CN117408086B - Mixed traffic flow simulation method based on driver response time - Google Patents
Mixed traffic flow simulation method based on driver response time Download PDFInfo
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- G08G1/00—Traffic control systems for road vehicles
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- G—PHYSICS
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- G08G1/00—Traffic control systems for road vehicles
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- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
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Abstract
The embodiment of the application discloses a hybrid traffic flow simulation method based on driver response time, which comprises the following steps: acquiring each vehicle type under a non-motor vehicle mixed running scene, wherein each vehicle type comprises: electric motorcycles, electric bicycles, and conventional bicycles; determining the traffic priority of each vehicle according to the response time of the driver; according to the traffic priority and the speed characteristics, a traffic flow cellular automaton model of the mixed traffic of the non-motor vehicles is established; and running the cellular automaton model to realize traffic flow simulation of the mixed running of the non-motor vehicles. The method and the device realize the accurate simulation of the mixed traffic flow of the non-motor vehicle.
Description
Technical Field
The embodiment of the application relates to the technical field of traffic flow microscopic simulation, in particular to a hybrid traffic flow simulation method based on driver response time.
Background
Based on various simulation models and traffic flow simulation of traffic data, traffic evolution within a period of time can be realized based on certain boundary conditions, and the method plays an important role in road planning, automatic driving, safety control and the like.
In the prior art, traffic flow simulation for motor vehicles is very common. However, for the driving scene of the non-motor vehicle, the traffic flow simulation is very rare, and the development of technologies such as road planning, intelligent traffic and the like is limited.
Disclosure of Invention
The embodiment of the application provides a hybrid traffic flow simulation method based on driver response time, which realizes the accurate simulation of the hybrid traffic flow of a non-motor vehicle.
In a first aspect, an embodiment of the present application provides a hybrid traffic flow simulation method based on a driver response time, including:
acquiring each vehicle type under a non-motor vehicle mixed running scene, wherein each vehicle type comprises: electric motorcycles, electric bicycles, and conventional bicycles;
determining the traffic priority of each vehicle according to the response time of the driver;
according to the traffic priority and the speed characteristics, a traffic flow cellular automaton model of the mixed traffic of the non-motor vehicles is established;
and running the cellular automaton model to realize traffic flow simulation of the mixed running of the non-motor vehicles.
In a second aspect, embodiments of the present application further provide an electronic device, including:
one or more processors;
a memory for storing one or more programs,
the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the driver response time based hybrid traffic flow simulation method of any of the embodiments.
In a third aspect, embodiments of the present application further provide a computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements the hybrid traffic flow simulation method according to any of the embodiments.
According to the method and the device for simulating the traffic flow of the hybrid driving scene of the non-motor vehicle, according to the response time of the driver, the influence rule of the response time on the traffic priority under different vehicle types is analyzed, and the matched traffic rule and deduction control equation are constructed, so that the non-motor vehicle hybrid driving cellular machine model is more in line with the actual driving rule, the traffic flow change under the hybrid driving scene of various vehicle types can be simulated more accurately, and the accuracy of simulation evolution is improved.
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In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings that are needed in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present application, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a flowchart of a hybrid traffic flow simulation method based on driver response time provided in an embodiment of the present application.
Fig. 2 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the present application more clear, the technical solutions of the present application will be clearly and completely described below. It will be apparent that the described embodiments are only some, but not all, of the embodiments of the present application. All other embodiments, which can be made by one of ordinary skill in the art without undue burden from the present disclosure, are intended to be within the scope of the present disclosure.
In the description of the present application, it should be noted that the directions or positional relationships indicated by the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc. are based on the directions or positional relationships shown in the drawings, are merely for convenience of description of the present application and to simplify the description, and do not indicate or imply that the devices or elements referred to must have a specific orientation, be configured and operated in a specific orientation, and thus should not be construed as limiting the present application. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.
In the description of the present application, it should also be noted that, unless explicitly specified and limited otherwise, the terms "mounted," "connected," and "connected" are to be construed broadly, and may be either fixedly connected, detachably connected, or integrally connected, for example; can be mechanically or electrically connected; can be directly connected or indirectly connected through an intermediate medium, and can be communication between two elements. The specific meaning of the terms in this application will be understood by those of ordinary skill in the art in a specific context.
Fig. 1 is a flowchart of a hybrid traffic flow simulation method based on driver response time provided in an embodiment of the present application. The method is suitable for traffic flow simulation under a non-motor vehicle mixed running scene, and is executed by electronic equipment. As shown in fig. 1, the method specifically includes:
s110, acquiring each vehicle type under a non-motor vehicle mixed running scene, wherein each vehicle type comprises: electric motorcycles, electric bicycles, and conventional bicycles.
Here, the scene of the non-motor vehicle mixed running refers to a running scene in which the non-motor vehicle exists, for example, a right side of a motor vehicle lane or a non-motor vehicle lane. Under these scenes, three types of typical vehicle types are selected in the embodiment, and the three types of typical vehicle types respectively correspond to different speed characteristics, wherein the speed of the electric motor car is the fastest, the speed of the electric bicycle is the next lowest, and the speed of the traditional bicycle is the slowest. Other vehicle types in the driving scene in actual traffic can be classified into the three typical representatives according to the speed characteristics, and the simulation method for various vehicle types in the subsequent steps is also suitable for other vehicle types of the same type. It should be noted that, although the electric motorcycle belongs to a motor vehicle, the electric motorcycle is similar to an electric bicycle or a conventional bicycle in size, and generally runs on the right side of a motor vehicle lane or a non-motor vehicle lane, and the electric bicycle or the conventional bicycle is mixed, so the three mixed running of the electric motorcycle and the conventional bicycle is studied in the embodiment.
S120, determining the traffic priority of each vehicle according to the response time of the driver.
The above-mentioned various types of vehicles are slower than such vehicles, and the complex conditions in the running of the vehicle are mostly due to the driver response time. The present embodiment therefore introduces driver response time into the traffic flow simulation of the driving scenario. The response time in the application is obtained through a dynamic time warping algorithm in the actual road test process:
assuming that the vehicle follows the driving scene of the front vehicle, if the response time of the driver of the vehicle is short, the driving data of the vehicle should be highly similar to the driving data of the front vehicle; if the driver response time of the host vehicle is long, the host vehicle driving data should slightly lag the front vehicle driving data, and therefore, the distance between the host vehicle driving data and the front vehicle driving data can represent the driver response time. Wherein the driving data comprises information such as position, time and speed. The running data of the vehicle and the front vehicle form two matrixes X and Y, and the accumulated cost paths of X and Y are calculated and the shortest path is found. And after the shortest path is calculated, calculating response time w according to the matching coordinates of each time step in the path.
w=t i -t j
Wherein t is i And t j Is the time difference of 2 matching coordinates for one time step.
The response time of each time step is calculated over a period of time and averaged to obtain the response time of the driver.
The driving data are actual road test data, so that response time of different drivers of different vehicle types can be obtained. And determining the response time of each driver in the simulation scene according to the response time distribution of the drivers in the actual road test, namely giving response time to each driver in the simulation scene so as to keep consistency with the actual road test.
The average response time for each model is then calculated. Table 1 shows that there is a large difference in average response time between different vehicle types, electric motorcycle response time < electric bicycle response time < bicycle response time. Strictly speaking, the response time of each driver is different, but the small error of the response time does not cause a large travel distance because of the slower speed of the non-motor vehicle, and in order to simplify the calculation, each vehicle model is divided into a first vehicle and a second vehicle according to the magnitude relation of the driver response time of each vehicle model and the threshold value. In the application, the average response time of each vehicle model is taken as a threshold value (the threshold value of each vehicle model is different), and the threshold value is calculated according to a dynamic time warping algorithm aiming at actual road test data. The driver-driven vehicle having a response time less than the threshold value may be referred to as a first vehicle including a first electric motorcycle, a first electric bicycle, and a first conventional bicycle, and the driver-driven vehicle having a response time greater than or equal to the threshold value may be referred to as a second vehicle including a second electric motorcycle, a second electric bicycle, and a second conventional bicycle.
TABLE 1 response time threshold for each vehicle
Then, calculating the average response time of the first vehicle and the average response time of the second vehicle of each vehicle type; and determining the traffic priorities of the first vehicle and the second vehicle in all vehicle types according to the order of the average response time from small to large. Table 2 shows the average response times of the first vehicle and the second vehicle for each vehicle type. The smaller the average response time, the higher the traffic priority.
TABLE 2 average response time of first and second vehicles for each model
As can be seen from table 2, the final prioritization is: first electric motorcycle > first electric bicycle > second electric motorcycle > second electric bicycle > first traditional bicycle > second traditional bicycle.
The correctness of the above-mentioned prioritization is demonstrated from an reasoning point of view as follows:
the traffic priority refers to the advance of each driver preempting the space ahead when there is a free space ahead of the road. Traffic priority is affected by factors such as vehicle speed and driver response time. In terms of vehicle speed, a vehicle model with high vehicle speed has high advance; the vehicle type with slow vehicle speed has lower precedent. In terms of driver response time, the second vehicle driver does not preempt the forward space with others, and therefore has less look ahead. The first vehicle driver pursues a higher speed as much as possible at each moment, and tries to preempt each space for forward movement, so that the first vehicle driver has a higher preemption.
In order to improve the accuracy of traffic simulation, the embodiment further analyzes the joint influence of the vehicle speed and the response time on the traffic priority.
Optionally, according to the high-speed characteristics of the electric motorcycle and the electric bicycle, determining that the influence of the response time of the driver on the priorities of the electric motorcycle and the electric bicycle is greater than the influence of the vehicle type on the priorities; according to the low-speed characteristics of the traditional bicycle, the influence of the vehicle type on the priority of the traditional bicycle is determined to be larger than the influence of the response time of the driver on the priority. That is, the speed and acceleration of the electric bicycle and the electric motorcycle are both fast, and the priority is easily affected by the response time of the driver, so that the priority is judged by the two to take the response time as a first factor and the vehicle speed characteristic as a second factor. While conventional bicycles are limited by the lowest speed and acceleration, the priority of conventional bicycles is lower than other models regardless of response time.
According to the influence law, the final traffic priority ranking can be determined. Optionally, each vehicle type is firstly ordered according to a speed rule, namely, electric motor car > electric bicycle > traditional bicycle.
Then, the ordered vehicle models are divided into a first vehicle and a second vehicle, respectively, that is, (first electric motorcycle, second electric motorcycle) > (first electric bicycle, second electric bicycle) > (first conventional bicycle, second conventional bicycle).
Finally, in combination with the effect of response time, the final prioritization is: first electric motorcycle > first electric bicycle > second electric motorcycle > second electric bicycle > first traditional bicycle > second traditional bicycle.
And S130, building a traffic flow cellular automaton model of the mixed traffic of the non-motor vehicles according to the traffic priority and the speed characteristics.
In the embodiment, a cellular automaton model is adopted to execute the traffic flow simulation, and the influence of factors such as traffic priority, speed characteristics, driver response time and the like on the traffic flow is emphasized in the model construction. The specific construction process comprises the following steps:
step one, according to the speed characteristics of each vehicle type, determining the moving speeds of an electric motorcycle, an electric bicycle and a traditional bicycle in a cellular automaton model to be respectively: the unit time moves forward by 3 cells, 2 cells and 1 cell. Specifically, a cell is understood to be a rectangular space of length 1 unit space (about 2 meters) and width M, where M is understood to be the width of a road that a non-motor vehicle can travel, and each cell can accommodate up to M unit spaces. The occupied areas of electric bicycles, electric motorcycles and traditional bicycles are similar, and each occupies 1 unit space. In combination with the actual speed, the running speed of the electric motorcycle is fastest, and the speed of the electric bicycle is faster than that of a traditional bicycle, so that the electric motorcycle is arranged in the model to move forward at most 3 cells in one time step, the electric bicycle moves forward at most 2 cells in one time step, and the traditional bicycle moves forward at most 1 cell in one time step.
Step two, dividing the movement of the vehicle in the unit time of the cellular automaton model into three stages according to the movement speed of each vehicle type, and the step two is thatiStages are used to calculate forward movementiThe number of vehicles per cell, wherein,i=1, 2,3. Specifically, the space boundary condition selected by the model is a periodic boundary, the roads formed by the cells are connected end to end in the evolution process, and the number of vehicles of each cell in the next time step is evolved according to the vehicle movement condition of each cell in the previous time step. In consideration of the moving speeds of different vehicle types, in the model evolution rule of the embodiment, the vehicle movement in unit time is divided into the three phases.
And thirdly, respectively constructing control equations of all stages according to the traffic priority.
Within each time step, the firstiThe overall architecture of the control equation for each stage is:
the number of vehicles moving forward by 1 cell in a certain type = total space limit of front cells-space currently occupied by front cells, number of vehicles of other vehicle types with higher traffic priority and current cell having forward moving capability + newly increased space of front cells in next time step.
Based on the above overall architecture, the present embodiment considers the impact of driver response time in two aspects:
in a first aspect, the fast-driving tendency of the driver of the first vehicle affects the remaining space of the cells. When the cell space in front is insufficient, the first vehicle driver has a certain probability rho to change the lane to the adjacent lane to seek the space for continuing to advance. The number of vehicles after lane change is not counted in the statistical range of the occupied space of the current cell. The lane change probability is set because lane change requirements, such as, for example, whether there is space on the left road, whether the first vehicle driver is located at a position where lane change is convenient, etc., are not 100% lane change possible.
Illustratively, when constructing the control equation, setting a lane replacement probability for the first vehicle according to the speed characteristics of each vehicle type; and calculating the residual space change caused by the lane change of the vehicle to the left motor vehicle lane in each cell according to the lane change probability, and introducing a control equation. Specifically, the speeds of the first electric motorcycle and the first electric bicycle generate lane changing behaviors, and lane changing probabilities are set for the two types of vehicles; the conventional bicycle usually does not generate lane change behavior due to the speed limitation, so that the lane change probability of the first conventional bicycle is avoided.
In a second aspect, the tendency of the second vehicle driver to retract affects the overall space constraints of the front cells. For the first vehicle, the maximum fast forward is pursued, and the total space limit of the front cell may be set to the maximum number M of vehicles accommodated per unit cell. For the second vehicle, the driver has strong self-protection consciousness, and can avoid possible saturation of the front space, the total space limit of the front cells can be set to be the maximum number of the accommodated vehicles of the unit cells-1, namely, the front cells can wait and do not run forward when the space occupation quantity of the front cells reaches M after running.
Based on the influences of the two aspects, a corresponding control equation can be constructed according to the operation characteristics of each stage and each type of vehicle in unit time and is used as the basis of traffic flow simulation deduction. The specific equation structure will be described in detail in connection with the process of simulation operations in the following embodiments.
And S140, running the cellular automaton model to realize traffic flow simulation of the mixed traffic of the non-motor vehicles.
After the control equation is built, the cellular automaton model has the simulation operation function. And running the model to realize a traffic flow model of the mixed running of the non-motor vehicles.
In one embodiment, first, model initialization is performed. The road length of the model is set as in this embodimentL(there is in the roadLIndividual cells), the proportion of the electric motor car to the whole vehicle isR sb The proportion of the electric bicycle isR fb The proportion of the traditional bicycle isR bc The total number of vehicles isN。N sb For the number of electric motorcycles,N fb for the number of electric bicycles,N bc for the number of bicycles. According to the response time distribution of drivers on the actual road, distributing response time for each driver in the simulation environment, wherein the proportion of drivers with response time larger than a threshold value is as followsR(agg) Driver ratio with response time less than thresholdR(con). The initial conditions of the model are:
then, model evolution is performed according to the control equation. In unit time (fromtFrom moment to momentt+Time 1), the following operations are performed respectively:
step one, according to the control equation of the 1 st stage, calculating a first vehicle number moving forward by 1 cell, namely, calculating the vehicle number moving forward by 1 cell from the time t to the time t+1/3. Optionally, for all types of vehicles, judging whether the cells in the front are provided with accommodating spaces or not; if yes, judging the priority condition according to the response time of the driver and the vehicle type; if the movement condition is still met after priority is considered, the movement will be to the front cell.
Specifically, the traffic priority at this stage is: first electric motorcycle > first electric bicycle > second electric motorcycle > second electric bicycle > first conventional bicycle. And according to the traffic priority ranking, calculating the number of forward moving 1 cell of each type of vehicle. Illustratively, the present embodiment uses cell j as the current cell and cell j+1 as the preceding cell, and the vehicle in cell j will drive into cell j+1 at the next time.
For a first electric motorcycle with a first traffic priority, adoptingRepresenting the total number of vehicles in the cell j+1 at time t, the remaining space of the front cell is +.>The simulation calculation process includes two cases:
first electric motorcycle quantity of current cellLess than the remaining space of the preceding cell, i.e. +.>. At this time, the front space is sufficient, the vehicle does not change lane, and the number of first electric motorcycles advancing by 1 cell is calculated according to the control equation (5)>：
In the second case, the number of the first electric motorcycles of the current cell is larger than or equal to the remaining space of the front cell, namely. At this time, the vehicles which can be accommodated in the remaining space travel forward, the vehicles which exceed the remaining space change lane to the adjacent lane with the probability ρ, and the first electric motorcycle number +_1 cell forward can be calculated according to the control equation (6)>Calculating the number of the first electric motor cars changing lanes at the stage according to a control equation (7)：
Wherein,representing the current celljThe number of the first electric motor cars exceeding the remaining space of the front cell.
For the first electric bicycle with the second passing priority, the residual space of the front cell isI.e. after the first electric motorcycle with higher priority enters the front cell, the remaining space of the front cell, the simulation calculation process includes two cases:
first electric bicycle quantity of current cellLess than the remaining space of the preceding cell, i.e. +.>. At this time, the front space is sufficient, the vehicle does not change lane, and the first electric bicycle number of advancing 1 cell is calculated according to the control equation (8)>：
In case two, the number of the first electric bicycles of the current cell is larger than the remaining space of the front cell, namely. At this time, the vehicle in the remaining space is driven forward beyond the remaining spaceThe vehicles in the room change lanes to adjacent lanes with probability rho, and the first electric bicycle quantity which advances by 1 cell can be calculated according to a control equation (9)>Calculating the first electric bicycle number of lane change at this stage according to the control equation (10)>：
Wherein,representing the current celljThe number of the first electric bicycles exceeding the residual space of the front cell.
Similarly, for the second electric motorcycle with the third passing priority, the remaining space of the front cell isI.e. the maximum spatial limit M-1 of the preceding cell minus the number of vehicles already in the preceding cell +.>The space left after the number of the first electric motor cars and the first electric bicycles which are to be driven into the front cell and have higher passing priority is subtracted. At this time, the number of second electric motorcycles advancing by 1 cell can be calculated according to the control equation (11)>：
Wherein,representation oftAnd the number of the second electric motor cars in the current cell j at the moment.
Similarly, for the second electric bicycle with the fourth passing priority, the residual space of the front cell isI.e. the maximum spatial limit M-1 of the preceding cell minus the total number of vehicles already present in the preceding cell +.>And subtracting the remaining space after the number of other vehicle types with higher traffic priority to be driven into the front cell. At this time, the second electric bicycle number advancing by 1 cell can be calculated according to the control equation (12)>：
Wherein,representation oftThe number of second electric bicycles in the current cell j at the moment.
For the first traditional bicycle with the fifth passing priority, the residual space of the front cell isThe first bicycle number advancing by 1 cell can be calculated according to control equation (13)>：
Wherein,representation oftMoment whenThe first number of conventional bicycles in the front cell j.
For the second conventional bicycle with the sixth pass priority, the remaining space of the front cell is The second conventional bicycle number advanced by 1 cell can be calculated according to the control equation (14)>：
After the six types of vehicles are calculated, adding and solving the first vehicle number of 1 cell forward moving in the current cell j at the moment t：
Wherein,the number of electric motorcycles which move forward by 1 cell in the current cell j at the time t is represented,representing the number of electric bicycles moving forward by 1 cell in the current cell j at time t,/>Representing the number of conventional bicycles moving forward by 1 cell within the current cell j at time t.
And step two, according to the control equation in the 2 nd stage, calculating a second vehicle number which continuously moves forward by 1 cell based on the first vehicle number, namely calculating the vehicle number which continuously moves forward by 1 cell (total 2 cells forward) from the time t to the time t+1/3 in the vehicles which move forward by 1 cell from the time t+1/3 to the time t+2/3. Specifically, the electric motorcycle and the electric bicycle can advance 2 cells at one moment, so that whether an accommodating space exists in the immediate vicinity of the cell in front is judged for the electric motorcycle and the electric bicycle which advance 1 cell in the first step; if yes, judging the traffic priority condition according to the response time of the driver and the vehicle type; if the movement condition is still satisfied after the traffic priority is considered, the movement is to be made to the front cell.
Specifically, the traffic priority at this stage is: the first electric motorcycle > the first electric bicycle > the second electric motorcycle > the second electric bicycle. The total number of forward movement 2 cells per class of vehicle is calculated per class according to the traffic priority. Illustratively, cell j+2 is the leading cell of cell j+1, and this stage takes cell j+1 as the current cell and cell j+2 as the leading cell, and the vehicle in cell j+1 will drive into cell j+2 at the next time.
For the first electric motorcycle with the first passing priority, the residual space of the front cell j+2 isWherein->Representing the total number of vehicles in the cell j+2 at the time t;the number of vehicles moving forwards by 1 cell in the cell j+1 at the moment t represents the space occupied by the vehicles driving into the cell j+2 in the cell j+1 at the moment t; />The number of vehicles moving forward by 1 cell in the cell j+2 at the time t is represented, and the newly added space of the cell j+2 at the time t is represented. At this time, the simulation calculation process includes two cases:
in the first case, the number of the first electric motor cars of the current cell is smaller than the remaining space of the front cell,i.e.. At this time, the front space is sufficient, the vehicles can not change lanes, and the number of first electric motorcycles advancing by 2 cells can be calculated according to the control equation (19)>：
In the second case, the number of the first electric motorcycles in the current cell is larger than or equal to the front residual space, namely. At this time, the vehicles which can be accommodated in the remaining space travel forward, the vehicles which exceed the remaining space change lane to the adjacent lane with the probability ρ, and the number of first electric motorcycles which advance by 2 cells can be calculated according to the control equation (20)/(A)>Calculating the number of first electric motorcycles +.A first electric motorcycle is changed at the stage according to the control equation (21)>：
Wherein,representing the number of first electric motorcycles that are currently in the cell beyond the remaining space of the front cell.
For the first electric bicycle with the second passing priority, the residual space of the front cell j+2 isI.e. first electric motor with higher traffic priorityVehicle->After entering the front cell, the remaining space of the front cell. At this time, the simulation calculation process includes two cases:
in case one, the number of the first electric bicycles of the current cell is smaller than the remaining space of the front cell, namely. At this time, the front space is sufficient, the vehicle does not change lanes, and the number of first electric bicycles advancing for 2 cells can be calculated according to the control equation (22)：
In case two, the number of the first electric bicycles of the current cell is larger than the remaining space of the front cell, namely. At this time, the vehicles that can be accommodated in the remaining space travel forward, the vehicles that exceed the remaining space lane change to the adjacent lane with the probability ρ, and the first electric bicycle number +_2 cells forward can be calculated according to the control equation (23)>Calculating the first electric bicycle number of lane change at this stage according to the control equation (24)>：
Wherein,represents the current intracellular supercellThe number of first electric bicycles leaving the remaining space of the front cell.
Similarly, for the second electric motorcycle with the third passing priority, the remaining space of the front cell isThe number of second electric motorcycles advancing by 2 cells can be calculated according to the control equation (25)>：
Wherein,representstAnd the number of second electric motorcycles in the current cell at the moment.
Similarly, for the second electric bicycle with the fourth passing priority, the residual space of the front cell isThe number of second electric bicycles advancing by 2 cells can be calculated according to the control equation (26)>：
Wherein,representstThe number of second electric bicycles in the current cell at the moment.
After the four types of vehicles are calculated, adding and solving the second vehicle number of 2 forward cells in the cell j at the moment t：/>
Wherein,representing the number of electric motorcycles moving forward 2 cells in cell j at time t,/>The number of electric bicycles moving forward by 2 cells in the cell j at the time t is shown.
And thirdly, calculating a third vehicle number which continuously moves forward by 1 cell based on the second vehicle number according to the control equation of the 3 rd stage, namely calculating the vehicle number which continuously moves forward by 1 cell (total 3 cells forward) from the time t to the time t+2/3 in the vehicles which move forward by 2 cells from the time t+2/3 to the time t+1. Specifically, the electric motorcycle is fast and can advance 3 cells in one time step, so that whether the accommodating space exists in the front adjacent cells is judged according to the electric motorcycle advancing 2 cells in the second step; if so, the driver response time is used to judge the advance condition and move forward.
Specifically, the traffic priority of this stage is ordered as: the first electric motorcycle is the second electric motorcycle. The total number of forward moving 3 cells per class of vehicle is calculated class by class according to the traffic priority ranking. Illustratively, cell j+3 is the leading cell of cell j+2, and this stage takes cell j+2 as the current cell and cell j+3 as the leading cell, and the vehicle in cell j+2 will drive into cell j+3 at the next time.
For the first electric motorcycle with the first traffic priority, the residual space of the front cell isWherein->Representing the total number of vehicles in cell j+3 at time t；/>Represents the number of vehicles moving forward 2 cells within cell j+1 at time t,/>Representing time t cell->Number of vehicles moving 1 cell forward inside,/-for example>And->The space occupied by the cell vehicles driving into the cell j+3 after the moment t is represented together; />Represents the number of vehicles moving forward 1 cell in cell j+3 at time t,/cell>Represents the number of vehicles moving forward 2 cells within cell j+3 at time t,/for>And->Together representing the newly increased space of the cell j+3 at the moment t due to the fact that the vehicle exits. At this time, the simulation calculation process includes two cases:
in case one, the number of the first electric motorcycles of the current cell is smaller than the remaining space of the front cell, namely. At the moment, the front space is sufficient, the vehicles can not change lanes, and the number of first electric motorcycles advancing for 3 cells can be calculated according to the control equation (30)：
In the second case, the number of the first electric motorcycles of the current cell is larger than or equal to the front residual space, namely. At this time, the vehicles which can be accommodated in the remaining space travel forward, the vehicles which exceed the remaining space change lane to the adjacent lane with the probability ρ, and the number of first electric motorcycles which advance by 3 cells can be calculated according to the control equation (31)/(A)>Calculating the number of first electric motorcycles +.A first electric motorcycle is changed at the stage according to the control equation (32)>：
Wherein,representing the number of first electric motorcycles that are currently in the cell beyond the remaining space of the front cell.
For a second electric motorcycle with a second traffic priority, the remaining space of the front cell isI.e. first electric motorcycle with higher traffic priority +.>After entering the front cell, the remaining space of the front cell. At this time, the number of second electric motorcycles advancing by 3 cells can be calculated according to the control equation (33)>：
Wherein,representstAnd the number of second electric motorcycles in the current cell at the moment.
After the two types of vehicles are calculated, adding and solving the third vehicle number of 3 forward cells in the cell j at the moment t：
Wherein,the number of electric motorcycles moving forward 3 cells in cell j at time t is shown.
And step four, updating the number of vehicles in the cell according to the first number of vehicles, the second number of vehicles, the third number of vehicles and the number of lane change vehicles in each stage. That is, as time steps are updated, the types of vehicles are updated according to the respective movement rules, and the number of vehicles on each cell is also updated according to the rules.
Specifically, the number of electric motor vehicles in the cell j at the time t+1 is calculated according to the control equation (36)：
Wherein, the number of the first electric motorcycles of the lane change in three stages、/>Andby influencing the number of vehicles in the cells, a change in the remaining space of the cells is brought about. />
Calculating the number of electric bicycles in the cell j at the time t+1 according to a control equation (37):
wherein, the number of the first electric bicycles with two-stage lane changing is the same as that of the second electric bicyclesAnd->By influencing the number of vehicles in the cells, a change in the remaining space of the cells is brought about.
Calculating the number of conventional bicycles in the cell j at the time t+1 according to the control equation (38)：
Calculating the number of vehicles in the cell j at the time t+1 according to the control equation (39)：
According to the embodiment, each vehicle type is further divided into a first vehicle and a second vehicle according to the response time of a driver, the response time is combined with the vehicle speed characteristics, the influence rule of the response time on the traffic priority under different vehicle types is analyzed, and a more accurate look-ahead rule and deduction control equation is constructed. On the one hand, lane change probability is set for the first driver (i.e. the driver driving the first vehicle), and lane change behavior of the first driver under the condition of front saturation is considered, but the lane change probability is not set for the speed limitation of the traditional bicycle; the lane change vehicle will exit the statistical range of the number of vehicles in the lane, thereby providing more residual space for the cells of the lane. On the other hand, the maximum space limitation of the front cell (smaller than M) is lowered for the second vehicle, and the characteristic that the second driver (i.e. the driver driving the second vehicle) can avoid space saturation and carefully drive is more accurately embodied. Through the measures, the constructed non-motor vehicle mixed running cellular machine model is more in line with the actual running rule, the traffic flow change under various vehicle type mixed running scenes can be simulated more accurately, and the accuracy of simulation evolution is improved.
Fig. 2 is a schematic structural diagram of an electronic device according to an embodiment of the present application, and as shown in fig. 2, the device includes a processor 60, a memory 61, an input device 62 and an output device 63; the number of processors 60 in the device may be one or more, one processor 60 being taken as an example in fig. 2; the processor 60, the memory 61, the input means 62 and the output means 63 in the device may be connected by a bus or other means, in fig. 2 by way of example.
The memory 61 is used as a computer readable storage medium for storing software programs, computer executable programs and modules, such as program instructions/modules corresponding to the hybrid traffic flow simulation method based on driver response time in the embodiments of the present application. The processor 60 performs various functional applications of the device and data processing by running software programs, instructions and modules stored in the memory 61, i.e., implements the above-described hybrid traffic flow simulation method based on driver response time.
The memory 61 may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, at least one application program required for functions; the storage data area may store data created according to the use of the terminal, etc. In addition, the memory 61 may include high-speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other non-volatile solid-state storage device. In some examples, memory 61 may further comprise memory remotely located relative to processor 60, which may be connected to the device via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The input means 62 may be used to receive entered numeric or character information and to generate key signal inputs related to user settings and function control of the device. The output 63 may comprise a display device such as a display screen.
The present embodiments also provide a computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements the hybrid traffic flow simulation method of any of the embodiments based on driver response time.
Any combination of one or more computer readable media may be employed as the computer storage media of the embodiments herein. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. The computer readable storage medium can be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples (a non-exhaustive list) of the computer-readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
The computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, either in baseband or as part of a carrier wave. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination of the foregoing. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Computer program code for carrying out operations of the present application may be written in one or more programming languages, including an object oriented programming language such as Java, smalltalk, C ++ and conventional procedural programming languages, such as the C-programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computer (for example, through the Internet using an Internet service provider).
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present application, and not for limiting the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some or all of the technical features thereof can be replaced by equivalents; these modifications or substitutions do not depart from the essence of the corresponding technical solutions from the technical solutions of the embodiments of the present application.
Claims (6)
1. A method of simulating a hybrid traffic flow based on driver response time, comprising:
acquiring each vehicle type under a non-motor vehicle mixed running scene, wherein each vehicle type comprises: electric motorcycles, electric bicycles, and conventional bicycles;
according to the response time distribution of drivers in the actual road test, determining the response time of each driver in the simulation scene;
dividing each vehicle type into a first vehicle and a second vehicle according to the magnitude relation between the response time of the driver of each vehicle type and the threshold value; the response time of the first vehicle driver is less than the response time of the second vehicle driver;
calculating the average response time of the first vehicle and the average response time of the second vehicle of each vehicle type;
determining the traffic priorities of the first vehicle and the second vehicle in all vehicle types according to the sequence of the average response time from small to large;
the threshold is calculated according to a dynamic time warping algorithm aiming at actual road test data;
according to the speed characteristics of each vehicle type, the moving speeds of the electric motor car, the electric bicycle and the traditional bicycle in the cellular automaton model are respectively determined as follows: moving 3 cells, 2 cells and 1 cell forward in unit time;
dividing the movement of the vehicle in unit time of the cellular automaton model into three stages according to the movement speed of each vehicle type, wherein the ith stage is used for calculating the number of vehicles moving forwards by i cells, wherein i=1, 2 and 3;
respectively constructing control equations of all stages according to the traffic priority;
in the analog computation per unit time, the following operations are performed:
according to the control equation of the 1 st stage, calculating the first vehicle number moving forward by 1 cell and the lane-changing vehicle number of the 1 st stage;
calculating a second vehicle number which continues to move forward by 1 cell and a lane-changing vehicle number of the 2 nd stage based on the first vehicle number according to a control equation of the 2 nd stage;
calculating a third vehicle number which continues to move forward by 1 cell and a lane-changing vehicle number in the 3 rd stage based on the second vehicle number according to a control equation in the 3 rd stage;
and updating the number of vehicles in the cell according to the first number of vehicles, the second number of vehicles, the third number of vehicles and the number of lane change vehicles in each stage.
2. The method of claim 1, wherein the constructing control equations for each stage based on the traffic priorities comprises:
determining the remaining space and the total space limit of the front cell according to the driver response time;
and constructing a control equation of each stage according to the traffic priority and the residual space and total space limit of the front cell.
3. The method of claim 2, wherein determining the remaining space and total space limitations of the front cells based on the driver response time comprises:
according to the speed characteristics of each vehicle type, setting the probability of changing lanes to the left motor vehicle lane for the first vehicle;
and calculating the residual space change generated by lane change of the vehicle in each cell according to the lane change probability.
4. The method of claim 2, wherein determining the remaining space and total space limitations of the front cells based on the driver response time comprises:
for a first vehicle, determining that the total space limit of a front cell is the maximum number of vehicles accommodated by a unit cell;
for the second vehicle, it is determined that the total spatial limit of the front cells is smaller than the maximum number of accommodated vehicles per unit cell.
5. An electronic device, comprising:
one or more processors;
a memory for storing one or more programs,
the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the driver response time based hybrid traffic flow simulation method of any of claims 1-4.
6. A computer readable storage medium, having stored thereon a computer program which when executed by a processor implements the driver response time based hybrid traffic flow simulation method of any of claims 1-4.
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