CN108961749A - A kind of intelligent transportation system and intellectual traffic control method - Google Patents
A kind of intelligent transportation system and intellectual traffic control method Download PDFInfo
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
- G08G1/0137—Measuring and analyzing of parameters relative to traffic conditions for specific applications
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0231—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0257—Control of position or course in two dimensions specially adapted to land vehicles using a radar
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0276—Control of position or course in two dimensions specially adapted to land vehicles using signals provided by a source external to the vehicle
- G05D1/0278—Control of position or course in two dimensions specially adapted to land vehicles using signals provided by a source external to the vehicle using satellite positioning signals, e.g. GPS
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0276—Control of position or course in two dimensions specially adapted to land vehicles using signals provided by a source external to the vehicle
- G05D1/0285—Control of position or course in two dimensions specially adapted to land vehicles using signals provided by a source external to the vehicle using signals transmitted via a public communication network, e.g. GSM network
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
- G08G1/0125—Traffic data processing
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/09—Arrangements for giving variable traffic instructions
- G08G1/0962—Arrangements for giving variable traffic instructions having an indicator mounted inside the vehicle, e.g. giving voice messages
- G08G1/0967—Systems involving transmission of highway information, e.g. weather, speed limits
- G08G1/096708—Systems involving transmission of highway information, e.g. weather, speed limits where the received information might be used to generate an automatic action on the vehicle control
- G08G1/096725—Systems involving transmission of highway information, e.g. weather, speed limits where the received information might be used to generate an automatic action on the vehicle control where the received information generates an automatic action on the vehicle control
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/09—Arrangements for giving variable traffic instructions
- G08G1/0962—Arrangements for giving variable traffic instructions having an indicator mounted inside the vehicle, e.g. giving voice messages
- G08G1/0967—Systems involving transmission of highway information, e.g. weather, speed limits
- G08G1/096766—Systems involving transmission of highway information, e.g. weather, speed limits where the system is characterised by the origin of the information transmission
- G08G1/096775—Systems involving transmission of highway information, e.g. weather, speed limits where the system is characterised by the origin of the information transmission where the origin of the information is a central station
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Abstract
The embodiment of the invention discloses a kind of intelligent transportation system and intellectual traffic control methods.The system includes: ground common control center and unmanned motor vehicle using communication connection；Ground common control center includes: traffic condition sensory perceptual system, for obtaining traffic environment condition information；Decision system, including programmed decision-making module are calculated, for determining the control information of unmanned motor vehicle according to traffic environment condition information；First communication module is sent to unmanned motor vehicle for that will control information；Unmanned motor vehicle includes: control system, including second communication module, for receiving control information, vehicle control module, for generating vehicle control signal according to the control information；Execution system, for executing vehicle control system according to vehicle control signal.By using above-mentioned technical proposal, the factory technology complexity for reducing automatic driving vehicle may be implemented and reduce the production of automatic driving vehicle and the effect of maintenance cost.
Description
Technical field
The present embodiments relate to unmanned technical field more particularly to a kind of intelligent transportation system and intelligent transportation
Control method.
Background technique
With the rapid development of artificial intelligence technology, unmanned technology has become the hot topic of this field.
It is unmanned to rely on artificial intelligence, it can be in the case where nobody's active operation, with allowing computer automatic safe
Operate motor vehicles.It is unmanned not only to free people from taking great energy in laborious driver behavior, but also due to calculating
Accuracy, response speed and the repeatability of machine can greatly promote the safety of motor vehicle considerably beyond the mankind, reduce
Traffic accident；It can be gone on a journey based on unpiloted intelligent transportation for the mankind and great convenience is provided, greatly improve road
Ability alleviates traffic congestion.Current unmanned technology is mainly set about from vehicle itself, and vehicle intelligent computing system is allowed to simulate
All behaviors of people in operating motor vehicles.Vehicle is allowed to perceive ambient enviroment and condition of road surface, planning traveling road as people
Line makes correlation analysis judgement and decision, completes sequence of operations of such as refueling, brake, turn to etc..However, setting in this way
The drawbacks of be to need to carry out each automatic driving vehicle the configuration of hardware and software aspects, and need to carry out before factory
Stringent detection, so that the production technology of automatic driving vehicle is complicated, production cost and maintenance cost are also high.
Summary of the invention
The embodiment of the present invention provides a kind of intelligent transportation system and intellectual traffic control method, may be implemented to reduce nobody
It drives the factory technology complexity of vehicle and reduces the production of automatic driving vehicle and the effect of maintenance cost.
In a first aspect, the system includes in ground common control the embodiment of the invention provides a kind of intelligent transportation system
The heart and unmanned motor vehicle, in which:
The ground common control center and the unmanned motor vehicle are using communication connection；
The ground common control center includes:
Traffic condition sensory perceptual system and calculating decision system；
The traffic condition sensory perceptual system is for obtaining traffic environment condition information；
The calculating decision system includes programmed decision-making module, and the programmed decision-making module is used for according to the traffic environment
Condition information determines the control information of unmanned motor vehicle；The calculating decision system further includes first communication module, is used
In the control information is sent to unmanned motor vehicle；
The unmanned motor vehicle includes:
Control system and execution system；
The control system, including second communication module and vehicle control module, the second communication module is for receiving
The control information, the vehicle control module are used to generate vehicle control signal according to the control information；
The execution system, for executing vehicle control system according to the vehicle control signal.
Further, the traffic condition sensory perceptual system includes: the camera, radar, wireless location being arranged on road surface
One or more of device.
Further, the calculating decision system further include:
Information Fusion Module, the traffic environment condition information for will get in traffic condition sensory perceptual system melt
It closes, forms traffic environment condition information set, and delete the duplicate message in the traffic environment condition information set.
Further, the information Fusion Module, is also used to:
The traffic environment condition information that unmanned motor vehicle is got is obtained by first communication module；And it will be described
The traffic environment condition information that unmanned motor vehicle is got is fused in traffic environment condition information set, and deletes institute
State the duplicate message in traffic environment condition information set；
Wherein, the traffic environment condition information that the unmanned motor vehicle is got includes: vehicle location information, figure
As one or more of information, radar information and vehicle speed information.
Further, the control information of the unmanned motor vehicle, including braking information, dynamic Information and steering
One or more of information.
Further, the system also includes:
Intelligent traffic monitoring center is connect with the ground common control center, and being used for will be in the ground common control
The control information and Vehicular behavior of the heart generate display picture or generate display image.
Second aspect, the embodiment of the invention also provides a kind of intellectual traffic control methods, this method comprises:
Obtain traffic environment condition information；The traffic environment condition information includes: to be obtained by the camera on road surface
Vehicle local environment image obtains vehicle local environment object movement speed by the radar on road surface and by road surface
The location information of radio positioner acquisition vehicle；
According to the traffic environment condition information, the control information of unmanned motor vehicle is generated；The control information
It include: one or more of braking information, dynamic Information and direction information；
The control information is sent to unmanned motor vehicle, is used to indicate nobody and drives by system by wireless communication
Motor vehicles are sailed according to the control information, execute unmanned motor vehicle control.
Further, in system by wireless communication, before the control information is sent to unmanned motor vehicle,
The method also includes:
Determine unmanned motor vehicle to be controlled；
Correspondingly, system by wireless communication, is sent to unmanned motor vehicle for the control information, comprising:
The control information is sent to fixed unmanned motor vehicle to be controlled by system by wireless communication.
Further, unmanned motor vehicle to be controlled is determined, comprising:
The first radio positioning signal is sent by the apparatus for transmitting signal of the fixation position on road surface, according to unmanned machine
The first radio positioning signal intensity that motor-car receives, determines unmanned motor vehicle to be controlled；
Alternatively,
By the wireless localization apparatus of the fixation position at least two road surfaces, obtain what unmanned motor vehicle was sent
Second radio positioning signal, the second nothing got according to the wireless localization apparatus of the fixation position at least two road surface
The difference of line positioning signal determines unmanned motor vehicle to be controlled.
Further, the method also includes:
By the control result of unmanned motor vehicle, monitoring signal is generated, and by the monitoring signal in set device
On shown.
Technical solution provided by the embodiment of the present application passes through setting ground centralized-control center and unmanned motor vehicle
, in which: the ground common control center and the unmanned motor vehicle are using communication connection；Concentrate control in the ground
Center processed includes: traffic condition sensory perceptual system and calculating decision system；The traffic condition sensory perceptual system is for obtaining traffic ring
Border condition information；The calculating decision system includes programmed decision-making module, and the programmed decision-making module is used for according to the traffic
Circumstance state information determines the control information of unmanned motor vehicle；The calculating decision system further includes the first communication mould
Block, for the control information to be sent to unmanned motor vehicle；The unmanned motor vehicle includes: control system
With the system of execution；The control system, including second communication module and vehicle control module, the second communication module is for connecing
The control information is received, the vehicle control module is used to generate vehicle control signal according to the control information；The execution
System, for executing vehicle control system according to the vehicle control signal.By using technical side provided herein
Case, may be implemented reduce automatic driving vehicle factory technology complexity and reduce automatic driving vehicle production and safeguard at
This effect.
Detailed description of the invention
Fig. 1 is the structural block diagram for the intelligent transportation system that the embodiment of the present invention one provides；
Fig. 2 is the schematic diagram for the traffic condition sensory perceptual system that the embodiment of the present invention one provides；
Fig. 3 is the flow chart of intellectual traffic control method provided by Embodiment 2 of the present invention.
Specific embodiment
The present invention 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 the present invention rather than limiting the invention.It also should be noted that in order to just
Only the parts related to the present invention are shown in description, attached drawing rather than entire infrastructure.
It should be mentioned that some exemplary embodiments are described as before exemplary embodiment is discussed in greater detail
The processing or method described as flow chart.Although each step is described as the processing of sequence by flow chart, many of these
Step can be implemented concurrently, concomitantly or simultaneously.In addition, the sequence of each step can be rearranged.When its operation
The processing can be terminated when completion, it is also possible to have the additional step being not included in attached drawing.The processing can be with
Corresponding to method, function, regulation, subroutine, subprogram etc..
The striving direction of automatic Pilot technology is all driving behaviors and thought for allowing vehicle based computing system to simulate people completely,
Automatic driving vehicle is namely allowed to have the powerful ability of Intellisense, calculating, real-time programmed decision-making etc., the reality of these abilities
Now depend on a series of high performance electronic equipments.Current Unmanned Systems are mainly by context aware systems, calculating decision
The three parts such as center, execution system composition.Wherein context aware systems include various types of sensors, such as camera, radar
Deng and GPS positioning system, mobile communication system etc..The information of these sensors acquisition is that motor vehicles act in next step
Original foundation.The essence for calculating decision center is powerful computing capability, and the major embodiment intelligence of automatic driving vehicle is
The core component of automated driving system.Vehicle control system is for finally controlling throttle, brake and the steering etc. of vehicle.
Decision center is calculated mainly to be made of several parts such as information fusion, decision rule, vehicle controls again.Information fusion portion
The effect divided is that the information sent to various types sensor carries out convergence analysis processing, so that it is determined that the position of vehicle, road
Situation and other surrounding enviroment information, correlated results give decision rule unit.Decision rule unit is according to information fusion unit
Processing result plan that vehicle movement, correlated results gives vehicle control system.Vehicle control system is according to deciding by oneself
The input information of plan planning unit and the present situation for combining vehicle are calculated throttle according to certain control algolithm, stop
The control amounts such as vehicle, steering form the execution system that control instruction gives bottom.
As can be seen that current automated driving system is dependent on many high-performance, high-cost sensing equipment and powerful
Computing capability.So more things is integrated on individual vehicle, so that the automated driving system of vehicle is extremely complex, and
It is with high costs.
Embodiment one
Fig. 1 is the structural block diagram for the intelligent transportation system that the embodiment of the present invention one provides, and the present embodiment is applicable, and nobody drives
The control situation of vehicle is sailed, which can be realized by the mode of software and/or hardware.
As shown in Figure 1, the intelligent transportation system includes:
Ground common control center 10 and unmanned motor vehicle 20, in which:
The ground common control center 10 and the unmanned motor vehicle 20 are using communication connection；
The ground common control center 10 includes:
Traffic condition sensory perceptual system 110 and calculating decision system 120；
The traffic condition sensory perceptual system 110 is for obtaining traffic environment condition information；
The calculating decision system 120 includes programmed decision-making module 121, and the programmed decision-making module 121 is used for according to institute
Traffic environment condition information is stated, determines the control information of unmanned motor vehicle；The calculating decision system further includes first
Communication module 122, for the control information to be sent to unmanned motor vehicle；
The unmanned motor vehicle 20 includes:
Control system 210 and execution system 220；
The control system 210, including second communication module 211 and vehicle control module 212, the second communication module
211 for receiving the control information, and the vehicle control module 212 is used to generate vehicle control letter according to the control information
Number；
The execution system 220, for executing vehicle control system according to the vehicle control signal.
In the present embodiment, traffic condition sensory perceptual system is set to ground common control center, rather than be arranged in nothing
On people's driving maneuver vehicle, it can thus require to configure extremely complex traffic shape to avoid each unmanned motor vehicle
Condition awareness apparatus, and ground common control center determines the control of unmanned motor vehicle according to traffic environment condition information
Information processed, in this way setting just transfer to ground common control center to complete the task that software calculates aspect, drive to reduce nobody
Sail the configuration burden of the software aspects of motor vehicles.And ground common control center is through wireless communication control information
It is sent to unmanned motor vehicle, as long as setting communication device can be held to complete in unmanned motor vehicle in this way
Reception to control information determines vehicle control signal, then execute the vehicle control signal further according to control information
To realize the timely reflection of unmanned motor vehicle road pavement situation.
In addition, ground common control center can lead to since control information is obtained from ground common control center
It crosses pre-set mode and corresponding speed-limiting messages is set for every kind of specific road section, for example in school zone, speed limit is
30Km/h can pass through the ground common control at school zone then in unmanned motor vehicle traveling to school zone
Center sends corresponding speed-limiting messages to unmanned motor vehicle, and vehicle can work as after obtaining corresponding information according to itself
Preceding speed determines and executes the operation such as deceleration.
In the present embodiment, optionally, the traffic condition sensory perceptual system includes: the camera being arranged on road surface, thunder
It reaches, one or more of radio positioner.Fig. 2 is showing for the traffic condition sensory perceptual system that the embodiment of the present invention one provides
It is intended to, in the present embodiment, camera, radar and radio positioner can be arranged in onto the Traffic signal post in roadside,
In addition to this it is possible to which roadside buildings object and other positions are arranged in, the benefit that the present embodiment is arranged in this way is can to reduce
The investigative range that unmanned motor vehicle is influenced because of nearby vehicle height, can accomplish it is comprehensive know information of road surface,
Improve the traffic safety of unmanned motor vehicle.
In the present embodiment, optionally, the calculating decision system further include: information Fusion Module is used for traffic shape
The traffic environment condition information got in condition sensory perceptual system is merged, and forms traffic environment condition information set, and delete
Duplicate message in the traffic environment condition information set.The benefit being arranged in this way is can be to camera, radar and nothing
Traffic environment condition information acquired in line positioning device is integrated, avoid for duplicate information carry out it is duplicate identification and
It calculates, and reduces calculating speed, increase computation burden, may further guarantee the traffic safety of unmanned motor vehicle.
On the basis of above-mentioned each technical solution, optionally, the information Fusion Module is also used to: passing through the first communication
Module obtains the traffic environment condition information that unmanned motor vehicle is got；And the unmanned motor vehicle is obtained
To traffic environment condition information be fused in traffic environment condition information set, and delete the traffic environment condition information collection
Duplicate message in conjunction；Wherein, the traffic environment condition information that the unmanned motor vehicle is got includes: vehicle location
One or more of information, image information, radar information and vehicle speed information.
The technical program provides a kind of feelings that traffic environment condition information can be also obtained in unmanned motor vehicle
It under condition, is obtained by communication device, and the traffic environment condition information got with ground common control center is melted
Close, the method for obtaining fused traffic condition environmental information, may be implemented ground common control center with it is unmanned motor-driven
Vehicle obtains traffic environment condition information simultaneously, is more accurately responded according to traffic condition, and vehicle operation is improved
In traffic safety.
In the present embodiment, optionally, the control information of the unmanned motor vehicle, including braking information, power
One or more of information and direction information.The benefit being arranged in this way is can timely to be made adding according to traffic environment
The various reactions such as speed, deceleration, braking and steering, realize comprehensive controllability in vehicle travel process.
In the present embodiment, optionally, the system also includes intelligent traffic monitoring centers, concentrate and control with the ground
Center processed connection, for by the control information at the ground common control center and Vehicular behavior generate display picture or
Person generates display image.The advantages of this arrangement are as follows road traffic control situation can be formed to corresponding picture or image
Be shown to staff, can for staff carry out real-time oversight, and can be realized road traffic control and monitoring simultaneously into
Capable effect provides deeper guarantee for traffic safety.
The technical solution of the present embodiment passes through setting ground centralized-control center and unmanned motor vehicle, in which: institute
Ground common control center and the unmanned motor vehicle are stated using communication connection；Pericardium in the ground common control
It includes: traffic condition sensory perceptual system and calculating decision system；The traffic condition sensory perceptual system is for obtaining traffic environment situation letter
Breath；The calculating decision system includes programmed decision-making module, and the programmed decision-making module is used for according to the traffic environment situation
Information determines the control information of unmanned motor vehicle；The calculating decision system further includes first communication module, and being used for will
The control information is sent to unmanned motor vehicle；The unmanned motor vehicle includes: control system and executes system
System；The control system, including second communication module and vehicle control module, the second communication module is for receiving the control
Information processed, the vehicle control module are used to generate vehicle control signal according to the control information；The execution system, is used for
According to the vehicle control signal, vehicle control system is executed.By using technical solution provided herein, may be implemented
It reduces the factory technology complexity of automatic driving vehicle and reduces the production of automatic driving vehicle and the effect of maintenance cost.
Embodiment two
Fig. 3 is the flow chart of intellectual traffic control method provided by Embodiment 2 of the present invention.This intellectual traffic control method
Can in the above-described embodiments provided by realize on the basis of intelligent transportation system.And it can integrate in intelligent transportation system
In.
As shown in figure 3, the intellectual traffic control method includes:
S310, traffic environment condition information is obtained；The traffic environment condition information includes: by the camera on road surface
Vehicle local environment image is obtained, vehicle local environment object movement speed is obtained by the radar on road surface and passes through road surface
On radio positioner obtain vehicle location information.
S320, according to the traffic environment condition information, generate the control information of unmanned motor vehicle；The control
Information includes: one or more of braking information, dynamic Information and direction information.
The control information is sent to unmanned motor vehicle, is used to indicate nothing by S330, by wireless communication system
People's driving maneuver vehicle executes unmanned motor vehicle control according to the control information.
Technical solution provided by the present embodiment, by obtaining traffic environment condition information；The traffic environment situation letter
Breath includes: to obtain vehicle local environment image by the camera on road surface, obtain ring locating for vehicle by the radar on road surface
Border object movement speed and the location information that vehicle is obtained by the radio positioner on road surface；According to the traffic environment
Condition information generates the control information of unmanned motor vehicle；The control information include: braking information, dynamic Information with
And one or more of direction information；The control information is sent to unmanned motor-driven by system by wireless communication
Vehicle is used to indicate unmanned motor vehicle according to the control information, executes unmanned motor vehicle control.By adopting
With above-mentioned technical proposal, the factory technology complexity for reducing automatic driving vehicle may be implemented and reduce automatic driving vehicle
The effect of production and maintenance cost.
On the basis of above-mentioned each technical solution, optionally, in system by wireless communication, the control information is sent
Before unmanned motor vehicle, the method also includes: determine unmanned motor vehicle to be controlled；Correspondingly, passing through
The control information is sent to unmanned motor vehicle by wireless communication system, comprising: system by wireless communication, by institute
It states control information and is sent to fixed unmanned motor vehicle to be controlled.Wherein, all due to being travelled on a road
More vehicles, then before being communicated to unmanned motor vehicle, it is thus necessary to determine that unmanned motor vehicle to be controlled, in this way
Setting is to be able to more fixed issue and controls information, avoids unmanned motor vehicle in the process of moving, receives not
Belong to the information of control itself and be filtered and delete, to achieve the effect that eliminate noise.
Based on the above technical solution, optionally, unmanned motor vehicle to be controlled is determined, comprising: pass through road
The apparatus for transmitting signal of fixation position on face sends the first radio positioning signal, is received according to unmanned motor vehicle
First radio positioning signal intensity determines unmanned motor vehicle to be controlled；Alternatively, passing through the fixation at least two road surfaces
The wireless localization apparatus of position obtains the second radio positioning signal that unmanned motor vehicle is sent, according to described at least two
The difference for the second radio positioning signal that the wireless localization apparatus of fixation position on a road surface is got, determine it is to be controlled nobody
Driving maneuver vehicle.
Wherein it is determined that the method the technical program of unmanned motor vehicle to be controlled gives two kinds, one is pass through
The apparatus for transmitting signal of fixation position on road surface sends the first radio positioning signal, is received according to unmanned motor vehicle
The first radio positioning signal intensity, determine unmanned motor vehicle to be controlled, wherein intensity is smaller, then shows and issue
The distance of first radio positioning signal is remoter, and specific numerical value can be determined by testing obtained mapping relations, in turn
Determine unmanned motor vehicle to be controlled.Another method is wireless from unmanned motor vehicle to be controlled at least two
Positioning device sends the second radio positioning signal, the second wireless location got according at least two wireless localization apparatus
The difference of signal determines the unmanned motor vehicle to be controlled for issuing the second radio positioning signal.
Based on the above technical solution, optionally, the method also includes: by the control of unmanned motor vehicle
As a result, generating monitoring signal, and the monitoring signal is shown on set device.The benefit being arranged in this way is can be right
Vehicle control result is monitored in real time, finds the problem formulate countermeasure in time, to guarantee traffic safety.
Key point of the invention is:
Road System is regarded as a big active transport system, and is not only the carrier of motor vehicles.Road System and
Motor vehicles, which cooperate, realizes the automatic running function of vehicle；
In this system, Road System is more like a transport pipeline, and motor vehicles are more like cargo.In motor vehicle
During from origin to destination, main driving judgement and decision are completed by Road System, and motor vehicles only need
It executes instruction.
Under this central controlled model, the driving function of each motor vehicles is greatly simplified, thus motor vehicles
Cost of implementation can be greatly reduced.
Under this central controlled model, comparatively, Road System is less sensitive to cost, and it is less by
To the restriction in space, thus the electronic equipment of higher performance can be used, this is more advantageous to the realization of Function for Automatic Pilot.
Road System, can be according to different roads for vehicle when arranging the sensing equipments such as radar, camera
Planar condition, density, height, in terms of flexible choice.The system being arranged so for the integral status on road surface have it is more preferable,
More fully control.
Since Road System has whole assurance to entire traffic condition, it is thus possible to flexibly adjust in real time according to the actual situation
Vehicle stream, this alleviates traffic congestion and is of great importance for improving road colleague's ability.
Note that the above is only a better embodiment of the present invention and the applied technical principle.It will be appreciated by those skilled in the art that
The invention is not limited to the specific embodiments described herein, be able to carry out for a person skilled in the art it is various it is apparent variation,
It readjusts and substitutes without departing from protection scope of the present invention.Therefore, although being carried out by above embodiments to the present invention
It is described in further detail, but the present invention is not limited to the above embodiments only, without departing from the inventive concept, also
It may include more other equivalent embodiments, and the scope of the invention is determined by the scope of the appended claims.
Claims (10)
1. a kind of intelligent transportation system, which is characterized in that including ground common control center and unmanned motor vehicle,
In:
The ground common control center and the unmanned motor vehicle are using communication connection；
The ground common control center includes:
Traffic condition sensory perceptual system and calculating decision system；
The traffic condition sensory perceptual system is for obtaining traffic environment condition information；
The calculating decision system includes programmed decision-making module, and the programmed decision-making module is used for according to the traffic environment situation
Information determines the control information of unmanned motor vehicle；The calculating decision system further includes first communication module, and being used for will
The control information is sent to unmanned motor vehicle；
The unmanned motor vehicle includes:
Control system and execution system；
The control system, including second communication module and vehicle control module, the second communication module are described for receiving
Information is controlled, the vehicle control module is used to generate vehicle control signal according to the control information；
The execution system, for executing vehicle control system according to the vehicle control signal.
2. system according to claim 1, which is characterized in that the traffic condition sensory perceptual system includes: to be arranged on road surface
On camera, radar, one or more of radio positioner.
3. system according to claim 2, which is characterized in that the calculating decision system further include:
Information Fusion Module, the traffic environment condition information for will get in traffic condition sensory perceptual system merge, shape
At traffic circumstance state information set, and delete the duplicate message in the traffic environment condition information set.
4. system according to claim 3, which is characterized in that the information Fusion Module is also used to:
The traffic environment condition information that unmanned motor vehicle is got is obtained by first communication module；And by it is described nobody
The traffic environment condition information that driving maneuver vehicle is got is fused in traffic environment condition information set, and deletes the friendship
Duplicate message in logical circumstance state information set；
Wherein, the traffic environment condition information that the unmanned motor vehicle is got includes: vehicle location information, image letter
One or more of breath, radar information and vehicle speed information.
5. system according to claim 1, which is characterized in that the control information of the unmanned motor vehicle, including
One or more of braking information, dynamic Information and direction information.
6. system according to claim 1, which is characterized in that further include:
Intelligent traffic monitoring center is connect with the ground common control center, for by the ground common control center
It controls information and Vehicular behavior generates display picture or generates display image.
7. a kind of intellectual traffic control method characterized by comprising
Obtain traffic environment condition information；The traffic environment condition information includes: to obtain vehicle by the camera on road surface
Local environment image obtains vehicle local environment object movement speed by the radar on road surface and by wireless on road surface
The location information of positioning device acquisition vehicle；
According to the traffic environment condition information, the control information of unmanned motor vehicle is generated；The control information includes:
One or more of braking information, dynamic Information and direction information；
The control information is sent to unmanned motor vehicle, is used to indicate unmanned machine by system by wireless communication
Motor-car executes unmanned motor vehicle control according to the control information.
8. the method according to the description of claim 7 is characterized in that the control information is sent out in system by wireless communication
Before giving unmanned motor vehicle, the method also includes:
Determine unmanned motor vehicle to be controlled；
Correspondingly, system by wireless communication, is sent to unmanned motor vehicle for the control information, comprising:
The control information is sent to fixed unmanned motor vehicle to be controlled by system by wireless communication.
9. according to the method described in claim 8, it is characterized in that, determining unmanned motor vehicle to be controlled, comprising:
The first radio positioning signal is sent by the apparatus for transmitting signal of the fixation position on road surface, according to unmanned motor vehicle
The the first radio positioning signal intensity received, determines unmanned motor vehicle to be controlled；
Alternatively,
By the wireless localization apparatus of the fixation position at least two road surfaces, unmanned motor vehicle is sent second is obtained
Radio positioning signal is wirelessly determined according to second that the wireless localization apparatus of the fixation position at least two road surface is got
The difference of position signal, determines unmanned motor vehicle to be controlled.
10. the method according to the description of claim 7 is characterized in that further include:
By the control result of unmanned motor vehicle, monitoring signal is generated, and the monitoring signal is enterprising in set device
Row display.
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Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109618136A (en) * | 2018-12-14 | 2019-04-12 | 北京汽车集团有限公司 | Vehicle management system and method |
| CN109901170A (en) * | 2019-03-21 | 2019-06-18 | 西安交通大学 | A kind of intelligent transportation detection system and method based on radar block array |
| CN109921883A (en) * | 2019-04-12 | 2019-06-21 | 成都宇俊盛科技有限公司 | Full-automatic unmanned driving's rail vehicle communication system of serverless backup data link |
| CN110377027A (en) * | 2019-06-04 | 2019-10-25 | 深圳市速腾聚创科技有限公司 | Unmanned cognitive method, system, device and storage medium |
| CN111583693A (en) * | 2020-05-07 | 2020-08-25 | 中国农业大学 | Intelligent traffic cooperative operation system for urban road and intelligent vehicle control method |
| CN113330497A (en) * | 2020-06-05 | 2021-08-31 | 曹庆恒 | Automatic driving method and device based on intelligent traffic system and intelligent traffic system |
Citations (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104269053A (en) * | 2014-08-29 | 2015-01-07 | 陈业军 | Intelligent traffic system and method and intelligent automobile |
| CN104267721A (en) * | 2014-08-29 | 2015-01-07 | 陈业军 | Unmanned driving system of intelligent automobile |
| CN106325270A (en) * | 2016-08-12 | 2017-01-11 | 天津大学 | Intelligent vehicle navigation system and method based on perception and autonomous calculation positioning navigation |
| CN106447137A (en) * | 2016-11-18 | 2017-02-22 | 广东省科技基础条件平台中心 | Traffic passenger flow forecasting method based on information fusion and Markov model |
| CN107161141A (en) * | 2017-03-08 | 2017-09-15 | 深圳市速腾聚创科技有限公司 | Pilotless automobile system and automobile |
| CN107272683A (en) * | 2017-06-19 | 2017-10-20 | 中国科学院自动化研究所 | Parallel intelligent vehicle control based on ACP methods |
| CN206696702U (en) * | 2017-03-06 | 2017-12-01 | 上海悦合自动化技术有限公司 | Robot automated navigation system |
| KR20180009882A (en) * | 2016-07-20 | 2018-01-30 | 인포뱅크 주식회사 | Apparatus and method for controling remote autonomous driving, and apparatus for controling vehicle |
| CN107851386A (en) * | 2015-08-04 | 2018-03-27 | 罗伯特·博世有限公司 | For positioning the method and system of the vehicle in parking lot |
| CN107992091A (en) * | 2017-10-31 | 2018-05-04 | 深圳市博鑫创科科技有限公司 | A kind of balance car follower method and system based on signal strength |
| CN108153311A (en) * | 2017-12-22 | 2018-06-12 | 武汉理工大学 | The intelligence control system and control method formed into columns towards unmanned boat |
| CN207541498U (en) * | 2017-09-22 | 2018-06-26 | 西华师范大学 | A kind of Unmanned Systems |
| US20180178770A1 (en) * | 2015-12-29 | 2018-06-28 | Thunder Power New Energy Vehicle Development Company Limited | [monitor] vehicle hazard detection and warning system |
| CN108225364A (en) * | 2018-01-04 | 2018-06-29 | 吉林大学 | A kind of pilotless automobile driving task decision system and method |
-
2018
- 2018-07-12 CN CN201810766474.5A patent/CN108961749A/en active Pending
Patent Citations (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104267721A (en) * | 2014-08-29 | 2015-01-07 | 陈业军 | Unmanned driving system of intelligent automobile |
| CN104269053A (en) * | 2014-08-29 | 2015-01-07 | 陈业军 | Intelligent traffic system and method and intelligent automobile |
| CN107851386A (en) * | 2015-08-04 | 2018-03-27 | 罗伯特·博世有限公司 | For positioning the method and system of the vehicle in parking lot |
| US20180178770A1 (en) * | 2015-12-29 | 2018-06-28 | Thunder Power New Energy Vehicle Development Company Limited | [monitor] vehicle hazard detection and warning system |
| KR20180009882A (en) * | 2016-07-20 | 2018-01-30 | 인포뱅크 주식회사 | Apparatus and method for controling remote autonomous driving, and apparatus for controling vehicle |
| CN106325270A (en) * | 2016-08-12 | 2017-01-11 | 天津大学 | Intelligent vehicle navigation system and method based on perception and autonomous calculation positioning navigation |
| CN106447137A (en) * | 2016-11-18 | 2017-02-22 | 广东省科技基础条件平台中心 | Traffic passenger flow forecasting method based on information fusion and Markov model |
| CN206696702U (en) * | 2017-03-06 | 2017-12-01 | 上海悦合自动化技术有限公司 | Robot automated navigation system |
| CN107161141A (en) * | 2017-03-08 | 2017-09-15 | 深圳市速腾聚创科技有限公司 | Pilotless automobile system and automobile |
| CN107272683A (en) * | 2017-06-19 | 2017-10-20 | 中国科学院自动化研究所 | Parallel intelligent vehicle control based on ACP methods |
| CN207541498U (en) * | 2017-09-22 | 2018-06-26 | 西华师范大学 | A kind of Unmanned Systems |
| CN107992091A (en) * | 2017-10-31 | 2018-05-04 | 深圳市博鑫创科科技有限公司 | A kind of balance car follower method and system based on signal strength |
| CN108153311A (en) * | 2017-12-22 | 2018-06-12 | 武汉理工大学 | The intelligence control system and control method formed into columns towards unmanned boat |
| CN108225364A (en) * | 2018-01-04 | 2018-06-29 | 吉林大学 | A kind of pilotless automobile driving task decision system and method |
Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109618136A (en) * | 2018-12-14 | 2019-04-12 | 北京汽车集团有限公司 | Vehicle management system and method |
| CN109901170A (en) * | 2019-03-21 | 2019-06-18 | 西安交通大学 | A kind of intelligent transportation detection system and method based on radar block array |
| CN109921883A (en) * | 2019-04-12 | 2019-06-21 | 成都宇俊盛科技有限公司 | Full-automatic unmanned driving's rail vehicle communication system of serverless backup data link |
| CN110377027A (en) * | 2019-06-04 | 2019-10-25 | 深圳市速腾聚创科技有限公司 | Unmanned cognitive method, system, device and storage medium |
| CN111583693A (en) * | 2020-05-07 | 2020-08-25 | 中国农业大学 | Intelligent traffic cooperative operation system for urban road and intelligent vehicle control method |
| CN111583693B (en) * | 2020-05-07 | 2021-06-15 | 中国农业大学 | Intelligent traffic cooperative operation system for urban road and intelligent vehicle control method |
| CN113330497A (en) * | 2020-06-05 | 2021-08-31 | 曹庆恒 | Automatic driving method and device based on intelligent traffic system and intelligent traffic system |
| WO2021244655A1 (en) * | 2020-06-05 | 2021-12-09 | 曹庆恒 | Intelligent-transportation-system-based autonomous driving method, apparatus and system for transportation vehicle |
| CN113993761A (en) * | 2020-06-05 | 2022-01-28 | 曹庆恒 | Automatic vehicle driving method, device and system based on intelligent transportation system |
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