CN103632558A - Bionic swarm intelligence-based real-time positioning navigation and motion control method and system for moving vehicle - Google Patents
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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。
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.
Description
技术领域technical field
本发明涉及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,还涉及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。The invention relates to a method for real-time positioning, navigation, and motion control of a mobile vehicle based on bionic swarm intelligence, and also relates to a real-time positioning, navigation, and motion control system for a mobile vehicle based on bionic swarm intelligence.
背景技术Background technique
车辆自动定位技术是智能交通系统中众多领域都涉及到的一项关键技术。目前,主要实际应用的车辆定位技术主要是GPS定位,及基于GPS的组合定位技术。Vehicle automatic positioning technology is a key technology involved in many fields of intelligent transportation system. At present, the main practical application of vehicle positioning technology is mainly GPS positioning, and combined positioning technology based on GPS.
文献1“专利公告号是CN201741289U的中国实用新型专利”公开了一种车辆定位装置,该定位装置主要是安装了GPS模块,车辆通过接收GPS信号对其进行实时定位。Document 1 "Chinese utility model patent whose patent announcement number is CN201741289U" discloses a vehicle positioning device. The positioning device is mainly equipped with a GPS module, and the vehicle performs real-time positioning by receiving GPS signals.
文献2“李桂芳,基于UPF算法的车辆GPS/DR组合导航研究,《科学技术与工程》2012.11,p8143-8146.”公开了一种GPS与DR融合的组合导航方法。该方法以当前统计模型作为系统的状态方程、以车辆装备的GPS装置得到的定位信号作为系统的量测值,对车辆进行实时定位。Document 2 "Li Guifang, Research on Vehicle GPS/DR Integrated Navigation Based on UPF Algorithm, "Science Technology and Engineering" 2012.11, p8143-8146." discloses an integrated navigation method of GPS and DR fusion. The method uses the current statistical model as the state equation of the system and the positioning signal obtained by the GPS device equipped on the vehicle as the measured value of the system to locate the vehicle in real time.
以上公开的车辆定位方法中,其实质是采用接收空间中多个卫星信号进行定位的GPS卫星导航方式,来自高空空间中的卫星信号是其定位系统中必不可少的组成部分,其缺陷在于:In the vehicle positioning method disclosed above, its essence is to adopt the GPS satellite navigation method for positioning by receiving multiple satellite signals in the space. The satellite signals from the high-altitude space are an indispensable part of its positioning system, and its defects are:
(1)GPS信号存在可靠性易受影响的问题,受外界环境的干扰较大,城市中的高层建筑、隧道等环境都会影响车辆定位的准确性和可靠性;长距离的卫星信号传输极易受自然环境及人为干扰的影响,如车辆驶入长隧道时,信号丢失会造成定位的暂时失效;战时卫星成为敌方的打击目标也会造成定位系统永久瘫痪。(1) The reliability of the GPS signal is easily affected, and it is greatly disturbed by the external environment. The environment such as high-rise buildings and tunnels in the city will affect the accuracy and reliability of vehicle positioning; long-distance satellite signal transmission is extremely easy Affected by the natural environment and human interference, for example, when the vehicle enters a long tunnel, the signal loss will cause the temporary failure of positioning; the satellite becoming the target of the enemy in wartime will also cause the permanent paralysis of the positioning system.
(2)车辆只获得自身的位置坐标,而没有考虑与其他邻居车辆间的位置关系,因而在复杂拥挤道路环境行驶下缺乏车辆群体间的协调统一性,使得车辆在道路中的行驶效率和安全性变差。(2) The vehicle only obtains its own position coordinates, without considering the positional relationship with other neighboring vehicles. Therefore, it lacks coordination and unity among vehicle groups when driving in a complex and congested road environment, making the driving efficiency and safety of vehicles on the road Sexual deterioration.
从以上可以看出公开文献难以提供准确、可靠性高的定位信息,同时也缺少协调多个车辆运动的功能。It can be seen from the above that it is difficult for public documents to provide accurate and highly reliable positioning information, and it also lacks the function of coordinating the movement of multiple vehicles.
发明内容Contents of the invention
为了克服现有车辆GPS及其组合定位系统在城市环境中可靠性较低的不足,本发明提供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。该方法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,通过测量车辆与参考节点间的相对距离差建立定位方程组,再将求解此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。对于多车辆间行驶控制方法,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,可以提高移动车辆实时定位导航、运动控制的可控性。In order to overcome the low reliability of existing vehicle GPS and its combined positioning system in urban environments, the present invention provides a real-time positioning navigation and motion control method for mobile vehicles based on bionic swarm intelligence. This method first selects vehicles and information nodes with known coordinates in complex roads as positioning reference nodes, establishes a positioning equation set by measuring the relative distance difference between the vehicle and the reference node, and then transforms the problem of solving this positioning equation set into an extreme value optimization problem , and use the bionic bee colony algorithm to solve the positioning coordinates. For the multi-vehicle driving control method, the controllability of real-time positioning navigation and motion control of moving vehicles can be improved by establishing a bionic group motion model to control the motion between vehicles by establishing the behavior of biological groups.
本发明还提供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。该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,可实现移动车辆可靠实时定位,及车辆间的群体行驶控制。The invention also provides a real-time positioning navigation and motion control system for a mobile vehicle based on bionic swarm intelligence. The system consists of vehicle control terminal module, road information node module and road traffic control center module. The three modules work together to realize reliable real-time positioning of moving vehicles and group driving control among vehicles.
本发明解决其技术问题所采用的技术方案是: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,其特点是包括以下步骤:The technical solution adopted by the present invention to solve the technical problems is: a method for real-time positioning navigation and motion control of mobile vehicles based on bionic swarm intelligence, which is characterized in that it comprises 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 and its adjacent vehicles and information nodes form a wireless communication network, 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
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
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 bee colony intelligent 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 neighbors.
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 , and γ it are the moving direction of the vehicle along the three coordinate axes at time t, and 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:
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).
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,其特点是: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。A real-time positioning navigation and motion control system for mobile vehicles based on bionic swarm intelligence, which is characterized in that it includes a vehicle 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 parameters required for vehicle 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 accurate position coordinates of the vehicle according to the algorithm. The data acquisition module receives the signals measured by the vehicle's own speed sensor, rotation angle sensor, and acceleration sensor, and converts them 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, obtains the real-time road environment and the vehicle's own data, and the vehicle's own position coordinates, and makes a reasonable and optimized driving path for the vehicle at the next moment planning. 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 and the display module receive and display the position and optimal route information from the data processing module and the route 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可识别的数字信号。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 processes the analog signal from the sensor module and converts it into a digital signal recognizable by the processor. 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, preprocesses it and stores it in the database module, and extracts the relevant road geographic information from the database according to the needs of the vehicle control terminal module. The database module stores road traffic flow information and road geographic information for navigation.
本发明的有益效果是: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,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,通过测量车辆与参考节点间的相对距离差建立定位方程组,再将求解此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。对于多车辆间行驶控制方法,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。该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,实现了移动车辆可靠实时定位,及车辆间的群体行驶控制。The beneficial effects of the present invention are: the real-time positioning navigation and motion control method of mobile vehicles based on bionic swarm intelligence, first select vehicles and information nodes with known coordinates in complex roads as positioning reference nodes, and measure the relative distance between the vehicle and the reference nodes Then, the problem of solving the positioning equations is transformed into an extreme value optimization problem, and the positioning coordinates are solved by using the bionic bee colony algorithm. For the multi-vehicle driving control method, the bionic group motion model is established to control the motion between vehicles by establishing the behavior of biological groups, which improves the controllability of real-time positioning, navigation and motion control of moving vehicles. Real-time positioning navigation and motion control system for mobile vehicles based on bionic swarm intelligence. The system consists of vehicle control terminal module, road information node module and road traffic control center module. The three modules work together to realize reliable real-time positioning of moving vehicles and group driving control among vehicles.
以下结合附图和具体实施方式详细说明本发明。The present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments.
附图说明Description of drawings
图1是本发明基于仿生群体智能的移动车辆实时定位导航、运动控制方法的流程图。Fig. 1 is a flowchart of the real-time positioning navigation and motion control method of a mobile vehicle based on bionic swarm intelligence in the present invention.
图2是本发明基于仿生群体智能的移动车辆实时定位导航、运动控制系统的方框图。Fig. 2 is the block diagram of the mobile vehicle real-time positioning navigation and motion control system based on bionic swarm intelligence of the present invention.
图3是图2中车载控制终端模块组成结构图。Fig. 3 is a structural diagram of the vehicle-mounted control terminal module in Fig. 2 .
图4是图2中道路信息节点模块组成结构图。Fig. 4 is a structural diagram of the road information node module in Fig. 2 .
图5是图2中道路交通控制中心模块组成结构图。Fig. 5 is a structural diagram of the modules of the road traffic control center in Fig. 2 .
图6是本发明首选实施例的示意图。Figure 6 is a schematic diagram of a preferred embodiment of the present invention.
具体实施方式Detailed ways
以下实施例参照图1-6。The following embodiments refer to Figures 1-6.
实施例1。本实施例详细描述基于仿生群体智能的移动车辆实时定位导航、运动控制方法的步骤:Example 1. This embodiment describes in detail the steps of the mobile vehicle real-time positioning navigation and motion control method based on bionic swarm intelligence:
步骤1:在时刻t,待定位车辆V与其邻近的车辆V1、V2、V3、V4、V5、V6和信息节点N1组成无线通信网络,车辆V1、V2、V3、V4、V5、V6和信息节点N1的坐标已知,并通过无线网络以广播发送的方式发送自身的位置坐标给车辆V。Step 1: At time t, the vehicle V to be positioned and its adjacent vehicles V1, V2, V3, V4, V5, V6 and the information node N1 form a wireless communication network, and the vehicles V1, V2, V3, V4, V5, V6 and the information node The coordinates of N1 are known, and the location coordinates of N1 are broadcast to the vehicle V through the wireless network.
步骤2:待定位车辆V接收到邻居车辆V1、V2、V3、V4、V5、V6和信息节点N1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V1、V2、V3、V4、V5、V6、信息节点N1间的距离dv1、dv2、dv3、dv4、dv5、dv6、dN1。Step 2: The vehicle V to be positioned receives the location coordinate information sent by the neighbor vehicles V1, V2, V3, V4, V5, V6 and the information node N1, and at the same time measures the distance between itself and the neighbor vehicles V1, V2, V3, V4, V5, V6, and the distances d v1 , d v2 , d v3 , d v4 , d v5 , d v6 , d N1 between the information nodes N1.
di=cti,i=v1,v2,v3,v4,v5,v6,N1 (1)d i = ct i , i = v1, v2, v3, v4, v5, v6, N1 (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或信息节点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 or information node i, and n is the number of received signals.
从dv1、dv2、dv3、dv4、dv5、dv6、dN1中选取值最小的m=4个车辆或信息节点作为待定位车辆的定位参考节点。本实例中选取V1、V2、V4、N1作为定位参考点。Select m=4 vehicles or information nodes with the smallest value from d v1 , d v2 , d v3 , d v4 , d v5 , d v6 , d N1 as the positioning reference nodes of the vehicle to be positioned. In this example, V1, V2, V4, and N1 are selected as positioning reference points.
步骤3:根据待定位车辆V与参考点V1、V2、V4、N1间的相对距离dv1、dv2、dv4、dN1和参考点的位置坐标(xv1,yv1)、(xv2,yv2)、(xv4,yv4)、(xN1,yN1)建立定位方程:Step 3: According to the relative distances d v1 , d v2 , d v4 , d N1 between the vehicle V to be positioned and the reference points V1, V2 , V4 , N1 and the position coordinates (x v1 , y v1 ), (x v2 ,y v2 ), (x v4 ,y v4 ), (x N1 ,y N1 ) to establish positioning equations:
式中,(xt,yt)为待定位车辆V在t时刻坐标。In the formula, (x t , y t ) is the coordinates of the vehicle V to be positioned at time t.
步骤4:将式(2)的定位方程转化为求极小值问题:Step 4: Transform the positioning equation of formula (2) into a minimum value problem:
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 bee colony intelligent 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=100领域内,选取领域内群体邻居车辆,其选取标准为Step 5: The vehicle to be positioned is within its radius R = 100, select group neighbor vehicles in the area, and the selection criteria are
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在垂直方向轴上的坐标值。此处设车辆处于同一水平面内,则zi值相同。In the formula, z i is the coordinate value of vehicle i on the vertical axis. Here it is assumed that the vehicles are in the same horizontal plane, then the value of zi is the same.
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 of the moving directions of its neighbors.
式中,αit、βit、γit为车辆在t时刻的运动方向,nt为t时刻邻居车辆个数。In the formula, α it , β it , and γ it are the moving directions of vehicles at time t, and 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:
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).
实施例2。本实施例详细描述基于仿生群体智能的移动车辆实时定位导航、运动控制系统的结构:Example 2. This embodiment describes in detail the structure of the mobile vehicle real-time positioning navigation and motion control system based on bionic swarm intelligence:
结构中的数据处理模块和路径规划模块统一采用TMS320F2808芯片;无线通信模块采用NRF905芯片;存储模块采用W25X16AVSIG芯片;传感器模块包括CCD传感器TSL1401CL、加速度计LSM303DLHC;车辆控制模块采用MC9S12XS128MAA芯片;显示模块为LCD1602显示屏。The data processing module and path planning module in the structure adopt TMS320F2808 chip; the wireless communication module adopts NRF905 chip; the storage module adopts W25X16AVSIG chip; the sensor module includes CCD sensor TSL1401CL, accelerometer LSM303DLHC; the vehicle control module adopts MC9S12XS128MAA chip; the display module is LCD1602 display screen.
本发明中车辆控制终端模块包括:无线通信模块、数据处理模块、数据采集模块、车辆控制模块、路径规划模块、存储模块和显示模块。数据处理模块从无线通信模块处获得定位所需参量,建立定位方程组,并采用蜂群算法对定位方程组进行求解从而获得待定位车辆的位置坐标。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,并将其转化为数字量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、数据处理模块的信号,以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 in the present invention includes: a wireless communication module, a data processing module, a data acquisition module, a vehicle control module, a path planning module, a storage module and a display module. The data processing module obtains the parameters required for positioning from the wireless communication module, establishes a positioning equation group, and uses the bee colony algorithm to solve the positioning equation group to obtain the position coordinates of the vehicle to be positioned. The data acquisition module receives the signals measured by the vehicle's own speed sensor, rotation angle sensor, and acceleration sensor, and converts them into digital quantities 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 vehicle own data, as well as the vehicle's own position coordinates, and reasonably and optimize the driving path of the vehicle at the next moment planning. 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 and the display module receive and display the position and optimal route information from the data processing module and the route planning module in real time.
车辆控制终端模块信息流向为:车辆在行驶过程中,车载控制终端中的无线通信模块向周围邻居车辆和道路信息节点发送定位请求信号,接收来自邻居车辆和道路信息节点的位置信息,并将此信息传送到数据处理模块;数据采集模块对定位所需的相对信息进行测量,并将其传送给数据处理模块;数据处理模块将计算得到的位置信息分别传送给路径规划模块、车辆控制模块、存储模块和显示模块;路径规划模块将规划好的车辆路径通过数据处理模块传送给车辆控制模块。The information flow direction of the vehicle control terminal module is as follows: when the vehicle is driving, the wireless communication module in the vehicle control terminal sends a positioning request signal to the surrounding neighbor vehicles and road information nodes, receives the location information from the neighbor vehicles and road information nodes, and sends this The information is transmitted to the data processing module; the data acquisition module measures the relative information required for positioning and transmits it to the data processing module; the data processing module transmits the calculated position information to the path planning module, vehicle control module, storage module and display module; the path planning module transmits the planned vehicle path to the vehicle control module through the data processing module.
道路信息节点由散布在道路中、及道路周围的大量信息节点组成,每个节点由无线通信模块、数据处理模块与传感器模块组成。传感器模块可测量道路环境中车辆数量、车流速度和能见度等道路信息,并将测量的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、车速等信号发送给车载控制终端、道路交通控制中心。The road information node is composed of a large number of information nodes scattered in and around the road, and each node is composed of a wireless communication module, a data processing module and a sensor module. The sensor module can measure road information such as the number of vehicles, traffic speed and visibility in the road environment, and transmit the measured analog signal to the data processing module. The data processing module processes the analog signal from the sensor module and converts it into a digital signal. The wireless communication module sends the node position, road traffic flow, vehicle speed and other signals from the data processing module to the vehicle control terminal and road traffic control center.
道路信息节点模块信息流向为:传感器模块将测量到的相关信息传送到数据处理模块,数据处理模块对测量信息进行处理后发送给无线通信模块。The information flow direction of the road information node module is as follows: the sensor module transmits the measured information to the data processing module, and the data processing module processes the measured information and sends it to the wireless communication module.
道路交通控制中心模块由无线通信模块、数据处理模块和数据库模块组成。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相关信息,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 is composed of 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 relevant information from the wireless communication module, preprocesses it and stores it in the database module, and extracts relevant road geographic information from the database according to the needs of the vehicle control terminal module. The database module stores road traffic flow information and road geographic information for navigation.
道路交通控制中心模块信息流向为:无线通信模块将接收到的相关信息发送给数据处理模块,信息经过处理后由数据处理模块指定安排存储到数据库模块中;同时数据存储模块也可以将局部道路地理信息传送给数据处理模块,并由无线通信模块发送给所需车辆。The information flow direction of the road traffic control center module is as follows: the wireless communication module sends the received relevant information to the data processing module, and after the information is processed, the data processing module arranges and stores it in the database module; at the same time, the data storage module can also store the local road geographic The information is sent to the data processing module and sent to the desired vehicle by the wireless communication module.
整个系统的信息流向为:车辆在行驶过程中,车载控制终端接收来自邻居车辆和道路信息节点的位置信息,同时接收来自道路交通控制中心模块的局部道路地理信息。另外,车载控制终端也可发送自身的状态信息给道路信息节点模块和道路交通控制中心模块。The information flow direction of the whole system is: when the vehicle is driving, the vehicle control terminal receives the location information from neighboring vehicles and road information nodes, and at the same time receives the local road geographic information from the road traffic control center module. In addition, the vehicle control terminal can also send its own status information to the road information node module and the road traffic control center module.
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