CN106064593A - System and method based on driver's work load scheduling driver interface task - Google Patents

Abstract

A kind of system and method based on driver's work load scheduling driver interface task is disclosed.A kind of driver interface system includes that processor, described processor are configured to: receives the driver interface task that will be performed, and optionally postpones or stop the execution of at least some of driver interface task based on driver's work load.Driver's work load is derived from the driver activity rate of change horizontally relative to the meansigma methods of driver activity level, and described rate of change is represented by the recursive calculation determinant of the covariance of described level of activation.

Description

System and method based on driver's work load scheduling driver interface task

Technical field

The present invention relates to a kind of system and method based on driver's work load scheduling driver interface task.

Background technology

Particular vehicle can provide information entertainment information, navigation information etc. to strengthen driving experience.Along with driver and these Mutual increase between vehicle, promotes that in the case of not increasing driver's work load such can be useful alternately.

Summary of the invention

A kind of driver interface system includes processor, and described processor receives the driver interface task that will be performed, And optionally postpone or stop the execution of at least some of driver interface task based on driver's work load.Drive employee Making burden and be derived from the driver activity rate of change horizontally relative to the meansigma methods of driver activity level, described rate of change passes through institute The recursive calculation determinant of the covariance stating level of activation represents.

According to one embodiment of present invention, processor is also configured to monitor described level of activation.

According to one embodiment of present invention, described level of activation is based on the data from wearable sensors.

According to one embodiment of present invention, the output of wearable sensors include physiological data, accelerometer data or Geographic position data.

According to one embodiment of present invention, processor is also configured to wireless receiving and indicates the letter of described level of activation Number.

According to one embodiment of present invention, processor is also configured to recursively calculate described determinant.

According to one embodiment of present invention, processor is also configured to before recursively calculating described determinant, will Band filter is applied to indicate the signal of described level of activation.

According to one embodiment of present invention, described determinant is recursively calculated by wearable sensors.

According to one embodiment of present invention, described determinant is recursively calculated by mobile phone.

According to one embodiment of present invention, processor is arranged in the mobile phone.

According to one embodiment of present invention, during processor is disposed in wearable sensors.

According to one embodiment of present invention, processor is also configured to be applied to band filter indicate described work The signal of dynamic level.

According to one embodiment of present invention, processor is also configured to optionally postpone in response to described or stop And produce instruction audio frequency, vision or the output of tactile alert.

A kind of method for operating driver interface system includes: optionally postpone based on driver's work load or Stoping the execution of driver interface task, wherein, driver's work load is derived from driver activity and lives horizontally relative to driver The rate of change of the meansigma methods of dynamic level, described rate of change is represented by the variance of the recursive calculation of described level of activation.

According to one embodiment of present invention, described method also includes: wireless receiving indicates the signal of described level of activation.

According to one embodiment of present invention, described method also includes: recursively calculate described variance.

According to one embodiment of present invention, described method also includes: in response to described optionally postpone or stop and Produce instruction audio frequency, vision or the output of tactile alert.

A kind of driver interface system includes that processor, described processor are configured to: based on driver activity level phase For the rate of change of the meansigma methods of driver activity level, optionally postpone the execution of driver interface task, wherein, described Rate of change is represented by the recursive calculation determinant of the covariance of described level of activation.

According to one embodiment of present invention, described level of activation is based on the data from wearable sensors.

According to one embodiment of present invention, during processor is disposed in wearable sensors.

Accompanying drawing explanation

Fig. 1 is the example block diagram of hybrid working burden estimating system.

Fig. 2 is the exemplary graph of car speed, traction and braking curve.

Fig. 3 A to Fig. 3 C is the exemplary graph of the state of motion of vehicle represented with yaw rate and yaw angle.

Fig. 4 A to Fig. 4 C is driftage, longitudinal direction and the exemplary graph of manipulation limit surplus of breakking away.

Fig. 5 is the exemplary graph of car speed, traction and braking curve.

Fig. 6 A to Fig. 6 C is the exemplary graph of the state of motion of vehicle represented with yaw rate and yaw angle.

Fig. 7 A to Fig. 7 C is driftage, longitudinal direction and the exemplary graph of manipulation limit surplus of breakking away.

Fig. 8 and Fig. 9 is finally to manipulate limit surplus and the exemplary graph of risk.

Figure 10 and Figure 11 is for high request environment and the exemplary graph of the low accelerator pedal position requiring environment respectively.

Figure 12 and Figure 13 is the rectangular histogram of the standard deviation of the accelerator pedal position of Figure 10 and Figure 11 respectively.

Figure 14 is the curve chart of the curve that the rectangular histogram with Figure 12 and Figure 13 is consistent.

Figure 15 A to Figure 15 D is accelerator pedal position, steering wheel angle, driver's control action (DCA) index and car respectively The exemplary graph of speed.

Figure 16 A to Figure 16 C is that running direction indicator activates, airconditioning control activates, the example of instrument board (IP) index is bent respectively Line chart.

Figure 17 is the schematic diagram that another vehicle followed by vehicle.

Figure 18, Figure 19 and Figure 20 are the exemplary graph of car speed, closing speed and distance travelled respectively.

Figure 21 and Figure 22 is interval and the exemplary graph of interval (HW) index respectively.

Figure 23 A to Figure 23 E is rule-based index, IP index, DCA index, synthetic work burden estimation (WLE) respectively Index and the exemplary graph of car speed.

Figure 24 is the exemplary graph for characterizing driver requested membership function based on WLE index.

Detailed description of the invention

I. introduction

Driver's work load/requirement may indicate that such vision, health and perception requirement, such as information amusement, phone, Driver is placed on primary flight activation and surmounts the activation of described primary flight and (makes by the secondary activation of perspective suggestion etc. Driver also carries out the secondary activation of suggestion in addition to carrying out primary flight activation).

Driver there may come a time when to think improperly they can primary flight discussed above activate and secondary activation it Between take sb's mind off sth.Therefore, if will estimate that driver requested operation is used for modulation communication and the vehicle system with driver System is mutual, then estimate that driver requested operation can have notable value.But, complicated driving environment may need novelty Forecasting Methodology is to estimate driver's work load.The development of the intelligence system that can carry out driver's work load identification is of value to Customization output is to the man-machine interface (HMI) of driver.

In order to estimate work load continuously, it may be necessary to design in the case of different driving environments and/or driver pre- Survey the estimator of work load.In adaptive compartment communication service can based on predicting the environment of driving demand wherein, and The value of service is sent to driver.Additionally, the driver's work load (such as, long-term characterization) characterized in a period of time is permissible It is useful.For such estimation of driver's work load can allow not only during the high workload burden time period suppression or Postpone communication technology in compartment, and in making compartment, communication technology is adapted to long drives requirement.

Specific embodiment described herein can provide for work load and estimates the method and system of (WLE).WLE can be from Observable vehicle, driver and environmental data for self adaptation real-time HMI task management perform driver's work load State estimation/classification.In some cases, WLE can use single real-time technique and/or use real-time mixed method to estimate Meter work load.Such as, based on driver, vehicle and environmental interaction, the algorithm of rule-based (rule-based) can be supplemented right Additional prediction continuously in driver's work load.WLE algorithm can be combined with special study and Computational intelligence technology to calculate And predict the WLE index (such as, representing the continuous signal of the work load load estimation for driver) collected.In some feelings Under condition, can infer the driving demand of driver from observable information of vehicles, described information of vehicles includes speed, acceleration, system Move, turn to, be spaced, instrument board and/or mutual etc. the change of console.

As example, WLE index can be used for arranging/avoid/limit/customized voice order and/or present to driver's Other tasks/information is to improve function.During needing vehicle performance operation, in dangerous driving environment, passing through instrument Plate was carried out during the high movable time period, can limit/customize/stop the customizing messages for driver.

Intelligent Hybrid algorithmic method is it is contemplated that long-term and short-term driver actions.WLE mixed method can catch driver's thing Part, situation and behavior, to adjust the communication of vehicle and driver.These and other technology described here can be driven by aid forecasting Member increase/reduce sensed condition state and existing vehicle sensors can be used.

WLE index may also allow for, based on driving demand/work load, the level of communication is presented to driver.Message prioritization Level (such as, low, high) can determine whether to post messages to driver during special time based on the burden of prediction.Also may be used Long drives based on driver requires specific HMI information is presented to driver.Selectively, mixing WLE framework can be in conjunction with GPS and digital map database are to consider road scene situation and condition.Health and physiological status about driver (include The posture (that is, position and direction) of galvanic skin response, heart rate, sight line, head or wrist and breathe) information can be as input It is attached to WLE framework extraly, for anormal detection.In other example, it was predicted that WLE index can be via audio frequency, vision Or tactile alert is sent to driver to remind driver to avoid carrying out secondary task under high workload burden.Other side Case is also feasible.

Fig. 1 is the block diagram of the embodiment of the WLE system 10 for vehicle 11.Certainly, can be at mobile device or sensor Environment realizes system 10 or one part.System 10 can include rule-based work load index subsystem 12, vehicle, drive The person of sailing and/or environment are followed the tracks of and evaluation work burden index subsystem 13, the work load index of dependence environment collect subsystem 14 and entirety collect/WLE long-term characterization subsystem 16.Subsystem 12,13,14,16 (individually or in combination) can be by reality It is now one or more controller/processing means in vehicle 11 etc., mobile device or sensor, or is distributed in theirs In combination.

Driver information and/or environmental information can (such as, may be used by subsystem 12 (such as explain in following part VII) Obtain from the controller local area network (CAN) of vehicle) be used as input information of vehicles, and export represent driver's work load based on The index of rule.Subsystem 13 (such as explain in following part III to VI) can be by driver information and/or environmental information (such as, can obtain from the CAN of vehicle) is used as input information of vehicles, and exports the one or more of expression driver's work load Chain index (such as, the manipulation limit (HL) index, driver's control action (DCA) index, instrument board (IP) index, interval (HW) index).The index produced by subsystem 13 can be used as input by subsystem 14 (such as explain in following part VIII), And output tracking (T) index.Subsystem 16 (such as explain in following part VIII) can be by rule-based index and T index It is used as input, and exports WLE index (such as explain in following part Ⅸ) and/or the long-term characterization of WLE index.

In other embodiments, system 10 can lack subsystem 12,14,16.It is to say, specific embodiment can be constructed For only producing one or more work load index.As example, system 10 may be structured to be based only upon particular vehicle information ( Hereinafter describe) produce IP index.Only exist driver's work load single measurement these in the case of, it is not necessary to collect. Therefore, in this example, WLE index is IP index.In these and other embodiment, scheduler 18 may be structured to produce The long-term characterization of WLE index.Other arrangement is also feasible.

WLE index may be sent to that scheduler 18, scheduler 18 can be implemented as one or more controller/process dress Put/etc..Scheduler 18 (such as explain in following part Ⅹ) can be used as wave filter based on WLE index prevent/delay by The information (either by wire transmission still by being wirelessly transferred) being transferred to driver arrives driver.Such as, if WLE index is more than 0.8, then can stop all information being intended for driver.If WLE index is close to 0.5, then can only stop The information of types of entertainment, etc..Scheduler 18 is also based on WLE exponent pair and the transmission being transferred to the information of driver is adjusted Degree.Such as, vehicle maintenance information, Text To Speech reading, Inbound Calls etc. can be postponed during the time period of high workload burden. Vehicle is made to be output as customized in driver, as begged in further detail below additionally, scheduler 18 can characterize based on long-term WLE index Opinion.Such as, the particular vehicle system including cruise control, adaptive learning algorithms, music suggestion, configurable HMI etc. is defeated Going out can be based on long drives requirement.

Can infer the work load state of driver from observable information of vehicles, described information of vehicles includes speed, adds Speed, brake, turn to, be spaced, instrument board is mutual etc. change.The example relevant to driver's work load load listed by table 1 Feature/standard (metric).

Table 1

Exemplary characteristics/the standard relevant to driver's work load

Standard	It is intended to the behavior effect quantified
		Average speed	Big speed increases/reduces
Maximal rate	Big speed increases
		Average time interval (interval time)	The interval reduced
Minimum interval	The minimum interval reduced
		Brake reaction time (BRT)	The BRT reduced
Braking abrupt change	The frequency increased
		Steering wheel Overturn ratio	The frequency of the increase of little reversion
Mutual (such as, pressing IP button) with IP	The frequency increased
		Traffic density	The density increased
Steering position	New driving environment
		Average speed	Big speed increases/reduces
Maximal rate	Big speed increases

Table 2a and table 2b lists the example information that can obtain via CAN known in the art/access.Following information can by with Make the input of any algorithm described here.

Table 2a

The example information that can obtain via CAN

Table 2b

The example system information that can obtain via CAN

Pull-in control system
	Anti-lock braking system
Electronic stability controls
	Adaptive learning algorithms
Relaxed by the collision of braking
	Blind spot monitors
Automatic stopping helps

II. the simple discussion that vehicle stabilization controls

The manipulation of vehicle determines turn inside diameter and the ability of manipulation.Vehicle needs by its adjacent road, four tire contact plane Face, thus maximize its handling.Exceed the tire meeting spinning of its limit of adhesion, skid or trackslip.One or more take turns Tire exceedes the condition of its limit of adhesion and is referred to alternatively as limit manipulation condition, and limit of adhesion is referred to alternatively as manipulating the limit.Once tire Reaching its manipulation limit, common driver the most no longer can control vehicle.In the case of so-called understeer, vehicle does not has Having abundant execution driver's to turn to input, the front tyre of vehicle exceedes its manipulation limit, and turning of driver ignored by vehicle Continue to request to keep straight on.In the case of so-called ovdersteering, vehicle excessively performs the input that turns to of driver, vehicle Rear tyre exceedes its manipulation limit, and vehicle continues spinning.For safety purposes, most vehicles are manufactured to grasp at it Understeer during the control limit.

In order to compensate wagon control, electronics can not control to meet or exceed the vehicle of the manipulation limit driver in the case of Stability contorting (ESC) system is designed to redistribute tire force can make vehicle ask with turning to of driver to produce effectively Seek the moment turned to being consistent.It is to say, control vehicle to avoid the situation of understeer or ovdersteering.

Since nineteen ninety-five comes out, ESC system has been implemented in various platform.Gradually carry out in vehicle year 2010, Realizing installing to vehicle year 2012, FMVSS 126 requires that ESC system is installed on gross weight grade and exists comprehensively On any vehicle of less than 10,000 pounds.ESC system can be implemented as anti-lock braking system (ABS) and full speed traction control system The extension of system (TCS).ESC system can provide driftage and lateral stability to help with the center that is intended to of driver to dynamics of vehicle Help.It also can make brake pressure (pressure applied higher or lower than driver) proportional to single wheel, thus produces effectively Moment is transported with unexpected driftage and horizontal cunning of opposing vehicle.This makes in braking, accelerates or slide period to lead for any Draw surface course changing control when manipulating the limit to strengthen.More specifically, current ESC system is by the intention path of driver and from car The actual vehicle response that set sensor is inferred compares.If the response of vehicle from be intended to path different (understeer or turn To excessively), and if requiring that vehicle is maintained on intention path and minimizes the out of control of vehicle, then ESC control by ESC controller The device processed wheel to selecting applies braking and reduces engine torque.

Can use present in the ESC system data carry out detectable limit manipulation situation, so need not new sensing Device.As example, it is considered to be equipped with the vehicle of ESC system, ESC system uses Yaw rate sensor, steering wheel sensor, laterally Accelerometer, vehicle-wheel speed sensor, master cylinder brake-pressure sensor, longitudinal accelerometer etc..As defined in ISO-8855 As, definition vehicle kinematic variables in a coordinate system, wherein, car frame fixing on car body have vertical axis upwards, Along car body longitudinal direction axle and from passenger side point to driver side lateral shaft.

It is said that in general, can from single kinematic variables (such as yaw rate, yaw angle or combinations thereof) and other Judgement in control command (such as operator brake, engine torque request, ABS and TCS) calculates vehicle feedback rank and controls. Wagon control level commands is discussed below.

Known auto model obtains dynamics of vehicle, vehicle along the yaw rate ω of the vertical axis of car body_zAnd at it The defective steering stabilizer angle beta of back axle definition_r, and meet below equation:

$\begin{array}{c}{I}_z{\stackrel{\·}{\mathrm{\ω}}}_z=-b_f{c}_f({\mathrm{\β}}_r+{\mathrm{b\ω}}_{zt}{v}_x^{-1}-\mathrm{\δ})+b_r{c}_r{\mathrm{\β}}_r+M_z\\ M({\stackrel{\·}{v}}_x{\mathrm{\β}}_r+v_x{\stackrel{\·}{\mathrm{\β}}}_r+b_r{\stackrel{\·}{\mathrm{\ω}}}_z+{\mathrm{\ω}}_z{v}_x)=-c_f({\mathrm{\β}}_r+{\mathrm{b\ω}}_z{v}_x^{-1}-\mathrm{\δ})-c_r{\mathrm{\β}}_r\end{array}---\left(1\right)$

Wherein, v_xIt is the travel speed of vehicle, M and I_zIt is gross mass and the yaw rotation inertia of vehicle, the c of vehicle_fAnd c_r It is the cornering stiffness of front tyre and rear tyre, b_fAnd b_rIt is the distance from the center of gravity of vehicle to front axle and back axle, b=b_f+ b_r, M_zBeing applied to the effective torque of vehicle, δ is front vehicle wheel steering angle.

Steering wheel angle δ and travel speed v of estimation of measurement can be used_xIt is used for from formula (1) calculating as input Target yaw rate ω turning to intention of reflection driver_ztWith target side slip angle β_rt.In such calculating, it will be assumed that Prevailing roadway condition (such as, high friction level and small cornering stiffness c_fAnd c_rVehicle is driven under).Can also carry out for surely Determine Signal Regulation, filtering and the gamma correction of the turning of the state limit with fine setting target yaw rate and target side slip angle.These meters The desired value calculated represents driver intention path on prevailing roadway.

Yaw rate feedback controller is mainly counted from yaw error (difference between yaw rate and the target yaw rate of measurement) The yawer calculated.If vehicle is turned left and ω_z≥ω_zt+ω_zdbos(wherein, ω_zdbosBe time dependent extremely District), or vehicle is turned right and ω_z≤ω_zt-ω_zdbos, then vehicle oversteering and activate the ovdersteering control in ESC Function processed.Such as, effective torque request can be calculated as below (to be applied to vehicle to reduce ovdersteering trend):

During left steering: M_z=min (0 ,-k_os(ω_z-ω_zt-ω_zdbos)) (2)

During right turn: M_z=max (0 ,-k_os(ω_z-ω_zt+ω_zdbos))

Wherein, k_osBeing the gain of velocity dependent, it can be defined below:

$k_{os}=k_0+(v_x-v_{xdbl})\frac{k_{dbu}-k_{dbl}}{v_{xdbu}-v_{xdbl}}---\left(3\right)$

Wherein, parameter k_o、k_dbl、k_dbu、v_xdbl、v_xdbuIt is adjustable.

If ω when the vehicle turns to the left_z≤ω_zt-ω_zdbos(wherein, ω_zdbosIt is time dependent dead band), or The ω when vehicle is turned right_z≥ω_zt+ω_zdbos, then the control of the understeer in ESC function is activated.Effective torque request can be such as Lower calculating:

During left steering: M_z=max (0 ,-k_us(ω_z-ω_zt+ω_zdbus)) (4)

During right turn: M_z=min (0 ,-k_us(ω_z-ω_zt-ω_zdbus))

Wherein, k_usIt it is adjustable parameter.

Yaw angle controller is the supplementary feedback controller of above-mentioned ovdersteering driftage feedback controller.Yaw angle controller By estimation sideslip angle beta_rWith target side slip angle β_rtCompare.If the difference between the two exceedes threshold value beta_rdb, then yaw angle feedback control It is activated.Such as, effective torque request is calculated as below:

During left steering:

During right turn:

Wherein, k_ssAnd k_sscmpIt is adjustable parameter,It it is the time-derivative of the compensation of yaw angle.

Other feedback control term based on variable, such as yaw acceleration and sideslip gradient can be produced similarly.When When main vehicle kinematic variables is yaw rate or yaw angle, above-mentioned effective torque can be directly used for determining the wheel that must control and inciting somebody to action It is sent to control accordingly the amount of the brake pressure of wheel.If dynamics of vehicle depends on multiple kinematic variables, then will carry out Control to judge and arrangement order of priority.The final effective torque judged is used for determining finally to control wheel and corresponding system subsequently Dynamic pressure.Such as, during the event of ovdersteering, outer front vehicle wheel is chosen as controlling wheel, and in the event phase of understeer Between, interior rear wheel is chosen as controlling wheel.In the case of big sideslip, outer front vehicle wheel is chosen as controlling wheel all the time.When simultaneously When occurring to break away with ovdersteering driftage, can consider that yaw error and yaw angle control command calculate brake pressure by entirety Amount.

In addition to the situation that the above steering operation due to driver causes exceeding the manipulation limit, vehicle can be at it Lengthwise movement direction arrives its limit manipulation condition.Such as, accumulated snow and eisbahn are braked may cause pin Wheel, which increases the stop distance of vehicle.On similar road open up the engine may cause driving wheel skid without Vehicle is made to advance.To this end, the manipulation limit may be alternatively used for these and non-turns to driving situation.It is to say, tire longitudinally braking or Driving force arrives the situation of its peak value and also is included within the definition of the manipulation limit.

ABS function monitors the rotary motion relative to Vehicle Speed of each wheel, and this can be by longitudinal sliding motion rate λ_iTable Show, wherein, i=1,2,3,4, it is respectively directed in the near front wheel, off-front wheel, left rear wheel and off hind wheel, λ_iCalculated as below:

$\begin{array}{c}{\mathrm{\λ}}_1=\frac{{\mathrm{\κ}}_1{\mathrm{\ω}}_1}{\max \left(\right(v_x+{\mathrm{\ω}}_z{t}_f\left)\cos \right(\mathrm{\δ})+(v_y+{\mathrm{\ω}}_z{b}_f\left)\sin \right(\mathrm{\δ}),v_{\min })}-1\\ {\mathrm{\λ}}_2=\frac{{\mathrm{\κ}}_2{\mathrm{\ω}}_2}{\max \left(\right(v_x+{\mathrm{\ω}}_z{t}_f\left)\cos \right(\mathrm{\δ})+(v_y+{\mathrm{\ω}}_z{b}_f\left)\sin \right(\mathrm{\δ}),v_{\min })}-1\\ {\mathrm{\λ}}_3=\frac{{\mathrm{\κ}}_3{\mathrm{\ω}}_3}{\max (v_x-{\mathrm{\ω}}_z{t}_r,v_{\min })}-1,{\mathrm{\λ}}_4=\frac{{\mathrm{\κ}}_4{\mathrm{\ω}}_4}{\max (v_x+{\mathrm{\ω}}_z{t}_r,v_{\min })}-1\end{array}---\left(6\right)$

Wherein, t_fAnd t_rIt is the half of the wheelspan of front axle and back axle, ω_iIt is the output of i-th vehicle-wheel speed sensor, κ_iIt is i-th wheel velocity scale factor, v_yIt is the vehicle lateral velocity in its c.g. position, v_minIt is to react admissible minimum The parameter preset of longitudinal velocity.Note when formula (6) is not only under vehicle is at reversing mode just effective.When the system that driver starts Move generation the biggest slip (such as ,-λ at wheel_i≥λ_bp=20%), then ABS module will be released in the brake pressure at wheel. Similarly, during the big throttle of applying causes producing big slip on i-th driven wheel, TCS module will request Reduce engine torque and/or request brake pressure is applied on the relative wheel on identical axletree.As a result, can be by monitoring λ_iWith λ_bpAnd λ_tpHave many close to predicting that ABS or TCS activates.

III. manipulation limit index

Although above-mentioned ESC (including ABS and TCS) is effectively realized security purpose, but further enhancing is also feasible 's.Such as, for roll stability control it may be desirable to increase ESC system.But, the suitable correction that ESC attempts carrying out can Offset by driver or surrounding.At the tire force of vehicle accelerated considerably beyond the driving power of road/tire, may result in Even if this vehicle can not avoid the event of understeer under the intervention of ESC.

In general, manipulation limiting case accurately determine the direct measurement that would generally relate to road and tire characteristics, or Person obtains, from many correlated variabless, the information included in the case of directly measurement is infeasible.At present, both approaches is the most inadequate Ripe with real-time implementation.

Feedback characteristic due to ESC system so that ESC system can be configured to monitor vehicle kinematic variables (vehicle Operating parameter) (the most last point describe variable) determine that the potential limit manipulates situation.When kinematic variables and its reference value During difference specified quantitative (such as, exceed specific dead band), ESC system can start calculate difference control for brake order and determine control Wheel.Corresponding brake pressure is sent to control wheel with stable vehicle subsequently.The starting point that ESC activates can be considered manipulation The beginning of the limit.

More specifically, we can be to manipulation limit surplus h relatively_xIt is defined below:

Wherein, x is the deviation of kinematic variables and its reference value,It is defined in the case of not starting ESC, ABS or TCS The interval, dead band that x falls into.X can be defined in last point any control variable (or any other suitably control become Amount).

At h defined in formula (7)_xAdvantage to be that driving situation can be expressed as with being quantized different classes of.Such as, h is worked as_x When≤10%, driving situation can be classified as red area situation, in the case of red area, driver pay particular attention to or Take some special action (such as, making vehicle deceleration)；As 10% < h_x< when 40%, driving situation can be classified as yellow area Situation, in the case of yellow area, driver needs paying special attention to of certain grade；As 40% < h_xWhen≤100%, drive feelings Condition can be classified as general case.In usual cases, driver has only to keep his normal driving attention.Certainly, also Other scope can be used.

More specifically, let us uses, the last point of control variable calculated, h is discussed_xCalculating.Can be by setting Put x=ω_z-ω_ztAndTo calculate in ovdersteering situation (now, when the vehicle turns to the left from formula (7) ω_z>ω_zt, the ω when vehicle is turned right_z>ω_ztDriftage manipulation limit surplus h of vehicle during)_OS, wherein, ω_zdbosIt is in formula Son ovdersteering yaw rate dead band (OSDB) defined in (2).

Similarly, can be by arranging x=ω_z-ω_ztAndTo calculate in understeer from formula (7) In the case of vehicle driftage manipulation limit surplus h_US, wherein, ω_zdbusIt is dead at the understeer yaw rate defined in formula (4) District (USDB).Noting, above-mentioned dead band is probably the function of the amount etc. of the yaw rate of speed, the amount of target yaw rate, measurement.Turn to Dead band in not enough situation (x<0) and the dead band in ovdersteering situation (x>0) are different, and they are adjustable parameters.

Can be by arranging x=β_r-β_rtAndMore than the next sideslip manipulation limit calculating vehicle from formula (7) Amount h_SSRA。

The longitudinal direction manipulation limit of vehicle relates to driving force or the situation of the brake force arrival manipulation limit of tire.Can be by setting Put x=λ_i、x=0 andTo calculate the traction control for i-th driven wheel from formula (7) and manipulate limit surplusAlso by arranging x=λ_i、x=λ_bpAndTo calculate the ABS for i-th wheel from formula (7) and manipulate the limit SurplusFinal traction manipulation limit surplus and braking manipulation limit surplus can be defined as:

$h_{ABS}=\underset{i\&Element;\{1,2,3,4\}}{\min }{h}_{{\mathrm{ABS}}_i},h_{TCS}=\underset{i\&Element;\{1,2,3,4\}}{\min }{h}_{{\mathrm{TCS}}_i}---\left(8\right)$

Note, when computationally stating manipulation limit surplus, further screening conditions can be used.Such as, following bar can be used Manipulation limit surplus is set to 0 by the combination of a condition in part or some conditions in following condition: target yaw rate Amount exceedes specific threshold；The amount of the yaw rate measured is more than specific threshold；The input that turns to of driver exceedes specific threshold；Or Person, limiting case, the turning acceleration of the such as vehicle deceleration more than 0.5g, vehicle is more than 0.7g, vehicle to exceed threshold value The speed traveling etc. of (such as, 100mph).

For known riving condition, calculate and verify their effectiveness to test above-mentioned manipulation limit surplus, assembling The vehicle having the research ESC system developed by Ford Motor Company is used to carry out vehicle testing.

For the riving condition drawn by car speed, throttle and braking described in fig. 2, measure and calculate Vehicle kinematic variables is as shown in Fig. 3 A to Fig. 3 C.Corresponding individually manipulation limit surplus h_US、h_OS、h_TCS、h_ABS、h_SSRAAt Fig. 4 A extremely Shown in Fig. 4 C.This test execution is in the case of all ESC calculate and run, and the free form obstacle on snow pad is sliding Snow travels.Closedown brake pressure applies, thus vehicle manipulates condition close to the real limit.

Test as another, the road surface with high friction level is driven vehicle.Describe in Figure 5 speed, traction and Braking curve.State of motion of vehicle is shown in Fig. 6 A to Fig. 6 C.Corresponding individually manipulation limit surplus h_US、h_OS、h_TCS、h_ABS、 h_SSRAShown in Fig. 7 A and Fig. 7 B.

The envelope variable of all of independent manipulation limit surplus is defined as

h_env=min{h_OS, h_US, h_TCS, h_ABS, h_SSRA} (9)

Changing suddenly of envelope manipulation limit surplus may be caused in view of due to signal noise, use low pass filter F Z () makes h_envSmooth, thus obtain the final manipulation limit (HL) index or surplus:

H=F (z) h_env (10)

For the vehicle testing data shown in Fig. 2 and Fig. 3 A to Fig. 3 C, final manipulation limit surplus is retouched in fig. 8 Paint, and for the vehicle testing data shown in Fig. 5 and Fig. 6 A to Fig. 6 C, final manipulation limit surplus is described in fig .9.

HL index can provide the continuous variable between 0 and 1, and indicates driver how close to have with the manipulation limit of vehicle (wherein, value 1 represents that driver is in the manipulation limit of vehicle).Being somebody's turn to do HL index based on model can be at the lowest μ driving path The driving demand information being even more important is provided during condition.

Assume along with vehicle manipulates the limit close to it, need more vision, health and perception to note maintaining vehicle control System, can infer driver's work load information from HL index.Along with the work load of driver increases, HL index increases.With The work load driver reduces, and HL index reduces.

IV. driver's control action index

Driver's control action (DCA) index can provide the continuous variable between 0 and 1, and indicates driver for such as Accelerate, brake, turn to, heart rate, breathing, sight line, head or the posture of wrist, galvanic skin response etc. control action (or movable Level) total rate of change.Any suitable or known sensor (such as, heart rate sensor, camera etc.) can be such as used Collect the data that this driver is correlated with.Increase rate of change from the operating level of driver and can reflect the driving demand of increase, instead As the same.Therefore, DCA index can provide and the different drivers of the wagon control action (or level of activation) carrying out different aspects The measurement of relevant rate of change (driving demand).

For example, it is contemplated that the impact that accelerator pedal rate of change is on driving demand.With reference to Figure 10 and Figure 11, such as, respectively low Real-time accelerator pedal position is temporally drawn in the case of requirement situation and high request.Situation is required, in high request feelings compared to low The rate of change of the accelerator pedal under condition is clearly the most larger.The health of driver or physiological status (such as, heart rate, exhale The posture of suction, sight line, head or wrist, galvanic skin response etc.) show characteristic variations also as the change required.

The standard deviation of the accelerator pedal position of Figure 10 and Figure 11 is respectively shown in Figure 12 and Figure 13.

With reference to Figure 14, the gamma function of canonical form is used to produce probability corresponding with the distribution of Figure 12 and Figure 13:

$y=f\left(x\right|a,b)=\frac{1}{b^a\mathrm{\&Gamma;}\left(a\right)}{x}^{(a-1)}{e}^{(-\frac{x}{b})}---\left(11\right)$

Wherein, a is scale factor, and b is form factor.Dotted line represents low driving demand distribution of standard deviation, and solid line represents High driving demand distribution of standard deviation.These probability distribution of accelerator pedal rate of change illustrate driving demand classification and current class The grade of the difference between opportunity.Such as, the standard deviation of 2% can represent low driving demand with bigger probability, and the mark of 10% Quasi-deviation can represent high driving demand etc. with bigger probability.This technology can be applied similarly to brake pedal position, steering wheel angle Degree and/or other driver's control action parameter.Therefore, DCA index can be based on for accelerator pedal, brake pedal, steering wheel Deng the rate of change of driver actions estimate driver requested.

The average of the standard deviation rate of change shown in Figure 14 can change for different drivers.DCA Index for Calculation can Consider these averages changed and calculate relative change rate.The derivative of driver's input also can be combined into acquisition expection action. Can be from analyzing each factor (such as, accelerator pedal position/speed, brake pedal position/speed, steering wheel angle position/speed Rate, heart rate/change rate of heartbeat, breathing/Ratio of respiratory changes etc.) covariance determinant obtain variance calculate.

In a particular embodiment, by the covariance affecting driving demand based on the following each factor of formula recursive calculation Determinant calculates DCA index:

${\mathrm{\&Delta;x}}_k=x_k-{\stackrel{\&OverBar;}{x}}_k---\left(12\right)$

${\stackrel{\&OverBar;}{x}}_{k+1}=(1-\mathrm{\&alpha;}){\stackrel{\&OverBar;}{x}}_k+\mathrm{\&alpha;}\&CenterDot;x_k---\left(13\right)$

$G_{k+1}=\&lsqb;\frac{(I-P_k\&CenterDot;{\mathrm{\&Delta;x}}_k)\&CenterDot;G_k}{(1-\mathrm{\&alpha;})}\&rsqb;---\left(14\right)$

$P_{k+1}=G_k\&CenterDot;{\mathrm{\&Delta;x}}_k^T\&CenterDot;\frac{\mathrm{\&alpha;}}{(1-\mathrm{\&alpha;})+\mathrm{\&alpha;}\&CenterDot;{\mathrm{\&Delta;x}}_k\&CenterDot;P_k{\mathrm{\&Delta;x}}_k^T}---\left(15\right)$

Wherein, x_kIt is (at moment k) each driver's control action and the two-dimensional vector of derivative thereof,It is average Number (they can be constantly updated during each drive cycle, and after each drive cycle reset), α be calibrate forget because of Son, G_kBeing the covariance inverse matrix estimated, I is unit matrix, P_kIt is the covariance matrix estimated,It is from formula (12) Δ x_kTransposed matrix.

The recursive calculation determinant det of covariance matrix, is provided below:

${\det }_{k+1}={(1-\mathrm{\&alpha;})}^n{\det }_k\&CenterDot;(1+\mathrm{\&alpha;}\&CenterDot;{\mathrm{\&Delta;x}}_k\&CenterDot;G_k\&CenterDot;{\mathrm{\&Delta;x}}_k^T)---\left(16\right)$

Wherein, n is vector x_kSize.It utilizes these parameters to provide the driving of the average relative to specific driver Member accelerates, brakes, turns to, heart rate, breathing, sight line, the survey of estimation rate of change of head or the posture of wrist, galvanic skin response etc. Amount.It also provides for the one-dimensional measurement of population variance, wherein, can follow the tracks of described one-dimensional measurement and (or live to catch driver's control action Dynamic level) the notable change of the rate of change collected.

Final DCA index (index) can be the continuous signal between 0 and 1 by ratio, and can be given by:

DCAIndex=max (accelerator pedal variance, brake pedal variance, turn to variance etc.) (17)

Use the accelerator pedal position drawn in above technical Analysis such as Figure 15 A and such as the side drawn in Figure 15 B To dish angle.Figure 15 C shows that the example for DCA index of input based on Figure 15 A and Figure 15 B exports.In this example, The determinant (16) of covariance matrix provides driver to accelerate and the measurement estimating rate of change of steering behaviour.By using each The maximum of rate of change produces the DCA index drawn in figure 15 c and uniforms each rate of change and collect.Speed Figure 15 D draws, as reference.In DCA index, the rate of change of increase is captured as the value closer to 1 and (indicates higher Driving demand), and in DCA index, the rate of change of reduction is captured as such as value between 0 and 0.2 and (indicates low driving to want Ask).

In other example, the unit dimensional vector (signal) representing physiological reaction can be applied to minimize calculating resource.Can Make the outputting measurement value from Variation of Drivers ' Heart Rate, breathing, sight line, galvanic skin response etc. experience recursive signal based on formula (13) Process.As the yaw rate described in part ii and target side slip angle, Signal Regulation, filtering and gamma correction can passed Process before returning signal processing or with recursive signal and be simultaneously applied to outputting measurement value.Then returned by the most recursively calculating One changes variance obtains index.So can come based on information of vehicles and the activity of connectivity management and the work load for customization Directly measuring driver condition is provided.Described index can directly comprise for vehicle and the association of the information on services of connection Adjust, or can be aggregated in overall work load estimator index.

V. instrument board index

Driver and instrument board and/or other interface relevant with touch/voice can provide driver activation's alternately Instruction.The increase of such driver activation's rank can increase the perception requirement to driver.As shown in table 1, driver presses The increase that button pressing activates can increase driver's work load.The frequency of interaction controlled with cabin can be aggregated as aggregative index, Wherein, control with cabin includes that rain brush control, climate controlling, volume control, running direction indicator, console control alternately The control of platform, vehicle window, automatic seat control, voice command interface etc..Therefore, instrument board (IP) index provides and represents driver and instrument The output (between zero and one) continuously that dash board, electronics and/or other HMI any are mutual.

Such as, when k pressing/trigger button/interface arrangement at any time, output is given by:

BP_i(k)=α BP_i(k-1)+(1-α)·1 (18)

When not pressing/trigger button/interface arrangement, output is given by:

BP_i(k)=α BP_i(k-1)+(1-α)·0 (19)

Wherein, BP_iBeing to press/trigger pursuit gain for the button/interface of each tracked button/interface, α is calibration Forgetting factor.

Then, the output of IP index can be given by:

IP index=max (BP₁,BP₂,BP₃,BP₄.......BP_n) (20)

Wherein, n is the quantity of tracked button/interface.It is also possible to use any technology of collecting described herein to determine IP index.As example, the technology etc. similar with the technology described referring to formula (28) and (29) can be used.

Example running direction indicator and air-conditioning activate input and draw in Figure 16 A and Figure 16 B respectively.Thus obtained IP index Determine according to formula (18), (19) and (20) and draw in Figure 16 C.In this example, rise time and steady-state value are based on swashing The duration lived.

VI. interval index

Interval index provides the continuous variable between 0 and 1, and indicates the vehicle and front (or side) vehicle just driven The degree of closeness of (or other object).As shown in Table 1, can be from the average time interval reduced and/or the minimum of reduction The work load load increased is inferred at interval.

Can from following formula obtain rely on present speed interval:

${\mathrm{HW}}_{curr}=\frac{\left(r_p\right(k)-r_f(k\left)\right)}{v_f\left(k\right)}---\left(21\right)$

Wherein, r_pK () is the position of k front vehicles at any time, r_fK () is the position following vehicle, v_f(k) be with Speed with vehicle.Equispaced HW_mK () can be obtained by following formula:

HW_M(k)=HW_M(k-1)+α(HW_curr-HW_M(k-1)) (22)

Wherein, α is the time constant for Exponential Filtration, can select as required.Then, HW index can obtain from following formula :

$HWIndex=\&lsqb;\mathrm{\&gamma;}(1-\frac{{\mathrm{HW}}_M}{{\mathrm{HW}}_{MAX}})\&rsqb;---\left(23\right)$

Wherein, γ is HW index sensitive gain, HW_MAXIt it is calibration value.Can according to the interval met needed for maximal index 1 time Between select/regulation gain.

In other embodiments, can be based on such as driver type selecting/regulation sensitive gain.If it is known that driver's class Type (such as " young ", " old ", " teenager ", " new hand ", " veteran " etc.), then can correspondingly adjust sensitive gain.Can be based on Driver is identified as " young ", " old ", " teenager " etc. by the certificate carried by driver known in the art.Can be by car Detection certificate, and certificate be used for identify driver type.Selectively, vehicle can provide and allow driver identify them The select button of the type of oneself.But, can use any properly/known technology to driver classify.For " teenager " " new hand " driver can increase sensitive gain, and can reduce sensitive gain for " veteran " driver etc..In other embodiments In, for " teenager " and " new hand " driver, sensitive gain can be chosen as greater value, and driver etc. can for " veteran " Sensitive gain is chosen as smaller value.Therefore, in the case of same intervals, HW index can be more for " teenager " driver It is worth greatly and " veteran " driver is waited as smaller value.

Selectively (or extraly), can select/regulate sensitive gain based on ambient conditions.By suitable/known skill Humidity or icy roads situation that art (such as by detection wheel skid) determines may result in sensitive gain and increase.Dry roads Situation may result in sensitive gain and reduces.Any suitable ambient conditions including traffic density, geographical position etc. can be used to select Select/change sensitive gain.

Can also calculate similarly and infrastructure interval apart with the calculating in formula (21), (22) and (23), Wherein, infrastructure includes crossroad, highway, high request highway geometry etc..In this case, HW index can by under Formula obtains:

HW index=max (HW₁,HW₂,......HW_n) (24)

Wherein, n is the quantity of project of separation of the most tracked high driving demand.It is also possible to use for formula (24) weighting function.

In other embodiments, the interval of the increase returned from the volume of traffic of the increase of adjacent lane is used as HW index Deviation (bias) input.(traffic density of increase can increase driving demand, as shown in table 1.)

In other embodiments, collision time can be followed the tracks of in less than the scheme of 1000ms.Will collide potential In the case of, the output of HW index can be defaulted as maximum 1.

With reference to Figure 17, collision time t_cCan be calculated by following formula:

$t_c=\frac{-V_x\&PlusMinus;\sqrt{{\left(V_x\right)}^2+2\left(A_x\right)\left(X\right)}}{\left(A_x\right)}---\left(25\right)$

Or

Wherein, V_xIt is closing speed, A_xBeing relative acceleration, X is the distance between vehicle.Can from any properly/known Radar system, visual system, laser radar system, vehicle-to-vehicle communication system etc. obtain range and range rate information.

The calculating of consideration HW index in example vehicle follows scene, Figure 18 to Figure 20 illustrates the main car during this scene Closing speed and distance travelled between speed, vehicle.Figure 21 and Figure 22 respectively illustrates interval (being calculated by formula (22)) With HW index (being calculated by formula (23)).

VII. rule-based subsystem

Referring again to Fig. 1, the fact that rule-based subsystem 12 can include for determining event binary system output identification And knowledge base.Subsystem 12 can provide specific specialists engineering and vehicle driver's environmental interaction rule using as its of system 10 Supplementing of its assembly.Knowledge may be expressed as one group of rule.The specific activation of Vehicular system can be comprised.

Each rule specifies the suggestion of output services burden, and if having (condition), then (action) structure.When meeting Rule condition part time perform action part.Each rule may specify the suggestion (0 or 1) that output services are born.Can be to appoint What suitable/known mode is monitored/obtains multiple vehicle parameter, described vehicle by subsystem 12 from the CAN of such as vehicle Parameter includes that longitudinal acceleration, transverse acceleration, deceleration, steering wheel angle, button use etc. (such as, are shown in Table 2a and table 2b).To these parameter is relevant the fact and combinations thereof can be used for arranging conditional plan.

The system convention realized by subsystem 12 can be according to following form:

Enable during event for cabin system or the specific delays of information entertainment or restriction from Expert Rules.Base Output in rule also can be processed making for carrying with the driving demand for condition advocated based on expert and special characteristic Collect for correlation output.

Rule can be based on information, such as, lists in above table 2a and 2b.Such as, if steering wheel angle > 105 Degree, then Event_Flag=1 (event flag=1).Certainly, Else Rule can also be built.

VIII. collect

One or more in HW index, DCA index, IP index and HL index can be collected to use by subsystem 14 following Technology formed follow the tracks of (T) index.But, only needing to use/calculate/determine in the embodiment of an index, can be not required to Collect.

In a particular embodiment, short-term collect can be used for scheduling/postpone/postpone by be transferred to the information of driver/ Task.In the case of needing the highest driving demand estimated, T index can be given by:

T Index=max (DCA Index, IP Index, HL Index, HW Index) (27)

In other embodiments, average/maximum output combination to exponential quantity as described below uses the remittance relying on environment Always.Can be combined by subsystem 14 for example, referring to Fig. 1, DCA index, IP index, HL index and HW index and be given by be formed T index:

$TIndex=\frac{\underset{i=1}{\overset{N}{\&Sigma;}}{w}_i{y}_i}{\underset{i=1}{\overset{N}{\&Sigma;}}{w}_i}---\left(28\right)$

Wherein, w_iIt it is the weight relying on environment according to the driving demand value being added in input.Launch formula (28) to obtain:

$TIndex=\frac{{\mathrm{WLE}}_{DCA}{w}_{DCA}+{\mathrm{WLE}}_{IP}{w}_{IP}+{\mathrm{WLE}}_{HL}{w}_{HL}+{\mathrm{WLE}}_{HW}{w}_{HW}}{w_{DCA}+w_{IP}+w_{HL}+w_{HW}}+bias---\left(29\right)$

Max (Tracking_Index)=1.0

Wherein, WLE_DCA、WLE_IP、WLE_HL、WLE_HWIt is DCA index, IP index, HL index and the output of HW index respectively.Phase The weight answered is by w_DCA、w_IP、w_HL、w_HWBe given.

The example rule for collecting listed by table 3 and table 4.

Table 3

For the example rule collected based on environment

Table 4

For the more example rules collected based on environment

Subsystem 16 can use the technology described above by reference to subsystem 14 rule-based index and T index to be collected For WLE index.As example, WLE index can be given by:

WLE Index=max (T Index, Rule-Based Index) (30)

Exemplary rule-based index, IP index and DCA index are drawn respectively in Figure 23 A and Figure 23 C.For consideration The situation of the highest driving demand situation estimated, has used technology described here to summarize these indexes and at figure 23D draws.Speed is drawn, for reference in Figure 23 E.

Ⅸ. long-term characterization

In other embodiments, WLE index can be characterized in time by subsystem 16 and/or scheduler 18 (according to configuration) To provide HMI suggestion.It is customized in driver based on driving demand in time that long-term WLE sign can make HMI.Such as, examine Consider r_kIt it is the reflection (k at any time) variable for the WLE exponential quantity of driver.Assume driving demand be classified as with a, 3 classes that b, c} represent, and there is the fuzzy membership functions μ as defined in fig. 24_a、μ_b、μ_c.Then, driving behavior d_kCan under The example calculations in face is inferred:

d_k=[μ_a(r_k), μ_b(r_k), μ_c(r_k)] (31)

Such as, if r_kValue be 0.4, then d_kMay be expressed as [0.18,0.62,0] (according to Figure 24).Filtered (long Phase) deformation driving behaviorCan be expressed from the next:

$d_{f_k}=(1-\mathrm{\&alpha;})d_{f_{k-1}}+{\mathrm{\&alpha;d}}_k---\left(32\right)$

Wherein, α be calibration forgetting factor (thus α specify/determine assessment TERM DEFORMATION driving behaviorTime period). Long term probability (p for each classification_k)_iCan obtain from following formula:

${\left(p_k\right)}_i={\left(d_{f_k}\right)}_i{\left(\underset{j\&Element;\{a,b,c\}}{\&Sigma;}{\left(d_{f_k}\right)}_j\right)}^{-1}---\left(33\right)$

According to formula (33), for the filtered deformation driving behavior of each classificationDivided by for all categories Filtered deformation driving behavior sumSuch as, ifIt is represented as [0,0.16,0.38], then (p_k)_aWill be equal to 0 divided by 0+0.016+0.38 ((p_k)_aWill be equal to 0), (p_k)_bWill be equal to 0.16 divided by 0+0.016+0.38 ((p_k)_b Will be equal to 0.29), (p_k)_cWill be equal to 0.38 divided by 0+0.016+0.38 ((p_k)_cWill be equal to 0.71).

Then, the final long-term WLE index of driving demand characterizes i_kCan infer from following formula:

$i_k=\underset{i\&Element;\{a,b,c\}}{\arg }max{\left(p_k\right)}_i---\left(34\right)$

Use above example, (p_k)_iThe maximum of value is 0.71 ((p_k)_c).Therefore, driving row can be inferred from formula (34) For being currently at " high request " classification.

Ⅹ. scheduler

Scheduler 18 can the WLE index of computation, the long-term characterization of WLE index or DCA index, IP index, HL index With any one (for only the using/calculate/determine the embodiment of single index) in HW index come to information entertainment systems and/ Or being modulated alternately between other conversational system and driver.WLE index provides the work load load estimated, is used for setting Put/avoid/customize/limit/dispatch voice command and other task being presented to driver, to improve functional and safety Property.

Mutual with the example of driver (no matter being wired mutual or wireless interaction) comprises the steps that generation Text To Speech turns Change, produce incarnation communication, produce the prompting about Inbound Calls, produce perspective dynamical system order, produce perspective voice and build Discuss, via such as feeling steering wheel generation haptic response or producing other audio frequency, vision and/or sense of touch output etc..These examples Each task in driver interface task can have relative priority.Such as, the prompting about Inbound Calls is produced Can have high priority, and produce the suggestion of perspective voice and can have low priority.

Any properly/known technology can be used for distributing to priority type given driver interface task.As showing Example, scheduler 18 can realize high/low priority protocol, wherein, all prompting distribution height about Inbound Calls that will be generated Priority, the suggestion distribution low priority that all vehicles being sent to driver are initiated.But, other priority can be used Scheme.As example, the numeral between 0 and 1.0 can represent the priority of task: particular task can distribute the priority of 0.3, and Other task dividable joins the priority etc. of 0.8.In other embodiments, can by produce task known in the art controller/ Processor/subsystem (not shown) distributes the priority type relevant to driver interface task.

Therefore, specific embodiment can allow driver interface task based on work load and priority by dispatching sequence in Existing.Such as, if the value that WLE index (or any one index depended on the circumstances) has between 0.4 and 0.6, then scheduler 18 can only allow to perform high priority driver interface task.In the case of WLE index is less than the value of 0.4, scheduler Relatively low priority tasks can be scheduling to more late execution by 18.Such as, if WLE index has the value between 0.7 and 1.0, then Scheduler 18 can stop the execution of all of driver interface task.During these high workloads are born, reach little at WLE index In the case of the value of 0.7, high-priority task can be scheduling to more late execution by scheduler 18, is less than 0.4 at WLE index Value in the case of, relatively low priority tasks can be scheduling to more late execution by scheduler 18.

Similarly, if long drives behavior is characterized as " high request ", then regardless of its priority, specific/all task can It is postponed/delayed/scheduled, until long drives behavior is characterized as " middle requirement " or " low requirement ".Selectively, if driven for a long time The behavior of sailing has any probability being in such as " high request " classification, and the most specific/all task can be postponed/delayed/scheduled, directly It is 0 to the probability being in " high request ".Certainly, other scheme is also feasible.Such as, it is not used for appointing in priority type In the embodiment of business classification, all tasks can be postponed/delayed/scheduled according to the work load inferred.

In the case of receiving Inbound Calls during high workload is born, Inbound Calls can be proceeded to voice postal by scheduler 18 Part system.Once WLE index reaches appropriate value, and scheduler 18 just can produce instruction and receive the prompting of Inbound Calls.

Algorithm disclosed herein can be sent to processing means by the way of wired or wireless transmission, such as system 12, 13, in 14,16 and 18 any/all, described processing means can include any existing Electronic Control list taken various forms First or special electronic control unit, described various ways includes but not limited to: be permanently stored in not writeable storage medium (such as ROM device) in information and be stored in writable storage media (such as floppy disk, tape, CD, ram set and other magnetic changeably With light medium) on information.Described algorithm also can be embodied as the executable object of software.Selectively, can use the most firmly Part assembly (such as special IC (ASIC), field programmable gate array (FPGA), state machine, controller) or other hardware The combination of assembly or device (movement or non-moving) or hardware, software and fastener components is implemented to calculate whole or in part Method.

Although it has been shown and described that embodiments of the invention, but being not intended to make these embodiments illustrate and describe this Institute's likely form of invention.The word used in the description is descriptive words rather than restricted word, it should be appreciated that Without departing from carrying out various change in the case of the spirit and scope of the present invention.

Claims (17)

1. a driver interface system, including:

Processor, is configured to:

Receive the driver interface task that will be performed；

Optionally postpone or stop the execution of at least some of driver interface task based on driver's work load, wherein, Driver's work load is derived from the driver activity rate of change horizontally relative to the meansigma methods of driver activity level, described change Rate is represented by the recursive calculation determinant of the covariance of described level of activation.

2. driver interface system as claimed in claim 1, wherein, processor is also configured to monitor described level of activation.

3. driver interface system as claimed in claim 2, wherein, described level of activation is based on from wearable sensors Data.

4. driver interface system as claimed in claim 3, wherein, the output of wearable sensors includes physiological data, adds Velometer data or geographic position data.

5. driver interface system as claimed in claim 1, wherein, it is described that processor is also configured to wireless receiving instruction The signal of level of activation.

6. driver interface system as claimed in claim 1, wherein, processor is also configured to recursively calculate described row Column.

7. driver interface system as claimed in claim 6, wherein, processor be also configured to recursively calculate described Before determinant, band filter is applied to indicate the signal of described level of activation.

8. driver interface system as claimed in claim 1, wherein, described determinant is to carry out recurrence by wearable sensors Ground calculates.

9. driver interface system as claimed in claim 1, wherein, described determinant is recursively to be counted by mobile phone Calculate.

10. driver interface system as claimed in claim 1, wherein, processor is arranged in the mobile phone.

11. driver interface systems as claimed in claim 1, wherein, processor is disposed in wearable sensors.

12. driver interface systems as claimed in claim 1, wherein, processor is also configured to apply band filter In the signal indicating described level of activation.

13. driver interface systems as claimed in claim 1, wherein, processor is also configured in response to described selectivity Ground postpones or stops and produce instruction audio frequency, vision or the output of tactile alert.

14. 1 kinds are used for the method operating driver interface system, and described method includes:

Optionally postpone or stop the execution of driver interface task based on driver's work load, wherein, driver works Burden is derived from the driver activity rate of change horizontally relative to the meansigma methods of driver activity level, and described rate of change is by described The variance of the recursive calculation of level of activation represents.

15. methods as claimed in claim 14, also include: wireless receiving indicates the signal of described level of activation.

16. methods as claimed in claim 14, also include: recursively calculate described variance.

17. methods as claimed in claim 14, also include: optionally postpone in response to described or stop and produce instruction sound Frequently, vision or the output of tactile alert.