CN114239272B - Hybrid bicycle flow microscopic modeling method and device based on retrograde behavior - Google Patents

Abstract

The invention discloses a hybrid bicycle flow microscopic modeling method and device based on retrograde motion, which comprises the following steps: acquiring the running speed of the hybrid bicycle; and establishing a cellular automaton model of the traffic flow of the hybrid bicycle based on the running rule and the lateral movement rule of the hybrid bicycle according to the running speed of the hybrid bicycle, and describing a lane changing process and a reverse behavior in the hybrid bicycle flow. By adopting the technical scheme of the invention, the problems that the personal safety of a driver is seriously threatened by the retrograde motion of the non-motor vehicle and the road passing efficiency is greatly influenced are solved.

Description

A mixed bicycle flow micro-modeling method and device based on retrograde behavior

Technical Field

The invention belongs to the technical field of traffic engineering, and in particular relates to a mixed bicycle flow micro-modeling method and device based on reverse behavior.

Background Art

With the promotion of electric bicycles and the rise of shared bicycles, bicycles have become an important tool for residents to travel and connect. The sharp increase in the number of non-motorized vehicles has put forward higher requirements on the conditions of non-motorized vehicle lanes. However, some existing non-motorized vehicle lanes lack reasonable planning and design, resulting in poor bicycle travel order, riding in the opposite direction, and running red lights. These phenomena not only reduce the traffic capacity of the road, but also have a serious negative impact on the travel safety of residents, which has attracted the attention of the transportation community to the study of bicycle traffic flow. Traffic flow simulation is a basic method to study the operation laws of traffic flow. Among them, due to the characteristics of simple rules and high operation efficiency of the Cellular Automaton (CA) model, domestic and foreign researchers have conducted extensive and in-depth research on non-motorized vehicle traffic flow based on the CA model.

Researchers have achieved rich results in the study of cellular automata in the characteristics of non-motorized vehicle traffic, but there are also some shortcomings: (1) Most researchers have conducted research on electric bicycles or traditional bicycles, and relatively few have studied the traffic characteristics of mixed bicycle flows composed of electric bicycles and traditional bicycles; (2) There are few studies on the impact of reverse behavior on mixed bicycle flows; (3) There is a lack of research on the design of traffic facilities that consider reverse bicycle behavior. Reverse riding can easily cause various conflicts and interferences, reduce travel efficiency, and easily lead to traffic accidents, seriously threatening the safety of drivers.

Summary of the invention

The technical problem to be solved by the present invention is to provide a mixed bicycle flow micro-modeling method and device based on retrograde behavior, and to solve the problem that the retrograde non-motor vehicle seriously threatens the personal safety of the driver and has a great impact on the road traffic efficiency by setting up a single-sided two-way non-motor vehicle lane.

To achieve the above object, the present invention adopts the following technical solution:

A mixed bicycle flow micro-modeling method based on retrograde behavior includes the following steps:

Step S1, obtaining the running speed of the hybrid bicycle;

Step S2: According to the running speed of the hybrid bicycles, a cellular automaton model of the hybrid bicycle traffic flow based on bicycle running rules and lateral movement rules is established to describe the lane changing process and reverse behavior in the hybrid bicycle flow.

Preferably, the lateral movement rule is: if the speed that the driver can achieve in the current lane is less than the speed after changing lanes, and the safety conditions for lane changing are met, then the driver will choose to change lanes to achieve a higher driving speed, otherwise he will continue to drive in the current lane; when there is a wrong-way behavior, the bicycle lane change is realized according to the driving direction of the front vehicle in the target lane. If the driving direction of the front vehicle in the target lane is the same as that of the current vehicle, the lane change can be realized by meeting the safety distance; if the driving direction of the front vehicle in the current lane is opposite to that of the current vehicle, the lane change must meet the safety distance and the distance between the two vehicles; when the distance between the two vehicles reaches greater than the first threshold, the vehicle will no longer enter the lane on its left; when the distance between the two vehicles is less than the second threshold, the vehicle changes lanes to the right lane. If the lane change cannot be completed, the movement stops and waits for the lane change.

As a preferred embodiment, the bicycle operation rule is: the bicycle will go through four steps of acceleration, deceleration, random slowing down, and position update to complete the update process.

Preferably, the bicycle acceleration operation rule is: during riding, the rider expects to travel at the maximum speed, that is, _vn (t+1)=min{ _vn (t)+a _n ,vn _max }, wherein _vn (t) is the speed of bicycle n at time t, _vn (t+1) is the speed of bicycle n at time t+1, a _n is the acceleration of bicycle n, and vn _max is the maximum speed of bicycle n.

Preferably, the bicycle deceleration operation rule is: firstly calculate the speed of the bicycle in the current lane and the lanes on its left and right sides in the next time step under the condition of meeting safety conditions, then compare the speeds of the lanes, and select the lane with the largest speed as the driving lane.

Preferably, the random slowing down operation rule is: the random slowing down probability of the bicycle is P, and when the random slowing down condition is met, the bicycle decelerates, that is, v _n (t+1)=max{v _n (t+1)-1,0}.

Preferably, the position update operation rule is: the bicycle moves forward at the updated speed, that is, _xn (t+1)= _xn (t)+ _vn (t+1), wherein _xn (t) is the position of bicycle n at time t, and _xn (t+1) is the position of bicycle n at time t+1.

The present invention also provides a hybrid bicycle flow microscopic modeling device based on retrograde behavior, comprising:

An acquisition module, used for acquiring the running speed of the hybrid bicycle;

The modeling module is used to establish a mixed bicycle traffic flow cellular automaton model based on bicycle operation rules and lateral movement rules according to the running speed of the mixed bicycles, and to describe the lane changing process and reverse behavior in the mixed bicycle flow.

Preferably, the lateral movement rule is: if the speed that the driver can achieve in the current lane is less than the speed after changing lanes, and the safety conditions for lane changing are met, then the driver will choose to change lanes to achieve a higher driving speed, otherwise he will continue to drive in the current lane; when there is a wrong-way behavior, the bicycle lane change is realized according to the driving direction of the front vehicle in the target lane. If the driving direction of the front vehicle in the target lane is the same as that of the current vehicle, the lane change can be realized by meeting the safety distance; if the driving direction of the front vehicle in the current lane is opposite to that of the current vehicle, the lane change must meet the safety distance and the distance between the two vehicles; when the distance between the two vehicles reaches greater than the first threshold, the vehicle will no longer enter the lane on its left; when the distance between the two vehicles is less than the second threshold, the vehicle changes lanes to the right lane. If the lane change cannot be completed, the movement stops and waits for the lane change.

As a preferred embodiment, the bicycle operation rule is: the bicycle will go through four steps of acceleration, deceleration, random slowing down, and position update to complete the update process.

The reverse movement of non-motor vehicles seriously threatens the personal safety of drivers and has a great impact on the road traffic efficiency. In order to solve the impact of reverse movement on the traffic characteristics of mixed bicycle flow, the present invention establishes a mixed bicycle flow micro-model that takes reverse movement into account, analyzes the impact of the proportion of electric bicycles and the proportion of reverse vehicles on the mixed bicycle flow, and the setting conditions of the single-sided two-way non-motor vehicle lane. The use of reverse movement will reduce the speed and flow of mixed bicycle flow; the speed and flow of mixed bicycle flow are nonlinearly related to the proportion of reverse vehicles; when the traffic density is relatively small, as the density increases, the average speed of the traffic with a low reverse ratio decreases faster than the average speed of the traffic with a high reverse ratio; the maximum flow when the reverse ratio is small is smaller than the maximum flow when the reverse ratio is large; the reasonable setting of single-sided two-way non-motor vehicle lanes can improve traffic efficiency.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG1 is a flow chart of a mixed bicycle flow micro-modeling method based on retrograde behavior;

Figure 2 is a schematic diagram of the direction of bicycle travel;

Fig. 3 Schematic diagram of the structure of the mixed bicycle flow micro-modeling device based on retrograde behavior.

DETAILED DESCRIPTION

In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Generally, the components of the embodiments of the present invention described and shown in the drawings here can be arranged and designed in various different configurations.

Embodiment 1:

The formula symbols involved in Example 1 are shown in Table 1:

Table 1:

As shown in FIG1 , the present invention provides a mixed bicycle flow micro-modeling method based on retrograde behavior, establishes a mixed bicycle traffic flow cellular automaton model considering retrograde behavior, obtains the changes of three parameters of mixed bicycle traffic flow under the influence of retrograde behavior, proposes a strategy for setting a unilateral bidirectional non-motorized vehicle lane considering retrograde behavior, and gives setting conditions. Specifically, the following steps are included:

Step S1, obtaining the running speed of the hybrid bicycle;

Step S2: According to the running speed of the hybrid bicycles, a cellular automaton model of the hybrid bicycle traffic flow based on bicycle running rules and lateral movement rules is established to describe the lane changing process and reverse behavior in the hybrid bicycle flow.

As an implementation method of an embodiment of the present invention, in step S2, in order to ensure that the vehicle travels at the maximum speed, a lateral movement rule is introduced. If the speed that the driver can reach in the current lane is less than the speed that he can travel after changing lanes, and the safety conditions for changing lanes can be met, then the driver will choose to change lanes to achieve a higher driving speed; otherwise, it will continue to drive in the current lane. When there is a reverse behavior, the lane change of the bicycle needs to consider the driving direction of the vehicle in front of the target lane. If the vehicle in front of the target lane is traveling in the same direction as the current vehicle, it is only necessary to meet the safety distance to achieve the lane change; if the vehicle in front of the current lane is traveling in the opposite direction to the current vehicle, it is necessary to meet the safety distance and the distance between the two vehicles to achieve the lane change; when the distance between the two vehicles reaches a value greater than the first threshold, the vehicle will no longer enter the lane on its left; when the distance between the two vehicles is less than the second threshold, the vehicle changes lanes to the right lane. If the lane change cannot be completed, the movement stops and waits for the lane change.

As shown in Figure 2, at time t→t+1, the bicycle will go through four steps of acceleration, deceleration, random slowing, and position update to complete the update process. The specific operation rules of the bicycle are as follows:

(1) Acceleration: During riding, the rider expects to travel at the maximum speed, that is:

v _n (t+1)＝min{v _n (t)+a _n ,v _{n max} } (1)

(2) Deceleration: First, calculate the speed of bicycle n in the current lane and the lanes on its left and right sides in the next time step while meeting safety conditions. Then compare the speeds of each lane and select the lane with the highest speed as the driving lane. Different traffic conditions correspond to different speed calculation rules, and the speed calculation rules need to be defined according to different traffic conditions.

When there is no retrograde behavior, the speed calculation formula of bicycle n in the current lane and the lanes on its left and right sides in the next time step is as follows:

当两车间距小于d₂时，为避免冲突发生，此时车辆需向右侧车道换道行驶，若换道无法完成，则停止运动等待换道，即：

When there is a reverse behavior, bicycle n may encounter vehicles traveling in the opposite direction during riding. The direction of the bicycle needs to be considered when calculating the speed of bicycle n in the current lane and the lanes on its left and right sides in the next time step. Two safety distance parameters d ₁ and d ₂ (d ₁ >d ₂ ) are defined in the model. When the distance between bicycle n and the bicycle n ^cf in front is less than d ₁ , in order to facilitate the passage of the oncoming vehicle, it is assumed that the vehicle will not enter its left lane again, that is:

When the distance between the two vehicles is less than d ₂ , in order to avoid conflict, the vehicle needs to change lanes to the right lane. If the lane change cannot be completed, the vehicle stops moving and waits for the lane change, that is:

The speed calculation formula of bicycle n in the current lane and the lanes on its left and right sides at the next time step is as follows:

表示t时刻自行车n与其左后方自行车n^lb行驶方向相同；

表示t时刻自行车n与其右后方自行车n^rb行驶方向相同；

表示t时刻自行车n与其前方自行车n^cf行驶方向相反。In formulas (6) and (7),

It means that at time t, bicycle n and bicycle n ^lb behind it on the left are traveling in the same direction;

It means that at time t, bicycle n and bicycle n ^rb behind it on the right are traveling in the same direction;

It means that at time t, bicycle n and bicycle n ^cf in front of it are traveling in opposite directions.

After determining the speed of the bicycle in the current lane and the lanes on the left and right sides, compare the maximum speeds that can be achieved in each lane to determine the driving lane for the next time step. The calculation rules are as follows:

if

So

if

So

if

So

(3) Random slowing down: The probability of random slowing down of a bicycle is P. When the random slowing down condition is met, the bicycle slows down, that is:

v _n (t+1)＝max{v _n (t+1)-1,0} (8)

(4) Position update: The bicycle moves forward at the updated speed, that is:

x _n (t+1)＝x _n (t)+v _n (t+1) (9)

Simulation experiment:

Visual Studio was used to simulate the mixed bicycle flow, and the simulation time was set to 8000 steps (i.e. 8000s). The simulation data of the last 2000 steps were selected for analysis. The simulation data in the present invention is the average value of 20 simulations to reduce the influence of randomness on the results. Other parameters in the model were set as: d ₁ =30, d ₂ =10, P=0.3, a _n =1.

To quantitatively analyze the influence of the proportion of electric bicycles and reverse behavior in mixed bicycle flow on the characteristics of bicycle traffic flow. Define the proportion of electric bicycles as α, the proportion of reverse vehicles in mixed bicycle flow as λ, the number of bicycles passing through a non-motorized lane section at time t as N(t), the total number of traditional bicycles in the non-motorized lane as R, the total number of electric bicycles as E, the speed of traditional bicycle i at time t as _vi (t), and the speed of electric bicycle j at time t as _vj (t). The calculation formulas for the average flow Q(bike/(s·m)), average density K(bike/ ^m2 ), average speed _Vr (m/s) of traditional bicycles, and average speed _Ve (m/s) of electric bicycles in non-motorized lanes are as follows:

Through simulation calculation, the relationship between the average speed and average density of bicycles under different reverse ratios when α＝0, α＝0.5, and α＝1 can be concluded as follows:

(1) When K≤0.1, when α＝0, the average speed of traditional bicycles remains unchanged as the average density increases; when α＝0.5 and 1, the average speeds of traditional bicycles and electric bicycles decrease as the average density increases. When 0.1＜K＜0.5, the average speed of bicycles decreases as the average density increases at different proportions of electric bicycles. This is because the expected speed of traditional bicycles is lower than that of electric bicycles. Under low density conditions, when there are no electric bicycles, the head spacing can ensure that the flow of traditional bicycles maintains a free flow state, and the average speed remains unchanged as the average density increases; when there are electric bicycles, the head spacing cannot ensure that the flow of bicycles maintains a free flow state, and the average speed decreases as the average density increases.

(2) When there is no wrong-way traffic, that is, when λ = 0, the average speed of bicycles is greater than that when there is wrong-way traffic. This is because the presence of wrong-way vehicles increases the conflict and interference of bicycle traffic flow. Conflicting vehicles need to slow down or even stop to avoid them, and the expected speed of wrong-way vehicles is lower than that of forward-way vehicles. Therefore, the average speed of bicycles when there is no wrong-way traffic is greater than that when there is wrong-way traffic.

(3) As the proportion of vehicles traveling against the flow increases, the relationship between the average speed of bicycles and the proportion of vehicles traveling against the flow becomes nonlinear. When K increases from 0.1 to 0.2, the average speeds of λ = 0.1 and 0.2 decrease faster than those of λ = 0.3, 0.4, and 0.5. This is because when the traffic density is not large and the number of bicycles traveling against the flow is small, in order to avoid the intermittent bicycles traveling against the flow, the bicycles that conflict with the flow will change lanes more frequently, causing a certain degree of disturbance to the overall traffic flow and reducing the average speed. When the traffic density is not large and the number of bicycles traveling against the flow is large, the probability of bicycles choosing to enter the left lane decreases. At this time, the two-way bicycle flow presents a state of following driving, and bicycles will not change lanes frequently, and conflict behavior is reduced. At this time, as the average density increases, the average speed decreases more slowly than when the proportion of vehicles traveling against the flow is small.

When λ＝0, 0.3, 0.4 and 0.5, the relationship curves between average flow and average density have similar changing trends. The average flow increases to a peak value first and then decreases with the increase of average density. When λ＝0.1 and 0.2, the relationship curves between average flow and average density have similar changing trends. The average flow increases to a peak value first and then maintains a flat peak with the increase of average density, and then decreases. The reason for the flat peak in the average flow is that when the traffic density is not large and the number of bicycles traveling against the flow is small (λ＝0.1 and 0.2), in order to avoid intermittent bicycles traveling against the flow, the bicycles that cause conflict will change lanes more frequently. When the number of bicycles traveling against the flow is large (λ＝0.3, 0.4 and 0.5), the two-way bicycle flow presents a state of following driving, and the conflict behavior is reduced. At this time, with the increase of average density, the average speed decreases faster when the proportion of vehicles traveling against the flow is small than when the proportion of vehicles traveling against the flow is large, resulting in a small change in the average flow and a flat peak state when the proportion of vehicles traveling against the flow is small.

When λ＝0.1 or 0.2, the maximum flow is smaller than when λ＝0.3, 0.4 or 0.5. From the previous analysis, it can be seen that when the number of bicycles traveling against the flow is small, there are more conflicts during the bicycle driving process, which reduces the efficiency of bicycle traffic; when the number of bicycles traveling against the flow is large, the two-way bicycle flow presents a following driving state, the conflict behavior is reduced, and the efficiency of bicycle traffic is improved. In addition, when λ＜0.5, the maximum flow of α＝1 is greater than the maximum flow of the other two cases. This is because electric bicycles have a higher driving speed. The larger the proportion of electric bicycles, the greater the maximum flow.

Embodiment 2:

As shown in FIG3 , the present invention further provides a hybrid bicycle flow microscopic modeling device based on retrograde behavior, comprising:

An acquisition module, used for acquiring the running speed of the hybrid bicycle;

The modeling module is used to establish a mixed bicycle traffic flow cellular automaton model based on bicycle operation rules and lateral movement rules according to the running speed of the mixed bicycles, and to describe the lane changing process and reverse behavior in the mixed bicycle flow.

Furthermore, the lateral movement rule is: if the speed that the driver can achieve in the current lane is less than the speed after changing lanes, and the safety conditions for lane changing are met, then the driver will choose to change lanes to achieve a higher driving speed, otherwise he will continue to drive in the current lane; when there is a reverse traffic behavior, the bicycle lane change is realized according to the driving direction of the front vehicle in the target lane. If the driving direction of the front vehicle in the target lane is the same as that of the current vehicle, the lane change can be realized by meeting the safety distance; if the driving direction of the front vehicle in the current lane is opposite to that of the current vehicle, the lane change must meet the safety distance and the distance between the two vehicles; when the distance between the two vehicles reaches greater than the first threshold, the vehicle will no longer enter the lane on its left; when the distance between the two vehicles is less than the second threshold, the vehicle changes lanes to the right lane. If the lane change cannot be completed, the movement stops and waits for the lane change.

Furthermore, the bicycle operation rules are as follows: the bicycle will go through four steps of acceleration, deceleration, random slowing down, and position update to complete the update process.

The present invention considers the lane-changing and reverse behavior characteristics of traditional bicycles and electric bicycles, and establishes a mixed bicycle flow micro-simulation model based on the NaSch model. The model is used to simulate and analyze the influence of the proportion of electric bicycles and the proportion of reverse vehicles on the traffic characteristics of mixed bicycle flow, and the setting conditions of the one-side two-way non-motorized vehicle lane are determined. The following conclusions are drawn:

(1) The average speed and average flow rate of mixed bicycle flow without counter-current behavior are greater than those with counter-current behavior.

(2) As the proportion of vehicles traveling against the flow increases, the relationship between the average speed, average flow rate and the proportion of vehicles traveling against the flow is nonlinear. When the traffic density is small, as the average density increases, the average speed decreases faster when there are fewer bicycles traveling against the flow than when there are more bicycles traveling against the flow. The maximum flow rate when the proportion of vehicles traveling against the flow is small (λ = 0.1 or 0.2) is smaller than the maximum flow rate when the proportion of vehicles traveling against the flow is large (λ = 0.3, 0.4 or 0.5).

(3) The conditions for setting up a one-sided two-way non-motorized vehicle lane in a four-lane non-motorized vehicle lane are as follows: when there are no vehicles going in the opposite direction, no opposite lane shall be set up; when the proportion of vehicles going in the opposite direction is small (0＜λ≤0.3), three forward lanes and one opposite lane may be set up; when the proportion of vehicles going in the opposite direction is large (λ≥0.3), two opposite lanes may be set up.

The reverse movement of non-motor vehicles seriously threatens the personal safety of drivers and has a great impact on the road traffic efficiency. In order to solve the impact of reverse movement on the traffic characteristics of mixed bicycle flow, the present invention establishes a mixed bicycle flow micro-model that takes reverse movement into account, analyzes the impact of the proportion of electric bicycles and the proportion of reverse vehicles on the mixed bicycle flow, and the setting conditions of the single-sided two-way non-motor vehicle lane. The use of reverse movement will reduce the speed and flow of mixed bicycle flow; the speed and flow of mixed bicycle flow are nonlinearly related to the proportion of reverse vehicles; when the traffic density is relatively small, as the density increases, the average speed of the traffic with a low reverse ratio decreases faster than the average speed of the traffic with a high reverse ratio; the maximum flow when the reverse ratio is small is smaller than the maximum flow when the reverse ratio is large; the reasonable setting of single-sided two-way non-motor vehicle lanes can improve traffic efficiency.

Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein by equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims (5)

1. A mixed bicycle flow micro-modeling method based on retrograde behavior, characterized by comprising the following steps: Step S1, obtaining the running speed of the hybrid bicycle; Step S2: establishing a cellular automaton model of mixed bicycle traffic flow based on bicycle running rules and lateral movement rules according to the running speed of the mixed bicycles, and describing the lane changing process and reverse behavior in the mixed bicycle flow; The lateral movement rule is as follows: if the speed that the driver can reach in the current lane is less than the speed after changing lanes, and the safety conditions for lane changing are met, then the driver will choose to change lanes to achieve a higher speed, otherwise he will continue to drive in the current lane; when there is a reverse driving behavior, the bicycle lane change is realized according to the driving direction of the front vehicle in the target lane. If the front vehicle in the target lane has the same driving direction as the current vehicle, the lane change can be realized by meeting the safety distance; if the front vehicle in the current lane is driving in the opposite direction to the current vehicle, the lane change must meet the safety distance and the distance between the two vehicles; when the distance between the two vehicles is less than the first threshold, the vehicle will no longer enter the lane on its left; when the distance between the two vehicles is less than the second threshold, the vehicle changes lanes to the right lane. If the lane change cannot be completed, the vehicle stops moving and waits for the lane change; The bicycle operation rules are as follows: the bicycle will go through four steps of acceleration, deceleration, random slowing, and position update to complete the update process; Deceleration: First, calculate the speed of bicycle n in the current lane and the lanes on its left and right sides in the next time step while meeting safety conditions. Then compare the speeds of each lane and select the lane with the highest speed as the driving lane. Different traffic conditions correspond to different speed calculation rules, and the speed calculation rules need to be defined according to different traffic conditions. When there is no retrograde behavior, the speed calculation formula of bicycle n in the current lane and the lanes on its left and right sides in the next time step is as follows:

Where v _n (t+1) is the speed of bicycle n at time t+1,

is the distance between bicycle n and the bicycle n ^cf in front at time t,

is the left lane for bicycle n at time t;

is the distance between bicycle n and the bicycle n ^lb behind it at time t,

The speed of bicycle n ^lb behind bicycle n at the moment,

is the distance between bicycle n and the bicycle n ^lf in front of it on the left at time t,

is the right lane for bicycle n at time t,

The distance between bicycle n and the bicycle n ^rb behind it at the moment,

is the speed of bicycle n ^rb behind bicycle n at time t+1,

is the distance between bicycle n and the bicycle n ^rf in front of it at time t; When there is a wrong-way behavior, bicycle n may encounter vehicles traveling in the opposite direction during riding. The direction of the bicycle needs to be considered when calculating the speed of bicycle n in the current lane and the lanes on its left and right sides at the next time step. Two safety distance parameters d ₁ and d ₂ are defined in the model, where d ₁ >d ₂ . When the distance between bicycle n and the bicycle n ^cf in front is less than d ₁ , in order to facilitate the passage of the oncoming vehicle, it is assumed that the vehicle will not enter its left lane again, that is:

When the distance between the two vehicles is less than d ₂ , in order to avoid conflict, the vehicle needs to change lanes to the right lane. If the lane change cannot be completed, the vehicle stops moving and waits for the lane change, that is:

The speed calculation formula of bicycle n in the current lane and the lanes on its left and right sides at the next time step is as follows:

In the formula,

It means that at time t, bicycle n and bicycle n ^1b behind it on the left are traveling in the same direction;

It means that at time t, bicycle n and bicycle n ^rb behind it on the right are traveling in the same direction;

It means that at time t, bicycle n and bicycle n ^cf in front of it are traveling in opposite directions; After determining the speed of the bicycle in the current lane and the lanes on the left and right sides, compare the maximum speeds that can be achieved in each lane to determine the driving lane _Ln (t+1) for the next time step. The calculation rules are as follows: if

So

if

So

if

So

2. The mixed bicycle flow microscopic modeling method based on retrograde behavior as claimed in claim 1 is characterized in that the bicycle acceleration operation rule is: during riding, the rider expects to travel at the maximum speed, that is, _vn (t+1)=min{ _vn (t)+a _n , _vnmax }, wherein _vn (t) is the speed of bicycle n at time t, _vn (t+1) is the speed of bicycle n at time t+1, a _n is the acceleration of bicycle n, and _vnmax is the maximum speed of bicycle n. 3. The mixed bicycle flow microscopic modeling method based on retrograde behavior as claimed in claim 2 is characterized in that the speed of the bicycle in the current lane and the lanes on its left and right sides in the next time step is calculated under the condition that the safety condition is met, and then the speeds of the lanes are compared, and the lane with the largest speed is selected as the driving lane. 4. The microscopic modeling method of mixed bicycle flow based on retrograde behavior as claimed in claim 3 is characterized in that the random slowing-down operation rule is: the random slowing-down probability of a bicycle is P, and when the random slowing-down condition is met, the bicycle slows down, that is, v _n (t+1)=max{v _n (t+1)-1,0}. 5. The mixed bicycle flow microscopic modeling method based on retrograde behavior as claimed in claim 4 is characterized in that the position update operation rule is: the bicycle moves forward at the updated speed, that is, _xn (t+1)= _xn (t)+ _vn (t+1), wherein _xn (t) is the position of bicycle n at time t, and _xn (t+1) is the position of bicycle n at time t+1.

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