CN103632558A - Bionic swarm intelligence-based real-time positioning navigation and motion control method and system for moving vehicle - Google Patents

Bionic swarm intelligence-based real-time positioning navigation and motion control method and system for moving vehicle Download PDF

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CN103632558A
CN103632558A CN201310577959.7A CN201310577959A CN103632558A CN 103632558 A CN103632558 A CN 103632558A CN 201310577959 A CN201310577959 A CN 201310577959A CN 103632558 A CN103632558 A CN 103632558A
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曲仕茹
来磊
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Northwestern Polytechnical University
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Abstract

本发明公开了一种基于仿生群体智能的移动车辆实时定位导航、运动控制方法,用于解决现有移动车辆实时定位导航、运动控制方法可靠性较低的技术问题。技术方案是首先选取复杂道路中已知坐标的车辆和信息节点作为定位参考节点,将求解定位方程组问题转化为极值优化问题,并采用仿生蜂群算法求解定位坐标。对于多车辆间行驶的控制,通过建立生物群体行为建立仿生群体运动模型控制车辆间的运动,提高了移动车辆实时定位导航、运动控制的可控性。基于仿生群体智能的移动车辆实时定位导航、运动控制系统由车载控制终端模块、道路信息节点模块和道路交通控制中心模块组成。三个模块协同工作,实现了移动车辆的实时定位导航和运动控制。

Figure 201310577959

The invention discloses a bionic swarm intelligence-based mobile vehicle real-time positioning navigation and motion control method, which is used to solve the technical problem of low reliability of the existing mobile vehicle real-time positioning navigation and motion control methods. The technical solution is to firstly select vehicles and information nodes with known coordinates in complex roads as positioning reference nodes, transform the problem of solving positioning equations into an extreme value optimization problem, and use the bionic bee colony algorithm to solve the positioning coordinates. For the control of driving among multiple vehicles, the bionic group motion model is established to control the movement between vehicles by establishing the behavior of biological groups, which improves the controllability of real-time positioning, navigation and motion control of moving vehicles. The real-time positioning navigation and motion control system of mobile vehicles based on bionic swarm intelligence consists of a vehicle control terminal module, a road information node module and a road traffic control center module. The three modules work together to realize the real-time positioning navigation and motion control of the moving vehicle.

Figure 201310577959

Description

The real-time location navigation of moving vehicle, motion control method and system based on bionical swarm intelligence
Technical field
The present invention relates to the real-time location navigation of a kind of moving vehicle based on bionical swarm intelligence, motion control method, also relate to the real-time location navigation of a kind of moving vehicle based on bionical swarm intelligence, kinetic control system.
Background technology
Vehicle automatic positioning technology is the gordian technique that in intelligent transportation system, various fields all relates to.At present, the vehicle positioning technology of main practical application is mainly GPS location, and the combined orientation technology based on GPS.
Document 1 " patent announcement number is the Chinese utility model patent of CN201741289U " discloses a kind of vehicle locating device, and this locating device is mainly that GPS module has been installed, and vehicle is located it in real time by receiving gps signal.
Document 2 " Li Guifang; the vehicle GPS/DR integrated navigation research based on UPF algorithm; < < science and technology and engineering > > 2012.11, p8143-8146. " discloses the Combinated navigation method of a kind of GPS and DR fusion.The method is usingd positioning signal that current statistical model obtains as the state equation of system, the GPS device of vehicle mounting of usining as the measuring value of system, and vehicle is located in real time.
In disclosed vehicle positioning method, its essence is to adopt to receive the gps satellite navigate mode that in space, a plurality of satellite-signals position above, is requisite ingredient in its positioning system from the satellite-signal in space, high-altitude, and its defect is:
(1) there is the susceptible problem of reliability in gps signal, is subject to the interference of external environment larger, and the environment such as the skyscraper in city, tunnel all can affect accuracy and the reliability of vehicle location; The satellite-signal transmission of long distance is very easily subject to the impact of physical environment and artificial interference, and while sailing long tunnel into as vehicle, dropout can cause the temporary transient inefficacy of location; Satellite became striking target of enemy and also can cause positioning system forever to paralyse wartime.
(2) vehicle only obtains the position coordinates of self, and do not have to consider and other neighbours' vehicles between position relationship, thereby the coordinating and unifying of travelling between lower shortage vehicle colony at the crowded road environment of complexity, make running efficiency and the deterioration of safety of vehicle in road.
As can be seen from the above the locating information that open source literature is difficult to provide accurately, reliability is high, also lacks the function of coordinating a plurality of vehicle movements simultaneously.
Summary of the invention
In order to overcome the lower deficiency of existing vehicle GPS and integrated positioning system thereof reliability in urban environment, the invention provides the real-time location navigation of a kind of moving vehicle based on bionical swarm intelligence, motion control method.First the method chooses the vehicle of known coordinate in complicated road and information node as position reference node, by the poor positioning equation group of setting up of the relative distance between measuring vehicle and reference mode, to solve again this positioning equation group problem and be converted into extremal optimization problem, and adopt bionical ant colony algorithm to solve the elements of a fix.For travel control method between many vehicles, by setting up biotic population behavior, set up the motion between bionical group movement model control vehicle, can improve the controllability of the real-time location navigation of moving vehicle, motion control.
The present invention also provides the real-time location navigation of a kind of moving vehicle based on bionical swarm intelligence, kinetic control system.This system is comprised of vehicle-mounted control terminal module, road information node module and road traffic control center module.Three module cooperative work, can realize the reliable location in real time of moving vehicle, and the control of travelling of the colony between vehicle.
The technical solution adopted for the present invention to solve the technical problems is: the real-time location navigation of a kind of moving vehicle based on bionical swarm intelligence, motion control method, be characterized in comprising the following steps:
Step 1: at moment t, vehicle vehicle adjacent thereto and information node form cordless communication network, and the vehicle of each known location coordinate sends the position coordinates of self in the mode of broadcast transmission by wireless network.
Step 2: vehicle to be positioned receives the location coordinate information of neighbours' vehicle and information node transmission is passed through the relative distance d between electromagnetic wave signal principle time of arrival measurement self and neighbours' vehicle, information node simultaneously i
d i=ct i,i=1,2,…,n (1)
In formula, c is the aerial velocity of propagation of electromagnetic wave signal, t ifor the travel-time of electromagnetic wave signal from vehicle to be positioned to neighbours' vehicle i, n is the number that receives signal.
Choose d ibe worth minimum m vehicle or information node as the position reference node of vehicle to be positioned.
Step 3: the relative distance d between vehicle basis to be positioned and reference mode iset up positioning equation with the position coordinates of reference mode, its positioning equation is expressed as
( x 1 t - x t ) 2 + ( y 1 t - y t ) 2 - ( x 2 t - x t ) 2 + ( y 2 t - y t ) 2 = d 2 - d 1 . . . ( x 1 t - x t ) 2 + ( y 1 t - y t ) 2 - ( x mt - x t ) 2 + ( y mt - y t ) 2 = d m - d 1 - - - ( 2 )
In formula, (x t, y t) be that vehicle to be positioned is at t moment coordinate, (x it, y it) be that reference mode is at t moment position coordinates.
Step 4: the positioning equation of formula (2) is converted into minimizing problem, and its expression formula is
f 1 = [ ( x 1 t - x t ) 2 + ( y 1 t - y t ) 2 - ( x 2 t - x t ) 2 + ( y 2 t - y t ) 2 ] 2 - ( d 2 - d 1 ) 2 = 0 . . . f m = [ ( x 1 t - x t ) 2 + ( y 1 t - y t ) 2 - ( x mt - x t ) 2 + ( y mt - y t ) 2 ] 2 - ( d m - d 1 ) 2 = 0 - - - ( 3 )
f 1 2 + f 2 2 + . . . + f m 2 = 0 - - - ( 4 )
For formula (4) minimal value equation, adopt artificial bee colony intelligent computation method to solve it, the minimum value (x solving t, y t) be the position coordinates of vehicle to be positioned.
Step 5: vehicle to be positioned, in its radius R field, is chosen field in-group neighbours' vehicle, and selection standard is
N it={i:[x t-x it] 2+[y t-y it] 2+[z t-z it] 2≤R 2} (5)
In formula, z ifor the vehicle i positional value on axle in the vertical direction.
Step 6: the direction of motion of vehicle k is the mean value of its neighbours' direction of vehicle movement.
&alpha; kt = 1 n kt - 1 &Sigma; i &Element; Nt &alpha; it - 1 &beta; kt = 1 n kt - 1 &Sigma; i &Element; Nt &beta; it - 1 &gamma; kt = 1 n kt - 1 &Sigma; i &Element; Nt &gamma; it - 1 - - - ( 6 )
In formula, α it, β it, γ itfor vehicle is at the t direction of motion along three axes constantly, n tfor t moment neighbours' vehicle number.
The location formula of vehicle k is:
x kt = x kt - 1 + v k cos &alpha; kt y kt = y kt - 1 + v k cos &beta; kt z kt = z kt - 1 + v k cos &gamma; kt - - - ( 7 )
In formula, v ktravel speed for vehicle k.
Each vehicle is constantly adjusted the position of oneself according to the position equation of formula (7).
The real-time location navigation of moving vehicle based on bionical swarm intelligence, a kinetic control system, be characterized in: comprise vehicle-mounted control terminal module, road information node module and road traffic control center module, transmission of signal between two between three modules.
Vehicle-mounted control terminal module comprises wireless communication module, data processing module, path planning module, data acquisition module, vehicle control module, memory module and display module.Wireless communication module and road information node, other vehicle communications, with reception, transmission information, obtain vehicle location and control required parameter.Data processing module obtains the required parameter in location from wireless communication module, and locating information car-mounted terminal node being received according to algorithm is converted into the accurate location coordinate of vehicle.Data acquisition module receives the signal of measuring from vehicle self speed pickup, rotary angle transmitter, acceleration transducer, and is translated into numerical information to obtain the motion state of self.Path planning module receives the signal from wireless communication module, data acquisition module and data processing module, obtain the position coordinates of Real-time Road environment and vehicle its data and vehicle self, to next driving path constantly of vehicle carry out reasonably, optimization plans.The travel route that vehicle control module RX path planning module is planned, control vehicle speed, turn to and acceleration.Memory module and display module receive and real-time position and the optimal path information showing from data processing module and path planning module.
Road information node module comprises wireless communication module, data processing module and sensor assembly.Sensor assembly is vehicle fleet size, wagon flow speed and visibility information in the road environment of measuring, with analog signal transmission to data processing module.The simulating signal of data processing module autobiography sensor module in future is processed and is translated into the discernible digital signal of processor.Wireless communication module sends to road traffic control center module by the node location from data processing module, road traffic and vehicle speed signal.
Road traffic control center module comprises wireless communication module, data processing module and database module.Wireless communication module is communicated by letter with vehicle-mounted control terminal module with road information node module, receives, sends information of vehicles, terrain vehicle stream information and road geographic information.Data processing module receives the information from wireless communication module, and it is carried out after pre-service, its appointment being stored in database module, need to from database, extract relevant road geographic information according to vehicle-mounted control terminal module simultaneously.The information of vehicle flowrate of database module stores road and the road geographic information for navigating.
The invention has the beneficial effects as follows: the real-time location navigation of moving vehicle based on bionical swarm intelligence, motion control method, first choose the vehicle of known coordinate in complicated road and information node as position reference node, by the poor positioning equation group of setting up of the relative distance between measuring vehicle and reference mode, to solve again this positioning equation group problem and be converted into extremal optimization problem, and adopt bionical ant colony algorithm to solve the elements of a fix.For travel control method between many vehicles, by setting up biotic population behavior, set up bionical group movement model and control the motion between vehicle, improved the controllability of the real-time location navigation of moving vehicle, motion control.The real-time location navigation of moving vehicle based on bionical swarm intelligence, kinetic control system.This system is comprised of vehicle-mounted control terminal module, road information node module and road traffic control center module.Three module cooperative work, have realized the reliable location in real time of moving vehicle, and the control of travelling of the colony between vehicle.
Below in conjunction with the drawings and specific embodiments, describe the present invention in detail.
Accompanying drawing explanation
Fig. 1 is the real-time location navigation of moving vehicle that the present invention is based on bionical swarm intelligence, the process flow diagram of motion control method.
Fig. 2 is the real-time location navigation of moving vehicle that the present invention is based on bionical swarm intelligence, the block scheme of kinetic control system.
Fig. 3 is that in Fig. 2, vehicle-mounted control terminal module forms structural drawing.
Fig. 4 is that in Fig. 2, road information node module forms structural drawing.
Fig. 5 is that in Fig. 2, road traffic control center module forms structural drawing.
Fig. 6 is the schematic diagram of the first-selected embodiment of the present invention.
Embodiment
Following examples are with reference to Fig. 1-6.
Embodiment 1.The present embodiment is described the real-time location navigation of moving vehicle based on bionical swarm intelligence, the step of motion control method in detail:
Step 1: at moment t, vehicle V to be positioned vehicle V1 adjacent thereto, V2, V3, V4, V5, V6 and information node N1 form cordless communication network, the coordinate of vehicle V1, V2, V3, V4, V5, V6 and information node N1 is known, and the position coordinates that sends self in the mode of broadcast transmission by wireless network is to vehicle V.
Step 2: vehicle V to be positioned receives the location coordinate information that neighbours' vehicle V1, V2, V3, V4, V5, V6 and information node N1 send is passed through the distance d between electromagnetic wave signal principle time of arrival measurement self and neighbours' vehicle V1, V2, V3, V4, V5, V6, information node N1 simultaneously v1, d v2, d v3, d v4, d v5, d v6, d n1.
d i=ct i,i=v1,v2,v3,v4,v5,v6,N1 (1)
In formula, c is the aerial velocity of propagation of electromagnetic wave signal, t ifor electromagnetic wave signal is from vehicle to be positioned to neighbours' vehicle or the travel-time of information node i, n is the number that receives signal.
From d v1, d v2, d v3, d v4, d v5, d v6, d n1the m=4 of a middle selected value minimum vehicle or information node are as the position reference node of vehicle to be positioned.In this example, choose V1, V2, V4, N1 as location reference point.
Step 3: according to the relative distance d between vehicle V to be positioned and reference point V1, V2, V4, N1 v1, d v2, d v4, d n1position coordinates (x with reference point v1, y v1), (x v2, y v2), (x v4, y v4), (x n1, y n1) set up positioning equation:
( x v 2 t - x t ) 2 + ( y v 2 t - y t ) 2 - ( x v 1 t - x t ) 2 + ( y v 1 t - y t ) 2 = d v 2 - d v 1 ( x v 3 t - x t ) 2 + ( y v 3 t - y t ) 2 - ( x v 1 t - x t ) 2 + ( y v 1 t - y t ) 2 = d v 3 - d v 1 ( x v 4 t - x t ) 2 + ( y v 4 t - y t ) 2 - ( x v 1 t - x t ) 2 + ( y v 1 t - y t ) 2 = d v 4 - d v 1 ( x N 1 t - x t ) 2 + ( y N 1 t - y t ) 2 - ( x v 1 t - x t ) 2 + ( y v 1 t - y t ) 2 = d N 1 - d v 1 - - - ( 2 )
In formula, (x t, y t) be that vehicle V to be positioned is at t moment coordinate.
Step 4: the positioning equation of formula (2) is converted into minimizing problem:
f 1 = [ ( x v 2 t - x t ) 2 + ( y v 2 t - y t ) 2 - ( x v 1 t - x t ) 2 + ( y v 1 t - y t ) 2 ] 2 - ( d v 2 - d v 1 ) 2 = 0 f 2 = [ ( x v 3 t - x t ) 2 + ( y v 3 t - y t ) 2 - ( x v 1 t - x t ) 2 + ( y v 1 t - y t ) 2 ] 2 - ( d v 3 - d v 1 ) 2 = 0 f 3 = [ ( x v 4 t - x t ) 2 + ( y v 4 t - y t ) 2 - ( x v 1 t - x t ) 2 + ( y v 1 t - y t ) 2 ] 2 - ( d v 4 - d v 1 ) 2 = 0 f 4 = [ ( x N 1 t - x t ) 2 + ( y N 1 t - y t ) 2 - ( x v 1 t - x t ) 2 + ( y v 1 t - y t ) 2 ] 2 - ( d N 1 - d v 1 ) 2 = 0 - - - ( 3 )
f 1 2 + f 2 2 + . . . + f m 2 = 0 - - - ( 4 )
For formula (4) minimal value equation, adopt artificial bee colony intelligent computation method to solve it, the minimum value (x solving t, y t) be the position coordinates of vehicle to be positioned.
Step 5: vehicle to be positioned, in its field, radius R=100, is chosen field in-group neighbours' vehicle, and its selection standard is
N it={i:[x t-x it] 2+[y t-y it] 2+[z t-z it] 2≤R 2} (5)
In formula, z ifor the vehicle i coordinate figure on axle in the vertical direction.Establish vehicle herein in same level, z ibe worth identical.
Step 6: the direction of motion of vehicle k is the mean value of its neighbours' direction of vehicle movement.
&alpha; kt = 1 n kt - 1 &Sigma; i &Element; Nt &alpha; it - 1 &beta; kt = 1 n kt - 1 &Sigma; i &Element; Nt &beta; it - 1 &gamma; kt = 1 n kt - 1 &Sigma; i &Element; Nt &gamma; it - 1 , i = v 1 , v 2 , v 3 , v 4 , v 5 , v 6 - - - ( 6 )
In formula, α it, β it, γ itfor vehicle is at t direction of motion constantly, n tfor t moment neighbours' vehicle number.
The location formula of vehicle k is:
x kt = x kt - 1 + v k cos &alpha; kt y kt = y kt - 1 + v k cos &beta; kt z kt = z kt - 1 + v k cos &gamma; kt - - - ( 7 )
In formula, v ktravel speed for vehicle k.
Each vehicle is constantly adjusted the position of oneself according to the position equation of formula (7).
Embodiment 2.The present embodiment is described the real-time location navigation of moving vehicle based on bionical swarm intelligence, the structure of kinetic control system in detail:
The unified TMS320F2808 chip that adopts of data processing module in structure and path planning module; Wireless communication module adopts NRF905 chip; Memory module adopts W25X16AVSIG chip; Sensor assembly comprises ccd sensor TSL1401CL, accelerometer LSM303DLHC; Vehicle control module adopts MC9S12XS128MAA chip; Display module is LCD1602 display screen.
In the present invention, vehicle control terminal module comprises: wireless communication module, data processing module, data acquisition module, vehicle control module, path planning module, memory module and display module.Data processing module obtains the required parameter in location from wireless communication module, sets up positioning equation group, thereby and adopts ant colony algorithm positioning equation group to be solved to the position coordinates that obtains vehicle to be positioned.Data acquisition module receives the signal of measuring from vehicle self speed pickup, rotary angle transmitter, acceleration transducer, and is translated into digital quantity to obtain the motion state of self.Path planning module receives the signal from wireless communication module, data acquisition module, data processing module, to obtain the position coordinates of Real-time Road environment and vehicle its data and vehicle self, to next driving path constantly of vehicle carry out reasonably, optimization plans.The travel route that vehicle control module RX path planning module is planned, control vehicle speed, turn to and acceleration.Memory module and display module receive and real-time position and the optimal path information showing from data processing module and path planning module.
Vehicle control terminal module information flows to: vehicle in the process of moving, wireless communication module in vehicle-mounted control terminal is neighbours' vehicle and road information node transmission positioning request signal towards periphery, reception is from the positional information of neighbours' vehicle and road information node, and this information is sent to data processing module; Data acquisition module is measured locating required relative information, and is sent to data processing module; Data processing module sends respectively the positional information calculating to path planning module, vehicle control module, memory module and display module; Path planning module sends by data processing module the vehicle route of having planned to vehicle control module.
The bulk information node of road information node in being dispersed in road and around road forms, and each node is comprised of wireless communication module, data processing module and sensor assembly.Sensor assembly can measurement road environment in the road information such as vehicle fleet size, wagon flow speed and visibility, and by the analog signal transmission of measuring to data processing module.The simulating signal of data processing module autobiography sensor module in future is processed and is translated into digital signal.Wireless communication module sends to vehicle-mounted control terminal, road traffic control center by signals such as the node location from data processing module, road traffic, the speed of a motor vehicle.
Road information node module information flow direction is: sensor assembly is sent to data processing module by the relevant information measuring, and data processing module sends to wireless communication module after metrical information is processed.
Road traffic control center module is comprised of wireless communication module, data processing module and database module.Wireless communication module is communicated by letter with vehicle-mounted control terminal module with road information node module, receives, sends information of vehicles, terrain vehicle stream information and road geographic information.Data processing module receives the relevant information from wireless communication module, and it is carried out after pre-service, its appointment being stored in database module, need to from database, extract relevant road geographic information according to vehicle-mounted control terminal module simultaneously.The information of vehicle flowrate of database module stores road and the road geographic information for navigating.
Road traffic control center module information flow direction is: wireless communication module sends to data processing module by the relevant information receiving, and information is specified and arranged to store in database module by data processing module after treatment; Data memory module also can send localized road geography information to data processing module simultaneously, and sends to required vehicle by wireless communication module.
The information flow direction of whole system is: in the process of moving, vehicle-mounted control terminal receives the positional information from neighbours' vehicle and road information node to vehicle, receives the localized road geography information from road traffic control center module simultaneously.In addition, the status information that vehicle-mounted control terminal also can send self is to road information node module and road traffic control center module.

Claims (2)

1.一种基于仿生群体智能的移动车辆实时定位导航、运动控制方法,其特征在于包括以下步骤:1. A mobile vehicle real-time positioning navigation, motion control method based on bionic swarm intelligence, is characterized in that comprising the following steps: 步骤1:在时刻t,车辆与其邻近的车辆和信息节点组成无线通信网络,每个已知位置坐标的车辆通过无线网络以广播发送的方式发送自身的位置坐标;Step 1: At time t, the vehicle forms a wireless communication network with its adjacent vehicles and information nodes, and each vehicle with known position coordinates sends its own position coordinates by broadcasting through the wireless network; 步骤2:待定位车辆接收邻居车辆和信息节点发送的位置坐标信息,同时通过电磁波信号到达时间原理测量自身与邻居车辆、信息节点间的相对距离di Step 2: The vehicle to be positioned receives the location coordinate information sent by the neighbor vehicle and the information node, and measures the relative distance d i between itself and the neighbor vehicle and the information node through the arrival time principle of the electromagnetic wave signal di=cti,i=1,2,…,n    (1)d i = ct i , i = 1, 2, ..., n (1) 式中,c为电磁波信号在空气中的传播速度,ti为电磁波信号从待定位车辆到邻居车辆i的传播时间,n为接收到信号的个数;In the formula, c is the propagation speed of the electromagnetic wave signal in the air, t i is the propagation time of the electromagnetic wave signal from the vehicle to be positioned to the neighbor vehicle i, and n is the number of received signals; 选取di值最小的m个车辆或信息节点作为待定位车辆的定位参考节点;Select m vehicles or information nodes with the smallest value of d i as the positioning reference nodes of the vehicle to be positioned; 步骤3:待定位车辆根据与参考节点间的相对距离di和参考节点的位置坐标建立定位方程,其定位方程表示为Step 3: The vehicle to be positioned establishes a positioning equation according to the relative distance d i from the reference node and the position coordinates of the reference node, and the positioning equation is expressed as (( xx 11 tt -- xx tt )) 22 ++ (( ythe y 11 tt -- ythe y tt )) 22 -- (( xx 22 tt -- xx tt )) 22 ++ (( ythe y 22 tt -- ythe y tt )) 22 == dd 22 -- dd 11 .. .. .. (( xx 11 tt -- xx tt )) 22 ++ (( ythe y 11 tt -- ythe y tt )) 22 -- (( xx mtmt -- xx tt )) 22 ++ (( ythe y mtmt -- ythe y tt )) 22 == dd mm -- dd 11 -- -- -- (( 22 )) 式中,(xt,yt)为待定位车辆在t时刻坐标,(xit,yit)为参考节点在t时刻位置坐标;In the formula, (x t , y t ) is the coordinates of the vehicle to be positioned at time t, and (x it , y it ) is the position coordinates of the reference node at time t; 步骤4:将式(2)的定位方程转化为求极小值问题,其表达式为Step 4: Transform the positioning equation of formula (2) into a minimum value problem, and its expression is ff 11 == [[ (( xx 11 tt -- xx tt )) 22 ++ (( ythe y 11 tt -- ythe y tt )) 22 -- (( xx 22 tt -- xx tt )) 22 ++ (( ythe y 22 tt -- ythe y tt )) 22 ]] 22 -- (( dd 22 -- dd 11 )) 22 == 00 .. .. .. ff mm == [[ (( xx 11 tt -- xx tt )) 22 ++ (( ythe y 11 tt -- ythe y tt )) 22 -- (( xx mtmt -- xx tt )) 22 ++ (( ythe y mtmt -- ythe y tt )) 22 ]] 22 -- (( dd mm -- dd 11 )) 22 == 00 -- -- -- (( 33 )) ff 11 22 ++ ff 22 22 ++ .. .. .. ++ ff mm 22 == 00 -- -- -- (( 44 )) 对于式(4)极小值方程,采用人工蜂群智能计算方法对其求解,求解的最小值(xt,yt)即为待定位车辆的位置坐标;For the minimum value equation of formula (4), the artificial swarm intelligence calculation method is used to solve it, and the minimum value (x t , y t ) of the solution is the position coordinate of the vehicle to be positioned; 步骤5:待定位车辆在其半径R领域内,选取领域内群体邻居车辆,选取标准为Step 5: The vehicle to be positioned is within its radius R field, select group neighbor vehicles in the field, and the selection standard is Nit={i:[xt-xit]2+[yt-yit]2+[zt-zit]2≤R2}    (5)N it ={i:[x t -x it ] 2 +[y t -y it ] 2 +[z t -z it ] 2 ≤R 2 } (5) 式中,zi为车辆i在垂直方向轴上的位置值;In the formula, z i is the position value of vehicle i on the vertical axis; 步骤6:车辆k的运动方向为其邻居车辆运动方向的平均值;Step 6: The moving direction of vehicle k is the average value of the moving directions of its neighbor vehicles; &alpha;&alpha; ktkt == 11 nno ktkt -- 11 &Sigma;&Sigma; ii &Element;&Element; NtNt &alpha;&alpha; itit -- 11 &beta;&beta; ktkt == 11 nno ktkt -- 11 &Sigma;&Sigma; ii &Element;&Element; NtNt &beta;&beta; itit -- 11 &gamma;&gamma; ktkt == 11 nno ktkt -- 11 &Sigma;&Sigma; ii &Element;&Element; NtNt &gamma;&gamma; itit -- 11 -- -- -- (( 66 )) 式中,αit、βit、γit为车辆在t时刻的沿三坐标轴的运动方向,nt为t时刻邻居车辆个数;In the formula, α it , β it , γ it are the moving direction of the vehicle along the three coordinate axes at time t, n t is the number of neighbor vehicles at time t; 则车辆k的位置公式为:Then the position formula of vehicle k is: xx ktkt == xx ktkt -- 11 ++ vv kk coscos &alpha;&alpha; ktkt ythe y ktkt == ythe y ktkt -- 11 ++ vv kk coscos &beta;&beta; ktkt zz ktkt == zz ktkt -- 11 ++ vv kk coscos &gamma;&gamma; ktkt -- -- -- (( 77 )) 式中,vk为车辆k的行驶速度;In the formula, v k is the driving speed of vehicle k; 每个车辆根据式(7)的位置方程不断调整自己的位置。Each vehicle constantly adjusts its position according to the position equation of Equation (7). 2.一种基于仿生群体智能的移动车辆实时定位导航、运动控制系统,其特征在于:包括车载控制终端模块、道路信息节点模块和道路交通控制中心模块,三个模块之间两两传递信号;2. A mobile vehicle real-time positioning navigation and motion control system based on bionic swarm intelligence, characterized in that: it includes a vehicle-mounted control terminal module, a road information node module and a road traffic control center module, and the three modules transmit signals in pairs; 车载控制终端模块包括无线通信模块、数据处理模块、路径规划模块、数据采集模块、车辆控制模块、存储模块和显示模块;无线通信模块与道路信息节点、其他车辆通信以接收、发送信息,获得车辆定位与控制所需的参量;数据处理模块从无线通信模块处获得定位所需参量,并根据算法将车载终端节点接收的定位信息转化为车辆的准确位置坐标;数据采集模块接收来自车辆自身速度传感器、转角传感器、加速度传感器测量的信号,并将其转化为数字信息以获取自身的运动状态;路径规划模块接收来自无线通信模块、数据采集模块和数据处理模块的信号,获取实时道路环境和车辆自身数据、及车辆自身的位置坐标,对车辆的下一时刻的行驶路径进行合理的、最优化规划;车辆控制模块接收路径规划模块规划好的行驶路线,控制车辆的速度、转向及加速度;存储模块和显示模块接收并实时显示来自数据处理模块和路径规划模块的位置和最优路径信息;The vehicle control terminal module includes a wireless communication module, a data processing module, a path planning module, a data acquisition module, a vehicle control module, a storage module and a display module; the wireless communication module communicates with road information nodes and other vehicles to receive and send information, and obtain vehicle The parameters required for positioning and control; the data processing module obtains the parameters required for positioning from the wireless communication module, and converts the positioning information received by the vehicle terminal node into the exact position coordinates of the vehicle according to the algorithm; the data acquisition module receives information from the vehicle's own speed sensor , rotation angle sensor, and acceleration sensor, and convert it into digital information to obtain its own motion state; the path planning module receives signals from the wireless communication module, data acquisition module and data processing module to obtain real-time road environment and the vehicle itself Data, and the position coordinates of the vehicle itself, make reasonable and optimal planning for the driving path of the vehicle at the next moment; the vehicle control module receives the driving route planned by the path planning module, and controls the speed, steering and acceleration of the vehicle; the storage module The display module receives and displays the position and optimal path information from the data processing module and the path planning module in real time; 道路信息节点模块包括无线通信模块、数据处理模块和传感器模块;传感器模块将测量的道路环境中车辆数量、车流速度和能见度信息,以模拟信号传输给数据处理模块;数据处理模块将来自传感器模块的模拟信号进行处理将其转化为处理器能够识别的数字信号;无线通信模块将来自数据处理模块的节点位置、道路车流量和车速信号发送给道路交通控制中心模块;The road information node module includes a wireless communication module, a data processing module and a sensor module; the sensor module transmits the measured vehicle quantity, traffic speed and visibility information in the road environment to the data processing module as an analog signal; the data processing module transmits the information from the sensor module The analog signal is processed to convert it into a digital signal that the processor can recognize; the wireless communication module sends the node position, road traffic volume and vehicle speed signals from the data processing module to the road traffic control center module; 道路交通控制中心模块包括无线通信模块、数据处理模块和数据库模块;无线通信模块与道路信息节点模块和车载控制终端模块通信,接收、发送车辆信息、道路车流信息和道路地理信息;数据处理模块接收来自无线通信模块的信息,对其进行预处理后将其指定存贮于数据库模块中,同时根据车载控制终端模块的需要从数据库中提取相关的道路地理信息;数据库模块存储道路的车流量信息和用于导航的道路地理信息。The road traffic control center module includes a wireless communication module, a data processing module and a database module; the wireless communication module communicates with the road information node module and the vehicle control terminal module to receive and send vehicle information, road traffic flow information and road geographic information; the data processing module receives The information from the wireless communication module is preprocessed and stored in the database module, and at the same time, the relevant road geographic information is extracted from the database according to the needs of the vehicle control terminal module; the database module stores the traffic flow information and Road geographic information for navigation.
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