CN118280104A - Urban traffic simulation-based vehicle lane change control method and device - Google Patents

Abstract

The present invention discloses a vehicle lane-changing control method and device based on urban traffic simulation. The method comprises the following steps: constructing a two-dimensional road network map according to actual roads, generating a vehicle driving route, performing microscopic traffic simulation, and obtaining vehicle status and road section information in the simulation; then judging whether there is a lane that meets the vehicle driving route and can reach the i+1th road section among all lanes of the current i-th road section; judging the number of vehicles that can reach the i+2th road section according to the lanes in the road section that can reach the i+1th road section; calculating the proportion of the number of vehicles from the current i-th lane to the i+1th road section to all downstream road sections of the current i-th lane according to the vehicle driving route; judging whether the lane-changing of the current vehicle will affect the driving of the following vehicle according to the vehicle status behind the vehicle position in the non-current lane; traversing the lanes in the current road section, giving each road section a congestion index according to the above conditions, and obtaining the optimal lane for lane-changing.

Description

A vehicle lane-changing control method and device based on urban traffic simulation

Technical Field

The present invention relates to the field of urban traffic simulation, and in particular to a vehicle lane changing control method and device based on urban traffic simulation.

Background technique

Urban traffic simulation is a technical means to analyze traffic flow, optimize traffic planning and improve traffic efficiency by simulating the operation of urban road traffic systems. The vehicle lane-changing model is a key component of urban traffic simulation. Its main function is to simulate the decision-making process of vehicles changing lanes on the road to improve the overall efficiency of the traffic system.

The importance of vehicle lane-changing models is reflected in the following aspects: a good lane-changing model can enable vehicles to adjust their driving paths more flexibly on the road, effectively alleviate congestion, and improve traffic flow; through reasonable lane-changing decisions, vehicles can use road space more effectively, reduce road resource waste, and improve road utilization; a good design of the lane-changing model can avoid traffic accidents, ensure that the vehicle takes into account the driving conditions of the vehicles in front and behind when changing lanes, and improve the overall safety of the traffic system. However, previous lane-changing models also have some shortcomings:

1. Only consider the congestion of the left and right lanes: This model performs poorly on wider roads and cannot fully consider the matching degree between the vehicle and the target road.

2. Simple judgment of the speed and distance of the vehicle in front: Previous models only made lane change decisions based on the speed and distance of the vehicle in front, and were unable to perceive in advance whether the vehicle in front was slowing down or stopping.

3. Not considering the subsequent driving road: Previous models failed to consider in advance the road that the vehicle was about to enter, resulting in a lack of long-term planning for lane changing decisions.

4. Ignoring the impact of the number of vehicles ahead: When waiting for traffic lights, previous models did not take into account the number of vehicles ahead, which may result in lanes not being fully utilized.

5. Lack of assessment of current vehicle and road conditions: Previous models did not fully assess the current vehicle and road conditions, which may result in the selection of suboptimal lane-changing strategies.

In order to overcome these shortcomings, it is necessary to further optimize and improve the lane-changing model and introduce more factors and advanced algorithms to achieve smarter and more adaptable vehicle lane-changing decisions in complex traffic environments.

Summary of the invention

The present invention aims to address the deficiencies of the prior art and to propose a vehicle lane changing control method and device based on urban traffic simulation.

The object of the present invention is achieved through the following technical solution: a vehicle lane changing control method based on urban traffic simulation, the method comprising the following steps:

(1) Construct a two-dimensional road network map based on actual roads, generate vehicle driving routes, perform microscopic traffic simulation, and obtain vehicle status and road section information in the simulation;

(2) Determine whether there is a lane among all lanes of the current i-th road section that meets the vehicle's driving route and can reach the i+1-th road section;

(3) Determine the number of vehicles that can reach the i+2th road section based on the lanes in the i+1th road section, and determine the congestion level T that affects the vehicle's driving route;

(4) Calculate the ratio K of the number of sections from the current i-th lane to the i+1-th lane to all downstream sections of the current i-th lane according to the vehicle's driving route;

(5) Based on the status of the vehicle behind the vehicle in the lane other than the current one, determine whether the lane change of the current vehicle will affect the driving of the following vehicle and assign a congestion impact coefficient B;

(6) Traverse the lanes in the current section and give each section a congestion index weight. The calculation formula is:

Where vehnum is the number of vehicles ahead, frontV is the speed of the vehicle ahead, limitV is the speed limit of the current lane, frontS is the position of the vehicle ahead, curS is the current vehicle position, nextNum is the number of lanes in the road section that can reach the i+2th on the vehicle's driving route, and a, b, and c are all parameters;

All lanes are sorted according to the congestion index, and the lane with the smallest congestion index is the optimal lane for lane change.

Furthermore, in step (1), a three-layer road network structure of lane, edge, and road is used to simulate a real road, and junction is used to simulate a real intersection;

There are two types of road edge: Internal Edge and Normal Edge. Normal Edge is the road section between intersections, which contains multiple lanes. Internal Edge is the driving route inside the intersection, which has only one lane.

A lane is a smaller unit than a road section. A lane cannot span two road sections and can only be arranged side by side within a road section.

Furthermore, in step (2), the i+1th downstream road section reachable from the current i-th road section is used to reversely obtain which road section downstream each lane in the current i-th road section leads to; determine whether the road section where the current vehicle is located is the terminal section in the vehicle's driving route; if it is the terminal, set the target lane to the rightmost lane in the road section; if it is not the terminal, determine which road section in the current vehicle's driving route is the same as the i+1th road section in the downstream road section reachable from the road section where the vehicle is located, and mark the lane corresponding to the road section as the lane that can reach the i+1th road section.

Furthermore, in step (3), if the i+2th road segment in the vehicle's driving route is the destination, then this step is skipped; otherwise, the number of lanes in the i+1th road segment that can reach the i+2th road segment on the driving route is found according to the vehicle's driving route, which is recorded as nextNum, and the driving route influence coefficient is recorded as T:

The meaning of T is: whether the current lane can reach the NextNormalEdge of the i+1th section in the driving route, and whether the downstream lane of the i+1th section can reach the section on the i+2th driving route. If both are satisfied, it is recorded as 1. If the first point is not satisfied, it is recorded as t _1. If the second point is not satisfied, it is recorded as t _2. If none of them are satisfied, it is recorded as t _3. At this time, t ₁ , t ₂ , and t ₃ should be less than 1 and decreasing.

Furthermore, in step (5), if there is a vehicle behind, the position information of the vehicle is obtained and recorded as backS, the speed information is recorded as backV, the current vehicle position information is recorded as curS, the current vehicle speed information is recorded as curV, and the for The maximum lane-changing time is recorded as maxA; the influence coefficient B of the vehicle coming from behind is calculated, that is, the coefficient of the current vehicle changing lanes to affect the driving of the following vehicle is:

when When it is greater than or equal to maxA, the rear vehicle will affect the lane change within the current maximum lane change time, then the rear vehicle is considered to be too fast, a higher congestion index is assigned, and consideration is given to changing lanes after the rear vehicle passes.

Furthermore, after obtaining the lane ranking according to the congestion index, it is necessary to determine the candidate lanes. The congestion indexes of all the ranked lanes except the current lane are compared with the current lane in turn until a certain value is greater than or equal to p% of the congestion index of the current lane. The lanes with a congestion index less than p% of the current lane are included in the candidate lanes, where the value of p is set as:

Among them, curV represents the current vehicle speed, limitV represents the maximum speed of the vehicle according to the speed limit of the road section and the speed limit of the current vehicle type; at this time, the meaning of p is that the lower the current vehicle speed is from the speed limit, the less desired it is to change lanes.

Furthermore, a safety check is performed on each selected lane, that is, after changing lanes at the current speed, it is determined whether there is a vehicle conflict in the target lane. The distance required for lane change is t*V, and the conflict judgment distance is t*(V+-v), where t is the set lane change time, V is the current vehicle speed, and v is the set speed offset value;

a. Whether the target lane is fully occupied within the range of the corresponding position plus the conflict judgment distance;

b. Whether there is a rear vehicle rushing into the target lane within the range of the corresponding position plus the conflict judgment distance. The rear vehicle judgment position is calculated as the rear vehicle's current position + t* the rear vehicle's current speed;

When there is no conflict, the current lane is output as the lane-changing target; when there is a conflict, the lane is judged to be unsafe and the judgment of the next lane continues. When all candidate lanes are unsafe, the output is empty, indicating that the current situation does not meet the lane-changing conditions.

In a second aspect, the present invention also provides a vehicle lane changing control device based on urban traffic simulation, comprising a memory and one or more processors, wherein the memory stores executable code, and when the processor executes the executable code, the vehicle lane changing control method based on urban traffic simulation is implemented.

In a third aspect, the present invention further provides a computer-readable storage medium having a program stored thereon, and when the program is executed by a processor, the vehicle lane changing control method based on urban traffic simulation is implemented.

In a fourth aspect, the present invention further provides a computer program product, including a computer program/instruction, which, when executed by a processor, implements the vehicle lane changing control method based on urban traffic simulation.

Beneficial effects of the present invention:

1. Consider the matching degree between the vehicle and the target road section: The new model introduces more factors, such as vehicle type, target road section characteristics, etc., so that the matching degree between the vehicle and the target road section can be better considered on wider road sections.

2. Pre-sense when the vehicle ahead is slowing down or stopping: The new model can sense when the vehicle ahead is slowing down or stopping in advance, avoiding simple judgments based solely on speed and distance. Such improvements make lane-changing decisions smarter and safer, reducing the risk of traffic accidents.

3. Long-term planning of lane change decisions: The new model takes into account the road section that the vehicle is about to enter, and achieves longer-term lane change planning. This helps avoid short-sighted decisions and improves the efficiency and smoothness of the overall traffic system.

4. Make full use of lane space: By taking into account the number of vehicles ahead, the new model ensures that lane space is fully utilized when waiting for traffic lights, reducing the situation where lanes are not fully filled, improving the utilization rate of road resources and reducing the possibility of congestion.

5. Comprehensive assessment of current vehicle and road conditions: The new model comprehensively assesses the current vehicle and road conditions to ensure the selection of the optimal lane-changing strategy. This helps improve the efficiency of the overall traffic system and reduce unnecessary traffic jams and delays.

BRIEF DESCRIPTION OF THE DRAWINGS

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

FIG1 is a flow chart of a vehicle lane changing control method based on urban traffic simulation provided by the present invention;

FIG2 is a schematic diagram of a road network structure of an urban traffic simulation;

FIG3 is a schematic diagram of a vehicle decision-making process for pre-sensing the subsequent journey;

Figure 4 is a diagram of a real traffic simulation scene;

FIG5 is a structural diagram of a vehicle lane-changing control device based on urban traffic simulation provided by the present invention.

Detailed ways

The specific implementation modes of the present invention are further described in detail below with reference to the accompanying drawings.

As shown in FIG1 , the present invention provides a vehicle lane changing control method based on urban traffic simulation, the method comprising the following steps:

(1) Constructing a road network based on actual roads

As shown in Figure 2, a three-layer road network structure of lanes, edges, and roads is used to simulate real roads, and junctions are used to simulate real intersections.

There are two types of road edge: Internal Edge and Normal Edge. Normal Edge (hereinafter referred to as Normal) is the road section in the usual sense, that is, the road section between intersections; while Internal Edge (hereinafter referred to as Internal) specifically refers to the driving route inside the intersection. The two have many similarities. The only difference is that Normal Edge can contain multiple lanes, while Internal Edge has only one lane. This is done to simplify the processing logic inside the intersection. The data contained in the road edge include: road speed limit, road attributes, road length, road width, included lanes, and included equipment.

Lane is a smaller unit than road section. A lane cannot span two road sections and can only be arranged side by side inside a road section. The difference between Normal Edge and Internal Edge at the Edge level is unified at the Lane level. Lane contains the following data: lane speed limit, lane length, lane width, road section to which the lane belongs, and the equipment included.

Road is a specific concept, which is above Edge. It is a concept of complete roads similar to "Renmin Road" and "Jiefang Road".

An intersection is a point where two or more directed roads intersect, and is used to connect adjacent edges. The data included are: the coordinates of the center point of the intersection, the road section entering the intersection, and the road section leaving the intersection.

The traffic light TrafficLight at the intersection is a device included in the road section, and the data included include: the traffic light cycle and the lane controlled by the traffic light.

(2) Build OD and generate routes based on new energy vehicle data

The method of the present invention directly obtains the smallest area block from the map structure, and then makes full use of GPS data to extract the starting and ending points in the trajectory data to construct the starting and ending point OD data set. It includes the following steps:

(2.1) Acquiring trajectory data, wherein the trajectory data includes a vehicle identification code (VIN), a time when the trajectory data is acquired, longitude, latitude, vehicle speed, and vehicle key status;

OD: Origin and destination, including the starting point (Origin) and the destination (Destination).

(2.2) Filter the trajectory data, delete the trajectory data with missing values, redundant data and other abnormal data, and obtain the normal trajectory data set;

(2.3) For each data in the normal trajectory data set, group it according to the vehicle identification code VIN, and sort the data in the same group in order from early to late according to time;

(2.4) According to the vehicle key status keystatus, determine whether it is the starting and ending point, and construct the OD data set A = {A ₁ , A ₂ , A ₃ , ..., _Ai , ..., A _N }, where the i-th OD data _Ai includes longitude and latitude. Assuming that the vehicle key will not be turned off during driving, the starting and ending point determination method is:

1) If the trajectory data is the first point in the group of data where the vehicle key state is turned on and the vehicle speed is not 0, it is judged as the starting point;

2) If the vehicle key status of the trajectory data changes from off (or ignition) to on, and the vehicle speed is no longer 0, it is determined to be the starting point;

3) If the trajectory data is the last point in the group of data where the vehicle key status is off and the vehicle speed is 0, it is determined as the end point;

4) If the vehicle key status of the trajectory data changes from on to off, and the vehicle speed becomes 0, it is determined to be the end point;

(2.5) Based on each piece of data from the vehicle’s GPS positioning, a directed array consisting of Normal Edges is generated in the road network as the vehicle’s route.

(3) Start micro traffic simulation

A microscopic traffic simulation system is realized through the two-dimensional map generated earlier. The simulation system is mainly composed of four parts: Network, Vehicle, Kernel, and Common Service. The Network module is responsible for the movement of vehicles, the construction of roads, and the construction of facilities on the roads; the Vehicle module is responsible for the behavior of the vehicle (changing lanes, accelerating, decelerating) and the construction of the vehicle's internal equipment; the Kernel module is responsible for controlling the operation of the road network and vehicles, and defining the clock metronome to control the speed of the simulation; the CommonService module is responsible for defining some global configurations and data access interfaces for the convenience of other modules.

(4) Obtaining the vehicle status in simulation

Get relevant information about the vehicle in the simulation, such as the vehicle's speed, acceleration, driving position, driving intention, vehicle type, current vehicle speed curV, and position curS in the current Lane.

(5) Obtaining road section information in simulation

Obtain relevant information of the road section in the simulation, including the speed limit sign, length, number of lanes, and subsequent sections.

(6) Obtain a list of lanes on the current i-th road segment that match the vehicle's route to the i+1-th road segment.

Through the i+1th downstream edge reachable by the current i-th edge, reversely obtain which edge each lane in the current i-th edge can pass to downstream, for example, the left-turn lane can reach the left edge of the intersection, and the straight lane can reach the front edge of the intersection; determine whether the edge where the current vehicle is located is the terminal edge in the vehicle route. If it is the terminal, set the target lane to the rightmost lane in the edge; if it is not the terminal, determine which edge of the downstream edges reachable by the edge where the vehicle is located is the same as the i+1th edge in the route of the current vehicle, and mark the lane corresponding to the edge as the lane that can reach the i+1th edge.

(7) Obtain the number of lanes that can reach the i+2th road section for each lane in the i+1th road section. This should be a list with a length equal to the number of lanes that can reach the i+1th road section, where is the number of lanes that each lane can reach the i+2th road section.

If the i+2th Normal Edge in the vehicle's route is the destination, skip this step; otherwise, find the number of Normal Edges on the route that can be reached from the lane in the i+1th Normal Edge according to the vehicle route, denoted as nextNum. Here, the route influence coefficient is denoted as T. At this time, the meaning of T is: whether the current lane can reach the i+1th Normal Edge in the route, and whether the i+2th Normal Edge on the route can be reached in the downstream lane of the i+1th Normal Edge. If both are satisfied, it is recorded as 1. If the first point is not satisfied, it is recorded as t _1. If the second point is not satisfied, it is recorded as t _2. If none of them are satisfied, it is recorded as t _3. At this time, t ₁ , t ₂ , and t ₃ should be less than 1 and decrease, as shown in Figure 3 as an additional explanation.

(8) Obtain the vehicle position and number of vehicles ahead in the lane

Through the vehicle manager of each Normal Edge in the micro-simulation system, the number of vehicles in front of each lane at the location of the vehicle is obtained, recorded as vehnum. Introducing the number of queued vehicles can make the queue at the traffic light intersection more even.

(9) Obtain the congestion level based on the speed of the vehicle in front and the distance between the vehicle and the vehicle in front

When traversing the lanes, if the number of vehicles in front of the vehicle in the current lane is not 0, find the first vehicle in front of the lane, obtain the distance between the vehicle and the current vehicle and the speed of the vehicle, which are recorded as frontS and frontV respectively. By introducing the speed and distance of the vehicle in front, the degree of congestion in front of the lane can be detected in advance.

(10) Calculate the ratio of the number of sections from the current i-th lane to the i+1-th lane to the number of sections downstream of the current i-th lane according to the route

Calculate the ratio of the number of downstream Internal Lanes in the current Normal Lane that can lead to the i+1th Normal Edge in the current vehicle route to the number of all downstream Internal Lanes, and record the proportional influence coefficient of the downstream section as K.

Among them, nextLanes indicates the number of Normal Edges that can lead to the i+1th Normal Edge in the current vehicle route; allLanes indicates the number of all downstream Internal Lanes in the current Normal Lane;

(11) Obtain the status of the vehicle behind the vehicle position in the non-current lane

If there is a vehicle behind, the position information of the vehicle is recorded as backS, the speed information is recorded as backV, the current vehicle position information is recorded as curS, the current vehicle speed information is recorded as curV, and the for The maximum lane-changing time is denoted as maxA, which means when When it is greater than or equal to maxA, the rear vehicle will affect the lane change within the current maximum lane change time, then the rear vehicle is considered to be too fast, a higher congestion index is assigned, and consideration is given to changing lanes after the rear vehicle passes.

Calculate the influence coefficient B of the vehicle coming from behind, that is, the coefficient of the current vehicle changing lanes that will affect the driving of the vehicle behind:

(12) Find the optimal lane based on the congestion index

After traversing the Lanes in the current Normal Edge, a congestion index weight is given to each road section. The calculation formula is:

Where vehnum is the number of vehicles ahead, frontV is the speed of the vehicle ahead, limitV is the speed limit of the current lane, frontS is the position of the vehicle ahead, curS is the current vehicle position, nextNum is the number of lanes that can reach the NormalEdge of the i+2th on the Route, a, b, c are all parameters, which are set to 100, 5, and 1 in the present invention. The congestion index weight is subsequently modified by T, K, and B:

weight’＝weight·T·K·B

Among them, weight’ is the corrected congestion index, T is the route influence coefficient, the value is less than or equal to 1 and greater than 0, K is the downstream section proportion influence coefficient, the value is less than or equal to 1 and greater than 0, B is the rear vehicle influence coefficient, the value is greater than or equal to 1.

Arrange all lanes in ascending order according to the congestion index, recorded as arranged Lanes, where the Lane with the smallest congestion index is the optimal Lane;

(13) Determine whether the vehicle is approaching the lane with the speed limit

1. Road sections without a center line

1) The maximum speed on urban roads shall not exceed 30 kilometers per hour;

2) The maximum speed on highways shall not exceed 40 kilometers per hour.

2. Road sections with only one motor vehicle lane in the same direction

1) The maximum speed on urban roads shall not exceed 50 kilometers per hour;

2) The maximum speed on highways shall not exceed 70 kilometers per hour.

3. Road sections with more than two motor vehicle lanes in the same direction (without speed limit signs or markings)

1) The maximum speed on urban roads shall not exceed 70 kilometers per hour;

2) The maximum speed on closed motor vehicle-only roads and highways shall not exceed 80 kilometers per hour.

Get the current vehicle speed, denoted as curV, and calculate the maximum speed of the vehicle based on the speed limit of the road section and the speed limit of the current vehicle type, denoted as limitV.

(14) If the lane exceeds a certain proportion compared to the original lane, it will be recorded as a candidate lane

Compare the congestion index of the arranged Lanes with that of the current Lane in turn (except the current Lane) until a value of one of the arranged items is greater than or equal to p% of the congestion index of the current lane. Then, the Lanes with a congestion index less than p% of the current lane are included in the candidate lanes, where the value of p is set as:

At this time, p means that the less the current vehicle speed reaches the speed limit, the less it is desired to change lanes. For example, when the driving speed reaches 90% of the speed limit, lane change is considered only when the congestion level reaches 10% of the current lane. The advantage of this is that it can eliminate the fluctuation of vehicle intentions and prevent vehicles from frequently changing lanes in relatively smooth Edges.

list＝{Weight _lane >Weight _cur ·p|Lane∈Lanes}

(15) Safety judgment of candidate lanes

A safety check is performed on each selected candidate road section, that is, at the current speed, the lane is changed to the lane in the direction of the candidate lane to determine whether there is any vehicle conflict. The distance required for lane change is t*V, and the conflict judgment distance is t*(V±v), where t is the set lane change time, V is the current vehicle speed, and v is the set speed offset value.

a. Whether the corresponding position on the target lane plus the conflict judgment distance is fully occupied by vehicles.

b. Whether there is a rear vehicle rushing into the target lane within the range of the corresponding position plus the conflict judgment distance. The rear vehicle judgment position is calculated as the rear vehicle's current position + t* the rear vehicle's current speed;

When there is no conflict, the current lane is output as the lane-changing target; when there is a conflict, the lane is judged to be unsafe, and the judgment of the next lane continues. When all candidate lanes are unsafe, the output is empty, indicating that the current situation does not meet the lane-changing conditions.

(16) Lane change judgment ends

Output the corresponding results and output the lane change intention.

(17) Output the lane change results in the simulation system

The lane-changing intention is introduced into each moving vehicle, as shown in FIG4 , which is a diagram of a real traffic simulation scene.

Corresponding to the aforementioned embodiment of a vehicle lane changing control method based on urban traffic simulation, the present invention also provides an embodiment of a vehicle lane changing control device based on urban traffic simulation.

Referring to FIG. 5 , a vehicle lane changing control device based on urban traffic simulation is provided in an embodiment of the present invention, comprising a memory and one or more processors, wherein the memory stores executable code, and when the processor executes the executable code, it is used to implement a vehicle lane changing control method based on urban traffic simulation in the above embodiment.

An embodiment of a vehicle lane changing control device based on urban traffic simulation provided by the present invention can be applied to any device with data processing capabilities, and the any device with data processing capabilities can be a device or apparatus such as a computer. The device embodiment can be implemented by software, or by hardware or a combination of software and hardware. Taking software implementation as an example, as a device in a logical sense, it is formed by the processor of any device with data processing capabilities in which it is located to read the corresponding computer program instructions in the non-volatile memory into the memory and run them. From the hardware level, as shown in Figure 5, it is a hardware structure diagram of any device with data processing capabilities in which a vehicle lane changing control device based on urban traffic simulation provided by the present invention is located. In addition to the processor, memory, network interface, and non-volatile memory shown in Figure 5, any device with data processing capabilities in which the device in the embodiment is located can also include other hardware according to the actual function of the device with data processing capabilities, which will not be described in detail.

The implementation process of the functions and effects of each unit in the above-mentioned device is specifically described in the implementation process of the corresponding steps in the above-mentioned method, and will not be repeated here.

For the device embodiment, since it basically corresponds to the method embodiment, the relevant parts can refer to the partial description of the method embodiment. The device embodiment described above is only schematic, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of the present invention. Ordinary technicians in this field can understand and implement it without paying creative work.

An embodiment of the present invention further provides a computer-readable storage medium having a program stored thereon. When the program is executed by a processor, a vehicle lane changing control method based on urban traffic simulation in the above embodiment is implemented.

The computer-readable storage medium may be an internal storage unit of any device with data processing capability described in any of the aforementioned embodiments, such as a hard disk or a memory. The computer-readable storage medium may also be an external storage device of any device with data processing capability, such as a plug-in hard disk, a smart media card (SMC), an SD card, a flash card, etc. equipped on the device. Furthermore, the computer-readable storage medium may also include both an internal storage unit and an external storage device of any device with data processing capability. The computer-readable storage medium is used to store the computer program and other programs and data required by any device with data processing capability, and may also be used to temporarily store data that has been output or is to be output.

The present invention also provides a computer program product, including a computer program/instruction, and when the computer program/instruction is executed by a processor, the vehicle lane changing control method based on urban traffic simulation is implemented.

The above embodiments are used to illustrate the present invention rather than to limit the present invention. Any modification and change made to the present invention within the spirit of the present invention and the protection scope of the claims shall fall within the protection scope of the present invention.

Claims (10)

1. A vehicle lane change control method based on urban traffic simulation is characterized by comprising the following steps:

(1) Constructing a road network two-dimensional map according to an actual road, generating a vehicle driving route, performing microscopic traffic simulation, and acquiring vehicle state and road section information in the simulation;

(2) Judging whether all lanes of the current ith road section have lanes which accord with the (i+1) th road section of the vehicle driving route;

(3) Judging the number of vehicles reaching the (i+2) th road section according to the lanes reaching the (i+1) th road section, and judging the congestion degree T affecting the running route of the vehicle;

(4) Calculating the proportion K of the number of the current ith lane to the (i+1) th road sections to the whole downstream road sections of the current ith lane according to the vehicle driving route;

(5) Judging whether the current vehicle lane change affects the running of the rear vehicle according to the state of the vehicle behind the vehicle position in the non-current lane, and giving a congestion influence coefficient B;

(6) Traversing lanes in a current road section, giving a congestion index weight to each road section, wherein the calculation formula is as follows:

Wherein vehnum is the number of vehicles ahead, frontV is the speed of vehicles ahead, limitV is the current lane speed limit, frontS is the position of vehicles ahead, curS is the current vehicle position, nextNum is the number of lanes in the road section on the vehicle driving route up to the (i+2) th lane, and a, b and c are parameters;

And sequencing all the lanes according to the congestion index, wherein the lane with the smallest congestion index is the optimal lane change lane.

2. The vehicle Lane change control method based on urban traffic simulation according to claim 1, wherein in the step (1), a three-layer Road network structure of a Lane, a Road section Edge and a Road is adopted to simulate a real Road, and a Junction is adopted to simulate a real intersection;

road segments Edge are divided into two types: INTERNAL EDGE and Normal Edge, which are road sections between intersections, including multiple lanes Lane, INTERNAL EDGE, which are driving routes inside the intersections, and only one Lane;

the Lane is a unit smaller than a road section, and one Lane cannot cross two road sections and can be arranged in parallel inside the road section.

3. The vehicle lane change control method based on urban traffic simulation according to claim 1, wherein in the step (2), the downstream i+1 road section accessible to the current i road section is reversely acquired, and each lane in the current i road section is respectively passed to the downstream road section; judging whether the road section where the current vehicle is located is a destination road section in the vehicle driving route, if yes, setting the target lane as the rightmost lane in the road section, if not, judging which road section in the i+1th road section in the current vehicle driving route is the same as the downstream road section reachable by the road section where the current vehicle is located, and marking the lane corresponding to the road section as the lane reaching the i+1th road section.

4. The urban traffic simulation-based vehicle lane change control method according to claim 1, wherein in the step (3), if the i+2th road section is the destination in the travel route of the vehicle, the step is skipped; otherwise, the number of sections on which the (i+2) th road section can be reached by the lane in the (i+1) th road section is searched according to the running route of the vehicle, which is marked as nextNum, and the running route influence coefficient is marked as T:

T has the meaning: if the current lane can reach the (i+1) th road section NextNormalEdge in the driving route and if the (i+2) th road section on the driving route can reach the (i+1) th road section in the downstream lane, the current lane is marked as 1 if both the road sections are satisfied, the current lane is marked as t ₁ if the first point is not satisfied, the current lane is marked as t ₂ if the second point is not satisfied, the current lane is marked as t ₃ if both the first point and the second point are not satisfied, and at this time, t ₁,t₂,t₃ should be smaller than 1 and gradually decreased.

5. The urban traffic simulation-based vehicle lane change control method according to claim 1, wherein in step (5), if there is a rear vehicle, the position information of the vehicle is obtained and is denoted as backS, the speed information is denoted as backV, the current vehicle position information is denoted as curS, the current vehicle speed information is denoted as curV, and the speed information is denoted asIs thatThe maximum lane change time is recorded as maxA; calculating an influence coefficient B of a rear coming vehicle, namely, a coefficient that the current vehicle lane change can influence the running of the rear vehicle is as follows:

When (when) When the traffic jam index is larger than or equal to maxA, the rear vehicle can influence lane change in the current maximum lane change time, and the rear vehicle is considered to be too fast, a higher jam index is given, and lane change after the rear vehicle passes is considered.

6. The vehicle lane change control method based on urban traffic simulation according to claim 1, wherein after obtaining the lane sequence according to the congestion index, the candidate lanes are further required to be determined, all sequenced lanes except the current lane are sequentially compared with the current lane for the congestion index, until a certain value is greater than or equal to p% of the current lane congestion index, the lane less than p% of the current lane congestion index is listed in the candidate lanes, wherein the value of p is set as follows:

Wherein curV represents the current vehicle speed, limitV represents deriving the maximum speed of the vehicle from the road segment speed limit and the current vehicle type speed limit; the meaning of p at this time is that the less the current vehicle speed reaches the speed limit, the less desirable the lane change is.

7. The urban traffic simulation-based vehicle lane change control method according to claim 1, wherein safety inspection judgment is performed on each selected lane, namely, whether a vehicle conflict exists on a target lane is judged after lane change at the current speed, the distance required for lane change is t x V, the conflict judgment distance t x (v+ -V), t is set lane change time, V is the current vehicle speed, and V is a set speed offset value;

a. whether the range of the conflict judgment distance is occupied by the vehicle or not is judged by adding the conflict in the corresponding position on the target lane;

b. Whether a rear vehicle rushes in the range of the conflict judgment distance is added to the corresponding position on the target lane, and the position where the rear vehicle is judged is calculated as the current position of the rear vehicle and t is the current speed of the rear vehicle;

when no conflict exists, the current lane is used as a lane change target to be output; when the collision exists, the lane is judged to be unsafe, the judgment of the next lane is continued, and when all the candidate lanes are unsafe, the output is empty, and the current situation is indicated to not meet the lane change condition.

8. A vehicle lane change control apparatus based on urban traffic simulation, comprising a memory and one or more processors, wherein executable codes are stored in the memory, and wherein the processor implements a vehicle lane change control method based on urban traffic simulation as claimed in any one of claims 1 to 7 when executing the executable codes.

9. A computer-readable storage medium having a program stored thereon, wherein the program, when executed by a processor, implements a vehicle lane change control method based on urban traffic simulation as claimed in any one of claims 1 to 7.

10. A computer program product comprising computer programs/instructions which, when executed by a processor, implement a vehicle lane change control method based on urban traffic simulation as claimed in claims 1-7.