CN109598950B - Ramp cooperative convergence control method and system for intelligent networked vehicles - Google Patents
Ramp cooperative convergence control method and system for intelligent networked vehicles Download PDFInfo
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Abstract
The invention discloses a ramp cooperative convergence control method for intelligent internet vehicles, and relates to the technical field of intelligent internet traffic. The invention also discloses a ramp cooperative import control system of the intelligent network connection vehicle, which realizes the practical application of the intelligent network connection technology in the aspect of ramp cooperative import and is beneficial to improving the passing efficiency of an expressway system.
Description
Technical Field
The invention relates to the technical field of intelligent network communication, in particular to a ramp collaborative convergence control method and system for intelligent network communication vehicles.
Background
With the rapid increase of the quantity of motor vehicles in China, the construction and development conditions of the current expressway are more and more difficult to meet the increasing travel demands of people. Especially, the peripheral area of the entrance ramp is often a bottleneck section caused by the confluence behavior. When the traffic flow on the highway main line road is dense, the ramp vehicles have to be decelerated to wait for a proper merge clearance, thereby causing queuing or even a backflow phenomenon of the vehicles at the entrance ramp. Meanwhile, the merging action taken by partial ramp vehicles under the condition of not finding an acceptable gap forces the main line vehicle to decelerate and even emergently brake, so that the running efficiency of the main line traffic flow is greatly reduced, the problems of traffic jam, traffic accidents and the like are further aggravated, and the efficient and orderly operation of the highway system is seriously influenced.
The entrance ramp control plays a prominent role in the operation of the existing highway system as an important means of managing the traffic flow entering the main line of the highway. The ramp control system limits the traffic flow which is converged into the main line by the ramp according to the running condition of the main line traffic flow, reduces the influence on the running of main line vehicles, and simultaneously improves the traffic capacity of the expressway. However, the ramp control method adopted in China today mainly utilizes traffic flow data acquired by a fixed detector on a main line road to estimate the traffic flow which can enter from the ramp. The accuracy of the traffic data collected by the fixed detector is not high, and the traffic data can only reflect the traffic condition of the fixed point within a period of time, so that the real-time requirement cannot be met. In addition, the existing ramp control method does not consider the running characteristics of single vehicles, and the unsuitable merging behavior of ramp vehicles can still cause great influence on the main line traffic flow.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provide a ramp cooperative import control method and system of intelligent networked vehicles, which reduce the influence on the operation of main line vehicles and improve the operation efficiency of highway traffic flow by controlling the import quantity and the import sequence of the vehicles at the entrance ramp of the highway.
The invention adopts the following technical scheme for solving the technical problems:
the invention provides a ramp cooperative entry control method of an intelligent networked vehicle, which comprises the following specific steps:
and 3, according to the sequence of the optimized vehicles merged into the main line obtained in the step 2, when ramp vehicles are allowed to be merged into the main line, recording the main line vehicles, the ramp vehicles allowed to be merged and the ramp vehicles not allowed to be merged in the decision process, and sending control instructions to the currently processed vehicles according to the sequence of the optimized vehicles merged into the main line.
As a further optimization scheme of the intelligent network vehicle ramp collaborative converging control method, the running state data in the step 1 comprise acceleration, speed and position information.
As a further optimization scheme of the ramp collaborative merging control method of the intelligent networked vehicle, the number of permitted merging ramp vehicles and the merging sequence of the permitted merging ramp vehicles into the main line are determined in step 2 by adopting genetic optimization.
As a further optimization scheme of the ramp collaborative merging control method of the intelligent networked vehicle, the gene coding in the genetic method is represented by 1 as a main line vehicle and 0 as a ramp vehicle, so that each individual in the genetic method represents a vehicle merging sequence formed by current m main line vehicles and r ramp vehicles; setting the size of a population to be N, and initializing the population to show the merging sequence of N vehicles; calculating the fitness of all individuals in the population, obtaining a new population containing N vehicle import sequences through selection operation, cross operation and variation operation, and repeating the previous operation; and after the maximum genetic algebra P is executed, obtaining the optimized number of allowed ramp vehicles to be imported and the order of the vehicles to be imported into the main line.
As a further optimization scheme of the intelligent network vehicle ramp collaborative converging control method, the genetic method specifically comprises the following steps:
step 5-1, the gene codes in the genetic method are represented by 1 as a main line vehicle and 0 as a ramp vehicle, so that each individual in the genetic method represents a vehicle import sequence formed by current m main line vehicles and r ramp vehicles; setting the size of a population to be N, and initializing the population to show the merging sequence of N vehicles;
5-2, for the individuals in the new population, when the number of 1 in one individual is not consistent with the current actual number of the mainline vehicles, directly endowing the fitness of the individual with a tiny positive number; when the number of 1 s and 0 s in the gene codes completely corresponds to the number of the main line vehicles and the ramp vehicles, calculating the fitness u, and integrating the travel time of the main line vehicles and the afflux number of the ramp vehicles in the formation process of the queue according to the virtual queue distribution when the main line vehicles and the ramp vehicles pass through the afflux point; the method comprises the following specific steps:
5-2-1, according to the total number r of unprocessed ramp vehicles and the number r of left ramp vehicleslCalculating the normalized ramp vehicle influx number f1 *：
5-2-2 according to the travel time tt of the ith mainline vehicleiThe number m of main line vehicles, the distance l between the ith main line vehicle and the convergence pointiMinimum desired vehicle speed viminAnd a maximum desired vehicle speed vimaxCalculating a normalized travel time of the main-line vehicle
5-2-3 by using a weighted sum method by normalizing the main line vehicle travel time f1 *Number of vehicles merging on the same ramp
Respectively constant coefficient w1And w2And calculating the fitness u:
step 5-3, after the fitness of all individuals in a population is obtained, obtaining a new population containing N vehicle import sequences through selection operation, cross operation and variation operation; when the genetic algebra is smaller than the set maximum genetic algebra P, turning to the step 5-2, otherwise, turning to the step 5-4;
and 5-4, after the maximum genetic algebra P is executed, determining the sequence of the optimized vehicles converging into the main line according to the individual with the maximum fitness.
As a further optimization scheme of the ramp collaborative merge control method of the intelligent networked vehicle, based on the optimization sequence in step 3, ramp vehicles behind the last main line vehicle are not allowed to merge, and are still used as unprocessed vehicles to be subjected to the next merge decision process, and other vehicles are marked as processed vehicles; integrating the vehicle import sequence with the vehicle running state data, sending a control instruction to each vehicle currently processed, informing the state information of the vehicles ahead of the virtual queue, and guiding the vehicles to finish the cooperative adaptive cruise control operation.
A ramp cooperative convergence control system of an intelligent networked vehicle comprises a roadside control unit and DSRC wireless communication equipment, wherein the roadside control unit is arranged at the intersection of a main lane and an entrance ramp of an expressway and is positioned in a cooperative convergence control area, the cooperative convergence control area consists of the rightmost lane of the expressway, the entrance ramp, an acceleration lane, a convergence point and a convergence decision point, and the actual control range of the area depends on the communication range of the roadside control unit; the road side control unit comprises an information detection system, a data processing system, a data storage system and an information distribution system, wherein,
the DSRC wireless communication equipment is used for carrying out information transmission on the roadside control unit and the intelligent networked vehicles in a communication range in real time;
the information detection system is used for collecting current running state data of all unprocessed main lines and ramp vehicles when the ramp vehicles which are not subjected to the import decision processing reach the import decision point in the cooperative import control area;
the data processing system is used for optimizing and determining the number of ramp vehicles allowed to be imported and the order of the ramp vehicles imported into the main line;
the data storage system is used for recording the main line vehicles, the ramp vehicles allowed to merge and the ramp vehicles not allowed to merge involved in the decision making process when ramp vehicles are allowed to merge into the main line;
and the information issuing system is used for sending control commands to the vehicles which are currently processed according to the sequence of the optimized vehicles merging into the main line.
Compared with the prior art, the invention adopting the technical scheme has the following technical effects:
(1) the method comprises the steps that advanced information detection technology, wireless communication technology and intelligent control technology are utilized, the vehicles transmit running states of the vehicles to a road side control unit and peripheral vehicles after entering a cooperative control area, the control unit determines the number of vehicles merging into a main line of a ramp and the merging sequence of the vehicles according to traffic flow conditions in the control area by taking maximization of the number of vehicles merging into the ramp and minimization of running time of main line vehicles as targets;
(2) in the traditional ramp control method, the traffic flow of the ramp converging into the main line mainly depends on the main line traffic flow operation characteristic data acquired by a fixed detector on the main line, the data precision of the fixed detector is not high, the information is relatively lagged, the real-time requirement of converging traffic flow control is difficult to meet, the control threshold involved in the implementation process of the traditional method is not easy to determine, and the selection of the threshold can cause great influence on the control result; in the invention, the collaborative import decision process is based on the real-time state information of the main line and the ramp vehicles, and the vehicle import sequence is optimized by predicting the virtual queue operation characteristics under different vehicle import sequences, thereby greatly enhancing the reliability of the control method;
(3) in the traditional ramp control method, the traffic flow control of the ramp merging into the main line mostly takes the traffic capacity of the main line traffic flow as a target, and the queuing and backflow phenomena of vehicles at the entrance ramp are rarely considered; in the invention, the control unit fully considers the current traffic running conditions and the expected traffic flow running characteristics on the two lanes, optimizes an objective function and simultaneously relates to the expected results of a main line vehicle and a ramp vehicle, so that the ramp vehicle is converged to fully cooperate with the main line vehicle, and the running efficiency of the main line and ramp traffic flow is improved on the basis of improving the traffic capacity of the expressway;
(4) according to the invention, the number of vehicles entering the ramp and the vehicle entering sequence of the ramp are optimized by combining the expected running characteristics of traffic flows under different vehicle entering sequences according to the real-time state information of the vehicles on the main line around the entrance ramp of the expressway and the vehicles on the ramp, so that the problems of traffic jam, vehicle collision and the like caused by the confliction of the main line around the ramp and the vehicles on the ramp can be solved, and the high efficiency and the orderliness of the operation of the expressway traffic system are realized.
Drawings
Fig. 1 is a schematic diagram of an intelligent networked vehicle cooperative convergence control area according to the present invention.
Fig. 2 is a schematic structural diagram of the ramp cooperative import control method of the intelligent networked vehicle of the present invention.
Fig. 3 is a schematic flow chart of the ramp cooperative import control method of the intelligent networked vehicle of the present invention.
FIG. 4 is a schematic diagram of the present invention for optimizing vehicle import sequence using a genetic algorithm.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention will be described in detail with reference to the accompanying drawings and specific embodiments.
Example (b):
the present embodiment is based on the following assumptions:
(1) in the embodiment, the cooperative convergence control area is in an intelligent network connection environment, a roadside control unit is arranged at the intersection of a main line and a ramp, and the actual coverage area of the control area depends on the transmission range of DSRC communication equipment loaded by the roadside unit;
(2) after entering the control area, the vehicle can perform real-time information transmission with other vehicles and roadside units around, completely follow the instruction of the roadside control unit, and follow the vehicle ahead of the virtual queue to perform following operation according to a given cooperative adaptive cruise control rule;
(3) in the cooperative convergence control area, the position of a convergence point is fixed, and convergence operation is executed on all ramp vehicles at the point;
(4) the speed of information transmission and data processing is fast enough and the delay generated in the middle process is negligible.
The specific implementation method is as follows:
fig. 1 is a schematic diagram of a cooperative convergence control area of an intelligent networked vehicle according to the present invention. The area consists of a right-most lane of the expressway, an entrance ramp, an acceleration lane, a convergence point and an convergence decision point, and the actual control range of the area depends on the communication range of the roadside control unit.
Fig. 2 is a schematic structural diagram of the ramp cooperative entry control method of the intelligent networked vehicle according to the present invention. The information detection system in the road side control unit monitors the running state of the ramp vehicles in real time, and when the ramp vehicles which are not subjected to import decision processing reach an import decision point in a control area, the information detection system collects acceleration, speed and position information of all unprocessed main lines and ramp vehicles at the current moment and transmits the acceleration, speed and position information to the data processing system and the information publishing system; the data processing system optimizes the vehicle import sequence based on a genetic algorithm and sends the optimized result to the data storage system according to the real-time state data of the main line vehicle and the ramp vehicle, with the targets of the minimum travel time of the main line vehicle and the maximum import number of the ramp vehicle; according to the optimized vehicle import sequence obtained by the data processing system, when ramp vehicles are allowed to be imported into the main line, all the main line vehicles and all the ramp vehicles allowed to be imported are marked as processed vehicles, the data storage system transmits the processed results to the information issuing system, and the information issuing system sends an import control instruction to each vehicle, informs the state information of the vehicles in front of the virtual queue and guides the vehicles to complete the cooperative adaptive cruise control operation.
The following details the ramp cooperative merge control strategy of the present embodiment with reference to fig. 3 and fig. 4, including the following steps:
step S1: when the genes are coded, a main line vehicle is represented by '1', a ramp vehicle is represented by '0', and each individual in the genetic algorithm represents a possible vehicle merging sequence formed by current m main line vehicles and r ramp vehicles; setting the size of a population to be N, and initializing the population to show N possible vehicle import sequences;
step S2: for individuals in the new population, the number of '1' may not be consistent with the current actual number of the mainline vehicles, and the fitness of the individuals is directly endowed with a tiny positive number; when the number of "1" and "0" in the gene coding completely corresponds to the number of the main line vehicles and the ramp vehicles, the calculation of the fitness u integrates the travel time of the main line vehicles and the number of the ramp vehicles merged in the formation process of the queue according to the virtual queue distribution when the main line vehicles and the ramp vehicles pass through the merging point, and the specific steps are as shown in step S21 to step S23:
step S21: according to the total number r of vehicles on the ramp and the number r of vehicles on the remaining ramplCalculating the normalized ramp vehicle influx number f1 *：
Step S22: according to the travel time tt of the main line vehicle iiThe number m of main line vehicles, the distance l between the main line vehicle i and the junction pointiMinimum desired vehicle speed viminAnd a maximum desired vehicle speed vimaxCalculating a normalized travel time of the main-line vehicle
Step S23: using a weighted sum method, by assigning a normalized dominant line vehicle travel time f1 *Number of vehicles merging on the same ramp
Respectively constant coefficient w1And w2And calculating the fitness u:
step S3: after the fitness of all individuals in a population is obtained, a new population containing N possible vehicle import sequences is obtained through selection operation, cross operation and variation operation; when the genetic algebra is smaller than the set maximum genetic algebra P, turning to step S2, otherwise, turning to step S4;
step S4: and after the maximum genetic algebra P is executed, determining the optimized vehicle importing sequence according to the individual with the maximum fitness.
The above description is only for the specific embodiment of the present invention, but the scope of the present invention is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present invention are included in the scope of the present invention.
Claims (4)
1. A ramp cooperative convergence control method for an intelligent networked vehicle is characterized by comprising the following specific steps:
step 1, collecting current running state data of all unprocessed main lines and ramp vehicles when ramp vehicles which are not subjected to convergence decision processing reach a convergence decision point in a cooperative convergence control area;
step 2, according to the real-time running state data of the main line and the ramp vehicles, optimizing and determining the number of ramp vehicles allowed to be imported and the order of the ramp vehicles imported into the main line according to the target that the travel time of the main line vehicle is minimum and the number of ramp vehicles imported into the ramp vehicle is maximum;
step 3, according to the sequence of the optimized vehicles merged into the main line obtained in the step 2, when ramp vehicles are allowed to be merged into the main line, recording the main line vehicles, the ramp vehicles allowed to be merged and the ramp vehicles not allowed to be merged in the decision process, and sending control instructions to the currently processed vehicles according to the sequence of the optimized vehicles merged into the main line;
step 2, optimizing and determining the number of allowed ramp vehicles and the sequence of allowed ramp vehicles entering a main line by adopting a genetic method;
the genetic code in the genetic method is represented by 1 as a main line vehicle and 0 as a ramp vehicle, so that each individual in the genetic method represents a vehicle import sequence formed by current m main line vehicles and r ramp vehicles; setting the size of a population to be N, and initializing the population to show the merging sequence of N vehicles; calculating the fitness of all individuals in the population, obtaining a new population containing N vehicle import sequences through selection operation, cross operation and variation operation, and repeating the previous operation; after the maximum genetic algebra P is executed, obtaining the optimized number of allowed ramp vehicles which are allowed to be imported and the order of the vehicles which are imported into the main line;
the genetic method specifically comprises the following steps:
step 5-1, the gene codes in the genetic method are represented by 1 as a main line vehicle and 0 as a ramp vehicle, so that each individual in the genetic method represents a vehicle import sequence formed by current m main line vehicles and r ramp vehicles; setting the size of a population to be N, and initializing the population to show the merging sequence of N vehicles;
5-2, for the individuals in the new population, when the number of 1 in one individual is not consistent with the current actual number of the mainline vehicles, directly endowing the fitness of the individual with a tiny positive number; when the number of 1 s and 0 s in the gene codes completely corresponds to the number of the main line vehicles and the ramp vehicles, calculating the fitness u, and integrating the travel time of the main line vehicles and the afflux number of the ramp vehicles in the formation process of the queue according to the virtual queue distribution when the main line vehicles and the ramp vehicles pass through the afflux point; the method comprises the following specific steps:
5-2-1, according to the total number r of unprocessed ramp vehicles and the number r of left ramp vehicleslCalculating the normalized ramp vehicle influx number f1 *：
5-2-2 according to the travel time tt of the ith mainline vehicleiThe number m of main line vehicles, the distance l between the ith main line vehicle and the convergence pointiMinimum desired vehicle speed viminAnd a maximum desired vehicle speed vimaxCalculating a normalized travel time of the main-line vehicle
5-2-3 by using a weighted sum method by normalizing the main line vehicle travel time f1 *Number of vehicles merging on the same ramp
Respectively constant coefficient w1And w2And calculating the fitness u:
step 5-3, after the fitness of all individuals in a population is obtained, obtaining a new population containing N vehicle import sequences through selection operation, cross operation and variation operation; when the genetic algebra is smaller than the set maximum genetic algebra P, turning to the step 5-2, otherwise, turning to the step 5-4;
and 5-4, after the maximum genetic algebra P is executed, determining the sequence of the optimized vehicles converging into the main line according to the individual with the maximum fitness.
2. The method for controlling the cooperative ramp influx of the intelligent networked vehicle as claimed in claim 1, wherein the operation state data in step 1 comprises acceleration, speed and position information.
3. The method according to claim 1, wherein, in step 3, based on the optimization sequence, ramp vehicles behind the last main line vehicle are not allowed to merge, and remain as unprocessed vehicles to be subjected to the next merging decision process, and other vehicles are marked as processed vehicles; integrating the vehicle import sequence with the vehicle running state data, sending a control instruction to each vehicle currently processed, informing the state information of the vehicles ahead of the virtual queue, and guiding the vehicles to finish the cooperative adaptive cruise control operation.
4. The control system of the ramp cooperative merging control method of the intelligent networked vehicle as claimed in claim 1, comprising a roadside control unit and DSRC wireless communication equipment, wherein the roadside control unit is arranged at the intersection of a main lane and an entrance ramp of the expressway and is located in a cooperative merging control area, the cooperative merging control area is composed of a rightmost lane of the expressway, an entrance ramp, an acceleration lane, a merging point and a merging decision point, and the actual control range of the area depends on the communication range of the roadside control unit; the road side control unit comprises an information detection system, a data processing system, a data storage system and an information distribution system, wherein,
the DSRC wireless communication equipment is used for carrying out information transmission on the roadside control unit and the intelligent networked vehicles in a communication range in real time;
the information detection system is used for collecting current running state data of all unprocessed main lines and ramp vehicles when the ramp vehicles which are not subjected to the import decision processing reach the import decision point in the cooperative import control area;
the data processing system is used for optimizing and determining the number of ramp vehicles allowed to be imported and the order of the ramp vehicles imported into the main line;
the data storage system is used for recording the main line vehicles, the ramp vehicles allowed to merge and the ramp vehicles not allowed to merge involved in the decision making process when ramp vehicles are allowed to merge into the main line;
and the information issuing system is used for sending control commands to the vehicles which are currently processed according to the sequence of the optimized vehicles merging into the main line.
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