CN115188210A - Intelligent internet vehicle and human-driven vehicle mixed intersection control method and system - Google Patents
Intelligent internet vehicle and human-driven vehicle mixed intersection control method and system Download PDFInfo
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Abstract
The invention relates to the technical field of intelligent control, in particular to a method and a system for controlling a mixed intersection of an intelligent internet vehicle and a human-driven vehicle, wherein the method comprises the following steps: acquiring a vehicle information set and a road information set of a current intersection; the vehicle information set includes a vehicle number, a vehicle position, a vehicle speed, and a vehicle acceleration of each vehicle; the road information set comprises indicating lamp data, straight lane number data and straight lane stop line central point data; obtaining a target vehicle set based on the vehicle number, the vehicle position, the straight lane stop line central point data and the indicating lamp data; if the target vehicle set has the target vehicles, judging each target vehicle, controlling the target vehicles to cross the current intersection based on the set crossing speed when the target vehicles meet the set conditions, and not crossing when the target vehicles do not meet the set conditions; and if the target vehicle set is empty, not traversing. The invention improves the passing efficiency and shortens the waiting time of the vehicle.
Description
Technical Field
The invention relates to the technical field of intelligent control, in particular to a method and a system for controlling a mixed intersection of an intelligent internet vehicle and a human-driven vehicle.
Background
In recent years, the problems of urban traffic jam, traffic accidents and the like are increasingly serious, intersections serve as nodes of an urban traffic network, the operation and control effect of road network traffic is directly influenced, and the solving of the traffic problem of the intersections has great significance for solving the whole urban traffic problem. With the development of communication technology, sensing and computer technology, intelligent networking technology becomes a key technology for solving traffic problems. Although great progress has been made in intelligent internet Vehicles (Connected and Automated Vehicles, for short, CAVs) to date, it takes a relatively long time to achieve full automation and high market penetration of CAVs, and before the CAVs completely replace Human Drive Vehicles (HDVs), roads will have mixed traffic flows of CAVs and HDVs for a long time.
Under the intelligent network connection environment, the CAVs has faster information detection capability and shorter reaction time than HDVs, and the road end sensing can also transmit the detected road and vehicle running conditions in the intersection range to the vehicle end in real time. How to exert the technical advantages of the intelligent networking system in the intersection control problem and realize safe, effective and scientific control is an important direction for the research in the field of traffic control at present. For HDVs, signal lamps are an important control means, while for CAVs, signal lamp control is not an essential means, and coordination and cooperation between internet workshops can be realized by controlling the traffic of each vehicle. Therefore, how to coordinate the two types of vehicles to pass through the intersection is a problem to be solved urgently.
Disclosure of Invention
In view of the above, the invention provides a method and a system for controlling an intersection where an intelligent internet vehicle and a human-driven vehicle are mixed, which improve the traffic efficiency of the intersection and shorten the waiting time of the vehicle at the intersection.
In order to achieve the purpose, the invention provides the following scheme:
a method for controlling an intersection where an intelligent internet vehicle and a human-driven vehicle are mixed to run comprises the following steps:
acquiring a vehicle information set and a road information set of a current intersection; the vehicle information set comprises a vehicle number, a vehicle position, a vehicle speed and a vehicle acceleration of each vehicle at the current intersection; the road information set comprises indicating lamp data of a current intersection, straight lane number data and straight lane stop line central point data;
obtaining a target vehicle set based on the vehicle number, the vehicle position, the straight lane stop line center point data and the indicator lamp data;
if the target vehicle set comprises target vehicles, judging each target vehicle, controlling the target vehicles to cross the current intersection based on a set crossing speed when the target vehicles meet set conditions, and not crossing when the target vehicles do not meet the set conditions; and if the target vehicle set is empty, not traversing.
Optionally, the obtaining a target vehicle set based on the vehicle number, the vehicle position, the straight lane stop line center point data, and the indicator light data includes:
selecting a vehicle of which the type is an intelligent networked vehicle and which is positioned on a straight lane at the current intersection to obtain an initial vehicle set; the vehicle type is obtained based on the vehicle number;
calculating the distance from each vehicle in the initial vehicle set to the coordinate of the corresponding central point of each vehicle in the initial vehicle set based on the vehicle position, the serial number data of the straight-going lane and the central point data of the stop line of the straight-going lane to obtain a distance set; the straight lane number data comprises lane numbers corresponding to all straight lanes; the straight lane stop line central point data comprises the central point coordinates of the stop line of each straight lane;
selecting vehicles corresponding to distances smaller than a set spacing distance threshold value in the distance set to obtain a distance vehicle set;
and selecting the vehicles which are red lights and green lights from the straight running indicator lights in the running direction at the current moment and the next moment in the vehicle set based on the indicator light data, and obtaining the target vehicle set.
Optionally, any two straight lanes perpendicular to each other correspond to a preset collision point to form a preset collision point set; selecting a vehicle which moves straight in a direction vertical to the running direction of the target vehicle to obtain a crossing vehicle set;
obtaining a collision distance set based on the passing vehicle set and the preset collision point set;
the set condition is that each collision distance in the set of collision distances is greater than a set collision threshold.
Optionally, obtaining a collision distance set based on the passing vehicle set and the preset collision point set includes:
executing the following process for each preset collision point in the preset collision point set to obtain a collision distance, and traversing the preset collision point set to obtain the collision distance set;
calculating the distance from the target vehicle to the preset collision point to obtain the driving distance of the target vehicle;
obtaining the running time of the target vehicle based on the running distance, the vehicle speed, the vehicle acceleration and the crossing speed;
and calculating the distance from the vehicle corresponding to the preset collision point in the crossing vehicle set to the preset collision point based on the target vehicle running time, the vehicle position and the vehicle speed to obtain a plurality of collision distances.
The invention also provides a control system for the intersection where the intelligent internet vehicle and the human-driven vehicle are mixed, which comprises the following components:
the data acquisition module is used for acquiring a vehicle information set and a road information set of a current intersection; the vehicle information set comprises a vehicle number, a vehicle position, a vehicle speed and a vehicle acceleration of each vehicle at the current intersection; the road information set comprises indicating lamp data of a current intersection, serial number data of a straight lane and stop line central point data of the straight lane;
the vehicle screening module is used for obtaining a target vehicle set based on the vehicle number, the vehicle position, the straight lane stop line central point data and the indicating lamp data;
the control module is used for judging each target vehicle if the target vehicle set has the target vehicle, controlling the target vehicle to pass through the current intersection based on a set passing speed when the target vehicle meets set conditions, and not passing through the current intersection when the target vehicle does not meet the set conditions; and if the target vehicle set is empty, not traversing.
Optionally, the vehicle screening module comprises:
the intelligent networked vehicle screening unit is used for selecting the vehicle of which the type is the intelligent networked vehicle and which is positioned on the straight lane at the current intersection to obtain an initial vehicle set; the vehicle type is obtained based on the vehicle number;
the central distance calculating unit is used for calculating the distance from each vehicle in the initial vehicle set to the coordinate of the corresponding central point of each vehicle in the initial vehicle set based on the vehicle position, the number data of the straight-going lane and the central point data of the stop line of the straight-going lane to obtain a distance set; the straight lane number data comprises lane numbers corresponding to all straight lanes; the straight lane stop line central point data comprises the central point coordinates of the stop line of each straight lane;
the distance screening unit is used for selecting the vehicles corresponding to the distance smaller than the set spacing distance threshold value in the distance set to obtain a distance vehicle set;
and the target vehicle screening unit is used for selecting the vehicles which are red lamps and green lamps from the straight indicator lamps in the driving direction at the current moment and the next moment in the vehicle set based on the indicator lamp data to obtain the target vehicle set.
Optionally, any two straight lanes perpendicular to each other correspond to a preset collision point to form a preset collision point set; the control module selects a vehicle which runs straight in a direction vertical to the running direction of the target vehicle to obtain a crossing vehicle set;
the control module obtains a collision distance set based on the crossing vehicle set and the preset collision point set;
the set condition is that each collision distance in the set of collision distances is greater than a set collision threshold.
Optionally, the obtaining, by the control module, a collision distance set based on the passing vehicle set and the preset collision point set includes:
the control module executes the following process for each preset collision point in the preset collision point set to obtain a collision distance, and traverses the preset collision point set to obtain the collision distance set;
calculating the distance from the target vehicle to the preset collision point to obtain the driving distance of the target vehicle;
obtaining the running time of the target vehicle based on the running distance, the vehicle speed, the vehicle acceleration and the crossing speed;
and calculating the distance from the vehicle corresponding to the preset collision point in the crossing vehicle set to the preset collision point based on the target vehicle running time, the vehicle position and the vehicle speed to obtain a plurality of collision distances.
According to the specific embodiment provided by the invention, the invention discloses the following technical effects:
the invention relates to a method and a system for controlling an intersection where an intelligent internet vehicle and a human-driven vehicle are mixed, wherein the method comprises the following steps: acquiring a vehicle information set and a road information set of a current intersection; the vehicle information set comprises a vehicle number, a vehicle position, a vehicle speed and a vehicle acceleration of each vehicle at the current intersection; the road information set comprises indicating lamp data of a current intersection, serial number data of a straight lane and stop line central point data of the straight lane; obtaining a target vehicle set based on the vehicle number, the vehicle position, the straight-through lane stop line central point data and the indicator lamp data; if the target vehicle set comprises target vehicles, judging each target vehicle, controlling the target vehicles to cross the current intersection based on a set crossing speed when the target vehicles meet set conditions, and not crossing when the target vehicles do not meet the set conditions; and if the target vehicle set is empty, not traversing. The invention improves the passing efficiency of the intersection and shortens the waiting time of the vehicle at the intersection.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings without inventive exercise.
FIG. 1 is a schematic cross-over view of an intersection of the present invention;
FIG. 2 is a flow chart of a method for controlling an intersection where an intelligent Internet vehicle and a human-driven vehicle are mixed;
FIG. 3 is a structural diagram of a control system for a mixed intersection of an intelligent Internet vehicle and a human-driven vehicle;
FIG. 4 is a schematic diagram of the control effect of the permeability of each intelligent Internet vehicle when the traffic demand level is 1200 veh/h;
FIG. 5 is a schematic diagram of the control effect of the permeability of each intelligent Internet vehicle when the traffic demand level is 2400 veh/h.
Description of the symbols: the system comprises a data acquisition module, a data transmission module, a vehicle screening module and a control module, wherein the data acquisition module, the data transmission module, the vehicle screening module and the control module are all arranged in sequence.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be obtained by a person skilled in the art without making any creative effort based on the embodiments in the present invention, belong to the protection scope of the present invention.
The invention aims to provide a method and a system for controlling an intersection where an intelligent internet vehicle and a human-driven vehicle are mixed, so that the traffic efficiency of the intersection is improved, and the waiting time of the vehicle at the intersection is shortened.
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in further detail below.
FIG. 1 is a schematic cross-over view of an intersection of the present invention; FIG. 2 is a flow chart of a control method of an intersection where an intelligent internet vehicle and a human-driven vehicle are mixed. As shown in fig. 1 and 2, the invention provides a method for controlling a mixed intersection of an intelligent internet vehicle and a human-driven vehicle, which comprises the following steps:
step S1, acquiring a vehicle information set and a road information set of a current intersection; the vehicle information set comprises a vehicle number, a vehicle position, a vehicle speed and a vehicle acceleration of each vehicle at the current intersection; the road information set comprises indicating lamp data of the current intersection, serial number data of the straight lane and stop line center point data of the straight lane.
And S2, obtaining a target vehicle set based on the vehicle number, the vehicle position, the straight-through lane stop line central point data and the indicator light data.
Specifically, the step S2 includes:
s21, selecting a vehicle which is an intelligent networked vehicle and is positioned in a straight lane at the current intersection to obtain an initial vehicle set; the vehicle type is derived based on the vehicle number.
Step S22, calculating the distance from each vehicle in the initial vehicle set to the corresponding center point coordinate of the vehicle to obtain a distance set based on the vehicle position, the straight-through lane number data and the straight-through lane stop line center point data; the straight lane number data includes a lane number corresponding to each straight lane. The straight lane stop line center point data includes center point coordinates of the stop line of each straight lane.
And S23, selecting the vehicles corresponding to the distances in the distance set smaller than the set spacing distance threshold value to obtain a distance vehicle set. In this embodiment, the set separation distance threshold is 5m.
And S24, selecting the vehicles which are red light straight running indicator lamps in the running direction at the current moment and the next moment in the distance vehicle set and green light straight running indicator lamps in the direction vertical to the running direction based on the indicator lamp data to obtain the target vehicle set. The vertical direction is defined relatively and can be adjusted according to the actual terrain of the intersection.
That is, only the vehicle type is the intelligent networked vehicle, the vehicle is located in the straight-going lane, the distance setting interval distance threshold value is arranged between the intelligent networked vehicle and the central point, the straight-going indicator light in the driving direction at the current moment and the next moment is the red light, and the straight-going indicator light in the direction perpendicular to the driving direction is the vehicle with the green light, so that the vehicle is determined to be the target vehicle.
S3, if the target vehicle set has the target vehicles, judging each target vehicle, controlling the target vehicles to pass through the current intersection based on a set passing speed when the target vehicles meet set conditions, and not passing through the current intersection when the target vehicles do not meet the set conditions; and if the target vehicle set is empty, not traversing.
Specifically, two arbitrary mutually perpendicular straight lanes correspond to a preset collision point to form a preset collision point set; and selecting a vehicle which runs straight in the direction vertical to the running direction of the target vehicle to obtain a crossing vehicle set.
And obtaining a collision distance set based on the passing vehicle set and the preset collision point set.
The set condition is that each collision distance in the set of collision distances is greater than a set collision threshold. In this embodiment, the set collision threshold is 20m.
Further, obtaining a collision distance set based on the passing vehicle set and the preset collision point set includes:
and executing the following process for each preset collision point in the preset collision point set to obtain a collision distance, and traversing the preset collision point set to obtain the collision distance set.
And calculating the distance from the target vehicle to the preset collision point to obtain the driving distance of the target vehicle.
And obtaining the running time of the target vehicle based on the running distance, the vehicle speed, the vehicle acceleration and the crossing speed. The calculation formula is as follows:
t0＝(v_set-v0)/a
x0＝(v_set+v0)×t0/2
in the formula: v _ set is a set traversing speed, v0 is a vehicle speed, a is a vehicle acceleration, the vehicle acceleration is a set value, the setting is specifically carried out according to performance parameters of each vehicle, dis _ to _ collision _ point is a target vehicle running distance, t _ to _ collision _ point is a target vehicle running time, and t0 and x0 are intermediate transition amounts.
And calculating the distance from the vehicle corresponding to the preset collision point in the crossing vehicle set to the preset collision point based on the target vehicle running time, the vehicle position and the vehicle speed to obtain a plurality of collision distances.
Fig. 3 is a structure diagram of a control system of an intersection where an intelligent internet vehicle and a human-driven vehicle are mixed. As shown in fig. 3, the invention provides an intersection control system for a hybrid vehicle of an intelligent internet vehicle and a human-driven vehicle, comprising: the system comprises a data acquisition module 1, a data transmission module 2, a vehicle screening module 3 and a control module 4.
The data acquisition module 1 is used for acquiring a vehicle information set and a road information set of a current intersection. The vehicle information set comprises a vehicle number, a vehicle position, a vehicle speed and a vehicle acceleration of each vehicle at the current intersection; the road information set comprises indicating lamp data of the current intersection, straight lane number data and straight lane stop line center point data.
Specifically, the data acquisition module 1 includes a vision sensor, a look-around camera, a vehicle-end radar, a road-end radar, and a camera. The vehicle-end radar and the road-end radar are any one of laser radar and millimeter wave radar.
The vision sensor and the look-around camera are used for assisting the vehicle-end radar to acquire the vehicle position and the vehicle speed.
The camera is used for assisting the road-end radar to obtain a vehicle number, the number data of the straight lane and the central point data of the stop line of the straight lane.
The indicator light data can be obtained through networking with an existing controller at the intersection.
The data transmission module 2 is configured to send the vehicle information set and the road information set to the vehicle screening module 3 and the control module 4. The data transmission module 2 is a data transmission communication module based on the LTE-V technology. The data transmission module 2 supports interfaces such as CAN, RS232, rj45 and USB.
The vehicle screening module 3 is used for obtaining a target vehicle set based on the vehicle number, the vehicle position, the straight lane stop line central point data and the indicator light data.
Specifically, the vehicle screening module 3 includes:
the intelligent networked vehicle screening unit is used for selecting the vehicle of which the type is the intelligent networked vehicle and is positioned on the straight lane at the current intersection to obtain an initial vehicle set; the vehicle type is derived based on the vehicle number.
The central distance calculating unit is used for calculating the distance from each vehicle in the initial vehicle set to the coordinate of the corresponding central point of each vehicle in the initial vehicle set based on the vehicle position, the number data of the straight-going lane and the central point data of the stop line of the straight-going lane to obtain a distance set; the straight lane number data comprises lane numbers corresponding to all straight lanes; the straight lane stop line center point data includes center point coordinates of the stop line of each straight lane.
And the distance screening unit is used for selecting the vehicles corresponding to the distances smaller than the set distance threshold value in the distance set to obtain a distance vehicle set.
And the target vehicle screening unit is used for selecting the vehicles which are red lamps away from the straight running indicator lamp in the running direction at the current moment and the next moment in the vehicle set and green lamps away from the straight running indicator lamp in the direction perpendicular to the running direction based on the indicator lamp data to obtain the target vehicle set.
The control module 4 is configured to, if a target vehicle exists in the target vehicle set, determine each target vehicle, control the target vehicle to cross a current intersection based on a set crossing speed when the target vehicle meets a set condition, and not cross when the target vehicle does not meet the set condition; and if the target vehicle set is empty, not traversing.
Two straight lanes which are perpendicular to each other correspond to a preset collision point to form a preset collision point set.
The control module 4 selects a vehicle which is going straight in a direction perpendicular to the running direction of the target vehicle to obtain a crossing vehicle set.
And the control module 4 obtains a collision distance set based on the passing vehicle set and the preset collision point set.
The set condition is that each collision distance in the set of collision distances is greater than a set collision threshold.
Specifically, the control module 4 obtains a collision distance set based on the passing vehicle set and the preset collision point set, including:
the control module 4 executes the following process for each preset collision point in the preset collision point set to obtain a collision distance, and traverses the preset collision point set to obtain the collision distance set.
Calculating the distance from the target vehicle to the preset collision point to obtain the driving distance of the target vehicle;
and obtaining the running time of the target vehicle based on the running distance, the vehicle speed, the vehicle acceleration and the crossing speed.
And calculating the distance from the vehicle corresponding to the preset collision point in the crossing vehicle set to the preset collision point based on the target vehicle running time, the vehicle position and the vehicle speed to obtain a plurality of collision distances.
According to the invention, simulation is carried out on the active traffic control of the intersection of the northeast Jiasong road and the Boyuan road in sumo software, different traffic demand levels and different scenes under the permeability of the intelligent Internet vehicle are set, and the effectiveness of the invention is verified. The control effect of different scenes is reflected by the average parking duration of the intersection.
The simulation intersection is provided with 8 phases which are respectively east-west straight green, east-west straight yellow, east-west left turning green, east-west left turning yellow, south-north straight green, south-north straight yellow, south-north left turning green and south-north left turning yellow, the period is 120 seconds, and the duration of each phase is 30s, 5s, 20s, 5s, 30s, 5s, 20s and 5s. The traffic demand level is set as: the ratio of the straight-driving vehicle, the left-turning vehicle and the right-turning vehicle is 4:2:1; the 1 hour traffic was set at 2 levels: 1200veh/h and 2400veh/h, veh representing the vehicle. CAVs permeability was set at 6 levels: 0. 20%, 40%, 50%, 60%, 100%. When the traffic demand level is 1200veh/h, the control effect of the permeability of each intelligent internet vehicle is shown in fig. 4, and when the traffic demand level is 2400veh/h, the control effect of the permeability of each intelligent internet vehicle is shown in fig. 5, and as can be seen from fig. 4 and 5, the control effect becomes better along with the increase of the permeability of the intelligent internet vehicles.
The embodiments in the present description are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other.
The principles and embodiments of the present invention have been described herein using specific examples, which are provided only to help understand the method and the core concept of the present invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, the specific embodiments and the application range may be changed. In view of the above, the present disclosure should not be construed as limiting the invention.
Claims (8)
1. A method for controlling an intersection where an intelligent internet vehicle and a human-driven vehicle are mixed is characterized by comprising the following steps:
acquiring a vehicle information set and a road information set of a current intersection; the vehicle information set comprises a vehicle number, a vehicle position, a vehicle speed and a vehicle acceleration of each vehicle at the current intersection; the road information set comprises indicating lamp data of a current intersection, straight lane number data and straight lane stop line central point data;
obtaining a target vehicle set based on the vehicle number, the vehicle position, the straight-through lane stop line central point data and the indicator lamp data;
if the target vehicle set comprises target vehicles, judging each target vehicle, controlling the target vehicles to cross the current intersection based on a set crossing speed when the target vehicles meet set conditions, and not crossing when the target vehicles do not meet the set conditions; and if the target vehicle set is empty, not traversing.
2. The method for controlling the intersection where the intelligent networked vehicle and the human-driven vehicle are mixed according to claim 1, wherein the obtaining of the target vehicle set based on the vehicle number, the vehicle position, the stop line center point data of the straight-through lane and the indicator light data comprises:
selecting a vehicle of which the type is an intelligent networked vehicle and which is positioned on a straight lane at the current intersection to obtain an initial vehicle set; the vehicle type is obtained based on the vehicle number;
calculating the distance from each vehicle in the initial vehicle set to the coordinate of the corresponding central point of each vehicle in the initial vehicle set based on the vehicle position, the serial number data of the straight-going lane and the central point data of the stop line of the straight-going lane to obtain a distance set; the straight lane number data comprises lane numbers corresponding to all straight lanes; the straight lane stop line central point data comprises the central point coordinates of the stop line of each straight lane;
selecting vehicles corresponding to distances smaller than a set spacing distance threshold value in the distance set to obtain a distance vehicle set;
and selecting the vehicles which are red lamps as the straight running indicator lamps in the running direction at the current moment and the next moment in the distance vehicle set and green lamps as the straight running indicator lamps in the direction vertical to the running direction based on the indicator lamp data to obtain the target vehicle set.
3. The method for controlling the intersection where the intelligent internet vehicle and the human-driven vehicle are mixed according to claim 1, wherein any two straight lanes perpendicular to each other correspond to one preset collision point to form a preset collision point set; selecting a vehicle which moves straight in a direction vertical to the running direction of the target vehicle to obtain a crossing vehicle set;
obtaining a collision distance set based on the passing vehicle set and the preset collision point set;
the set condition is that each collision distance in the set of collision distances is greater than a set collision threshold.
4. The method for controlling the intersection where the intelligent internet vehicle and the human-driven vehicle are mixed according to claim 3, wherein obtaining a collision distance set based on the passing vehicle set and the preset collision point set comprises:
executing the following process for each preset collision point in the preset collision point set to obtain a collision distance, and traversing the preset collision point set to obtain the collision distance set;
calculating the distance from the target vehicle to the preset collision point to obtain the driving distance of the target vehicle;
obtaining the running time of the target vehicle based on the running distance, the vehicle speed, the vehicle acceleration and the crossing speed;
and calculating the distance from the vehicle corresponding to the preset collision point in the crossing vehicle set to the preset collision point based on the target vehicle running time, the vehicle position and the vehicle speed to obtain a plurality of collision distances.
5. The utility model provides an intelligence internet of things and human driving car are crossing control system that thoughtlessly goes which characterized in that includes:
the data acquisition module is used for acquiring a vehicle information set and a road information set of a current intersection; the vehicle information set comprises a vehicle number, a vehicle position, a vehicle speed and a vehicle acceleration of each vehicle at the current intersection; the road information set comprises indicating lamp data of a current intersection, straight lane number data and straight lane stop line central point data;
the vehicle screening module is used for obtaining a target vehicle set based on the vehicle number, the vehicle position, the straight lane stop line central point data and the indicator lamp data;
the control module is used for judging each target vehicle if the target vehicle set has the target vehicle, controlling the target vehicle to pass through the current intersection based on a set passing speed when the target vehicle meets set conditions, and not passing through the current intersection when the target vehicle does not meet the set conditions; and if the target vehicle set is empty, not traversing.
6. The intelligent internet vehicle and human-driven vehicle mixed intersection control system according to claim 5, wherein the vehicle screening module comprises:
the intelligent networked vehicle screening unit is used for selecting the vehicle of which the type is the intelligent networked vehicle and which is positioned on the straight lane at the current intersection to obtain an initial vehicle set; the vehicle type is obtained based on the vehicle number;
the central distance calculating unit is used for calculating the distance from each vehicle in the initial vehicle set to the coordinate of the corresponding central point of each vehicle in the initial vehicle set based on the vehicle position, the number data of the straight-going lane and the central point data of the stop line of the straight-going lane to obtain a distance set; the straight lane number data comprises lane numbers corresponding to all straight lanes; the straight lane stop line central point data comprises the central point coordinates of the stop line of each straight lane;
the distance screening unit is used for selecting the vehicles corresponding to the distance smaller than the set spacing distance threshold value in the distance set to obtain a distance vehicle set;
and the target vehicle screening unit is used for selecting the vehicles which are red lamps away from the straight running indicator lamp in the running direction at the current moment and the next moment in the vehicle set and green lamps away from the straight running indicator lamp in the direction perpendicular to the running direction based on the indicator lamp data to obtain the target vehicle set.
7. The intelligent internet vehicle and human-driven vehicle mixed intersection control system according to claim 5, wherein any two straight lanes perpendicular to each other correspond to a preset collision point to form a preset collision point set; the control module selects a vehicle which moves straight in a direction vertical to the running direction of the target vehicle to obtain a crossing vehicle set;
the control module obtains a collision distance set based on the crossing vehicle set and the preset collision point set;
the set condition is that each collision distance in the set of collision distances is greater than a set collision threshold.
8. The system as claimed in claim 7, wherein the control module obtains a collision distance set based on the crossing vehicle set and the preset collision point set, and comprises:
the control module executes the following process for each preset collision point in the preset collision point set to obtain a collision distance, and traverses the preset collision point set to obtain the collision distance set;
calculating the distance from the target vehicle to the preset collision point to obtain the driving distance of the target vehicle;
obtaining the running time of the target vehicle based on the running distance, the vehicle speed, the vehicle acceleration and the crossing speed;
and calculating the distance from the vehicle corresponding to the preset collision point in the crossing vehicle set to the preset collision point based on the target vehicle running time, the vehicle position and the vehicle speed to obtain a plurality of collision distances.
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| CN202210799426.2A CN115188210A (en) | 2022-07-06 | 2022-07-06 | Intelligent internet vehicle and human-driven vehicle mixed intersection control method and system |
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