CN107123173A - For the method and apparatus for the transport condition for monitoring unmanned vehicle - Google Patents
For the method and apparatus for the transport condition for monitoring unmanned vehicle Download PDFInfo
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- CN107123173A CN107123173A CN201710274300.2A CN201710274300A CN107123173A CN 107123173 A CN107123173 A CN 107123173A CN 201710274300 A CN201710274300 A CN 201710274300A CN 107123173 A CN107123173 A CN 107123173A
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- G—PHYSICS
- G07—CHECKING-DEVICES
- G07C—TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
- G07C5/00—Registering or indicating the working of vehicles
- G07C5/008—Registering or indicating the working of vehicles communicating information to a remotely located station
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- G—PHYSICS
- G07—CHECKING-DEVICES
- G07C—TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
- G07C5/00—Registering or indicating the working of vehicles
- G07C5/08—Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle or waiting time
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Abstract
This application discloses the method and apparatus of the transport condition for monitoring unmanned vehicle.One embodiment of the above method includes：Obtain the transport condition data of unmanned vehicle in the process of moving；Transport condition data is handled, the first driving parameters are obtained；Obtain the second driving parameters of passenger's input of unmanned vehicle；According to the first driving parameters and the second driving parameters, the transport condition of unmanned vehicle is monitored.The embodiment can realize that the objective rational transport condition to unmanned vehicle is monitored, and be conducive to the optimization of the control algolithm of unmanned vehicle.
Description
Technical field
The application is related to field of computer technology, and in particular to technical field of data processing, more particularly to a kind of for supervising
The method and apparatus for surveying the transport condition of unmanned vehicle.
Background technology
Unmanned vehicle, as a kind of new vehicles, is the revolution and innovation to orthodox car.But its essence and traditional vapour
Car is the same, is all as a kind of vehicles.Its transport condition and each road user are closely bound up, realize the row to unmanned vehicle
Sail the monitoring of state effectively can optimize to unmanned vehicle, to ensure good road traffic order, ensure road occupation
The safety of person.
The content of the invention
The purpose of the application is to propose a kind of method and apparatus for being used to monitor the transport condition of unmanned vehicle.
In a first aspect, the embodiment of the present application provides a kind of method for being used to monitor the transport condition of unmanned vehicle, above-mentioned side
Method includes：Obtain the transport condition data of unmanned vehicle in the process of moving；Transport condition data is handled, the first row is obtained
Sail parameter；Obtain the second driving parameters of passenger's input of unmanned vehicle；According to the first driving parameters and the second driving parameters, monitoring
The transport condition of unmanned vehicle.
In certain embodiments, above-mentioned transport condition data includes：Transverse acceleration, the longitudinal direction along unmanned vehicle travel direction
Acceleration, the vertical acceleration perpendicular to ground upwardly, wherein, it is horizontal, longitudinal and vertical meet right-handed Cartesian coordinate system.
In certain embodiments, it is above-mentioned that transport condition data is handled, including：Respectively to transverse acceleration, longitudinal direction
Acceleration and vertical acceleration carry out derivative operation, obtain horizontal anxious acceleration, the anxious acceleration in longitudinal direction and vertical anxious acceleration
Degree；The variance of laterally anxious acceleration, the anxious acceleration in longitudinal direction and vertical anxious acceleration is determined respectively；According to transverse acceleration, indulge
To acceleration, the variance of horizontal anxious acceleration, the variance and the variance of vertical anxious acceleration of the anxious acceleration in longitudinal direction, first is determined
Driving parameters.
In certain embodiments, it is above-mentioned to determine laterally anxious acceleration, the anxious acceleration in longitudinal direction and vertical anxious acceleration respectively
Variance, including：Each laterally anxious acceleration magnitude, the anxious acceleration in each longitudinal direction obtained during the traveling of unmanned vehicle is determined respectively
Value and each vertical anxious acceleration magnitude；Determine the continuous predetermined number of sequential laterally anxious acceleration magnitude, the anxious acceleration magnitude in longitudinal direction
And the average value of vertical anxious acceleration magnitude；Determination laterally each average value of anxious acceleration, each the putting down of the anxious acceleration in longitudinal direction respectively
The variance of each average value of average and vertical anxious acceleration.
In certain embodiments, it is above-mentioned according to transverse acceleration, laterally longitudinal acceleration, the variance of anxious acceleration, longitudinal direction
The variance of the variance of anxious acceleration and vertical anxious acceleration, determines the first driving parameters, including：According to transverse acceleration and
Longitudinal acceleration, determines the traveling intensity index of unmanned vehicle；According to the laterally variance of anxious acceleration, the variance of the anxious acceleration in longitudinal direction
And the variance of vertical anxious acceleration, determine the traveling nergy Index of unmanned vehicle；According to traveling intensity index and traveling energy
Index, determines the first driving parameters.
In certain embodiments, it is above-mentioned that transport condition data is handled, including：Respectively to transverse acceleration, vertical
Before carrying out derivative operation to acceleration and vertical acceleration, respectively to transverse acceleration, longitudinal acceleration and it is vertical plus
Speed carries out Fourier transformation, obtains horizontal frequency domain acceleration, longitudinal frequency domain acceleration and vertical frequency domain acceleration；Select respectively
Take the acceleration information preset in horizontal frequency domain acceleration, longitudinal frequency domain acceleration and vertical frequency domain acceleration in frequency domain
As valid data, effectively horizontal frequency domain acceleration, effectively longitudinal frequency domain acceleration and effective vertical frequency domain acceleration are obtained；
Inverse Fourier is carried out to effective horizontal frequency domain acceleration, effectively longitudinal frequency domain acceleration and effectively vertical frequency domain acceleration to become
Change, obtain effective transverse acceleration, effective longitudinal acceleration and effective vertical acceleration.
In certain embodiments, it is above-mentioned according to the first driving parameters and the second driving parameters, monitor the traveling shape of unmanned vehicle
State, including：Summation is weighted to the first driving parameters and the second driving parameters, transport condition parameter is obtained；By transport condition
Parameter is compared with preset value；It is less than preset value in response to transport condition parameter, the control algolithm to unmanned vehicle is optimized.
Second aspect, the embodiment of the present application provides a kind of device for being used to monitor the transport condition of unmanned vehicle, above-mentioned dress
Put including：First acquisition unit, for obtaining the transport condition data of unmanned vehicle in the process of moving；Processing unit, for pair
Transport condition data is handled, and obtains the first driving parameters；Second acquisition unit, is inputted for obtaining the passenger of unmanned vehicle
Second driving parameters；Monitoring unit, for according to the first driving parameters and the second driving parameters, monitoring the traveling shape of unmanned vehicle
State.
In certain embodiments, above-mentioned transport condition data includes：Transverse acceleration, the longitudinal direction along unmanned vehicle travel direction
Acceleration, the vertical acceleration perpendicular to ground upwardly, wherein, it is horizontal, longitudinal and vertical meet right-handed Cartesian coordinate system.
In certain embodiments, above-mentioned processing unit includes：Derivative operation module, for respectively to transverse acceleration, vertical
Derivative operation is carried out to acceleration and vertical acceleration, laterally anxious acceleration, the anxious acceleration in longitudinal direction and vertical urgency is obtained and adds
Speed；Variance determination module, the side for determining laterally anxious acceleration, the anxious acceleration in longitudinal direction and vertical anxious acceleration respectively
Difference；First traveling parameter determination module, for according to transverse acceleration, laterally longitudinal acceleration, the variance of anxious acceleration, longitudinal direction
The variance of the variance of anxious acceleration and vertical anxious acceleration, determines the first driving parameters.
In certain embodiments, above-mentioned variance determines that mould is further used for：Determine respectively during the traveling of unmanned vehicle
Obtained each laterally anxious acceleration magnitude, each anxious acceleration magnitude in longitudinal direction and each vertical anxious acceleration magnitude；Determine that sequential is continuously pre-
If the average value of the horizontal anxious acceleration magnitude of quantity, the anxious acceleration magnitude in longitudinal direction and vertical anxious acceleration magnitude；Determine respectively laterally
The variance of each average value of each average value of anxious acceleration, each average value of the anxious acceleration in longitudinal direction and vertical anxious acceleration.
In certain embodiments, above-mentioned first traveling parameter determination module is further used for：According to transverse acceleration and
Longitudinal acceleration, determines the traveling intensity index of unmanned vehicle；According to the laterally variance of anxious acceleration, the variance of the anxious acceleration in longitudinal direction
And the variance of vertical anxious acceleration, determine the traveling nergy Index of unmanned vehicle；According to traveling intensity index and traveling energy
Index, determines the first driving parameters.
In certain embodiments, above-mentioned processing unit also includes：Time-frequency conversion module, in derivative operation module difference
Transverse acceleration, longitudinal acceleration and vertical acceleration are carried out before derivative operation, transverse acceleration, longitudinal direction added respectively
Speed and vertical acceleration carry out Fourier transformation, obtain horizontal frequency domain acceleration, longitudinal frequency domain acceleration and vertical frequency
Domain acceleration；Module is chosen, for choosing horizontal frequency domain acceleration, longitudinal frequency domain acceleration and vertical frequency domain acceleration respectively
In preset acceleration information in frequency domain as valid data, obtain effectively horizontal frequency domain acceleration, effectively longitudinal frequency domain
Acceleration and effectively vertical frequency domain acceleration；Frequency-time domain transformation module, for effective horizontal frequency domain acceleration, effectively longitudinal direction frequency
Domain acceleration and effectively vertical frequency domain acceleration carry out inverse Fourier transform, obtain effective transverse acceleration, effectively longitudinal direction and add
Speed and effective vertical acceleration.
In certain embodiments, above-mentioned monitoring unit includes：Weighting block, for being travelled to the first driving parameters and second
Parameter is weighted summation, obtains transport condition parameter；Comparison module, for transport condition parameter and preset value to be compared
Compared with；Optimization module, for being less than preset value in response to transport condition parameter, the control algolithm to unmanned vehicle is optimized.
The third aspect, the embodiment of the present application provides a kind of server, including：One or more processors；Storage device,
For storing one or more programs, when said one or multiple programs are by said one or multiple computing devices so that on
State one or more processors and realize method described by any of the above-described embodiment.
Fourth aspect, the embodiment of the present application provides a kind of computer-readable recording medium, is stored thereon with computer journey
Sequence, the program realizes the method described by any of the above-described embodiment when being executed by processor.
The method and apparatus for being used to monitor the transport condition of unmanned vehicle that the application is provided, obtain unmanned vehicle in traveling first
During transport condition data, then above-mentioned transport condition data is handled, the first driving parameters of unmanned vehicle are obtained,
Then in conjunction with the second driving parameters of passenger's input of unmanned vehicle, the transport condition of unmanned vehicle is monitored.It is objective so as to realize
The rational transport condition to unmanned vehicle is monitored, and is conducive to the optimization of the control algolithm of unmanned vehicle.
Brief description of the drawings
By reading the detailed description made to non-limiting example made with reference to the following drawings, the application's is other
Feature, objects and advantages will become more apparent upon：
Fig. 1 is that the application can apply to exemplary system architecture figure therein；
Fig. 2 is the flow chart for being used to monitor one embodiment of the method for the transport condition of unmanned vehicle according to the application；
Fig. 3 is the signal for being used to monitor an application scenarios of the method for the transport condition of unmanned vehicle according to the application
Figure；
Fig. 4 be in the method for the transport condition for monitoring unmanned vehicle according to the application to transport condition data at
The flow chart of reason；
Fig. 5 is the structural representation for being used to monitor one embodiment of the device of the transport condition of unmanned vehicle according to the application
Figure；
Fig. 6 is adapted for the structural representation of the computer system of the server for realizing the embodiment of the present application.
Embodiment
The application is described in further detail with reference to the accompanying drawings and examples.It is understood that this place is retouched
The specific embodiment stated is used only for explaining related invention, rather than the restriction to the invention.It also should be noted that, in order to
Be easy to description, illustrate only in accompanying drawing to about the related part of invention.
It should be noted that in the case where not conflicting, the feature in embodiment and embodiment in the application can phase
Mutually combination.Describe the application in detail below with reference to the accompanying drawings and in conjunction with the embodiments.
Fig. 1 is shown can be using the method for the transport condition for monitoring unmanned vehicle of the application or for monitoring nobody
The exemplary system architecture 100 of the embodiment of the device of the transport condition of car.
As shown in figure 1, system architecture 100 can include unmanned vehicle 101, network 102 and server 103.Network 102 is used to
The medium of communication link is provided between unmanned vehicle 101 and server 103.Network 102 can include various connection types, for example
Wired, wireless communication link or fiber optic cables etc..
Multiply passenger seated in unmanned vehicle 101, passenger can utilize unmanned vehicle 101
User can be interacted with using terminal equipment 101,102,103 by network 102 with server 103, to receive or send out
Send data etc..Various electronic installations can be installed, for example inertial navigation unit, unmanned vehicle controller, antilock on unmanned vehicle 101
Dead system, braking force distribution system etc..
Unmanned vehicle 101 can be various unmanned vehicles, including but not limited to motorbus, tractor, city bus, medium-sized
Car, high capacity waggon, kart, small-sized automatic catch automobile, automatic Pilot unmanned vehicle or other Intelligent unattended cars etc..
Server 103 can be to provide the server of various services, for example, the transport condition of unmanned vehicle 101 is monitored
Background server.The data such as the transport condition data during traveling can be sent to background server by unmanned vehicle 101, with
Background server is handled above-mentioned transport condition data, then receive the second row of passenger's input in unmanned vehicle 101
Parameter is sailed, to monitor the transport condition of unmanned vehicle 101.
It should be noted that the method for being used to test unmanned vehicle that the embodiment of the present application is provided is general by server 103
Perform, correspondingly, be generally positioned at for testing the device of unmanned vehicle in server 103.
It should be understood that the number of the unmanned vehicle, network and server in Fig. 1 is only schematical.According to realizing needs,
Can have any number of unmanned vehicle, network and server.
With continued reference to Fig. 2, the reality for being used to monitor the method for the transport condition of unmanned vehicle according to the application is shown
Apply the flow 200 of example.The method for being used to monitor the transport condition of unmanned vehicle of the present embodiment, comprises the following steps：
Step 201, the transport condition data of unmanned vehicle in the process of moving is obtained.
In the present embodiment, for monitor unmanned vehicle transport condition method operation electronic equipment thereon (for example
Server shown in Fig. 1) it can be obtained in the process of moving by wired connection mode or radio connection unmanned vehicle
Transport condition data, above-mentioned transport condition data can be the various data related to the transport condition of unmanned vehicle, for example plus
Speed data, angular velocity data etc..
It is pointed out that above-mentioned radio connection can include but is not limited to 3G/4G connections, WiFi connections, bluetooth
Connection, WiMAX connections, Zigbee connections, UWB (ultra wideband) connections and other currently known or exploitations in the future
Radio connection.
In some optional implementations of the present embodiment, Inertial Measurement Unit (Inertial is installed in unmanned vehicle
Measurement unit, IMU), when it can measure object and moves in three dimensions, along the acceleration of each axle.Above-mentioned row
Sailing status data includes：Transverse acceleration, longitudinal acceleration and vertical acceleration.Wherein, longitudinally refer to travel along unmanned vehicle
Direction, it is vertical to refer to perpendicular to ground upwardly direction, laterally and longitudinally, vertical meet right-handed Cartesian coordinate system.
Step 202, above-mentioned transport condition data is handled, obtains the first driving parameters.
Server is after above-mentioned transport condition data is got, and car carries out various processing to above-mentioned data, to obtain the
One driving parameters.For example, time-domain and frequency-domain conversion can be carried out to above-mentioned status data, above-mentioned transport condition data is obtained in frequency domain
Interior information, then monitors the transport condition of unmanned vehicle using frequency domain information；Can also be to determining unmanned vehicle according to above-mentioned data
Pose, and the transport condition of unmanned vehicle is monitored according to the pose of determination.Accordingly, above-mentioned first driving parameters can be with
It is the frequency domain information of transport condition data or the posture information of unmanned vehicle.
Step 203, the second driving parameters of passenger's input of unmanned vehicle are obtained.
In the present embodiment, comprehensively the transport condition of unmanned vehicle is monitored in order to more objective, server can also be obtained
The second driving parameters for taking the passenger in unmanned vehicle to input.It is understood that passenger can be by user circle in unmanned vehicle
Face inputs above-mentioned second driving parameters, and above-mentioned second driving parameters then are sent into server using unmanned vehicle and network,
Above-mentioned second driving parameters can be inputted by the terminal being connected with server communication.Above-mentioned second driving parameters can be passenger
Marking or unmanned vehicle to the transport condition of unmanned vehicle during the traveling of unmanned vehicle are taken a sudden turn in the process of moving
Or the number of times brought to a halt etc..
Step 204, according to the first driving parameters and the second driving parameters, the transport condition of unmanned vehicle is monitored.
Server can carry out certain place after above-mentioned first driving parameters and the second driving parameters are got to the two
Reason, to monitor the transport condition of unmanned vehicle.Above-mentioned processing can be that the two is weighted, and the present embodiment is not done to this
Limit.
In some optional implementations of the present embodiment, above-mentioned steps 204 can specifically include not shown in Fig. 2
Following steps：
Summation is weighted to the first driving parameters and the second driving parameters, transport condition parameter is obtained；By transport condition
Parameter is compared with preset value；It is less than preset value in response to transport condition parameter, the control algolithm to unmanned vehicle is optimized.
Server can be weighted summation to the two, obtain after the first driving parameters and the second driving parameters are obtained
To transport condition parameter, then above-mentioned transport condition parameter is compared with preset value, is less than in traveling state parameter default
During value, the control algolithm to unmanned vehicle is optimized.
With continued reference to Fig. 3, Fig. 3 is the applied field for being used to monitor the method for the transport condition of unmanned vehicle according to the present embodiment
One schematic diagram of scape.In Fig. 3 application scenarios, passenger seated 302 are multiplied in unmanned vehicle 301, in running over for unmanned vehicle 301
Cheng Zhong, server 303 can obtain the transport condition data of unmanned vehicle, and the first driving parameters are obtained after processing.Meanwhile, server
303 can also obtain the second driving parameters of the input of passenger 302, and server 303 combines the first driving parameters and the second driving parameters,
Monitor the transport condition of unmanned vehicle 301.
The method for being used to monitor the transport condition of unmanned vehicle that above-described embodiment of the application is provided, obtains unmanned vehicle first
Transport condition data in the process of moving, is then handled above-mentioned transport condition data, obtains the first row of unmanned vehicle
Parameter is sailed, then in conjunction with the second driving parameters of passenger's input of unmanned vehicle, the transport condition of unmanned vehicle is monitored.So as to reality
The existing objective rational transport condition to unmanned vehicle is monitored, and is conducive to the optimization of the control algolithm of unmanned vehicle.
With continued reference to Fig. 4, it illustrates right in the method for the transport condition for monitoring unmanned vehicle according to the application
The flow 400 that transport condition data is handled.As shown in figure 4, in the present embodiment, can be realized by following steps to traveling
Status data is handled：
Step 401, derivative operation is carried out to transverse acceleration, longitudinal acceleration and vertical acceleration respectively, obtains horizontal stroke
To anxious acceleration, the anxious acceleration in longitudinal direction and vertical anxious acceleration.
In the present embodiment, server can be obtained from IMU transverse acceleration, longitudinal acceleration and vertical acceleration with
The change curve of time, derivative operation is carried out to this curve, it is possible to is obtained laterally anxious acceleration, the anxious acceleration in longitudinal direction and is hung down
To anxious acceleration versus time curve.
Step 402, the variance of laterally anxious acceleration, the anxious acceleration in longitudinal direction and vertical anxious acceleration is determined respectively.
After horizontal anxious acceleration, the anxious acceleration in longitudinal direction and vertical anxious acceleration versus time curve has been obtained,
Laterally anxious acceleration magnitude, the anxious acceleration magnitude in longitudinal direction and the vertical anxious acceleration magnitude at each moment can be determined, then can root
The laterally variance of anxious acceleration, the variance and the variance of vertical anxious acceleration of the anxious acceleration in longitudinal direction are determined according to below equation：
Wherein, xrmsRepresent variance, laterally anxious acceleration magnitude that N represents to obtain during traveling, the anxious acceleration magnitude in longitudinal direction or
The number of vertical anxious acceleration magnitude, xiRepresent in N number of laterally anxious acceleration magnitude, the anxious acceleration magnitude in longitudinal direction or vertical anxious acceleration magnitude
I-th laterally anxious acceleration magnitude, the anxious acceleration magnitude in longitudinal direction or vertical anxious acceleration magnitude.
In some optional implementations of the present embodiment, above-mentioned steps 402 specifically can also be by not shown in Fig. 4
Following steps realize：
Each laterally anxious acceleration magnitude for determining to obtain during the traveling of unmanned vehicle respectively, the anxious acceleration magnitude in each longitudinal direction with
And each vertical anxious acceleration magnitude；Determine the continuous predetermined number of sequential laterally anxious acceleration magnitude, the anxious acceleration magnitude in longitudinal direction and
The average value of vertical anxious acceleration magnitude；Laterally each average value of anxious acceleration, each average value of the anxious acceleration in longitudinal direction are determined respectively
And the variance of each average value of vertical anxious acceleration.
Server can be first according to the change of laterally anxious acceleration, the anxious acceleration in longitudinal direction and vertical anxious acceleration with the time
Change curve, it is determined that laterally anxious acceleration magnitude, the anxious acceleration magnitude in longitudinal direction and the vertical anxious acceleration magnitude at each moment.It is then determined that
The individual laterally anxious acceleration magnitudes of the continuous m of sequential (m is the positive integer more than 1), the anxious acceleration magnitude in longitudinal direction and vertical anxious acceleration
The average value of value, then obtains multiple average values, finally determine horizontal each average value of anxious acceleration, the anxious acceleration in longitudinal direction it is each
The variance of each average value of average value and vertical anxious acceleration.
Step 403, according to transverse acceleration, longitudinal acceleration, laterally the variance of anxious acceleration, the anxious acceleration in longitudinal direction side
The variance of poor and vertical anxious acceleration, determines the first driving parameters.
Server can determine that the first traveling is joined after the processing of step 402 complete according to obtained multiple parameters
Number.For example, server can obtain above-mentioned parameter weighted sum the first driving parameters.
In some optional implementations of the present embodiment, above-mentioned steps 403 specifically can be by not shown in Fig. 4
Following steps are realized：
According to transverse acceleration and longitudinal acceleration, the traveling intensity index of unmanned vehicle is determined；Accelerated according to laterally anxious
The variance and the variance of vertical anxious acceleration of the variance of degree, the anxious acceleration in longitudinal direction, determine the traveling nergy Index of unmanned vehicle；Root
According to traveling intensity index and traveling nergy Index, the first driving parameters are determined.
In this implementation, server can be weighted summation to transverse acceleration and longitudinal acceleration first, obtain
To the traveling intensity index of unmanned vehicle.Above-mentioned traveling intensity index experiences shadow during the traveling for representing unmanned vehicle to passenger
Obvious quick change behavior is rung, such as brings to a halt, take a sudden turn.Then server is according to the laterally variance of anxious acceleration, longitudinal direction
The variance of the variance of anxious acceleration and vertical anxious acceleration, determines the traveling nergy Index of unmanned vehicle.Above-mentioned traveling energy refers to
On the obvious violent oscillatory motion behavior of passenger's impression influence, such as severe jolt during traveling of the number for representing unmanned vehicle.
Finally, server is weighted summation to above-mentioned traveling intensity index and traveling nergy Index, determines the first driving parameters.
In some optional implementations of the present embodiment, before step 401 is carried out, Fig. 4 can also be carried out first
Not shown in following steps：
Fourier transformation is carried out to transverse acceleration, longitudinal acceleration and vertical acceleration respectively, horizontal frequency domain is obtained
Acceleration, longitudinal frequency domain acceleration and vertical frequency domain acceleration；Horizontal frequency domain acceleration, longitudinal frequency domain acceleration are chosen respectively
And the acceleration information in vertical frequency domain acceleration in default frequency domain is as valid data, obtains effectively horizontal frequency domain and add
Speed, effectively longitudinal frequency domain acceleration and effective vertical frequency domain acceleration；To effective horizontal frequency domain acceleration, effectively longitudinal direction frequency
Domain acceleration and effectively vertical frequency domain acceleration carry out inverse Fourier transform, obtain effective transverse acceleration, effectively longitudinal direction and add
Speed and effective vertical acceleration.
In this implementation, server can be carried out to transverse acceleration, longitudinal acceleration and vertical acceleration first
Fourier transformation, obtains the information of transverse acceleration, longitudinal acceleration and vertical acceleration in frequency domain, that is, obtains horizontal frequency domain
Acceleration, longitudinal frequency domain acceleration and vertical frequency domain acceleration.Then decomposited and human body in above-mentioned frequency domain data
Feel the low-frequency data part of strong correlation, that is, to preset the part in frequency domain, obtain horizontal frequency domain acceleration, longitudinal frequency domain and add
Live part in speed and vertical frequency domain acceleration, i.e., effectively horizontal frequency domain acceleration, effectively longitudinal frequency domain acceleration with
And effective vertical frequency domain acceleration.Then inverse Fourier transform is carried out to obtained effective frequency domain information, returns again to domain portion,
Effective transverse acceleration, effective longitudinal acceleration and effective vertical acceleration are obtained, the place in step 401 is then carried out again
Reason.
It is understood that carrying out derivation fortune to transverse acceleration, longitudinal acceleration and vertical acceleration in step 401
Calculate, be that derivative operation is carried out to effective transverse acceleration, effective longitudinal acceleration and effective vertical acceleration.
The method for being used to monitor the transport condition of unmanned vehicle that above-described embodiment of the application is provided, can extract and respectively add
Live part in speed data carries out the monitoring of unmanned vehicle travelling state；Can simultaneously be effectively run over according to unmanned vehicle
Quick change behavior and violent oscillatory motion behavior in journey, are monitored to transport condition, improve the accuracy of monitoring.
With further reference to Fig. 5, as the realization to method shown in above-mentioned each figure, it is used to monitor nothing this application provides one kind
One embodiment of the device of the transport condition of people's car, the device embodiment is corresponding with the embodiment of the method shown in Fig. 2, the dress
Put and specifically can apply in various electronic equipments.
As shown in figure 5, the device 500 of the transport condition for monitoring unmanned vehicle of the present embodiment includes：First obtains single
Member 501, processing unit 502, second acquisition unit 503 and monitoring unit 504.
Wherein, first acquisition unit 501, for obtaining the transport condition data of unmanned vehicle in the process of moving.
Processing unit 502, for handling transport condition data, obtains the first driving parameters.
Second acquisition unit 503, for obtaining the second driving parameters that the passenger of unmanned vehicle inputs.
Monitoring unit 504, for according to the first driving parameters and the second driving parameters, monitoring the transport condition of unmanned vehicle.
In some optional implementations of the present embodiment, above-mentioned transport condition data includes：Transverse acceleration, along nothing
Longitudinal acceleration, the vertical acceleration perpendicular to ground upwardly of people's car travel direction, wherein, it is horizontal, longitudinal and vertical full
Sufficient right-handed Cartesian coordinate system.
In some optional implementations of the present embodiment, above-mentioned processing unit 502 may further include in Fig. 5 not
Derivative operation module, variance determination module and the first traveling parameter determination module shown.
Wherein, derivative operation module, for asking respectively transverse acceleration, longitudinal acceleration and vertical acceleration
Computing is led, laterally anxious acceleration, the anxious acceleration in longitudinal direction and vertical anxious acceleration is obtained.
Variance determination module, for determining horizontal anxious acceleration, the anxious acceleration in longitudinal direction and vertical anxious acceleration respectively
Variance.
First traveling parameter determination module, for according to transverse acceleration, longitudinal acceleration, horizontal anxious acceleration side
The variance and the variance of vertical anxious acceleration of the anxious acceleration in poor, longitudinal direction, determine the first driving parameters.
In some optional implementations of the present embodiment, above-mentioned variance determination module can be further used for：Respectively
It is determined that each laterally anxious acceleration magnitude, each anxious acceleration magnitude in longitudinal direction and each vertical urgency that are obtained during the traveling of unmanned vehicle add
Velocity amplitude；Determine the continuous predetermined number of sequential laterally anxious acceleration magnitude, the anxious acceleration magnitude in longitudinal direction and vertical anxious acceleration
The average value of value；Determine that laterally each average value of anxious acceleration, each average value of the anxious acceleration in longitudinal direction and vertical urgency add respectively
The variance of each average value of speed.
In some optional implementations of the present embodiment, above-mentioned first traveling parameter determination module can be used further
In：According to transverse acceleration and longitudinal acceleration, the traveling intensity index of unmanned vehicle is determined；According to the side of laterally anxious acceleration
The variance and the variance of vertical anxious acceleration of the anxious acceleration in poor, longitudinal direction, determine the traveling nergy Index of unmanned vehicle；According to traveling
Intensity index and traveling nergy Index, determine the first driving parameters.
In some optional implementations of the present embodiment, above-mentioned processing unit 502 may further include in Fig. 5 not
Time-frequency conversion module, selection module and the frequency-time domain transformation module shown.
Wherein, time-frequency conversion module, for transverse acceleration, longitudinal acceleration and being hung down respectively in derivative operation module
Before carrying out derivative operation to acceleration, Fourier is carried out to transverse acceleration, longitudinal acceleration and vertical acceleration respectively
Conversion, obtains horizontal frequency domain acceleration, longitudinal frequency domain acceleration and vertical frequency domain acceleration.
Module is chosen, for choosing horizontal frequency domain acceleration, longitudinal frequency domain acceleration and vertical frequency domain acceleration respectively
In preset acceleration information in frequency domain as valid data, obtain effectively horizontal frequency domain acceleration, effectively longitudinal frequency domain
Acceleration and effectively vertical frequency domain acceleration.
Frequency-time domain transformation module, for effective horizontal frequency domain acceleration, effectively longitudinal frequency domain acceleration and effectively vertical
Frequency domain acceleration carries out inverse Fourier transform, obtains effective transverse acceleration, effective longitudinal acceleration and effectively vertical acceleration
Degree.
In some optional implementations of the present embodiment, above-mentioned monitoring unit 504 may further include in Fig. 5 not
Weighting block, comparison module and the optimization module shown.
Wherein, weighting block, for being weighted summation to the first driving parameters and the second driving parameters, obtains travelling shape
State parameter.
Comparison module, for transport condition parameter and preset value to be compared.
Optimization module, for being less than preset value in response to transport condition parameter, the control algolithm to unmanned vehicle is optimized.
The device for the transport condition for monitoring unmanned vehicle that above-described embodiment of the application is provided, obtains unmanned vehicle first
Transport condition data in the process of moving, is then handled above-mentioned transport condition data, obtains the first row of unmanned vehicle
Parameter is sailed, then in conjunction with the second driving parameters of passenger's input of unmanned vehicle, the transport condition of unmanned vehicle is monitored.So as to reality
The existing objective rational transport condition to unmanned vehicle is monitored, and is conducive to the optimization of the control algolithm of unmanned vehicle.
It should be appreciated that unit 501 described in the device 500 of transport condition for monitoring unmanned vehicle is to 504 points of unit
It is not corresponding with each step in the method with reference to described in Fig. 2.Thus, above with respect to the traveling shape for monitoring unmanned vehicle
The operation of the method description of state and feature are equally applicable to device 500 and the unit wherein included, will not be repeated here.Device
500 corresponding units can cooperate to realize the scheme of the embodiment of the present application with the unit in server.
Below with reference to Fig. 6, it illustrates suitable for the computer system 600 for the server of realizing the embodiment of the present application
Structural representation.Server shown in Fig. 6 is only an example, to the function of the embodiment of the present application and should not use range band
Carry out any limitation.
As shown in fig. 6, computer system 600 includes CPU (CPU) 601, it can be read-only according to being stored in
Program in memory (ROM) 602 or be loaded into program in random access storage device (RAM) 603 from storage part 608 and
Perform various appropriate actions and processing.In RAM 603, the system that is also stored with 600 operates required various programs and data.
CPU 601, ROM 602 and RAM 603 are connected with each other by bus 604.Input/output (I/O) interface 605 is also connected to always
Line 604.
I/O interfaces 605 are connected to lower component：Importation 606 including keyboard, mouse etc.；Penetrated including such as negative electrode
The output par, c 607 of spool (CRT), liquid crystal display (LCD) etc. and loudspeaker etc.；Storage part 608 including hard disk etc.；
And the communications portion 609 of the NIC including LAN card, modem etc..Communications portion 609 via such as because
The network of spy's net performs communication process.Driver 610 is also according to needing to be connected to I/O interfaces 605.Detachable media 611, such as
Disk, CD, magneto-optic disk, semiconductor memory etc., are arranged on driver 610, in order to read from it as needed
Computer program be mounted into as needed storage part 608.
Especially, in accordance with an embodiment of the present disclosure, the process described above with reference to flow chart may be implemented as computer
Software program.For example, embodiment of the disclosure includes a kind of computer program product, it includes carrying on a machine-readable medium
Computer program, the computer program include be used for execution flow chart shown in method program code.Implement such
In example, the computer program can be downloaded and installed by communications portion 609 from network, and/or from detachable media 611
It is mounted.When the computer program is performed by CPU (CPU) 601, what is limited in execution the present processes is upper
State function.
It should be noted that computer-readable medium described herein can be computer-readable signal media or
Computer-readable recording medium either the two any combination.Computer-readable recording medium for example can be --- but
Be not limited to --- electricity, magnetic, optical, electromagnetic, system, device or the device of infrared ray or semiconductor, or it is any more than combination.
The more specifically example of computer-readable recording medium can include but is not limited to：Electrical connection with one or more wires,
Portable computer diskette, hard disk, random access storage device (RAM), read-only storage (ROM), erasable type may be programmed read-only deposit
Reservoir (EPROM or flash memory), optical fiber, portable compact disc read-only storage (CD-ROM), light storage device, magnetic memory
Part or above-mentioned any appropriate combination.In this application, computer-readable recording medium can any be included or store
The tangible medium of program, the program can be commanded execution system, device or device and use or in connection.And
In the application, computer-readable signal media can include believing in a base band or as the data of carrier wave part propagation
Number, wherein carrying computer-readable program code.The data-signal of this propagation can take various forms, including but not
It is limited to electromagnetic signal, optical signal or above-mentioned any appropriate combination.Computer-readable signal media can also be computer
Any computer-readable medium beyond readable storage medium storing program for executing, the computer-readable medium can send, propagate or transmit use
In by the use of instruction execution system, device or device or program in connection.Included on computer-readable medium
Program code any appropriate medium can be used to transmit, include but is not limited to：Wirelessly, electric wire, optical cable, RF etc., Huo Zheshang
Any appropriate combination stated.
Flow chart and block diagram in accompanying drawing, it is illustrated that according to the system of the various embodiments of the application, method and computer journey
Architectural framework in the cards, function and the operation of sequence product.At this point, each square frame in flow chart or block diagram can generation
The part of one module of table, program segment or code, the part of the module, program segment or code is used comprising one or more
In the executable instruction for realizing defined logic function.It should also be noted that in some realizations as replacement, being marked in square frame
The function of note can also be with different from the order marked in accompanying drawing generation.For example, two square frames succeedingly represented are actually
It can perform substantially in parallel, they can also be performed in the opposite order sometimes, this is depending on involved function.Also to note
Meaning, the combination of each square frame in block diagram and/or flow chart and the square frame in block diagram and/or flow chart can be with holding
The special hardware based system of function or operation as defined in row is realized, or can use specialized hardware and computer instruction
Combination realize.
Being described in unit involved in the embodiment of the present application can be realized by way of software, can also be by hard
The mode of part is realized.Described unit can also be set within a processor, for example, can be described as：A kind of processor bag
Include first acquisition unit, processing unit, second acquisition unit and monitoring unit.Wherein, the title of these units is in certain situation
Under do not constitute restriction to the unit in itself, for example, first acquisition unit is also described as " obtaining unmanned vehicle in traveling
During transport condition data unit ".
As on the other hand, present invention also provides a kind of computer-readable medium, the computer-readable medium can be
Included in device described in above-described embodiment；Can also be individualism, and without be incorporated the device in.Above-mentioned calculating
Machine computer-readable recording medium carries one or more program, when said one or multiple programs are performed by the device so that should
Device：Obtain the transport condition data of unmanned vehicle in the process of moving；Transport condition data is handled, the first traveling is obtained
Parameter；Obtain the second driving parameters of passenger's input of unmanned vehicle；According to the first driving parameters and the second driving parameters, nothing is monitored
The transport condition of people's car.
Above description is only the preferred embodiment of the application and the explanation to institute's application technology principle.People in the art
Member should be appreciated that invention scope involved in the application, however it is not limited to the technology of the particular combination of above-mentioned technical characteristic
Scheme, while should also cover in the case where not departing from foregoing invention design, is carried out by above-mentioned technical characteristic or its equivalent feature
Other technical schemes formed by any combination.Such as features described above has similar work(with (but not limited to) disclosed herein
The technical characteristic of energy carries out technical scheme formed by replacement mutually.
Claims (16)
1. a kind of method for being used to monitor the transport condition of unmanned vehicle, it is characterised in that methods described includes：
Obtain the transport condition data of unmanned vehicle in the process of moving；
The transport condition data is handled, the first driving parameters are obtained；
Obtain the second driving parameters of passenger's input of the unmanned vehicle；
According to first driving parameters and second driving parameters, the transport condition of the unmanned vehicle is monitored.
2. according to the method described in claim 1, it is characterised in that the transport condition data includes：Transverse acceleration, along institute
The longitudinal acceleration of unmanned vehicle travel direction, the vertical acceleration perpendicular to ground upwardly are stated, wherein, it is horizontal, longitudinal and vertical
To meeting right-handed Cartesian coordinate system.
3. method according to claim 2, it is characterised in that described to handle the transport condition data, including：
Derivative operation is carried out to the transverse acceleration, the longitudinal acceleration and the vertical acceleration respectively, horizontal stroke is obtained
To anxious acceleration, the anxious acceleration in longitudinal direction and vertical anxious acceleration；
The variance of the laterally anxious acceleration, the anxious acceleration in longitudinal direction and the vertical anxious acceleration is determined respectively；
According to the transverse acceleration, the longitudinal acceleration, the variance of the laterally anxious acceleration, the anxious acceleration in the longitudinal direction
Variance and the vertical anxious acceleration variance, determine first driving parameters.
4. method according to claim 3, it is characterised in that it is described determine the laterally anxious acceleration respectively, it is described vertical
To the variance of anxious acceleration and the vertical anxious acceleration, including：
Each laterally anxious acceleration magnitude for determining to obtain during the traveling of the unmanned vehicle respectively, the anxious acceleration magnitude in each longitudinal direction with
And each vertical anxious acceleration magnitude；
Determine the horizontal anxious acceleration magnitude of the continuous predetermined number of sequential, the anxious acceleration magnitude in longitudinal direction and vertical anxious acceleration magnitude
Average value；
Each average value of the laterally anxious acceleration, each average value of the anxious acceleration in the longitudinal direction and described vertical are determined respectively
The variance of each average value of anxious acceleration.
5. method according to claim 3, it is characterised in that it is described according to the transverse acceleration, the longitudinal direction accelerates
Degree, the variance of the laterally anxious acceleration, the variance and the variance of the vertical anxious acceleration of the anxious acceleration in the longitudinal direction, really
Fixed first driving parameters, including：
According to the transverse acceleration and the longitudinal acceleration, the traveling intensity index of the unmanned vehicle is determined；
According to the variance, the variance of the anxious acceleration in the longitudinal direction and the side of the vertical anxious acceleration of the laterally anxious acceleration
Difference, determines the traveling nergy Index of the unmanned vehicle；
According to the traveling intensity index and the traveling nergy Index, first driving parameters are determined.
6. method according to claim 2, it is characterised in that described to handle the transport condition data, including：
It is described respectively to the transverse acceleration, the longitudinal acceleration and the vertical acceleration carry out derivative operation it
Before, Fourier transformation is carried out to the transverse acceleration, the longitudinal acceleration and the vertical acceleration respectively, horizontal stroke is obtained
To frequency domain acceleration, longitudinal frequency domain acceleration and vertical frequency domain acceleration；
Choose in the horizontal frequency domain acceleration, longitudinal frequency domain acceleration and the vertical frequency domain acceleration and preset respectively
Acceleration information in frequency domain obtains effectively horizontal frequency domain acceleration, effectively longitudinal frequency domain acceleration as valid data
And effective vertical frequency domain acceleration；
To effective horizontal frequency domain acceleration, effective longitudinal frequency domain acceleration and the effectively vertical frequency domain acceleration
Inverse Fourier transform is carried out, effective transverse acceleration, effective longitudinal acceleration and effective vertical acceleration is obtained.
7. the method according to claim any one of 1-6, it is characterised in that described according to first driving parameters and institute
The second driving parameters are stated, the transport condition of the unmanned vehicle is monitored, including：
Summation is weighted to first driving parameters and second driving parameters, transport condition parameter is obtained；
The transport condition parameter is compared with preset value；
It is less than the preset value in response to the transport condition parameter, the control algolithm to the unmanned vehicle is optimized.
8. a kind of device for being used to monitor the transport condition of unmanned vehicle, it is characterised in that described device includes：
First acquisition unit, for obtaining the transport condition data of unmanned vehicle in the process of moving；
Processing unit, for handling the transport condition data, obtains the first driving parameters；
Second acquisition unit, for obtaining the second driving parameters that the passenger of the unmanned vehicle inputs；
Monitoring unit, for according to first driving parameters and second driving parameters, monitoring the traveling of the unmanned vehicle
State.
9. device according to claim 8, it is characterised in that the transport condition data includes：Transverse acceleration, along institute
The longitudinal acceleration of unmanned vehicle travel direction, the vertical acceleration perpendicular to ground upwardly are stated, wherein, it is horizontal, longitudinal and vertical
To meeting right-handed Cartesian coordinate system.
10. device according to claim 9, it is characterised in that the processing unit includes：
Derivative operation module, for entering respectively to the transverse acceleration, the longitudinal acceleration and the vertical acceleration
Row derivative operation, obtains laterally anxious acceleration, the anxious acceleration in longitudinal direction and vertical anxious acceleration；
Variance determination module, for determining the laterally anxious acceleration, the anxious acceleration in longitudinal direction and the vertical urgency respectively
The variance of acceleration；
First traveling parameter determination module, for according to the transverse acceleration, the longitudinal acceleration, the laterally anxious acceleration
The variance and the variance of the vertical anxious acceleration of the variance of degree, the anxious acceleration in the longitudinal direction, determine the first traveling ginseng
Number.
11. device according to claim 10, it is characterised in that the variance determines that mould is further used for：
Each laterally anxious acceleration magnitude for determining to obtain during the traveling of the unmanned vehicle respectively, the anxious acceleration magnitude in each longitudinal direction with
And each vertical anxious acceleration magnitude；
Determine the horizontal anxious acceleration magnitude of the continuous predetermined number of sequential, the anxious acceleration magnitude in longitudinal direction and vertical anxious acceleration magnitude
Average value；
Each average value of the laterally anxious acceleration, each average value of the anxious acceleration in the longitudinal direction and described vertical are determined respectively
The variance of each average value of anxious acceleration.
12. device according to claim 10, it is characterised in that the first traveling parameter determination module is further used
In：
According to the transverse acceleration and the longitudinal acceleration, the traveling intensity index of the unmanned vehicle is determined；
According to the variance, the variance of the anxious acceleration in the longitudinal direction and the side of the vertical anxious acceleration of the laterally anxious acceleration
Difference, determines the traveling nergy Index of the unmanned vehicle；
According to the traveling intensity index and the traveling nergy Index, first driving parameters are determined.
13. device according to claim 9, it is characterised in that the processing unit also includes：
Time-frequency conversion module, for the derivative operation module respectively to the transverse acceleration, the longitudinal acceleration with
And before the vertical acceleration carries out derivative operation, respectively to the transverse acceleration, the longitudinal acceleration and described
Vertical acceleration carries out Fourier transformation, obtains horizontal frequency domain acceleration, longitudinal frequency domain acceleration and vertical frequency domain acceleration；
Module is chosen, for choosing the horizontal frequency domain acceleration, longitudinal frequency domain acceleration and the vertical frequency respectively
The acceleration information in frequency domain is preset in the acceleration of domain as valid data, effectively horizontal frequency domain acceleration, effectively is obtained
Longitudinal frequency domain acceleration and effectively vertical frequency domain acceleration；
Frequency-time domain transformation module, for effective horizontal frequency domain acceleration, effective longitudinal frequency domain acceleration and described
Effectively vertical frequency domain acceleration carries out inverse Fourier transform, obtains effective transverse acceleration, effective longitudinal acceleration and effectively
Vertical acceleration.
14. the device according to claim any one of 8-13, it is characterised in that the monitoring unit includes：
Weighting block, for being weighted summation to first driving parameters and second driving parameters, obtains travelling shape
State parameter；
Comparison module, for the transport condition parameter to be compared with preset value；
Optimization module, for being less than the preset value in response to the transport condition parameter, to the control algolithm of the unmanned vehicle
Optimize.
15. a kind of server, it is characterised in that including：
One or more processors；
Storage device, for storing one or more programs,
When one or more of programs are by one or more of computing devices so that one or more of processors are real
The existing method as described in any in claim 1-7.
16. a kind of computer-readable recording medium, is stored thereon with computer program, it is characterised in that the program is by processor
The method as described in any in claim 1-7 is realized during execution.
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