CN107544330A - The dispatching method and device of autonomous adjustment - Google Patents

Abstract

This application discloses a kind of dispatching method and device of autonomous adjustment.Methods described includes：Receive the Condition Monitoring Data of one or more vehicles；Adjustment project and adjustment demand levels are treated according to what Condition Monitoring Data determined each vehicle；One or more test vehicles are selected from one or more vehicles according to adjustment demand levels；Test vehicle is sent and treats adjustment project, test vehicle is treated that adjustment project carries out autonomous adjustment to corresponding；The scheduling planning of one or more vehicles is determined according to the result of the autonomous adjustment of test vehicle and adjustment demand levels；Scheduling planning is sent to one or more vehicles, so that one or more vehicles carry out autonomous adjustment according to scheduling planning.The method and device that the embodiment of the present application provides determines that the adjustment of vehicle is planned by the state and adjustment history of the multiple vehicles of synthesis, so as to while the safety and reliability of vehicle is ensured, realize the quick flat of adjustment of extensive vehicle along running scheduling.

Description

The dispatching method and device of autonomous adjustment

Technical field

The application belongs to technical field of vehicle detection, more particularly to a kind of dispatching method and device of autonomous adjustment.

Background technology

Automatic driving vehicle is compared with orthodox car, and it is equipped with more intelligent parts such as laser radar, tests the speed, presses The sensing systems such as power, temperature and various control systems, pilotless automobile are highly dependent on number caused by these sensors According to and be based on automatic Pilot strategy caused by these data.But the particular elements in vehicle due to a variety of causes such as software upgrading, Part replacement, network instruction (such as server compulsive requirement) and abrasion and/or season, a variety of causes of weather change over time Adjustment again (including verify, test and calibrate) is needed Deng under conditions of.Pilotless automobile is inputted also just based on perception It is control of the data and then realization gathered using sensing system to automatic driving vehicle, therefore to the tune of intelligent parts parameter The adjustment requirement of school especially sensor-based system becomes very strict, substantially zeroed error tolerance.

On the one hand, the uninterrupted operation of pilotless automobile requires that vehicle can independently be calibrated, tested, failure is repaiied It is multiple；On the other hand, the feature of pilotless automobile, which also determines, to be completed using the mode that Traditional Man participates in, especially In the case where deploying largely shared pilotless automobile.

However, a technological challenge is, the calibration of a large amount of pilotless automobiles, test, the demand of fault restoration are possible Occur in the identical period.For example, whole pilotless automobile fleet by network upgrade new software systems, with a collection of The sensor service life of secondary pilotless automobile fleet reaches identical prover time point, and nobody of a collection of new dispensing drives Sailing automotive fleet needs test etc. before road.The calibration requirements of burst may cause serious resource congestion in short time, such as Need the test event in particular calibration place that the vehicle being largely lined up, then for example a large amount of vehicles can be caused to be calibrated and to whole The transport bearing capacity of fleet, which is brought, significantly to be fluctuated, then such as vehicle concentrates the peak value brought to network transmission calibration data Data transfer.This fleet's state fluctuation brought by impulse type calibration requirements is neither also unfavorable for beneficial to the quickly calibrated of vehicle The delivery operation of smooth-going.

In addition, for the adjustment largely concentrated, directly challenge is for another, if disposably to all software systems Upgrade and calibrate, when new software systems have compatible or stability problem, whole fleet all suffers from the risk that can not be run.

To sum up, it is frequent, a large amount of autonomous adjustment demands concentrated of reply pilotless automobile, it is necessary to which design is a kind of Schedulable and safe and reliable adjusting process.

The content of the invention

The embodiment of the present application provides a kind of dispatching method and device of autonomous adjustment.

In a first aspect, a kind of dispatching method of autonomous adjustment is provided in the embodiment of the present application, including：

Receive the Condition Monitoring Data of one or more vehicles；

Adjustment project and adjustment demand levels are treated according to each vehicle of Condition Monitoring Data determination；

One or more test vehicles are selected from one or more of vehicles according to the adjustment demand levels；

The test vehicle is sent and treats adjustment project, the test vehicle is treated that adjustment project is carried out independently to corresponding Adjustment；

One or more of cars are determined according to the result of the autonomous adjustment of the test vehicle and the adjustment demand levels Scheduling planning；

The scheduling planning is sent to one or more of vehicles, so that one or more of vehicles are according to the tune Metric, which is drawn, carries out autonomous adjustment.

Optionally, the Condition Monitoring Data includes：Software information, hardware information, system operation information, sensor letter One or more in breath, car outer shroud environment information and environment inside car information.

Optionally, it is described to select one or more test vehicles and include：According to the adjustment demand levels, from one Or the vehicle set for meeting a minimum diversity requirement is chosen in multiple vehicles, using the vehicle in the vehicle set as institute State test vehicle.

Optionally, methods described also includes：Adjustment result to the test vehicle carries out statistical analysis；

The scheduling planning of one or more of vehicles is determined according to statistic analysis result.

Optionally, it is described determine each vehicle treat that adjustment project further comprises：According to described in rolling stock Need to treat adjustment project described in the priority selection of the project of adjustment.

Optionally, the scheduling planning for determining one or more of vehicles includes：According to the position of each vehicle Put and determine its affiliated coverage；According to the sequence of the adjustment demand levels of all vehicles in each coverage come Determine the scheduling planning；Wherein, the scheduling planning includes：Each vehicle carries out time, place and the project of adjustment.

Optionally, the adjustment demand levels for calculating each vehicle include：Institute is calculated for each vehicle State the discrete demand grade for treating adjustment project；Utilize the probability of demand data that adjustment project is treated described in vehicle calculating described in one group； The adjustment demand levels of each vehicle are determined according to the discrete demand grade and the probability of demand data.

Optionally, methods described also includes：Gather the implementing result of the scheduling planning；According to the implementing result again Calculate the adjustment demand levels of each vehicle；Advised according to the adjustment demand levels renewal scheduling after calculating again Draw.

Optionally, methods described also includes：The coverage is divided according to the capacity at each adjustment center dynamic.

Second aspect, the embodiment of the present application provide a kind of dispatching device of autonomous adjustment, including：

Receiving unit, for receiving the Condition Monitoring Data of one or more vehicles；

Determining unit, for treating adjustment project and adjustment need according to each vehicle of Condition Monitoring Data determination Seek grade；

Module of selection, for selecting one or more from one or more of vehicles according to the adjustment demand levels Test vehicle；

Transmitting element, adjustment project is treated for being sent to the test vehicle, makes the test vehicle wait to adjust to corresponding School project carries out autonomous adjustment；

Scheduling planning unit, determined for the result according to the autonomous adjustment of the test vehicle and the adjustment demand levels The scheduling planning of one or more of vehicles；

Scheduling unit, for sending the scheduling planning to one or more of vehicles, so that one or more of Vehicle carries out autonomous adjustment according to the scheduling planning.

Optionally, the Condition Monitoring Data includes：Software information, hardware information, system operation information, sensor letter One or more in breath, car outer shroud environment information and environment inside car information.

Optionally, the module of selection includes：Minimum diversity chooses module, for according to the adjustment demand levels, The vehicle set for meeting a minimum diversity requirement is chosen from one or more of vehicles, by the vehicle set Vehicle is as the test vehicle.

Optionally, described device also includes：Adjustment interpretation of result unit, for being tried described in the history adjustment data The adjustment result for testing adjustment project carries out statistical analysis；Scheduling unit, for according to statistic analysis result determine it is one or The scheduling planning of multiple vehicles.

Optionally, the project determining unit includes：Adjustment project chooses module, for the need according to rolling stock Want to treat adjustment project described in the priority selection of the project of adjustment.

Optionally, the scheduling planning unit includes：Region affiliation module, it is true for the position according to each vehicle Its fixed affiliated coverage；Regional planning module, for the adjustment need according to all vehicles in each coverage The sequence of grade is asked to determine the scheduling planning；Wherein, the scheduling planning includes：Each vehicle carry out adjustment when Between, place and project.

Optionally, the determining unit includes：Discrete demand computing module, described in being calculated for each vehicle Treat the discrete demand grade of adjustment project；Probability of demand computing module, for treating adjustment using described in vehicle calculating described in one group The probability of demand data of project；Level determination module, for true according to the discrete demand grade and the probability of demand data The adjustment demand levels of fixed each vehicle.

Optionally, described device also includes：Results acquisition unit, for gathering the implementing result of the scheduling planning；Need Grade computing unit again is sought, for calculating the adjustment demand levels of each vehicle again according to the implementing result；Scheduling Updating block is planned, for updating the scheduling planning according to the adjustment demand levels after calculating again.

Optionally, described device also includes：Area division unit, divided for the capacity dynamic according to each adjustment center The coverage.

In the another further aspect of the embodiment of the present application, a kind of electronic equipment is also provided, including：

Memory and one or more processors；

Wherein, the memory is connected with one or more of processor communications, and being stored with the memory can quilt The instruction of one or more of computing devices, the instruction is by one or more of computing devices, so that described one Individual or multiple processors can realize method as described above.

At the another aspect of the embodiment of the present application, a kind of computer-readable recording medium is also provided, it is characterised in that described Be stored with computer executable instructions in computer-readable recording medium, the computer executable instructions be performed after to reality Now method as described above.

Brief description of the drawings

, below will be to embodiment or existing in order to illustrate more clearly of the embodiment of the present application or technical scheme of the prior art There is the required accompanying drawing used in technology description to be briefly described, it should be apparent that, drawings in the following description are only this Some embodiments of application.

Fig. 1 is a typical application scenarios schematic diagram in the embodiment of the present application；

Fig. 2 is the schematic diagram of the dispatching method for the autonomous adjustment that the application one embodiment provides；

Fig. 3 is the checking scheduling schematic diagram of the vehicle based on server end of the application another embodiment offer；

Fig. 4 is the polycentric checking scheduling schematic diagram that the application further embodiment provides；

Fig. 5 is the block diagram of the dispatching device of the autonomous adjustment of the application another embodiment offer；

Fig. 6 is the module frame chart of the dispatching device of the autonomous adjustment of the application another embodiment offer；

Fig. 7 is the electronic devices structure figure of the application another embodiment offer；

Fig. 8 is realization and/or propagates a kind of structured flowchart of example of the universal computing device of technical scheme.

Embodiment

To enable present invention purpose, feature, advantage more obvious and understandable, below in conjunction with the application Accompanying drawing in embodiment, the technical scheme in the embodiment of the present application is clearly and completely described, it is clear that described reality It is only some embodiments of the present application to apply example, and not all embodiments.Based on the embodiment in the application, people in the art The every other embodiment that member is obtained under the premise of creative work is not made, belong to the scope of the application protection.

It will be understood by those skilled in the art that the term such as " first ", " second " in the application is only used for distinguishing difference and set Standby, module or parameter etc., any particular technology implication is neither represented, also do not indicate that the inevitable logical order between them.

Fig. 1 is the typical case scene of the dispatching method of the autonomous adjustment in the embodiment of the present application.As shown in figure 1, in vapour Car 101,104,105 is in during unpiloted traveling, and multiple sensor (not shown) gather in the traveling of automobile 101 in real time Various data, sensor can include laser radar, binocular camera, monocular cam, millimetre-wave radar, infrared radar, Global positioning system (GPS), Inertial Measurement Unit, attitude transducer etc., unmanned device is right according to the data collected The drive system (not shown) of vehicle, such as steering, dynamical system, brake system, suspension are controlled, so as to real Existing vehicle realizes the traveling of safety in the case of no driver's intervention, or less intervention.Pass through in automobile 101,104,105 High in the clouds 102 and server 103 update new software systems, and to carry out the upgrading of system, high in the clouds and server can enter to vehicle Row scheduling.Communication link between vehicle, high in the clouds and server can include various connection types, such as wireless communication link Road, global positioning system or fiber optic cables etc..The dispatching method of the autonomous adjustment in the embodiment of the present application is carried out below Describe in detail.

Fig. 2 is the dispatching method schematic diagram for the autonomous adjustment that the application one embodiment provides.As shown in Fig. 2 this method Comprise the following steps：

Step 201, the Condition Monitoring Data of one or more vehicles is received；

In one embodiment, vehicle includes various parts, and the various parts are included in software, sensor, interface etc. One or more.Described software is soft including platform management software, tire driving and management program, laser radar driving One or more in part, camera driver software and speed control software etc.；Described sensor include laser radar, Binocular camera, monocular cam, millimetre-wave radar, infrared radar, global positioning system (GPS), Inertial Measurement Unit, posture One or more in sensor etc.；The interface includes a kind of or more in touch-screen, communication interface, network interface etc. Kind.

In certain embodiments, the Condition Monitoring Data of the vehicle, including the sensor of vehicle, vehicle part and vehicle-mounted The state of electronic equipment, specifically including software information, hardware information, system operation information, sensor information, outside input letter One or more in breath etc..The software information includes the version of software, the check code of software, the user name and use of software One or more in family password etc.；Described hardware information is included in ID, MAC Address and physical address of hardware etc. One or more；Described system operation information includes the operation duration of system, the duration calibrated apart from last time, running log Or one or more in system mistake etc.；Described sensor information refers to the real time data that sensor collects, such as The range data that laser radar and camera collect, the position data arrived of GPS gathers etc.；Described external input information bag Include information, the information of server push, external monitoring/information of sensing equipment input, the periphery of driver or car owner's input Other vehicles input information, traffic control system input one or more in information etc..The state can reflect vehicle Whether need to perform an adjustment task.

The example above, which is merely for convenience of, understands vehicle-state Monitoring Data, does not do any limit to vehicle monitoring data System, as long as data caused by vehicle or the data applied to vehicle all should be included.It should be noted that the adjustment Including calibrating, verifying, detecting and/or testing, hereafter corresponding expression way will be used according to the adjustment task actually performed.

Step 202, adjustment project and adjustment demand etc. are treated according to each vehicle of Condition Monitoring Data determination Level；

In one embodiment, whether adjustment is needed according to default condition judgment.Specifically, when state is believed for software Breath, preparatory condition be when detect the version number of software there occurs change, software check code there occurs change, user name and use Family password is increased, deleted or changed, and after software is upgraded, the platform management software of vehicle (is used for whole car The management of each part) read write-in fixed position each software module version number, including platform management software, tire driving And management program, laser radar drive software, camera driver software etc., if the software version change of part, then it is assumed that related Part need calibrated.When state is hardware information, such as hardware ID, MAC Address or physical address, preparatory condition is works as Detect that hardware ID, MAC Address or physical address are changed, now think that hardware is changed, then it is assumed that the hardware Need to be calibrated.When state is system operation information, preparatory condition is that system operation duration exceedes first threshold, away from previous school More than accumulative warning number in Second Threshold, daily record more than the 3rd threshold value and gross error occurs for punctual length, such as system operation Duration crashes more than 7 days, away from previous calibration duration more than warning number is added up in 3 days, daily record more than 10 times, system, this When represent corresponding to part need to recalibrate.When status information is sensor information, preparatory condition is sensor information with before Secondary calibrated first data are not inconsistent or judgement of multiple sensors to same situation is different, specifically, at least can be with Abnormality detection is carried out according to following several sensor informations：(a) distance measuring sensor, for same target, the multiple sensors of vehicle Independently measure obtained distance and have preferable uniformity under normal circumstances, the scope that mutual gap allows in error it It is interior, if judging the result of some or some sensor instrument distances with other sensor instrument distance results or its mean difference more than one Fixed threshold value, then it is assumed that the sensor needs to recalibrate；(b) vision sensor, for same target, the multiple visions of vehicle pass Sensor independently measures obtained corresponding some regions brightness or aberration has preferable uniformity under normal circumstances, mutually it Between gap within the scope of error permission, if judging some regions brightness or the aberration of some or some sensors measurement Exceed certain threshold value with other sensor measurements or its mean difference, then it is assumed that the sensor needs to recalibrate. The abnormal judgement of other types of sensing data, also takes similar mode, will not be repeated here.When state is an externally input Information, preparatory condition, which is an externally input one or more of information, includes calibration command or the serious police to Vehicular behavior Show, for example server directly sends calibration command to vehicle, it is tight that traffic control system directly warns the transport condition of vehicle to exist Weight problem, either from Vehicle manufacturers or car operation side, calibration is proposed for the service condition of particular vehicle, such as After heavy rain, after heavy snow, either there occurs small accident or certain car will arrange a long-distance travel for certain car, this When illustrate that the external world is found that vehicle goes wrong, it is necessary to recalibrate.

In one embodiment, same vehicle or multiple vehicles may have multiple projects to need adjustment, now can root Adjustment project is treated to choose according to the priority of adjustment project, such as is related to the adjustment priority of speed control and is greater than in-car temperature Spend the adjustment of control.

In one embodiment, adjustment project is the calibration to sensor.Such adjustment task is to be used for adjustment Within the scope of current sensor performance maintains one effectively.Because the continuous service of sensor may bring accumulative mistake Difference, pilotless automobile need to calibrate sensor.

In another embodiment, adjustment project is software and hardware test, because the software systems of vehicle may pass through network Constantly renewal, and new software and the existing hardware system of vehicle whether can compatible needs progress is corresponding tests.Meanwhile Due to vehicle maintenance, the variation of vehicle hardware may also be brought by updating.Such as taken using a new laser sensor For old sensor.The purpose of this test is the compatibility of the new software and hardware system of checking.Herein, the compatibility of system is Refer to, after software or hardware component has been changed, both carry out the interaction of input and output by interface, realize the traveling to vehicle Control, the expected performance level of command character unification.

In another embodiment, adjustment project is fault detect, and fault detect is also a kind of testing for pilotless automobile Card task.Due to lacking the on duty of driver, vehicle needs automatic progress fault detect, can be by various kinds of sensors and control The daily record of part processed is analyzed so as to carry out Fault Identification, and then judges whether vehicle is in malfunction.

In pilotless automobile field, adjustment can be divided into several types：

A：The adjustment that vehicle can be performed voluntarily, because sensor and vehicle-mounted meter that these adjustment can be by itself Calculation machine program carries out continual monitoring.Such as the monitoring of tire pressure, the monitoring of electricity, the monitoring of cabin temperature, suspension Monitoring etc..

B：Another adjustment needs to be arranged and dispatched by server or operation centre, such as needs to use spy Fixed resource, than if desired for certain object of reference, it is therefore desirable to which server or operation centre are planned and arranged.For another example Need server to be recorded by contrasting big data, the potential problems of vehicle could be found.For another example detection after software upgrading and Checking, and the checking after assault, both of which need to use the related data that server end stores, it is therefore desirable to service The participation at device end.

In one embodiment, a checking detection simply simple counting to using course.For example, detection is appointed Business is to follow the trail of the time of various kinds of sensors continuous service, and vehicle tyre distance travelled, data volume caused by sensor counts, battery Discharge and recharge number etc..

In another embodiment, the checking detection is a judgement to vehicle-state.Such as tire pressure and one Otherness between individual reference data, the difference between battery electric quantity state and a reference data.

In another embodiment, the triggering of the checking detection be one to vehicle drive software and/or hardware more Newly.For example, vehicle has downloaded a kind of new unmanned algorithm, vehicle has changed a new sensor element, and vehicle is changed New suspension, turn to, brake, the related vehicle device such as throttle.

In another embodiment, the checking detection is the detection to a unknown failure state.For example, it can not perform Automatic Pilot algorithm, power input can not be obtained, abnormal tire pressure, vehicle unit status is abnormal, the sensing of None- identified Device data etc..

In another embodiment, the checking detection includes the configuration to detecting environment, it is necessary to dispatch buses traveling extremely Particular location (including aligned environment).For example laser radar or vision sensor need specific environment, so as to by the result Compare with the otherness referred between Truth data.This includes the environmental variances such as the time that detection performs, place, external tool. For example, the time that sensor states detection performs can be arranged on sometime point, to obtain the sensor under the time point Performance state.Such as imaging sensor is more sensitive to illumination condition, therefore the performance state under different time points has substantially Difference, therefore detect the status information for configuring and a certain sensor being obtained by using special time point.In addition, exist The section of some daily travelings, can be by setting special detection auxiliary equipment, such as reflecting pole, Quick Response Code, rangefinder etc. Facility auxiliary vehicle carries out Detection task.And automatic Pilot algorithm needs to carry out under the complexity traffic conditions of road surface in real time, therefore The test of automatic Pilot algorithm can be ensured by detecting the configuration of environment.

In another embodiment, verify that detection cycle includes the frequency that checking detection performs, checking detection every time performs Time span, twice checking detection between most long interval can time correlation configuration.

In another embodiment, verify that the data structure of testing result and feedback method include how to handle, store, send out The result that censorship is surveyed.Wherein, including the processing to initial data, compress, store, send.The transmission of examining report can be week It is that phase property is carried out or by specific events trigger.For example, the data volume of laser radar is big, therefore can use relatively low The method of frequency is sent by wirelessly or non-wirelessly network.For another example can handle the data of laser radar, and only send Result (such as Occupancy Grid Mapping) after processing is transmitted again, can thus reduce the data of transmission Amount.Every fixed time period, vehicle is by above-mentioned course data, such as sensor usage time, tread life, sensing The accumulative data of device beam back server by network.For another example vehicle detection is to a failure, and the Trouble Report is sent out immediately Server is returned, and adheres to the information such as failure cause, sensing data of correlation.

In one embodiment, server is according to the data of a large amount of vehicles of acquisition, by the statistics to data and contrast, A checking demand levels are calculated for each vehicle.It is discrete that demand levels are that the mode based on predefined principle calculates Value, that is, demand levels are under the jurisdiction of a classification.Shown in following form, 4 grades of discrete demand levels are shared.According to predefined Criterion, server can calculate the score of demand levels.

Table1：The calculating of discrete demand grade

Demand levels	Checking demand	Automatic driving vehicle demand
			1	Without checking	Without any demand
2	Time limit is verified	Checking is completed in time predefined
			3	Verify immediately	It is immediately performed one-time authentication
4	Stop travelling and verifying immediately	Need to stop travelling immediately

For example, it is assumed that tire pressure is p, demand levels r, then a calculation criterion be

For another example sensor error is σ, then a calculation criterion is

For another example assuming that laser radar signal state δ=0 represents does not receive laser radar signal, δ=1 represents and received Laser radar signal.Then a calculation criterion is

Similar, Δ can indicate whether vehicle software upgrades, if by upgrading, vehicle needs to be verified, such as Fruit by upgrading, then need not verified.

Calculation criterion can also be calculated by the combination of multiple parameters, such as

R=f (p, σ)

Wherein f is a formula that demand levels are calculated according to two variables.For some special circumstances, can use pre- The method (rulebasedmethod) of criterion is defined, can be by the state assignment of any pilotless automobile to predefined A demand levels in.Such as：When key sensor breaks down, automatic driving vehicle should calibration verification immediately.Compare again Such as, it is necessary to judge to be verified accordingly after system software upgrading.

For another example the data renewal of the entry region map of a renewal, it is necessary to which vehicle is immediately performed, the needs of upgrading Can is calculated as 4.However, because entry region is related to locality, then the vehicle of different location is distributed in Score that may be final is different.For example, it is probably 2 that the vehicle away from entry region, which calculates score, close to entry region Vehicle calculates and is scored at 3, and the vehicle in entry region is scored at 4.

For another example due to the difference of vehicle, vehicle is equipped with different hardware systems.Such as server or operation centre's hair When a certain program for having showed current automatic Pilot has security breaches, discrete demand etc. can be calculated according to the difference of vehicle Level.Such as the pilotless automobile that can be run at high speed is scored at 4 to the program upgrading for security breaches, and the garden of low speed Vehicle is scored at 2.

Method specifically based on a fixed criterion may have many kinds, not enumerate herein, its core is area Separating vehicles are to adjustment demand degree of urgency.

In addition, server can calculate according to substantial amounts of travel condition of vehicle data and draw an event of vehicle Barrier state, and according to the malfunction, discrete demand levels are calculated.For example, server can gather largely normally The sensing data of vehicle is run, path planning decision-making, the execution data of strategy is travelled and is counted, and then obtains a peace Full numerical intervals.If the data of a vehicle fall into security value (s) section, then it is assumed that its normal operation；If vehicle Data exceed security value (s) section, then it is assumed that failure be present.For example, detect vehicle sensors (vision positioning and GPS) number Deviation is frequently present of between, according to the size and frequency of deviation, vehicle can be needed to verify setting corresponding demand grade. Again for example, server will be seen that a certain vehicle has relatively big difference with speed and acceleration of other vehicles in same section, this When, the vehicle is identified as potential fault car.For each checking demand, the behavior of automatic driving vehicle also has accordingly Change.Such as demand levels are 1, now pilotless automobile is without great checking demand.

In another embodiment, demand levels are a continuous probable values being calculated by multivariable (probabilitybasedmethod).Such as：

R=f (x1, x2, x3 ..., xN)

Wherein x1, x2, x3 ..., xN are multiple report variables of automatic driving vehicle feedback, and each variable is in certain journey Determine vehicle currently to the demand of checking on degree.A kind of calculation is, by a polynomial method to probability of demand Calculated：

R=f (x1, x2, x3 ..., xN)=a1x1+a2x2+a3x3+ ... aNxN

Wherein a1, a2, a3 ..., aN are one group of weighted values, for adjusting the contribution between parameters to verifying demand. Weighted value can be determined by the principle being pre-designed, such as balance influence of each factor to checking demand.Other one Kind mode, can determine these weighted values by the statistics to mass data, and then by the method for machine learning.For example, adopt Collect the data of a large amount of vehicles, and probability of demand is demarcated according to artificial mode.By optimizing with minor function, it is possible to To the weighted value of correlation

argmin_{a1,a2,a3,…,aN}||r_g-r′_g||

Wherein r_gIt is the demand levels of one group of vehicle, r '_gIt is the vehicle demand levels by manually demarcating.Except using upper Polynomial method is stated, the method for neutral net can also be used to calculate the checking probability of demand of a vehicle.By to vehicle Demarcated, and using the detection data of vehicle as input, network is trained using mass data.One may finally be obtained The individual neutral net for being used to predict vehicle probability of demand.

As follows, one group of vehicle is as follows by the probability of demand data being calculated：

Vehicle 1[0.9]Vehicle 2[0.8]Vehicle 3[0.1]

In another embodiment, both the above method is combined：Calculated by a method based on criterion Discrete demand levels, a probability of demand data are then calculated again, and combined both, obtain final demand levels Numerical value.

In one embodiment, for different Verification Projects, such as laser radar is calibrated or automatic Pilot is longitudinally controlled Algorithm, the demand levels of checking individually calculate, such as

r₁=f₁(x1,x2,x3,…,xN)

r₂=f₂(x1,x2,x3,…,xN)

For example, in the method merged using laser radar and vision sensor, x1, x2 can be points of two sensors Other confidence level,

r₁=f₁(x1, x2)=ax1+bx2

The probability of demand of a pick up calibration can be gone out by the confidence calculations of the two.

For another example an automatic Pilot algorithm for being used for City Regions (UrbanArea) driving vehicle needs to update.Then may be used Upgrade requirement probability is calculated to different vehicle in a manner of more than.It can wherein be used to calculate upgrade requirement probability Position and history run track including Current vehicle, so as to be calculated in the higher vehicle of the City Regions operation frequency, The namely higher vehicle of those probability of demand values.For example,

x1,x2

Be respectively Current vehicle position and the past period by the frequency of close quarters, then according to above-mentioned multinomial Formula or the method for machine learning, a, the upgrade requirement of b two cars is calculated.

Ra=f (x1_a,x2_a),

Rb=f (x1_b,x2_b)

For another example upgrade requirement can be calculated according to the upgrading expense of software upgrading.Such as a software upgrading needs Go to a special calibration and test center is calibrated and tested, therefore software upgrading needs vehicle to travel extra mileage The calibration and test after upgrading could be completed.Therefore, by the course of travelling, and the data needed for upgrading and flow Isoquant conduct Variable, different upgrade requirement parameter probability valuings can also be calculated.

In one embodiment, upgrading needs to be calculated according to CAR SERVICE operation maintenance situation.Such as one In the individual shared fleet by pilotless automobile, the demand of business and scheduling are all to be completed by server according to real-time data 's.One task of server is that distribution vehicle resources go meet the needs of client.However, software upgrading may cause car Temporary transient business stops.Therefore, the probability of demand value of upgrading can calculate according to the negative effect to business.For example, x1, X2, x3 are respectively the current transport power of the vehicle, this area's storage transport power, the region transport power demand, then distribute a unmanned vapour The transport power loss that car is brought can pass through a cost formula

L=g (x1, x2, x3)

To calculate, wherein g () is the cost formula of a calculating transport power loss.Its specific implementation can pass through machine The model of study or predetermined fitting is realized.Now, then upgrade requirement function can be obtained using in the following manner

Or

R=-log (ag+b)

As known from the above, vehicle software upgrading pair can be controlled by the design of the circular to upgrade requirement Pressure caused by business O＆M, so that whole fleet is unlikely to because software upgrading brings excessive business to decline.

In addition, the type of vehicle, level of hardware, running region, current path planning, history driving path, if In the presence of auxiliary driver, current charge level, the current sensor degree of accuracy, current geographic position, the environment residing for Current vehicle, It can be input to as variable in described method, and then calculate the probability of demand of a software upgrading.It is specific to calculate The derivation and optimization of method, it constantly can carry out feedback with data according to demand and be improved and adjust.

Another embodiment is to combine both the above method.Calculated by a method based on criterion Discrete upgrade requirement grade, a probability of demand data are then calculated again, and combined both, obtain final demand Level value.

After upgrade requirement grade obtains calculating, the value of server can grade as desired is ranked up.One The direct method of kind is directly by sequence from high to low.Server can be according to a ratio, or according to a certain setting Threshold value, select the preferential vehicle list for carrying out software upgrading.

Step 203, one or more experiments are selected from one or more of vehicles according to the adjustment demand levels Vehicle；

In one embodiment, server selects one according to the adjustment demand levels from one or more vehicles Or the test vehicle that multiple demand levels are high.

In another embodiment, server is according to the adjustment demand levels, from one or more of vehicles The vehicle set for meeting a minimum diversity requirement is chosen, using the vehicle in the vehicle set as the test vehicle. The minimum diversity is, for example, that every kind of adjustment project at least car is corresponding.

In one embodiment, server selects a part of vehicle to carry out software upgrading according to the position between vehicle.Choosing Select criterion and be not less than a predetermined threshold for the distance between vehicle.This is because, new software systems may bring operation not Stable factor, if more proximate vehicles are upgraded simultaneously, the unstability of new software system may cause security Decline.According to the selection mode, the vehicle of software upgrading is carried out in certain area, can only run into no software upgrading Vehicle.Even if software upgrading brings certain unstability, but other vehicles can still rely on old software systems and enter Professional etiquette is kept away, and this probability for allowing for colliding between vehicle reduces.

In one embodiment, server selects to carry out the vehicle of software upgrading according to the surrounding vehicles situation of vehicle.This It is due to that relative to fixed buildings, identification to mobile object and the requirement evaded to unmanned algorithm are higher.Therefore, Server can select around to carry out software liter without other operation vehicles, or the vehicle that surrounding only has a small number of operation vehicles Level.So, the vehicle for carrying out software upgrading just has more clean running environment.And then cause due to software upgrading band The risk come reduces.

In one embodiment, server selects a specific period to select a part of car according to the situation of fleet Upgraded.For example, selection carries out stoppage in transit state in period at night, most of someone and automatic driving vehicle, it is possible to Selection remains in that the vehicle of operation carries out software upgrading.Likewise, can also so reduce software upgrading bring it is unstable Risk caused by property.

In one embodiment, the position between server combination adjustment demand levels and vehicle, surrounding's car of vehicle One or more of situation and the situation of fleet selected section vehicle.

Pay attention to, the selection that vehicle is run in part also includes the other modes do not listed above.By to the various of vehicle The control of state and risk, there are all various ways preferably to go out first vehicle for carrying out software upgrading, herein not one by one Enumerate.

Step 204, the test vehicle is sent and treats adjustment project, the test vehicle is treated adjustment project to corresponding Carry out autonomous adjustment；

In one embodiment, server sends to selected test vehicle from step 203 and treats adjustment project, tests Vehicle independently treats adjustment project and carries out adjustment.

In one embodiment, the content of autonomous adjustment includes：(a) time of autonomous adjustment is determined.In some embodiments In, during normal vehicle operation, determine the adjustment time.For example, when in normally travel, if it is some to identify that roadside is present Available for the special identifier of some part adjustment, including apart from mark post, standard picture etc., then it can start the tune of associated components immediately School.In certain embodiments, adjustment is carried out with car plan according to passenger during the in-use automotive leisure.(b) autonomous adjustment is determined Position and autonomous adjustment project, and autonomous adjustment is carried out, and from master record adjustment result, as a result generally complete or not complete Into.

In certain embodiments, range sensor, such as laser radar, range finding camera etc. need adjustment, then vehicle exists During traveling, sensor collection surrounding road condition, if finding, there are 50m/100m mark posts in front, can carry out the inspection of range sensor Survey.Started counting up when vehicle enters one end of mark post, the other end to mark post terminates to count.If the value that is measured passes through Within the threshold value that the value and the difference of actual range drawn after survey calculation is previously set, then range sensor is accurate.If both Difference exceeds threshold value, then carries out adjustment.Parameter for being capable of autonomous adjustment, internal system carry out adjustment.Complete adjustment and/or After verification operation, next ginseng for needing adjustment is continually looked for according to road conditions, environment or other information during traveling Number.Among automatic driving vehicle, because the gathered data of sensor is to control the data source of vehicle behavior, the accuracy of data The security during car amount traveling is directly affected, therefore uninterrupted adjustment item can be classified as.

In certain embodiments, if treat adjustment is traffic lights identification sensor, vehicle runs into during traveling Traffic lights with V2I functions, system just need to carry out new adjustment by automatic detection vehicle, then corresponding sensor Red light data are acquired in good time and carry out traffic lights judgement.The result of judgement is compared with V2I true value.Pass through ratio Relatively result carries out adjustment.

In certain embodiments, if treat adjustment is acceleration and brake function, brake and acceleration function relative risk, because This preferably carries out adjustment in the time without passenger, and adjustment behavior is dispatched and managed by high in the clouds, in verification place, can use advance The position of setting and distance marker, acceleration and brake operation accordingly are carried out to vehicle, so as to examine respective performances, to judge to be It is no to need adjustment.

In certain embodiments, if treat adjustment is vision sensor, the object 3D rendering data of standard shape are gathered, The 3D object parameters of data after collection or the data after calculating is handled and the standard stored is compared, if comparing Parameter value in threshold range, then without adjustment, if parameter area value is more than threshold value, system automatically to parameter adjustment, if System can not carry out adjustment to the parameter more than threshold value, carry out adjustment again after the adjustment of available requests remote assistance or keep to the side to stop The artificial intervention adjustment such as car.

In one embodiment, adjustment can also be carried out using other vehicles, high in the clouds can dispatch some vehicles and be adjusted School, such as adjustment relative velocity, relative acceleration, relative distance, meeting, doubling etc..

Treat that adjustment vehicle knows that nearby vehicle has completed adjustment in one embodiment, it is modulated to treat that adjustment vehicle can utilize School distance measuring sensor, such as laser radar, binocular camera etc., in real time the distance between measurement and modulated school bus, and calculate Go out the speed and acceleration of relatively modulated school bus, it is then the speed+wait to adjust of modulated school bus to treat the actual speed of adjustment vehicle The relative velocity of school bus, and it is then the acceleration+treat adjustment vehicle of modulated school bus to treat the actual acceleration of adjustment vehicle Relative acceleration.With the speed and the velocity sensor and acceleration transducer of acceleration adjustment vehicle actually obtained.

In one embodiment, modulated school bus is measured respectively and treats relative acceleration, the phase of adjustment vehicle therebetween Adjust the distance, meeting avoids steering angle, doubling relative distance etc., it is modulated to treat that adjustment vehicle obtains by V2V or by server The result of school bus measurement, the sensor for adjustment itself.

Pay attention to, part adjustment project is not listed.The adjustment project of vehicle is numerous, is related to the various sensors, soft of vehicle The adjustment of part, hardware, interface, is not enumerated herein.

Step 205, determined according to the result of the autonomous adjustment of the test vehicle and the adjustment demand levels one Or the scheduling planning of multiple vehicles；

For the result of the autonomous adjustment, in one embodiment, pilotless automobile installs new software systems, and Implement calibration and test.Because the hardware system of pilotless automobile may not changed, so needing to be calibrated and tested The operation stability of new software systems can be confirmed.Except the measurement of the sensors towards ambient of front end, such as laser radar Point cloud chart, the IMAQ of imaging sensor, the echo-signal lamp of millimetre-wave radar, and later stage vehicle traveling strategy hold OK, it is such as unexpected by throttle, brake, suspension, the control of steering, at middle all unmanned related signals Reason, detection of obstacles, path planning, strategy execution are completed by software systems.Therefore, the software systems to upgrading are only passed through Tested and calibrated the operational reliability that just can ensure that new software systems.The content of test and calibration can be according to upgrading Related software is configured, and the software that correlation may be had by being related to each part in the control flow of pilotless automobile is risen Level.For the upgrading of each part, the mode of test and calibration is also different.In software upgrade process, what vehicle was downloaded The improved program to function, algorithm part are not only contained in software kit, also contains what the partial function was calibrated The information such as program, algorithm, reference data.So, a software upgrading also just contains two parts of function adjustment and test Required data.

In one embodiment, the various sensors processing software of vehicle is upgraded.Such as the point cloud of laser radar Diagram data processing, the processing method of imaging sensor, echo signal processing method of millimetre-wave radar etc..Now, a kind of method It is such as the barrier map being calculated according to laser radar point cloud atlas and new edition software by the data processed result of old edition Result is contrasted.Because external environment is unique constant, therefore both results should be maintained at less error Within the scope of.Pass through standard when the result that both compare meets test, such as when error amount is less than some threshold value, then it is assumed that test Pass through.

In one embodiment, the upgrading of environment sensing software may bring the unmanned performance of enhancing.For example, have one Kind can only cognitive disorders thing software upgrading to can be with the new software of cognitive disorders species (people, car, building etc.).Although New software can provide more rich perception, but its most basic barrier cannot be below legacy version in the presence of perception Performance.At this point it is possible to which the obstacle species perceived in new software are merged, and contrasted with the detection of obstacles of legacy version, And then test the basic performance of new version software.Now, the data of contrast are no longer undressed sensing datas, but are passed through Cross the intermediate data of algorithms of different generation, such as Obstacle Position and quantity in barrier map.Similar, still it can incite somebody to action Two kinds of results are contrasted and then observe error between the two to judge the reliability of new software.In addition, it is unmanned Automobile can be tested or calibrated to software by way of network, for example, pilotless automobile is by original image and obstacle Quality testing geodetic graph sends back server by wireless network, and server is detected by artificial or machine method to result, When testing result reaches predefined performance, then the result that test passes through is returned.For example, vehicle is by a two field picture and obstacle species The classification of class sends back server, is confirmed by the degree of accuracy manually to classification.Only vehicle can accurately identify enough Obstacle species after, test can just be considered as passing through.If there is the situation of a large amount of wrong identifications, then it is considered as new soft Part system is unreliable., can be in extreme weather, such as another example vehicle has upgraded a kind of new lane detection software systems Lane detection is completed under the scenes such as sleet night.And now the software of legacy version can not realize that lane line is examined in this case Survey.Now, vehicle can drive to specific testing location, when entering related meteorological scene, carry out traveling test on the spot. If software can clearly identify lane line and complete autonomous traveling, then it represents that new software has passed through test.

In one embodiment, the related software of path planning can also need to calibrate and test that stable fortune could be entered Row state.For example, a kind of new emergency processing software is installed to path planning module.However, in normal operation, tightly Anxious situation may not occur often, such as in highway situations such as emergent wild animal.Therefore, even if whole car Team has all carried out software upgrading, and the running situation of fleet may can not detect change within some time.Therefore, one is selected The test that separating vehicles carry out path planning is also necessary.For another example the path planning based on choosing lane may be due to high-precision Spend the change of map and change.The upgrading of high-precision map especially frequently may only upgrade a certain part in map each time Region.Therefore, a part of vehicle is selected to carry out special test and calibrate just to be enough to judge new map liter to the part map Whether level is credible.

In one embodiment, after vehicle completes calibration and test, it will test and the result of calibration feed back to server. The result of test and calibration can be by the result of the success and failure of pilotless automobile judgement, that is, a two states Instruction.Wherein, if test and calibration failure, the reason for being indicated unsuccessfully in report.For example, pick up calibration fails, Path planning has differences with reference value, obstacle recognition mistake, the reason such as weather identification mistake.

In another embodiment, the related data of Testing And Regulating is only fed back to server by vehicle.By server By being counted to all test results, so as to the result for judging to test and calibrating.For example, allow in barrier category identification In the presence of certain error, so the result of test is to count the error of all vehicles, and judge to test whether to pass through. In certain situation, there is larger difference in the result of test and calibration in Some vehicles, server by the contrast to big data, It may determine that the reliability of new software system and find individual problem vehicle.

One or more of vehicles are determined according to demand levels determined by the result and step 202 of above-mentioned autonomous adjustment Scheduling planning.

In one embodiment, server judges whether to the soft of next group vehicle according to the result of test and calibration Part upgrades.After the judgement of stability of new software system is obtained, server further can select one in the vehicle not upgraded Criticize vehicle and carry out software upgrading.Now, due to being provided with certain data, more cars can be selected in new batch of selection Or relax a part of restrictive condition.Server is gradually completing the software upgrading of all vehicles by above-mentioned alternative manner.

In one embodiment, server possesses two or more similar softwares and is used for identical purpose.Server exists The first step selects two or more groups vehicle, and controls two groups of vehicles to upgrade different software.Then, server collect two groups or Test and calibration result after the upgrading of more vehicles.Server, can by contrasting test and the calibration result of multigroup vehicle Draw the performance difference of multiple similar softwares.According to the performance difference, one of be used as of server selection most preferably upgrades Software, and upgrade the software in the vehicle selection of a new round.By the process of iteration, final all vehicles have all upgraded preferably Software scenario.

In one embodiment, after the demand levels numerical value of vehicle is obtained, server can be carried out using dispatching algorithm Vehicle checking is scheduled.

The scheduling of vehicle validation task needs to consider the task to pilotless automobile and the feelings of the demand of external resource Condition.In some validation tasks, vehicle can perform whenever and wherever possible, and the validation task of vehicle does not need any outside money Source, for example, it is necessary to enter to GPS, IMU, LIDAR, ImageSensor when being chronically at the unmanned vehicle restarting of closed mode Row signal reception condition is verified, to ensure that unmanned algorithm can obtain corresponding data.Such as vehicle is to tire pressure again, Battery electric quantity, the operation monitoring of cabin temperature, for example whether within the scope of one suitable, waits validation task.Now, service The dispatching algorithm of device only needs to calculate whether the vehicle needs to perform one-time authentication task.If result of calculation is to need to hold Row one-time authentication task, then server guiding vehicle, which is immediately performed, verifies and is repeated cyclically the validation task.

In more tasks, checking needs to use specific external resource.For example, the pick up calibration of vehicle need by Vehicle, which drives to fixed calibration center, could implement primary calibration, such as LIDAR accuracy calibration, the figure of imaging sensor Image sharpness calibration etc..The calibration of LIDAR system sometimes needs the method for artificial calibration and experiment, therefore result in this Demand of the kind to special calibration center.Now, due to there may be the vehicle for largely needing to calibrate, if server guides simultaneously Vehicle is calibrated into calibration center, then situation of a large amount of vehicle congestions in same calibration center occurs.If checking needs Wireless network is used, a large amount of vehicles calibrate the congestion that will also result in communication network simultaneously.In addition, if vehicle is shared operation Vehicle, a large amount of vehicles of concentration, which carry out calibration, can cause the transient fluctuation of transport power.Therefore, checking be scheduling to will be different Vehicle, which was assigned in the different periods, completes calibration.A kind of dispatching method is to calculate a capacity at current alignment center (capacity) calibration tasks that, i.e., can be carried in certain time, and the value of grade is ranked up according to demand, preferential peace The high vehicle of row's demand levels is calibrated.Because the calculating of demand levels also includes the run time of vehicle, thus not by It is immediately performed the meetings of calibration tasks over time, its demand levels numerical value can also increase, and then by scheduling more preferably.

In one embodiment, Fig. 3 shows a kind of vehicle checking scheduling based on server end.Wherein, triangle is One calibration center, can complete the calibration of various kinds of sensors or vehicle.In the range of calibration center covering, there are more nothings People, which drives a car, the demand of calibration verification.Server is according to above-mentioned method, by different Transporting Arrangement to different time Calibrated.

In the case where demand levels are discrete, it is understood that there may be a large amount of vehicles possess identical demand levels.Now can be with These vehicles are arranged to be verified using some classical dispatching algorithms, such as roundrobinscheduling.

Different scheduler tasks can produce different dispatching methods.For example, in some validation tasks, although vehicle needs Place is specifically calibrated, but these places are mounted in the near roads that vehicle can exercise, such as in a four crossway The both sides of mouth or highway.The validation task of vehicle can be completed to calibrate by way of inflight.Such as pass through one The individual traffic light intersection for being equipped with sensing facilities, vehicle only need to record the traffic light signal that locally identifies and with it is real red green Lamp state (such as being obtained by V2I), which carries out contrast, can complete the checking of traffic lights identifying system.Obviously, this InFlight Validation task from it is above-mentioned specific calibration center realize LIDAR calibrations it is different.Therefore, the scheduling of checking combines specific every Individual validation task dispatches the frequency to the complexity arrangement required for vehicle.For InFlight validation task, scheduling can be pacified The higher checking frequency of row, and validation task is attached in path planning.During the traveling of unmanned vehicle, it is only necessary to protect Barrier passes through specific place in fixed time period.For example, 50 InFlight calibration points in a region, clothes The calibration tasks of business device arrangement are weekly at least through 1 calibration point.And validation task complexity is higher, then need to pacify Arrange the specific time, and specific calibration center, verified with the relatively low frequency.Assuming that { T_a,b,P_a,bBe a vehicles b Validation task, T are the scheduled proving times, and P is scheduled checking place.Scheduling process is exactly in given r₁,r₂,...., r_nIn the case of, the active volume C of calibration is limited, calculates each group of { T_a,b,P_a,b}.For example, a specific mode is, calibration Active volume C be can be used in a unit interval calibration vehicle number.Then by r₁,₂,....,r_nAccording to descending row Sequence, the C maximum vehicles of current r values are arranged to be verified within each unit interval.Pay attention to, adjusted in the case of resource-constrained Be present many ripe dispatching algorithms in task of the degree with priority, do not enumerate herein, but those skilled in the art can appoint Meaning applies other dispatching methods.

In one embodiment, validation task is completed in a region.In region comprising multiple authentication centers with And multiple vehicles to be verified.Therefore, the problem of dispatching method includes how efficiently to utilize multiple authentication centers.It is if a large amount of Vehicle is arranged to identical authentication center, even if having carried out good schedule for the center, such as avoids the occurrence of a large amount of Vehicle simultaneously etc. situation to be verified.Because the capacity at the center is limited, also more vehicles are caused to be in queueing condition.Meanwhile Other authentication centers are most likely in idle condition.In one embodiment, dispatching method includes entering whole operational area Row sub-zone dividing, a kind of division methods comprise at least an authentication center to ensure that every sub-regions are interior.Hereafter, server Scheduling is directed to per sub-regions, individually carries out a scheduling planning.The vehicle wherein planned is the coverage and neighbouring The validation task of vehicle in region.Now, validation task is assigned in more sub-regions and the complete independently region Scheduling.Another of this method is as a result, the vehicle for being arranged checking within the same time, different subregions has difference Checking demand levels.This is different from the method for not dividing subregion, because in not dividing the dispatching method of subregion, only tests Card higher being just preferentially scheduled of demand levels is verified.Fig. 4 gives a kind of polycentric checking dispatching method. Plurality of calibration center can be used for validation task, and more pilotless automobiles are arranged into by server by dispatching algorithm Different calibration centers completes validation task.

Step 206, the scheduling planning is sent to one or more of vehicles, so that one or more of vehicles are pressed Autonomous adjustment is carried out according to the scheduling planning.

The adjustment task dispatched is sent to other vehicles by server by network, so that vehicle is advised according to the scheduling Draw and complete autonomous adjustment.

Herein it should be noted that automatic driving vehicle to calibrating, testing, the formulation of the validation task such as fault restoration be Bright.That is, automatic driving vehicle not it will be clear that calibration, test, the Scheduling criteria of fault restoration task and method, its It is to perform validation task in the way of structural standardization.For example, automatic driving vehicle only need according to task specify when Between, in specified or anywhere, complete the validation task of correlation.The execution of its specific tasks can be according to current state Judged, such as the calibration of a certain sensor or the survey of a certain new algorithm are carried out during its non-traffic peak value that can arrange by oneself Examination.Meanwhile server also only needs to know task performance according to the report of the result of tasks carrying.For example, when sensing After the completion of device calibration tasks, pilotless automobile feedback Mission Accomplishment Report, server updates corresponding number in local storage According to this and algorithm, such as the counting of a new round is opened, when server is based on detection feedback report and local count judges to need Once during new calibration, it can plan primary calibration task again and be sent to automatic driving vehicle.

By approach described above, the judgement of the checking such as the calibration of pilotless automobile pair, test, fault restoration and row To become extremely simple and transparent, as long as it follows Detection task and the task configuration of calibration, test, fault restoration performs accordingly Task.And server then can constantly be changed by data constantly accumulating, being fed back from a large amount of pilotless automobiles Enter dispatching method.Meanwhile server can constantly be optimized by accessing planning and configuration of the external data to task.And The use of external data is then extremely difficult for pilotless automobile.And then in the feelings for not increasing any vehicle burden Under condition, the verification efficiency of whole fleet is continued to optimize.

Detected by the checking of vehicle, server can collect the current and passing status data of vehicle, according to these Data, server can formulate the validation task scheduling of vehicle, finally guide vehicle to complete validation task.

Step 207, the implementing result of the scheduling planning is gathered；Each vehicle is calculated according to the implementing result again The adjustment demand levels；The scheduling planning is updated according to the adjustment demand levels after calculating again.

With reference to figure 5, the dispatching device schematic diagram of the autonomous adjustment provided for the application one embodiment.As shown in figure 5, should Device includes：

First receiving unit 501, for receiving the Condition Monitoring Data of one or more vehicles；

Determining unit 502, for treating adjustment project and tune according to each vehicle of Condition Monitoring Data determination School demand levels；

Module of selection 503, for according to the adjustment demand levels selected from one or more of vehicles one or Multiple test vehicles；

Transmitting element 504, adjustment project is treated for being sent to the test vehicle, the test vehicle is treated to corresponding Adjustment project carries out autonomous adjustment；

Scheduling planning unit 505, for the result according to the autonomous adjustment of the test vehicle and the adjustment demand levels Determine the scheduling planning of one or more of vehicles；

Scheduling unit 506, for sending the scheduling planning to one or more of vehicles, so that one or more Individual vehicle carries out autonomous adjustment according to the scheduling planning.

Further, the Condition Monitoring Data includes：Software information, hardware information, system operation information, sensor letter One or more in breath, car outer shroud environment information and environment inside car information.

Further, as shown in fig. 6, the module of selection 503 includes：Minimum diversity chooses module 601, for basis The adjustment demand levels, the vehicle set for meeting a minimum diversity requirement is chosen from one or more of vehicles, Using the vehicle in the vehicle set as the test vehicle.

Further, as shown in fig. 6, the scheduling planning unit 505 also includes：Adjustment interpretation of result unit 602, is used for Adjustment result to the test vehicle carries out statistical analysis；Scheduling unit 603, described in being determined according to statistic analysis result The scheduling planning of one or more vehicles.

Further, as shown in fig. 6, the determining unit 502 includes：Adjustment project chooses module 604, for according to complete The priority of the project for needing adjustment of portion's vehicle treats adjustment project described in choosing.

Further, as shown in fig. 6, the scheduling planning unit 505 includes：Region affiliation module 605, for according to every The position of the individual vehicle determines its affiliated coverage；Regional planning module 606, for according in each coverage The sequences of the adjustment demand levels of all vehicles determines the scheduling planning；Wherein, the scheduling planning includes：Each The vehicle carries out time, place and the project of adjustment.

Further, as shown in fig. 6, the determining unit 502 includes：Discrete demand computing module 607, for for every The discrete demand grade of adjustment project is treated described in the individual vehicle calculating；Probability of demand computing module 608, for utilizing one group of institute State the probability of demand data that adjustment project is treated described in vehicle calculating；Level determination module 609, for according to described discrete demand etc. Level and the probability of demand data determine the adjustment demand levels of each vehicle.

Further, described device also includes：Results acquisition unit 507, for gathering the execution knot of the scheduling planning Fruit；Demand levels computing unit 508, the adjustment demand for calculating each vehicle again according to the implementing result etc. again Level；Scheduling planning updating block 509, for updating the scheduling planning according to the adjustment demand levels after calculating again.

Further, as shown in fig. 6, the scheduling planning unit 505 also includes：Area division unit 610, for basis The capacity dynamic at each adjustment center divides the coverage.

Refer to the attached drawing 7, the electronic equipment schematic diagram provided for the application one embodiment.As shown in fig. 7, the electronic equipment 700 include：

Memory 730 and one or more processors 710；

Wherein, the memory 730 communicates to connect with one or more of processors 710, is deposited in the memory 730 The instruction 732 that can be performed by one or more of processors 710 is contained, the instruction 732 is by one or more of processing Device 710 performs, so that one or more of processors 710 perform：

Receive the Condition Monitoring Data of one or more vehicles；

Adjustment project and adjustment demand levels are treated according to each vehicle of Condition Monitoring Data determination；

One or more test vehicles are selected from one or more of vehicles according to the adjustment demand levels；

Sent to the test vehicle and treat adjustment project, the test vehicle is treated that adjustment project is carried out independently to corresponding Adjustment；

One or more of cars are determined according to the result of the autonomous adjustment of the test vehicle and the adjustment demand levels Scheduling planning；

The scheduling planning is sent to one or more of vehicles, so that one or more of vehicles are according to the tune Metric, which is drawn, carries out autonomous adjustment.

One embodiment of the application provides a kind of computer-readable recording medium, in the computer-readable recording medium Computer executable instructions are stored with, the computer executable instructions perform following steps after being performed：

Receive the Condition Monitoring Data of one or more vehicles；

Adjustment project and adjustment demand levels are treated according to each vehicle of Condition Monitoring Data determination；

One or more test vehicles are selected from one or more of vehicles according to the adjustment demand levels；

Sent to the test vehicle and treat adjustment project, the test vehicle is treated that adjustment project is carried out independently to corresponding Adjustment；

One or more of cars are determined according to the result of the autonomous adjustment of the test vehicle and the adjustment demand levels Scheduling planning；

The scheduling planning is sent to one or more of vehicles, so that one or more of vehicles are according to the tune Metric, which is drawn, carries out autonomous adjustment.

It is apparent to those skilled in the art that for convenience and simplicity of description, the equipment of foregoing description With the specific work process of module, the corresponding description in aforementioned means embodiment is may be referred to, will not be repeated here.

Although subject matter described herein is held in the execution on the computer systems of binding operation system and application program There is provided in capable general context, but it will be appreciated by the appropriately skilled person that may also be combined with other kinds of program module To perform other realizations.In general, program module include perform particular task or realize particular abstract data type routine, Program, component, data structure and other kinds of structure.It will be understood by those skilled in the art that subject matter described herein can To be put into practice using other computer system configurations, including portable equipment, multicomputer system, based on microprocessor or can compile Journey consumption electronic product, minicom, mainframe computer etc., it is possible to use task by communication network by being connected wherein In the DCE that remote processing devices perform.In a distributed computing environment, program module can be located locally and far Journey memory storage device both in.

Those of ordinary skill in the art are it is to be appreciated that the list of each example described with reference to the embodiments described herein Member and method and step, it can be realized with the combination of electronic hardware or computer software and electronic hardware.These functions are actually Performed with hardware or software mode, application-specific and design constraint depending on technical scheme.Professional and technical personnel Described function can be realized using distinct methods to each specific application, but this realization is it is not considered that exceed Scope of the present application.

If the function is realized in the form of SFU software functional unit and is used as independent production marketing or in use, can be with It is stored in a computer read/write memory medium.Based on such understanding, the technical scheme of the application is substantially in other words The part to be contributed to original technology or the part of the technical scheme can be embodied in the form of software product, the meter Calculation machine software product is stored in a storage medium, including some instructions are causing a computer equipment (can be People's computer, server, or network equipment etc.) perform each embodiment methods described of the application all or part of step. For example typically, the technical scheme of the application can be by least one general purpose computer node 810 as shown in Figure 8 come real Existing and/or propagation.In fig. 8, general purpose computer node 810 includes：Computer system/server 812, peripheral hardware 814 and aobvious Show equipment 818；Wherein, the computer system/server 812 includes processing unit 820, input/output interface 822, network Data transfer is generally realized in adapter 824 and memory 830, inside by bus；Further, memory 830 is generally by more Kind storage device composition, such as, RAM (RandomAccessMemory, random access memory) 832, caching 834 and storage system (being typically made up of one or more Large Copacity non-volatile memory mediums) 838 etc.；Realize technical scheme part or The program 840 of repertoire is stored in memory 830, is existed generally in the form of multiple program modules 842.

And foregoing computer read/write memory medium is included with storage such as computer-readable instruction, data structure, program Any mode or technology of the information such as module or other data are come the physics volatibility realized and non-volatile, removable and can not Because of eastern medium.Computer read/write memory medium specifically includes, but is not limited to, USB flash disk, mobile hard disk, read-only storage (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), erasable programmable is read-only deposits Reservoir (EPROM), EEPROM (EEPROM), flash memory or other solid-state memory technologies, CD-ROM, number Word versatile disc (DVD), HD-DVD, blue light (Blue-Ray) or other light storage devices, tape, disk storage or other magnetic Storage device can be used for any other medium that stores information needed and can be accessed by computer.Embodiment of above is only For illustrating the present invention, and not limitation of the present invention, the those of ordinary skill about technical field, do not departing from the present invention Spirit and scope in the case of, can also make a variety of changes and modification, therefore all equivalent technical schemes fall within this The category of invention, scope of patent protection of the invention should be defined by the claims.

Claims (10)

1. a kind of dispatching method of autonomous adjustment, it is characterised in that methods described includes：

Receive the Condition Monitoring Data of one or more vehicles；

Adjustment project and adjustment demand levels are treated according to each vehicle of Condition Monitoring Data determination；

One or more test vehicles are selected from one or more of vehicles according to the adjustment demand levels；

Sent to the test vehicle and treat adjustment project, the test vehicle is treated that adjustment project is carried out from homophony to corresponding School；

One or more of vehicles are determined according to the result of the autonomous adjustment of the test vehicle and the adjustment demand levels Scheduling planning；

The scheduling planning is sent to one or more of vehicles, so that one or more of vehicles are advised according to the scheduling Draw and carry out autonomous adjustment.

2. according to the method for claim 1, it is characterised in that described to select one or more test vehicles and include：

According to the adjustment demand levels, the car for meeting a minimum diversity requirement is chosen from one or more of vehicles Set, using the vehicle in the vehicle set as the test vehicle.

3. according to the method for claim 1, it is characterised in that the scheduling planning for determining one or more of vehicles Including：

Its affiliated coverage is determined according to the position of each vehicle；

The scheduling planning is determined according to the sequence of the adjustment demand levels of all vehicles in each coverage； Wherein, the scheduling planning includes：Each vehicle carries out time, place and the project of adjustment.

4. according to the method for claim 1, it is characterised in that the adjustment demand levels bag for calculating each vehicle Include：

Discrete demand grade for treating adjustment project described in each vehicle calculating；

Utilize the probability of demand data that adjustment project is treated described in vehicle calculating described in one group；

The adjustment demand levels of each vehicle are determined according to the discrete demand grade and the probability of demand data.

5. the method according to claim 1 or 4, it is characterised in that methods described also includes：

Gather the implementing result of the scheduling planning；

Calculate the adjustment demand levels of each vehicle again according to the implementing result；

The scheduling planning is updated according to the adjustment demand levels after calculating again.

A kind of 6. dispatching device of autonomous adjustment, it is characterised in that including：

Receiving unit, for receiving the Condition Monitoring Data of one or more vehicles；

Determining unit, for treating adjustment project and adjustment demand etc. according to each vehicle of Condition Monitoring Data determination Level；

Module of selection, for selecting one or more experiments from one or more of vehicles according to the adjustment demand levels Vehicle；

Transmitting element, adjustment project is treated for being sent to the test vehicle, the test vehicle is treated adjustment item to corresponding Mesh carries out autonomous adjustment；

Scheduling planning unit, for described in the result according to the autonomous adjustment of the test vehicle and adjustment demand levels determination The scheduling planning of one or more vehicles；

Scheduling unit, for sending the scheduling planning to one or more of vehicles, so that one or more of vehicles Autonomous adjustment is carried out according to the scheduling planning.

7. device according to claim 10, it is characterised in that described device also includes：

Adjustment interpretation of result unit, for being united to the adjustment result that adjustment project is tested described in the history adjustment data Meter analysis；

Scheduling unit, for determining the scheduling planning of one or more of vehicles according to statistic analysis result.

8. device according to claim 10, it is characterised in that the project determining unit includes：

Adjustment project chooses module, the priority for the project for needing adjustment according to rolling stock choose described in wait to adjust School project.

9. a kind of electronic equipment, it is characterised in that including：

Memory and one or more processors；

Wherein, the memory is connected with one or more of processor communications, and being stored with the memory can be described The instruction that one or more processors perform, the instruction by one or more of computing devices so that it is one or Multiple processors can realize the method as any one of claim 1-5.

10. a kind of computer-readable recording medium, it is characterised in that be stored with computer in the computer-readable recording medium Executable instruction, the computer executable instructions be performed after realizing the side as any one of claim 1-5 Method.