CN103258409B - Based on the system and method for 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. The power manipulation state that can check vehicles, driver are determined one or more measurements of driver's work load to the input of vehicle etc. Then, can postpone and/or stop driver's interface task to be performed based on driver's work load, thereby not increase driver's work load. For example, selectively, can dispatch the execution of driver's interface task based on driver's work load, and driver's interface task is performed according to scheduling, carry out to minimize the impact that driver's interface task brings as driver's work load.

Description

Based on the system and method for driver's work load scheduling driver interface task

The application is to be on July 29th, 2010 applying date, and application number is 201080068204.9, denomination of invention be " forBased on the system and method for driver's work load scheduling driver interface task " the divisional application of application for a patent for invention.

Technical field

Embodiments of the invention relate in general to a kind of for based on driver's work load scheduling driver interface taskSystem and method.

Background technology

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

Summary of the invention

Can determine from vehicle, driver and/or environmental information the measurement of driver's work load. Driving that can be based on definiteMember's work load optionally postpones or stops the execution of specific driver interface task. Selectively, can be based on driving of determiningThe execution of the person's of sailing work load scheduling driver interface task, and make subsequently driver's interface task according to this scheduled for executing.

Brief description of the drawings

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 that represents with yaw rate and yaw angle.

Fig. 4 A to Fig. 4 C is driftage, longitudinally and the exemplary graph of the 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 that represents with yaw rate and yaw angle.

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

Fig. 8 and Fig. 9 are the exemplary graph that finally manipulates limit surplus and risk.

Figure 10 and Figure 11 are respectively the exemplary graph for high request environment and the low accelerator pedal position that requires environment.

Figure 12 and Figure 13 are respectively the histograms of the standard deviation of the accelerator pedal position of Figure 10 and Figure 11.

Figure 14 is the curve map of the curve that conforms to the histogram of Figure 12 and Figure 13.

Figure 15 A to Figure 15 D is respectively accelerator pedal position, steering wheel angle, driver's control action (DCA) exponential sum carThe exemplary graph of speed.

Figure 16 A to Figure 16 C is respectively the example song of running direction indicator activation, air-conditioning control activation, instrument board (IP) indexLine chart.

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

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

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

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

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

Detailed description of the invention

I. introduction

Driver's work load/requirement can be indicated such vision, health and perception requirement, such as information amusement, phone,The less important activation of perspective suggestion etc. is placed on main driving activation by driver and surmounts described main driving activation and (makesDriver is except carrying out the main less important activation of also carrying out suggestion activation of driving).

Driver sometimes may think improperly they can main driving discussed above activate and less important activation itBetween take sb's mind off sth. Therefore, if will estimate that driver requested operation for modulation communication and with driver's vehicle isSystem is mutual, estimates that driver requested operation can have remarkable value. But complicated driving environment may need noveltyForecasting Methodology is to estimate driver's work load. The development that can carry out the intelligence system of driver's work load identification is of value toThe man-machine interface (HMI) that driver is exported in customization.

In order to estimate continuously work load, may need design pre-in the situation that of different driving environments and/or driverSurvey the estimator of work load. In adaptive compartment, communication service can be driven the environment requiring based on predicting therein, andThe value of service is sent to driver. In addition the driver's work load (for example, characterizing for a long time) characterizing in a period of time, canUseful. Can allow not only to suppress during the high workload burden time period for such estimation of driver's work load orPostpone the communication technology in compartment, and make the communication technology in compartment be adapted to drive for a long time requirement.

Specific embodiment described herein can be provided for the method and system of work load estimation (WLE). WLE can be fromObservable vehicle, driver and environmental data for the real-time HMI task management of self adaptation are carried out driver's work loadState estimation/classification. In some cases, WLE can and/or adopt real-time mixed method to estimate with independent real-time techniqueMeter work load. For example, can be supplementary right to the algorithm of rule-based (rule-based) based on driver, vehicle and environmental interactionIn the additional prediction continuously of driver's work load. WLE algorithm can be combined to calculate with special study and Computational intelligence technologyAnd the WLE index (for example, representing the continuous signal for driver's work load load estimation) that gathers of prediction. In some feelingsUnder condition, can infer from observable information of vehicles driver's driving requirement, described information of vehicles comprises speed, acceleration, systemMove, turn to, interval, instrument board and/or mutual etc. the variation of console.

As example, WLE index can be used for arranging/avoiding/restriction/customized voice order and/or present to driver'sOther tasks/information is to improve function. Needing vehicle performance operating period, in dangerous driving environment, passing through instrumentPlate carries out during the high movable time period etc., can limit/customize/stop the customizing messages for driver.

Intelligent Hybrid algorithmic method can be considered long-term and short-term driver action. WLE mixed method can catch driver's thingPart, situation and behavior, to adjust communicating by letter of vehicle and driver. These and other technology described here can be driven by aid forecastingThe sensed condition state that member increases/reduces also can use existing vehicle sensors.

WLE index also can allow, based on driving requirement/work load, the level of communication is presented to driver. Message is preferentialLevel (for example, low, high) can the burden based on prediction determine whether, during special time, message is passed to driver. Also canLong-term driving based on driver requires specific HMI information to present to driver. Selectively, mixing WLE framework can be in conjunction withGPS and digital map database are to consider road scene situation and condition. About driver's physiological status (comprise heart rate,Sight line and breathing) information can be used as amount of imports other places and be attached to WLE framework, for anormal detection. In other example,The WLE index of prediction can be sent to driver to remind driver to avoid carrying out secondary task under high workload burden.Other scheme is also feasible.

Fig. 1 is the block diagram for the embodiment of the WLE system 10 of vehicle 11. System 10 can comprise that rule-based work is negativeLoad index subsystem 12, vehicle, driver and/or environment tracking and evaluation work burden index subsystem 13, dependence environmentWork load index gathers subsystem 14 and gather/WLE of entirety characterizes subsystem 16 for a long time. Subsystem 12,13,14,16(are mono-Solely or in combination) can be implemented as one or more controller/treating apparatus etc.

Subsystem 12(as explained in following part VII) driver information and/or environmental information (for example, canObtain from the controller local area network (CAN) of vehicle) as input information of vehicles, and output represent driver's work load based onThe index of rule. Subsystem 13(as in following part III to explaining in VI) can be by driver information and/or environmental information(for example, can obtain from the CAN of vehicle) is as input information of vehicles, and output represents the one or more of driver's work loadChain index (for example, the manipulation limit (HL) index, driver's control action (DCA) index, instrument board (IP) index, interval(HW) index). Subsystem 14(as explained in following part VIII) can be by the index being produced by subsystem 13 as input,And output tracking (T) index. Subsystem 16(as explained in following part VIII) can be by rule-based exponential sum T indexAs inputting, and export the long-term sign of WLE index (as what explain) and/or WLE index in following part IX.

In other embodiments, system 10 can lack subsystem 12,14,16. That is to say, specific embodiment can be constructedFor only producing one or more work load indexes. As example, system 10 only can be constructed to based on particular vehicle information (Below describe) generation IP index. In these situations of single measurement that only have driver's work load, do not need to gather.Therefore, in this example, WLE index is IP index. In these and other embodiment, scheduler 18 can be constructed to produceThe long-term sign of WLE index. Other arrangement is also feasible.

WLE index can be sent to scheduler 18, and scheduler 18 can be implemented as one or more controllers/processing dressPut/etc. Scheduler 18(as explained in following part X) can be used as wave filter-will based on WLE index prevent/delayThe information that is transferred to driver arrives driver. For example, if WLE index is greater than 0.8, can stop all being intended to for drivingThe information of the person of sailing. If WLE index approaches 0.5, can only stop the information of types of entertainment, etc. Scheduler 18 also can be based on WLEIndex is to dispatching the transmission of the information that is transferred to driver. For example, can during the time period of high workload burden, prolongLate vehicle maintenance information, Text To Speech read, Inbound Calls etc. In addition, scheduler 18 can characterize and make based on long-term WLE indexVehicle is output as driver and customizes, as discussed in more detail below. For example, comprise the control of cruising, adaptive cruise controlThe output of the particular vehicle system of system, music suggestion, configurable HMI etc. can be based on long-term driving requirement.

The work load state that can infer from observable information of vehicles driver, described information of vehicles comprises speed, addsSpeed, brake, turn to, interval, instrument board are mutual etc. variation. Table 1 is listed and driver's work load relevant example of loadingFeature/standard (metric).

Table 1

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

Standard	Be intended to the behavior effect quantizing
		Average speed	Large speed increases/reduces
Maximal rate	Large speed increases
		The Ping Zhuo time interval (interval time)	The interval of reducing
Minimum interval	The minimum interval of reducing
		Brake reaction time (BRT)	The BRT reducing
Braking abrupt change	The frequency increasing
		Steering wheel reversion rate	The frequency of the increase of little reversion 3 -->
Mutual (for example, pressing IP button) with IP	The frequency increasing
		Traffic density	The density increasing
Steering position	New driving environment
		Average speed	Large speed increases/reduces
Maximal rate	Large speed increases

Table 2a and table 2b list the example information that can obtain/access via CAN known in the art. Following information can be usedDo the input of any algorithm described here.

Table 2a

The example information that can obtain via CAN

Accelerator pedal position	Microphone input
		Steering wheel angle	Glass stand sensor
Seat sensor	The speed of a motor vehicle
		Turn signal	Yaw rate
Defrosting signal	Transverse acceleration
		Temperature control	Longitudinal acceleration
Headlight state	Wheel speed
		High beam state	Throttle position
Fog lamp state	Master cylinder pressure
		Radio tuner order	Driver's requested torque

Rain brush state	Total axletree moment of torsion
		Gear	Total torque distribution
Rain sensor	Roll velocity
		Configurable HMI	Yaw angle
Touch HMI	Respective side inclination angle

Table 2b

The example system information that can obtain via CAN

Pull-in control system
	Anti-lock braking system
Electronic stability control
	Adaptive cruise control
Collision by braking relaxes
	Blind spot monitors
Automatic stopping helps

II. the simple discussion of vehicle stabilization control

The manipulation of vehicle determines the ability of turn inside diameter and manipulation. Vehicle need to pass through its four adjacent roads of tire contact-making surfaceFace, thus maximize its handling. The tire that exceedes its limit of adhesion is understood spinning, is skidded or trackslip. One or more wheelThe condition that tire exceedes its limit of adhesion can be called as limit manipulation condition, and limit of adhesion can be called as the manipulation limit. Once tireReach its manipulation limit, common driver no longer can control vehicle conventionally. The in the situation that of so-called understeer, vehicle does not haveHave abundant execution driver's the input that turns to, the front tyre of vehicle exceedes its manipulation limit, and vehicle is ignored turning of driverContinue to request to keep straight on. The in the situation that of so-called ovdersteering, vehicle is excessively carried out driver's the input that turns to, vehicleRear tyre exceedes its manipulation limit, and vehicle continues spinning. For the object of safety, most vehicles are manufactured to its behaviourUndersteer when the control limit.

Compensate vehicle control, electronics in order not control in the case of driver the vehicle that meets or exceeds the manipulation limitStable control (ESC) system is designed to redistribute tire force can make turning to of vehicle and driver ask to produce effectivelyAsk the moment that conforms to and turn to. That is to say, control vehicle is avoided the situation of understeer or ovdersteering.

Since nineteen ninety-five comes out, ESC system has been implemented in various platforms. Carry out gradually in vehicle year 2010,Realize comprehensively and installing to vehicle years 2012, FMVSS 126 requires ESC system to be installed on gross weight grade to existOn 10,000 pounds of following any vehicles. ESC system can be implemented as anti-lock braking system (ABS) and full speed traction control systemThe expansion of system (TCS). ESC system can provide driftage and lateral stability side with driver's the middle mind-set dynamics of vehicle that is intended toHelp. It also can make brake pressure (higher or lower than driver's applied pressure) and single wheel proportional, thereby produces effectivelyMoment is with the unexpected driftage of opposing vehicle and laterally slide fortune. This makes to lead for any during braking, accelerate or slidingDraw surface turns to and controls enhancing in the time of the manipulation limit. More particularly, current ESC system is by driver's intention path and from carThe actual vehicle response that set sensor is inferred compares. If the response of vehicle (understeers or turn different from intention pathTo excessive), and if require ESC controller vehicle is remained on intention path and minimize the out of control of vehicle, ESC controlDevice processed applies and brakes and reduce engine torque the wheel of selecting.

Can carry out detectable limit manipulation situation by the data that exist in ESC system, so do not need new sensingDevice. As example, consider to be equipped with the vehicle of ESC system, ESC system is used Yaw rate sensor, steering wheel sensor, horizontalAccelerometer, vehicle-wheel speed sensor, master cylinder brake-pressure sensor, longitudinal acceleration meter etc. As defined in ISO-8855Like that, in coordinate system, define vehicle movement variable, wherein, on car body fixing car frame have vertical axis upwards,Along the axle of the longitudinal direction of car body and point to the lateral shaft of driver side from passenger side.

Generally speaking, can be from single kinematic variables (such as yaw rate, yaw angle or their combination) and otherThe control of vehicle feedback level is calculated in judgement in control command (such as driver's braking, engine torque request, ABS and TCS).The order of vehicle control hierarchy is discussed below.

Known auto model obtains dynamics of vehicle, the vehicle yaw rate ω along the vertical axis of car body_zAnd at itThe vehicle side slip angle β of back axle definition_r, and meet following equation:

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

Wherein, v_xThe travel speed of vehicle, M and I_zThe gross mass of vehicle and the driftage rotary inertia of vehicle, c_fAnd c_rThe cornering stiffness of front tyre and rear tyre, b_fAnd b_rThe distance from the center of gravity of vehicle to front axle and back axle, b=b_f+b_r，M_zBe the effective torque that is applied to vehicle, δ is front vehicle wheel steering angle.

Can use the steering wheel angle δ of measurement and the travel speed v of estimation_xCalculate and be used for from formula (1) as inputReflection driver's the target yaw rate ω that turns to intention_ztWith target side slip angle β_rt. In such calculating, we exist at hypothesisPrevailing roadway condition (for example, high friction level and small cornering stiffness c_fAnd c_r) lower steering vehicle. Also can carry out for surelyDetermine 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 metersThe desired value of calculating represents the intention path of driver on prevailing roadway.

Yaw rate feedback controller is mainly from yaw error (between the yaw rate of measurement and target yaw rate poor) meterThe yawer of calculating. If vehicle is turned left and ω_z≥ω_zt+ω_zdbos(wherein, ω_zdbosTime dependent deadDistrict), or vehicle is turned right and ω_z≤ω_zt-ω_zdbos, the ovdersteering control in vehicle oversteering and activation ESCFunction processed. For example, effective torque request can be calculated as follows (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_osBe the gain of velocity dependent, it can be as given a definition:

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

Wherein, parameter k_o、k_dbl、k_dbu、v_xdbl、v_xdbuAdjustable.

If ω in the time that vehicle is turned left_z≤ω_zt-ω_zdbos(wherein, ω_zdbosTime dependent dead band), orω in the time that vehicle is turned right_z≥ω_zt+ω_zdbos, the understeer control function in ESC is activated. Effective torque request can be asLower 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 is adjustable parameter.

Yaw angle controller is the supplementary feedback controller of above-mentioned ovdersteering driftage feedback controller. Yaw angle controllerTo estimate yaw angle β_rWith target side slip angle β_rtCompare. If the difference of the two exceedes threshold value beta_rdb, yaw angle FEEDBACK CONTROLBe activated. For example, effective torque request is calculated as follows:

During left steering: ${\mathrm{\β}}_r\≥0:M_z=\min (0,k_{\mathrm{ss}}({\mathrm{\β}}_r-B_{\mathrm{rt}}-B_{\mathrm{rdb}})-k_{\mathrm{sscmp}}{\stackrel{\·}{\mathrm{\β}}}_{\mathrm{rcmp}})---\left(5\right)$

During right turn: ${\mathrm{\&beta;}}_r<0:M_z=\max (0,k_{\mathrm{ss}}(\mathrm{\&beta;}-B_{\mathrm{rt}}+B_{\mathrm{rdb}})-k_{\mathrm{sscmp}}{\stackrel{\&CenterDot;}{\mathrm{\&beta;}}}_{\mathrm{rcmp}})$

Wherein, k_ssAnd k_sscmpAdjustable parameter,It is the time-derivative of the compensation of yaw angle.

Can produce similarly other FEEDBACK CONTROL term based on variable, such as yaw acceleration and sideslip gradient. WhenWhen main vehicle movement variable is yaw rate or yaw angle, above-mentioned effective torque can be directly used in to be determined the essential wheel of controlling and incites somebody to actionBe sent to the amount of the brake pressure of corresponding control wheel. If dynamics of vehicle depends on multiple kinematic variableses, will carry outControl and judge and arrangement order of priority. The effective torque of final decision is subsequently used to determine final wheel and the corresponding system controlledDynamic pressure. For example, during the event of ovdersteering, outer front vehicle wheel is chosen as control wheel, and in event phase of understeerBetween, interior rear wheel is chosen as control wheel. In large sideslip situation, outer front vehicle wheel is chosen as control wheel all the time. When simultaneouslyOccur to break away and when ovdersteering is gone off course, can consider that yaw error and yaw angle control command calculate brake pressure by entiretyAmount.

Except the above steering operation due to driver causes exceeding the situation that manipulates the limit, vehicle can be at itLengthwise movement direction arrives its limit manipulation condition. For example, on accumulated snow and eisbahn, brake and may cause pinningWheel, this has increased the stop distance of vehicle. On similar road, open up the engine may cause driving wheel skid and can notVehicle is advanced. For this reason, the manipulation limit also can be used to these non-driving situations that turns to. That is to say, tire longitudinally brake orThe situation that driving force arrives its peak value also can be included in the definition of the manipulation limit.

ABS function monitors that each wheel is with respect to the rotatablely moving of Vehicle Speed, and this can be by longitudinal sliding motion rate λ_iTableShow, wherein, i=1,2,3,4, is directed to respectively the near front wheel, off-front wheel, left rear wheel and off hind wheel, λ_iFollowing calculating:

${\mathrm{\&lambda;}}_1=\frac{{\mathrm{\&kappa;}}_1{\mathrm{\&omega;}}_1}{\max ((v_x+{\mathrm{\&omega;}}_z{t}_f)\cos \left(\mathrm{\&delta;}\right)+(v_y+{\mathrm{\&omega;}}_z{b}_f)\sin \left(\mathrm{\&delta;}\right),v_{\min })}-1$

${\mathrm{\&lambda;}}_2=\frac{{\mathrm{\&kappa;}}_2{\mathrm{\&omega;}}_2}{\max ((v_x+{\mathrm{\&omega;}}_z{t}_f)\cos \left(\mathrm{\&delta;}\right)+(v_y+{\mathrm{\&omega;}}_z{b}_f)\sin \left(\mathrm{\&delta;}\right),v_{\min })}-1---\left(6\right)$

${\mathrm{\&lambda;}}_3=\frac{{\mathrm{\&kappa;}}_3{\mathrm{\&omega;}}_3}{\max (v_x-{\mathrm{\&omega;}}_z{t}_r,v_{\min })}-1,{\mathrm{\&lambda;}}_4=\frac{{\mathrm{\&kappa;}}_4{\mathrm{\&omega;}}_4}{\max (v_x+{\mathrm{\&omega;}}_z{t}_r,v_{\min })}-1$

Wherein, t_fAnd t_rThe half of the wheelspan of front axle and back axle, ω_iI vehicle-wheel speed sensor output,κ_iI wheel velocity scale factor, v_yThe lateral velocity of vehicle in its c.g. position, v_minIt is the admissible minimum of reactionThe parameter preset of longitudinal velocity. Notice that formula (6) is only just effective in the time that vehicle is not under reversing mode. When the system of driver's startupMove and produce too large slip (for example ,-λ at wheel place_i≥λ_bp=20%), ABS module will be released in the brake pressure at wheel place. ClassLike, causing producing in the process of large slip on i driven wheel applying large throttle, TCS module subtracts requestLittle engine torque and/or request brake pressure are applied on the relative wheel on identical axletree. As a result, can be by monitoring λ_iWith λ_bpAnd λ_tpApproach more and predict that ABS or TCS activate.

III. manipulation limit index

Although above-mentioned ESC(comprises ABS and TCS) effectively realize security purpose, further enhancing is also feasible. For example, may expect to increase ESC system for roll stability control. But the suitable correction that ESC attempts carrying out canOffset by driver or surrounding environment. , can cause considerably beyond the driving power of road/tire at the tire force of the vehicle acceleratingEven if this vehicle can not be avoided the event of understeer under the intervention of ESC.

In general, accurately definite direct measurement that conventionally can relate to road and tire characteristics of manipulation limiting case, orPerson is directly measuring in infeasible situation and is obtaining from many correlated variables the information including. At present, these two kinds of methods are all inadequateRipe with real-time implementation.

Due to the feedback characteristic of ESC system, ESC system can be configured to by monitoring vehicle movement variable (vehicleOperating parameter) (such as the variable of last point of description) determine potential limit manipulation situation. When kinematic variables and its reference valueFor example, while differing specified quantitative (, exceeding specific dead band), ESC system can start to calculate difference braking control command and determine and controlWheel. Corresponding brake pressure is sent to and controls wheel to stablize vehicle subsequently. The starting point that ESC activates can be regarded as manipulationThe beginning of the limit.

More particularly, we can be to relative manipulation limit surplus h_xCarry out as given a definition:

Wherein, x is the deviation of kinematic variables and its reference value,Be defined in the situation that does not start ESC, ABS or TCSThe interval, dead band that x falls into. X can be any control variables (or any other suitable control change of definition in last pointAmount).

Definition h in formula (7)_xAdvantage be driving situation can be quantized be expressed as different classes of. For example, work as h_x≤ 10% time, driving situation can be classified as red area situation, in red area situation, driver pay particular attention to orTake some special action (for example, making vehicle deceleration); As 10% < h_x< 40% time, driving situation can be classified as yellow area feelingsCondition, in yellow area situation, driver needs paying special attention to of certain grade; As 40% < h_x≤ 100% time, driving situation canBe classified as general case. Under general case, driver only need to keep his normal driving notice. Certainly, also can makeUse other scope.

More particularly, let us is used in the control variables of last point of calculating h is discussed_xCalculating. Can be by establishingPut x=ω_z-ω_ztAndCome to calculate in ovdersteering situation (now, in the time that vehicle is turned left from formula (7)ω_z>ω_zt, ω in the time that vehicle is turned right_z>ω_zt) during the driftage manipulation limit surplus h of vehicle_OS, wherein, ω_zdbosIn formulaThe ovdersteering yaw rate dead band (OSDB) of definition in son (2).

Similarly, can be by x=ω be set_z-ω_ztAndCalculate in understeer feelings from formula (7)The driftage of vehicle manipulation limit surplus h under condition_US, wherein, ω_zdbusIt is the understeer yaw rate dead band of definition in formula (4)(USDB). Note, above-mentioned dead band may be the function of the amount of the yaw rate of amount, the measurement of the speed of a motor vehicle, target yaw rate etc. Turn to notDead band in dead band under foot situation (x<0) and ovdersteering situation (x>0) is different, and they are adjustable parameters.

Can be by x=β be set_r-β_rtAndCarry out to calculate from formula (7) the sideslip manipulation limit surplus of vehicleh_SSRA。

Driving force or brake force that longitudinal manipulation limit of vehicle relates to tire arrive the situation that manipulates the limit. Can be by establishingPut x=λ_i、x=0 andCome to calculate the traction control manipulation limit surplus for i driven wheel from formula (7)Also can be by x=λ be set_i、x=λ_bpAndCome to calculate for the ABS of i wheel and manipulate more than the limit from formula (7)AmountFinal traction manipulation limit surplus and braking manipulation limit surplus can be defined as:

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

Note, in the time calculating above-mentioned manipulation limit surplus, can use further screening conditions. For example, can use following barThe combination of some conditions in a following condition of conditioned disjunction in part is made as 0 by manipulation limit surplus: target yaw rateAmount exceedes specific threshold; The amount of the yaw rate of measuring is greater than specific threshold; Driver's the input that turns to exceedes specific threshold; OrPerson, limiting case, the deceleration that is greater than 0.5g, vehicle such as the turning acceleration of vehicle is greater than 0.7g, vehicle to exceed threshold valueThe speed of (for example, 100mph) is travelled etc.

For known riving condition, calculate and verify their validity in order to test above-mentioned manipulation limit surplus, assemblingThere is the vehicle of the research ESC system of being developed by Ford Motor Company to be used to carry out vehicle testing.

Pass through the riving condition that car speed, throttle and braking are drawn, measurements and calculations for what describe in Fig. 2Vehicle movement variable is as shown in Fig. 3 A to Fig. 3 C. The corresponding limit of manipulation separately surplus h_US、h_OS、h_TCS、h_ABS、h_SSRAAt Fig. 4 A extremelyShown in Fig. 4 C. This test execution is in the situation that all ESC calculate operation, the free form obstacle skiing on snow padTravel. Close brake pressure and apply, thus the real limit manipulation of vehicle approach condition.

As another test, steering vehicle on the road surface with high friction level. In Fig. 5, describe the speed of a motor vehicle, traction andBraking curve. State of motion of vehicle is shown in Fig. 6 A to Fig. 6 C. The corresponding limit of manipulation separately surplus h_US、h_OS、h_TCS、h_ABS、h_SSRAShown in Fig. 7 A and Fig. 7 B.

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

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

Consider the unexpected variation that may cause envelope manipulation limit surplus due to signal noise, use low pass filter F(z) make h_envSmoothly, thus obtain final the 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, finally manipulate limit surplus and retouch in Fig. 8Paint, and in the vehicle testing data shown in Fig. 5 and Fig. 6 A to Fig. 6 C, finally manipulate limit surplus and describe in Fig. 9.

HL index can provide the continuous variable between 0 and 1, and indicates the manipulation limit of driver and vehicle how approachingly to have(wherein, value 1 represents the manipulation limit of driver in vehicle). The HL index being somebody's turn to do based on model can be at for example low μ driving pathDuring condition, provide the driving being even more important to require information.

Supposing, along with its manipulation limit of vehicle approach, needs more vision, health and perception to note maintaining vehicle controlSystem, can infer driver's work load information from HL index. Along with driver's work load increases, HL exponent increase. WithThe work load of 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 for exampleTotal rate of change of the control action that accelerates, brakes and turn to. Increase rate of change from driver's operating level and can reflect increaseDrive requirement, vice versa. Therefore, DCA index can provide and the different drivers of vehicle control action that carry out different aspectsThe measurement of relevant rate of change (drive and require).

For example, consider that accelerator pedal rate of change is on driving the impact requiring. With reference to Figure 10 and Figure 11, for example, respectively lowIn requirement situation and high request situation, draw real-time accelerator pedal position by the time. Than the low situation that requires, in high request feelingsThe rate of change of the accelerator pedal under condition is obviously relatively larger.

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, produce and the corresponding probability of distribution of Figure 12 and Figure 13 with the gamma function of canonical form:

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

Wherein, a is scale factor, and b is form factor. Dotted line represents that low driving requires distribution of standard deviation, and solid line representsHigh driving requires distribution of standard deviation. These probability distribution of accelerator pedal rate of change illustrate to drive and require classification and current classificationThe grade of the difference between opportunity. For example, 2% standard deviation can represent low driving requirement with larger probability, and 10% standardDeviation can represent the high requirement etc. of driving with larger probability. This technology can be applied to brake pedal position, steering wheel angle similarlyAnd/or other driver's control action parameter. Therefore, DCA index can be based on for accelerator pedal, brake pedal, steering wheel etc.The rate of change of driver action estimate driver requested.

The average of the standard deviation rate of change shown in Figure 14 can change for different drivers. DCA index calculates canConsider the average of these changes and calculate relative change rate. The derivative of driver's input also can be combined into and obtain expection action.Can for example, from analyzing each factor (, accelerator pedal position/speed, brake pedal position/speed, steering wheel angle position/speedDeng) covariance determinant obtain variance calculate.

In a particular embodiment, drive by the impact based on the each factor of following formula recursive calculation the covariance requiringDeterminant calculates DCA index:

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

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

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

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

Wherein, x_kThe two-dimensional vector of (at moment k place) each driver's control action and derivative thereof,Average(it can constantly update during each driving cycle, and resets after each driving cycle), α is calibration forgetting factor,G_kBe the covariance inverse matrix of estimating, I is unit matrix, P_kThe covariance matrix of estimating,It is the Δ from formula (12)x_kTransposed matrix.

The recursive calculation determinant det of covariance matrix, provides 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 that the driving with respect to the average of specific driver is providedThe measurement of the estimation rate of change of member's acceleration, braking and/or steering behaviour. It also provides the one-dimensional measurement of population variance, wherein, can followDescribed in track, one-dimensional measurement catches the marked change of the rate of change gathering of driver's control action.

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

DCAindex=max(accelerator pedal variance, brake pedal variance, turn to variance) (17)

Use above technical Analysis as the accelerator pedal position of drawing in Figure 15 A with as the side drawing in Figure 15 BTo dish angle. Figure 15 C shows the output of the example for DCA index of the input based on Figure 15 A and Figure 15 B. In this example,The determinant (16) of covariance matrix provides driver to accelerate and the measurement of the estimation rate of change of steering behaviour. By using eachThe maximum of rate of change is created in the DCA index of drawing in Figure 15 C and each rate of change is carried out homogenization and gathered. The speed of a motor vehicleIn Figure 15 D, draw, as a reference. In DCA index, the rate of change of increase is captured as and more approach 1 value and (indicate higherDrive and require), (indicate low driving to want and the rate of change of reduction is captured as to for example value between 0 and 0.2 in DCA indexAsk).

V. instrument board index

Driver activates to the driver that can provide alternately of instrument board and/or other interface relevant with touch/voiceInstruction. The increase that such driver activates rank can increase the perception requirement to driver. As shown in table 1, driver pressesThe increase that button is pressed activation can increase driver's work load. The frequency of interaction of controlling with car cabin can be gathered for composite index,Wherein, comprise alternately rain brush control, climate controlling, volume control, running direction indicator, console control with car cabin is controlledPlatform, vehicle window control, automatic seat control, voice command interface etc. Therefore, instrument board (IP) index provides and represents driver and instrumentThe continuous wave output (between 0 and 1) that dash board, electronics and/or any other HMI are mutual.

For example, in the time of press/trigger button/interface arrangement of k at any time, output is provided by following formula:

BP_i(k)＝α·BP_i(k-1)+(1-α)·1(18)

In the time of do not press/trigger button/interface arrangement, output is provided by following formula:

BP_i(k)＝α·BP_i(k-1)+(1-α)·0(19)

Wherein, BP_iBe to press/trigger pursuit gain for the button/interface of each tracked button/interface, α is calibrationForgetting factor.

Then, the output of IP index can be provided by following formula:

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

Wherein, n is the quantity of tracked button/interface. Also can determine by any technology of gathering described hereinIP index. As example, can use with technology like the technology type of describing referring to formula (28) and (29) etc.

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

VI. interval index

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

Can obtain relying on from following formula the interval of present speed:

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

Wherein, r_p(k) be the position of k front vehicles at any time, r_f(k) be the position of following vehicle, v_f(k) be to followWith the speed of vehicle. Equispaced HW_m(k) 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:

$\mathrm{HWIndex}=\left[\mathrm{\&gamma;}(1-\frac{H{W}_M}{{\mathrm{HW}}_{\mathrm{MAX}}})\right]---\left(23\right)$

Wherein, γ is the responsive gain of HW index, HW_MAXIt is calibration value. Can be when meeting the required interval of maximal index 1Between select/regulate gain.

In other embodiments, can be based on the responsive gain of for example driver's type selecting/adjusting. If known driver's classType (such as " youth ", " old age ", " teenager ", " new hand ", " veteran " etc.), can correspondingly adjust responsive gain. Can be based onThe certificate being carried by driver known in the art is identified as driver " youth ", " old age ", " teenager " etc. Can be by carDetect certificate, and certificate is used to the type of identification of driver. Selectively, vehicle can provide and allow driver identify themThe selection button of the type of oneself. But, can use any suitable/known technology to classify to driver. For " teenager "" new hand " driver can increase responsive gain, and can reduce responsive gain for " veteran " driver etc. At other embodimentIn, can be larger value by responsive gain selection for " teenager " and " new hand " driver, and driver etc. can for " veteran "Be less value by responsive gain selection. Therefore,, the in the situation that of same intervals, HW index can be for " teenager " driver for moreLarge value and be less value for " veteran " driver etc.

Selectively (or extraly), can select/regulate responsive gain based on ambient conditions. By suitable/known skillThe humidity that art (such as take turns slip by inspection vehicle) is definite or icy roads situation can cause responsive gain to increase. Dry roadsSituation can cause responsive gain to reduce. Can select with any suitable ambient conditions that comprises traffic density, geographical position etc.Select/change responsive gain.

Can also with like compute classes in formula (21), (22) and (23), calculate and infrastructure interval apart,Wherein, infrastructure comprises crossroad, highway, high request highway geometry etc. In this case, HW index can by underFormula obtains:

HWindex=max(HW₁,HW₂,......HW_n)(24)

Wherein, n is the quantity that just tracked height is driven the project of the separation requiring. Also can use for formula(24) weighting function.

The interval of the increase of returning from the volume of traffic of the increase of adjacent lane in other embodiments, can be used as HW indexDeviation (bias) input. (traffic density of increase can increase driving requirement, shown in table 1. )

In other embodiments, can in the scheme that is less than 1000ms, follow the tracks of collision time. Bump potential being about toSituation under, HW index output 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 $t_c=\frac{X}{V_x}$

Wherein, V_xClosing speed, A_xBe relative acceleration, X is the distance between vehicle. Can be from any suitable/knownRadar system, vision system, laser radar system, car obtain range and range rate information to car communication system etc.

Consider to follow in example vehicle the calculating of the HW index in scene, Figure 18 to Figure 20 illustrates the main car during this sceneClosing speed and distance travelled between speed, vehicle. Figure 21 and Figure 22 show respectively interval (calculating by formula (22))With HW index (calculating by formula (23)).

VII. rule-based subsystem

Referring again to Fig. 1, rule-based subsystem 12 can comprise the fact for determining event binary system output identificationAnd knowledge base. Subsystem 12 can provide specific specialists engineering science and vehicle driver's environmental interaction rule using as its of system 10Supplementing of its assembly. Knowledge can be represented as one group of rule. Can comprise the specific activation of Vehicular system.

Each rule is specified the suggestion of output services burden, and if have (condition), (action) structure then. When meetingThe part that the performs an action when condition part of rule. Each rule can be specified the suggestion (0 or 1) of output services burden. Can be to appointWhat suitable/known mode by subsystem 12 from the CAN bus monitoring of for example vehicle/obtain multiple vehicle parameters, described vehicleParameter comprises that longitudinal acceleration, transverse acceleration, deceleration, steering wheel angle, button use etc. are (for example,, in Table 2a and table2b). Can be used for arranging conditional plan with the true and combination of these parameter correlations.

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

If

Vehicle_parameter1>x_iAnd Vehicle_parameter2 > y_i

(26)

Enable specific delays or the restriction for car cabin system or information entertainment during event from Expert Rules. BaseIn regular output also can be processed making for carrying with the driving requirement for condition of advocating based on expert and special characteristicGather for relevant output.

Rule can, based on information, for example, be listed in above table 2a and 2b. For example, if steering wheel angle > 105 degree,Event_Flag=1(event flag=1). Certainly, also can build Else Rule.

VIII. gather

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

In a particular embodiment, short-term gather can be used to scheduling/postpone/postpone by be transferred to driver's information/Task. The highest driving of estimating at needs requires, T index can be provided by following formula:

TIndex＝max(DCAIndex，IPIndex，HLIndex，HWIndex)(27)

In other embodiments, average/maximum output combination of exponential quantity as described below is adopted to the remittance that relies on environmentAlways. For example, with reference to Fig. 1, DCA index, IP index, HL exponential sum HW index can be combined to form by following formula by subsystem 14 and provideT index:

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

Wherein, w_iIt is the weight that basis is added to the dependence environment of the driving required value in input. Launching formula (28) obtains:

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

Max(Tracking_Index)＝1.0

Wherein, WLE_DCA、WLE_IP、WLE_HL、WLE_HWRespectively DCA index, IP index, the output of HL exponential sum HW index. PhaseThe weight of answering is by w_DCA、w_IP、w_HL、w_HWProvide.

Table 3 and table 4 are listed the example rule for gathering.

Table 3

For the example rule gathering based on environment

Table 4

For the more example rules that gather based on environment

Subsystem 16 can gather rule-based exponential sum T index by the technology of describing with reference to subsystem 14 aboveFor WLE index. As example, WLE index can be provided by following formula:

WLEIndex＝max(TIndex，Rule-BasedIndex)(30)

Exemplary rule-based index, IP exponential sum DCA index are drawn respectively in Figure 23 A and Figure 23 C. For considerationThe highest driving estimated require the situation of situation, used technology described here to gather these indexes and at figureIn 23D, draw. In Figure 23 E, draw the speed of a motor vehicle, for reference.

IX. characterize for a long time

In other embodiments, can be by subsystem 16 and/or scheduler 18(according to configuration) characterize in time WLE indexSo that HMI suggestion to be provided. Long-term WLE characterizes and can make the driving of HMI based in time require to be customized by driver. For example, examineConsider r_kThat reflection is (at any time k) for the variable of driver's WLE exponential quantity. Suppose drive require be classified as with a,B, 3 classes that c} represents, and there is the fuzzy membership functions μ as defined in Figure 24_a、μ_b、μ_c. Then, driving behavior d_kCan underIn the example calculations of face, infer:

d_k＝[μ_a(r_k)，μ_b(r_k)，μ_c(r_k)](31)

For example,, if r_kValue be 0.4, d_kCan be represented as [0.18,0.62,0] (according to Figure 24). Filtered (longPhase) distortion 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 is that (thereby α specifies/determine the driving behavior of assessment TERM DEFORMATION to calibration forgetting factorTime period). PinTo the long-term probability (p of each classification_k)_iCan obtain from following formula:

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

According to formula (33), for the filtered distortion driving behavior of each classificationDivided by for all categoriesFiltered distortion driving behavior sumFor example, ifBe represented as [0,0.16,0.38],(p_k)_aTo equal 0 divided by 0+0.016+0.38((p_k)_aTo equal 0), (p_k)_bTo equal 0.16 divided by 0+0.016+0.38((p_k)_bTo equal 0.29), (p_k)_cTo equal 0.38 divided by 0+0.016+0.38((p_k)_cTo equal 0.71).

Then, drive the final long-term WLE index requiring and characterize 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, can infer and drive row from formula (34)For current in " high request " classification.

X. scheduler

The WLE index that scheduler 18 can computation, the long-term sign of WLE index or DCA index, IP index, HL indexWith any one (for only using/calculate/determine the embodiment of single index) in HW index come to information entertainment systems and/Or modulating alternately between other conversational system and driver. WLE index provides the work load load of estimation, for establishingPut/avoid/customization/restriction/dispatch voice command and other task of being presented to driver, to improve functional and safetyProperty.

Can comprise alternately with driver's example: the conversion of generation Text To Speech, generation incarnation are communicated by letter, produced about incoming callThe prompting of phone, produce perspective dynamical system order, produce perspective voice suggestion, produce sense of touch via for example feeling steering wheelRespond or produce other audio frequency, vision and/or sense of touch output etc. Each task in these examples driver interface task canThere is relative priority. For example, produce and can there is high priority about the prompting of Inbound Calls, and produce perspective languageSound suggestion can have low priority.

Any suitable/known technology can be used to priority type to distribute to given driver's interface task. As showingExample, scheduler 18 can be realized high/low priority protocol, wherein, all promptings about Inbound Calls that produced is distributed highPriority, the suggestion that all vehicles that are sent to driver are initiated distributes low priority. But, can use other priorityScheme. As example, the numeral between 0 and 1.0 can represent the priority of task: particular task can be distributed 0.3 priority, andOther task dividable is joined 0.8 priority etc. In other embodiments, can by produce task known in the art controller/Processor/subsystem (not shown) distributes the priority type relevant to driver's interface task.

Therefore, specific embodiment can allow driver's interface task to be by dispatching sequence based on work load and priorityExisting. For example,, if WLE index (or any one index depending on the circumstances) has the value between 0.4 and 0.6, scheduler18 can only allow to carry out high priority driver interface task. The value that is less than 0.4 at WLE index, scheduler18 can be scheduling to more late execution by lower priority tasks. For example,, if WLE index has the value between 0.7 and 1.0,Scheduler 18 can stop the execution of all driver's interface tasks. During these high workload burdens, reach little at WLE indexIn the situation of the value in 0.7, scheduler 18 can be scheduling to high-priority task more late execution, is less than 0.4 at WLE indexThe situation of value under, scheduler 18 can be scheduling to more late execution by lower priority tasks.

Similarly, if long-term driving behavior is characterized by " high request ",, regardless of its priority, specific/all task canBe postponed/delayed/scheduled, until long-term driving behavior is characterized by " middle requirement " or " low requirement ". Selectively, if driven for a long timeThe behavior of sailing has in for example any probability of " high request " classification, and specific/all task can be postponed/delayed/scheduled, straightBe 0 to the probability in " high request ". Certainly, other scheme is also feasible. For example, be not used to appointing in priority typeIn the embodiment of business classification, all tasks can be postponed/delayed/scheduled according to the work load of inferring.

In the situation that receiving Inbound Calls during high workload burden, scheduler 18 can proceed to Inbound Calls voice postalPart system. Once WLE index reaches appropriate value, scheduler 18 just can produce indicates the prompting that receives Inbound Calls.

Algorithm disclosed herein can be sent to treating apparatus, any/complete such as in system 12,13,14,16 and 18Portion, described treating apparatus can comprise any existing electronic control unit that takes various forms or special electronic control unit,Described various ways includes but not limited to: permanent storage is can not write information in storage medium (such as ROM device) and variableBe stored in the information that can write on storage medium (such as floppy disk, tape, CD, ram set and other magnetic and light medium). DescribedAlgorithm also can be embodied as the executable object of software. Selectively, can use suitable nextport hardware component NextPort (such as special IC(ASIC), field programmable gate array (FPGA), state machine, controller) or other nextport hardware component NextPort or device or hardware, softwareCarry out implementation algorithm whole or in part with the combination of fastener components.

Although illustrated and described embodiments of the invention, be not intended to make these embodiment to illustrate and describe thisThe likely form of institute of invention. The word using in description is descriptive words instead of restricted word, should be understood thatDo not depart from the situation of the spirit and scope of the present invention and can carry out various changes.

Claims (10)

1. for managing a method for multiple driver's interface tasks, comprising:

Driver's work load is categorized as to multiple work load classifications of the driver's work load that represents different brackets;

In special time period, determine that driver's work load falls into the relative frequency of each classification;

Based on relative frequency to dispatching for the described task of carrying out;

According to task described in scheduled for executing.

The method of claim 1, wherein based on relative frequency to the step of dispatching for the described task of carrying outSuddenly comprise: determine the maximum relative frequency in described relative frequency.

3. method as claimed in claim 2, wherein, dispatches described task according to the relative frequency of described maximum.

4. the method for claim 1, wherein determine that driver's work load falls into the step of the relative frequency of each classificationSuddenly comprise: for each classification, the driver's work load based on from current slot and from the driving of time period in the pastThe scale factor of member's work load and definite fixed time section is determined long-term driver's work load.

5. the method for claim 1, wherein described multiple driver's interface task comprises at least one in following operationIndividual: to produce audio frequency output, produce vision output and produce sense of touch output.

6. a vehicle, comprising:

At least one processor, is configured to (I) and driver's work load is categorized as to the driver's work that represents different bracketsMultiple work load classifications of burden, (II), in special time period, determines that driver's work load falls into the phase of each classificationTo frequency, (III) receives the multiple driver's man-machine interface tasks that are performed, (IV) based on relative frequency to for carrying outDescribed task is dispatched, and (V) is according to task described in scheduled for executing.

7. vehicle as claimed in claim 6, wherein, described at least one processor is also configured to: determine described relative frequencyMaximum relative frequency in rate.

8. vehicle as claimed in claim 7, wherein, dispatches described task according to the relative frequency of described maximum.

9. vehicle as claimed in claim 6, wherein, described at least one processor is also configured to: for described multiple worksMake the each classification of burden in classification, the driver's work load based on from current slot and from driving of time period in the pastThe scale factor of the person's of sailing work load and definite fixed time section is determined long-term driver's work load.

10. vehicle as claimed in claim 6, wherein, described multiple driver's man-machine interface tasks comprise in following operationAt least one: produce audio frequency output, produce vision output and produce sense of touch output.