Method and device for generating traffic light information

Abstract

A method and apparatus for generating traffic light information, the method comprising: acquiring a traffic flow data set, the traffic flow data set comprising data of a plurality of vehicle driving paths in a first road, the first road communicating with at least one road via a first intersection, the first road comprising a plurality of lanes, the traffic flow data set comprises a first set of data associated with a first lane in the multiple lanes; obtaining perception information, wherein the perception information indicates the states of a plurality of traffic lights at the first intersection in different time periods; and according to the first group of data and the perception information, traffic light information is generated, and the traffic light information indicates that the first lane is associated with a first traffic light in the plurality of traffic lights. The scheme can be applied to the field of intelligent driving of intelligent vehicles such as electric vehicles and new energy vehicles, and the traffic light information indicating the association relationship between the lane and the traffic light at the intersection can be generated to assist the vehicle to pass through the intersection, so that the passing efficiency of the vehicle at the intersection is improved, and the probability of traffic accidents of the vehicle at the intersection is reduced.

Description

Technical Field

[0001] This application relates to the field of intelligent driving, and more specifically, to a method and apparatus for generating traffic light information. Background Technology

[0002] With the rapid development of the automotive industry, many driver assistance and autonomous driving technologies have emerged, which can reduce driving stress and improve safety and traffic efficiency. Currently, most autonomous driving technologies rely on high-precision maps for navigation. However, high-precision maps have drawbacks such as high collection and production costs, long processing times, insufficient coverage, and difficulty in ensuring data freshness, making it difficult to promote autonomous driving technologies that rely on high-precision maps nationwide or globally. If navigation is not based on high-precision maps and relies solely on environmental information perceived by vehicle sensors, vehicles may fail to understand or misinterpret the information released by traffic lights at intersections with complex traffic lights, leading to difficulties in passing through intersections and potentially causing traffic accidents. Summary of the Invention

[0003] This application provides a method and apparatus for generating traffic light information, which can generate traffic light information indicating the relationship between traffic lights at lanes and intersections, so as to assist vehicles in passing through intersections, improve the traffic efficiency of vehicles at intersections, and reduce the probability of traffic accidents at intersections.

[0004] In one aspect, a method for generating traffic light information is provided, which can be executed by a cloud server, for example, by a computing platform of the cloud server, or by a chip or circuit used in the cloud server.

[0005] The method includes: acquiring a traffic flow data set, which includes data on the travel paths of multiple vehicles on a first road, the first road connecting to at least one road via a first intersection, the first road including multiple lanes, and the traffic flow data set including a first set of data associated with a first lane among the multiple lanes; acquiring perception information, which indicates the status of multiple traffic lights at the first intersection at different time periods; and generating traffic light information based on the first set of data and the perception information, the traffic light information indicating that the first lane is associated with a first traffic light among the multiple traffic lights.

[0006] In some implementations, the sensing information can be associated with traffic flow data sets, meaning that sensing information is collected simultaneously with the generation of traffic flow data by vehicles. The states of multiple traffic lights at different time periods can include: the color of the traffic light, and / or the duration for which the traffic light remains in a certain color.

[0007] In some implementations, associating the first set of data with the first lane can be understood as: multiple traffic flow points in each traffic flow data in the first set of data are located in the first lane; or, the vehicle travel path indicated by each traffic flow data is traveling from the first lane to the first intersection.

[0008] In the above technical solution, the relationship between traffic lights and lanes at intersections is determined based on traffic flow data and associated perception information. This approach does not rely on high-precision maps and places lower demands on the vehicle's perception capabilities (such as perception range) and computing power. Even when there are multiple traffic lights of the same type at an intersection that control different lanes, it can provide vehicles with accurate information on the relationship between lanes and traffic lights. This reduces the likelihood of vehicles following incorrect traffic lights and stopping at intersections, thus improving traffic efficiency and driving safety at intersections.

[0009] In conjunction with the first aspect, in some implementations of the first aspect, traffic light information is generated based on the first set of data and perception information, including: generating traffic light information based on the motion status of multiple vehicles in a first time period indicated by the first set of data and the color of each traffic light in the multiple traffic lights in the first time period indicated by the perception information; wherein each of the multiple vehicles is a vehicle traveling towards the first intersection via the first lane.

[0010] In conjunction with the first aspect, in certain implementations of the first aspect, generating traffic light information includes: when the first traffic light is a first color during a first time period, and the remaining traffic lights (excluding the first traffic light) are all a second color during the first time period, and when the average acceleration of multiple vehicles during the first time period is less than or equal to an acceleration threshold, and / or the average speed of multiple vehicles during the first time period is less than or equal to a speed threshold, generating traffic light information indicating a correlation between the first lane and the first traffic light; wherein the first color indicates permission to pass, and the second color indicates prohibition to pass.

[0011] In the above technical solution, the relationship between traffic lights and lanes is determined based on the changes in vehicle speed and / or acceleration. This method has a low dependence on the precise location of the intersection boundary. In other words, even when the intersection boundary cannot be precisely determined (e.g., there is a certain deviation between the determined intersection boundary and the actual boundary), traffic light information can still be generated. This helps to reduce processing complexity and improves the reliability and accuracy of the generated traffic light information.

[0012] In conjunction with the first aspect, in some implementations of the first aspect, the permissible driving direction indicated by each of the multiple traffic lights is the same as the permissible driving direction of the first lane at the first intersection; obtaining perception information includes: obtaining first perception information associated with the first lane based on the permissible driving direction of the first lane at the first intersection, the perception information including the first perception information.

[0013] In the above technical solution, when the traffic light indicates the driving direction, the perceived information is filtered according to the driving direction indicated by the traffic light and the driving direction of the lane at the intersection, which helps to reduce the data processing complexity in the process of generating traffic light information.

[0014] In conjunction with the first aspect, in some implementations of the first aspect, multiple traffic lights also include a second traffic light, and multiple lanes also include a second lane; the method further includes: when the drivable direction indicated by the second traffic light is the same as the drivable direction of the second lane at the first intersection, and the drivable directions indicated by the remaining traffic lights other than the second traffic light among the multiple traffic lights are all different from the drivable direction of the second lane at the first intersection, generating traffic light information indicating that the second lane and the second traffic light are associated.

[0015] In the above technical solution, the traffic light indicates the driving direction, and the driving direction indicated by the traffic light corresponds one-to-one with the driving direction of the lane at the intersection. This uniquely determines the relationship between the traffic light and the lane, which helps to reduce the data processing complexity in the process of generating traffic light information.

[0016] In conjunction with the first aspect, in some implementations of the first aspect, the method further includes: acquiring map information indicating the location of at least one intersection, the at least one intersection including a first intersection; acquiring perception information, including: determining the location of the first intersection based on the map information and a traffic flow data set; and acquiring perception information based on the location of the first intersection.

[0017] In the above technical solution, the location of the first intersection is determined based on map information and the perception information associated with the first intersection is obtained. When there are changes in the real scene (such as changes in the lane indicated by the traffic light information), it helps to update the traffic light information in a timely manner and ensure the effectiveness of the traffic light information.

[0018] In conjunction with the first aspect, in some implementations of the first aspect, the first lane is associated with the first traffic light among multiple traffic lights, including: the first traffic light is used to regulate the traffic flow of vehicles in the first lane at the first intersection.

[0019] Secondly, an apparatus for generating traffic light information is provided. The apparatus includes an acquisition unit and a processing unit. The acquisition unit is configured to: acquire a traffic flow data set, which includes data on the travel paths of multiple vehicles on a first road. The first road connects to at least one road via a first intersection. The first road includes multiple lanes, and the traffic flow data set includes a first set of data associated with a first lane among the multiple lanes. The acquisition unit is further configured to: acquire perception information, which indicates the status of multiple traffic lights at the first intersection at different time periods. The processing unit is configured to: generate traffic light information based on the first set of data and the perception information, whereby the traffic light information indicates that a first lane is associated with a first traffic light among the multiple traffic lights.

[0020] In conjunction with the second aspect, in some implementations of the second aspect, the processing unit is used to: generate traffic light information based on the motion status of multiple vehicles within a first time period indicated by the first set of data, and the color of each traffic light among multiple traffic lights within the first time period indicated by the perception information; wherein each of the multiple vehicles is a vehicle traveling towards the first intersection via the first lane.

[0021] In conjunction with the second aspect, in some implementations of the second aspect, the processing unit is configured to: generate traffic light information indicating a correlation between the first lane and the first traffic light when the first traffic light is a first color during a first time period, and when the remaining traffic lights (excluding the first traffic light) are all a second color during the first time period, and when the average acceleration of multiple vehicles during the first time period is less than or equal to an acceleration threshold, and / or the average speed of multiple vehicles during the first time period is less than or equal to a speed threshold; wherein the first color indicates permission to pass, and the second color indicates prohibition to pass.

[0022] In conjunction with the second aspect, in some implementations of the second aspect, the permissible driving direction indicated by each of the multiple traffic lights is the same as the permissible driving direction of the first lane at the first intersection; the acquisition unit is used to: acquire first perception information associated with the first lane based on the permissible driving direction of the first lane at the first intersection, the perception information including the first perception information.

[0023] In conjunction with the second aspect, in some implementations of the second aspect, multiple traffic lights also include a second traffic light, and multiple lanes also include a second lane; the processing unit is further configured to: generate traffic light information indicating a relationship between the second lane and the second traffic light when the permissible direction indicated by the second traffic light is the same as the permissible direction of the second lane at the first intersection, and the permissible directions indicated by the remaining traffic lights other than the second traffic light among the multiple traffic lights are all different from the permissible direction of the second lane at the first intersection.

[0024] In conjunction with the second aspect, in some implementations of the second aspect, the acquisition unit is further configured to: acquire map information indicating the location of at least one intersection, the at least one intersection including a first intersection; determine the location of the first intersection based on the map information and a traffic flow data set; and acquire perception information based on the location of the first intersection.

[0025] In conjunction with the second aspect, in some implementations of the second aspect, the first lane is associated with the first traffic light among multiple traffic lights, including: the first traffic light is used to regulate the traffic flow of vehicles in the first lane at the first intersection.

[0026] Thirdly, an apparatus for generating traffic light information is provided, the apparatus comprising: a processor for executing a computer program stored in the memory, such that the apparatus performs the method in any possible implementation of the first aspect described above.

[0027] In conjunction with the third aspect, in some implementations of the third aspect, the device also includes a memory.

[0028] Fourthly, a computer program product is provided, comprising: computer program code, which, when executed on a computer or processor, causes the computer or processor to perform the method in any possible implementation of the first aspect.

[0029] It should be noted that the above computer program code can be stored in whole or in part on a storage medium, which can be packaged together with the processor or packaged separately from the processor.

[0030] Fifthly, a computer-readable storage medium is provided, the computer-readable medium storing instructions that, when executed by a processor, cause the processor to implement the method in any possible implementation of the first aspect.

[0031] In a sixth aspect, a chip is provided that includes circuitry for performing the method in any of the possible implementations of the first aspect described above.

[0032] In a seventh aspect, a server is provided, the server including means as in any possible implementation of the second to third aspects, or the server including computer-readable storage as in any possible implementation of the fifth aspect, or the server including a chip as in any possible implementation of the sixth aspect, or the server loaded with computer program code as in any possible implementation of the fourth aspect.

[0033] Eighthly, a vehicle is provided that is used to acquire traffic light information involved in any of the implementations of the first to seventh aspects, and then control the vehicle to pass through the relevant intersection according to the traffic light information and the vehicle's location.

[0034] In conjunction with aspect eight, in some implementations of aspect eight, the vehicle is used in a broad sense, such as transportation vehicles (e.g., commercial vehicles, passenger cars, motorcycles, flying cars, trains, etc.), industrial vehicles (e.g., forklifts, trailers, tractors, etc.), engineering vehicles (e.g., excavators, bulldozers, cranes, etc.), agricultural equipment (e.g., lawnmowers, harvesters, etc.), amusement equipment, toy vehicles, etc. In practical implementation, the vehicle can also be other intelligent driving equipment such as road vehicles, water vehicles, air vehicles, industrial equipment, agricultural equipment, or entertainment equipment.

[0035] For the beneficial effects not described in detail in aspects two through eight, please refer to the description in aspect one, which will not be repeated here. Attached Figure Description

[0036] Figure 1 This is a schematic diagram of a system for generating traffic light information provided in an embodiment of this application;

[0037] Figure 2 This is a schematic block diagram of the device for generating traffic light information provided in the embodiments of this application;

[0038] Figure 3 This is a schematic flowchart of a method for generating traffic light information provided in an embodiment of this application;

[0039] Figure 4 This is a schematic diagram illustrating an application scenario of the solution provided in the embodiments of this application;

[0040] Figure 5 This is yet another schematic diagram illustrating an application scenario of the solution provided in the embodiments of this application;

[0041] Figure 6 This is another schematic diagram illustrating the application scenario of the solution provided in the embodiments of this application;

[0042] Figure 7 This is another schematic flowchart of the method for generating traffic light information provided in the embodiments of this application;

[0043] Figure 8 This is another schematic block diagram of the device for generating traffic light information provided in the embodiments of this application;

[0044] Figure 9 This is another schematic block diagram of the device for generating traffic light information provided in the embodiments of this application. Detailed Implementation

[0045] To facilitate understanding of the technical solutions of this application, the technical terms involved in this application are introduced below.

[0046] 1. Vectorized map: A map composed of vector data representing the location and shape of geographic entities. Vector data can include at least one of points, lines, and polygons.

[0047] 2. Map vector elements: Geographic entities whose location or shape is identified using vector data, including road vectors, lane vectors, intersection vectors, etc.

[0048] 3. Traffic Flow Data: Data collected by vehicles or roadside units (RSUs) that includes the travel paths of at least one vehicle. When traffic flow data is collected by vehicles, the travel path of at least one vehicle includes the travel path of at least one of its own vehicles and / or the travel path of at least one other vehicle. Traffic flow data consists of a traffic flow identifier (ID) and traffic flow point information. The traffic flow ID uniquely identifies a set of traffic flow data, and the traffic flow point information contains information about several traffic flow points, each indicating the coordinates of a point in the travel path. In some implementations, the information for each traffic flow point also indicates a timestamp of a point in the travel path, which indicates the time when a vehicle arrived at that point.

[0049] As mentioned above, when a vehicle is in autonomous driving mode, without relying on high-precision maps and in situations with complex traffic lights at intersections, the vehicle may fail to understand or misinterpret the information released by the traffic lights. This could lead to the vehicle being unable to pass through the intersection smoothly, or even causing a traffic accident. For example, some intersections may have multiple traffic lights of the same type, but each controlling different lanes. In this case, the information collected by the vehicle's perception system may not be able to determine which traffic light's instruction the vehicle is currently in, causing the vehicle to stop at the intersection. Alternatively, the vehicle may mistakenly follow the instructions of other traffic lights, proceeding when it should not, affecting traffic flow and even causing a traffic accident.

[0050] In view of this, embodiments of this application provide a scheme for generating traffic light information. This scheme generates traffic light information based on traffic flow data and associated sensory information. The traffic light information indicates the relationship between traffic lights and lanes at each intersection. Furthermore, vehicles can plan their travel trajectory through the intersection based on this relationship, their lane location, and the traffic light status information perceived by the vehicle. This helps improve traffic efficiency when vehicles pass through intersections with complex traffic lights, reduces the probability of traffic congestion, reduces the probability of traffic accidents at intersections, and contributes to improved driving safety.

[0051] The technical solutions in the embodiments of this application will now be described with reference to the accompanying drawings.

[0052] Figure 1 This is a schematic diagram of the system architecture for generating map information provided in an embodiment of this application. The system includes a vehicle 100, or may further include a server 200. Figure 1 As shown, vehicle 100 may include a perception system 120, a communication system 130, and a computing platform 150. The perception system 120 may include several sensors for sensing information about the environment surrounding vehicle 100. For example, the perception system 120 may include a positioning system, which can be a global navigation satellite system (GNSS), such as GPS or BeiDou. Alternatively, the perception system 120 may also include one or more of the following: an inertial measurement unit (IMU), lidar, millimeter-wave radar, ultrasonic radar, and a camera device.

[0053] The communication system 130 is used for information exchange between vehicle 100 and server 200, other vehicles, and roadside equipment. For example, when vehicle 100 is traveling on the current road, it can receive at least one of the following through the communication system 130: traffic flow data of the current road collected by other vehicles, traffic flow data collected by roadside equipment of the current road, and historical traffic flow data of the current road stored by server 200. Alternatively, vehicle 100 can also report its collected traffic flow data to server 200 or send it to other vehicles or roadside equipment through the communication system. Exemplarily, the communication system 130 can communicate with server 200, other vehicles, roadside equipment, etc., based on a vehicle-to-everything (V2X) network, which includes, but is not limited to, vehicle-to-vehicle (V2V) communication networks, vehicle-to-infrastructure (V2I) communication networks, and vehicle-to-network (V2N) communication networks.

[0054] Some or all of the functions of vehicle 100 can be controlled by computing platform 150. Computing platform 150 may include processors 151 to 15n. A processor is a circuit with signal processing capabilities. In one implementation, the processor can be a circuit with instruction read and execute capabilities, such as a central processing unit (CPU), microprocessor, graphics processing unit (GPU) (which can be understood as a type of microprocessor), or digital signal processor (DSP). In another implementation, the processor can implement certain functions through the logical relationships of hardware circuits. These logical relationships are fixed or reconfigurable. For example, the processor may be a hardware circuit implemented using an application-specific integrated circuit (ASIC) or a programmable logic device (PLD), such as a field-programmable gate array (FPGA). In reconfigurable hardware circuits, the process of the processor loading a configuration document and configuring the hardware circuit can be understood as the process of the processor loading instructions to implement some or all of the functions of the aforementioned units. Furthermore, the processor can also be a hardware circuit designed for artificial intelligence, which can be understood as an ASIC, such as a neural network processing unit (NPU), tensor processing unit (TPU), deep learning processing unit (DPU), etc. In addition, the computing platform 150 may also include a memory for storing instructions. Some or all of the processors 151 to 15n can call the instructions in the memory to implement the corresponding functions.

[0055] Vehicle 100 may include an intelligent driving system, which may include an advanced driving assistance system (ADAS) and an autonomous driving system (ADS). The intelligent driving system utilizes various sensors on the intelligent driving device (including but not limited to: lidar, millimeter-wave radar, camera devices, ultrasonic sensors, global positioning system, inertial measurement unit) to acquire information from the surroundings of the intelligent driving device, and analyzes and processes the acquired information to achieve functions such as obstacle perception, target recognition, intelligent driving device localization, path planning, driver monitoring / alert, etc., thereby improving the safety, automation and comfort of driving the intelligent driving device.

[0056] Logically, an intelligent driving system generally includes three main functional modules: a perception module, a decision-making module, and an execution module. The perception module uses sensors to sense the vehicle's surroundings and inputs real-time data to the decision-making processing center. The perception module mainly includes onboard cameras, ultrasonic radar, millimeter-wave radar, and lidar. The decision-making module uses computing devices and algorithms to make corresponding decisions based on the information obtained from the perception module. The execution module receives the decision signals from the decision-making module and takes corresponding actions, such as driving, changing lanes, steering, braking, and issuing warnings.

[0057] At different levels of autonomous driving (or intelligent driving levels, ranging from L0 to L5, totaling six levels), intelligent driving systems can achieve different levels of automated driving assistance based on artificial intelligence algorithms and information acquired by multiple sensors. These levels of autonomous driving are based on the classification standards of the Society of Automotive Engineers (SAE). Specifically, L0 is no automation; L1 is driver assistance; L2 is partial automation; L3 is conditional automation; L4 is high automation; and L5 is full automation. At levels L1 to L3, the task of monitoring road conditions and reacting is jointly completed by the driver and the system, requiring the driver to take over dynamic driving tasks. Levels L4 and L5 allow the driver to completely transform into a passenger. Currently, the functions that intelligent driving systems can achieve mainly include, but are not limited to: adaptive cruise control, automatic emergency braking, automatic parking, blind spot monitoring, forward cross-traffic alert / braking, rear cross-traffic alert / braking, forward collision warning, lane departure warning, lane keeping assist, rear collision warning, traffic sign recognition, traffic jam assist, and highway assist. It should be understood that the above-mentioned functions can have specific modes at different levels of autonomous driving (L0-L5). The higher the level of autonomous driving, the more intelligent the corresponding mode.

[0058] In this embodiment, server 200 can generate traffic light information based on traffic flow data, perception information associated with the traffic flow data, and map information. This traffic light information indicates the relationship between traffic lights and lanes at each intersection in at least one intersection. Server 200 can send the traffic light information to vehicle 100. The computing platform 150 in vehicle 100 can plan the trajectory of vehicle 100 through the intersection based on the status information of traffic lights at the intersection collected by perception system 120, the lane where vehicle 100 is located, and the traffic light information, and control vehicle 100 to pass through the intersection according to the planned trajectory. In some implementations, vehicle 100 can also generate traffic light information based on traffic flow data, perception information associated with the traffic flow data, and map information; further, vehicle 100 plans the trajectory to pass through the intersection based on the traffic light information and controls the vehicle to travel along the trajectory to pass through the intersection.

[0059] Figure 2 A schematic block diagram of a device for generating traffic light information according to an embodiment of this application is shown. Figure 2 The device shown is installed in server 200. For example... Figure 2 As shown, the device comprises a traffic flow information acquisition module 210, a map information acquisition module 220, a road-level relationship determination module 230, and a traffic light information generation module 240. The functions of each module are described below.

[0060] (a) The traffic flow information acquisition module 210 is used to receive traffic flow information from each of the multiple vehicles. The traffic flow information includes at least one traffic flow data and perception information associated with each traffic flow data in the at least one traffic flow data. The perception information includes an image of the intersection through which the traffic flow passes. The image includes traffic lights at the intersection. Based on the perception information, the number of traffic lights at the intersection and the status of the traffic lights (such as what color the light is currently lit) can be determined.

[0061] (II) The map information acquisition module 220 is used to acquire map information, which may include a standard map, a vectorized map, or information that can be obtained as map vector elements through normalization or other methods. The map information indicates the location of road intersections and the topological relationships between roads. It may also indicate lane information (such as the number of lanes and lane width). For example, the vectorized map may be generated by the server 200 based on traffic flow data. For instance, road vectors are obtained by segmenting and clustering the traffic flow data. Further, for multiple roads intersecting at the same intersection, the vector points connecting each road to the intersection are determined based on the traffic flow data and road vectors. The vector points corresponding to the multiple roads constitute the intersection vector. The road width is determined based on the traffic flow data. The intersections of multiple traffic flows with the perpendicular lines of the roads are clustered, and the number of lanes is determined based on the clustering results. Then, the lane vectors are determined based on the road width and the number of lanes. It can be understood that the lane vectors, road vectors, and intersection vectors constitute the vectorized map. Among them, the road vector indicates the location and direction of a road segment, the intersection vector indicates the location and boundary of an intersection, the lane vector indicates the roadway for various vehicles to travel together within the same road width, or the lane vector can also indicate the position of each lane in a certain road segment.

[0062] The traffic flow information acquisition module 210 and the map information acquisition module 220 send the traffic flow information and map information to the road-level relationship determination module 230, respectively.

[0063] (III) The road-level relationship determination module 230 is used to establish the relationship between traffic flow data and roads based on map information and traffic flow information, and to determine the relationship between roads and one or more traffic lights based on map information and perception information.

[0064] (iv) The traffic light information generation module 240 is used to generate traffic light information based on the lane direction, traffic flow direction and the status of traffic lights associated with the road. The traffic light information indicates the relationship between the lane and the traffic light.

[0065] It should be understood that the above module is only an example, and in actual applications, it may be added or removed as needed. For example, Figure 2 In the device shown, the road-level relationship determination module 230 and the traffic light information generation module 240 can be combined into one module.

[0066] The systems and apparatus involved in the embodiments of this application have been described above. The methods provided by this application will be described in detail below with reference to the accompanying drawings.

[0067] Figure 3A schematic flowchart of a method for generating traffic light information provided in an embodiment of this application is shown. The method 300 can be executed by a server 200 and includes steps S301 to S305.

[0068] S301, Obtain map information, which indicates the location of one or more intersections.

[0069] For example, the map information can be a vectorized map as described in the foregoing embodiments, or it can be a standard map.

[0070] Understandably, map information can also indicate the topological relationships between two or more roads.

[0071] S302, Obtain traffic flow information, which includes at least one traffic flow data and sensing information associated with each traffic flow data in the at least one traffic flow data, the sensing information indicating the number of traffic lights and the status of traffic lights at the intersections through which the traffic flow passes.

[0072] It is understandable that each traffic flow consists of several traffic flow points, each corresponding to traffic flow point data in the traffic flow data. That is, each traffic flow point corresponds to a coordinate and the time when a vehicle arrives at that point. The coordinates of the traffic flow points and the coordinates used in the map information can be associated with the same coordinate system. For example, the coordinates of the traffic flow points and the coordinates used in the map information are located in the same coordinate system, or the coordinate system associated with the coordinates of the traffic flow points and the coordinate system associated with the coordinates used in the map information can be converted to each other.

[0073] For example, traffic light status can indicate traffic light color.

[0074] S303 determines the relationship between roads and traffic lights based on traffic flow information and map information.

[0075] For example, each traffic flow data point in at least one data set is matched with map information to determine the location of the intersection traversed by each traffic flow data point. Specifically, the coordinates of traffic flow points in the traffic flow data can be matched with the coordinates of a vectorized map or a standard map to determine the location of the intersection traversed by the traffic flow. Furthermore, the coordinates of traffic flow points in the traffic flow data can also determine the correlation between the traffic flow and the lanes in the road, indicating which lane the traffic flow data represents.

[0076] Furthermore, based on the perceived information related to traffic flow and the direction of traffic flow, the traffic lights associated with the intersections through which the traffic flow passes are determined. Generally, an intersection includes at least one traffic light directing vehicles in one direction. For more complex scenarios, an intersection may include at least two traffic lights directing vehicles in two directions. For example, if a road includes at least one lane traveling from south to north and at least one lane traveling from north to south, then at an intersection on that road, there may be traffic lights directing vehicles traveling from south to north, or traffic lights directing vehicles traveling from north to south. In addition, an intersection may be a merging intersection (such as the merging of a main road and a side road), therefore, there may be traffic lights at that intersection corresponding to two or more roads, each directing vehicles in one direction. For example, these two or more roads may include a main road and a side road with the same direction of travel. Therefore, based on the perception information associated with the traffic flow and the direction of the traffic flow, at least one traffic light associated with the intersection that indicates a road direction can be determined. Different traffic lights in the at least one traffic light can be used to direct vehicles in different roads. More specifically, each traffic light in the at least one traffic light can be used to direct vehicles in one or more lanes of the road.

[0077] It's important to clarify that traffic lights at an intersection that indicate a road direction are different from those that indicate a travel direction. Road direction refers to the direction the road runs, such as from south to north or from east to west. When a vehicle is traveling on a road with a specific road direction, its travel direction at the intersection can be the same as or different from that road direction. For example, if a road runs from south to north and intersects with an east-west road at an intersection, the travel direction of vehicles at that intersection can include any of the following: north, east, west, or south. Vehicles traveling in different directions can be directed by different traffic lights associated with the south-north road. In other words, traffic lights at an intersection indicating a road direction can include multiple traffic lights indicating different travel directions.

[0078] More specifically, such as Figure 4As shown, a north-south road and an east-west road intersect at intersection a. Intersection a can include multiple traffic lights indicating south-to-north travel, such as traffic lights a, b, c, and d. Traffic lights a through d can each direct vehicles traveling in different directions. For example, traffic light a directs vehicles turning left, while traffic lights b, c, and d direct vehicles going straight. In other words, the traffic lights associated with intersection a indicating south-to-north travel include traffic lights a through d; the traffic lights associated with intersection a indicating straight travel include traffic lights b through d; and the traffic lights associated with intersection a indicating left turns include traffic light a.

[0079] S304 determines the relationship between lanes and traffic lights based on traffic light status, traffic flow direction, and lane guidance.

[0080] For example, lane guidance can be determined based on map information, or it can be determined based on an image containing lane guidance lines in the perceived information. It is understood that lane guidance indicates the direction a vehicle traveling in that lane should travel when entering the intersection segment; for example, if the lane guidance is left turn, the vehicle should turn left when entering the intersection segment; if the lane guidance is both left turn and straight ahead, the vehicle can either turn left or go straight when entering the intersection segment. The following describes the methods for determining the relationship between lanes and traffic lights in different scenarios:

[0081] Scenario 1: Traffic flow information includes perceived information, and the traffic lights are directional traffic lights. When the traffic lights are directional traffic lights, the association relationship 1 between lanes and traffic lights can be determined based on the direction indicated by the traffic lights and lane guidance. This association relationship 1 indicates the traffic lights associated with each type of lane in different directions. For example, when the traffic light indicates a left turn (e.g., the traffic light includes a left-pointing arrow), the lane guidance includes left-turn lanes associated with that traffic light; when the traffic light indicates a straight-ahead direction (e.g., the traffic light includes an upward-pointing arrow), the lane guidance includes straight-ahead lanes associated with that traffic light. A more detailed association relationship between the direction indicated by the traffic lights and lanes can be found in Table 1 below.

[0082] Table 1

[0083] The direction indicated by the traffic lights Lane guidance corresponding to the associated lane Turn left Turn left; turn left and go straight; turn left and make a U-turn; turn left, make a U-turn and go straight; turn left and turn right straight Go straight; go straight and turn left; go straight and turn right; turn left, make a U-turn, and go straight; go straight and make a U-turn Turn right Turn right; go straight and turn right; turn left and turn right.

[0084] In some scenarios, a direction of travel may correspond to multiple traffic lights. For example, vehicles in different straight lanes need to follow the instructions of different traffic lights. These traffic lights indicate different time periods when passage is permitted and prohibited. Therefore, it is necessary to determine which lane(s) each traffic light indicates.

[0085] For example, after determining association 1, association 2 between lanes and traffic lights can be determined based on traffic flow data and perception information. Association 2 indicates the traffic lights associated with different lanes of the same direction. For instance, the time period when vehicles travel into the intersection can be determined based on traffic flow data, and then the color of each traffic light indicated by the perception information during that time period can be determined. Based on the color of each traffic light, the association between lanes and traffic lights can be determined.

[0086] For example, based on association 1, it is determined that both traffic light 1 and traffic light 2 are used to direct vehicles in straight-ahead lanes, where straight-ahead lanes include lane 1, lane 2, and lane 3. For example, based on traffic flow data associated with lane 1, the time period when a vehicle enters the intersection is determined, and then the color of the traffic light indicated by the associated perception information during that time period is determined. If traffic light 1 is green and traffic light 2 is red during that time period, it can be determined that traffic light 1 is used to direct vehicles in lane 1, and traffic light 2 is not used to direct vehicles in lane 1. Similarly, based on traffic flow data associated with lane 2, the time period when a vehicle enters the intersection is determined, and then the color of the traffic light indicated by the associated perception information during that time period is determined. If traffic light 1 is green and traffic light 2 is red during that time period, it can be determined that traffic light 1 is used to direct vehicles in lane 2, and traffic light 2 is not used to direct vehicles in lane 2. Based on the traffic flow data associated with lane 3, the time period when a vehicle travels into the intersection is determined, and then the color of the traffic light indicated by the associated perception information during that time period is determined. If traffic light 2 is green and traffic light 1 is red during that time period, it can be determined that traffic light 2 is used to direct vehicles in lane 3, and traffic light 1 is not used to direct vehicles in lane 3.

[0087] Scenario 2: Traffic flow information does not include sensor information, and the traffic lights are directional traffic lights. When the traffic lights are directional traffic lights and the traffic flow information does not include sensor information, the server can obtain traffic light status information at each intersection from roadside equipment, or the server can obtain timestamped sensor information from vehicles. This timestamped sensor information indicates the traffic light status and the time period for which the sensor information was obtained. In this case, based on association 1, according to the time information associated with the traffic flow points and the traffic light status during the relevant time period, association 2 between lanes and traffic lights can be determined.

[0088] Taking, as an example, traffic light 1 and traffic light 2 are both used to direct vehicles in lanes that can proceed straight, based on association 1, and these lanes include lane 1, lane 2, and lane 3:

[0089] In one example, during the period when traffic light 1 is red, some traffic flow data corresponding to lane 1 has no traffic flow point information within the intersection. However, during the period when traffic light 2 is red and traffic light 1 is green, some traffic flow data corresponding to lane 1 has traffic flow point information within the intersection. That is, when traffic light 1 is red, vehicles from lane 1 do not travel within the intersection (or cannot travel within the intersection), and when traffic light 2 is red, vehicles from lane 1 have a travel trajectory within the intersection (or can travel within the intersection). In this case, it can be determined that traffic light 1 is used to direct vehicles in lane 1, and traffic light 2 is not used to direct vehicles in lane 1.

[0090] In another example, during the period when traffic light 1 is red, the traffic flow data corresponding to lane 1 indicates that the speed of vehicles is less than or equal to the speed threshold 1, and the average acceleration of the traffic flow is less than zero; and during the period when traffic light 2 is red and traffic light 1 is green, the traffic flow data corresponding to lane 1 indicates that the speed of vehicles is greater than the speed threshold 1. That is, when traffic light 1 is red, vehicles in lane 1 are waiting for the red light, and when traffic light 2 is red, vehicles in lane 1 do not need to wait for the red light. In this case, it can be determined that traffic light 1 is used to direct vehicles in lane 1, and traffic light 2 is not used to direct vehicles in lane 1.

[0091] In another example, if traffic light 1 is red while a vehicle in lane 1 is traveling from position 1 to position 2, causing the time required for the vehicle to travel from position 1 to position 2 to be greater than or equal to a time threshold 1, and if traffic light 2 is red while the time required for the vehicle to travel from position 1 to position 2 is still less than the time threshold 1, then it can be determined that traffic light 1 is used to direct vehicles in lane 1, and traffic light 2 is not used to direct vehicles in lane 1. Here, position 1 can be the location entering the intersection through lane 1, and position 2 can be the location exiting the intersection through lane 1. The distance between position 1 and position 2 can be less than or equal to the length 1 of the intersection in the direction parallel to lane 1. For example, the time required for a vehicle in lane 1 to travel from position 1 to position 2 can be determined based on traffic flow data. Specifically, the time required for a vehicle to travel from position 1 to position 2 is determined based on the time difference between the earliest time corresponding to the nearest neighbor traffic flow point 1 to position 1 in the traffic flow data and the earliest time corresponding to the nearest neighbor traffic flow point 2 to position 2 in the traffic flow data.

[0092] For example, the traffic flow data associated with lane 1 can be determined by the method described in S303. In the three examples, taking the time period when traffic light 1 is red, or the time period when traffic light 1 is red from time t0 to time t1, the traffic flow data corresponding to lane 1 can be the data generated by vehicles traveling in lane 1 and passing through the intersection from time t0' to time t1'. Time t0' is the time before time t0 and has a time interval 1 between it and time t0, and time t1' is the time after time t1 and has a time interval 2 between it and time t1. Time interval 1 and time interval 2 can be 1 minute, 2 minutes, or other durations.

[0093] Referring to the method described above for determining the relationship between lane 1 and traffic light 1, the relationships between lane 2, lane 3 and traffic light can be determined respectively.

[0094] Furthermore, the speed threshold 1 can be determined based on the road speed limit, for example, 80% of the road speed limit; or, the speed threshold 1 can be the average speed of vehicles on the same road segment in lane 1 within a nearby time period; or, the speed threshold 1 can be other values. The duration threshold 1 can be determined based on the length 1 and the red light duration of traffic light 1; the larger the length 1, the larger the duration threshold 1. In some scenarios, the duration threshold 1 can also be related to the speed limit of the road where lane 1 is located; the smaller the speed limit of the road where lane 1 is located, the larger the duration threshold 1. It should be noted that the above explanation uses lane 1 as a straight-ahead lane as an example. In actual implementation, if lane 1 is a left-turn lane, the duration threshold 1 can be related to the average path length between the entry point and the exit point of the intersection.

[0095] Scenario 3: The traffic light is not a directional traffic light. That is, the traffic light only directs traffic through color changes and no longer has arrows. In this case, the relationship 3 between the lane and the traffic light can be determined based on the time information associated with the traffic flow point, the direction of traffic flow, and the status of the traffic light. This relationship 3 indicates the traffic light associated with each lane.

[0096] For example, the traffic lights associated with road direction 1 at the intersection include traffic light A, traffic light B, and traffic light C. Traffic light A directs left-turning vehicles, while traffic lights B and C direct straight-going vehicles. The left-turn lane includes lane a, and the straight-going lanes include lane a, lane b, and lane c. For example, the lane guidance supported by a lane can be determined based on the traffic flow direction indicated by the traffic flow data associated with the lane. Further, the association between the traffic lights and the lanes is determined based on the traffic light status and the traffic flow data corresponding to the lanes.

[0097] For example, taking the traffic flow direction indicated by lane-associated traffic flow data as an example, determine that lane a supports left turns and going straight, and lanes b and c support going straight:

[0098] In one example, during the period when traffic light a is red, there is no traffic flow point information for some of the traffic flow data corresponding to lane a within the intersection. However, during the period when traffic lights B and C are red and traffic light A is green, there is traffic flow point information for some of the traffic flow data corresponding to lane a within the intersection. That is, when traffic light A is red, vehicles in lane a do not travel within the intersection (or cannot travel within the intersection). When traffic lights B and C are red, but traffic light A is green, vehicles traveling in lane a have a travel trajectory within the intersection (or can travel within the intersection). In this case, it can be determined that traffic light A is used to direct vehicles in lane a, while traffic lights B and C are not used to direct vehicles in lane a. Furthermore, during the period when traffic light B is red, the traffic flow data corresponding to lane b has no traffic flow point information within the intersection. However, during the period when traffic light C is red and traffic light B is green, the traffic flow data corresponding to lane b has traffic flow point information within the intersection. That is, when traffic light B is red, vehicles going straight from lane b do not travel within the intersection (or cannot travel within the intersection), and when traffic light C is red, vehicles going straight from lane b have a travel trajectory within the intersection (or can travel within the intersection). In this case, it can be determined that traffic light B is used to direct vehicles in lane b, and traffic light C is not used to direct vehicles in lane b.

[0099] In another example, the relationship between each lane and the traffic light can be determined based on the speed and / or acceleration of traffic flow in each lane during the red light periods. For instance, during the red light period of traffic light A, if the traffic flow data for lane a indicates that the vehicle speed is less than or equal to a speed threshold of 2 and the average acceleration of the traffic flow for lane a is less than zero, and during the red light periods of traffic lights B and C and the green light period of traffic light A, the traffic flow data for lane a indicates that the vehicle speed is greater than a speed threshold of 2, meaning that when traffic light A is red, vehicles in lane a are waiting for the red light, and when traffic lights B and C are red, vehicles going straight and turning left in lane a do not need to wait for the red light, then it can be determined that traffic light A is used to direct vehicles in lane a, while traffic lights B and C are not used to direct vehicles in lane a. Furthermore, during the period when traffic light B is red, the traffic flow data for lane b indicates that the speed of vehicles is greater than speed threshold 2. And during the period when traffic light C is red and traffic light B is green, the traffic flow data for lane b indicates that the speed of vehicles is less than or equal to speed threshold 2, and the average acceleration of the traffic flow for lane b is less than zero. That is, when traffic light B is red, vehicles going straight in lane b are waiting for the red light; when traffic light C is red, vehicles going straight in lane b do not need to wait for the red light. In this case, it can be determined that traffic light B is used to direct vehicles in lane c, and traffic light C is not used to direct vehicles in lane b. For example, speed threshold 2 can be determined based on road speed limits, and speed threshold 1 can also be determined based on the average speed of vehicles on the same road segment within adjacent time periods.

[0100] Following the methods described above for determining the relationships between lanes a and b and traffic lights A and B respectively, the relationship between traffic light C and lane c can be determined. The methods for filtering traffic flow data used in the examples of this implementation can be found in the description of the previous implementation and will not be repeated here.

[0101] To facilitate understanding of the aforementioned methods, the following will combine... Figures 4 to 6 The scenario shown illustrates a more detailed implementation of the aforementioned method.

[0102] like Figure 4 As shown, sub-roads 1 to 6 intersect at intersection a. Sub-road 1 includes lanes 5 and 6, sub-road 2 includes lanes 1 to 4, sub-road 3 includes lane 5, and sub-road 4 includes lanes 1 to 4. Sub-roads 1 and 3 are auxiliary roads, while sub-roads 2 and 4 are main roads. Furthermore, the traffic lights at intersection a, indicating southbound traffic, include traffic lights a to d. Traffic light a directs vehicles in lanes 1 and 2, traffic light b directs vehicles in lane 3, traffic light c directs vehicles in lane 4, and traffic light d directs vehicles in lanes 5 and 6. Figure 4 Solid line curves (such as curves 11 and 12), dashed line curves (such as curves 21 to 25), and dashed-dot lines (such as curves 31 to 33) represent the vehicle travel paths indicated by different traffic flow data.

[0103] When traffic lights do not indicate direction (e.g., traffic lights do not include arrows), the relationship between traffic lights and lanes can be determined based on the traffic flow direction indicated by the traffic flow data and the color of each traffic light during the time period when vehicles enter intersection a. For example, curves 11, 12, and 22 indicate that traffic light a is green and other traffic lights are red during a certain time period when vehicles enter intersection a, thus traffic light a is associated with lanes ① and ②. Similarly, curves 25, 31, and 32 indicate that traffic light d is green and other traffic lights are red during a certain time period when vehicles enter intersection a, thus traffic light d is associated with lanes ⑤ and ⑥. Furthermore, curves 21 and 23 indicate that traffic light b is green and other traffic lights are red during a certain time period when vehicles enter intersection a, thus traffic light b is associated with lane ③. For example, curves 24 and 33 indicate that during a certain period of time when a vehicle enters intersection a, traffic light c is green and other traffic lights are red. Therefore, it can be determined that traffic light c is associated with lane ④.

[0104] It is understood that the above methods for determining the relationship between traffic lights and lanes are merely illustrative examples. In actual implementation, the method described in Case 3 above can also be used to determine the relationship between traffic lights and lanes.

[0105] In some implementations, the traffic flow data used in determining the relationship between traffic lights and lanes in the aforementioned embodiments can be filtered traffic flow data that conforms to traffic rules or preset requirements. For example, Figure 5As shown, A1 and A2 illustrate the lanes that vehicles traveling from lane ② towards intersection a can enter when exiting the intersection; B and C illustrate the lanes that vehicles traveling from lane ③ and lane ⑤ towards intersection a can enter when exiting the intersection. The relationship between the entry and exit lanes shown in A1, A2, B, and C conforms to traffic rules and human driving habits. Therefore, for all traffic flow data corresponding to lanes ②, ③, and ⑤, traffic flow data that does not meet the aforementioned relationship between entry and exit lanes will be removed. For example, traffic flow data traveling from lanes ②, ③, and ⑤ towards sub-road 5 will be removed, and the remaining traffic flow data will be used to determine the relationship between traffic lights and lanes. Furthermore, the preset requirement can be that traffic flow data includes the portion within the road surface, the portion entering the intersection, and the portion exiting the intersection. If the traffic flow data lacks one or more of the portions within the road surface, the portion entering the intersection, and the portion exiting the intersection, it is determined that the traffic flow data does not meet the preset requirement and will be removed.

[0106] In some implementations, if the traffic light is a directional traffic light, the relationship between the lane and the traffic light can be determined based on the direction indicated by the traffic light and the lane guidance.1 Figure 6 As shown, traffic light a is a left-turn indicator, and traffic lights b through d are all straight-ahead indicators. Lanes ① and ② are both left-turn lanes. Therefore, the following relationship can be determined: Traffic light a is associated with lanes ① and ②, and traffic lights b through d are associated with lanes ③ through ⑥. Further, based on traffic flow data and perception information, a more specific relationship between traffic lights b through d and lanes ③ through ⑥ can be determined. For the specific implementation method, please refer to the description in Case 1 above, which will not be repeated here.

[0107] Figure 7 This illustration shows another schematic flowchart of the method for generating traffic light information provided in an embodiment of this application. This method 700 can be applied to... Figure 1 In the server 200 shown, or this method can be used by Figure 2 The system shown executes this. In some implementations, this method can also be... Figure 1 The vehicle 100 shown performs this action. More specifically, the method includes:

[0108] S710, acquire traffic flow data set, which includes data on the travel paths of multiple vehicles in a first road, the first road being connected to at least one road via a first intersection, the first road including multiple lanes, and the traffic flow data set including a first set of data associated with the first lane among the multiple lanes.

[0109] For example, the first set of data associated with the first lane can be understood as: multiple traffic flow points in each traffic flow data in the first set of data are located in the first lane; or, the vehicle travel path indicated by each traffic flow data is traveling from the first lane to the first intersection.

[0110] S720 acquires perception information, which indicates the status of multiple traffic lights at the first intersection at different times.

[0111] For example, the traffic flow data set may include at least one traffic flow data in method 300, and the perception information may include the perception information associated with each traffic flow data in the at least one traffic flow data, or the perception information may also include information collected by roadside equipment, including the status of traffic lights at the first intersection.

[0112] S730 generates traffic light information based on the first set of data and perception information. The traffic light information indicates that the first lane is associated with the first traffic light among multiple traffic lights.

[0113] The first lane is linked to the first traffic light among multiple traffic lights, including: the first traffic light is used to regulate the traffic flow of vehicles in the first lane at the first intersection. For example, the first traffic light is used to direct vehicles in the first lane.

[0114] For example, multiple traffic lights can be traffic lights indicating a direction at the first intersection. For instance, the first intersection may include intersection a in the aforementioned embodiment, and the multiple traffic lights may include traffic lights a to d in the aforementioned embodiment. Further, taking lane ① or lane ② as an example, the first traffic light is traffic light a; taking lane ③ as an example, the first traffic light is traffic light b.

[0115] In some implementations, S730 can be further refined as follows: based on the motion status of multiple vehicles in the first time period indicated by the first set of data, and the color of each traffic light in the first time period indicated by the perception information, traffic light information is generated; wherein, each of the multiple vehicles is a vehicle traveling towards the first intersection via the first lane.

[0116] For example, the motion status of multiple vehicles during a first time period can indicate one or more of the following: speed, acceleration, and distance traveled by the multiple vehicles during the first time period.

[0117] In some implementations, generating traffic light information includes: when the first traffic light is a first color during a first time period, and the remaining traffic lights (excluding the first traffic light) are all a second color during the first time period, and when the average acceleration of multiple vehicles during the first time period is less than or equal to an acceleration threshold, and / or the average speed of multiple vehicles during the first time period is less than or equal to a speed threshold, generating traffic light information indicating a correlation between the first lane and the first traffic light; wherein the first color indicates permission to pass, and the second color indicates prohibition to pass.

[0118] For example, the first color can be green as in the foregoing embodiments, and the second color can be red as in the foregoing embodiments. The velocity threshold and velocity threshold 1 or velocity threshold 2 in the foregoing embodiments can be the same threshold, and the acceleration threshold can be zero, or it can be any other value less than zero.

[0119] For example, it can also be determined whether the first traffic light is used to direct vehicles in the first lane based on the average displacement of multiple vehicles within the first time period; or, it can also be determined whether the first traffic light is used to direct vehicles in the first lane based on whether there are trajectory points in the first intersection within the first time period based on the first set of data. For a more specific determination of the relationship between the first traffic light and the first lane, please refer to the description in the aforementioned method 300, which will not be repeated here.

[0120] In some implementations, the permissible driving direction indicated by each of the multiple traffic lights is the same as the permissible driving direction of the first lane at the first intersection; obtaining perception information includes: obtaining first perception information associated with the first lane based on the permissible driving direction of the first lane at the first intersection, the perception information including the first perception information.

[0121] For example, taking the direction of travel for the first lane at the first intersection as straight-ahead, the first perception information may include information indicating the status of one or more traffic lights used to direct straight-ahead travel. For instance, the first lane is... Figure 6 If lane ③ or lane ④ is shown, the first sensing information may include information indicating the status of traffic lights b to d.

[0122] In some implementations, multiple traffic lights also include a second traffic light, and multiple lanes also include a second lane; the method further includes: when the permissible direction of travel indicated by the second traffic light is the same as the permissible direction of travel of the second lane at the first intersection, and the permissible directions of travel indicated by the remaining traffic lights other than the second traffic light among the multiple traffic lights are all different from the permissible direction of travel of the second lane at the first intersection, generating traffic light information indicating that the second lane and the second traffic light are associated.

[0123] For example, the second traffic light is a directional traffic light, such as... Figure 6 Any one of the traffic lights a to d shown. The specific implementation of the relationship between the traffic lights and lanes, based on the permissible driving direction indicated by the traffic lights and the permissible driving direction indicated by the lanes, can be referred to the descriptions in Case 1 and Case 2 of Method 300, and will not be repeated here.

[0124] In some implementations, the method further includes: acquiring map information indicating the location of at least one intersection, the at least one intersection including a first intersection; acquiring perception information, including: determining the location of the first intersection based on the map information and traffic flow data; and acquiring perception information based on the location of the first intersection.

[0125] For example, the map information may include the map information in method 300. The specific implementation of determining the location of the first intersection based on the map information and the traffic flow data group can be found in the description in S301, and will not be repeated here.

[0126] The method for generating traffic light information provided in this application does not rely on high-precision maps and has low requirements for the vehicle's perception capabilities. When there are multiple traffic lights of the same type at an intersection that control different lanes, it can provide vehicles with accurate information on the relationship between lanes and traffic lights. This can reduce the probability of vehicles following the wrong traffic lights and stopping at intersections, thus helping to improve the efficiency of vehicle traffic at intersections and vehicle driving safety.

[0127] In the various embodiments of this application, unless otherwise specified or in case of logical conflict, the terminology and / or descriptions between the various embodiments are consistent and can be referenced by each other. Technical features in different embodiments can be combined to form new embodiments according to their inherent logical relationships.

[0128] The above text combines Figures 1 to 7 The methods provided in the embodiments of this application are described in detail below. Figure 8 and Figure 9 The apparatus provided in the embodiments of this application is described in detail. It should be understood that the description of the apparatus embodiments corresponds to the description of the method embodiments. Therefore, for content not described in detail, please refer to the method embodiments above. For the sake of brevity, it will not be repeated here.

[0129] Figure 8A schematic block diagram of a device 2000 for generating traffic light information according to an embodiment of this application is shown. The device 2000 may include units for executing the methods described in the foregoing embodiments. Furthermore, each unit in the device 2000 implements a corresponding process of the above method embodiments. The device 2000 includes an acquisition unit 2010, which can be used to implement corresponding data acquisition or transmission / reception functions. The device 2000 also includes a processing unit 2020, which can be used to implement corresponding processing functions.

[0130] Optionally, the device 2000 further includes a storage unit, which can be used to store instructions and / or data. The processing unit 2020 can read the instructions and / or data in the storage unit so that the device can perform the relevant actions in the aforementioned method embodiments.

[0131] It should be understood that the specific process of each unit performing the above-mentioned corresponding steps has been described in detail in the above method embodiments, and will not be repeated here for the sake of brevity.

[0132] It should also be understood that the device 2000 described herein is embodied in the form of a functional unit. The terms “module” or “unit” may refer to application-specific ASICs, electronic circuits, processors (e.g., shared processors, proprietary processors, or group processors) and memory for executing one or more software or firmware programs, integrated logic circuits, and / or other suitable components that support the described functions.

[0133] The apparatus in this embodiment has the function of implementing the corresponding steps in the aforementioned method. The function can be implemented by hardware or by hardware executing corresponding software. The hardware or software includes one or more modules corresponding to the above functions; for example, the acquisition unit 2010 can be replaced by a transceiver, and other units, such as the processing unit, can be replaced by a processor, used to execute the relevant processing operations in each method embodiment.

[0134] For example, the acquisition unit 2010 and the processing unit 2020 can be set in Figure 1 In server 200 shown, or it can also be set in Figure 2 In the illustrated system, more specifically, the acquisition unit 2010 and processing unit 2020 can be located within the lane-level relationship determination module 240. Exemplarily, the operations performed by the acquisition unit 2010 and processing unit 2020 can be executed by a single processor, or they can be executed by different processors. In specific implementations, the one or more processors can be located within the lane-level relationship determination module 240. Figure 1 The processor in the server 200 shown; or, the device 2000 described above can be a chip disposed in the server 200.

[0135] In the specific implementation process, the units in the above device can be fully or partially integrated together, or they can be implemented independently. In one implementation, these units are integrated together and implemented in the form of a system-on-a-chip (SoC).

[0136] Figure 9 This is another schematic block diagram of the device for generating traffic light information provided in the embodiments of this application. Figure 9 The illustrated device 2100 may include a processor 2110, a transceiver 2120, and a memory 2130. The processor 2110, transceiver 2120, and memory 2130 are connected via internal interconnects. The memory 2130 stores instructions, and the processor 2110 executes the instructions stored in the memory 2130 to implement the methods described in the above embodiments. Optionally, the memory 2130 may be coupled to the processor 2110 via an interface or integrated with the processor 2110.

[0137] It should be noted that the transceiver 2120 mentioned above may include, but is not limited to, transceiver devices such as input / output interfaces, to realize communication between device 2100 and other devices or communication networks.

[0138] Memory 2130 can be volatile memory and / or non-volatile memory. Non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. Volatile memory can be random access memory (RAM). For example, RAM can be used as an external cache. By way of example and not limitation, RAM includes various forms such as: static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous linked dynamic random access memory (SLDRAM), and direct rambus RAM (DR RAM).

[0139] Transceiver 2120 uses transceiver devices, such as but not limited to transceivers, to enable communication between device 2100 and other devices or communication networks to receive / send data / information for implementing the methods in the above embodiments.

[0140] This application embodiment also provides a server, the vehicle including the device 2000 or device 2100 in the above embodiments.

[0141] This application also provides a computer program product, which includes computer program code. When the computer program code is run on a computer, it causes the computer to implement the methods described in the above embodiments of this application.

[0142] This application also provides a computer-readable storage medium storing computer instructions that, when executed on a computer, cause the computer to implement the methods described in the above embodiments of this application.

[0143] This application also provides a chip, including circuitry, for performing the methods described in the above embodiments of this application.

[0144] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0145] In the description of the embodiments of this application, unless otherwise stated, " / " means "or", for example, A / B can mean A or B; "and / or" in this document describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. In this application, "at least one" means one or more, and "more" means two or more. "At least one of the following" or similar expressions refer to any combination of these items, including any combination of single or multiple items. For example, at least one of a, b, or c can represent: a, b, c, ab, ac, bc, or abc, where a, b, and c can be single or multiple.

[0146] The use of prefixes such as "first" and "second" in this application embodiment is solely for distinguishing different descriptive objects and does not limit the position, order, priority, quantity, or content of the described objects. The use of ordinal numbers and other prefixes to distinguish descriptive objects in this application embodiment does not constitute a limitation on the described objects. The description of the described objects is found in the claims or the context of the embodiments, and the use of such prefixes should not constitute unnecessary restrictions.

[0147] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0148] In the various embodiments of this application, unless otherwise specified or in case of logical conflict, the terminology and / or descriptions between the various embodiments are consistent and can be referenced by each other. Technical features in different embodiments can be combined to form new embodiments according to their inherent logical relationships.

[0149] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0150] In addition, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0151] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for generating traffic light information, characterized in that, include: Acquire a traffic flow data set, which includes data on the travel paths of multiple vehicles on a first road. The first road connects to at least one road via a first intersection. The first road includes multiple lanes. The traffic flow data set includes a first set of data associated with a first lane among the multiple lanes. Acquire sensing information, which indicates the status of multiple traffic lights at the first intersection at different time periods; Based on the first set of data and the perceived information, traffic light information is generated, indicating that the first lane is associated with the first traffic light among the plurality of traffic lights.

2. The method according to claim 1, characterized in that, The step of generating traffic light information based on the first set of data and the perceived information includes: Based on the motion status of multiple vehicles within a first time period indicated by the first set of data, and the color of each of the multiple traffic lights within the first time period indicated by the perception information, the traffic light information is generated. Each of the plurality of vehicles is a vehicle traveling towards the first intersection via the first lane.

3. The method according to claim 2, characterized in that, The generation of traffic light information includes: When the first traffic light is the first color during the first time period, and the remaining traffic lights other than the first traffic light are all the second color during the first time period, and when the average acceleration of the multiple vehicles during the first time period is less than or equal to an acceleration threshold, and / or the average speed of the multiple vehicles during the first time period is less than or equal to a speed threshold, traffic light information indicating the association between the first lane and the first traffic light is generated. The first color indicates permission to pass, while the second color indicates prohibition to pass.

4. The method according to any one of claims 1 to 3, characterized in that, The permissible driving direction indicated by each of the plurality of traffic lights is the same as the permissible driving direction of the first lane at the first intersection; The acquisition of perceived information includes: Based on the drivable direction of the first lane at the first intersection, first perception information associated with the first lane is obtained, and the perception information includes the first perception information.

5. The method according to any one of claims 1 to 3, characterized in that, The plurality of traffic lights further includes a second traffic light, and the plurality of lanes further includes a second lane; the method further includes: When the permissible driving direction indicated by the second traffic light is the same as the permissible driving direction of the second lane at the first intersection, and the permissible driving directions indicated by the remaining traffic lights (excluding the second traffic light) are all different from the permissible driving direction of the second lane at the first intersection, traffic light information indicating a relationship between the second lane and the second traffic light is generated.

6. The method according to any one of claims 1 to 5, characterized in that, The method further includes: Obtain map information, the map information indicating the location of at least one intersection, the at least one intersection including the first intersection; The acquisition of perceived information includes: The location of the first intersection is determined based on the map information and the traffic flow data set; The sensing information is obtained based on the location of the first intersection.

7. The method according to any one of claims 1 to 6, characterized in that, The first lane is associated with a first traffic light among the plurality of traffic lights, including: the first traffic light is used to regulate the traffic flow of vehicles in the first lane at the first intersection.

8. A device for generating traffic light information, characterized in that, include: An acquisition unit is used to acquire a traffic flow data set, the traffic flow data set including data on the travel paths of multiple vehicles in a first road, the first road being connected to at least one road via a first intersection, the first road including multiple lanes, and the traffic flow data set including a first set of data associated with a first lane among the multiple lanes; The acquisition unit is further configured to: acquire sensing information, the sensing information indicating the status of multiple traffic lights at the first intersection at different time periods; The processing unit is configured to generate traffic light information based on the first set of data and the perceived information, wherein the traffic light information indicates that the first lane is associated with the first traffic light among the plurality of traffic lights.

9. The apparatus according to claim 8, characterized in that, The processing unit is used for: Based on the motion status of multiple vehicles within a first time period indicated by the first set of data, and the color of each of the multiple traffic lights within the first time period indicated by the perception information, the traffic light information is generated. Each of the plurality of vehicles is a vehicle traveling towards the first intersection via the first lane.

10. The apparatus according to claim 9, characterized in that, The processing unit is used for: When the first traffic light is the first color during the first time period, and the remaining traffic lights other than the first traffic light are all the second color during the first time period, and when the average acceleration of the multiple vehicles during the first time period is less than or equal to an acceleration threshold, and / or the average speed of the multiple vehicles during the first time period is less than or equal to a speed threshold, traffic light information indicating the association between the first lane and the first traffic light is generated. The first color indicates permission to pass, while the second color indicates prohibition to pass.

11. The apparatus according to any one of claims 8 to 10, characterized in that, The permissible driving direction indicated by each of the plurality of traffic lights is the same as the permissible driving direction of the first lane at the first intersection; The acquisition unit is used for: Based on the drivable direction of the first lane at the first intersection, first perception information associated with the first lane is obtained, and the perception information includes the first perception information.

12. The apparatus according to any one of claims 8 to 10, characterized in that, The plurality of traffic lights also includes a second traffic light, and the plurality of lanes also includes a second lane; the processing unit is further configured to: When the permissible driving direction indicated by the second traffic light is the same as the permissible driving direction of the second lane at the first intersection, and the permissible driving directions indicated by the remaining traffic lights (excluding the second traffic light) are all different from the permissible driving direction of the second lane at the first intersection, traffic light information indicating a relationship between the second lane and the second traffic light is generated.

13. The apparatus according to any one of claims 8 to 12, characterized in that, The acquisition unit is also used for: Obtain map information, the map information indicating the location of at least one intersection, the at least one intersection including the first intersection; The location of the first intersection is determined based on the map information and the traffic flow data set; The sensing information is obtained based on the location of the first intersection.

14. The apparatus according to any one of claims 8 to 13, characterized in that, The first lane is associated with a first traffic light among the plurality of traffic lights, including: the first traffic light is used to regulate the traffic flow of vehicles in the first lane at the first intersection.

15. A device for generating traffic light information, characterized in that, include: A processor for executing a computer program stored in memory to cause the apparatus to perform the method as described in any one of claims 1 to 7.

16. A computer-readable storage medium, characterized in that, It stores instructions that, when executed by a processor, implement the method as described in any one of claims 1 to 7.

17. A chip, characterized in that, The chip includes circuitry for performing the method as described in any one of claims 1 to 7.

18. A computer program product, characterized in that, The computer program product includes: computer program code, which, when executed by a processor, implements the method as described in any one of claims 1 to 7.

19. A server, characterized in that, Includes the apparatus as described in any one of claims 8 to 15, or the computer-readable storage medium as described in claim 16, or the chip as described in claim 17, or the server loaded with the computer program product as described in claim 18.

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