure 5 shows a basic diagram of a pre-treatment circuit for the speed and acceleration signals according to the particular mode;
    [015] Figure 6 shows a state diagram referring to an example of a method of automatically revealing the stops and starts of the motor vehicle;
    [016] Figure 7 shows a flow chart referring to another method of estimating the driving style for motor vehicles which can be implemented using the estimation system described with reference to figure 1;
    [017] Figures 8a, 8b and 8c show curves referring to various kinematic characteristics associated with the movement of the vehicle;
    [018] Figure 8d shows acceleration samples and pull-out values for the motor vehicle, represented on a Cartesian plane reference system;
    [019] Figure 9 shows an example of a screen view on a smartphone on the results of the estimation methods mentioned above. DESCRIPTION OF THE MODALITIES OF THE INVENTION
    [020] Figure 1 shows an example of an estimation system with 100 driving style for the driver of a motor vehicle. In particular, the estimation system 100 comprises a measuring device 1 and a computer system 2 capable of communicating, for example, via a communication port device 3 (GTW). For example, the estimation system 100 is also provided with a device for presenting or reporting 4 the results of an performed estimate.
    [021] Measuring device 1 is preferably mounted on the motor vehicle and allows the supply of electrical signals, in particular digital signals, representative of the kinematic characteristics associated with the movement of the vehicle itself. The digital signals emitted by the measuring device 1 can be a signal about the speed of the motor vehicle and, for example, also an acceleration signal from the motor vehicle itself. Alternatively, the measuring device 1 can provide the electrical signal in an analogous way, which can be converted into a digital signal in order to allow, for example, numerical elaborations made through the software. The digital conversion can also be done, for example, by the communication port device 3.
    [022] According to a specific modality, the measuring device 1 may comprise a speed transducer and an acceleration transducer for the motor vehicle. For this purpose, the apparatus for acquiring signals 1 is, for example, equipped with an inertia measurement system 5 (IMU), known by itself (known in the field by the name of "inertial platform"), which comprises a computer and motion sensors capable of providing the speed signal and the acceleration signal of the motor vehicle (in direction, direction and amplitude) and optionally, even other signals that describe the movement of the motor vehicle.
    [023] In addition, the measuring device 1 can also advantageously be equipped with a positioning device 6 (GPS) as a receiver that acts in a satellite positioning system such as, for example, the GPS system (GPS tracking system). Global Positioning). The GPS6 receiver is capable of providing a corresponding speed signal in addition to the position of the motor vehicle.
    [024] With reference to computing device 2, that is, according to a modality, a data processing unit or a computer (equipped with memories, processing units and interfaces with the outside world) capable of receiving signals from the measuring device 1 and to carry out the computation and elaboration operations in order to estimate the driving style of the motor vehicle adopted by a private driver.
    [025] In particular, the data processing unit 2 also comprises a calculated data memory 7 (MEM) and a plurality of modules, preferably a software-type module and a low-pass filter 8 (LPF), a first estimation module 9 (EST1-MOD) and a calculation module 10 (CLC-MOD). As will be explained later, the first estimation module 9 is capable of estimating the driving style based on the energy used or consumed by the motor vehicle. According to another modality, the data processing unit 1 is also equipped with a second estimation module 11 (EST2-MOD) configured to perform a guide style estimate based on the safety of the passengers of the motor vehicle.
    [026] The data processing unit 2 can be mounted on the dashboard of the motor vehicle or it can be remote and from there reside, for example, in a monitoring station. When mounted on the motor vehicle, the data processing unit 2 can be connected to the measuring device 1 via cables or via the communication port device 3, which guarantees a connection with a low radio frequency band (such as, for example, the connection based on the Bluetooth protocol) with the data processing unit 2 and with the inertia measurement system 5 and the GPS receiver 6.
    [027] Advantageously, the data processing unit of the 2 can be equipped with a cellular transmission device capable of communicating via a mobile phone system with a monitoring station. Alternatively, if the data processing unit 2 is arranged on the monitoring station, such a cell phone transmission device allows communication with another suitable cell phone transmission device arranged on the motor vehicle panel. Advantageously, the processing device 2 can be a smartphone.
    [028] Reporting device 4 may reside preferentially on the dashboard of the motor vehicle and in this case, it coincides advantageously with processing unit 2. Reporting device 4 may also reside on the monitoring station or it can reside on the motor vehicle and be a device separate from the processing device 2. In any case, the reporting device 4 preferably comprises a screen capable of viewing the information that allows the driver to know the result of the estimate of his own driving style. Figure 2 shows a flowchart 200 that refers to a method of estimating the driving style of the motor vehicle, which can be, for example, implemented using the estimation system described with reference to figure 1.
    [029] After a symbolic pull-out phase, the method provides a measurement phase 201, in which the inertia measurement system 5 provides an electrical and digital signal representative of the development of the kinematic characteristics associated with the movement of the motor vehicle, such as , for example, the speed amplitude v (t) assumed by the motor vehicle along a measurement path. The speed signal v (t) can also be provided alternatively by the GPS receiver 6. A possible definition criterion and the automatic calculation of the duration of the measurement path considered for the estimate, will be described hereinafter.
    [030] The electric and digital signal of speed v (t) is made available to data processing unit 2, through the communication port device 3. Figure 3 shows a curve v (t) that corresponds to a development specific velocity, measured in an experimental way. The curve v (t) of figure 3 has extensions that correspond to the sudden variations in speed. The digital values that correspond to the speed signal v (t) are stored in memory 7.
    [031] In a filtering phase 202, the processing unit 2 processes the digital values associated with the speed signal v (t) by performing a low-pass digital filtering, thereby providing a filtered digital signal .
    [032] The filtered digital signal corresponds to a filtered speed vF (t), shown as an example in figure 3 and indicative of the reference development for the speed. The filtered speed curve vF (t) in figure 3 does not have the sudden and pre-sent variations in curve v (t). It is considered that the filtering phase eliminates these sudden variations in the speed signal, which are caused by an imprudent way of driving and which, therefore, allows a significant reference signal to be obtained. For example, these sudden variations could occur due to the fact that the driver did not immediately notice that the traffic light is yellow and suddenly slowed down.
    [033] With reference to low-pass filtering, it can be done through the filter module 8 of figure 1 by means of well-known digital filtering techniques that employ, for example, a FIR filter (Finite Pulse Response), or preferably, an IIR (Infinite Pulse Response) filter, for example, of the Butterworth type and in a suitable order. Alternatively, it is also possible to make the filtering of the speed signal analogous, if available, by means of an analogous low-pass filter.
    [034] With reference to the particular case on the estimation of the driving style of bus drivers, it was realized in an experimental way that the preferred values for a cutoff frequency fc associated with low-pass filtering are, for example, comprised between 0.04 Hz and 0.06 Hz, in the case of a second-order Butterworth IIR filter. A particularly preferred value of the cutoff frequency fc equal to 0.05 Hz was obtained experimentally by analyzing the behavior of several bus drivers, over the same distance and considering a second order Butterworth filter. The particular value of 0.05 Hz was obtained by observing the frequency spectrum of the entire parking test and choosing the value reached by the majority of prudent drivers.
    [035] Based on a comparison between the speed signal of v (t) and the filtered signal vF (t), it is possible to provide an indication of the driving style of the motor vehicle. In particular, this comparison and the related indication of the driving style are based on a calculation of the energy used by the motor vehicle in the measurement path.
    [036] More deeply, in a first 203 calculation phase, a calculation is made of an estimate of the energy E1 (t) used by the motor vehicle in the measurement path, using the speed signal v (t ) (preferably in a digital form) and in a mathematical model of the motor vehicle. The calculation of the energy E1 can be done by the calculation module 10 of figure 1. With reference to the mathematical model to be used, we will consider that the longitudinal force Fmotor provided by the motor of the motor vehicle could be, for example, expressed as: Fmotor (t) = Ma (t) + 1/2 pSCxv (t) 2 (1) in which: • M is the mass of the motor vehicle; • a (t) is the longitudinal acceleration of the motor vehicle; • p is the density of air that depends on the conditions of pressure, altitude and temperature; • S is the front surface of the motor vehicle; • Cx is the aerodynamic coefficient describing the shape of the vehicle with an engine; • the term M a (t) represents the inertial force of the motor vehicle; • the term 1 / 2pSCxv (t) represents the aerodynamic force.
    [037] In formula (1), terms referring to the braking force and the force associated with the inclination of the area covered by the trajectory of the motor vehicle are not indicated, since they are not considered in the tests performed. Nevertheless, the term referring to the braking force could advantageously be considered in the case of a vehicle with an electric motor, for which the energy associated with such a term is at least partially recoverable.
    [038] The Pmotor power supplied by the motor is given as:

    [039] The first term of formula (2) is the power of inertia, while the second term is aerodynamic power. In the following tests carried out on the distances covered by the bus, it was observed that the inertia power is approximately ten times greater than the aerodynamics, when a low speed has been adopted.
    [040] The estimated energy E1 (t) is provided by the time integral of the power, in the measurement range 0-t1:

    [041] In the first calculation phase 203, calculation module 10, based on formulas (2) and (3), performs a numerical processing of the available digital data and estimates the E1 energy used by the engine of the motor vehicle. In particular, for the purposes of this calculation in addition to the velocity signal v (t) obtained through measurement, an acceleration signal is also used, representative of the acceleration a (t), which can be supplied by the inertia measurement system 5 or can be obtained by an operation of a time derivative of the speed signal v (t), in turn measured by the inertia measurement system 5 or supplied by the GPS receiver 6.
    [042] Figure 4 shows an example of the estimated energy time course E1 (t) associated with the measured energy course v (t). According to this example, the estimated energy E1 (t) consumption also corresponds to 0.428 KWh.
    [043] In a second calculation step 204, the calculation module 10 makes an estimate of the reference energy E2 (t) that represents the energy that the motor vehicle engine would have used in the case where driving the motor vehicle it would have occurred according to a reference standard associated with the filtered speed signal vF (t). For this calculation, calculation module 10 uses, for example, the following formulas:

    [044] In such formulas (4) and (5), in addition to the parameters still defined, the filtered speed signal vF (t) and its derivative aF (t) appear. Figure 4 shows an example of the time course of the reference energy E2 (t) associated with the reference speed course vF (t) obtained by filtering the measured speed signal v (t). According to this example, the reference energy E2 (t) corresponds to a consumption of 0.358 KWh.
    [045] In a comparison step 205, the first estimation module 9 compares the value of the energy associated with the measured course with the value of the reference energy and, depending on its difference, provides an indication regarding the driving style adopted by the driver . This indication can be supplied in different ways. According to an example, an estimation module calculates and makes available a first IND1 indication that represents in percentage, the difference between the estimated energy E1 consumed in the entire measurement path and the reference E2 for the same path: IND1 = (E1 ( t1) -E2 (t1)) / E2 (t1) 100.
    [046] Processing unit 2 can make this first indication IND1 available to reporting device 4 so that it can also be visible to the driver. Method 200 ends with a symbolic END stage.
    [047] Returning to measurement step 201, it should be noted that for the purpose of accuracy in estimating the energy used, it is advantageous to provide a measurement device 1 capable of providing a speed signal v (t) that has a rich content information, that is, that it has a band at least equal to the dynamics of the characteristics of the motor vehicle. It is possible that the inertia measurement system 5 is only provided with an accelerometer for measuring longitudinal acceleration, while for speed measurement only the GPS receiver 6 is available.
    [048] Still with reference to the tests carried out on buses for passenger transport, the Depositor noted that the signal representing the speed supplied by receiver 6, has a good quality information content at low frequencies and a modest quality at high frequencies , that is, it is the speed signal spectrum appears to be rich in information content up to approximately 0.05 Hz. Instead, the acceleration signal supplied by an accelerometer of the inertia measurement system 5 appears to be accurate at high frequencies, being of lower quality at low frequencies, that is, its spectrum is rich in information content above approximately 0.05 Hz. It should be understood that, for example, the accelerometer of the inertia system 5 is typically created with a MEMS (Micro Electro Mechanical Systems) technology.
    [049] In this case, the frequency separation method is applicable in order to build a speed signal which takes into account the information content supplied by both the GPS receiver and the inertia accelerometer. A basic diagram of a pretreatment circuit 300 is shown in figure 5 by means of function blocks. In any case, this method can be carried out by software, for example, in the processing unit 2 and by means of an optional frequency separation module 12 (FRSP-MOD).
    [050] The pretreatment circuit 300 comprises a first processing branch 301 of the speed signal vGPS (t) supplied by the GPS receiver 6 and a second processing branch 302 of the acceleration signal aINS (t) supplied by the accelerometer of inertia 5, a first junction 303 and a second junction 304.
    [051] The first branch 301 is equipped with an input for the speed signal vGPS (t) supplied by the GPS receiver 5 connected to the first low-pass filter LPF1 capable of eliminating noise components at high frequency. The first LPF1 low-pass filter is, for example, a Butterworth type IIR filter, of the fourth order, which in particular has a cut-off frequency of about 0.4 Hz.
    [052] The signal v'GPS (t) coming out of the first low-pass filter LPF1 is supplied to a first high-pass filter HPF1 which removes its high frequencies by returning the high frequency signal vH (t) . The high frequency signal vH (t) is supplied to a subtraction input of the first junction 303, for which the same signal v'GPS (t) coming out of the first low-pass filter LPF1 is also supplied. At the output of the first junction 303 a speed signal with frequency vL (t) is present, which is supplied to an add terminal of the second junction 304.
    [053] The second branch 302 is equipped with an input terminal for the acceleration signal aINS (t) supplied by the inertia accelerometer 5 and connected to a second low-pass filter LPF2 (for example, the same as the first LPF1 filter ) for the removal of high frequency noise, which returns a pre-filtered acceleration signal aPREF (t). The pre-filtered acceleration signal aPREF (t) is then sampled by a sample lock DS so that it has in its digital form the same sampling frequency as the speed signal vGPS (t).
    [054] A sample acceleration signal a'INS (t), which comes out of the block DS block is then supplied to a second HPF2 high-pass filter which returns the high frequency acceleration signal aH (t). This high frequency acceleration signal aH (t) is then integrated by an INT integrator which then supplies a high frequency speed signal vHNUM (t) which is added from the second junction 304 until the low frequency speed signal vL (t) thereby generating the speed signal -v- (t) obtained through the frequency separation technique described above, which can be used by the estimation method 200 of figure 2.
    [055] It should be noted that the low frequency speed signal vL (t) applied to the second junction 30 could also be obtained through another low-pass filter of the signal v'GPS (t), however, the basic diagram shown in figure 5 it is possible to use a second high-pass filter HPF2 identical to the first high-pass filter HPF1 and, therefore, this choice reduces the complexity of the numerical algorithm that implements the diagram in figure 5.
    [056] So, advantageously, the first and second high pass filters HPF1 and HPF2 have the same order and the same cutoff frequency which, for example, can be fixed and chosen based on experimental tests or can be determined choosing the value of the frequency that minimizes the difference between a first distance d1 covered by the motor vehicle and determined based on the latitude and longitude coordinates provided by the GPS 6 receiver and a second distance d2 obtained as a speed integral vGPS ( t). A possible value for the cutoff frequency of the HPF1 and HPF2 high-pass filters is between 0.06 and 0.08 Hz, preferably 0.07 Hz. The first and second HPF1 and HPF2 high-pass filters are created through a second order Butterworth filter.
    [057] Regarding the times of presentation to the driver or any other observer of the estimation of the driving style, several criteria can be adopted. For example, it is possible to provide the result of the estimate at the end of a predetermined distance covered by the motor vehicle or periodically, that is, at the expiration of a predetermined period. According to a preferred mode, the result of the estimate is provided on each of the motor vehicle.
    [058] It is considered that, based on the experimental evaluations, the choice to perform the calculations for the estimation of the direction considering the speed signal acquired between a start and a stop, allows to make reference to an average speed of the vehicle with which is correct, thus making the estimate particularly reliable.
    [059] In addition, choosing to provide the result to the driver after the stop allows the same driver a quick view of the first IND1 indication that represents his own driving style.
    [060] An example of a criterion for automatic determination of the start and stop of the motor vehicle is, therefore, the determination of a start time of the acquisition of the results of the measured speed and acceleration of a final time, in which the result of the estimate to be provided to the driver, will be described below.
    [061] The automatic determination of a stop made based on the speed signal provided by the GPS 6 receiver may have a difficulty due to the fact that the information provided by such a receiver has a quality highly dependent on the specific satellite coverage.
    [062] Reference is made to the state diagram 400 of figure 6, which defines a waiting state for start S1 and a waiting state for stop S2. Such diagram describes an algorithm which can be implemented through software, in the calculation module 10 of the processing unit 2 or by means of a state machine created through a logic. According to such an algorithm, there is a person in the waiting state for the start (cycle 401) until it does not occur that for the three subsequent measurement times, the speed of the motor vehicle is greater than an equal limit value, for example , at 0.3 m / s. In more detail, a person makes the transition 402 towards the waiting state for stop S2 when: • the measured speed value in time i-th, v (i), is greater than 0.3 m / s; and • the measured value of the speed in time (i + 1) -th, v (i + 1), is greater than 0.3 m / s; and • the measured value of velocity in time (i + 2) -th, v (i + 2), is greater than 0.3 m / s.
    [063] The i-th time is considered as a start-up time. A person then remains in the waiting state for stop S2 (cycle 403) until it does not occur that the speed measured in the three subsequent times is less than or equal to the limit value 0.3 m / s. Then the person returns (transition 404) to the waiting time for the start S1 when the following conditions occur: • the measured value of the speed in time i-th, v (i2), is less than or equal to 0.3 m / s; and • the measured value of speed in time (i + 1) -th, v (i + 1), is less than or equal to 0.3 m / s; and • the measured value of speed in time (i + 2) -th, v (i + 2), is less than or equal to 0.3 m / s.
    [064] The i-th time is considered to be a stop time.
    [065] After transition 404, the estimated value obtained is supplied to the reporting device 4 in figure 1.
    [066] In the following an example is described about an additional style of estimation method of direction, which can be used in addition to the estimation method 200, illustrated with reference to figure 2, or such additional method can be independent of the method of estimation. estimation 200. This style of additional steering estimation method can be used, for example, in order to assess how the behavior or the driver is more or less safe, especially in relation to the passengers transported.
    [067] Reference will now be made to figure 7, which shows a flowchart 500 of the said style of additional method of estimating direction. In a first phase 501, an ares (t) acceleration signal from the motor vehicle is acquired, which represents the amplitude of a resulting acceleration that corresponds to the sum of the vector of the longitudinal acceleration along (t) and the lateral acceleration alat (t). In particular, the signal resulting from the acceleration ares (t) can be obtained through the implantation, for example, in the calculation module 10, of an algorithmic software that corresponds to the following formula:

    [068] Regarding the determination of the longitudinal acceleration signal along (t), it can be obtained directly from the inertia measurement system 5, if available, or it can be determined by means of the signal derivation speed v (t) of the motor vehicle. The signal representing the lateral acceleration alat (t) can be provided by the inertia measurement system 5 or it can be obtained using the following formula, which can, for example, be implemented using software via the calculation module 10 : alat (t) = ® (t) v (t) (7) where w (t) is the angular rotation or yaw rate of the motor vehicle, provided by a suitable sensor of the inertia measurement system 5 ev (t) is the still defined speed of the motor vehicle. The speed signal v (t) can be, for example, that provided by the GPS receiver 6 or by a speed sensor of the inertia measurement system 5 or it can be obtained by integrating the longitudinal acceleration signal along of (t) provided by the inertia measurement system 5. Alternatively, the speed signal is the one obtained through the frequency separation technique described with reference to figure 5.
    [069] In a second phase 502, based on the resulting acceleration ares (t), (for example, through calculation module 10), the "pull-out" characteristic is calculated, also known as "jolt", ie , the time derived from the resulting acceleration ares (t) using the following formula:

    [070] In particular, the calculation module 10 can implement the formula (8) in a numerical way. In a third phase 503, another estimate of the steering style is made, for example, using the second estimation module 11, which takes into account both the amplitude of the resulting acceleration ares (t) and the drag (t) expressed in the relation 8. It should be noted that this estimate indicates how imprudent these driving modes are in which the modulus of the resulting acceleration ares (t) is high and / or the drag (t) is high.
    [071] Figure 8 refers experimentally to the data obtained. In particular, figure 8a shows the velocity curve v (t), figure 8b shows a longitudinal acceleration curve along (t) and a lateral acceleration curve alat (t) and figure 8c shows an acceleration curve resulting airs (t) and a start-up curve (t). In figure 8d, samples are shown measured with a second period that corresponds to pairs of normalized values for the resulting accelerations and the sprint. The digital data referring to such samples are stored in the sample memory 7. The normalization was done according to this example, considering the sample closest to the origin of the entire experimental parking test as the zero of the parking system. geometric axes of the Cartesian plane and the most remote one from the origin of the whole experimental parking test as the unit.
    [072] In addition, in the diagram in figure 8d, an A1 arc is indicated which limits a circular sector that includes the samples corresponding to a driving style considered safe. In fact, the samples within the A1 arc have as coordinates a resulting acceleration ares (t) and a sprint (t) to which a Euclidean distance, from the origin, corresponds and which is less than a normalized limit, in the example 0.7 (ie less than the radius of arc A1). It is believed that samples that have a Euclidean distance from the origin greater than the 0.7 limit correspond to an unsafe driving style.
    [073] It is also possible to divide the area of the diagram in figure 8d into a plurality of rings associated with different levels of security. It should be noted that the limit of 0.7 in an empirical value, is provided only as an example, however, from which the plausibility was evaluated in an experimental way.
    [074] The second estimation module 11 can be configured in order to perform calculations which allow to compare the Euclidean distance of each point of the plane defined by the diagram of figure 8 (which has specific values of the ares (t) and uprooted (t) coordinates ) with the limit value mentioned above. By defining with N the total number of samples, it is possible to calculate a first N1 percentage and a second N2 percentage. The first N1 percentage is given by the percentage of samples in relation to the total number N which has the distance from the origin less than the 0.7 limit. The second percentage N2 is given by the percentage of samples in relation to the total number N which has the distance from the origin greater than the limit of 0, 7. These percentages provide a second IND2 indication of the driving style estimate.
    [075] Alternatively, the direction style estimate can also be made, for example, not based on a calculation of the distance of each sample in relation to the center of the ares (t) and pull-out (t) geometric axis system ), but by calculating a center of gravity of the sample set and comparing the distance of this center of gravity with the limit indicated above. It is also possible to calculate the position of the center of gravity in a weighted way, that is, by associating a different weight to each sample depending on the fact that it is the normalized value of the resulting acceleration or the drag.
    [076] Regarding the duration of the measurement path and the times required to present the estimate to the driver, this additional estimation method can also be applied with the same considerations made with reference to method 200 in figure 2.
    [077] Figure 9 shows an example of a possible display mode on the screen of a reporting device 4 (as in particular, on the same smartphone screen with which processing unit 2 is created) of the first indication IND1, which refers to the energy used and the second indication IND2 which refers to the safety of the steering. According to this example, a horizontal bar 901 has an approximate extension of the percentages of reckless behavior, that is, it has an approximate extension of the percentage N2 described above, which then becomes, according to this example, the second indicator IND2 .
    [078] On a 902 scale, the first indication IND1 = (E1- E2) / E2 100 is also shown, which represents the portion of energy E1 used by the motor, which exceeds the reference energy E2. The first indication IND1 is also representing the fuel consumption that exceeds the consumption that would occur if the steering were carried out in prudent ways.
    [079] Advantageously, another bar 903 can be provided, for example, a vertical bar having the length that represents a moving average that takes into account the driver's behavior in relation to consumption as estimated in a plurality of time frames. measurement, between a start and a stop. Therefore, the driver, when observing his own smartphone 4, will be able to quickly know the driving style he is adopting, in order to be able to improve it by acting more carefully to reduce consumption and improve safety of any and all passengers among the items carried.
    [080] The depositor performed experimental measurements by estimating the behavior of several drivers on the same trajectory and under comparable traffic conditions, and thus, it was possible to observe how both methods described allow the identification of different driving styles, associated with different drivers.
    [081] With reference to the estimation method 200 in figure 2, it should be noted that the choice to use the comparison on which the estimate is based, the reference characteristic obtained by a low-pass filtering of a measured characteristic makes it particularly realistic to estimate made by the simple fact that she avoids considering such reckless driver behaviors, which when unavoidable, were caused, for example, by traffic, traffic lights or other factors.
    [082] The depositor understood and applied the fact that this approach seems better than an approach according to which the estimate was based on a comparison between the measured kinematic characteristic and a predefined "ideal" performance of the same kinematic characteristic, simply obtained based on the model of the motor vehicle and on a general analysis made a priori of the trajectory covered by the motor vehicle.
    [083] As previously said, the results of the estimate can also be made available by a monitoring station in which calculations and additional statistics could be performed, through the preparation of reports regarding the drivers' behavior.
    [084] It should be noted that even if, in the description provided above, reference has often been made to the bus context for passenger transport, the teachings described are also applicable to land vehicles (such as, for example, taxi, rental cars and trucks), or to marine vehicles (for example, powered planes or hydrofoils) or to aircraft (for example, airplanes or helicopters) for the transportation of passengers and / or products.
    权利要求:
    Claims (12)
    [0001]
    1. System for estimating the driving style of a motor vehicle (110), comprising: measuring device (1) of a kinematic signal representative of the trend in the amount of movement of a motor vehicle (v (t)) along the measurement path; characterized by the fact that it still comprises: low-pass filter module (8) configured to filter the kinematic signal and provide a corresponding filtered reference signal associated with the reference trend of said quantity (vF (t)); - processing module (2) comprising: - computing module (10) configured to: compute (203) according to the kinematic signal and according to a model description of the motor vehicle, an estimate of the power used by the vehicle with motor (E1) along the measurement path; compute (204) from the reference signal and the said motor vehicle description model, a power reference (E2) associated with the reference trend; first estimation module (9) configured to compare (205) said first power with the reference power and provide the indication (IND1) about the steering style depending on a compensation between the first power and the reference power.
    [0002]
    2. Estimation system (100), according to claim 1, characterized by the fact that said measuring device (1) is constructed in such a way that such quantity is the speed and the kinematic signal is a representative speed signal the trend of speed of a vehicle with an engine; the filter module (8) being configured in such a way that said filtered signal is a reference speed signal.
    [0003]
    System (100) according to any one of the preceding claims, characterized in that said measuring device (1) and said filtering module (8) are such that the kinematic signal and the are digital and in which said computing module (10) is configured to: estimate a power delivered by a motor vehicle engine based on the kinematic signal and said motor vehicle model and calculate said energy from of said power; estimate a reference power associated with said reference trend and said vehicle model with an engine, and calculate said reference energy from the reference power.
    [0004]
    4. System (100) according to any one of the preceding claims, characterized by the fact that it is configured in such a way that said indication of the direction style is provided at the end of a time interval associated with said measurement path and between a moment of starting and a moment of stopping the motor vehicle.
    [0005]
    5. System (100), according to claim 4, characterized by the fact that it comprises an automatic evaluation module (10) to automatically evaluate the stop and start times of the motor vehicle, which operates according to the signals received from the measuring device (1).
    [0006]
    6. System (100), according to any one of the preceding claims, characterized by the fact that said measuring device (1) is configured to acquire an acceleration signal representative of said acceleration of the motor vehicle, said module of processing (2) further comprising: acceleration signal derivation module (10) configured to return a start signal representative of the time variation in said acceleration signal; storage module (7) configured to store a plurality of samples each being indicative of an acceleration value and a corresponding start-up value; second estimation module (11) configured to compare the acceleration pairs and the pull-out values with the reference values and provide an additional indication of the driving style of the motor vehicle, related to safety in the motor vehicle direction.
    [0007]
    7. System (100), according to claim 6, characterized by the fact that said acceleration is the amplitude of an acceleration resulting (ares) from a vector sum of a longitudinal acceleration of the motor vehicle and a lateral acceleration of the vehicle with engine.
    [0008]
    8. System (100) according to any one of the preceding claims, characterized by the fact that said measuring device comprises at least one of the following devices: a GPS receiver, a speed sensor, an acceleration sensor, an inertia measurement system.
    [0009]
    9. System (100) according to any one of the preceding claims, characterized by the fact that the measuring device (1) is constructed in such a way as to send the measurement signals to said filter module (8) and to the said processing module (2) according to a wireless mode.
    [0010]
    10. System (100), according to any of the preceding claims, characterized by the fact that it comprises a device with a screen (4; 2) adapted to provide the first indication of the driving style and / or the said indication of the driving style a vehicle with driver engine.
    [0011]
    11. System (100), according to claim 2, characterized by the fact that the measuring device comprises: measuring device (6) structured to provide a first speed signal from the motor vehicle; accelerometer (5) structured to provide a longitudinal acceleration signal for the motor vehicle; and in which the processing module (2) comprises a frequency separation pretreatment module (300) configured for: filtering with the low-pass filter (HPF1, 303) of the first speed signal; filtering with the high-pass filter (HPF2) of the longitudinal acceleration signal; integration (INT) of the longitudinal acceleration signal resulting from high-pass filtering in order to obtain a second speed signal; combining (303; 304) the first speed signal, the second speed signal and the first speed signal as a result of the filtering, in order to obtain said representative speed signal of the motor vehicle with trend speed.
    [0012]
    12. Method for estimating the driving style of a motor vehicle, comprising: generation (201) from measurements of a kinematic signal representative of a trend in the amount of movement of the motor vehicle (v (t)) along the measurement path; characterized by comprising: low-pass filtering (202) of the kinematic signal, obtaining a corresponding filtered reference signal associated with the reference trend of said amount of movement of the motor vehicle (vF (t)); computation (203) according to the kinematic signal and according to a model of description of the motor vehicle, of an estimate of the power used by the motor vehicle (E1) along the measurement path; computation (204) from said filtered signal and said reference energy from the description model of the motor vehicle (E2) associated with the reference trend; comparison (205) of said energy with the reference energy and the provision of an indication (IND1) on the driving style depending on a trade-off between the energy and the reference energy.
    类似技术:
    公开号 | 公开日 | 专利标题
    BR112012020504B1|2021-02-09|system and method of estimating the driving style of a motor vehicle.
    CN106926845B|2019-02-12|A kind of method for dynamic estimation of vehicle status parameters
    CN105109490B|2019-12-13|Method for judging sharp turn of vehicle based on three-axis acceleration sensor
    WO2014002208A1|2014-01-03|Drive-pattern evaluation device
    CN104091079B|2017-10-31|One kind is based on MEMS IMU Bus driver driving ability assessment methods
    CN105128872B|2017-12-26|The adhesion control method of EMUs
    CN109631881A|2019-04-16|A kind of mileage optimization method based on Gsensor
    CN105015561B|2018-01-09|The adhesion control system of EMUs
    CN104417565B|2018-07-06|The system and method that sensor merges automobile speedestimate
    CN103063218A|2013-04-24|Vehicle remote monitoring and track reconstruction system and track reconstruction method thereof
    US10942521B2|2021-03-09|Method and apparatus for determining a vehicle control parameter, vehicle on-board controller and autonomous vehicle
    Derbel2015|Driving style assessment based on the GPS data and fuzzy inference systems
    JP2014038441A|2014-02-27|Drive recorder
    CN206155177U|2017-05-10|Safety system for vehicle
    JP6796527B2|2020-12-09|Vehicle condition monitoring device, vehicle condition monitoring system and vehicle condition monitoring method
    CN103241243B|2016-09-14|A kind of method and apparatus determining vehicle-state
    CN108399789A|2018-08-14|A kind of intelligent parking management system and method
    EP3018030A1|2016-05-11|Device for the detection of the attitude of motor vehicles and corresponding method
    WO2017218139A1|2017-12-21|Power estimation from sensor readings for cycling
    CN109572815A|2019-04-05|Judge the positive device and method of the steering wheel return of vehicle
    US20220041169A1|2022-02-10|System and Method for Providing an Indication of Driving Performance
    US20060276939A1|2006-12-07|Real-time determination of grade and superelevation angles of roads
    GB2579559A|2020-07-01|System and method for providing an indication of driving performance
    GB2579558A|2020-07-01|System and method for providing an indication of driving performance
    CN106384515A|2017-02-08|Vehicle speed fitting method by combining obd and sensing equipment
    同族专利:
    公开号 | 公开日
    BR112012020504A2|2020-08-25|
    ITMI20100261A1|2011-08-20|
    EP2536611A1|2012-12-26|
    CA2787456C|2017-10-03|
    US8958975B2|2015-02-17|
    WO2011101713A1|2011-08-25|
    US20120316767A1|2012-12-13|
    RU2549598C2|2015-04-27|
    CA2787456A1|2011-08-25|
    IT1398073B1|2013-02-07|
    ES2475720T3|2014-07-11|
    EP2536611B1|2014-03-26|
    RU2012140025A|2014-03-27|
    引用文献:
    公开号 | 申请日 | 公开日 | 申请人 | 专利标题
    SU1376112A1|1986-06-13|1988-02-23|Московский Автомобильно-Дорожный Институт|Device for recording operation time of vehicle in various operating conditions|
    FR2741931B1|1995-11-30|1998-01-09|Renault|METHOD FOR CONTROLLING AN AUTOMATIC TRANSMISSION BASED ON THE DRIVING STYLE OF THE CONDUCTOR|
    NL1009775C2|1998-07-30|2000-02-01|Univ Twente|System and method for the efficient driving of a motor vehicle.|
    GB0108766D0|2001-04-06|2001-05-30|Ricardo Consulting Engineers 1|Driveability rating method and system|
    DE60316549T2|2003-07-15|2008-05-21|Miyama, Inc.|Device for determining the fuel consumption of a vehicle|
    EP1780090A1|2005-10-28|2007-05-02|CRF Societa'Consortile per Azioni|Method for defining the driving style of a vehicle driver|
    US7537293B2|2005-12-22|2009-05-26|Gm Global Technology Operations, Inc.|Vehicle stability enhancement control adaptation to driving skill|
    JP4640224B2|2006-03-15|2011-03-02|日産自動車株式会社|VEHICLE TRAVEL BENDING DETECTING DEVICE AND VEHICLE ACTION RESPONSE|
    DE102006043676A1|2006-09-18|2008-03-27|Robert Bosch Gmbh|Driver assistance system with warning function|
    JP5169011B2|2007-05-07|2013-03-27|日産自動車株式会社|Driving skill determination device, variable steering device, automobile, and driving skill determination method|
    US7831407B2|2008-07-24|2010-11-09|Gm Global Technology Operations, Inc.|Adaptive vehicle control system with driving style recognition based on vehicle U-turn maneuvers|
    US8170740B2|2008-07-24|2012-05-01|GM Global Technology Operations LLC|Adaptive vehicle control system with driving style recognition based on vehicle launching|
    DE102008041618B4|2008-08-27|2013-02-28|Ford Global Technologies, Llc|Method and device for evaluating the driving style of a driver in a motor vehicle in relation to the fuel consumption|
    JP4602444B2|2008-09-03|2010-12-22|株式会社日立製作所|Driver driving skill support apparatus and driver driving skill support method|
    RU81691U1|2008-12-22|2009-03-27|Дмитрий Юрьевич Манин|CAR DRIVING QUALITY ASSESSMENT DEVICE|
    US8170725B2|2009-02-18|2012-05-01|GM Global Technology Operations LLC|Vehicle stability enhancement control adaptation to driving skill based on highway on/off ramp maneuver|US8731736B2|2011-02-22|2014-05-20|Honda Motor Co., Ltd.|System and method for reducing driving skill atrophy|
    US9014876B2|2012-06-19|2015-04-21|Telogis, Inc.|System for processing fleet vehicle operation information|
    ITMI20130802A1|2013-05-16|2014-11-17|Novia S R L E|SYSTEM FOR THE ESTIMATE OF ONE OR MORE PARAMETERS RELATED TO THE LOADING OF A VEHICLE, IN PARTICULAR OF ITS ABSOLUTE VALUE AND ITS DISTRIBUTION|
    JP6229376B2|2013-09-02|2017-11-15|トヨタ自動車株式会社|Vehicle driving situation determination device and vehicle driving situation determination method|
    JP5861680B2|2013-09-02|2016-02-16|トヨタ自動車株式会社|Driving characteristic determination device and driving characteristic determination method|
    FR3013140B1|2013-11-13|2017-04-14|Flightwatching|SYSTEM AND METHOD FOR DIAGNOSING AIRCRAFT FAILURE|
    US9944297B2|2014-01-10|2018-04-17|E-Novia S.R.L.|System and method for estimating the driving style of a vehicle|
    RU2594046C2|2014-02-11|2016-08-10|ИНФОМОБИЛИТИ.АйТи С.П.А.|System for driving style description of vehicle drivers|
    EP3360749A4|2015-11-12|2018-10-24|Panasonic Intellectual Property Management Co., Ltd.|Driving improvement detection device and driving improvement detection system|
    US20170154476A1|2015-11-30|2017-06-01|Metal Industries Research & Development Centre|Information backing up method and system|
    RU2638327C2|2016-01-22|2017-12-13|Общество с ограниченной ответственностью "Аэростарт"|Device for determining degree of vehicle driving dynamicity|
    ITUA20162368A1|2016-04-07|2017-10-07|Drive2Go S R L|System and method of estimating an indication of the driving style of a vehicle|
    EP3367062B1|2017-02-23|2020-11-18|Tata Consultancy Services Limited|System and method for driver profiling corresponding to an automobile trip|
    US20190061769A1|2017-08-25|2019-02-28|GM Global Technology Operations LLC|System and method for driver engagement assessment|
    US11225264B2|2018-09-20|2022-01-18|International Business Machines Corporation|Realtime driver assistance system|
    RU2760043C1|2020-12-30|2021-11-22|Сергей Васильевич Сумароков|System and method for assessment of driver behavior|
    法律状态:
    2020-09-15| B06U| Preliminary requirement: requests with searches performed by other patent offices: procedure suspended [chapter 6.21 patent gazette]|
    2020-10-13| B25G| Requested change of headquarter approved|Owner name: TELEPARKING S.R.L. (IT) |
    2020-11-03| B25A| Requested transfer of rights approved|Owner name: DRIVE2GO S.R.L. (IT) |
    2020-12-08| B09A| Decision: intention to grant [chapter 9.1 patent gazette]|
    2021-02-09| B16A| Patent or certificate of addition of invention granted [chapter 16.1 patent gazette]|Free format text: PRAZO DE VALIDADE: 10 (DEZ) ANOS CONTADOS A PARTIR DE 09/02/2021, OBSERVADAS AS CONDICOES LEGAIS. |
    优先权:
    申请号 | 申请日 | 专利标题
    ITMI2010A000261|2010-02-19|
    ITMI2010A000261A|IT1398073B1|2010-02-19|2010-02-19|SYSTEM AND ESTIMATE METHOD OF THE DRIVING STYLE OF A MOTOR VEHICLE|
    PCT/IB2010/055933|WO2011101713A1|2010-02-19|2010-12-20|A motor-vehicle driving style estimating system and method|
    [返回顶部]