CN116740945A - Method and system for multi-vehicle collaborative grouping intersection of expressway confluence region in mixed running environment - Google Patents
Method and system for multi-vehicle collaborative grouping intersection of expressway confluence region in mixed running environment Download PDFInfo
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Abstract
The application discloses a method and a system for combining and converging multiple vehicles in a rapid road converging area under a mixed running environment, which relate to the technical field of intelligent control of vehicles and comprise the steps of taking intelligent network vehicles and manual driving vehicles as research objects and establishing a vehicle constraint model; grouping vehicles on the ramp in the confluence area; acquiring vehicle information, and mapping a main road and a ramp vehicle to the same lane in a virtual mapping mode; and constructing a multi-vehicle cooperative grouping intersection model, realizing the safe convergence of ramp vehicles, and improving the road network passing efficiency. The method constructs a novel multi-vehicle cooperative intersection strategy of the rapid road merging area under the mixed traffic environment, and solves the problems of lack of research on the multi-mode vehicle mixed marshalling process strategy and traffic of the merging area.
Description
Technical Field
The application belongs to the technical field of intelligent control of vehicles, and particularly relates to a method and a system for multi-vehicle collaborative marshalling intersection of a rapid road merging area in a mixed running environment.
Background
In recent years, with the rapid increase of the quantity of the reserved automobiles, a series of problems such as traffic jam, traffic accidents, environmental pollution and the like are brought to cities, and a converging area formed at the junction of a main road and a ramp becomes an important node for the frequent occurrence of the traffic accidents and the congestion. Vehicles running on the ramp must enter the main road after passing through the accelerating lane to finish lane change, but unpredictable behaviors can have negative influence on traffic due to different entering moments and entering gaps selected by drivers. The intelligent networking and automatic driving technologies provide a new solution for solving the traffic problem in the confluence area. Information such as the speed and the position of the intelligent network-connected vehicles in the communication area of the converging area is collected and transmitted to the road side infrastructure for communication, the road side infrastructure exchanges information with the control center, the control center calculates the running speed of the vehicles and transmits the running speed to the vehicles, and the control of the vehicles is achieved. Therefore, a novel multi-vehicle cooperative intersection strategy of the rapid road merging area under the mixed traffic environment is constructed, and the method has important significance for improving the traffic efficiency and traffic safety of the merging area.
At present, control strategies of an integrated area in the prior art are mainly divided into vehicle speed guiding and vehicle queuing. For vehicle speed guidance, most of the consideration is the merging of one ramp vehicle and a few related main road vehicles in a merging area, but only a few vehicles are used for generating safe and stable merging tracks; for vehicle fleet studies, fleets are built by intelligent networked vehicles communicating with each other, but there is a lack of research on multi-mode vehicle hybrid consist process strategies.
Disclosure of Invention
This section is intended to outline some aspects of embodiments of the application and to briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this section as well as in the description of the application and in the title of the application, which may not be used to limit the scope of the application.
The present application has been made in view of the above-described problems occurring in the prior art.
Therefore, the application provides a multi-vehicle collaborative grouping intersection method for a rapid road merging area in a mixed running environment, the model aims at improving the ramp and road network passing efficiency, and the vehicle maneuvering performance can be improved on the premise of ensuring the safety.
In order to solve the technical problems, the application provides a method for combining multiple vehicles in a rapid road merging area under a mixed running environment, which comprises the following steps:
taking intelligent network vehicles and manual driving vehicles as research objects, and establishing a vehicle constraint model;
grouping vehicles on the ramp in the confluence area;
acquiring vehicle information, and mapping a main road and a ramp vehicle to the same lane in a virtual mapping mode;
the method comprises the steps of constructing a multi-vehicle cooperative grouping intersection model, calculating traffic efficiency and realizing safe ramp vehicle import, wherein the multi-vehicle cooperative grouping intersection model comprises the steps of forming vehicles on a main line and a ramp into C-CHDV vehicle queues through formation, and providing that only one CAV exists in each C-CHDV vehicle queue, the rest are HDVs, wherein the expression is as follows:
；
wherein ,representing a binary variable>Indicating the number of HDVs in the C-CHDV fleet, and (2)>If->If the vehicle team has no HDV, otherwise, the number of the HDVs is at least 1, and h represents the vehicles in the vehicle team;
after the number of HDVs is determined in the area detector, the length of the fleet can be obtained:
；
where i represents the index value of the ith C-HDV fleet,indicating the length of the ith C-HDV fleet, t indicates time, +.>Indicating the position of the head car CAV in the ith C-HDV fleet at time t,/->Indicating the position of the last HDV in the ith C-HDV motorcade at the time t, and l indicating the vehicle length;
the position of the first HDV in the fleet at a certain moment:
；
wherein ,indicate->The first HDV in the individual C-HDV fleet is at time +.>Is (are) located>Indicating response delay time, +.>Indicate->The first HDV in the individual C-HDV fleet is at time +.>Is a function of the speed of the machine.
As a preferable scheme of the multi-vehicle collaborative grouping intersection method of the rapid transit confluence area under the mixed running environment, the application comprises the following steps: the vehicle restraint model includes a model of the vehicle,
；
wherein ,indicating the position of the vehicle i at time t +.>Indicating the speed of the vehicle i at time t +.>The acceleration of the vehicle i at time t is shown.
As a preferable scheme of the multi-vehicle collaborative grouping intersection method of the rapid transit confluence area under the mixed running environment, the application comprises the following steps: the grouping of the junction ramp vehicles includes,
when a vehicle enters a road network, vehicle information on a ramp area detector is acquired, the type of the vehicle is judged, if the vehicle is CAV, the vehicle is controllable, the vehicle is used as a marshalling head vehicle, if the vehicle is HDV, the vehicle is used as a rear vehicle to follow the CAV, the CAV in the ramp area detector is numbered, one CAV represents that a vehicle team exists, whether the HDV follows after the CAV is judged, if the vehicle is judged, the number of the vehicles of the vehicle team is increased until the maximum scale of 4 vehicles in the vehicle team is reached, if the HDV between the adjacent CAVs exceeds three vehicles, the vehicle is ignored, and when the number of the vehicles in the vehicle team reaches the maximum scale or the head vehicle leaves the end point of the area detector, the marshalling is ended.
As a preferable scheme of the multi-vehicle collaborative grouping intersection method of the rapid transit confluence area under the mixed running environment, the application comprises the following steps: mapping the host road and ramp vehicles to the same lane includes,
determining a passing sequence according to positions of vehicles reaching the main road area detector and the ramp area detector, determining front and rear auxiliary vehicles on the main road, mapping ramp vehicles to the main road in a virtual mapping mode, sequencing the passing sequence according to the positions, forming corresponding virtual vehicles, and planning vehicles on different lanes.
As a preferable scheme of the multi-vehicle collaborative grouping intersection method of the rapid transit confluence area under the mixed running environment, the application comprises the following steps: the multi-vehicle cooperative grouping intersection model comprises the following steps that the safety distance required to be kept by adjacent C-HDV motorcades on a main line and a ramp is expressed as:
；
wherein ,representing that the first car CAV in the C-HDV fleet on the ramp is +.>The position of the moment in time,representing that the head car CAV in the C-HDV fleet on the main road is +.>Position of moment->Representing that the head car CAV in the C-HDV fleet on the main road is +.>Speed of moment->Indicating the acceleration or deceleration of the running of the vehicle;
the safety distance to be kept when the main line and the ramp are converged is as follows:
；
as a preferable scheme of the multi-vehicle collaborative grouping intersection method of the rapid transit confluence area under the mixed running environment, the application comprises the following steps: the calculation of the traffic efficiency comprises the steps of selecting the number of vehicles passing through the road network and the average loss time of the vehicles according to the traffic efficiency index, wherein the calculation formula of the MTL is as follows:
；
wherein ,representing the total number of vehicles on the main road>Representing the total number of vehicles on the ramp->Representing the travel time of the host road vehicle i on the road network,/->Indicating the travel time of ramp vehicle j on the road network,/->Indicating the distance travelled by the main road vehicle, +.>Indicating the distance travelled by the ramp vehicle, +.>Average speed representing the driving course of the main road vehicle,/->Average speed of the vehicle during driving on the ramp, < > is indicated>Desired vehicle speed indicative of CAV or HDV on ramp,/->Representing a desired vehicle speed of the CAV;
to ensure that vehicle speed and acceleration are within safe ranges, constraints include,
；
wherein ,representing the minimum allowable speed of the vehicle,/->Indicating the maximum allowable speed of the vehicle,/->Representing the minimum allowed acceleration of the vehicle,/->Indicating the maximum allowable acceleration.
The application further aims to provide a multi-vehicle cooperative grouping intersection system of the rapid road merging area in a mixed traffic environment, which can solve the problems of low traffic efficiency and frequent traffic safety accidents of the existing merging area by constructing a novel cooperative intersection strategy of the rapid road merging area in the mixed traffic environment.
The system of the multi-vehicle collaborative grouping intersection method of the expressway confluence area in the mixed running environment is characterized by comprising a sensing module, a data processing module, a control module, a communication module, a multi-vehicle collaborative grouping module and a navigation and driving auxiliary module;
the sensing module is used for acquiring the position, speed and running direction information of vehicles, pedestrians and other traffic participants, monitoring traffic conditions on a road in real time and providing basis for subsequent traffic control and planning;
the data processing module is used for processing the data acquired by the sensing module, analyzing the traffic condition and generating a traffic control instruction;
the control module is used for controlling signal lamps and signboards on a road according to the traffic control instruction generated by the data processing module, so that vehicles and pedestrians can safely pass through the converging area;
the communication module is responsible for communication between the traffic management center and the vehicle, the vehicle receives real-time traffic information through communication with the traffic management center, and the speed and the driving route of the vehicle are controlled through the communication module;
the multi-vehicle cooperative grouping module is responsible for communication and coordination among a plurality of vehicles and guiding the vehicles to meet and group in an optimized mode;
the navigation and driving assistance module provides real-time navigation and traffic information for a driver through the vehicle-mounted equipment and provides an automatic driving assistance function for the driver, so that the vehicle can safely run in the confluence area.
The computer equipment comprises a memory and a processor, wherein the memory stores a computer program, and the computer program is characterized in that the processor realizes the steps of the method for combining and combining multiple vehicles in a rapid transit merging area in a mixed running environment when executing the computer program.
A computer readable storage medium having stored thereon a computer program, wherein the computer program when executed by a processor implements the steps of a method for collaborative marshalling and intersection of multiple vehicles in a highway merge area in a mixed-line environment.
The application has the beneficial effects that: the application is based on a novel mixed traffic environment scene, namely, a CAV special lane is arranged at the outer side of a main road, and judgment is carried out when a ramp is a mixed lane, so that the combination of vehicles of the main road related to a plurality of vehicles in the ramp in a combination area is considered, meanwhile, information such as the speed, the position and the like of intelligent network vehicles in a communication area of a converging area is collected, and information is exchanged with a road side infrastructure and a control center, thereby realizing the control of the vehicles, improving the passing efficiency of the converging area and ensuring traffic safety.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for the description of the embodiments will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present application, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art. Wherein:
fig. 1 is a flow chart of cooperative control of vehicles in a merging area of a multi-vehicle cooperative grouping merging method in a fast road merging area under a mixed running environment according to an embodiment of the present application.
Fig. 2 is a schematic diagram of a rapid transit merging area merging in a mixed traffic environment by using a multi-vehicle cooperative grouping merging method in a mixed traffic environment according to an embodiment of the present application.
Fig. 3 is a traffic scene diagram of a method for merging multiple vehicles in a highway and a junction area under a mixed running environment according to an embodiment of the present application.
Fig. 4 is a schematic diagram of a method for merging multiple vehicles in a highway and a merge area in a hybrid environment according to an embodiment of the present application, wherein the number of vehicles passes through the method under a control strategy of vehicle-based group.
Fig. 5 is a schematic workflow diagram of a rapid transit merging area multi-vehicle collaborative grouping intersection system in a mixed traffic environment according to an embodiment of the present application.
Detailed Description
So that the manner in which the above recited objects, features and advantages of the present application can be understood in detail, a more particular description of the application, briefly summarized above, may be had by reference to the embodiments, some of which are illustrated in the appended drawings. All other embodiments, which can be made by one of ordinary skill in the art based on the embodiments of the present application without making any inventive effort, shall fall within the scope of the present application.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present application, but the present application may be practiced in other ways other than those described herein, and persons skilled in the art will readily appreciate that the present application is not limited to the specific embodiments disclosed below.
Further, reference herein to "one embodiment" or "an embodiment" means that a particular feature, structure, or characteristic can be included in at least one implementation of the application. The appearances of the phrase "in one embodiment" in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments.
While the embodiments of the present application have been illustrated and described in detail in the drawings, the cross-sectional view of the device structure is not to scale in the general sense for ease of illustration, and the drawings are merely exemplary and should not be construed as limiting the scope of the application. In addition, the three-dimensional dimensions of length, width and depth should be included in actual fabrication.
Also in the description of the present application, it should be noted that the orientation or positional relationship indicated by the terms "upper, lower, inner and outer", etc. are based on the orientation or positional relationship shown in the drawings, are merely for convenience of describing the present application and simplifying the description, and do not indicate or imply that the apparatus or elements referred to must have a specific orientation, be constructed and operated in a specific orientation, and thus should not be construed as limiting the present application. Furthermore, the terms "first, second, or third" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.
The terms "mounted, connected, and coupled" should be construed broadly in this disclosure unless otherwise specifically indicated and defined, such as: can be fixed connection, detachable connection or integral connection; it may also be a mechanical connection, an electrical connection, or a direct connection, or may be indirectly connected through an intermediate medium, or may be a communication between two elements. The specific meaning of the above terms in the present application will be understood in specific cases by those of ordinary skill in the art.
Example 1
Referring to fig. 1, fig. 2 and fig. 3, a first embodiment of the present application provides a method for merging multiple vehicles in a highway and a confluence area in a mixed running environment, including:
s1: and taking the intelligent network-connected vehicle and the manual driving vehicle as research objects to establish a vehicle constraint model.
Still further, the vehicle restraint model includes,
；
wherein ,the position of the vehicle i at time t is indicated,/>indicating the speed of the vehicle i at time t +.>The acceleration of the vehicle i at time t is shown.
S2: and grouping the ramp vehicles in the confluence area.
Furthermore, when the vehicle enters the road network, the vehicle information on the ramp area detector is acquired, the type of the vehicle is judged, if the vehicle is CAV, the vehicle is controllable, and if the vehicle is HDV driven manually, the vehicle is CAV to be followed by the following vehicle. The CAVs within the ramp area detectors are numbered, one CAV representing the presence of a fleet. Judging whether the HDV is followed after the CAV, if so, increasing the number of vehicles in the motorcade until the maximum scale of the number of vehicles in the motorcade is reached, namely 4 vehicles. If the HDV between adjacent CAVs exceeds three, it is ignored. When the number of vehicles in the fleet reaches a maximum scale or the head vehicle leaves the zone detector end point, the consist ends.
S3: and acquiring vehicle information, and mapping the main road and the ramp vehicles to the same lane by adopting a virtual mapping mode.
Further, the passing sequence is determined according to the positions of the vehicles reaching the main road area detector and the ramp area detector, and the front auxiliary vehicle and the rear auxiliary vehicle on the main road are determined. In order to realize planning of vehicles on different lanes, the ramp vehicles are mapped to a main road in a virtual mapping mode, and after passing sequence ordering is carried out according to positions, corresponding virtual vehicles are formed.
S4: and constructing a multi-vehicle cooperative grouping intersection model, calculating traffic efficiency and realizing safe merging of ramp vehicles.
Still further, consider that vehicles on the main line and ramp are formed into C-CHDV fleets by fleeting, and that only one CAV is specified in each C-CHDV fleet, with the remainder being HDV. Parameters (parameters)Indicating the number of HDVs in the C-CHDV fleet, and (2)>If->There is no HDV in the fleet, otherwise the number of HDVs is at least 1.
；
wherein ,is a binary variable, and takes only the value 0 or 1.
It should be noted that after the number of HDVs is determined in the area detector, the length of the fleet can be obtained:
；
wherein ,is->Index values for the individual C-HDV fleets; />Is->The length of the individual C-HDV fleet; />Is a certain moment; />Is->Head car CAV in a C-HDV fleet at time +.>Is a position of (2); />Is->The last HDV in a fleet of C-HDVs is at time +.>Is a position of (2); />The vehicle length is 5m.
It should also be noted that the first HDV in the fleet is located at a certain point in time:
；
wherein ,is->The first HDV in the individual C-HDV fleet is at time +.>Is a position of (2); />Taking a value of 1s as the reaction delay time; />Is->The first HDV in the individual C-HDV fleet is at time +.>Is a function of the speed of the machine.
Further, the safe distance to be maintained by the adjacent C-HDV fleet on the main line and ramp is then:
；
wherein ,is the first car CAV in the C-HDV motorcade on the ramp>The position of the moment;the first car CAV in the C-HDV fleet on the main road is +.>The position of the moment; />The first car CAV in the C-HDV fleet on the main road is +.>Speed of time; />Is the acceleration and deceleration of the vehicle running.
Furthermore, the safety distance to be kept when the main line and the ramp are converged is as follows:
；
it should be noted that, the traffic efficiency index is the number of vehicles passing through the road network and the average loss time (MTL) of the vehicles, and the calculation formula of the MTL is as follows:
；
wherein ,and->Is divided intoThe total number of vehicles on the main road and the ramp is distinguished; />、/>Main road vehicle->And ramp vehicle->Travel time on the road network; />And->The distance between the main road vehicle and the ramp vehicle is respectively; />And (3) withThe average speed of the vehicles on the main road and the ramp in the running process is respectively; />Is the expected speed of CAV or HDV on the ramp;is the desired vehicle speed of CAV.
Further, to ensure that the vehicle speed and acceleration are within safe ranges, the constraints are as follows:
；
wherein ,、/>the minimum allowable speed and the maximum allowable speed of the vehicle are respectively; />、/>Respectively minimum and maximum allowable acceleration of the vehicle, respectively taking the value +.>Is->。
Example 2
Referring to fig. 4, for one embodiment of the present application, a method for merging multiple vehicles in a highway and a merge area in a mixed running environment is provided, and in order to verify the beneficial effects of the present application, scientific demonstration is performed through experiments.
To evaluate and verify the effectiveness of the proposed method, experiments were simulated using microscopic simulation software SUMO in combination with Python. The CAV permeability is sequentially increased at 20% intervals under the conditions of the same flow and different permeabilities, the number of vehicles passing through a main road and a ramp under the condition of a marshalling control strategy is shown in fig. 4, and the average loss time of the vehicles is shown in fig. 5. It can be seen that the number of vehicles passing through the main road and the ramp in the road network in fig. 4 is not lower than that of the non-control strategy, and the number of vehicles passing through the road network is relatively stable and is about 56veh and 33 veh. When no marshalling control strategy exists and the CAV permeability is 0-40%, the number of main road passing vehicles is small, and the number of main road passing vehicles is only about 33veh, and is reduced by 41% compared with the control strategy. The number of vehicles passing through the ramp in other scenes except the CAV permeability of 40% is reduced by 8.3% -20% in the non-control strategy compared with the number of vehicles passing through the ramp in the scene with control, and the higher the CAV permeability is, the higher the automation level in the road network is, and the number of vehicles passing through is also higher even under the non-control strategy. When the CAV permeability is 0-40%, the average lost time per vehicle is higher than other cases, although the average lost time per vehicle is improved. The main reasons of low permeability and low optimization rate are that the proportion of the HDVs in the road network is high, uncertain factors are many, the probability of application of the grouping control strategy proposed by the chapter is less until the grouping control strategy fails when the permeability is 0%, and therefore the grouping cooperative control strategy is not recommended to be used when the HDV flow is large. When the permeability is greater than 40%, the optimization rate shows a group of similar rules, namely, the optimization rate of the main road, the ramp and the whole road network is improved along with the improvement of the permeability, and is respectively improved from 0.47% to 0.98%, 38.64% to 63.06%, and 23.79% to 36.45%. In summary, the method provided by the application can effectively relieve traffic jam, reduce average loss time of vehicles and improve traffic efficiency of road network.
It should be noted that the above embodiments are only for illustrating the technical solution of the present application and not for limiting the same, and although the present application has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications and equivalents may be made thereto without departing from the spirit and scope of the technical solution of the present application, which is intended to be covered by the scope of the claims of the present application.
Example 3
A third embodiment of the present application, which is different from the first two embodiments, is: the functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution, in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, randomAccess Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes. Logic and/or steps represented in the flowcharts or otherwise described herein, e.g., a ordered listing of executable instructions for implementing logical functions, can be embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions. For the purposes of this description, a "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of the computer-readable medium would include the following: an electrical connection (electronic device) having one or more wires, a portable computer diskette (magnetic device), a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). In addition, the computer readable medium may even be paper or other suitable medium on which the program is printed, as the program may be electronically captured, via, for instance, optical scanning of the paper or other medium, then compiled, interpreted or otherwise processed in a suitable manner, if necessary, and then stored in a computer memory. It is to be understood that portions of the present application may be implemented in hardware, software, firmware, or a combination thereof. In the above-described embodiments, the various steps or methods may be implemented in software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, may be implemented using any one or combination of the following techniques, as is well known in the art: discrete logic circuits having logic gates for implementing logic functions on data signals, application specific integrated circuits having suitable combinational logic gates, programmable Gate Arrays (PGAs), field Programmable Gate Arrays (FPGAs), and the like.
Example 4
Referring to fig. 5, in an embodiment of the present application, a system for merging multiple vehicles in a highway and a merge area in a mixed traffic environment is provided, which is characterized by comprising a sensing module, a data processing module, a control module, a communication module, a multiple vehicle collaborative grouping module, and a navigation and driving assistance module;
and the sensing module is used for acquiring the position, speed and running direction information of vehicles, pedestrians and other traffic participants, monitoring traffic conditions on a road in real time and providing basis for subsequent traffic control and planning.
The data processing module is used for processing the data acquired by the sensing module, analyzing the traffic condition and generating a traffic control instruction.
And the control module is used for controlling signal lamps and signboards on the road according to the traffic control instruction generated by the data processing module so as to ensure that vehicles and pedestrians can safely pass through the converging area.
The communication module is responsible for communication between the traffic management center and the vehicle, the vehicle receives real-time traffic information through communication with the traffic management center, and the speed and the driving route of the vehicle are controlled through the communication module.
The multi-vehicle cooperative grouping module is responsible for communication and coordination among a plurality of vehicles and guiding the vehicles to meet and group in an optimized mode.
And the navigation and driving auxiliary module provides real-time navigation and traffic information for a driver through the vehicle-mounted equipment and provides an automatic driving auxiliary function for the driver, so that the vehicle can safely run in the confluence area.
It should be noted that the above embodiments are only for illustrating the technical solution of the present application and not for limiting the same, and although the present application has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications and equivalents may be made thereto without departing from the spirit and scope of the technical solution of the present application, which is intended to be covered by the scope of the claims of the present application.
Claims (9)
1. A multi-vehicle collaborative grouping intersection method for a highway confluence region in a mixed running environment is characterized by comprising the following steps of: comprising the steps of (a) a step of,
taking intelligent network vehicles and manual driving vehicles as research objects, and establishing a vehicle constraint model;
grouping vehicles on the ramp in the confluence area;
acquiring vehicle information, and mapping a main road and a ramp vehicle to the same lane in a virtual mapping mode;
the method comprises the steps of constructing a multi-vehicle cooperative grouping intersection model, calculating traffic efficiency and realizing safe ramp vehicle import, wherein the multi-vehicle cooperative grouping intersection model comprises the steps of forming vehicles on a main line and a ramp into C-CHDV vehicle queues through formation, and providing that only one CAV exists in each C-CHDV vehicle queue, the rest are HDVs, wherein the expression is as follows:
；
wherein ,representing a binary variable>Indicating the number of HDVs in the C-CHDV fleet, and (2)>If->If the vehicle team has no HDV, otherwise, the number of the HDVs is at least 1, and h represents the vehicles in the vehicle team;
after the number of HDVs is determined in the area detector, the length of the fleet can be obtained:
；
where i represents the index value of the ith C-HDV fleet,indicating the length of the ith C-HDV fleet, t indicates time,indicating the position of the head car CAV in the ith C-HDV fleet at time t,/->Indicating the position of the last HDV in the ith C-HDV motorcade at the time t, and l indicating the vehicle length;
the position of the first HDV in the fleet at a certain moment:
；
wherein ,indicate->The first HDV in the individual C-HDV fleet is at time +.>Is (are) located>Indicating response delay time, +.>Indicate->The first HDV in the individual C-HDV fleet is at time +.>Is a function of the speed of the machine.
2. The method for multi-vehicle collaborative grouping intersection of a highway confluence region in a mixed running environment according to claim 1, which is characterized in that: the vehicle restraint model includes a model of the vehicle,
；
wherein ,indicating the position of the vehicle i at time t +.>Indicating the speed of the vehicle i at time t +.>The acceleration of the vehicle i at time t is shown.
3. The method for merging multiple vehicles in a highway and a confluence area into a cooperative grouping and merging under a mixed running environment as claimed in claim 2, which is characterized in that: the grouping of the junction ramp vehicles includes,
when a vehicle enters a road network, vehicle information on a ramp area detector is acquired, the type of the vehicle is judged, if the vehicle is CAV, the vehicle is controllable, the vehicle is used as a marshalling head vehicle, if the vehicle is HDV, the vehicle is used as a rear vehicle to follow the CAV, the CAV in the ramp area detector is numbered, one CAV represents that a vehicle team exists, whether the HDV follows after the CAV is judged, if the vehicle is judged, the number of the vehicles of the vehicle team is increased until the maximum scale of 4 vehicles in the vehicle team is reached, if the HDV between the adjacent CAVs exceeds three vehicles, the vehicle is ignored, and when the number of the vehicles in the vehicle team reaches the maximum scale or the head vehicle leaves the end point of the area detector, the marshalling is ended.
4. The method for multi-vehicle collaborative grouping intersection in a highway confluence area in a mixed running environment according to claim 3, wherein the method comprises the following steps: said mapping the host road and ramp vehicles to the same lane includes,
determining a passing sequence according to positions of vehicles reaching the main road area detector and the ramp area detector, determining front and rear auxiliary vehicles on the main road, mapping ramp vehicles to the main road in a virtual mapping mode, sequencing the passing sequence according to the positions, forming corresponding virtual vehicles, and planning vehicles on different lanes.
5. The method for merging multiple vehicles in a highway and a confluence area into a cooperative grouping and merging under the mixed running environment as claimed in claim 4, which is characterized in that: the multi-vehicle collaborative marshalling intersection model comprises the following safe distance expressions which are required to be kept by adjacent C-HDV motorcades on a main line and a ramp:
；
wherein ,representing that the first car CAV in the C-HDV fleet on the ramp is +.>Position of moment->Representing that the head car CAV in the C-HDV fleet on the main road is +.>Position of moment->Representing that the head car CAV in the C-HDV fleet on the main road is +.>Speed of moment->Indicating the acceleration or deceleration of the running of the vehicle;
the safety distance to be kept when the main line and the ramp are converged is as follows:
。
6. the method for merging multiple vehicles in a highway and a confluence area into a cooperative grouping and merging under the mixed running environment as set forth in claim 5, which is characterized in that: the calculation of the traffic efficiency comprises the steps of selecting the number of vehicles passing through the road network and the average loss time of the vehicles according to the traffic efficiency index, wherein the calculation formula of the MTL is as follows:
；
wherein ,representing the total number of vehicles on the main road>Representing the total number of vehicles on the ramp->Representing the travel time of the host road vehicle i on the road network,/->Indicating the travel time of ramp vehicle j on the road network,/->Indicating the distance travelled by the main road vehicle, +.>Indicating the distance travelled by the ramp vehicle, +.>Average speed representing the driving course of the main road vehicle,/->Average speed of the vehicle during driving on the ramp, < > is indicated>Representing CAV or HDV on rampDesired vehicle speed,/->Representing a desired vehicle speed of the CAV;
to ensure that vehicle speed and acceleration are within safe ranges, constraints include:
；
wherein ,representing the minimum allowable speed of the vehicle,/->Indicating the maximum allowable speed of the vehicle,/->Representing the minimum allowed acceleration of the vehicle,/->Indicating the maximum allowable acceleration.
7. A system employing the method for merging multiple vehicles in a highway merge area under a mixed running environment as claimed in any one of claims 1 to 6, wherein: the system comprises a sensing module, a data processing module, a control module, a communication module, a multi-vehicle cooperative grouping module and a navigation and driving auxiliary module;
the sensing module is used for acquiring the position, speed and running direction information of vehicles, pedestrians and other traffic participants, monitoring traffic conditions on a road in real time and providing basis for subsequent traffic control and planning;
the data processing module is used for processing the data acquired by the sensing module, analyzing the traffic condition and generating a traffic control instruction;
the control module is used for controlling signal lamps and signboards on a road according to the traffic control instruction generated by the data processing module, so that vehicles and pedestrians can safely pass through the converging area;
the communication module is responsible for communication between the traffic management center and the vehicle, the vehicle receives real-time traffic information through communication with the traffic management center, and the speed and the driving route of the vehicle are controlled through the communication module;
the multi-vehicle cooperative grouping module is responsible for communication and coordination among a plurality of vehicles and guiding the vehicles to meet and group in an optimized mode;
the navigation and driving assistance module provides real-time navigation and traffic information for a driver through the vehicle-mounted equipment and provides an automatic driving assistance function for the driver, so that the vehicle can safely run in the confluence area.
8. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the steps of the method of any of claims 1 to 6 when the computer program is executed.
9. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 6.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117218881A (en) * | 2023-11-08 | 2023-12-12 | 北京理工大学前沿技术研究院 | Intelligent vehicle collaborative import decision planning method and system in full network environment |
| CN117496689A (en) * | 2023-12-29 | 2024-02-02 | 苏州观瑞汽车技术有限公司 | Continuous signal intersection fleet cooperative control method and system in mixed traffic environment |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113345268A (en) * | 2021-07-16 | 2021-09-03 | 长沙理工大学 | CAV lane change decision-making method for expressway down-ramp diversion area based on automatic driving special lane deployment scene |
| US20220351625A1 (en) * | 2021-04-14 | 2022-11-03 | Zhejiang University | Dynamic platoon formation method under mixed autonomous vehicles flow |
| CN115376346A (en) * | 2022-08-11 | 2022-11-22 | 苏州大学 | Multi-mode driving vehicle collaborative intersection method for expressway confluence area under mixed-driving condition |
| CN116434517A (en) * | 2023-04-04 | 2023-07-14 | 武汉理工大学 | Ramp confluence cooperative control method and device based on vehicle formation and electronic equipment |
-
2023
- 2023-08-11 CN CN202311008981.XA patent/CN116740945B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20220351625A1 (en) * | 2021-04-14 | 2022-11-03 | Zhejiang University | Dynamic platoon formation method under mixed autonomous vehicles flow |
| CN113345268A (en) * | 2021-07-16 | 2021-09-03 | 长沙理工大学 | CAV lane change decision-making method for expressway down-ramp diversion area based on automatic driving special lane deployment scene |
| CN115376346A (en) * | 2022-08-11 | 2022-11-22 | 苏州大学 | Multi-mode driving vehicle collaborative intersection method for expressway confluence area under mixed-driving condition |
| CN116434517A (en) * | 2023-04-04 | 2023-07-14 | 武汉理工大学 | Ramp confluence cooperative control method and device based on vehicle formation and electronic equipment |
Non-Patent Citations (2)
| Title |
|---|
| 秦严严;王昊;: "智能网联车辆交通流优化对交通安全的改善", 中国公路学报, no. 04 * |
| 胡笳;安连华;李欣: "面向新型混合交通流的快速路合流区通行能力建模", 交通信息与安全, no. 001 * |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117218881A (en) * | 2023-11-08 | 2023-12-12 | 北京理工大学前沿技术研究院 | Intelligent vehicle collaborative import decision planning method and system in full network environment |
| CN117218881B (en) * | 2023-11-08 | 2024-02-13 | 北京理工大学前沿技术研究院 | Intelligent vehicle collaborative import decision planning method and system in full network environment |
| CN117496689A (en) * | 2023-12-29 | 2024-02-02 | 苏州观瑞汽车技术有限公司 | Continuous signal intersection fleet cooperative control method and system in mixed traffic environment |
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