CN114071421B - Open type unmanned vehicle group model in expressway scene and vehicle group forming method - Google Patents
Open type unmanned vehicle group model in expressway scene and vehicle group forming method Download PDFInfo
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Abstract
An open unmanned vehicle group model in a highway scene and a vehicle group forming process research method comprise the following steps: defining; constructing a network topology structure of the unmanned vehicle group; defining a vehicle state; and (5) carrying out a state transition process of the unmanned vehicle. The invention provides a concept facing an open type unmanned vehicle group for the first time, a multi-hop vehicle group is formed for unmanned vehicles in each direction of an expressway road, an unmanned vehicle group model which is considered in an expressway scene, faces a driving environment of the open type unmanned vehicle group, can keep interconnection and intercommunication among vehicle groups all the time and effectively meet the requirement of intellectualization of future unmanned moving behaviors is designed and constructed, and the initialization state, the election state, the leading node state, the common node state, the free node state and the conversion process of the unmanned vehicle nodes are researched at the same time, the rudiment of an unmanned vehicle group forming method is provided, and the theory and the method required for intellectualization of the future unmanned moving behaviors are provided.
Description
Technical Field
The invention relates to an unmanned network, which belongs to the brand new field.
Background
The prior art of the interconnection and intercommunication of the existing vehicle networking is as follows:
at present, the internet of vehicles refers to human-driven vehicles. Related researchers have conducted related research in the aspects of Vehicular Ad-hoc networks (VANET), infrastructure-based internet of Vehicles (VINET), and VANET and VINET hybrid networks.
(1) VANET in vehicle self-organizing network
At present, researchers develop researches on how connectivity of the VANET changes along with space-time change by using simulation and analysis methods:
i. aspects of simulation
The ViriyasittaVAT W and the like carry out simulation research on the connectivity of the V2V network based on key indexes such as link duration, the number and duration of connected networks and the healing time of disconnected networks, and the result shows that the urban area has a highly dynamic network connection mode. AKHTAR N and the like abstract a road scene into one-dimensional road traffic flow, analyzes topological characteristics of the road traffic flow under three different channel models, and compares neighbor distance, node degree, cluster quantity, link duration and connection quality under different propagation ranges. The Huang Hong-Yu and the like map GPS data collected from 4000 taxis in Shanghai onto a digital map, obtain the driving tracks of the taxis, and research virtual VANET under the assumption of different communication radiuses, and the result shows that when the communication radius is 500m, most of the taxis can be connected to the same network subarea, and the number of neighbor nodes in different communication radiuses is analyzed by using a cumulative distribution function. NABOULSI D and the like utilize complex network theory to research the real instantaneous topological characteristics of a large-scale urban VANET, analyze the instantaneous topological characteristics from three different layers of networks, components and nodes under various communication radiuses, and advocate that a forwarding carrying mechanism is adopted and an RSU is deployed at a weak connection place. VANET communication network indices in the 25 square km area of zurich within 3 hours of the early peak for 20 million vehicles: (a) VANET obeys a power law with a stable good fit; (b) it does not exhibit small world characteristics; (c) Intermediary centralities and gossip centralities are sufficient and appropriate to describe the characteristics of their network structure; (d) the VANET network map comprises one large cluster; (e) The arrival and departure of vehicles from the giant cluster are both sudden on different time scales; (f) the connections of the clusters remain stable for a period of time; (g) The dense cluster simultaneously comprises nodes with small value and large value; (h) VANET comprises overlapping communities; (i) The size of the compact community varies over a very small size; (j) the VANET graph is not robust.
Analytical method aspect
The development history, characteristics and application fields of the vehicle ad hoc network are introduced in the popular science and technology, the advantages and the disadvantages of various wireless communication technologies used for the vehicle ad hoc network are discussed by using an analysis and comparison method, and the design idea and the breakthrough direction for building a communication system between vehicles are provided according to the application and the characteristics of the vehicle ad hoc network. HO I-H etc. have analyzed the dynamic change of VANET connectivity on a urban road controlled by signal light, and studied the more general k and connected the network (k-connected) problem, verified through the simulation that even the vehicle moves and is controlled by the traffic light, the connectivity analysis and simulation result obtained in the text have good approximation. LOULLOUDES N et al analyzed the instantaneous topological features and statistical properties of VANETs based on real and simulated movement trajectories, and considered the impact of market penetration on network connectivity. The Liuye and the like firstly analyze and deduce mathematical analytic expressions of the relation between connectivity model parameter indexes such as the communication probability, the diameter length of a communication set, the number of the communication sets and the like between any two vehicles on a certain specific road section in the highway VANET and the vehicle density and the transmission distance, and analyze that the node position of the VANET meets the conclusion of gamma distribution on the basis. Bear, etc. models the VANET into a path loss geometric random graph, deduces a probability analysis algorithm for VANET 1-connectivity necessary conditions in an expressway scene, and performs a large number of simulation experiments by means of verified vehicle motion trajectory data to obtain upper and lower bounds which ensure that the communication distance of each node is satisfied under the condition that no isolated node exists in the network.
(2) Internet of vehicles network based on infrastructure (VINET)
ABDRABOU A and the like adopt an effective bandwidth theory and a concept of actual capacity to obtain the maximum distance between RSUs, and research the influence of vehicle density, transmission range and vehicle speed difference on end-to-end packet transmission delay so as to solve the RSU deployment problem. Three algorithms are proposed by SALVO P and the like to expand the coverage area of the RSU in VANET, and the forwarding direction is selected by using the position of the sender node and the geometric principle. And obtaining an optimal RSU and OBU installation configuration scheme through the analysis result. LIU Y and the like design a new RSU deployment strategy for file downloading in VANETs, model the connection between a vehicle and the RSU as a continuous time homogeneous Markov chain, model a road network as a weighted undirected graph, and design an RSU deployment algorithm aiming at file downloading based on a depth-first traversal algorithm of the edge of the graph. Chenli and the like utilize a bus as a mobile gateway to carry out I2V data forwarding in a VANET without deploying dense RSUs. Firstly, a road network model is converted into a state-space diagram, then an optimal forwarding decision is obtained by solving through a Markov decision method, and under the condition that the requirement of a constraint transmission success rate threshold is met, an intersection node with the minimum transmission delay is selected as an optimal aggregation node of a data packet and a target vehicle.
MATOLAK D W and the like adopt an empirical model in a V2V channel and use computer simulation to demonstrate the feasibility of using LTE to carry out broadband wireless access by a V2V terminal user under different transmission rates in an expressway environment. ABID H and the like use an LTE network for V2I communication, and a VANET framework based on an LTE smart phone is provided, so that the VANET framework is suitable for expressways instead of urban scenes. REMY G et al propose an LTE 4V 2X architecture, utilize enbs in the LTE network as the infrastructure for VANET cluster management, and employ a centralized architecture around the enbs to optimize cluster management and provide better performance. KIHL M and the like evaluate the performance of different downlink scheduling strategies under a plurality of urban and rural scenes, and experimental results show that LTE vehicle-mounted communication is very suitable for rural scenes. IDE C, etc. estimates vehicle travel time by increasing the number of sensors in the road network and analyzes the estimation accuracy of vehicle travel time using scalable Nagel-Schreckenberg model, ray tracing simulation and markov model based on several experimental metrics, and the balance between negative impact on the LTE air interface.
(3) VANET and VINET mixed network
Network architecture and channel access technology have a large impact on the internet of vehicles. V2V typically uses ieee802.11p as the physical and MAC layer protocols, while V2I may employ WiFi, WAVE, wiMAX and LTE. Since each access technology is limited, hybrid usage is more helpful for V2I and V2V communications instead.
The WiMAX technology is applied to a vehicle communication network for the first time by YANG Kun, SHAN Lianhai and the like, and vehicle-mounted mobile broadband wireless access is carried out on vehicles and users thereof. Aiming at the problem that the vertical switching technology can not support the vertical switching among WAVE, wiMAX and 3G generally, the paradigm memory group and the like provides a vertical switching algorithm based on Bayesian decision. Simulation experiment results show that the algorithm not only effectively realizes the vertical switching among WAVE, wiMAX and 3G wireless access technologies, but also avoids the ping-pong effect and ensures the timely update of the network. The DOYLE N C and the like provide WiMAX and WAVE integrated network layer design for providing internet access for vehicles, the inherent defects of pure WAVE and pure WiMAX are analyzed in the text, and a mixed solution is provided. Liufu, etc. propose WiMAX and WAVE novel heterogeneous network converged vehicle-mounted mobile network architecture, the communication between the vehicle is realized through being based on WAVE, and the communication between the vehicle and the roadside base station is realized through WiMAX. Chang B-J and the like propose a self-adaptive navigation method based on a wireless sensor network, and a WiMAX multi-hop relay network is adopted for V2V communication so as to improve the reliability and effectiveness of communication between vehicles. Compared with the CHOU C-M and the like, the feasibility that V2I uses WiMAX and Wi-Fi for communication is researched, and the result shows that the delay of WiMAX in a short distance (such as less than 100M) is obviously larger than that of Wi-Fi, and the duration of a frame has a remarkable influence on the WiMAX performance. MOJELA L S et al in a simple VANET, evaluated the performance of Wi-Fi for V2V communication and WiMAX for V2I communication. Streaming video, streaming audio and video conferencing can be run successfully in the V2I environment they build. ZHAO Qingwen et al, the first attempt to assist data transmission over 3G in VANET, proposed a method called 3GDD to allocate the available 3G traffic per timeslot by solving an integer linear programming problem in the original optimization problem. YAACOUB E and the like research a real-time video streaming transmission cooperation technology using scalable video coding in V2I communication, consider that LTE and WAVE technologies are used for providing communication for moving vehicles, compare different video transmission modes, and draw a conclusion that the joint cooperation effect between an LTE base station and a WAVE roadside infrastructure unit is the best.
The internet of vehicles (manned) is from the perspective of the information field, and does not consider external factors of the surrounding environment, such as interference of obstacles, manned vehicle bodies (here, moving obstacle nodes), traffic lights, and the like, for direct information interaction from vehicle to vehicle, vehicle to road infrastructure, and with background servers.
Disclosure of Invention
The technical scheme of the invention is especially suitable for highway scenes, and is not suitable for closed scenes such as ports, logistics and the like, and is also not suitable for urban scenes.
The invention aims to disclose an open type unmanned vehicle group model in a highway scene and a vehicle group forming process research method.
Therefore, the invention specifically provides the following technical scheme:
the research method is characterized by comprising the following steps:
1. predefining steps (including unmanned vehicle direct connectivity, neighbor nodes, neighbor node set)
The following definitions are given:
defining 1 Driverless Vehicle direct Connectivity DVC (Driverless Vehicle Connectivity) to represent the stability of two Driverless Vehicle node direct connections, the mathematical expression of which is (1):
wherein the content of the first and second substances,
DCR (Driverless Communication Range) represents a maximum Communication Range of the unmanned vehicle Communication;
dist t (v i ，v j ) Node v representing unmanned vehicle at time t i With another unmanned vehicle node v j The distance between them; when the distance between the nodes is larger than the maximum communication range, the DVC is 0, which indicates that the two unmanned vehicle nodes are not connected, namely, the topological graph shows that no edge exists between the two nodes; when the distance between the unmanned vehicle nodes is less than or equal to the maximum transmission range, the DVC is inversely related to the distance between the vehicles. The closer the distance between the nodes is, the larger the DVC is, the higher the reliability of direct connection between two unmanned vehicle nodes is, the tighter the connection is, and the larger the weight reflected to the upper side of the topological graph is.
Define 2 neighbor nodes NeiNode: if unmanned vehicle node v i Node v with another unmanned vehicle j Satisfy DVC (v) i ，v j ) If greater than 0, then v is called i And v j Nodes which are adjacent to each other are reflected in the topological graph, namely v i And v j An edge is arranged between the two edges; the neighbor node NeiNode is characterized by a mathematical expression of (2):
NeiNode(v i ，v j )＝1 if DVC(v i ，v j )＞0 (2)
defining 3 neighbor node set N i，t : representing an unmanned node v i Set V of neighbor nodes at time t j The mathematical expression is (3):
2. step for constructing network topology structure of unmanned vehicle group
The unmanned vehicle group is the neighbor vehicle group NeiVG, if two unmanned vehicle groups VG i And VG i If a connecting edge exists between the nodes in the unmanned vehicle cluster, the two vehicle clusters are mutually neighbor vehicle clusters, and the network structure of the unmanned vehicle cluster adopts a mathematical expression of (4):
forming a multi-hop cluster topology for unmanned vehicles in each direction of a highway road, as shown in fig. 1, is a three-hop cluster network topology, in which: the radius of the vehicle which can be communicated is represented by R in the figure, the dotted line among the vehicle nodes represents that the vehicles can be communicated with each other, and the vehicle nodes which are not in the communication range can be used for relaying communication by other vehicles;
3. defining vehicle states
Definition 6 to describe the formation process of the unmanned vehicle group in the expressway scene, the following five unmanned vehicle states are defined:
(1) Initialization state IN (Initialization)
The initialization state is the starting state of the unmanned vehicle node.
During initialization, each unmanned Vehicle node maintains a Vehicle Basic Information Table VIBT (Vehicle Information Basic Table) including Vehicle Information of the node itself and its neighbor nodes, wherein: the vehicle information includes its vehicle ID, direction, speed, position coordinates, current vehicle state,
the neighbor vehicle information comprises the ID of the vehicle group; if the node is the common node CN, the neighbor vehicle information also comprises the hop count from the common node CN to the leading node LN, and the vehicle ID connected to the leading node LN and passing through the common node CN;
in addition, the vehicle group leading node LN needs to store the vehicle group member ID.
(2) Election State SE (Select State)
After each unmanned vehicle node is in the initialized state, the unmanned vehicle node comprehensively senses the information of the neighbor nodes, simultaneously sends the information of the unmanned vehicle node to the neighbor nodes around, updates the basic information table VIBT of the vehicle to the latest state, and at the moment, switches the state of the unmanned vehicle node into the election state.
(3) (4) leading node LN state and common node CN state
In order to characterize the position of the unmanned vehicle nodes in the vehicle cluster and the degree of their contribution in the maintenance of the vehicle cluster, after an election state, one unmanned vehicle cluster generates more than one Leading node LN (Leading node) and several Common nodes CN (Common node).
Each leading node LN is responsible for managing various information of the vehicle group, such as a vehicle group node set, and the position, the speed and the like of each unmanned vehicle node in the vehicle group; meanwhile, in the movement process of the vehicle group, the leading node LN often determines whether a node other than the vehicle group can join the vehicle group.
Meanwhile, node set N of vehicle group i Except for the leading node LN, the remaining unmanned vehicle nodes are in a common node CN state.
(5) Free Node FN (Freeing Node) state
In the movement process of the unmanned vehicle node, if the node cannot be connected to any existing vehicle cluster and no nodes capable of being communicated exist around the node, the node is in a free node state.
4. Unmanned vehicle state transition process
According to the motion characteristics and five states of the unmanned vehicle node in the expressway scene, giving the unmanned vehicle state conversion process:
1) The unmanned vehicle node starts to be in an initialization state, and in the state, the vehicle periodically exchanges HELLO data packets to construct a vehicle basic information table VIBT of the vehicle;
the vehicle then transitions to an election state SE in which the vehicle makes its next state decision, step 2);
2) When no adjacent node exists near the unmanned vehicle node in the election state SE, the vehicle is converted into a free node FN state, and the step 3) is carried out;
3) When the unmanned vehicle node in the free node FN state finds other free nodes FN which can be directly connected, the vehicle is converted into an election state SE;
when the vehicle group node of the leading node LN or the common node CN exists near the unmanned vehicle node in the free node state, the node is converted into the common node CN, or the vehicle is converted into the election state SE;
4) If the relative attribute measurement of the node is the best, the vehicle state is converted into a leading node LN state; entering step 5) or step 6);
5) In an election state SE, if the node metric of the piloting node LN of the unmanned vehicle is not optimal, the piloting node LN is converted into a common node CN state; otherwise, converting into a leading node LN state;
6) When no common node CN exists near the leading node LN, the node is converted into an election state SE;
7) When the vehicle group leading node LN to which the common node CN belongs does not exist, the state is converted to the election state SF.
Further, in said step 5), node relative mobility is defined for characterizing said metric to determine whether it is optimal to elect a lead node LN.
Selecting a stable lead node LN using said node relative mobility, node i relative mobility Mob i The mathematical expression is (5):
wherein, the first and the second end of the pipe are connected with each other,
N i representing unmanned vehicle node v i Set of nodes of the vehicle group, i j Indicating a vehicle group N i J-th node in, S i Represents the speed of node i;
Mob i the smaller the value, the smaller the difference in relative speed between the node i and other nodes in the vehicle group, and the more stable the relative mobility.
If v is i In the leading node LN state, the mathematical expression is (6):
wherein the content of the first and second substances,
Mob i indicating the relative mobility of the nodes of the unmanned vehicle i, i belonging to the unmanned vehicle node in the election state.
Drawings
FIG. 1 is a network topology structure diagram of the invention
FIG. 2 is a block diagram of the unmanned vehicle state transition framework of the present invention
Detailed Description
One of the purposes of the invention is to disclose an open type unmanned vehicle group model in a highway scene and a vehicle group forming process research method
The research method is characterized by comprising the following steps:
1. predefining steps (including direct connectivity of unmanned vehicles, neighbor nodes, and neighbor node sets) in order to study an unmanned vehicle cluster formation algorithm based on highway scenes, the present invention provides the following definitions:
defining 1 Driverless Vehicle direct Connectivity DVC (Driverless Vehicle Connectivity) to represent the degree of stability of the direct connection of two Driverless Vehicle nodes, the mathematical expression of which is (1):
wherein the content of the first and second substances,
DCR (Driverless Communication Range) represents a maximum Communication Range of the unmanned vehicle Communication;
dist t (v i ，v j ) Node v representing unmanned vehicle at time t i Node v with another unmanned vehicle j The distance between them; when the distance between the nodes is larger than the maximum communication range, the DVC is 0, which indicates that the two unmanned vehicle nodes are not connected, namely, the topological graph shows that no edge exists between the two nodes; when the distance between the unmanned vehicle nodes is less than or equal to the maximum transmission range, the DVC is inversely related to the distance between the vehicles. The closer the distance between the nodes is, the larger the DVC is, the higher the reliability of direct connection between two unmanned vehicle nodes is, the tighter the connection is, and the larger the weight reflected to the upper side of the topological graph is.
Defining 2 neighbor nodes NeiNode: if unmanned vehicle node v i Node v with another unmanned vehicle j Satisfy DVC (v) i ，v j ) If greater than 0, then v is called i And v j The nodes which are adjacent to each other are reflected in the topological graph, namely v i And v j An edge is arranged between the two edges; the neighbor node NeiNode is characterized by a mathematical expression of (2):
NeiNode(v i ，v j )＝1 if DVC(v i ，v j )＞0 (2)
defining 3 neighbor node set N i，t : representing an unmanned node v i Set V of neighbor nodes at time t j The mathematical expression is (3):
2. step for constructing network topology structure of unmanned vehicle group
The unmanned vehicle group is the neighbor vehicle group NeiVG, if two unmanned vehicle groups VG i And VG j If a connecting edge exists between the nodes in the unmanned vehicle group, the two vehicle groups are mutually adjacent vehicle groups, and the network structure of the unmanned vehicle group adopts a mathematical expression of (4):
forming a multi-hop cluster topology for unmanned vehicles in each direction of a highway road, as shown in fig. 1, is a three-hop cluster network topology, in which: the radius of the vehicle which can be communicated is represented by R in the figure, the dotted line among the vehicle nodes represents that the vehicles can be communicated, and the vehicle nodes which are not in the communication range can be used for forwarding communication by other vehicles;
3. defining vehicle states
Definition 6 to describe the formation process of the unmanned vehicle group in the highway scenario, the following five unmanned vehicle states are defined:
(1) Initialization state IN (Initialization)
The initialization state is the starting state of the unmanned vehicle node.
During initialization, each unmanned Vehicle node maintains a Vehicle Basic Information Table VIBT (Vehicle Information Basic Table) including Vehicle Information of the node itself and its neighbor nodes, wherein: the vehicle information includes its vehicle ID, direction, speed, position coordinates, current vehicle state,
the neighbor vehicle information comprises the ID of the vehicle group; if the node is the common node CN, the neighbor vehicle information also comprises the hop count from the common node CN to the leading node LN, and the vehicle ID connected to the leading node LN and passing through the common node CN;
in addition, the vehicle group leading node LN needs to store the vehicle group member ID.
By way of example and not limitation, table 2 is a vehicle basic information table as follows:
(2) Election State SE (Select State)
After each unmanned vehicle node is in the initialized state, the unmanned vehicle node comprehensively senses the information of the neighbor nodes, simultaneously sends the information of the unmanned vehicle node to the neighbor nodes around, updates the basic information table VIBT of the vehicle to the latest state, and at the moment, switches the state of the unmanned vehicle node into the election state.
(3) /(4) leading node LN State and ordinary node CN State
In order to characterize the position of the unmanned vehicle nodes in the vehicle cluster and their contribution in the maintenance of the vehicle cluster, after an election state, one unmanned vehicle cluster generates more than one Leading node LN (Leading node) and several Common nodes CN (Common node).
Each leading node LN is responsible for managing various information of the vehicle group, such as a vehicle group node set, the position and the speed of each unmanned vehicle node in the vehicle group and the like; meanwhile, in the movement process of the vehicle group, the leading node LN often determines whether a node other than the vehicle group can join the vehicle group.
Meanwhile, node set N of vehicle group i Except for the leading node LN, the remaining unmanned vehicle nodes are in a common node CN state.
(5) Free Node FN (Freeing Node) state
In the process of the movement of the unmanned vehicle node, if the node cannot be connected to any existing vehicle cluster and no connectable nodes exist around the node, the node is in a free node state.
4. Unmanned vehicle state transition process
According to the motion characteristics and five states of the unmanned vehicle node in the expressway scene, the unmanned vehicle state conversion process is given, and a frame diagram of the unmanned vehicle state conversion process is shown in FIG. 2;
the specific conversion process is as follows:
1) The unmanned vehicle node starts to be in an initialization state, and in the state, the vehicle periodically exchanges HELLO data packets to construct a vehicle basic information table VIBT of the vehicle;
the vehicle then transitions to an election state SE in which the vehicle makes its next state decision, step 2);
2) When no adjacent node exists near the unmanned vehicle node in the election state SE, the vehicle is converted into a free node FN state, and the step 3) is carried out;
3) When the unmanned vehicle node in the free node FN state finds other free nodes FN which can be directly connected, the vehicle is converted into an election state SE;
when the vehicle group node of the leading node LN or the common node CN exists near the unmanned vehicle node in the free node state, the node is converted into the common node CN, or the vehicle is converted into the election state SE;
4) If the relative attribute measurement of the node is the best, the vehicle state is converted into a leading node LN state; entering step 5) or step 6);
5) In an election state SE, if the node metric of the piloting node LN of the unmanned vehicle is not optimal, the piloting node LN is converted into a common node CN state; otherwise, converting into a leading node LN state;
6) When no common node CN exists near the leading node LN, the node is converted into an election state SE;
7) And when the vehicle group leading node LN to which the common node CN belongs does not exist, the state is converted into an election state SE.
Further, in said step 5), node relative mobility is defined for characterizing said metric to determine whether it is optimal to elect a lead node LN.
Selecting a stable lead node LN, a node i relative mobility Mob, using said node relative mobility i The mathematical expression is (5):
wherein, the first and the second end of the pipe are connected with each other,
N i representing unmanned vehicle node v i Set of nodes of the vehicle group, i j Indicating a vehicle group N i J-th node in, S i Represents the speed of node i;
Mob i the smaller the value, the smaller the difference in relative speed between the node i and other nodes in the vehicle group, and the more stable the relative mobility.
If v is i In the lead node LN state, the mathematical expression is (6):
wherein, the first and the second end of the pipe are connected with each other,
Mob i indicating the relative mobility of the nodes of the unmanned vehicle i, i belonging to the unmanned vehicle node in the election state.
As an example, the main symbols required in the formation process of the vehicle group in the expressway scene are given, and the meaning description is shown in table 1.
TABLE 1
In summary,
the invention provides a concept facing an open type unmanned vehicle group for the first time, a multi-hop vehicle group is formed for unmanned vehicles in each direction of an expressway road, an unmanned vehicle group model which is considered in an expressway scene, faces the driving environment of the open type unmanned vehicle group, can keep interconnection and intercommunication among vehicle groups all the time and effectively meet the requirement of intellectualization of future unmanned moving behaviors is designed and constructed, and conversion processes of an initialization state, a election state, a leading node LN state, a common node CN state, a free node state and five states of nodes of the unmanned vehicle are researched at the same time, the prototype of the unmanned vehicle group forming method is provided, so that the theory and the method required for intellectualization of the future unmanned moving behaviors are provided, and practical application of the unmanned vehicles in the expressway scene becomes possible.
The unmanned vehicle serves as a terminal node of a vehicle group, serves as an intelligent agent, and is internally provided with a plurality of devices for sensing, data processing, data storage, communication transmission and the like, so that the unmanned vehicle can acquire information in the vehicle and real-time information of adjacent vehicles, and can effectively keep interconnection and intercommunication among the vehicle group nodes. But these support devices do not serve the inventive task of the present invention.
Various networks in the physical environment, including different types of roadside infrastructure networks, mobile communication networks, etc., are considered as prior art, and are considered as road network space-time resources that can be perceived by the unmanned single intelligent vehicle node of the present invention, but are not the inventive task of the present invention.
The invention is used as an original technical scheme. The access network type, the service quality of the network, the protocol type, the network bandwidth, the terminal capability and the like are not the invention tasks of the invention, and other subsequent patents further disclose and perfect.
The unmanned vehicle has application value in highway scenes.
Claims (6)
1. An open unmanned vehicle group model in a highway scene and a vehicle group forming method are characterized by comprising the following steps:
1. predefining steps
The following definitions are given:
defining 1 Driverless Vehicle direct Connectivity DVC (Driverless Vehicle Connectivity) to represent the stability of two Driverless Vehicle node direct connections, the mathematical expression of which is (1):
wherein, the first and the second end of the pipe are connected with each other,
DCR (Driverless Communication Range) represents a maximum Communication Range of the unmanned vehicle Communication;
dist t (v i ,v j ) Node v representing unmanned vehicle at time t i With another unmanned vehicle node v j The distance therebetween; when festivalWhen the distance between the points is larger than the maximum communication range, the DVC is 0, which indicates that the two unmanned vehicle nodes are not connected, namely, the topological graph shows that no edge exists between the two nodes; when the distance between the unmanned vehicle nodes is less than or equal to the maximum transmission range, the DVC is inversely related to the distance between the vehicles; the closer the distance between the nodes is, the larger the DVC is, the higher the reliability of direct connection between the two unmanned vehicle nodes is, the tighter the connection is, and the larger the weight reflected to the upper side of the topological graph is;
defining 2 neighbor nodes NeiNode: if unmanned vehicle node v i Node v with another unmanned vehicle j Satisfy DVC (v) i ,v j )>0, then v i And v j Nodes which are adjacent to each other are reflected in the topological graph, namely v i And v j An edge is arranged between the two edges; the neighbor node NeiNode is characterized by a mathematical expression as (2):
NeiNode(v i ,v j )＝1 if DVC(v i ,v j )>0 (2)
defining 3 neighbor node set N i,t : representing an unmanned node v i Set V of neighbor nodes at time t j The mathematical expression is (3):
2. step for constructing network topology structure of unmanned vehicle group
An unmanned vehicle group, namely a neighbor vehicle group NeiVG, if two unmanned vehicle groups VG i And VG j If a connecting edge exists between the nodes in the unmanned vehicle group, the two vehicle groups are mutually adjacent vehicle groups, and the network structure of the unmanned vehicle group adopts a mathematical expression of (4):
the method is characterized in that a multi-hop vehicle group topology is formed for unmanned vehicles in each direction of a highway road, and the three-hop vehicle group network topology is a three-hop vehicle group network topology structure, wherein: the radius of the vehicle which can be communicated is represented by R, the vehicle nodes are communicated within the range of the radius of the communication R, and the vehicle nodes which are not within the range of the communication can be forwarded by other vehicles;
3. defining a vehicle state step
Definition 4 to describe the formation process of the unmanned vehicle group in the expressway scene, the following five unmanned vehicle states are defined:
(1) Initialization state IN (Initialization)
The initialization state is the initial state of the unmanned vehicle node;
during initialization, each unmanned vehicle node maintains a vehicle Basic information Table VIBT (vehicle information Basic Table) which comprises vehicle information of the node and neighbor nodes of the node;
(2) Election State SE (Select State)
After each unmanned vehicle node is in an initialized state, sensing neighbor node information comprehensively, sending self information to surrounding neighbor nodes, updating a vehicle basic information table VIBT into a latest state, and switching the self state of the unmanned vehicle node into an election state;
(3) (4) leading node LN state and common node CN state
In order to represent the positions of the unmanned vehicle nodes in the vehicle group and the contribution degrees of the unmanned vehicle nodes in the vehicle group maintenance, after the election state, one unmanned vehicle group generates more than one Leading node LN, leading node and a plurality of Common nodes CN, common node;
each leading node LN is responsible for managing various information of the vehicle group; in the movement process of the vehicle group, the leading node LN usually determines whether a node which is not the vehicle group can join the vehicle group;
meanwhile, node set N of vehicle group i Except for a leading node LN, the remaining unmanned vehicle nodes are in a common node CN state;
(5) FN (Freeing Node) state of free Node
In the process of the movement of the unmanned vehicle node, if the node cannot be connected to any existing vehicle group and no nodes capable of being communicated exist around the node, the node is in a free node state;
4. unmanned vehicle state transition process steps
According to the motion characteristics and five states of the unmanned vehicle nodes in the highway scene, giving a state conversion process of the unmanned vehicle:
1) The unmanned vehicle node starts to be in an initialization state, and in the state, the vehicle periodically exchanges HELLO data packets to construct a vehicle basic information table VIBT of the vehicle;
the vehicle then transitions to an election state SE in which the vehicle makes its next state decision, step 2);
2) When no adjacent node exists near the unmanned vehicle node in the election state SE, the vehicle is converted into a free node FN state, and the step 3) is carried out;
3) When the unmanned vehicle node in the free node FN state finds other free nodes FN which can be directly connected, the vehicle is converted into an election state SE;
when the vehicle group node of the leading node LN or the common node CN exists near the unmanned vehicle node in the free node state, the node is converted into the common node CN, or the vehicle node is converted into the election state SE;
4) If the relative attribute measurement of the node is the best, the vehicle state is converted into a leading node LN state; entering step 5) or step 6);
5) In an election state SE, if the node metric of the piloting node LN of the unmanned vehicle is not optimal, the piloting node LN is converted into a common node CN state; otherwise, converting into a leading node LN state;
6) When no common node CN exists near the leading node LN, the node is converted into an election state SE;
7) And when the vehicle group leading node LN to which the common node CN belongs does not exist, the state is converted into an election state SE.
2. The method as claimed in claim 1, wherein the Vehicle Information of the node itself and its neighbor nodes in the Vehicle Basic Information Table VIBT (Vehicle Information Basic Table), wherein:
the vehicle information includes its vehicle ID, direction, speed, position coordinates, current vehicle state,
the neighbor vehicle information comprises the ID of the vehicle group; if the node is a common node CN, the neighbor vehicle information further includes the hop count from the common node CN to the lead node LN, and the vehicle ID connected to the lead node LN and passing through the common node CN.
3. The method of claim 1, characterized in that the vehicle group leader node LN also needs to save the vehicle group member ID.
4. The method of claim 1, wherein in step 5) node relative mobility is defined for characterizing the metric to determine whether it is optimal to elect a lead node LN:
selecting a stable lead node LN using said node relative mobility, node i relative mobility Mob i The mathematical expression is (5):
wherein, the first and the second end of the pipe are connected with each other,
N i representing unmanned vehicle node v i Set of nodes of the vehicle group, i j Indicating a vehicle group N i J-th node in, S i Represents the velocity of node i;
Mob i the smaller the value, the smaller the difference in relative speed between the node i and other nodes in the vehicle group, and the more stable the relative mobility.
5. The method of claim 1, wherein in step 5), if v is i In the leading node LN state, the mathematical expression is (6):
wherein, the first and the second end of the pipe are connected with each other,
Mob i indicating the relative mobility of the nodes of the unmanned vehicle i, i belonging to the unmanned vehicle node in the election state.
6. The method according to claim 1, characterized in that each lead node LN is responsible for managing various items of information of the vehicle group in which it is located, including: the position and the speed of each unmanned vehicle node in the vehicle group node set and the vehicle group.
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