CN114627647B - Mixed traffic flow optimal control method based on combination of variable speed limit and lane change - Google Patents
Mixed traffic flow optimal control method based on combination of variable speed limit and lane change Download PDFInfo
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Abstract
The invention discloses a mixed traffic flow optimization control method based on combination of variable speed limit and lane change, which comprises the following steps: s1, dividing a road network into a VSL control area, an LC control area and a bottleneck area; s2, calculating expected output flow of each lane in the VSL control area; s3, calculating the expected speed of each lane in the VSL control area and the speed limit value of the single vehicle of each vehicle; s4, lane change control is carried out on the vehicles in the LC control area. According to the invention, the variable speed limit value is customized for each vehicle at different positions through the internet of vehicles technology, and the speed limit is directly sent to a corresponding single vehicle, so that the influence that the number and the positions of the traditional speed limit signboard are fixed and cannot be flexibly changed is overcome. Meanwhile, when the variable speed limiting algorithm is designed, the permeability of the automatic driving vehicle is considered, and the compliance of the human driving vehicle is considered, so that the effect of variable speed limiting control is improved.
Description
Technical Field
The invention belongs to the technical field of intelligent traffic information, and particularly relates to a mixed traffic flow optimization control method based on combination of variable speed limit and lane change.
Background
In the peak period of national trip, large-scale traffic jam is caused, especially in the bottleneck road sections which are easy to generate traffic jam, such as the reduction of the number of expressway tracks, the interweaving area of main road and ramp, and the like, caused by road design, construction and maintenance, traffic events, and the like. The traffic demand upstream of the bottleneck region is greater than the maximum traffic capacity of the bottleneck region, vehicles are queued from the bottleneck region, and traffic congestion is easily formed in the bottleneck region. Traffic congestion often causes a decrease in road traffic capacity, i.e., a phenomenon of decreased traffic capacity, further exacerbating the degree of congestion of the vehicle. In addition, traffic congestion can have many negative effects, including higher fuel consumption and exhaust emissions, increased risk of vehicle collisions, and serious driving discomfort.
Currently, most scholars use Variable speed limit (Variable SPEED LIMIT, VSL) control and lane change control strategies to solve the problem of reduced traffic capacity in urban expressway bottleneck areas. Most of variable speed limiting control is to obtain real-time data of each traffic parameter of a road section through fixed sensor equipment such as road monitoring and detectors, and adjust the speed limit of vehicles on a lane in a speed limiting mode of the road section, so that traffic jam is effectively relieved, and the purposes of improving driving safety and improving traffic environment are achieved. There are a number of drawbacks to this variable speed limit. The conventional variable speed limit is to estimate traffic state through historical data measured by fixed sensors arranged on a road, and real-time performance of the traffic state cannot be reflected, while the road state between the fixed sensors is an unknown state. In addition, the placement position of the variable speed limit signboard, the rate of change of the speed limit value, the compliance of the driver with the speed limit value, and other factors have significant influence on the control effect of the variable speed limit. The lane change control is to send lane change information to the vehicle in advance so that the vehicle finishes lane change operation a certain distance in front of the bottleneck, most vehicles are prevented from lane change at the bottleneck, traffic jam at the bottleneck is relieved, and the traffic capacity at the bottleneck is enabled to reach the maximum traffic capacity.
With the development of the internet of vehicles and automatic driving technologies, the emerging internet-connected automatic driving vehicles (Autonomous Vehicle, AV) can not only transmit real-time information, but also can run strictly according to given instructions. The system can overcome the disadvantage of data acquisition of the fixed sensor and eliminate the problem of compliance of a human driver to the speed limit value. But in the future, the road must be a traffic flow state where an autonomous vehicle and a Human Vehicle (HV) are mixed. Therefore, when designing a variable speed limit and lane change combined control method, it is necessary to consider the mixed traffic flow state of an autonomous vehicle and a human-driven vehicle.
Patent document CN113450583a discloses a variable speed limit and lane change cooperative control method for a highway under the cooperation of a vehicle and a road, and the method is based on real-time information sharing of the cooperation of the vehicle and the road, and judges whether the traffic density of each control section on a main line of the highway is greater than a critical density or not through prediction, and performs variable speed limit control and cooperative lane change control on each control section on the main line of the highway, thereby regulating and controlling the flow flowing into the downstream, and further improving the traffic efficiency of the highway. However, the method is to carry out speed limiting control on each control road section on the main line of the expressway according to lanes, only the same speed limiting value can be applied to vehicles in the same road section, and more accurate and reasonable speed limiting values can not be determined according to the state of each vehicle. Meanwhile, the control effect of the variable speed limit method is affected by the driver's compliance with the speed limit value, but the method does not propose a control method for this factor.
Disclosure of Invention
The invention aims to provide a mixed traffic flow optimal control method based on combination of variable speed limit and lane change, which is used for controlling speed limit and lane change of a single vehicle at the upstream of a bottle neck region by adopting a mixed traffic flow optimal control method based on combination of variable speed limit and lane change when traffic congestion occurs in a bottleneck region of an urban expressway through a vehicle networking technology under the mixed traffic condition of automatic driving and human driving, so that the reduction of road traffic capacity of the bottleneck region caused by traffic congestion is avoided, the maximum road traffic capacity of the bottleneck region can be achieved under the condition of road congestion, and the road traffic efficiency is improved.
In order to achieve the above purpose, the present invention provides the following technical solutions: a mixed traffic flow optimal control method based on combination of variable speed limit and lane change comprises the following steps:
S1, dividing a road network into a VSL control area, an LC control area and a bottleneck area along the running direction of a vehicle; the VSL control zone and the LC control zone are both upstream of the bottleneck zone, the LC control zone being located between the VSL control zone and the bottleneck zone;
Numbering the lane with m from right to left along the lane width direction, wherein m is {0,1, …, N };
deploying an RSU in the bottleneck area, and collecting position, speed and lane information of each vehicle in the VSL control area and the LC control area through the RSU;
transmitting the information collected by the RSU to a central server for operation;
s2, calculating expected output flow of each lane in the VSL control area according to the average speed of each lane in the LC control area;
S3, calculating the expected speed of each lane in the VSL control area according to the expected output flow and the average density of each lane in the VSL control area;
Calculating a single vehicle speed limit value of each automatic driving vehicle and each human driving vehicle according to the expected speed, the density and the maximum speed limit value of each lane in the VSL control area;
s4, lane change control is carried out on the vehicle in the LC control area;
calculating the density of each lane of the LC control area according to the number of vehicles of each lane of the LC control area;
Calculating the expected lane change vehicle number of each lane according to the actual density of each lane and the average density of the non-narrowed lanes of the LC control area;
And selecting a proper vehicle to change the lane according to the expected number of lane-changing vehicles of each lane of the LC control area, the number of vehicles of the automatic driving vehicle and the compliance degree of the human driving vehicle.
Further, in the step S1, the RSU and the vehicle transmit information by using wireless connection signals, and transmit information by using wired connection with the central server; the vehicles are provided with a positioning system and a wireless communication device.
Further, the step S2 includes the following steps:
S21: and introducing parameters r E [0,1] to describe the influence of vehicle lane changing in the LC control area on the traffic efficiency of the bottleneck area, wherein the value of the parameters r is related to the number of lanes narrowed in the bottleneck area, and the more the number of the narrowed lanes is, the larger the value of r is. For example, in the case of a 4 lane to 3 lane change, a value of 0.2 is recommended for r;
S22: calculating the maximum allowable output flow of each lane in the VSL control area according to the number of lanes upstream of the bottleneck area, the number of lanes downstream of the bottleneck area, the parameter r and the maximum traffic capacity of the bottleneck area, and expressing by using a formula;
Wherein r is [0,1]; n U represents the number of lanes upstream of the bottleneck (including LC control region and VSL control region); n D represents the number of lanes downstream of the bottleneck; c represents the maximum capacity downstream of the bottleneck region (bottleneck section).
S23: and calculating the expected output flow of each lane of the VSL control area according to the average speed of each lane of the LC control area, the maximum allowable output flow and the maximum speed limit value of the vehicle, and expressing the expected output flow by using a formula.
Wherein the method comprises the steps ofAn average speed of lane m representing the LC control zone in the last period, wherein 0.ltoreq.m.ltoreq.N; sl Max represents the maximum speed limit of the vehicle;
further, the step S3 includes the following steps:
S31: setting a speed limit value updating time u i for each vehicle i to represent the next speed limit value updating time of the vehicle i;
S32: calculating the average vehicle density d m,k-1 of each lane m of the VSL control area in the last period according to the vehicle speed and lane information acquired by the RSU;
S33: and (2) calculating the expected speed of each lane of the VSL control area according to the relation among the traffic flow, the density and the speed of the lane based on the expected traffic flow of each lane of the VSL control area in S2 and the average vehicle density of the lane, and expressing the expected speed by using a formula.
Where d m,k-1 represents the average vehicle density over lane m in the VSL control region during the last cycle; f m,k represents the desired output flow of lane m.
Further, in S31, the vehicles i are classified into automatic driving vehicles and human driving vehicles; the speed limit value of the autonomous vehicle is set to the desired speed of lane m, i.eThe speed limit value calculating method of the human-driven vehicle comprises the following steps:
1) Calculating the degree of the compliance of the vehicle of the VSL control area with the speed limit value in the last control period according to the average speed and the expected speed of the VSL control area, and expressing the degree by using a formula;
Wherein v m,k-1 and Respectively representing the average speed and the expected speed on the lane m of the VSL control area in the last updating period;
2) Calculating the average speed which can be driven by a human-driven vehicle which does not follow the speed limiting value in the VSL control area according to the permeability of the automatic driving vehicle, the density of each lane in the VSL control area, the critical density of the lanes and the maximum speed limiting value of the vehicle, wherein the average speed can be expressed by using a formula;
Wherein β represents the permeability of AV; d Max represents the maximum density of a single lane; d c represents the critical density of a single lane, namely the road density corresponding to the maximum traffic capacity; p represents compliance with HV; v represents the average speed of HV that does not obey the speed limit; b represents the average speed of the vehicle that is subject to speed constraints in the VSL control zone; SL represents the maximum speed that HV, which does not adhere to the speed limit, can reach in the VSL control zone.
For HVs that do not adhere to speed control in the VSL control zone, if the road is not congested (i.e., 0 < d m,k≤dc), they can accelerate to a maximum speed limit sl Max (such as free-flow traffic). However, the HV may not be able to accelerate to the maximum speed limit sl Max because its speed is limited by neighboring vehicles, such as its lead vehicle. Therefore, when 0 < d m,k≤dc, Given by the formula, the average speed of the vehicle that is subject to the speed limit in the VSL control zone is represented. When d c＜dm,k≤dMax, HV that does not obey the speed limit cannot accelerate to the maximum speed limit sl Max, for which reason use/>Representing the maximum speed that an HV that does not adhere to the speed limit can reach in the VSL control zone, is calculated using a formula. Therefore, at the time of d c＜dm,k≤dMax,
3) Calculating a speed limit value sl i,k of the driving vehicle according to the expected speed of each lane of the VSL control area, the average speed of the driving vehicle which does not accord with the speed limit value and the degree of the driving vehicle which accords with the speed limit value of the VSL control area, and obtaining the speed limit value sl i,k of the driving vehicle by solving a formula;
4) Rounding down the determined speed limit value to the nearest Integer multiples of (1), wherein/>For a given constant, the value is usually 5km/h or 10km/h, and can be calculated according to a formula;
After the speed limit of the automatically driven vehicle or the man-driven vehicle is obtained, the time required for accelerating or decelerating the vehicle i to a given speed limit value is calculated according to the maximum comfortable acceleration, the minimum comfortable deceleration and the instantaneous speed of the vehicle i, and can be expressed by using a formula;
Where v i,t represents the instantaneous speed of vehicle i at time t; a i,max and b i,max represent the maximum comfortable acceleration and minimum comfortable deceleration, respectively, of the vehicle i.
Calculating the next speed limit value updating time of the vehicle i according to the current time t and the time required by the vehicle i to accelerate or decelerate to a given speed limit value, wherein the next speed limit value updating time of the vehicle i can be expressed by using a formula;
ui＝t+ti,k (1.11)
In order to avoid frequent acceleration and deceleration of the vehicle, a new speed limit value is recalculated for the vehicle only after the vehicle accelerates or decelerates to the speed limit value, i.e. the speed limit value updating time of each vehicle is independent.
Further, the step S4 includes the following steps:
S41: calculating the road density of all lanes in the LC control area according to the collected vehicle lanes and position information, using M.epsilon.0, 1, …, N } represents the road density of lane m in the LC control area; calculating the average road density/> of the non-narrowed lanes according to the road density of each lane and the number of the non-narrowed lanesFor ease of understanding, assuming that only the right lane is narrowed and the number of narrowed lanes is δ, the average road density/>Can be calculated using a formula;
s42: the expected lane change number of each non-narrowed lane in the LC control area is calculated so that the density of the non-narrowed lane is equal to the average road density. In order to make the road density and average road density of the non-narrowed lanes Equal, it is necessary to determine the average road density/> according to the non-narrowed lanesTo calculate the number of desired lane change vehicles per lane in the LC control area, use/>M-w=1 represents the number of vehicles in the LC control area that change lanes from lane m to lane w, and m-w=1 represents that the vehicles cannot change lanes continuously. Since only the right lane is narrowed, the vehicles on the narrowed lane need to change into the left lane, resulting in more vehicles on the lane closer to the right narrowed lane and greater lane density. Therefore, it can be considered that the vehicle on the right lane needs to change lanes to the left lane in order to make the road density of the non-narrowed lane reach the average road density/>Based on this assumption, the expected lane change vehicle number per lane in the LC control area/>Can be determined according to the following method:
first, starting from the leftmost lane N, the number of vehicles that change lanes N-1 to N can be calculated from the road density of the leftmost lane N Calculation using the formula:
Wherein L LC represents the length of the LC control region. Then, the density of the lane N-1 is changed to Calculation using the formula:
for lanes N-1 through delta, the number of lane-changing vehicles expected for each remaining non-narrowed lane can be calculated using the method described above. After determining the number of vehicles desiring lane changing for each non-narrowed lane, selecting a vehicle lane changing meeting the condition with step S43;
S43: selecting proper vehicles to change lanes according to the expected number of lane-changing vehicles of each lane in the LC lane-changing control area;
when the lane change vehicle is selected, an automatic driving vehicle is preferably selected; when the number of the automatic driving vehicles is smaller than the number of the expected lane change vehicles, the number of the driving vehicles needing lane change is calculated according to the difference between the compliance degree of the driving vehicles, the number of the expected lane change vehicles and the number of the automatic driving vehicles, and the driving vehicles meeting the number of the expected lane change vehicles are randomly selected from the driving vehicles to change lanes. Wherein, the number of people driving The formula may be used to calculate:
where p represents the compliance of a person driving.
S44: for the vehicle on the narrowed lane, after entering the lane change control area, the lane is changed to the non-narrowed lane as far as possible on the premise of meeting the lane change safety, so that the lane change behavior of the vehicle at the bottleneck position is reduced.
The beneficial effects are that:
Aiming at the problem of reduced traffic capacity in a bottleneck area in the prior art, the invention provides a mixed traffic flow optimization control method based on combination of variable speed limit and lane change, which has the beneficial effects that:
1. Compared with the traditional variable speed limit, the hybrid traffic flow optimization control method based on the combination of variable speed limit and lane change is not only based on real-time macroscopic traffic information (average speed and average density of roads) but also based on real-time microscopic vehicle information (acceleration, deceleration and speed of single vehicle) to determine the speed limit value of single vehicle. Since real-time microscopic information can reflect the behavior of a single vehicle, the speed limit value determined for the single vehicle is more accurate and reasonable than the speed limit value determined for a road section.
2. Compared with the traditional speed limiting technology, the variable speed limiting value is customized for each vehicle at different positions through the internet of vehicles technology and the speed limiting value is directly sent to a corresponding single vehicle, so that the influence that the number and the position of the traditional speed limiting signboard are fixed and cannot be flexibly changed is overcome. Meanwhile, when the variable speed limiting algorithm is designed, the permeability of the automatic driving vehicle is considered, and the compliance of the human driving vehicle is considered, so that the effect of variable speed limiting control is improved.
3. According to the invention, variable speed limit and lane changing are combined, so that on one hand, the influence of lane changing behavior of vehicles near the bottleneck on variable speed limit performance is eliminated, on the other hand, lane changing is completed by a distance on the upstream of the bottleneck through lane changing control, the centralized lane changing behavior of the vehicles at the bottleneck is eliminated, the traffic capacity of the bottleneck is maximized as much as possible, the traffic capacity decline phenomenon of the bottleneck is greatly reduced, and the road traffic efficiency is improved.
Drawings
FIG. 1 is a flow chart of a hybrid traffic flow optimization control method based on variable speed limit and lane change combination;
Fig. 2 is a schematic diagram of a road network structure.
Detailed Description
The present invention will be further described with reference to the following detailed description, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to like or similar elements or elements having like or similar functionality throughout.
Example 1
As shown in fig. 1 to 2, the present embodiment provides a hybrid traffic flow optimization control method based on variable speed limit and lane change combination, which includes the following steps:
Step A: dividing the upstream of the bottleneck area into a VSL control area and a lane change (LANE CHANGE, LC) control area, collecting information such as the position, the speed and the lane of each vehicle in the VSL control area and the LC control area through communication between the vehicles (Vehicle to Vehicle, V2V) and the vehicles and the infrastructure (Vehicle to Infrastructure, V2I), transmitting the information to a central server through an RSU, and operating a mixed traffic flow optimization control method with variable speed limit and lane change on the server;
and (B) step (B): calculating expected output flow of each lane in the VSL control area according to the average speed information of each lane in the LC control area;
Step C: calculating the expected speed of each lane in the VSL control area according to the expected output flow of each lane in the VSL control area and the average density of each lane, and calculating the speed limit value of each automatic driving vehicle and each individual driving vehicle according to the information such as the expected speed of the lane, the density of the lane, the maximum speed limit value and the like;
step D: and (5) performing lane change control on the vehicle in the LC control area. Firstly, calculating the average road density of each lane of the LC control area according to the number of vehicles of each lane of the LC control area. And then calculating the expected lane change vehicle number of each lane according to the actual road density of each lane and the average road density information of the LC control area. And finally, selecting a proper vehicle to change the lane according to the expected number of lane-changing vehicles, the number of AV vehicles and the compliance degree of HV of each lane.
Further, in step a, the entire road network is divided into three parts, namely, a VSL control area, an LC control area, and a bottleneck area, and as shown in fig. 2, lanes are numbered m, m e {0,1, …, N } from right to left along the road width direction. The mixed traffic flow optimization control method combining variable speed limit and lane change operates on a central server, and the central server is connected with a road side unit (RoadSideUnit, RSU) in a wired connection mode. The RSU is deployed in a bottleneck section, with two network connection types. The first is a wireless connection through which the RSU and the vehicle transmit information, and the second is a wired connection through which the RSU can transmit information via a wired and central server connection. It is assumed that different types of sensors, global positioning systems and wireless communication devices, have been embedded in vehicles. Thus, the vehicle can collect real-time traffic information (such as speed and position information of the vehicle) while the vehicle is traveling on a road. And uploading the real-time traffic information to a central server. Specifically, real-time traffic information is first transmitted to the RSU through wireless communication and then transmitted to the central server through wired communication.
In step B, in order to minimize the drop in capacity of the bottleneck area, the purpose of the present invention is to increase the flow rate of the LC control area to the maximum capacity C. However, as the lane closes, the vehicle makes a lane change operation upstream of the bottleneck, resulting in a reduced capacity of the bottleneck area. Therefore, the invention firstly introduces a parameter r E [0,1] to describe the influence of vehicle lane changing in the LC control area on the traffic efficiency of the bottleneck area. The value of the parameter r is related to the number of lanes with narrowed bottleneck regions, and the more the number of lanes is narrowed, the larger the value of r is. For example, in the case of a 4 lane to 3 lane change, it is recommended that r take a value of 0.2. Then calculating the maximum allowable output flow of each lane in the VSL control area according to the number of lanes N U on the upstream of the bottleneck, the number of lanes N D on the downstream of the bottleneck, the parameter r and the traffic capacity C of the bottleneck section, and calculating by using a formula:
finally according to the average speed of each lane of the LC control area The maximum allowable output flow Φ 1 and the maximum speed limit value sl Max of the vehicle calculate the expected output flow for each lane of the VSL control zone, using the formula:
In step C, the present invention calculates a bicycle speed limit for the vehicle in the VSL control area. Since the acceleration and deceleration capability and the traffic state of different vehicles may be different, the present invention sets a speed limit value update time u i for each vehicle i. The limit value update time u i indicates the next limit value update time of the vehicle i. The invention firstly calculates the average vehicle density of each lane m of the VSL control area in the last period based on the collected vehicle speed and lane information. And then calculating the expected speed of each lane of the VSL control area according to the relation among the flow, the density and the speed based on the expected flow f m,k of each lane of the VSL control area in the step B and the average density d m,k-1 of the lanes, and calculating by using a formula:
finally, for a vehicle i on lane m of the VSL control area, if vehicle i is an autonomous vehicle, its speed limit value can be assumed to be the desired speed for lane m, i.e If the vehicle i is a human-driven vehicle, the method for calculating the speed limit value sl i,k of the vehicle i is described as the following steps:
Step C1: the degree to which the VSL control zone vehicle complies with the speed limit value in the last control period is calculated based on the average speed v m,k-1 and the desired speed of the VSL control zone To calculate, in particular using a formula;
step C2: calculating the average speed which can be driven by a person driving a vehicle and does not follow the speed limit value in the VSL control area, and calculating by using a formula:
wherein β represents the permeability of AV; d Max represents the maximum density of a single lane; d c represents the critical density of a single lane, namely the road density corresponding to the maximum traffic capacity; p represents compliance with HV; mean speed of HV that does not obey the speed limit; /(I) Representing the average speed of a vehicle that is subject to speed constraints in the VSL control area, can be calculated using a formula; /(I)Representing the maximum speed that a HV that does not adhere to the speed limit can reach in the VSL control zone can be calculated using a formula.
Step C3: calculating the speed limit value of the human driving vehicle according to the expected speed of each lane of the VSL control area, the average speed of the human driving vehicle which does not accord with the speed limit value, the degree of the VSL control area which accords with the speed limit value and the AV permeability information, and calculating by using a formula:
step C4: rounding down the determined speed limit value to the nearest Integer multiples of (1), wherein/>For a given constant, the value is usually 5km/h or 10km/h, and can be calculated according to a formula;
After obtaining the speed limit value sl i,k of the vehicle i, the invention calculates the time required for accelerating or decelerating the vehicle i to a given speed limit value according to the maximum comfortable acceleration, the minimum comfortable deceleration and the instantaneous speed of the vehicle i. Calculation using the formula:
Where v i,t represents the instantaneous speed of vehicle i at time t; a i,max and b i,max represent the maximum comfortable acceleration and minimum comfortable deceleration, respectively, of the vehicle i.
In order to avoid frequent acceleration and deceleration of the vehicle, a new speed limit is recalculated for the vehicle only after the vehicle has accelerated or decelerated to its speed limit value, i.e. the speed limit value update time is different for each vehicle. The next speed limit value update time of the vehicle i can be calculated from the current speed limit value update time and the time required to accelerate to a given speed limit value, using the formula:
ui＝t+ti,k (1.26)
In step D, the present invention performs lane change control on the vehicle in the LC control area. Further, for ease of understanding, it is assumed that only the right-side lane is narrowed and the number of narrowed lanes is δ. The lane change control method of the LC control area may be described as the following steps:
Step D1: the road density of all lanes in the LC control area and the average road density after all vehicles lane onto the non-narrowed lanes are calculated. First, the road density of each lane is calculated based on the collected vehicle lanes and position information, using M.epsilon.0, 1, …, N represents the road density of lane m in the LC control area. Then, the average road density/>, of the non-narrowed lanes of the LC control area is calculated from the road density of each lane, the number of non-narrowed lanesCalculating by using a formula;
step D2: in order to make the road density and average road density of the non-narrowed lanes Equal, it is necessary to determine the average road density/> according to the non-narrowed lanesTo calculate the number of desired lane change vehicles per lane in the LC control area, use/>M-w=1 represents the number of vehicles in the LC control area that change lanes from lane m to lane w, and m-w=1 represents that the vehicles cannot change lanes continuously. Since only the right lane is narrowed, the vehicles on the narrowed lane need to change into the left lane, resulting in more vehicles on the lane closer to the right narrowed lane and greater lane density. Therefore, it can be considered that the vehicle on the right lane needs to change lanes to the left lane in order to make the road density of the non-narrowed lane reach the average road density/>Based on this assumption, the expected lane change vehicle number/>, of the non-narrowed lane in the LC control areaCan be determined according to the following method:
first, starting from the leftmost lane N, the number of vehicles that change lanes N-1 to N can be calculated from the road density of the leftmost lane N Calculation using the formula:
Wherein L LC represents the length of the LC control region. Then, the density of the lane N-1 is changed to Calculation using the formula:
For lanes N-2 through delta, the number of lane-changing vehicles expected for each remaining non-narrowed lane can be calculated using the method described above. After determining the number of vehicles desiring lane changing per non-narrowed lane, a step D3 is used to select a vehicle lane changing meeting the condition.
Step D3: calculating the expected lane change number of each lane in the LC control areaThen, a suitable vehicle is required to be selected for lane change. Since the driving of a person may not follow the received lane change instruction, when the vehicle is selected, the automatic driving vehicle is preferably selected to change lanes, and the number of the automatic driving vehicles/>Less than the number of lane change expected vehicles/>When the vehicle is driven, the number of the vehicles to be changed is/>, according to the compliance degree of driving and the expected number of vehicles to be changedAnd the difference between the number of the automatic driving vehicles to calculate the driving quantity/>, of the person needing to change the laneRandomly selecting/>, from driving of peopleThe vehicle drives to change lanes. Number of person driving/>The formula may be used to calculate:
where p represents the compliance of a person driving.
Step D4: for the vehicle on the narrowed lane, after entering the lane change control area, the lane is changed to the non-narrowed lane as far as possible on the premise of meeting the lane change safety, so that the lane change behavior of the vehicle at the bottleneck position is reduced.
The above embodiments are only for illustrating the technical solution of the present invention and not for limiting the same, and although the present invention 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 invention, which is intended to be covered by the scope of the claims of the present invention.
Claims (5)
1. The mixed traffic flow optimal control method based on the combination of variable speed limit and lane change is characterized by comprising the following steps:
S1, dividing a road network into a VSL control area, an LC control area and a bottleneck area along the running direction of a vehicle; the VSL control zone and the LC control zone are both upstream of the bottleneck zone, the LC control zone being located between the VSL control zone and the bottleneck zone;
Numbering lanes m, m=0, 1, and N along the lane width direction;
deploying an RSU in the bottleneck area, and collecting position, speed and lane information of each vehicle in the VSL control area and the LC control area through the RSU;
Dividing the upstream of the bottleneck area into a VSL control area and a lane change LC control area, and collecting the position, speed and lane information of each vehicle in the VSL and LC control areas through communication between the vehicles and the vehicles V2V and between the vehicles and the infrastructure V2I;
The RSU and the vehicle adopt wireless connection signals to transmit information, and adopt wired connection to transmit information; the vehicles are provided with a positioning system and wireless communication equipment;
transmitting the information collected by the RSU to a central server for operation;
s2, calculating expected output flow of each lane in the VSL control area according to the average speed of each lane in the LC control area;
S3, calculating the expected speed of each lane in the VSL control area according to the expected output flow and the average density of each lane in the VSL control area;
Calculating a single vehicle speed limit value of each automatic driving vehicle and each human driving vehicle according to the expected speed, the density and the maximum speed limit value of each lane in the VSL control area;
s4, lane change control is carried out on the vehicle in the LC control area;
calculating the density of each lane of the LC control area according to the number of vehicles of each lane of the LC control area;
calculating the expected lane change vehicle number of each lane according to the actual density and the average density of each lane in the LC control area;
And selecting a proper vehicle to change the lane according to the expected number of lane-changing vehicles of each lane of the LC control area, the number of vehicles of the automatic driving vehicle and the compliance degree of the human driving vehicle.
2. The hybrid traffic flow optimization control method based on the combination of variable speed limit and lane change according to claim 1, wherein S2 comprises the steps of:
S21: introducing parameters r E [0,1] to describe the influence of vehicle lane changing in the LC control area on the traffic efficiency of the bottleneck area;
S22: calculating the maximum allowable output flow of each lane in the VSL control area according to the number of lanes upstream of the bottleneck area, the number of lanes downstream of the bottleneck area and the traffic capacity of the bottleneck area;
s23: and calculating the expected output flow of each vehicle in the VSL control area according to the average speed of each lane in the LC control area, the maximum allowable output flow and the maximum speed limit value of the vehicle.
3. The hybrid traffic flow optimization control method based on the combination of variable speed limit and lane change according to claim 2, wherein S3 comprises the steps of:
s31: setting a speed limit value updating time u i for each vehicle to represent the next speed limit value updating time of the vehicle i;
s32: calculating the average vehicle density of each lane m of the VSL control area in the last period according to the vehicle speed and lanes acquired by the RSU;
S33: and (2) calculating the expected speed of each lane of the VSL control area according to the relation among the traffic flow, the density and the speed of the lanes based on the expected traffic flow of each lane of the VSL control area and the average density of the lanes in the S2.
4. The hybrid traffic flow optimization control method based on the combination of variable speed limit and lane change according to claim 3, wherein the vehicles i in S31 are classified into autonomous vehicles and human driven vehicles; the speed limit value of the automatic driving vehicle is set to be the expected speed of the lane m; the speed limit value calculating method of the human-driven vehicle comprises the following steps:
1) Calculating the degree of compliance of the vehicle in the VSL control area with the speed limit value in the last control period according to the average speed and the expected speed of the VSL control area;
2) Calculating the average speed of the driving vehicle which does not follow the speed limit value in the VSL control area according to the permeability of the driving vehicle, the density of each lane in the VSL control area, the critical density of the lanes and the maximum limit of the vehicle;
3) Calculating the speed limit value of the driving vehicle according to the expected speed of each lane of the VSL control area, the average speed of the driving vehicle which does not accord with the speed limit value and the degree of the driving vehicle which accords with the speed limit value in the VSL control area;
4) Rounding down the calculated speed limit value to the integer multiple closest to A, wherein A is a given constant, and the value is 5km/h or 10km/h;
After the speed limit of the human-driven vehicle or the automatic-driven vehicle is calculated, calculating the time required for accelerating or decelerating the vehicle i to a given speed limit value according to the maximum comfortable acceleration, the minimum comfortable deceleration and the instantaneous speed of the vehicle i;
Calculating the next speed limit value updating time of the vehicle i according to the current time t and the time required by the vehicle i to accelerate or decelerate to a given speed limit value;
In order to avoid frequent acceleration and deceleration of the vehicle, a new speed limit value is recalculated for the vehicle only after the vehicle accelerates or decelerates to the speed limit value, i.e. the speed limit value updating time of each vehicle is independent.
5. The hybrid traffic flow optimization control method based on the combination of variable speed limit and lane change according to claim 4, wherein S4 comprises the steps of:
S41: calculating the road density of all lanes in the LC control area according to the collected vehicle position and lane information; calculating the average road density of the non-narrowed lanes according to the road density of each lane and the number of the non-narrowed lanes;
S42: calculating the expected lane change number of the non-narrowed lanes in the LC control area to make the density of the non-narrowed lanes equal to the average road density;
s43: according to the expected lane change number of each non-narrowed lane in the LC lane change control area, selecting a proper vehicle for lane change;
s44: for the vehicles on the narrowed lanes, after entering the lane change control area, the lane is changed to the non-narrowed lanes as far as possible on the premise of meeting lane change safety, so that lane change behaviors of the vehicles at bottleneck positions are reduced;
When the lane change vehicle is selected, an automatic driving vehicle is preferably selected; when the number of the automatic driving vehicles is smaller than the number of the expected lane change vehicles, the number of the driving vehicles needing lane change is calculated according to the difference between the compliance degree of the driving vehicles, the number of the expected lane change vehicles and the number of the automatic driving vehicles, and the driving vehicles meeting the number of the expected lane change vehicles are randomly selected from the driving vehicles to change lanes.
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| CN115440088B (en) * | 2022-07-25 | 2024-05-14 | 重庆大学 | Intelligent vehicle lane change decision method based on field |
| CN115331435B (en) * | 2022-08-04 | 2024-05-31 | 北京交通大学 | Intelligent networking vehicle speed control method based on local space-time traffic state |
| CN116052413B (en) * | 2022-11-28 | 2024-04-16 | 中国第一汽车股份有限公司 | V2X-based high-speed congestion-free recommendation method, system and vehicle |
| CN116246466B (en) * | 2023-03-13 | 2024-01-23 | 长安大学 | Hybrid traffic flow management method and system considering autopilot multimode characteristics |
| CN116486609B (en) * | 2023-03-24 | 2024-03-26 | 合肥工业大学 | Traffic flow control method considering road movement bottleneck in network environment |
| CN116432448B (en) * | 2023-04-06 | 2024-02-23 | 西南交通大学 | Variable speed limit optimization method based on intelligent network coupling and driver compliance |
| CN116884220A (en) * | 2023-08-01 | 2023-10-13 | 同济大学 | Global variable speed limit compliance prediction method based on track data |
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