EP2086785A1 - Procédé et dispositif pour déceler le comportement de conduite d'un conducteur - Google Patents

Procédé et dispositif pour déceler le comportement de conduite d'un conducteur

Info

Publication number
EP2086785A1
EP2086785A1 EP07803253A EP07803253A EP2086785A1 EP 2086785 A1 EP2086785 A1 EP 2086785A1 EP 07803253 A EP07803253 A EP 07803253A EP 07803253 A EP07803253 A EP 07803253A EP 2086785 A1 EP2086785 A1 EP 2086785A1
Authority
EP
European Patent Office
Prior art keywords
driver
frequency
lane
steering
signal
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Withdrawn
Application number
EP07803253A
Other languages
German (de)
English (en)
Inventor
Carsten Schmitz
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Robert Bosch GmbH
Original Assignee
Robert Bosch GmbH
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Robert Bosch GmbH filed Critical Robert Bosch GmbH
Publication of EP2086785A1 publication Critical patent/EP2086785A1/fr
Withdrawn legal-status Critical Current

Links

Classifications

    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60K—ARRANGEMENT OR MOUNTING OF PROPULSION UNITS OR OF TRANSMISSIONS IN VEHICLES; ARRANGEMENT OR MOUNTING OF PLURAL DIVERSE PRIME-MOVERS IN VEHICLES; AUXILIARY DRIVES FOR VEHICLES; INSTRUMENTATION OR DASHBOARDS FOR VEHICLES; ARRANGEMENTS IN CONNECTION WITH COOLING, AIR INTAKE, GAS EXHAUST OR FUEL SUPPLY OF PROPULSION UNITS IN VEHICLES
    • B60K28/00—Safety devices for propulsion-unit control, specially adapted for, or arranged in, vehicles, e.g. preventing fuel supply or ignition in the event of potentially dangerous conditions
    • B60K28/02—Safety devices for propulsion-unit control, specially adapted for, or arranged in, vehicles, e.g. preventing fuel supply or ignition in the event of potentially dangerous conditions responsive to conditions relating to the driver
    • B60K28/06—Safety devices for propulsion-unit control, specially adapted for, or arranged in, vehicles, e.g. preventing fuel supply or ignition in the event of potentially dangerous conditions responsive to conditions relating to the driver responsive to incapacity of driver
    • B60K28/066—Safety devices for propulsion-unit control, specially adapted for, or arranged in, vehicles, e.g. preventing fuel supply or ignition in the event of potentially dangerous conditions responsive to conditions relating to the driver responsive to incapacity of driver actuating a signalling device
    • 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
    • B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
    • B60W40/08—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to drivers or passengers
    • B60W40/09—Driving style or behaviour
    • G—PHYSICS
    • G08—SIGNALLING
    • G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
    • G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
    • G08B21/02—Alarms for ensuring the safety of persons
    • G08B21/06—Alarms for ensuring the safety of persons indicating a condition of sleep, e.g. anti-dozing alarms
    • 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
    • B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
    • B60W40/08—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to drivers or passengers
    • B60W2040/0818—Inactivity or incapacity of driver
    • 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
    • B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
    • B60W40/08—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to drivers or passengers
    • B60W2040/0818—Inactivity or incapacity of driver
    • B60W2040/0863—Inactivity or incapacity of driver due to erroneous selection or response of the driver
    • 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
    • B60W2540/00—Input parameters relating to occupants
    • B60W2540/18—Steering angle
    • 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
    • B60W2540/00—Input parameters relating to occupants
    • B60W2540/26—Incapacity
    • 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
    • B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units
    • B60W30/08—Active safety systems predicting or avoiding probable or impending collision or attempting to minimise its consequences

Definitions

  • the invention relates to a method and a device for driver condition detection.
  • Driver warning in which a degree of attention of the driver is taken into account.
  • This degree of attention is derived from the steering angle, in particular from a change in the steering angle such as its gradient and / or the frequency of the angle changes and / or the distance of successive steering angle changes.
  • other factors influencing the recognition of the driver's condition are described, such as the accelerator pedal position and its change.
  • a clear improvement of the driver condition detection, in particular their reliability, is achieved by deriving the signal indicating the driver condition from a quantity which determines the frequency of the occurring extreme values in the time course of the tracking behavior of the driver Indicates the driver's representative size. It has been found that such a size in a drowsy or inattentive driver identifies a characteristic behavior that can be evaluated for driver condition detection. By evaluating this size, satisfactory results in terms of reliability and hit rate were achieved. In particular, the high rate of correct classification of a drowsy driver is advantageous. The corresponding evaluation of the quantity "time-to-line-crossing" has proved to be particularly advantageous.
  • Hit rate for recognizing the sleepy driver offers particular advantages in conjunction with driver assistance systems which are controlled as a function of the ascertained driver status, for example setting thresholds for triggering a warning to the driver or the type of warning (eg loud, quiet) depending on the driver's condition.
  • FIG. 1 shows a device for detecting driver states.
  • FIG. 2 shows a flow chart illustrating the implementation of a method for detecting driver states as
  • FIG. 3 shows a driver state detection with a neuronal classifier.
  • FIG. 1 shows a device for detecting driver states.
  • Essential components are an electronic control unit 10, which essentially consists of components such as input circuit 12, computer 14 and output circuit 16. These components are connected to a bus system 10 for mutual information and data exchange.
  • various sensors are connected, preferably via a bus system. In connection with the procedure described below, the sensor system described below is used in one embodiment. Alternatively, in another embodiment, another sensor, the corresponding size detected or from the measured variables corresponding quantities can be derived, are used. In addition, other sensors can be connected to the device whose signals are evaluated in the context of other functionalities. Via a supply line 20, a steering angle sensor 22 is connected to the input circuit 12. Via a further input line 24, a video camera 26, which detects the scene in front of the vehicle and is the basis for the recognition of lane edge markings, is connected to the input circuit 12.
  • sensors 34 to 38 are connected via the input lines 28 to 32, for example for detecting the accelerator pedal position, the extent of the brake actuation, etc., whose signals are important in an embodiment of the invention.
  • Information is output via the output circuit 16, for example via an output line 40, a warning lamp 42 or an information display 42, by means of which the driver status can be displayed.
  • an actuator 46 is controlled via an output line 24 for influencing the steering angle of the vehicle, the acceleration and / or the deceleration of the vehicle.
  • part of the device described in FIG. 1 is a driver assistance system which operates on the basis of lane recognition, such as, for example, so-called lane departure warning.
  • lane recognition such as, for example, so-called lane departure warning.
  • Such systems are known for example from the aforementioned prior art.
  • the course of the lane markings is recognized from the image of the video camera, the position of the own vehicle or the expected position of the own vehicle compared with these lane markings and issued a warning to the driver or an intervention in the steering, if Vehicle the lane leaves or threatens to leave.
  • An essential parameter, which is determined in this context, is the lateral distance of the vehicle to the lane edge marking or a boundary derived therefrom.
  • a driver state recognition is performed by checking this variable and determining the frequency of extreme values, preferably minima, in the time course of such a variable. The more frequently the minima occur, the sooner a sleepy or inattentive driver can be expected. If one compares the frequency of the minima with a limit value, then a sleepy or inattentive driver can be assumed if the limit value is exceeded. In particular, the magnitude of the detected lateral distance to the lane edge marking or the time that the vehicle has to reach the lane markings have
  • Lane limit is required (TLC, time-to-line-crossing) proven.
  • a variable representing the steering wheel movement by the driver is also used in one embodiment.
  • various sensors are available for determining such a variable, for example a sensor for detecting the steering wheel angle, a sensor for detecting the wheel positions, a sensor for detecting the yaw rate, a sensor for detecting the lateral acceleration, etc.
  • the time profile of the steering angle is detected and checked. If, first, a steering angle speed in the range of zero with a subsequent steering correction and a steering speed greater than a certain limit, it is from an inattentiveness of the driver or a Fatigue of the driver is assumed. This behavior represents a typical inattentive driver reaction that is frighteningly responsive to his wrong driving by severely engaging the steering wheel and making a steering correction. It is also essential that the driver before the sudden steering intervention shows no significant reaction to the steering wheel.
  • An improvement of the driver condition detection is achieved by not only checking the occurrence of such a behavioral pattern but also by monitoring a measurement of the frequency and / or the time interval of such a behavioral pattern and adopting a drowsy driver if such Steering corrections occur more frequently than specified.
  • Minima of the course of a distance size (lateral distance or TLC) to the lane boundary marking or a threshold derived therefrom with the same steering angle and subsequent steering correction is detected.
  • a neural classifier is used, to which the features to be evaluated are supplied.
  • An example of such a neural classifier is shown in FIG.
  • the classifier receives the above-mentioned signals, which represent themselves as functions of time.
  • not all These features are used, but only the evaluation of the extreme values in the course of a driver's lane behavior size (distance to lane marker, TLC) or a threshold derived therefrom and the frequency of constant steering wheel positions with and / or without subsequent steering correction. Already with it can be achieved considerable results.
  • the driver state is derived in a preferred manner from the frequency of the minima of the course of the curve of such a size. If the frequency of these minima exceeds a predetermined limit within a certain period of time, it is assumed that the driver is drowsy and / or inattentive.
  • FIG. 2 shows a corresponding procedure based on a flowchart.
  • the illustrated flowchart outlines the program of
  • Control unit 10 which is traversed at predetermined times.
  • step 100 the determined value (TLC) of the time duration which the vehicle requires in a substantially constant driving state is read in until the lane boundary marking or a threshold derived therefrom is exceeded. This value is used in step 102 along with the
  • step 104 it is calculated from the current and past values whether there is an extreme value of the curve of this quantity (TLC).
  • This extreme value is usually a minimum value of the value curve.
  • the calculation is done by forming differences over a predetermined number of values.
  • step 106 it is then checked whether there is a minimum of the curve. It is not distinguished in a preferred embodiment between the right and left side of the vehicle. The consideration of a vehicle side is sufficient. In another embodiment, this is sketched here Go through the program for the left and right margins, determine the minima and determine the frequency from both sides. If a minimum is present in step 106, a counter is incremented in step 108 in this case. This counter has the property of being incremented every time a minimum of the TLC curve is detected, after a certain time has elapsed
  • step 110 it is checked whether the counter reading has reached or exceeded a certain value. If this is the case, then, according to step 112, the driver state is classified as tired or inattentive and the program outlined again at the next point in time. In the case of negative answers in step 106 or 110, a classification of the driver state is carried out as attentive in step 114, whereupon the program outlined is repeated with step 100 at the next point in time.
  • the driver in addition to determining the minima in the TLC curve with the frequencies of constant steering wheel position for longer periods while driving and / or the frequencies of constant steering wheel position for longer periods during the ride with subsequent steering correction evaluated.
  • the driver is classified as inattentive when at least two of these characteristics exceed predetermined limits.
  • the non-moving of the steering wheel during longer periods of time is derived from the changes in steering angle or from changes in corresponding quantities, if they are within a predetermined tolerance band for a predetermined period of time.
  • Also particularly advantageous is a combination of the frequency of the minima of the TLC curve with the non-movement of the steering wheel during the crossing of lateral thresholds for estimating the inattentive driver state. If the vehicle exceeds the determined lane boundary marking or a threshold derived therefrom and in the meantime the steering wheel is not moved or only within predetermined tolerances, it is assumed that the driver is inattentive, if the frequency of the minima of the TLC curve has simultaneously reached or exceeded a certain size , It has been found that all of these approaches provide satisfactory classification results.
  • a further improvement of the classification results results from the use of a neural classifier, at least those mentioned above
  • Characteristics of the minima of the TLC curve and the frequencies of the constant steering positions with and without steering correction evaluates.
  • other variables are linked, for example, the steering speeds, which are determined on the basis of a steering wheel angle, a steering angle sensor, yaw rate or lateral acceleration sensor, wherein jerky steering movements, d. H. high steering speeds, is assumed by an inattentive driver.
  • the determination of a standard deviation of the lateral position of the vehicle in the lane has proven to be an important factor, as well as the known in the literature as Perclos operating variables of the accelerator pedal and / or brake pedal and / or the monitoring of the blinking frequency or the average time duration of closed eyelids.
  • Figure 3 shows the structure of a corresponding device for driver fatigue detection using a neural classifier
  • the neuronal classifier embodied in FIG. 3 is multi-layered. As an output of the level U3 of the neural classifier, a classification signal is output and output to a display and / or another control system 202, the classification signal indicating an inattentive driver.
  • a classification signal is output and output to a display and / or another control system 202, the classification signal indicating an inattentive driver.
  • Embodiment is present in a driver assumed to be tired a signal in an attentively classified driver no output signal.
  • the input variables input in the first level U L of the neural classifier are, in a preferred embodiment, the features described above under Perclos, ie a measure of the blink frequency or the time during which the lids are closed and / or a measure of the type of operation of Controls such as accelerator or brake pedal. Further, the standard deviation of the lateral position of the vehicle on the road is entered.
  • a third input is a measure of the size of the steering speeds, the fourth input represents the Frequency of the minimum of the TLC curve, while the fifth and last input is a measure of the frequency of a constant steering wheel position with and / or without overreactive steering corrections. It has been shown that the latter two features already show good classification results, while the additional three mentioned first
  • Characteristics for driver state detection represent a further improvement, but in some embodiments, these features or one or more thereof is dispensed with.
  • the signal supplied to the first input of the neural classifier 200 about the size of the blinking frequency or the duration of the closing of the eyelids is recorded by a camera 204 observed by the driver with corresponding image evaluation, a variable for said criteria is calculated and supplied to the neural classifier. Is used instead of or in addition to the blink frequency or the duration of closing the eyelids
  • Actuation speed of the accelerator pedal and / or brake pedal evaluated this is done in response to the corresponding position signals, the means 204 then transmits a size for the operating speed to the neural classifier.
  • the second input quantity represents a measure for the lateral distance of the vehicle to an edge marking.
  • the roadway is detected by means of a camera 206 and image evaluation unit mounted in the vehicle, and the position of the vehicle within the roadway is calculated.
  • the individual measurement results are then averaged in the calculation unit 208 and the standard deviation in the averaged measured values is determined and fed to the neural classifier.
  • the underlying consideration is that the more inaccurate the driver is, the greater the standard deviation, as he moves the vehicle back and forth within his lane.
  • Another input is the steering speed.
  • the steering wheel angle, the steering angle or one of the abovementioned comparable signals is determined in the measuring device 210 and the steering speed is determined in the calculation unit 212.
  • This quantity is then supplied to the neural classifier 200.
  • the frequency of the minima of the TLC curve is provided as the fourth input variable.
  • the time which the vehicle requires without steering correction for example, is determined by a driver assistance function (lane departure warning 214) to exceed the lane edge markings or a threshold derived therefrom.
  • a temporal progression is stored from these variables and the frequency of the minima of this curve is determined in the calculation unit 216. This quantity is then fed to the neural classifier.
  • a calculation unit 218 is provided, to which the steering angle or a comparable variable is supplied, on the basis of which the calculation unit 218 derives the frequency of constant steering wheel positions for longer periods of time, as mentioned above, with and / or without subsequent steering correction.
  • a corresponding quantity is fed to the neural classifier 200 as the fifth input variable.
  • the neural classifier 200 in another embodiment is supplied with values between 0 and 1, which were generated by comparing the determined variables with threshold values. So 1 means that one size is sure to come from an inattentive driver. Depending on the degree of recognition, this value is between 0 (attention) and 1 (inattention).
  • the individual quantities supplied are weighted with the weights deposited in the neural classifier and transmitted to the neurons of the second level.
  • the results of the first level (also values between 0 and 1) are combined, preferably multiplied and weighted with weights stored in the neurons in level 2.
  • the level 2 results will then be in the neuron of the
  • Level 3 is transmitted, which also combines the results of level 2 and generates there from the weight stored there, the output fatigue or inattention.
  • the weights (threshold values for the evaluation of the input variables) of the individual neurons are determined during a training. This training is based on results of test series in which the respective behavior of the evaluated operating variables is recorded with the actual driver state. By means of a learning algorithm, the weights of the neurons are optimized in such a way that the greatest possible classification success of the experimental data results.

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  • Engineering & Computer Science (AREA)
  • Transportation (AREA)
  • Physics & Mathematics (AREA)
  • Mechanical Engineering (AREA)
  • Business, Economics & Management (AREA)
  • Mathematical Physics (AREA)
  • Automation & Control Theory (AREA)
  • Emergency Management (AREA)
  • General Physics & Mathematics (AREA)
  • Chemical & Material Sciences (AREA)
  • Combustion & Propulsion (AREA)
  • Traffic Control Systems (AREA)
  • Auxiliary Drives, Propulsion Controls, And Safety Devices (AREA)
  • Emergency Alarm Devices (AREA)

Abstract

L'invention concerne un procédé et un dispositif pour déceler le comportement de conduite d'un conducteur. Un signal caractérisant le comportement du conducteur est dérivé de la fréquence des minima dans l'évolution dans le temps d'une variable qui représente le respect de la voie de circulation par le conducteur, en particulier le « time to line crossing » (temps avant coupure de la ligne), c'est-à-dire le temps restant avant que le véhicule n'empiète sur le marquage de voie.
EP07803253A 2006-11-03 2007-09-05 Procédé et dispositif pour déceler le comportement de conduite d'un conducteur Withdrawn EP2086785A1 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
DE102006051930.2A DE102006051930B4 (de) 2006-11-03 2006-11-03 Verfahren und Vorrichtung zur Fahrerzustandserkennung
PCT/EP2007/059291 WO2008052827A1 (fr) 2006-11-03 2007-09-05 Procédé et dispositif pour déceler le comportement de conduite d'un conducteur

Publications (1)

Publication Number Publication Date
EP2086785A1 true EP2086785A1 (fr) 2009-08-12

Family

ID=38582362

Family Applications (1)

Application Number Title Priority Date Filing Date
EP07803253A Withdrawn EP2086785A1 (fr) 2006-11-03 2007-09-05 Procédé et dispositif pour déceler le comportement de conduite d'un conducteur

Country Status (6)

Country Link
US (1) US20090322506A1 (fr)
EP (1) EP2086785A1 (fr)
JP (2) JP2010508611A (fr)
CN (1) CN101535079B (fr)
DE (1) DE102006051930B4 (fr)
WO (1) WO2008052827A1 (fr)

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