CN114613179A - Gathering and passing method for internet-connected automatic-driving mixed-driving vehicle intersection and control system thereof - Google Patents

Gathering and passing method for internet-connected automatic-driving mixed-driving vehicle intersection and control system thereof Download PDF

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CN114613179A
CN114613179A CN202111582226.3A CN202111582226A CN114613179A CN 114613179 A CN114613179 A CN 114613179A CN 202111582226 A CN202111582226 A CN 202111582226A CN 114613179 A CN114613179 A CN 114613179A
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vehicle
gathering
motorcade
speed
signal
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CN114613179B (en
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梁军
李燕青
陈龙
盘朝奉
曹淑超
蔡涛
罗媛
徐永龙
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Jiangsu University
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    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/09—Arrangements for giving variable traffic instructions
    • G08G1/0962—Arrangements for giving variable traffic instructions having an indicator mounted inside the vehicle, e.g. giving voice messages
    • G08G1/0968—Systems involving transmission of navigation instructions to the vehicle
    • G08G1/096833—Systems involving transmission of navigation instructions to the vehicle where different aspects are considered when computing the route
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/01—Detecting movement of traffic to be counted or controlled
    • G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/09—Arrangements for giving variable traffic instructions
    • G08G1/0962—Arrangements for giving variable traffic instructions having an indicator mounted inside the vehicle, e.g. giving voice messages
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/20—Monitoring the location of vehicles belonging to a group, e.g. fleet of vehicles, countable or determined number of vehicles

Abstract

The invention provides a gathering and passing method and a control system for a mixed-driving intersection of networked automatic driving vehicles, wherein an intelligent agent of the networked automatic driving vehicles receives a gathering instruction, selects gathering objects to form a gathering motorcade, judges whether the gathering motorcade can pass through a pre-signal stop line without stopping at the current speed according to an information base of the gathering motorcade and the residual green light duration of the current phase, and otherwise, carries out a speed induction strategy on the gathering motorcade; after the gathering motorcade passes through the pre-signal stop line, speed suggestion is carried out on the gathering motorcade, vehicles run according to suggested speed, and the vehicles pass through the signalized intersection without stopping in cooperation with a coordination timing scheme of the main signal and the pre-signal. The invention can improve the traffic efficiency and safety of road traffic to a great extent and relieve the congestion condition of mixed traffic flow.

Description

Gathering and passing method for internet-connected automatic-driving mixed-driving vehicle intersection and control system thereof
Technical Field
The invention belongs to the technical field of intelligent traffic intersection traffic control, and particularly relates to a method for gathering traffic at a mixed-traffic intersection of networked automatic driven vehicles and a control system thereof.
Background
In recent years, with the continuous development of automatic driving technology And Vehicle networking technology, a Connected And automated driving Vehicle (CAV) starts to rush into the road, And the situation that the CAV And a Connected Human-drive Vehicle (CHV) are mixed in the future is faced for a long time. However, there are some differences between the CHV and the CAV in driving behaviors, for example, CHV drivers are easily interfered by various factors such as emotions, and further some irregular driving behaviors occur, even serious traffic accidents are caused; also, CAV has difficulty in making the most reasonable driving decisions like human drivers when dealing with complex traffic conditions, such as intersections where traffic accidents occur. In such mixed traffic flow, it can be said that CHV and CAV are mutually restricted and have strong coupling. Therefore, many new traffic problems emerge, and particularly, the problem of how to improve the traffic efficiency of the road intersection and ensure the safety is solved.
The road intersection is an important component of a road traffic network, is a node for gathering, turning and evacuating traffic flow of each road section, and is a place where traffic jam and accidents occur frequently. The current intersection passing method is only suitable for CHV, and as CAV is increased continuously, the passing condition of the intersection is bound to be controlled by the control difference between human and non-human in the CHV and CAV, so that the conflict is increased and the efficiency is reduced.
How to design a reasonable CAV mixed crossing gathering passing method and further improve the passing efficiency of urban roads is a difficult problem to be solved urgently at present. On one hand, a reasonable CAV hybrid vehicle flow control theory and a reasonable CAV hybrid vehicle flow guiding idea are lacked; on the other hand, the existing intersection traffic control model is not closely related to the future mixed traffic environment, and an ideal effect cannot be achieved.
Disclosure of Invention
Aiming at the defects in the prior art, the invention provides a gathering passing method and a control system for an internet automatic driving mixed-driving intersection, which can reduce traffic delay time and improve the passing efficiency of the intersection under the condition of ensuring the traffic safety of roads.
The present invention achieves the above-described object by the following technical means.
A gathering passing method for a mixed-road intersection of networked automatic driven vehicles comprises the following specific steps:
in a road section control area, selecting a gathering target internet automatic driving vehicle intelligent body according to the state of mixed traffic flow, receiving a gathering instruction by the internet automatic driving vehicle intelligent body, firstly selecting a vehicle in front of the same lane in the same direction as a gathering object by the target internet automatic driving vehicle intelligent body, judging whether the vehicle is the internet automatic driving vehicle intelligent body and meets a gathering condition, and if the vehicle is the internet automatic driving vehicle intelligent body and meets the gathering condition, gathering the vehicle with a front vehicle; if the vehicle is not met, the gathering object is replaced, whether the vehicle in front of the left and right adjacent lanes is the internet automatic driving vehicle intelligent agent or not is continuously judged, and the gathering condition is met, if the vehicle in front of the left and right adjacent lanes is met, the lane is immediately changed, and the vehicle is gathered with the front vehicle after the lane is changed; if not, selecting the networking manually-driven vehicle in the front of the same lane in the same direction as the gathering object, judging whether the gathering condition is met, and if so, gathering; when gathering, updating the speed and the position in real time to form a gathering fleet; in the gathering process, the internet-connected manually-driven vehicle intelligent agent has probability phSelecting to join the gathering motorcade;
according to the information base of the gathering fleet
Figure BDA0003426491700000021
And the remaining green time t of the current phaseeJudging whether the gathering motorcade can pass through a pre-signal stop line without stopping at the current speed, otherwise, carrying out speed induction strategy on the gathering motorcade; wherein R is the vehicle surrounding environment informationN, kiIs the own vehicle type,/jIs the lane in which the vehicle is located, xiIs the position of the vehicle, viFor the current vehicle speed, nqTo gather the captain of a fleet, v0In order to cluster the vehicle speeds of a fleet of vehicles,
Figure BDA0003426491700000022
in order to gather the head vehicle position of the fleet, the vehicle number i is 1, 2.. n, and the lane number j is 1, 2.. u;
after the gathering motorcade passes through the pre-signal stop line, speed suggestion is carried out on the gathering motorcade, vehicles run according to suggested speed, and the vehicles pass through the signalized intersection without stopping in cooperation with a coordination timing scheme of the main signal and the pre-signal.
In the technical scheme, the internet-connected manually-driven vehicle intelligent agent has probability phSelectively joining a fleet of gathering vehicles, said phComprises the following steps:
Figure BDA0003426491700000023
wherein: the receiver indicates that the driver receives the suggestion of gathering driving, the internal indicates the internal factors influencing the internet connection manual driving vehicle driver to join the gathering motorcade, and the external indicates the external factors influencing the internet connection manual driving vehicle driver to join the gathering motorcade.
In the technical scheme, the external factor external omega influencing the addition of the intelligent bodies of the networked manual driving vehicles into the gathering motorcade1ρ+ω2ratecon+ω3y + σ, where parameter ω1Influencing specific gravity, omega, for traffic flow density2Influencing the proportion, omega, for road congestion situations3Influencing specific gravity, omega, for a lumped dominance functioniIs epsilon [0,1) and
Figure RE-GDA0003603395630000024
rho is the traffic flow density; rateconThe condition is road congestion; y is the dominance function y ═ mu of CHV added to the gathering fleet1tdelay+μ2squeue+θ，tdelayReduced delay time, s, for networked manually driven vehicles to join a cluster fleetqueueReduced queue length, mu, for networked manually driven vehicles1To reduce the influence of delay time, mu2To reduce the impact specific gravity of the queue length, muiE [0,1) and μ1+μ 21 is ═ 1; both theta and sigma are random errors;
when the external belonged to (0, 0.3), the suggestion level of the internet man-made driving vehicle intelligent body for adding the internet man-made driving vehicle into the gathering motorcade is primary, the driver is reminded to add the gathering motorcade, when the external belonged to (0.3, 0.6), the suggestion level of the internet man-made driving vehicle intelligent body for adding the internet man-made driving vehicle into the gathering motorcade is intermediate, the driver is reminded and is advised to add the gathering motorcade, and when the external belonged to (0.6,1), the suggestion level of the internet man-made driving vehicle intelligent body for adding the internet man-made driving vehicle into the gathering motorcade is advanced, the driver is reminded and is strongly advised to add the gathering motorcade.
In the technical scheme, the internet-connected manually-driven vehicle intelligent agent has probability phInternal factors influencing adding of internet-connected manually-driven vehicle intelligent bodies into gathering motorcade by selecting to add into gathering motorcade
Figure BDA0003426491700000031
αjIndicating whether the driver has accepted the aggregated advicejRepresenting the relative weight of each influencing factor and delta representing the random error.
In the above technical solution, the real-time update of the speed and the position is performed according to the following rules:
Figure BDA0003426491700000032
wherein:
Figure BDA0003426491700000033
representing the speed of the target vehicle at time t +1,
Figure BDA0003426491700000034
representing the speed of the target vehicle at time t, a representing the conventional acceleration of the networked autonomous vehicle agent, vmaxRepresents the maximum vehicle speed allowed for the road segment,
Figure BDA0003426491700000035
indicates the position of the preceding vehicle at time t +1, dgfRepresenting the distance between the target vehicle and the preceding vehicle, dsafeIndicates the minimum safety distance, vsafeIndicating the safe vehicle speed for the road segment.
In the technical scheme, before the intelligent body of the target internet automatic driving vehicle changes lanes, whether the distance between vehicles in front of and behind adjacent lanes meets the requirement or not needs to be judged
Figure BDA0003426491700000036
If the distance between the front vehicle and the rear vehicle of the adjacent lane does not meet the condition, the target internet automatic driving vehicle intelligent agent and the lagging vehicle of the target lane perform collaborative cross lane change, wherein the collaborative cross lane change condition is as follows:
Figure BDA0003426491700000037
wherein
Figure BDA0003426491700000038
Indicating the location of the target vehicle at time t +1,
Figure BDA0003426491700000039
showing the position of the vehicle behind the adjacent lane of the road at the time t,
Figure BDA00034264917000000310
represents the speed of the vehicle behind the adjacent lane of the local lane at the time point t +1,
Figure BDA00034264917000000311
showing the vehicle position in front of two adjacent lanes of the road at the time of t +1,
Figure BDA00034264917000000312
indicating the position of the target vehicle at time t,
Figure BDA00034264917000000313
representing the speed of the target vehicle at time t +1,
Figure BDA00034264917000000314
indicating the position of the vehicle behind at time t,
Figure BDA0003426491700000041
indicating the position of the vehicle behind the adjacent lane of the target lane at time t +1, dsafeRepresenting the minimum safe separation.
In the technical scheme, whether the gathering motorcade can pass through the pre-signal stop line without stopping at the current speed is judged, and the judgment comprises constant speed, acceleration, deceleration and parking induction control strategies;
the judgment condition of the uniform speed control strategy is as follows:
Figure BDA0003426491700000042
wherein d isgIndicates the vehicle length, dcRepresenting the spacing of the vehicles in the gathering fleet;
the judgment conditions of the acceleration control strategy are as follows:
Figure BDA0003426491700000043
wherein t isaRepresenting the time required to accelerate to the highest speed permitted for the road section, vmaxRepresents the maximum speed allowed for the road segment;
the deceleration judgment conditions are as follows:
Figure BDA0003426491700000044
wherein t isdIndicating the time required to decelerate to the lowest speed permitted for the road section, trIndicating waiting for the next green light on time, vminRepresents the minimum speed allowed for the road segment;
the judgment conditions of the induced parking control strategy are as follows:
Figure BDA0003426491700000045
in the above technical solution, the position of the pre-signal stop line is based on the traffic information C ═ Qm,ra,ph,tr,dg,dsAnd u, carrying out real-time dynamic adjustment on different conditions of the parking line, wherein the position of the pre-signal parking line is as follows:
Figure BDA0003426491700000046
wherein QmIndicating the arrival rate of the vehicle, raIndicating the permeability, p, of an on-line autonomous vehiclehIndicating the acceptance of the network connection manually driven vehicle driver, trIndicating the duration of the red light of the main signal, dgRepresenting the length of a single vehicle, dsThe safety distance of the gathering motorcade when parking is shown, and u represents the gathering lane number controlled by the pre-signal.
In the above technical solution, the coordination timing scheme of the main signal and the pre-signal is adjusted on the basic signal timing as follows: the green light of the gathering motorcade of the pre-signal is turned on earlier than the green light of the main signal, the red light of the gathering motorcade of the pre-signal is turned on earlier than the red light of the main signal, the green light of the vehicle driven by the single vehicle networking manual driving of the pre-signal is turned on at the same time as the green light of the main signal, and the red light of the vehicle driven by the single vehicle networking manual driving of the pre-signal is turned on at the earlier time than the red light of the main signal.
A control system for realizing the gathering and passing method of the internet automatic driving mixed-driving vehicle intersection comprises the following steps:
the vehicle intelligent bodies are divided into a network connection automatic driving vehicle intelligent body and a network connection manual driving vehicle intelligent body; the internet automatic driving vehicle intelligent agent comprises a sensing module, a task analysis module and a decision execution module, wherein the sensing module is used for sensing own vehicle information, surrounding environment information and interaction information with other modules, the task analysis module is used for analyzing lane information, position information and speed information of a vehicle, and the decision execution module is used for executing vehicle gathering, left-right lane changing and speed updating according to the condition of the task analysis module; the internet-connected manual-driving vehicle intelligent body comprises an information detection module, a state analysis module and a reaction decision module, wherein the information detection module is used for detecting information of the vehicle intelligent body, other vehicle intelligent bodies and the surrounding environment, the state analysis module is used for analyzing internal and external factors influencing the addition of the internet-connected manual-driving vehicle driver into the centralized motorcade, and the reaction decision module is used for enabling a driver to quickly react to emergency through own experience knowledge and making a decision according to the information provided by the internet-connected manual-driving vehicle intelligent body and a road detector in a normal state;
the road section intelligent agent comprises a road section information module, a road section detection module and a data processing module; the road section information module comprises road section attributes, lane information and speed limit information of road sections, the road section detection module is used for detecting vehicle information, environment information and interaction information with other modules, and the data processing module is used for processing and analyzing information such as traffic capacity conditions, congestion conditions and traffic flow conditions;
the signal lamp intelligent body comprises a timing scheme module, a pre-signal control module and a main signal control module; the timing scheme module comprises an existing signal period, a signal ratio, a phase difference and a green light threshold value, the pre-signal control module comprises phase information of lanes, an induction module, traffic flow state analysis and speed induction, and the main signal control module comprises phase information of intersections, the induction module, state analysis of vehicles and corresponding speed suggestions;
the management agent comprises a system control module, a gathering analysis module and a command issuing module; the system control module comprises command receiving, task planning and feedback information, the gathering analysis module is used for analyzing the type, position and speed information of the vehicle, and the command issuing module issues commands to the vehicle according to the gathering analysis condition.
The invention has the beneficial effects that:
(1) the invention effectively combines a Multi-Agent control system, realizes real-time and dynamic sharing of traffic information among Veh-Agent, Roa-Agent and TL-Agent by utilizing the interactivity and coordination of the Multi-Agent, is suitable for the situation of CAV and CHV mixed traffic, and provides a new data source and technical means for traffic control of mixed traffic intersections.
(2) The invention is suitable for mixed traffic flow environment, combines the aggregation advantages of mixed driving teams, and provides the probability p of CHV drivers to accept the aggregation suggestionshThe adaptability of the intersection traffic control model to the future mixed traffic environment is improved, the contradiction generated by the CAV and the CHV in the driving process is effectively reduced, vehicles can drive on a longer road section in a gathering mode, the average delay and the average oil consumption of the CAV and the CHV are obviously reduced, and the traffic efficiency and the safety of road traffic can be improved to a great extent.
(3) The invention provides a dynamic virtual pre-signal concept and a speed induction strategy sent by the dynamic virtual pre-signal concept, so that a motorcade can better utilize green time of a current phase, the times of stopping and starting of vehicles are reduced, the vehicles run quickly when passing through an intersection, the stop waiting time and the average delay time of a mixed traffic intersection are obviously reduced, the congestion condition of the mixed traffic flow can be relieved, and the service level of the intersection is improved.
(4) The invention is matched with the intersection signal scheme design of the pre-signal and the suggested speed v given by the main signal control modulesThe gathering probability p of the gathering motorcade can be improved by increasing the probability that the vehicles pass through the intersection without stopping and giving priority to the gathering motorcade in the passing process, so that the willingness of CHV drivers to join the gathering motorcade can be increasedhAnd further the traffic efficiency of the whole road is improved.
Drawings
FIG. 1 is a block diagram of a centralized traffic control system for a mixed-driving intersection of networked automatic driven vehicles according to the present invention;
FIG. 2 is a flow chart of a method for controlling the cluster traffic of a hybrid vehicle fleet according to the present invention;
FIG. 3 is a schematic diagram of the aggregate traffic of a hybrid fleet controlled based on pre-signal control according to the present invention;
fig. 4 is a signal coordination timing scheme design diagram of the main signal and the pre-signal according to the present invention.
Detailed Description
The invention will be further described with reference to the following figures and specific examples, without limiting the scope of the invention.
As shown in FIG. 1, the centralized Traffic control system for the networked automatic driven mixed-driving intersection of vehicles is based on Multi-Agent (Multi-Agent), and specifically comprises Vehicle-Agent (Vehicle Agent, recorded as Veh-Agent), Road-Agent (Road segment Agent, recorded as Roa-Agent), Traffic _ Light-Agent (signal Light Agent, recorded as TL-Agent) and Management-Agent (Management Agent, recorded as Man-Agent); the Veh-Agent is divided into a CAV-Agent (network connection automatic driving vehicle intelligent Agent) and a CHV-Agent (network connection manual driving vehicle intelligent Agent), wherein the CAV-Agent comprises a sensing module, a task analysis module and a decision execution module, and the CHV-Agent comprises an information detection module, a state analysis module and a reaction decision module; Roa-Agent includes road section information module, road section detection module and data processing module; the TL-Agent comprises a timing scheme module, a pre-signal control module and a main signal control module; the Man-Agent comprises a system control module, a gathering analysis module and a command issuing module.
Each Agent (intelligent Agent) comprises a communication module and is used for carrying out real-time communication with other agents; the sensing module is used for sensing the information of the vehicle, the information of the surrounding environment, the interaction information with other modules and the like; the task analysis module is used for analyzing lane information, position information, speed information and the like of the vehicle; the decision execution module executes actions such as vehicle gathering, left-right lane changing, speed updating and the like according to the condition of the task analysis module; the information detection module is mainly responsible for detecting the Veh-Agent, other Veh-agents and the information of the surrounding environment; the state analysis module is mainly used for analyzing internal and external factors influencing CHV drivers to join the gathering motorcade; the reaction decision module is used for enabling a driver to quickly react to an emergency situation through experience knowledge of the driver and to make a decision according to the CHV-Agent and information provided by a road detector in a normal state; the timing scheme module comprises the existing information of a signal period, a signal ratio, a phase difference, a green light threshold value and the like; the pre-signal control module comprises phase information of a lane, an induction module, traffic flow state analysis and speed induction, wherein the induction module is used for inducing the arrival condition of a vehicle, the phase information and the speed induction are transmitted to the Veh-Agent in an information form through the communication module, and an independent signal lamp entity is not needed; the main signal control module comprises phase information of intersections, an induction module, state analysis of vehicles and corresponding speed suggestions; the system control module comprises command receiving, task planning and feedback information; the gathering analysis module is used for analyzing the type, position and speed information of the vehicle; the command issuing module issues commands to the vehicles according to the condition of the cluster analysis; the road section information module comprises road section attributes, lane information and speed limit information of the road section; the road section detection module is used for detecting vehicle information, environment information and interaction information with other modules; the data processing module is used for processing and analyzing information such as traffic capacity conditions, congestion conditions, traffic flow conditions and the like.
First, an aggregation command is manually input to the Man-Agent, and the Man-Agent obtains the vehicle driving state information base a ═ R, k through the Veh-Agenti,lj,xi,viAnd fourthly, judging the driving state of the Veh-Agent, selecting an aggregation target vehicle, issuing an aggregation instruction to the aggregation target vehicle, and sending an aggregation suggestion to the single CHV-Agent. Secondly, the Veh-Agent senses other vehicle information bases A ═ R, k through a sensing modulei,lj,xi,viNext, selecting a vehicle to be collected, and generating a collected vehicle group by judging a collection condition, wherein the CHV driver has a probability phAnd (4) selecting to accept the gathering suggestion and adding the gathering vehicle group. Thirdly, the pre-signal control module in the TL-Agent is used for collecting the fleet information base
Figure BDA0003426491700000071
Making a judgment as to the current speed v0Whether the parking line x can pass through the pre-signal without stoppingzOtherwise, sending speed inducing strategy to the gathering motorcade, and finally establishing speed v according to the main signal control modulesThe gathering motorcade can pass through the signalized intersection without stopping. Wherein, the vehicle number i is 1, 2.. n, the lane number j is 1, 2.. u, R is the vehicle surrounding environment information, k isiIs the own vehicle type,/jIs the lane in which the vehicle is located, xiIs the position of the vehicle, viIs the current vehicle speed.
Fig. 2 is a flow chart of the method for controlling the collective traffic of the hybrid fleet. In a road section control area, inputting an instruction to a system control module of the Man-Agent, selecting an aggregation target CAV-Agent according to the state of the mixed traffic flow, issuing an aggregation instruction to the system control module, selecting a vehicle in front of the same lane in the same direction as an aggregation object by the target CAV-Agent, judging whether the vehicle is the CAV-Agent and meets an aggregation condition, and if the vehicle meets the aggregation condition, aggregating the vehicle with a front vehicle; if not, the gathering object is replaced, whether the vehicles on the left and right adjacent lanes meet the gathering condition is judged, and if the gathering condition is met, the lane is immediately replaced
Figure BDA0003426491700000072
And a velocity viAnd position xiUpdating in real time and forming a gathering motorcade as soon as possible. Wherein the Man-Agent will send aggregation advice to a single CHV-Agent, and the CHV driver has probability phChoose to join the gathering fleet. At this time, the pre-signal control module can gather the motorcade information base
Figure BDA0003426491700000073
Making a judgment as to the current speed v0Whether the parking line x can pass through the pre-signal without stoppingzOtherwise, speed induction strategy is carried out on the gathering motorcade, when the gathering motorcade passes through the pre-signal stop line, the main signal control module carries out speed suggestion on the gathering motorcade, and the vehicle carries out speed suggestion according to the suggested speed vsThe vehicle can pass through the signalized intersection without stopping.
Fig. 3 is a schematic diagram of the collective traffic of the hybrid fleet controlled based on the pre-signal. Taking a cross intersection composed of six bidirectional lanes as an example, each entrance is provided with three lanes, namely a special left-turn lane, a special straight lane and a special right-turn lane, vehicles can change lanes before entering an unchangeable lane area, and the right-turn direction is always green. The passing road sections of all vehicles entering the intersection are divided into two parts, and the middle parts are separated by a dynamic virtual pre-signal stop line; vehicle first entering road sectionIn the control area, a CAV and CHV gathering fleet is generated in the road section control area, the generated gathering fleet occupies two left lanes, the right lane is the CHV for driving a single vehicle, the pre-signal transmits phase information to each Veh-Agent through the communication module, speed induction is carried out on the fleet in the road section control area, and then the vehicles enter the control area with the center of the intersection as the center of a circle and the radius of xzIn the intersection control area, the main signal suggests the speed of the vehicle in the intersection control area, so that the vehicle can pass through the signalized intersection without stopping.
Fig. 4 is a design diagram of a signal coordination timing scheme of a main signal and a pre-signal, and is mainly characterized by a lighting time difference between a red light and a green light. The first point is as follows: the green light starting time of the gathering motorcade of the pre-signal is earlier than the green light starting time T of the main signal, and the second point is as follows: the red light turn-on time of the gathering motorcade of the pre-signal is earlier than the red light turn-on time T of the main signal, and the third point is that: the green light starting time of the pre-signal CHV running is the same as the green light starting time of the main signal, and the fourth point is that: the red light on time of the CHV running of the bicycle of the pre-signal is earlier than the red light on time T of the main signal. Followed by the speed v suggested by the fleet in accordance with the master signal control modulesAnd (4) driving, and enabling the vehicle to pass through the signalized intersection without stopping by combining the adjusted signal timing scheme.
The invention relates to a centralized traffic control method for a mixed-driving intersection of networked automatic-driving vehicles, which specifically comprises the following steps:
step (1) forming a gathering fleet
In the road section control area, an instruction is manually input to a system control module of the Man-Agent, the Man-Agent selects the CAV-Agent positioned in the middle lane as a target vehicle through task planning and aggregation analysis, and then a motorcade aggregation instruction is issued to the target vehicle. After receiving the aggregation command, the target CAV-Agent immediately starts to select an aggregation object in the road section control area, then judges whether an aggregation condition is met, and discusses the aggregation behaviors of CAV and HPV according to situations:
the first condition is as follows: if the target CAV-Agent is CAV-Agent in the same direction and same lane front Veh-Agent
If the target CAV-Agent is CAV-Agent in the same direction and in front of the same lane, the target CAV-Agent is regarded as a gathering object and issues a gathering command to the gathering object, and because the front vehicle is also CAV-Agent, the target CAV-Agent can be used for giving a speed v of the front vehicle according to the sensing moduleiPosition xiThe change is sensed in real time, and when the distance between the target CAV-Agent and the front vehicle meets the distance condition
Figure BDA0003426491700000081
The speed v of the target CAV-Agent can be gathered with the front vehicle immediatelyiAnd position xiAnd performing real-time updating, wherein the specific updating rule is as follows:
Figure BDA0003426491700000082
wherein: g denotes a target vehicle, f denotes a preceding vehicle, l denotes a target lane, i.e., a lane in which the target vehicle is located, dgIndicates the length of the vehicle, vmaxIndicates the maximum vehicle speed, vsafeIndicating a safe vehicle speed, dgfRepresenting the distance between the target vehicle and the preceding vehicle, dmaxRepresenting the maximum distance travelled by the set in the control zone of the road section, dsafeRepresents a minimum safe distance, and
Figure BDA0003426491700000091
wherein tau isgRepresenting the reaction time of the CAV-Agent i.e. the communication and network delay time,
Figure BDA0003426491700000092
and
Figure BDA0003426491700000093
respectively representing the positions of the target vehicle and the preceding vehicle at time t,
Figure BDA0003426491700000094
and
Figure BDA0003426491700000095
respectively representing the speeds of the target vehicle and the preceding vehicle at time t,
Figure BDA0003426491700000096
representing the speed of the target vehicle at time t +1,
Figure BDA0003426491700000097
denotes the position of the vehicle ahead at time t +1, a denotes the conventional acceleration of the CAV-Agent, agAnd afRepresenting the maximum deceleration of the target vehicle and the preceding vehicle, respectively, at time t.
Target CAV-Agent same front CAV-Agent passing viAnd xiThe updating of (a) can complete the aggregation, i.e. the driving in the form of a fleet over the road section. If the distance between the target CAV-Agent and the front vehicle cannot meet the distance condition, the target CAV-Agent cannot be gathered with the front vehicle, and the gathering object needs to be replaced.
Case two: if the front Veh-Agent of the adjacent lane in the same direction of the target CAV-Agent is CAV-Agent
If the front Veh-Agent of the target CAV-Agent in the same direction and the same lane is not the CAV-Agent, the target CAV-Agent immediately searches whether the CAV-Agent exists in the front of the two adjacent lanes of the lane, if only one side of the front of the two adjacent lanes of the target CAV-Agent is the CAV-Agent, the target CAV-Agent is regarded as a gathering object, and the lane change to the lane is selected
Figure BDA0003426491700000098
If the front of the left lane and the front of the right lane are both CAV-Agents, the optimal target lane needs to be considered, and because the left lane is generally a fast lane, the left lane is selected as the target lane and is changed to the target lane, namely the lane is changed
Figure BDA0003426491700000099
Because the target vehicle and the left (right) front gathering object are CAV-agents, the target CAV-agents can be used for v of the vehicles in front of and behind the left (right) lane according to the perception moduleiAnd xiThe change is sensed in real time, and when the distance between the target CAV-Agent and the front and rear vehicles on the left (right) lane meets the distance condition
Figure BDA00034264917000000910
When the vehicle is running, the lane change can be performed to the left (right), and then the vehicle returns to the first condition; wherein: b denotes a rear vehicle which is driven by a vehicle,
Figure BDA00034264917000000911
indicating the location of the target vehicle at time t +1,
Figure BDA00034264917000000912
showing the position of the vehicle behind the adjacent lane of the road at the time t,
Figure BDA00034264917000000913
representing the speed of the vehicle behind the adjacent lane of the own lane at time t +1,
Figure BDA00034264917000000914
and the vehicle position in front of two adjacent lanes of the lane at the time of t +1 is shown.
If the distance between the target CAV-Agent and the left (right) rear vehicle meets the distance condition, the vehicle-vehicle communication technology can be used for obtaining communication with a lagging vehicle of the target lane, and under the condition that the condition is proper, the vehicle-vehicle communication technology can be used for performing collaborative cross lane change with the lagging vehicle, namely:
Figure BDA0003426491700000101
wherein the collaborative cross lane change conditions are as follows:
Figure BDA0003426491700000102
if the collaborative cross lane change condition is met, performing collaborative cross lane change, and then returning to the first condition; if not, the aggregation object needs to be replaced; wherein
Figure BDA0003426491700000103
Indicating the position of the vehicle behind the target lane at time t,
Figure BDA0003426491700000104
after the target lane is adjacent to the target lane at the time t +1The position of the party's vehicle,
Figure BDA0003426491700000105
representing the speed of the vehicle behind the target lane at time t +1,
Figure BDA0003426491700000106
representing the speed of the vehicle behind the adjacent lane of the target lane at the time of t + 1;
case three: if the target CAV-Agent is CHV-Agent in the same direction and same lane front Veh-Agent
If the target CAV-Agent searches that the Veh-Agent in the same direction and in front of the same lane and the Veh-Agent in front of the adjacent lane are both CHV-agents, the CHV-Agent in the same direction and in front of the same lane is regarded as an aggregation object and issues an aggregation suggestion to the aggregation object, and after the CHV-Agent receives the aggregation suggestion, the information detection module of the CHV-Agent immediately sets the driving state information base A of the vehicle to be { R, k ═ Ri,lj,xi,viAnalyzing whether the driver can add the gathering running or not, and calculating a recommendation coefficient of the driver which can add the gathering running through a state analysis module, namely an external factor omega influencing the CHV driver to add the gathering motorcade1ρ+ω2ratecon+ω3y + σ, wherein: rho is traffic flow density, rateconFor road congestion, y is the dominance function of CHV into the gathering fleet, and y is μ1tdelay+μ2squeue+ θ, parameter ω1Influencing specific gravity, omega, for traffic flow density2Influencing the proportion, omega, for road congestion situations3Influencing specific gravity, omega, for a lumped dominance functioniIs epsilon [0,1) and
Figure BDA0003426491700000107
σ is a random error, tdelayReduced latency, s, for adding CHV to gathering fleetsqueueReduced queue length, μ, for CHV joining gathering fleets1To reduce the influence of delay time, mu2To reduce the impact specific gravity of the queue length, muiE [0,1) and μ1+μ2θ is a random error, 1. When external ∈ (0, 0.3)]The CHV-Agent adds CHV into gathering motorcade with the primary suggestion level, reminds the driver to add into gathering motorcade; when external ∈ (0.3, 0.6)]The recommendation level of the CHV-Agent for adding the CHV into the gathering motorcade is a middle level, and the driver is reminded and recommended to add the CHV into the gathering motorcade; when external ∈ (0.6,1), the CHV-Agent's recommendation level for CHV to join the gathering fleet is high, reminding the driver and strongly recommending the driver to join the gathering fleet.
Internal factors influencing CHV drivers to join the gathering fleet can be calculated according to the following formula:
Figure BDA0003426491700000111
in the above formula, alphajThe main influence factors indicating whether the driver accepts the aggregated advice, such as the personal character, experience, acceptance of guidance information, familiarity with surrounding roads, etc., of the driver, ηjThe relative weights of the various influencing factors are expressed and artificially specified empirically, and δ represents the random error.
In consideration of the complexity of CHV drivers, the invention introduces the fuzzification idea that the driver accepts the suggestion of gathering driving, and the acceptance probability is the acceptance degree phValue of [0,1]0 indicates that the driver does not accept the aggregation suggestion, and 1 indicates that the driver accepts the aggregation suggestion; therefore, it is judged whether the CHV can join the gathering vehicle group or not, and the driver's acceptance phThe recommendation coefficient given by the CHV-Agent and the internal influence factor are restricted together and can be calculated according to the Bayes conditional probability as follows:
Figure BDA0003426491700000112
if the front CHV driver agrees to join the gathering fleet, then go back to condition one, where the minimum safe separation of the gathering fleet is
Figure BDA0003426491700000113
τhThe response time of the CHV-Agent is represented by including the response time of the driver, the communication and the network delay time.
If the CHV driver fails to hear the suggestion and the single vehicle lags, the human driver can flexibly choose to rejoin the gathering fleet and also choose whether to gather and form the fleet with the next gathering target vehicle.
Step (2) speed induction process for pre-signal control
When the gathered motorcade runs in the road section control area, the pre-signal control module can control the motorcade according to the gathered motorcade information base
Figure BDA0003426491700000114
And the remaining green time t of the current phaseeAnd judging whether the automobile can pass through the pre-signal parking line without stopping. The pre-signal control module has four different speed inducing strategies for the gathered motorcade, namely a constant speed inducing strategy, an accelerating strategy, a decelerating strategy and a parking inducing strategy, and the communication module can induce the speed inducing strategy and the parking line position xzAnd the current phase information is sent to each Veh-Agent in real time.
The case-by-case discussion here is based on different speed-inducing strategies:
the first condition is as follows: if the current motorcade can pass through the pre-signal stop line without stopping under the uniform speed control strategy
The pre-signal control module is used for storing the information of the gathered fleet
Figure BDA0003426491700000115
And the remaining green time t of the current phaseeMaking a decision that the vehicle fleet is at the current vehicle speed v0And (3) running at a constant speed, judging whether the vehicle can pass through a pre-signal stop line without stopping, wherein the judgment condition of the constant speed control strategy is as follows:
Figure BDA0003426491700000121
wherein:
Figure BDA0003426491700000122
indicating the head vehicle position, n, of the current cluster fleetqIndicating the number of vehicles included in the fleet, dcIndicating the spacing of vehicles in a cluster fleet, v0Indicating the current speed of the fleet, teIndicating the remaining green time duration for the current phase.
If the speed v of the current motorcade is0If the judgment condition is met, the gathering motorcade can follow the current speed v0And (4) continuing to drive at a constant speed, and not intervening the speed by the pre-signal control module.
Wherein the uniform speed control strategy is as follows: v (t) min { v ═ v0,vmax}。
If the first vehicle passes the stop line of the pre-signal and there are vehicles continuously joining the gathering motorcade, the green time of the pre-signal will be based on the number n of the vehicles joining the motorcadecThe time t of the green light is prolongedcNumber n of vehicles added to fleetcIs proportional, i.e.
Figure BDA0003426491700000123
When the head car has reached the main signal stop line
Figure BDA0003426491700000124
Or reaches the preset maximum green light time tg＝tmaxAnd the current green light phase time is cut off, and the pre-signal control module reserves 3 seconds of yellow light time for phase switching.
Case two: if the current motorcade can pass through the pre-signal stop line without stopping under the acceleration control strategy
If the gathering motorcade is at the current speed v0The pre-signal stop line cannot be smoothly passed under the condition of uniform-speed running, and at the moment, the acceleration control strategy judgment is carried out on the fleet, and the acceleration control strategy judgment conditions are as follows:
Figure BDA0003426491700000125
wherein: t is taIndicating acceleration to the highest speed permitted for the road segmentThe time required for the formation of
Figure BDA0003426491700000126
vmaxIndicating the highest speed allowed for the road segment.
If the gathering motorcade meets the acceleration control condition, the pre-signal control module guides the motorcade to slowly accelerate to the highest speed v allowed by the road section at the acceleration amaxThen the vehicle runs at a constant speed, namely the green time t can be remained in the current phaseeNo-parking passing pre-signal parking line xz。
Similarly, if the first vehicle passes through the pre-signal stop line and continuously adds the vehicles into the gathering motorcade, the green time of the pre-signal can be properly prolonged, and the green time can be prolonged
Figure BDA0003426491700000127
When in use
Figure BDA0003426491700000128
Or to tg＝tmaxAnd the green lamp phase time is cut off, and the pre-signal control module also reserves 3 seconds of yellow lamp time for phase switching.
The acceleration control strategy is as follows: v (t) min { v ═ v0+at,vmax}。
Case three: if the current motorcade can pass through the pre-signal stop line without stopping under the deceleration control strategy
If the current gathering motorcade does not meet the uniform speed control strategy or the acceleration control strategy, judging whether the motorcade meets the deceleration control strategy or not, wherein the judgment conditions of the deceleration control strategy are as follows:
Figure BDA0003426491700000131
wherein: t is tdIndicating the time required to decelerate to the lowest speed permitted for the road section, i.e.
Figure BDA0003426491700000132
vminIndicating the lowest speed allowed for the road section, trIndicating waiting for the next green light on time.
If the gathering motorcade meets the deceleration control condition, the pre-signal control module can guide the motorcade to decelerate to the lowest speed v allowed by the road section at the acceleration aminThen the vehicle runs at a constant speed, namely the green time t can be remained at the current phaseeThe vehicle passes through the pre-signal stop line without stopping. The deceleration control strategy is as follows: v (t) max { v0-at,vmin}。
Similarly, if the first vehicle passes through the pre-signal stop line and continuously has vehicles to join the gathering motorcade, the green time of the pre-signal is properly prolonged, and the green time is prolonged
Figure BDA0003426491700000133
When in use
Figure BDA0003426491700000134
Or to tg＝tmaxAnd the green lamp phase time is cut off, and the pre-signal control module also reserves 3 seconds of yellow lamp time for phase switching.
Case four: if the current fleet can not pass through the pre-signal stop line in the remaining green light time of the current phase
If the motorcade can not pass through the stop line without stopping under the constant speed, acceleration and deceleration strategies, the pre-signal control module adopts an induced parking strategy for the vehicle, and the induced parking judgment conditions are as follows:
Figure BDA0003426491700000135
if the gathering motorcade meets the condition of guiding parking, the pre-signal control module guides the motorcade to accelerate at an acceleration asThe speed is slowly reduced, so that rear-end accidents caused by untimely braking of the rear vehicle are prevented, and the speed is reduced to zero just before a stop line.
The induced parking control strategy is as follows: v (t) max { v }0-ast,0}, wherein
Figure BDA0003426491700000136
At this moment, the gathering motorcade needs to stop for waiting, and the vehicles can pass through the pre-signal parking line only after the green light time of the next phase is lightened.
Step (3) matched with intersection signal scheme design of pre-signal control
Since the traffic flow of urban roads can be greatly different in different time periods, the distance between the main pre-signal stop lines must meet the requirement of CAV gathering traffic at the moment, which is mainly determined by the arrival rate Q of vehiclesmPermeability of CAV, raCHV driver acceptance phThe number u of gathering lanes controlled by the pre-signal and the time length t of red light of the main signalrSafe spacing d when gathering motorcade parkssAnd length d of individual vehicleg. Wherein the position of the pre-signal stop line is represented by the formula
Figure BDA0003426491700000141
Determined and may be based on traffic information C ═ { Q) obtained from Roa-Agentm，ra，ph，tr，dg，dsU, to meet the needs of different traffic flow conditions.
Wherein: x is the number ofzIndicating the position of the pre-signal stop line, QmIndicating the arrival rate (veh/h), r of the vehicleaThe permeability of the CAV is shown,
Figure BDA0003426491700000142
na、nhrepresenting traffic flow, p, of CAV and CHV, respectivelyhIndicates the acceptance of the CHV driver, trIndicating the red light duration(s), d) of the main signalgRepresenting the length (m), d) of a single vehiclesThe safe interval (m) of the gathering motorcade when parking is shown, and u represents the gathering lane number controlled by the pre-signal.
When the gathered motorcade passes through the pre-signal stop line, the motorcade enters the intersection control area, and then enters different lanes according to the steering requirements of the motorcade and the main signalThe signal control module sends speed suggestions to vehicles entering the intersection control area according to the suggested speed vsThe running is matched with the coordination timing scheme of the main signal and the pre-signal, so that the automobile can pass through the current main signal intersection without stopping. According to the position x of the pre-signal stop linezAnd the suggested speed v of the main signal to the vehiclesObtaining the time T of the vehicle from the pre-signal stop line to the main signal stop line, wherein
Figure BDA0003426491700000143
In the design of the coordinated timing scheme of the main signal and the pre-signal, the time difference of the turn-on of the red light and the turn-on of the green light is emphasized, as shown in fig. 4.
The first point is as follows: the green light turn-on time of the gathering motorcade of the pre-signal is earlier than the green light turn-on time T of the main signal, namely when the green light of the main signal turns on, the gathering motorcade turns on according to the suggested speed v of the main signalsAnd the vehicle runs just to the stop line of the main signal, and then can pass through the intersection without stopping.
And a second point: the red light turn-on time of the gathering motorcade of the pre-signal is also earlier than the red light turn-on time T of the main signal, so that the gathering motorcade passing through the pre-signal is prevented from being incapable of passing through a stop line of the main signal, and the parking waiting time, delay time and fuel consumption of the motorcade are further increased.
And a third point: the green light starting time of the CHV single vehicle running of the pre-signal is the same as that of the main signal, namely the green light starting time is later than that of the gathering motorcade, so that the single CHV can enter the intersection behind the gathering motorcade, the gathering motorcade is given priority to enter the intersection, and the gathering will of the driver is improved.
A fourth point: the red light starting time of the CHV single vehicle running of the pre-signal is earlier than the red light starting time T of the main signal, namely the red light starting time of the gathering motorcade of the pre-signal is synchronous, so that vehicles entering the intersection control area completely pass through the intersection in the remaining time, all vehicles in the intersection control area are emptied, and paving is well carried out on the gathering motorcade of the next phase for passing through the intersection without stopping.
Therefore, by the coordinated design of the main signal and the pre-signal, the average delay time and the fuel consumption of the vehicle can be reduced, and the acceptance p of the CHV driver to join the gathering motorcade can be improvedhThe gathering proportion of the gathering motorcade is improved, and the traffic efficiency of the whole road is further improved.
The present invention is not limited to the above-described embodiments, and any obvious improvements, substitutions or modifications can be made by those skilled in the art without departing from the spirit of the present invention.

Claims (10)

1. A gathering and passing method for a network connection automatic driving vehicle mixed-driving intersection is characterized by comprising the following steps:
in a road section control area, selecting an aggregation target internet automatic driving vehicle intelligent body according to the state of mixed traffic flow, receiving an aggregation instruction by the internet automatic driving vehicle intelligent body, firstly selecting a vehicle in front of a same lane in the same direction as an aggregation object by the target internet automatic driving vehicle intelligent body, judging whether the vehicle is the internet automatic driving vehicle intelligent body and meets an aggregation condition, and if the vehicle is the internet automatic driving vehicle intelligent body and meets the aggregation condition, aggregating the vehicle with a front vehicle; if the vehicle is not met, the gathering objects are replaced, whether the vehicles in front of the left and right adjacent lanes are internet-connected automatic driving vehicle intelligent bodies or not is continuously judged, and the gathering conditions are met, if the vehicle is met, the lane is immediately changed, and the gathering is carried out with the front vehicle after the lane is changed; if not, selecting the networking manually-driven vehicle in the front of the same lane in the same direction as the gathering object, judging whether the gathering condition is met, and if so, gathering; when gathering, updating the speed and the position in real time to form a gathering motorcade; in the gathering process, the internet-connected manually-driven vehicle intelligent agent has probability phSelecting to join the gathering motorcade;
according to the information base of the gathering fleet
Figure FDA0003426491690000011
And the remaining green time t of the current phaseeFor gathering fleets of vehiclesJudging whether the speed can pass through a pre-signal stop line without stopping, and otherwise, carrying out a speed induction strategy on the gathering motorcade; wherein R is vehicle surrounding environment information, kiIs the own vehicle type,/jIs the lane in which the vehicle is located, xiIs the position of the vehicle, viFor the current vehicle speed, nqTo gather the captain of a fleet, v0In order to cluster the vehicle speeds of a fleet of vehicles,
Figure FDA0003426491690000012
in order to gather the head vehicle position of the fleet, the vehicle number i is 1, 2.. n, and the lane number j is 1, 2.. u;
after the gathering motorcade passes through the pre-signal stop line, speed suggestion is carried out on the gathering motorcade, vehicles run according to the suggested speed, and the vehicles pass through the signalized intersection without stopping by matching with a coordination timing scheme of the main signal and the pre-signal.
2. The collective passing method for intersections of networked automatically-driven vehicles on mixed roads according to claim 1, wherein there is a probability p of the intelligent agents of networked manually-driven vehicleshSelectively joining a fleet of gathering vehicles, said phComprises the following steps:
Figure FDA0003426491690000013
∝P(internal,external|receive)P(receive)
＝P(external,receive|internal)P(internal)
＝P(external|internal)P(receive|internal)P(internal)
wherein: the receiver indicates that the driver receives the suggestion of gathering driving, the internal indicates the internal factors influencing the internet connection manual driving vehicle driver to join the gathering motorcade, and the external indicates the external factors influencing the internet connection manual driving vehicle driver to join the gathering motorcade.
3. The collective passing method for the intersections of the networked automatic driven vehicles according to claim 2, wherein the images are collectedExternal factor of gathering motorcade added by network-connected man-driven vehicle intelligent agent1ρ+ω2ratecon+ω3y + σ, where parameter ω1Influencing specific gravity, omega, for traffic flow density2Influencing the proportion, omega, for road congestion situations3Influencing specific gravity, omega, for a lumped dominance functioniIs epsilon [0,1) and
Figure FDA0003426491690000021
rho is the traffic flow density; rateconThe condition is road congestion; y is the dominance function y ═ mu of CHV added to the gathering fleet1tdelay+μ2squeue+θ，tdelayReduced delay time, s, for networked manually driven vehicles to join a cluster fleetqueueThe queuing length which can be reduced by adding the gathering motorcade to the networked manually-driven vehicles; mu.s1To reduce the influence of delay time, mu2To reduce the impact specific gravity of the queue length, muiEpsilon [0,1) and mu1+μ21 is ═ 1; both theta and sigma are random errors;
when the external belonged to (0, 0.3), the suggestion level of the internet man-made driving vehicle intelligent body for adding the internet man-made driving vehicle into the gathering motorcade is primary, the driver is reminded to add the gathering motorcade, when the external belonged to (0.3, 0.6), the suggestion level of the internet man-made driving vehicle intelligent body for adding the internet man-made driving vehicle into the gathering motorcade is intermediate, the driver is reminded and is suggested to add the gathering motorcade, and when the external belonged to (0.6,1), the suggestion level of the internet man-made driving vehicle intelligent body for adding the internet man-made driving vehicle into the gathering motorcade is advanced, the driver is reminded and is strongly suggested to add the gathering motorcade.
4. The collective passing method for intersections of networked automatically-driven vehicles on mixed roads according to claim 2, wherein the networked manually-driven vehicle agent has a probability phInternal factors influencing adding of internet-connected manually-driven vehicle intelligent bodies into gathering motorcade by selecting to add into gathering motorcade
Figure FDA0003426491690000022
αjA main influencing factor, eta, representing whether the driver accepts the aggregated advicejRepresenting the relative weight of each influencing factor and delta representing the random error.
5. The collective traffic method for the intersections of online automatic driven vehicles according to claim 1, wherein the real-time update of the speed and the position is performed according to the following rules:
Figure FDA0003426491690000023
wherein:
Figure FDA0003426491690000024
representing the speed of the target vehicle at time t +1,
Figure FDA0003426491690000025
representing the speed of the target vehicle at time t, a representing the conventional acceleration of the networked autonomous vehicle agent, vmaxRepresents the maximum vehicle speed allowed for the road segment,
Figure FDA0003426491690000026
indicates the position of the preceding vehicle at time t +1, dgfRepresenting the distance between the target vehicle and the preceding vehicle, dsafeIndicates the minimum safety distance, vsafeIndicating the safe vehicle speed for the road segment.
6. The method as claimed in claim 1, wherein before the target networked automatic vehicle intelligent object changes lanes, it is determined whether the distance between the vehicles in front of and behind the adjacent lanes meets the requirement
Figure FDA0003426491690000027
If the distance between the front and rear vehicles of the adjacent lane does not satisfy the above conditionAnd then the target internet automatic driving vehicle intelligent agent and the lagging vehicle of the target lane perform collaborative cross lane changing, wherein the collaborative cross lane changing conditions are as follows:
Figure FDA0003426491690000031
wherein
Figure FDA0003426491690000032
Indicating the location of the target vehicle at time t +1,
Figure FDA0003426491690000033
showing the position of the vehicle behind the adjacent lane of the lane at the time t,
Figure FDA0003426491690000034
representing the speed of the vehicle behind the adjacent lane of the lane at time t +1,
Figure FDA0003426491690000035
shows the vehicle position in front of two adjacent lanes of the vehicle lane at the time of t +1,
Figure FDA0003426491690000036
indicating the position of the target vehicle at time t,
Figure FDA0003426491690000037
representing the speed of the target vehicle at time t +1,
Figure FDA0003426491690000038
indicating the position of the vehicle behind at time t,
Figure FDA0003426491690000039
indicating the position of the vehicle behind the adjacent lane of the target lane at time t +1, dsafeRepresenting the minimum safe separation.
7. The gathering and passing method at the intersection for the internet-connected automatic driven vehicles to travel in mixed mode according to claim 1, wherein whether the gathering motorcade can pass through a pre-signal stop line without stopping at the current speed is judged, and the control strategies comprise constant speed, acceleration, deceleration and parking induction;
the judgment condition of the uniform speed control strategy is as follows:
Figure FDA00034264916900000310
wherein d isgIndicates the vehicle length, dcRepresenting the spacing of the vehicles in the gathering fleet;
the judgment conditions of the acceleration control strategy are as follows:
Figure FDA00034264916900000311
wherein t isaRepresenting the time required to accelerate to the highest speed permitted for the road section, vmaxRepresents the maximum speed allowed for the road segment;
the deceleration judgment conditions are as follows:
Figure FDA00034264916900000312
wherein t isdIndicating the time required to decelerate to the lowest speed permitted for the road section, trIndicating waiting for the next green light on time, vminRepresents the minimum speed allowed for the road segment;
the judgment conditions of the induced parking control strategy are as follows:
Figure FDA00034264916900000313
8. the collective traffic method at the intersection for mixed-driving of networked automatic driven vehicles according to claim 1, wherein the position of the pre-signal stop line is determined according to traffic information C ═ { Q ═ Qm,ra,ph,tr,dg,dsAnd u, dynamically adjusting in real time according to different conditions of the parking line, wherein the position of the pre-signal parking line is as follows:
Figure FDA00034264916900000314
wherein QmFor indicating vehiclesArrival rate raIndicating the permeability, p, of an on-line autonomous vehiclehIndicating the acceptance of the network connection manually driven vehicle driver, trIndicating the duration of the red light of the main signal, dgRepresenting the length of a single vehicle, dsThe safety distance of the gathering motorcade when parking is shown, and u represents the gathering lane number controlled by the pre-signal.
9. The collective traffic method at the intersection of online automatic driven mixed-road vehicles according to claim 1, wherein the coordination timing scheme of the main signal and the pre-signal is adjusted on the basis of the signal timing as follows: the green light turning-on time of the gathering motorcade of the pre-signal is earlier than that of the main signal, the red light turning-on time of the gathering motorcade of the pre-signal is earlier than that of the main signal, the green light turning-on time of the driving of the bicycle networking manual driving vehicle of the pre-signal is the same as that of the main signal, and the red light turning-on time of the driving of the bicycle networking manual driving vehicle of the pre-signal is earlier than that of the main signal.
10. A control system for implementing the collective passing method for the internet-connected automatic driving vehicle mixed-road intersection as claimed in any one of claims 1 to 9, comprising:
the vehicle intelligent bodies are divided into a network connection automatic driving vehicle intelligent body and a network connection manual driving vehicle intelligent body; the networked automatic driving vehicle intelligent body comprises a sensing module, a task analysis module and a decision execution module, wherein the sensing module is used for sensing own vehicle information, surrounding environment information and interaction information with other modules, the task analysis module is used for analyzing lane information, position information and speed information of a vehicle, and the decision execution module is used for executing vehicle gathering, left-right lane changing and speed updating according to the condition of the task analysis module; the internet-connected manual-driving vehicle intelligent body comprises an information detection module, a state analysis module and a reaction decision module, wherein the information detection module is used for detecting information of the vehicle intelligent body, other vehicle intelligent bodies and the surrounding environment, the state analysis module is used for analyzing internal and external factors influencing the addition of the internet-connected manual-driving vehicle driver into the gathered motorcade, and the reaction decision module is used for enabling the driver to quickly react to emergency through self experience knowledge and making a decision according to the information provided by the internet-connected manual-driving vehicle intelligent body and the on-road detector in a normal state;
the road section intelligent agent comprises a road section information module, a road section detection module and a data processing module; the road section information module comprises road section attributes, lane information and speed limit information of a road section, the road section detection module is used for detecting vehicle information, environment information and interaction information with other modules, and the data processing module is used for processing and analyzing information such as traffic capacity conditions, congestion conditions and traffic flow conditions;
the signal lamp intelligent body comprises a timing scheme module, a pre-signal control module and a main signal control module; the timing scheme module comprises an existing signal period, a signal ratio, a phase difference and a green light threshold value, the pre-signal control module comprises phase information of lanes, an induction module, traffic flow state analysis and speed induction, and the main signal control module comprises phase information of intersections, the induction module, state analysis of vehicles and corresponding speed suggestions;
the management agent comprises a system control module, a gathering analysis module and a command issuing module; the system control module comprises command receiving, task planning and feedback information, the gathering analysis module is used for analyzing the type, position and speed information of the vehicle, and the command issuing module issues commands to the vehicle according to the gathering analysis condition.
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