WO2022193891A1

WO2022193891A1 - Vehicle travel control method and apparatus, vehicle, server, and storage medium

Info

Publication number: WO2022193891A1
Application number: PCT/CN2022/076398
Authority: WO
Inventors: 张少康; 朱振夏; 朱加伟
Original assignee: 北京航迹科技有限公司
Priority date: 2021-03-17
Filing date: 2022-02-16
Publication date: 2022-09-22
Also published as: CN113066298A; CN113066298B

Abstract

Provided are a vehicle travel control method and apparatus, a vehicle, a server, and a storage medium. The method comprises: obtaining target map data, wherein the target map data comprises attribute information of lanes, each piece of attribute information comprises a lane line type of at least one road segment in the corresponding lane, and in the case where the congestion degree of the road segment is greater than a preset degree threshold, the lane line type is a solid line type (S201); in the case where a target vehicle travels on a target lane on the basis of path planning information, if it is detected that the target vehicle satisfies a lane change condition, determining, on the basis of the target map data, a target laneline type of a target road segment corresponding to the target vehicle in the target lane (S202); and if the target lane line type is the solid line type, controlling the target vehicle to travel along the target lane (S203). The traveling reliability of the target vehicle can be improved.

Description

Vehicle driving control method, device, vehicle, server, storage medium

cross reference

This application claims priority to Chinese Patent Application No. 202110285977.2 filed on March 17, 2021, the entire contents of which are incorporated herein by reference.

technical field

The embodiments of the present disclosure relate to the technical field of automatic driving, and in particular, to a vehicle driving control method, device, vehicle, server, and storage medium.

Background technique

With the rapid development of artificial intelligence technology, autonomous driving has become a frontier hotspot in the field of artificial intelligence. The research and development of autonomous driving is expected to reduce traffic accidents and reduce the accident casualty rate.

At present, autonomous vehicles generally drive based on the results of path planning. The purpose of path planning is to guide the vehicle from the starting point to the destination. The goal of path planning is to ensure the safety of driving and the comfort of passengers in the vehicle during the driving process.

However, various temporary conditions often exist in the driving process of autonomous vehicles, resulting in low driving reliability of the vehicles.

SUMMARY OF THE INVENTION

Embodiments of the present disclosure provide a vehicle driving control method, device, vehicle, server, and storage medium, which can improve the driving reliability of a target vehicle.

In a first aspect, an embodiment of the present disclosure provides a vehicle driving control method, the method comprising:

Acquiring target map data, the target map data includes attribute information of each lane, and each attribute information includes a lane boundary type of at least one section in the corresponding lane, wherein the congestion degree in the section is greater than a preset degree threshold. In this case, the type of the lane dividing line is a solid line type;

In the case where the target vehicle is driving in the target lane based on the path planning information, if it is detected that the target vehicle satisfies the lane change condition, the target road section corresponding to the target vehicle in the target lane is determined based on the target map data The type of target lane dividing line;

If the type of the target lane boundary line is a solid line type, the target vehicle is controlled to drive along the target lane.

In a second aspect, embodiments of the present disclosure provide a vehicle driving control device, the device comprising:

an acquisition module, configured to acquire target map data, where the target map data includes attribute information of each lane, and each attribute information includes the lane boundary type of at least one section in the corresponding lane, wherein the congestion degree in the section is greater than In the case of a preset degree threshold, the type of the lane dividing line is a solid line type;

The first determination module is configured to determine, based on the target map data, whether the target vehicle is in the target lane with the target vehicle if it is detected that the target vehicle meets the lane change condition when the target vehicle is driving in the target lane based on the path planning information. Describe the target lane boundary type of the target road section corresponding to the target vehicle;

A first control module, configured to control the target vehicle to drive along the target lane if the type of the target lane boundary line is a solid line type.

In a third aspect, an embodiment of the present disclosure provides a vehicle, including a memory, a processor, and a computer program stored on the memory and executable on the processor, where the processor implements the above when executing the computer program The method described in the first aspect.

In a fourth aspect, an embodiment of the present disclosure provides a server, including a memory, a processor, and a computer program stored on the memory and executable on the processor, where the processor implements the above when executing the computer program The method described in the first aspect.

In a fifth aspect, an embodiment of the present disclosure provides a storage medium on which a computer program is stored, and when the computer program is executed by a processor, implements the method described in the first aspect.

In a sixth aspect, embodiments of the present disclosure provide a computer program product, including a computer program, which implements the method described in the first aspect when the computer program is executed by a processor.

The vehicle driving control method, device, vehicle, server, and storage medium provided by the embodiments of the present disclosure obtain target map data, and then, when the target vehicle is driving in the target lane based on the path planning information, if it is detected that the target vehicle satisfies the lane The replacement condition is based on the target map data to determine the target lane boundary type of the target road section corresponding to the target vehicle in the target lane. Since the target map data includes attribute information of each lane, each attribute information includes the lane division of at least one section in the corresponding lane. Boundary line type, and when the congestion level of the road segment is greater than the preset level threshold, the lane boundary line type is the solid line type. In this way, if the target lane boundary line type is the solid line type, it indicates that the target road segment in the target lane may be congested. Therefore, the target vehicle is controlled to continue to drive along the target lane, that is, the target vehicle is prohibited from changing lanes, which effectively avoids the target vehicle changing to other lanes when the target lane is congested, but cannot return to the target lane due to congestion in the target lane. For the problem of wrong paths, the embodiments of the present disclosure improve the driving reliability of the target vehicle.

Description of drawings

FIG. 1-a is an application environment diagram of a vehicle driving control method in one embodiment;

FIG. 1-b is an application environment diagram of the vehicle driving control method in another embodiment;

2 is a schematic flowchart of a vehicle driving control method in one embodiment;

3 is a schematic flowchart of a vehicle driving control method in another embodiment;

4 is a schematic flowchart of step 201 in another embodiment;

5 is a schematic flowchart of generating target map data according to congestion information and original map data in another embodiment;

6 is a schematic flowchart of a vehicle driving control method in another embodiment;

FIG. 7 is a schematic flowchart of detecting whether the target vehicle satisfies the lane change condition in another embodiment;

8 is a structural block diagram of a vehicle driving control device in one embodiment;

Fig. 9 is the internal structure diagram of the target vehicle in one embodiment;

FIG. 10 is an internal structure diagram of a server in one embodiment.

Detailed ways

In order to make the objectives, technical solutions and advantages of the embodiments of the present disclosure more clear, the embodiments of the present disclosure will be described in further detail below with reference to the accompanying drawings and the embodiments. It should be understood that the specific embodiments described herein are only used to explain the embodiments of the present disclosure, and are not used to limit the embodiments of the present disclosure.

First, before introducing the technical solutions of the embodiments of the present disclosure in detail, the technical background or technical evolution context on which the embodiments of the present disclosure are based is introduced.

At present, autonomous vehicles generally drive based on pre-planned path planning results. However, during the driving process, the vehicle often encounters various temporary situations. For example, after the vehicle changes lanes and overtakes, the original lane may be congested. Returning to the original lane, especially in some situations that require the vehicle to turn/turn around, because the inability to return to the original lane to make a turn/turn causes the vehicle's driving path to be wrong, and the vehicle's driving reliability is low.

How to improve the driving reliability of the vehicle has become an urgent problem to be solved at present. In addition, it should be noted that the applicant has devoted a lot of creative work since it was discovered that the vehicle could not return to the original lane due to congestion in the original lane and the technical solutions described in the following embodiments after changing lanes and overtaking.

The technical solutions involved in the embodiments of the present disclosure will be introduced below with reference to the application environment of the embodiments of the present disclosure.

FIG. 1-a is a schematic diagram of an implementation environment involved in a vehicle driving control method provided by an embodiment of the present disclosure. As shown in FIG. 1-a, the implementation environment may include a target vehicle 110, and the target vehicle 110 may be a motor vehicle or non-motorized vehicles.

In the implementation environment shown in FIG. 1-a, the target vehicle 110 can acquire target map data, where the target map data includes attribute information of each lane, and each attribute information includes the lane boundary type of at least one section in the corresponding lane, wherein, When the congestion level of the road section is greater than the preset level threshold, the lane boundary type is the solid line type; when the target vehicle 110 is driving in the target lane based on the path planning information, if the target vehicle 110 detects that the target vehicle 110 satisfies the lane To change the condition, the target vehicle 110 can determine the target lane boundary type of the target road section corresponding to the target vehicle 110 in the target lane based on the target map data; if the target lane boundary type is a solid line type, the target vehicle 110 can control the target vehicle 110 Drive along the target lane.

FIG. 1-b is a schematic diagram of another implementation environment involved in the vehicle driving control method provided by the embodiment of the present disclosure. As shown in FIG. 1-b, the implementation environment may further include a target vehicle 110 and a server 120, and communication between the target vehicle 110 and the server 120 may be performed through a network.

The target vehicle 110 may be a motor vehicle or a non-motor vehicle, and the server 120 may be one server or a server cluster composed of multiple servers.

In the implementation environment shown in FIG. 1-b, the server 120 may acquire target map data, where the target map data includes attribute information of each lane, and each attribute information includes the lane boundary type of at least one section in the corresponding lane, wherein, in the When the congestion degree of the road section is greater than the preset degree threshold, the type of the lane dividing line is the solid line type; in the case that the target vehicle 110 is driving in the target lane based on the path planning information, the server 120 detects that the target vehicle 110 satisfies the lane To change the condition, the server 120 may determine the target lane boundary type of the target road section corresponding to the target vehicle 110 in the target lane based on the target map data; if the target lane boundary type is a solid line type, the server 120 may control the target vehicle 110 to move along the target lane drive.

In one embodiment, as shown in FIG. 2 , a vehicle driving control method is provided, and the method is applied to the target vehicle in FIG. 1-a as an example to illustrate, including the following steps:

Step 201, the target vehicle acquires target map data.

In this embodiment of the present disclosure, the target vehicle may be any vehicle with an automatic driving function. The target map data may be obtained by the target vehicle from a server or terminal, or may be obtained by the target vehicle from other vehicles, and of course, may also be generated by the target vehicle based on the original map data.

Taking the target map data as an example that the target vehicle generates by itself based on the original map data, optionally, the original map data may be obtained by the target vehicle from a server, and the original map data may be a high-precision map. The original map data can include the precise location and original attributes of traffic elements such as roads, lanes, intersections, traffic lights, original lane boundaries, curbs, etc. The original attributes such as whether the lane is a straight lane or a turning lane, and the original lane boundary type is a dashed line type Or the solid line type, etc.

It should be noted that, in the original map data, the original lane boundary type is the real lane boundary type, that is, the original lane boundary type in the original map data is consistent with the actual lane boundary type of the real lane in the road.

In the embodiment of the present disclosure, the target vehicle can also obtain congestion information of each lane. Taking lane A as an example, the congestion information can represent, for example, the congestion position of lane A (that is, which section of lane A is congested) and the degree of congestion. In this way, the target vehicle adjusts or keeps the original lane boundary type in the original map data correspondingly according to the obtained congestion information of each lane, so that when a certain road segment is congested, the lane boundary type of the road segment can be adjusted accordingly. Can be of solid line type.

For example, if the congestion level of road segment A of lane A is greater than the preset degree threshold and the original lane boundary type of road segment A is a dotted line type, the original lane boundary type of the road segment A is modified to a solid line type, and so on.

Through the above embodiments, the target vehicle can acquire the target map data. Wherein, the target map data includes attribute information of each lane, and each attribute information includes the lane boundary type of at least one road section in the corresponding lane, and when the congestion degree of the road section is greater than the preset degree threshold, the lane boundary type is true line type.

Optionally, the target vehicle may also periodically acquire the congestion information of each lane, and each time the target vehicle acquires the congestion information of each lane, the latest updated target map data may be used as the original map data according to the above-mentioned implementation manner. And use the newly acquired congestion information of each lane to process the original map data to obtain the latest target map data. In this way, the length of the solid line corresponding to the congested road section of each lane in the target map data can be dynamically changed according to the length of the congested traffic flow, that is, the length of the solid line corresponding to the congested road section is consistent with the length of the congested traffic flow.

Step 202: In the case where the target vehicle is driving in the target lane based on the path planning information, if the target vehicle detects that the target vehicle meets the lane change condition, then, based on the target map data, determine the target lane of the target road section corresponding to the target vehicle in the target lane Demarcation line type.

The path planning information may be obtained by the target vehicle or the server performing path planning on the target vehicle. Optionally, the path planning information may include the identification and sequence of each lane planned between the starting point position and the ending point position of the target vehicle.

When the target vehicle is driving in the target lane based on the path planning information, optionally, if the target vehicle detects that a vehicle in front of the current lane is traveling at a low speed or is stationary, it is determined that the target vehicle satisfies the lane changing condition.

It can be understood that after the target vehicle determines that the target vehicle meets the lane change conditions, if the real lane boundary type of the current road section is determined to be a dashed line type based on the original map data, the dashed line in the traffic rules can change lanes. Therefore, the target vehicle can change lanes. . However, there is a problem: after the target vehicle changes lanes, it may not be able to return to the target lane due to congestion in the target lane, especially in some scenarios that require turning/U-turn, that is, the target lane also includes the target vehicle not driving If the target vehicle can no longer return to the target lane for turning/turning, the driving path of the target vehicle will be wrong, and the driving reliability of the vehicle will be low.

In the embodiment of the present disclosure, in order to avoid the above problems, after the target vehicle determines that the target vehicle meets the lane change condition, it does not immediately change the lane, but determines the target lane division of the target road section corresponding to the target vehicle in the target lane based on the target map data. Boundary type.

The following describes the process for the target vehicle to determine the target lane boundary type of the target road section corresponding to the target vehicle in the target lane based on the target map data.

Optionally, the target vehicle may determine the target lane mark of the target lane, and determine the target attribute information corresponding to the target lane in the target map data according to the target lane mark, where the target attribute information is the attribute information of the target lane in the target map data, and then , the target vehicle obtains the vehicle position of the target vehicle, and determines the target lane boundary type of the target road section according to the vehicle position and target attribute information, so as to realize the goal of determining the target road section corresponding to the target vehicle in the target lane based on the target map data Lane Demarcation Line Type Process.

Specifically, the attribute information of each lane may also include the lane mark of the lane, and the target vehicle selects the attribute information including the target lane mark in the target map data to obtain the target attribute information, and the target attribute information includes at least one of the target lanes. The type of lane boundaries for the segment. In this way, according to the vehicle position, the target vehicle can determine the target lane boundary type of the target road section where the target vehicle is located from the target attribute information.

Step 203 , if the type of the boundary line of the target lane is a solid line type, the target vehicle controls the target vehicle to drive along the target lane.

Since in the target map data, when the congestion level of the road section is greater than the preset level threshold, the lane boundary type is a solid line type. Therefore, if the target vehicle detects that the target lane boundary type is a solid line type, it indicates that the target lane is in the target lane. may be congested on the target road. In order to avoid the situation that the target vehicle cannot return to the target lane after changing lanes due to the congestion of the target lane, the target vehicle controls the target vehicle to drive along the target lane, that is, the target vehicle is prohibited from changing lanes.

It should be noted that if the target vehicle detects that the target lane boundary type is a solid line type, it may also be that the target lane boundary type is a solid line in the actual target lane, but in the traffic rules, the solid line is not allowed to change. Therefore, the target vehicle also controls the target vehicle to drive along the target lane.

The foregoing embodiments are briefly supplemented below with reference to a specific application scenario.

In the traditional technology, it is assumed that the target vehicle is in lane A and needs to turn at the intersection ahead, and the target vehicle is assumed to be 500 meters away from the intersection. A slow-speed or stationary vehicle is in front of the vehicle.

However, due to the limited sensing range of the target vehicle (for example, the sensing range is 200 meters), the target vehicle cannot know that the intersection is congested at this time. Since there is a low-speed vehicle or a stationary vehicle in front of the target vehicle, the target vehicle changes lanes, such as changing to the straight lane. B.

After the target vehicle changes lanes, because lane A is already congested, the target vehicle can no longer return to lane A, and can only go straight along the straight lane B, which makes the target vehicle unable to turn according to the path planning information, resulting in the occurrence of the target vehicle's driving path. error, low driving reliability.

However, in the embodiment of the present disclosure, if the lane A is seriously congested at a distance of 500 meters from the intersection, then in the target map data, the lane boundary type corresponding to the road section from the intersection to 500 meters in the lane A is a solid line type . In this way, even if the target vehicle detects that the lane changing conditions are met (for example, a low-speed vehicle or a stationary vehicle appears in front of the target vehicle), since the target lane boundary type of the current road segment is a solid line type, the lane cannot be changed according to the traffic rules, so the target vehicle is not allowed to change lanes. The target vehicle is controlled to continue driving along lane A, which avoids the situation that the target vehicle cannot return to lane A after changing lanes.

The above embodiment obtains the target map data, and then, in the case that the target vehicle is driving in the target lane based on the path planning information, if it is detected that the target vehicle meets the lane change condition, then the target lane is determined based on the target map data. The target lane boundary type of the target road segment. Since the target map data includes attribute information of each lane, each attribute information includes the lane boundary type of at least one road segment in the corresponding lane, and when the congestion degree of the road segment is greater than the preset degree threshold. The lane boundary type is a solid line type. In this way, if the target lane boundary type is a solid line type, it indicates that the target road section in the target lane may be congested, so that the target vehicle is controlled to continue driving along the target lane, that is, the target vehicle is prohibited from changing lanes. This effectively avoids the problem that the target vehicle changes to other lanes when the target lane is congested, but cannot return to the target lane due to the congestion in the target lane, resulting in an incorrect driving path. The embodiment of the present disclosure improves the driving of the target vehicle. reliability.

Based on the above-mentioned embodiment shown in FIG. 2 , referring to FIG. 3 , this embodiment relates to the process of how the target vehicle acquires path planning information. As shown in FIG. 3 , the vehicle driving control method in this embodiment further includes step 204:

Step 204 , the target vehicle performs path planning on the target vehicle according to the starting point position of the target vehicle, the end position of the target vehicle, and the path selection weight of each lane, and obtains path planning information.

In the embodiment of the present disclosure, each attribute information further includes a path selection weight of the corresponding lane, and the path selection weight is related to the congestion degree corresponding to the lane. Optionally, the route selection weight may be positively correlated with the congestion degree corresponding to the lane, that is, for a lane, the more congested the lane is, the higher the route selection weight.

In this way, the target vehicle can determine the path selection weights of all lanes between the start and end positions in the target map data according to the start and end positions of the target vehicle, and use the depth-first search algorithm or the breadth-first search algorithm to select the weights The multiple lanes with the smallest sum are used as the global path of the target vehicle from the starting position to the ending position, that is, the path planning information. The path planning information can include the identification and sequence of each lane planned between the starting position and the ending position of the target vehicle. order.

Of course, in other embodiments, the path selection weight may also be negatively correlated with the congestion degree corresponding to the lane, that is, for a lane, if the lane is more congested, the path selection weight is lower, so that the target vehicle can select the sum of the weights The largest number of lanes are used as the global path of the target vehicle from the starting position to the ending position, which is not specifically limited here.

Hereinafter, the process of determining the path selection weight of the lane will be briefly introduced.

In the embodiment of the present disclosure, the path selection weight of the lane is determined by the dynamic path selection weight of the lane and the static path selection weight of the lane, wherein the dynamic path selection weight is related to the congestion degree corresponding to the lane, and the static path selection weight is related to the type and size of the lane. At least one of the lengths is related.

For the dynamic route selection weight, optionally, the congestion information corresponding to the lane acquired by the target vehicle may include congestion degree information, and the congestion degree information may be in the form of a congestion level or a congestion percentage. Taking the congestion level as an example, it is assumed that the higher the congestion level, the more congested the lane is, and the mapping relationship between each congestion level and each dynamic route selection weight can be preconfigured in the target vehicle. For example, the dynamic route selection weight corresponding to congestion level 1 is A1. , the dynamic route selection weight corresponding to congestion level 2 is A2, and so on, so that the dynamic route selection weight of the lane can be obtained.

For the static routing weight, the static routing weight is related to at least one of the type and length of the lane. The type of lane may be a straight type of lane, eg, straight lanes are weighted low (ie, straight lanes are preferred), curved lanes are weighted high, and so on.

Taking the static path selection weight related to the type of lane as an example, the target vehicle can spread points at equal intervals on all lanes, and the points are connected by directional and weighted edges, and the direction is consistent with the driving direction of the lane. ;The calculation of the weight is related to the curvature of the connection between the points, for example, the weight of the straight connection is set to 1; the weight of the curved connection is the sum of the base weight and the additional weight, where the base weight for right turns is set to 2, and the weight for left turns is set to 2. The base weight is set to 3, and the additional weight is positively related to the curvature of the turning line, that is, the greater the curvature, the greater the additional weight; the lane change weight is 8, and so on. In this way, the target vehicle gets the static path selection weight of the lane.

Optionally, the target vehicle can also determine the static route selection weight according to the length of the lane, and the static route selection weight of the lane can be positively correlated with the length of the lane, that is, the longer the lane is, the higher the static route selection weight (that is, the shortest preferred distance). lane).

Of course, the target vehicle can also determine the static path selection weight of the lane in combination with the type of the lane and the length of the lane. For example, the static path selection weight determined by the type of the lane and the static path selection weight determined by the length of the lane are summed to obtain the lane. The final static path selection weight, etc., are not specifically limited here.

In this way, for each lane, the dynamic routing weight and the static routing weight of the lane are summed to obtain the routing weight of the lane.

In the process of path planning, the target vehicle can determine all lanes between the start and end positions in the target map data according to the start and end positions of the target vehicle, and use the depth-first search algorithm or breadth-first search algorithm to select the weights The multiple lanes with the smallest sum are used as the global path of the target vehicle from the starting position to the ending position, that is, the path planning information.

It should be noted that in the process of driving based on the path planning information, if the target vehicle travels incorrectly due to various reasons, for example, it should turn right according to the path planning information, but the target vehicle does not turn right, but continues to execute, then the target The vehicle can use the current position as the starting position of the target vehicle, and the end position remains unchanged, and re-plan the global path according to the above method to remedy the erroneous driving of the target vehicle and improve the driving reliability.

In the embodiment of the present disclosure, in the path planning process, the congestion degree corresponding to the lane is combined to avoid severely congested lanes in advance, so as to improve the capability of path planning and improve the ride experience of passengers.

Optionally, since the congestion degree of the lane is constantly changing, the path selection weight of the corresponding lane included in each attribute information can periodically change dynamically with the congestion degree of the lane, so that the target vehicle can select the path based on the latest path selection weight. Path planning improves the reliability of path planning.

In one embodiment, based on the embodiment shown in FIG. 2 , referring to FIG. 4 , this embodiment relates to the process of how the target vehicle acquires the target map data. As shown in FIG. 4, step 201 may include step 401 and step 402:

Step 401, the target vehicle acquires congestion information of at least one lane.

The target vehicle can obtain the congestion information of the lane from the terminal or the server, and the target vehicle can also obtain the congestion information of the lane from the roadside sensing device. The congestion information includes lane markings of the lane, congestion degree information, and a congestion position, which may include, for example, a congestion start position and a congestion end position.

Optionally, the roadside perception device can analyze the number, speed, distance and other information of vehicles passing through the surrounding area per unit time through cameras, lidars, etc., and comprehensively analyze the congestion information of the lane. The terminal or the server can obtain the congestion information of each navigation software, and extract the lane marking, the congestion degree information and the congestion position as the congestion information of the lane. In this way, the target vehicle can acquire the congestion information of at least one lane from one or more devices among the terminal, the server, and the roadside perception device.

In step 402, the target vehicle acquires original map data, and generates target map data according to the congestion information and the original map data.

The original map data may be a high-precision map. The original map data can include the precise location and original attributes of traffic elements such as roads, lanes, intersections, traffic lights, original lane boundaries, curbs, etc. The original attributes such as whether the lane is a straight lane or a turning lane, and the original lane boundary type is a dashed line type Also solid line type, road number, lane number, etc. It should be noted that the lane boundary type of each lane in the original map data is the real lane boundary type, that is, the original lane boundary type in the original map data is consistent with the actual lane boundary type of the real lane in the road.

After the target vehicle obtains the original map data, it generates the target map data according to the congestion information and the original map data. In the following, the process of how the target vehicle generates the target map data according to the congestion information and the original map data will be introduced.

Referring to Fig. 5, the target vehicle can perform

steps

501, 502, 503 and 504 shown in Fig. 5 to realize the process of generating target map data according to the congestion information and the original map data:

Step 501 , the target vehicle determines the congested road section in the corresponding lane in the original map data based on the lane mark and the congested location.

For the congestion information of each lane, the target vehicle first determines the corresponding lane and the original attributes of the lane from the original map data based on the lane identification. Solid line type, etc.

Next, the target vehicle determines a congested road segment in the lane based on the congested location.

Step 502, if the congestion degree of the congested road section represented by the congestion degree information is greater than the preset degree threshold, and the lane boundary type of the congested road section in the original map data is a dotted line type, the target vehicle will be based on the original map data. Change the type to solid line type to get the target map data.

Optionally, the congestion level information may be a congestion level, and the target vehicle may detect whether the congestion level is greater than a congestion level threshold. Optionally, the congestion degree information may be a congestion percentage, and the target vehicle may detect whether the congestion percentage is greater than a congestion percentage threshold.

According to the original attribute of the lane, if the target vehicle determines that the type of the lane dividing line of the congested road section is a dashed line type, in order to avoid the target vehicle changing lanes in the congested road section, the target vehicle changes the type of the lane dividing line of the congested road section in the original map data to a solid line Type, and the length of the solid line is consistent with the length of the traffic congestion flow, that is, the starting point of the solid line is the same as the starting point of the congestion, and the end point of the solid line is the same as the ending point of the congestion.

After the target vehicle changes the lane boundary type of the congested road section in the original map data to the solid line type, the modified original map data can be used as the target map data.

In another possible implementation, before the target vehicle changes the lane boundary type of the congested road segment to the solid line type based on the original map data, it can also detect whether the congested road segment includes a non-straight road segment based on the original map data; correspondingly, The step of changing the type of the lane dividing line of the congested road section to the solid line type based on the original map data may be: if the congested road section includes a non-straight road section, the target vehicle changes the type of the lane dividing line of the congested road section to the solid line type based on the original map data type.

The non-straight road section may be a turning section or a U-turn section. Usually, there is only one turning lane or U-turn lane in the road. If the congested road section includes a non-straight road section, it means that the lane where the congested road section is located is the turning lane or the U-turn lane. If the target vehicle is in the turning lane or the U-turn lane, change the lane. Afterwards, it may be unable to return to the original lane due to congestion in the turning lane or the U-turn lane, and the target vehicle cannot turn or turn around, resulting in driving errors. Therefore, the congested road section includes non-straight road sections, and the target vehicle changes the lane boundary type of the congested road section to a solid line type based on the original map data. The problem of congestion in the U-turn lane and the inability to return to the original lane improves driving reliability.

In another possible implementation manner, the target vehicle may perform the following steps A0 and A1 to realize the process of changing the type of the lane boundary of the congested road section to the solid line type based on the original map data, so as to obtain the target map data:

Step A0, the target vehicle changes the lane boundary type of the congested road section in the original map data to the solid line type, and sets the path selection weight of the lane in the original map data according to the congestion degree information.

In step A1, attribute information of the lane is generated according to the lane boundary type of the congested section in the lane and the path selection weight of the lane, and the target map data is obtained.

The original map data can include the precise positions and original attributes of traffic elements such as roads, lanes, intersections, traffic lights, and curbs. The original attributes of the lanes, such as the real lane boundary type of the section in the lane, whether the lane is a straight lane or a turning lane, etc. Wait.

In this way, based on the original map data, the target vehicle changes the real lane boundary type of the congested road section in the original attribute of the lane to a solid line type. For the purpose of avoiding severely congested lanes in advance, the target vehicle may also set the path selection weight of the lane in the original attribute of the lane based on the congestion information.

As mentioned above, the lane's routing weight is determined by the lane's dynamic routing weight and the lane's static routing weight.

For the dynamic route selection weight, the congestion level information can be in the form of congestion level or congestion percentage; taking the congestion level as an example, it is assumed that the higher the congestion level, the more congested the lane is, and each congestion level and each dynamic route selection can be pre-configured in the target vehicle. The mapping relationship between the weights, for example, the dynamic route selection weight corresponding to congestion level 1 is A1, the dynamic route selection weight corresponding to congestion level 2 is A2, and so on, so that the dynamic route selection weight of the lane can be obtained.

For the static routing weight, the static routing weight is related to at least one of the type and length of the lane. The type of lane may be a straight type of lane, such as low weight for straight lanes (ie straight lanes are preferred), high weight for curved lanes, and so on.

After the target vehicle obtains the dynamic path selection weight of the lane and the static path selection weight of the lane, the dynamic path selection weight of the lane and the static path selection weight of the lane are summed to obtain the path selection weight of the lane, and the path selection weight of each lane is added. In the original attribute of the corresponding lane, the attribute information of the corresponding lane is obtained, thereby obtaining the final target map data, and the target map data includes the attribute information of each lane.

Step 503: If the congestion degree of the congested road section represented by the congestion degree information is greater than the preset degree threshold, and the lane boundary type of the congested road section in the original map data is a solid line type, the target vehicle maintains the lane division of the congested road section based on the original map data. The boundary type is unchanged to obtain the target map data.

However, if the congestion degree of the congested road section is greater than the preset degree threshold, but the lane boundary type of the congested road section in the original map data is a solid line type, since the solid line does not allow lane changes in the traffic rules, the target vehicle must also be in the congested road section. It will not change lanes, and there will be no problem that the target vehicle cannot return to the congested road section after changing lanes. Therefore, the target vehicle keeps the lane boundary type of the congested road section unchanged in the original map data, that is, the congested road section in the original map data will not be changed. The type of lane dividing line is not modified.

Further, as described above, the target vehicle may also set the path selection weight of the lane in the original map data based on the congestion information to obtain the final target map data.

Step 504, if the congestion degree of the congested road section represented by the congestion degree information is less than or equal to the preset degree threshold, the target vehicle keeps the lane boundary type of the congested road section unchanged based on the original map data to obtain the target map data.

If the congestion degree of the congested road section represented by the congestion degree information is less than or equal to the preset degree threshold, it indicates that the congested road section is not seriously congested. , regardless of whether the lane boundary type of the congested road section in the original map data is a solid line type or a dashed line type, it will not be modified.

In this way, when the target vehicle performs path planning based on the target map data, it can avoid severely congested lanes in advance according to the congestion degree corresponding to the lane, improve the ability of path planning, improve the riding experience of passengers, and can effectively avoid the target vehicle in the current When the lane is congested, it is changed to another lane, but the current lane cannot be returned to the current lane because the current lane is congested, resulting in an error of the driving path. The embodiment of the present disclosure improves the driving reliability of the target vehicle.

In one embodiment, based on the embodiment shown in FIG. 2 , referring to FIG. 6 , this embodiment relates to a process of how to control the driving of the target vehicle when the type of the target lane boundary is a dashed line type. As shown in FIG. 6 , the vehicle driving control method in this embodiment further includes step 205:

Step 205 , if the type of the target lane boundary line is a dotted line type, the target vehicle controls the target vehicle to change lanes according to a preset local path.

Based on the target map data, the target vehicle determines the target lane boundary line type of the target road section corresponding to the target vehicle in the target lane. The dashed line can change lanes, and the target vehicle controls the target vehicle to change lanes according to the preset local path.

The following is a brief introduction to the process of obtaining the local path:

The target vehicle can sprinkle points on the surrounding lanes and calculate the appropriate connection curve. If the curve is close to the target lane dividing line, the weight of the curve is lower; if the curve deviates from the target lane dividing line, the weight of the curve is higher; if the curve passes through a static obstacle, the weight of the curve is infinite. Then the curve weight is infinite. In this way, the target vehicle selects a set of curves with smaller weights as the candidate curve family through the dynamic programming algorithm. It can be understood that the local curves crossing the solid lane boundaries are not included in the candidate curve family.

The target vehicle performs the optimization calculation in the candidate curve family, avoids the dynamic obstacles, and assigns the speed value and the time value to the path point in the curve, that is, the trajectory is obtained. The target vehicle selects a trajectory with the smallest weight, no collision risk and little difference from the historical trajectory as the preset local path.

In this way, the target vehicle controls the target vehicle to change lanes according to the preset local path. Since the target road section is less or not congested, even if the target vehicle changes lanes, it can switch back to the target lane to ensure that the target vehicle follows the correct lane. path of travel.

In one embodiment, based on the embodiment shown in FIG. 2 , referring to FIG. 7 , this embodiment relates to a process of how the target vehicle detects whether the target vehicle satisfies the lane change condition. As shown in Figure 7, the process may include steps 701 and 702:

Step 701 , the target vehicle obtains the traveling speed of the vehicle in front of the target vehicle, and detects whether the traveling speed is less than a preset speed threshold.

A lidar sensor can be installed in the target vehicle. The lidar sensor periodically emits a laser beam, and when the laser beam hits the vehicle in front, the distance between the target vehicle and the vehicle in front can be obtained.

The target vehicle determines the time interval between the two outwardly emitted laser beams, and obtains the distance difference between the two outwardly emitted laser beams and the vehicle in front, and divides the distance difference by the time interval to obtain the speed of the vehicle in front.

The target vehicle detects whether the travel speed is less than a preset speed threshold.

Step 702, if the traveling speed is less than the preset speed threshold, the target vehicle determines that the target vehicle satisfies the lane changing condition.

If the traveling speed is less than the preset speed threshold, it indicates that the vehicle ahead is traveling at a low speed or is stationary, and the target vehicle determines that the target vehicle satisfies the lane changing condition.

It can be understood that, after the target vehicle determines that the target vehicle meets the lane change condition, if the real lane boundary type of the current road section is determined to be a dotted line type based on the original map data, the target vehicle can change lanes. However, there is a problem: after the target vehicle changes lanes, it may not be able to return to the target lane due to congestion in the target lane; especially in some scenarios that require turning/U-turn, that is, the target lane also includes the target vehicle not driving If the target vehicle can no longer return to the target lane for turning/turning, the driving path of the target vehicle will be wrong, and the driving reliability of the vehicle will be low.

In the disclosed embodiment, in order to avoid the above problems, after the target vehicle determines that the target vehicle satisfies the lane change condition, it does not immediately change the lane, but determines the target lane boundary of the target road section corresponding to the target vehicle in the target lane based on the target map data. Type, if the target lane boundary type is a solid line type, the target vehicle controls the target vehicle to drive along the target lane to avoid the situation that the target vehicle cannot return to the target lane after changing lanes due to congestion in the target lane, thereby avoiding congestion in the target lane. , the target vehicle cannot return to the target lane after changing lanes.

It should be understood that although the steps in the above flow charts are displayed in sequence according to the arrows, these steps are not necessarily executed in the sequence indicated by the arrows. Unless explicitly stated herein, the execution of these steps is not strictly limited to the order, and these steps may be performed in other orders. Moreover, at least a part of the steps in the above flow chart may include multiple steps or multiple stages. These steps or stages are not necessarily executed at the same time, but may be executed at different times. The execution sequence of these steps or stages It is also not necessarily performed sequentially, but may be performed alternately or alternately with other steps or at least a portion of a step or phase within the other steps.

In one embodiment, as shown in FIG. 8, a vehicle driving control device is provided, and the device includes:

The obtaining module 801 is configured to obtain target map data, where the target map data includes attribute information of each lane, and each attribute information includes the lane boundary type of at least one section in the corresponding lane, wherein the congestion degree in the section In the case of being greater than the preset degree threshold, the type of the lane dividing line is a solid line type;

The first determination module 802 is configured to determine, based on the target map data, whether the target vehicle is in the target lane with the target vehicle if it is detected that the target vehicle meets the lane change condition when the target vehicle is driving in the target lane based on the path planning information. the target lane boundary type of the target road section corresponding to the target vehicle;

The first control module 803 is configured to control the target vehicle to drive along the target lane if the type of the target lane boundary line is a solid line type.

Optionally, each of the attribute information further includes a path selection weight of the corresponding lane, and the path selection weight is related to the congestion degree corresponding to the lane, and the device further includes:

The planning module is configured to perform path planning on the target vehicle according to the starting point position of the target vehicle, the end position of the target vehicle, and the path selection weight of each lane to obtain the path planning information.

Optionally, the path selection weight is determined by a dynamic path selection weight of the lane and a static path selection weight of the lane, wherein the dynamic path selection weight is related to the congestion degree corresponding to the lane, and the static path selection weight is related to the congestion degree corresponding to the lane. The routing weight is related to at least one of the type and length of the lane.

Optionally, the obtaining module 801 includes:

a first acquiring unit, configured to acquire congestion information of at least one of the lanes, where the congestion information includes lane markings, congestion degree information, and congestion locations of the lane;

The second acquiring unit is configured to acquire original map data, and generate the target map data according to the congestion information and the original map data, where the lane boundary type of the road sections of each lane in the original map data is the real lane division Boundary type.

Optionally, the second obtaining unit is specifically configured to determine, in the original map data, a corresponding congested road section in the lane based on the lane mark and the congested position; If the congestion degree of the congested road section is greater than the preset degree threshold, and the lane boundary type of the congested road section in the original map data is a dotted line type, then based on the original map data, the lane boundary line of the congested road section is divided Change the type to solid line type to get the target map data.

Optionally, the second obtaining unit is specifically configured to change the type of the lane dividing line of the congested road section in the original map data to a solid line type, and set in the original map data according to the congestion degree information. The path selection weight of the lane; the attribute information of the lane is generated according to the lane boundary type of the congested road section in the lane and the path selection weight of the lane, and the target map data is obtained.

Optionally, the obtaining module 801 further includes:

a detection unit, configured to detect whether the congested road section includes a non-straight road section based on the original map data;

The second obtaining unit is specifically configured to, if the congested road segment includes the non-straight road segment, change the type of the lane boundary of the congested road segment to a solid line type based on the original map data.

Optionally, the second obtaining unit is specifically further configured to, if the congestion degree of the congested road section represented by the congestion degree information is greater than the preset degree threshold, and the lane of the congested road section in the original map data If the boundary line type is a solid line type, the lane boundary type of the congested road section is kept unchanged based on the original map data, so as to obtain the target map data.

Optionally, the second acquiring unit is specifically further configured to maintain the congestion based on the original map data if the congestion level of the congested road section represented by the congestion level information is less than or equal to the preset level threshold. The lane boundary type of the road segment remains unchanged, so as to obtain the target map data.

Optionally, the device further includes:

The second control module is configured to control the target vehicle to change lanes according to a preset local path if the type of the target lane boundary line is a dotted line type.

Optionally, the device further includes:

a detection module, configured to obtain the driving speed of the vehicle in front of the target vehicle, and detect whether the driving speed is less than a preset speed threshold;

A second determining module, configured to determine that the target vehicle satisfies the lane changing condition if the traveling speed is less than the preset speed threshold.

Optionally, the first determining module 802 includes:

a first determining unit, configured to determine a target lane mark of the target lane, and determine target attribute information corresponding to the target lane in the target map data according to the target lane mark, where the target attribute information is the attribute information of the target lane in the target map data;

The second determining unit is configured to acquire the vehicle position of the target vehicle, and determine the target lane boundary type of the target road segment according to the vehicle position and the target attribute information.

For the specific limitation of the vehicle driving control device, reference may be made to the above limitation on the vehicle driving control method, which will not be repeated here. Each module in the above-mentioned vehicle driving control device may be implemented in whole or in part by software, hardware and combinations thereof. The above modules can be embedded in or independent of the processor in the target vehicle in the form of hardware, and can also be stored in the memory in the target vehicle in the form of software, so that the processor can call and execute the corresponding operations of the above modules.

FIG. 9 is a block diagram of a target vehicle 1300 according to an exemplary embodiment. For example, the target vehicle 1300 may be a motor vehicle or a non-motor vehicle, or the like.

9, the target vehicle 1300 may include one or more of the following components: a processing component 1302, a memory 1304, a power supply component 1306, an input/output (I/O) interface 1308, a sensor component 1310, and a communication component 1312. The memory stores computer programs or instructions running on the processor.

The processing component 1302 generally controls the overall operation of the target vehicle 1300 . The processing component 1302 can include one or more processors 1314 to execute instructions to perform all or some of the steps of the methods described above. Additionally, processing component 1302 may include one or more modules that facilitate interaction between processing component 1302 and other components.

The memory 1304 is configured to store various types of data to support operation at the target vehicle 1300 . Examples of such data include instructions for any application or method operating on the target vehicle 1300, and the like. Memory 1304 may be implemented by any type of volatile or nonvolatile storage device or combination thereof, such as static random access memory (SRAM), electrically erasable programmable read only memory (EEPROM), erasable Programmable Read Only Memory (EPROM), Programmable Read Only Memory (PROM), Read Only Memory (ROM), Magnetic Memory, Flash Memory, Magnetic or Optical Disk.

Power supply assembly 1306 provides power to various components of target vehicle 1300 . The power components 1306 may include a power management system, one or more power sources, and other components associated with generating, managing, and distributing power to the target vehicle 1300 .

The I/O interface 1308 provides an interface between the processing component 1302 and a peripheral interface module, which may be a keyboard, a click wheel, a button, or the like. These buttons may include, but are not limited to: home button, volume buttons, start button, and lock button.

Sensor assembly 1310 includes one or more sensors for providing various aspects of condition assessment for target vehicle 1300 . For example, the sensor assembly 1310 can detect the open/closed state of the target vehicle 1300, the relative positioning of the components, such as the display and keypad of the target vehicle 1300, the sensor assembly 1310 can also detect the target vehicle 1300 or a target vehicle 1300 The position of the components changes, the presence or absence of user contact with the target vehicle 1300 , the orientation or acceleration/deceleration of the target vehicle 1300 and the temperature of the target vehicle 1300 changes. Sensor assembly 1310 may include a proximity sensor configured to detect the presence of nearby objects in the absence of any physical contact. Sensor assembly 1310 may also include a light sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, the sensor assembly 1310 may also include an acceleration sensor, a gyroscope sensor, a lidar sensor, a magnetic sensor, a pressure sensor, or a temperature sensor.

The communication component 1312 is configured to facilitate wired or wireless communication between the target vehicle 1300 and other devices. The target vehicle 1300 may access a wireless network based on a communication standard, such as WiFi, 2G, 3G, 4G, 5G, or a combination thereof. In one exemplary embodiment, the communication component 1312 receives broadcast signals or broadcast related information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communication component 1312 also includes a near field communication (NFC) module to facilitate short-range communication. For example, the NFC module may be implemented based on radio frequency identification (RFID) technology, infrared data association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology and other technologies.

In an exemplary embodiment, target vehicle 1300 may be powered by one or more application specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable A programmed gate array (FPGA), a controller, a microcontroller, a microprocessor or other electronic components are implemented for implementing the above-mentioned vehicle driving control method.

FIG. 10 is a block diagram of a server 1400 according to an exemplary embodiment. 10, server 1400 includes processing component 1420, which further includes one or more processors, and a memory resource, represented by memory 1422, for storing instructions or computer programs, such as application programs, executable by processing component 1420. An application program stored in memory 1422 may include one or more modules, each corresponding to a set of instructions. Additionally, the processing component 1420 is configured to execute instructions to perform the vehicle travel control method described above.

The server 1400 may also include a power component 1424 configured to perform power management of the device 1400, a wired or wireless network interface 1426 configured to connect the device 1400 to a network, and an input output (I/O) interface 1428. Server 1400 may operate based on an operating system stored in memory 1422, such as Windows 14 14erverTM, Mac O14 XTM, UnixTM, LinuxTM, FreeB14DTM or the like.

In an exemplary embodiment, a non-transitory computer-readable storage medium including instructions, such as a memory 1304 including instructions, executable by the processor 1314 of the target vehicle 1300 to perform the method described above is also provided. For example, the non-transitory computer-readable storage medium may be ROM, random access memory (RAM), CD-ROM, magnetic tape, floppy disk, optical data storage device, and the like.

In an exemplary embodiment, a storage medium including instructions, such as a memory 1422 including instructions, is also provided, and the instructions are executable by the processor of the server 1400 to accomplish the above method. The storage medium may be a non-transitory computer-readable storage medium such as ROM, random access memory (RAM), CD-ROM, magnetic tape, floppy disk, optical data storage device, and the like.

In an exemplary embodiment, there is also provided a computer program product which, when executed by a processor, can implement the above method. The computer program product includes one or more computer instructions. When these computer instructions are loaded and executed on a computer, some or all of the above methods can be implemented in whole or in part according to the processes or functions described in the embodiments of the present disclosure.

Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be implemented by instructing relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage In the medium, when the computer program is executed, it may include the processes of the above-mentioned method embodiments. Wherein, any reference to memory, storage, database, or other media used in the various embodiments provided by the embodiments of the present disclosure may include at least one of non-volatile and volatile memory. Non-volatile memory may include read-only memory (Read-Only Memory, ROM), magnetic tape, floppy disk, flash memory, or optical memory, and the like. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, the RAM may be in various forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM).

The technical features of the above embodiments can be combined arbitrarily. In order to make the description simple, all possible combinations of the technical features in the above embodiments are not described. However, as long as there is no contradiction in the combination of these technical features It is considered to be the range described in this specification.

The above-mentioned embodiments only represent several implementations of the embodiments of the present disclosure, and the descriptions thereof are relatively specific and detailed, but should not be construed as a limitation on the scope of the invention patent. It should be noted that for those skilled in the art, without departing from the concept of the embodiments of the present disclosure, several modifications and improvements can be made, which all belong to the protection scope of the embodiments of the present disclosure. Therefore, the protection scope of the patent of the embodiments of the present disclosure should be subject to the appended claims.

Claims

A vehicle driving control method, characterized in that the method comprises:

Acquiring target map data, the target map data includes attribute information of each lane, and each attribute information includes a lane boundary type of at least one section in the corresponding lane, wherein the congestion degree in the section is greater than a preset degree threshold. In this case, the type of the lane dividing line is a solid line type;

In the case where the target vehicle is driving in the target lane based on the path planning information, if it is detected that the target vehicle satisfies the lane change condition, the target road section corresponding to the target vehicle in the target lane is determined based on the target map data The type of target lane dividing line;

If the type of the target lane boundary line is a solid line type, the target vehicle is controlled to drive along the target lane.
The method according to claim 1, wherein each of the attribute information further includes a path selection weight of the corresponding lane, and the path selection weight is related to the congestion degree corresponding to the lane, and the method further comprises:

The path planning information is obtained by performing path planning on the target vehicle according to the starting point position of the target vehicle, the end position of the target vehicle, and the path selection weight of each lane.
The method according to claim 2, wherein the path selection weight is determined by a dynamic path selection weight of the lane and a static path selection weight of the lane, wherein the dynamic path selection weight is related to the lane. Corresponding congestion levels are related, and the static routing weight is related to at least one of the type and length of the lane.
The method according to claim 1, wherein the acquiring target map data comprises:

acquiring congestion information of at least one of the lanes, where the congestion information includes lane markings, congestion level information, and congestion locations of the lane;

Obtain original map data, and generate the target map data according to the congestion information and the original map data, where the lane boundary type of each lane in the original map data is the real lane boundary type.
The method according to claim 4, wherein the generating the target map data according to the congestion information and the original map data comprises:

determining a corresponding congested road segment in the lane in the original map data based on the lane marking and the congested location;

If the congestion degree of the congested road section represented by the congestion degree information is greater than the preset degree threshold, and the lane boundary type of the congested road section in the original map data is a dotted line type, then based on the original map data Change the type of the lane dividing line of the congested road section to the type of solid line, so as to obtain the target map data.
The method according to claim 5, wherein the changing the lane boundary type of the congested road section to a solid line type based on the original map data to obtain the target map data, comprising:

changing the lane boundary type of the congested road section in the original map data to a solid line type, and setting the path selection weight of the lane in the original map data according to the congestion degree information;

The attribute information of the lane is generated according to the lane boundary type of the congested road section in the lane and the path selection weight of the lane to obtain the target map data.
The method according to claim 5, characterized in that, before changing the type of the lane dividing line of the congested road section to the type of solid line based on the original map data, the method further comprises:

based on the original map data, detecting whether the congested road section includes a non-straight road section;

Correspondingly, the changing the lane boundary type of the congested road section to the solid line type based on the original map data includes:

If the congested road section includes the non-straight road section, the lane boundary type of the congested road section is changed to a solid line type based on the original map data.
The method according to claim 5, wherein the method further comprises:

If the congestion degree of the congested road section represented by the congestion degree information is greater than the preset degree threshold, and the lane boundary type of the congested road section in the original map data is a solid line type, then based on the original map The data keeps the lane boundary type of the congested road section unchanged, so as to obtain the target map data.
The method according to claim 5, wherein the method further comprises:

If the congestion degree of the congested road section represented by the congestion degree information is less than or equal to the preset degree threshold, keep the lane boundary type of the congested road section unchanged based on the original map data, so as to obtain the target map data.
The method according to claim 1, wherein the method further comprises:

If the type of the target lane boundary line is a dashed line type, the target vehicle is controlled to change lanes according to a preset local path.
The method according to claim 1, wherein, before it is detected that the target vehicle satisfies the lane change condition, the method further comprises:

acquiring the driving speed of the vehicle in front of the target vehicle, and detecting whether the driving speed is less than a preset speed threshold;

If the traveling speed is less than the preset speed threshold, it is determined that the target vehicle satisfies the lane changing condition.
The method according to claim 1, wherein the determining, based on the target map data, the target lane boundary type of the target road section corresponding to the target vehicle in the target lane comprises:

Determine the target lane mark of the target lane, and determine the target attribute information corresponding to the target lane in the target map data according to the target lane mark, and the target attribute information is the target in the target map data. attribute information of the lane;

The vehicle position of the target vehicle is acquired, and the target lane boundary type of the target road segment is determined according to the vehicle position and the target attribute information.
A vehicle driving control device, characterized in that the device comprises:

an acquisition module, configured to acquire target map data, where the target map data includes attribute information of each lane, and each attribute information includes the lane boundary type of at least one section in the corresponding lane, wherein the congestion degree in the section is greater than In the case of a preset degree threshold, the type of the lane dividing line is a solid line type;

The first determination module is configured to determine, based on the target map data, whether the target vehicle is in the target lane with the target vehicle if it is detected that the target vehicle meets the lane change condition when the target vehicle is driving in the target lane based on the path planning information. Describe the target lane boundary type of the target road section corresponding to the target vehicle;

A first control module, configured to control the target vehicle to drive along the target lane if the type of the target lane boundary line is a solid line type.
The device according to claim 13, wherein each of the attribute information further comprises a path selection weight of the corresponding lane, and the path selection weight is related to the congestion degree corresponding to the lane, and the device further comprises:

The planning module is configured to perform path planning on the target vehicle according to the starting point position of the target vehicle, the end position of the target vehicle, and the path selection weight of each lane to obtain the path planning information.
The apparatus of claim 14, wherein the path selection weight is determined by a dynamic path selection weight of the lane and a static path selection weight of the lane, wherein the dynamic path selection weight is related to the lane Corresponding congestion levels are related, and the static routing weight is related to at least one of the type and length of the lane.
The device according to claim 13, wherein the acquiring module comprises:

a first acquiring unit, configured to acquire congestion information of at least one of the lanes, where the congestion information includes lane markings, congestion degree information, and congestion locations of the lane;

The second acquiring unit is configured to acquire original map data, and generate the target map data according to the congestion information and the original map data, where the lane boundary type of the road sections of each lane in the original map data is the real lane division Boundary type.
The apparatus according to claim 16, wherein the second acquiring unit is specifically configured to determine, in the original map data, a corresponding congested road section in the lane based on the lane mark and the congested location; If the congestion degree of the congested road section represented by the congestion degree information is greater than the preset degree threshold, and the lane boundary type of the congested road section in the original map data is a dotted line type, then based on the original map data Change the type of the lane dividing line of the congested road section to the type of solid line, so as to obtain the target map data.
The device according to claim 17, wherein the second acquiring unit is specifically configured to change the type of the lane boundary line of the congested road section in the original map data to a solid line type, and determine the type according to the congestion degree. information to set the path selection weight of the lane in the original map data; generate attribute information of the lane according to the lane boundary type of the congested road section in the lane and the path selection weight of the lane, Obtain the target map data.
The device according to claim 17, wherein the acquiring module further comprises:

a detection unit, configured to detect whether the congested road section includes a non-straight road section based on the original map data;

The second obtaining unit is specifically configured to, if the congested road segment includes the non-straight road segment, change the type of the lane boundary of the congested road segment to a solid line type based on the original map data.
The device according to claim 17, wherein the second obtaining unit is further configured to be further configured to, if the congestion degree of the congested road section represented by the congestion degree information is greater than the preset degree threshold, and the original If the lane boundary type of the congested road section in the map data is a solid line type, then based on the original map data, keep the lane boundary type of the congested road section unchanged to obtain the target map data.
The device according to claim 17, wherein the second obtaining unit is further configured to, if the congestion degree of the congested road section represented by the congestion degree information is less than or equal to the preset degree threshold, based on The original map data keeps the lane boundary type of the congested road section unchanged, so as to obtain the target map data.
The apparatus of claim 13, wherein the apparatus further comprises:

The second control module is configured to control the target vehicle to change lanes according to a preset local path if the type of the target lane boundary line is a dotted line type.
The apparatus of claim 13, wherein the apparatus further comprises:

a detection module, configured to acquire the driving speed of the vehicle in front of the target vehicle, and detect whether the driving speed is less than a preset speed threshold;

A second determining module, configured to determine that the target vehicle satisfies the lane changing condition if the traveling speed is less than the preset speed threshold.
The device according to claim 13, wherein the first determining module comprises:

a first determining unit, configured to determine a target lane mark of the target lane, and determine target attribute information corresponding to the target lane in the target map data according to the target lane mark, where the target attribute information is the attribute information of the target lane in the target map data;

The second determining unit is configured to acquire the vehicle position of the target vehicle, and determine the target lane boundary type of the target road segment according to the vehicle position and the target attribute information.
A vehicle, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, when the processor executes the computer program, the implementation of claims 1 to 12 The steps of any one of the methods.
A server, comprising a memory, a processor, and a computer program stored on the memory and running on the processor, characterized in that, when the processor executes the computer program, the implementation of claims 1 to 12 The steps of any one of the methods.
A storage medium on which a computer program is stored, characterized in that, when the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 12 are implemented.
A computer program product, comprising a computer program, characterized in that, when the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 12 are implemented.